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Fetcho RN, Parekh PK, Chou J, Kenwood M, Chalençon L, Estrin DJ, Johnson M, Liston C. A stress-sensitive frontostriatal circuit supporting effortful reward-seeking behavior. Neuron 2024; 112:473-487.e4. [PMID: 37963470 DOI: 10.1016/j.neuron.2023.10.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 07/06/2023] [Accepted: 10/18/2023] [Indexed: 11/16/2023]
Abstract
Effort valuation-a process for selecting actions based on the anticipated value of rewarding outcomes and expectations about the work required to obtain them-plays a fundamental role in decision-making. Effort valuation is disrupted in chronic stress states and is supported by the anterior cingulate cortex (ACC), but the circuit-level mechanisms by which the ACC regulates effort-based decision-making are unclear. Here, we show that ACC neurons projecting to the nucleus accumbens (ACC-NAc) play a critical role in effort valuation behavior in mice. Activity in ACC-NAc cells integrates both reward- and effort-related information, encoding a reward-related signal that scales with effort requirements and is necessary for supporting future effortful decisions. Chronic corticosterone exposure reduces motivation, suppresses effortful reward-seeking, and disrupts ACC-NAc signals. Together, our results delineate a stress-sensitive ACC-NAc circuit that supports effortful reward-seeking behavior by integrating reward and effort signals and reinforcing effort allocation in the service of maximizing reward.
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Affiliation(s)
- Robert N Fetcho
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Puja K Parekh
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Jolin Chou
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Margaux Kenwood
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Laura Chalençon
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - David J Estrin
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Megan Johnson
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
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2
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Dunlop K, Grosenick L, Downar J, Vila-Rodriguez F, Gunning FM, Daskalakis ZJ, Blumberger DM, Liston C. Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample. Biol Psychiatry 2024:S0006-3223(24)00055-6. [PMID: 38280408 DOI: 10.1016/j.biopsych.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/21/2023] [Accepted: 01/13/2024] [Indexed: 01/29/2024]
Abstract
BACKGROUND Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample. METHODS We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes. RESULTS The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. CONCLUSIONS Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.
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Affiliation(s)
- Katharine Dunlop
- Centre for Depression and Suicide Studies, St Michael's Hospital, Toronto, Ontario, Canada; Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Logan Grosenick
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Jonathan Downar
- Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Faith M Gunning
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - Zafiris J Daskalakis
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Daniel M Blumberger
- Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, Weill Cornell Medicine, New York, New York; Temerty Centre for Therapeutic Brain Intervention and Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, New York; Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York.
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3
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Munguba H, Gutzeit VA, Srivastava I, Kristt M, Singh A, Vijay A, Arefin A, Thukral S, Broichhagen J, Stujenske JM, Liston C, Levitz J. Projection-Targeted Photopharmacology Reveals Distinct Anxiolytic Roles for Presynaptic mGluR2 in Prefrontal- and Insula-Amygdala Synapses. bioRxiv 2024:2024.01.15.575699. [PMID: 38293136 PMCID: PMC10827048 DOI: 10.1101/2024.01.15.575699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Dissecting how membrane receptors regulate neural circuit function is critical for deciphering basic principles of neuromodulation and mechanisms of therapeutic drug action. Classical pharmacological and genetic approaches are not well-equipped to untangle the roles of specific receptor populations, especially in long-range projections which coordinate communication between brain regions. Here we use viral tracing, electrophysiological, optogenetic, and photopharmacological approaches to determine how presynaptic metabotropic glutamate receptor 2 (mGluR2) activation in the basolateral amygdala (BLA) alters anxiety-related behavior. We find that mGluR2-expressing neurons from the ventromedial prefrontal cortex (vmPFC) and posterior insular cortex (pIC) preferentially target distinct cell types and subregions of the BLA to regulate different forms of avoidant behavior. Using projection-specific photopharmacological activation, we find that mGluR2-mediated presynaptic inhibition of vmPFC-BLA, but not pIC-BLA, connections can produce long-lasting decreases in spatial avoidance. In contrast, presynaptic inhibition of pIC-BLA connections decreased social avoidance, novelty-induced hypophagia, and increased exploratory behavior without impairing working memory, establishing this projection as a novel target for the treatment of anxiety disorders. Overall, this work reveals new aspects of BLA neuromodulation with therapeutic implications while establishing a powerful approach for optical mapping of drug action via photopharmacology.
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Affiliation(s)
- Hermany Munguba
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Vanessa A. Gutzeit
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ipsit Srivastava
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Melanie Kristt
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ashna Singh
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Akshara Vijay
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Anisul Arefin
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Sonal Thukral
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Johannes Broichhagen
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), 13125 Berlin, Germany
| | - Joseph M. Stujenske
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15219, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Joshua Levitz
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
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4
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Hergenreder E, Minotti AP, Zorina Y, Oberst P, Zhao Z, Munguba H, Calder EL, Baggiolini A, Walsh RM, Liston C, Levitz J, Garippa R, Chen S, Ciceri G, Studer L. Combined small-molecule treatment accelerates maturation of human pluripotent stem cell-derived neurons. Nat Biotechnol 2024:10.1038/s41587-023-02031-z. [PMID: 38168993 DOI: 10.1038/s41587-023-02031-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 10/13/2023] [Indexed: 01/05/2024]
Abstract
The maturation of human pluripotent stem cell (hPSC)-derived neurons mimics the protracted timing of human brain development, extending over months to years for reaching adult-like function. Prolonged in vitro maturation presents a major challenge to stem cell-based applications in modeling and treating neurological disease. Therefore, we designed a high-content imaging assay based on morphological and functional readouts in hPSC-derived cortical neurons which identified multiple compounds that drive neuronal maturation including inhibitors of lysine-specific demethylase 1 and disruptor of telomerase-like 1 and activators of calcium-dependent transcription. A cocktail of four factors, GSK2879552, EPZ-5676, N-methyl-D-aspartate and Bay K 8644, collectively termed GENtoniK, triggered maturation across all parameters tested, including synaptic density, electrophysiology and transcriptomics. Maturation effects were further validated in cortical organoids, spinal motoneurons and non-neural lineages including melanocytes and pancreatic β-cells. The effects on maturation observed across a broad range of hPSC-derived cell types indicate that some of the mechanisms controlling the timing of human maturation might be shared across lineages.
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Affiliation(s)
- Emiliano Hergenreder
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Andrew P Minotti
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Yana Zorina
- Gene Editing and Screening Core Facility, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Polina Oberst
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Hermany Munguba
- Department of Biochemistry, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - Elizabeth L Calder
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Arianna Baggiolini
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Ryan M Walsh
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - Joshua Levitz
- Department of Biochemistry, Weill Cornell Medicine, New York, NY, USA
| | - Ralph Garippa
- Gene Editing and Screening Core Facility, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Gabriele Ciceri
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Lorenz Studer
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA.
- Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA.
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Buch AM, Liston C. Gene-brain-behavior mechanisms underlying autism spectrum disorder: implications for precision psychiatry. Neuropsychopharmacology 2024; 49:343-344. [PMID: 37717083 PMCID: PMC10700301 DOI: 10.1038/s41386-023-01722-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/18/2023]
Affiliation(s)
- Amanda M Buch
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69th Street, Box 240, New York, NY, 10021, USA.
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69th Street, Box 240, New York, NY, 10021, USA.
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6
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Nieves GM, Liston C. Divergent reward cue representations in the prefrontal cortex drive reward motivation in adolescence and adulthood. bioRxiv 2023:2023.11.07.565069. [PMID: 37986789 PMCID: PMC10659319 DOI: 10.1101/2023.11.07.565069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Alterations in motivation and reward-seeking are a transdiagnostic feature of numerous psychiatric disorders that commonly emerge in adolescence, including depression, obsessive- compulsive disorder, and attention deficit hyperactivity disorder. During adolescence, reward motivation is naturally heightened, compared to adulthood, but the underlying mechanisms are not well understood. The medial prefrontal cortex (mPFC) is a late developing brain region that regulates reward learning and motivation and is still maturing in adolescence. The mPFC modulates reward-motivated behaviors in adults, and has been hypothesized to be responsible for adolescents' inability to suppress reward-seeking and impulsive behaviors. Using 2-photon imaging of the mPFC and an active reward task, we demonstrate that both the adult and adolescent mPFC encode reward-predictive cues, with distinct neuronal populations encoding rewarded and unrewarded cues. In adolescence the mPFC is hyper-responsive to reward cues and recruits a larger population of neurons to encode reward predictive cues. Furthermore, in the adolescent mPFC, representations of unrewarded cues are attenuated, compared to the adult mPFC, which may tip the balance of action toward reward-seeking. Differences in neuronal responses to rewarded and unrewarded cues were observed in both GABAergic and glutamatergic neurons, with GABAergic inhibition causing disparate effects in adolescents compared to adults. Together our findings identify differences in the functional properties of mPFC microcircuits in adolescents that may underlie differences in reward-seeking behavior and the ability to adaptively suppress reward seeking.
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Affiliation(s)
- Gabriela Manzano Nieves
- Department of Psychiatry and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021
| | - Conor Liston
- Department of Psychiatry and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021
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7
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Ashar YK, Lumley MA, Perlis RH, Liston C, Gunning FM, Wager TD. Reattribution to Mind-Brain Processes and Recovery From Chronic Back Pain: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2333846. [PMID: 37768666 PMCID: PMC10539987 DOI: 10.1001/jamanetworkopen.2023.33846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/08/2023] [Indexed: 09/29/2023] Open
Abstract
Importance In primary chronic back pain (CBP), the belief that pain indicates tissue damage is both inaccurate and unhelpful. Reattributing pain to mind or brain processes may support recovery. Objectives To test whether the reattribution of pain to mind or brain processes was associated with pain relief in pain reprocessing therapy (PRT) and to validate natural language-based tools for measuring patients' symptom attributions. Design, Setting, and Participants This secondary analysis of clinical trial data analyzed natural language data from patients with primary CBP randomized to PRT, placebo injection control, or usual care control groups and treated in a US university research setting. Eligible participants were adults aged 21 to 70 years with CBP recruited from the community. Enrollment extended from 2017 to 2018, with the current analyses conducted from 2020 to 2022. Interventions PRT included cognitive, behavioral, and somatic techniques to support reattributing pain to nondangerous, reversible mind or brain causes. Subcutaneous placebo injection and usual care were hypothesized not to affect pain attributions. Main Outcomes and Measures At pretreatment and posttreatment, participants listed their top 3 perceived causes of pain in their own words (eg, football injury, bad posture, stress); pain intensity was measured as last-week average pain (0 to 10 rating, with 0 indicating no pain and 10 indicating greatest pain). The number of attributions categorized by masked coders as reflecting mind or brain processes were summed to yield mind-brain attribution scores (range, 0-3). An automated scoring algorithm was developed and benchmarked against human coder-derived scores. A data-driven natural language processing (NLP) algorithm identified the dimensional structure of pain attributions. Results We enrolled 151 adults (81 female [54%], 134 White [89%], mean [SD] age, 41.1 [15.6] years) reporting moderate severity CBP (mean [SD] intensity, 4.10 [1.26]; mean [SD] duration, 10.0 [8.9] years). At pretreatment, 41 attributions (10%) were categorized as mind- or brain-related across intervention conditions. PRT led to significant increases in mind- or brain-related attributions, with 71 posttreatment attributions (51%) in the PRT condition categorized as mind- or brain-related, as compared with 22 (8%) in control conditions (mind-brain attribution scores: PRT vs placebo, g = 1.95 [95% CI, 1.45-2.47]; PRT vs usual care, g = 2.06 [95% CI, 1.57-2.60]). Consistent with hypothesized PRT mechanisms, increases in mind-brain attribution score were associated with reductions in pain intensity at posttreatment (standardized β = -0.25; t127 = -2.06; P = .04) and mediated the effects of PRT vs control on 1-year follow-up pain intensity (β = -0.35 [95% CI, -0.07 to -0.63]; P = .05). The automated word-counting algorithm and human coder-derived scores achieved moderate and substantial agreement at pretreatment and posttreatment (Cohen κ = 0.42 and 0.68, respectively). The data-driven NLP algorithm identified a principal dimension of mind and brain vs biomechanical attributions, converging with hypothesis-driven analyses. Conclusions and Relevance In this secondary analysis of a randomized trial, PRT increased attribution of primary CBP to mind- or brain-related causes. Increased mind-brain attribution was associated with reductions in pain intensity.
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Affiliation(s)
- Yoni K. Ashar
- Division of Internal Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora
| | - Mark A. Lumley
- Department of Psychology, Wayne State University, Detroit, Michigan
| | - Roy H. Perlis
- Center for Quantitative Health, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medical College, New York, New York
| | - Faith M. Gunning
- Department of Psychiatry, Weill Cornell Medical College, New York, New York
| | - Tor D. Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire
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8
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Lynch CJ, Elbau I, Ng T, Ayaz A, Zhu S, Manfredi N, Johnson M, Wolk D, Power JD, Gordon EM, Kay K, Aloysi A, Moia S, Caballero-Gaudes C, Victoria LW, Solomonov N, Goldwaser E, Zebley B, Grosenick L, Downar J, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Williams N, Gunning FM, Liston C. Expansion of a frontostriatal salience network in individuals with depression. bioRxiv 2023:2023.08.09.551651. [PMID: 37645792 PMCID: PMC10461904 DOI: 10.1101/2023.08.09.551651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Hundreds of neuroimaging studies spanning two decades have revealed differences in brain structure and functional connectivity in depression, but with modest effect sizes, complicating efforts to derive mechanistic pathophysiologic insights or develop biomarkers. 1 Furthermore, although depression is a fundamentally episodic condition, few neuroimaging studies have taken a longitudinal approach, which is critical for understanding cause and effect and delineating mechanisms that drive mood state transitions over time. The emerging field of precision functional mapping using densely-sampled longitudinal neuroimaging data has revealed unexpected, functionally meaningful individual differences in brain network topology in healthy individuals, 2-5 but these approaches have never been applied to individuals with depression. Here, using precision functional mapping techniques and 11 datasets comprising n=187 repeatedly sampled individuals and >21,000 minutes of fMRI data, we show that the frontostriatal salience network is expanded two-fold in most individuals with depression. This effect was replicable in multiple samples, including large-scale, group-average data (N=1,231 subjects), and caused primarily by network border shifts affecting specific functional systems, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was unexpectedly stable over time, unaffected by changes in mood state, and detectable in children before the subsequent onset of depressive symptoms in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in specific frontostriatal circuits that tracked fluctuations in specific symptom domains and predicted future anhedonia symptoms before they emerged. Together, these findings identify a stable trait-like brain network topology that may confer risk for depression and mood-state dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.
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Gordon EM, Chauvin RJ, Van AN, Rajesh A, Nielsen A, Newbold DJ, Lynch CJ, Seider NA, Krimmel SR, Scheidter KM, Monk J, Miller RL, Metoki A, Montez DF, Zheng A, Elbau I, Madison T, Nishino T, Myers MJ, Kaplan S, Badke D'Andrea C, Demeter DV, Feigelis M, Ramirez JSB, Xu T, Barch DM, Smyser CD, Rogers CE, Zimmermann J, Botteron KN, Pruett JR, Willie JT, Brunner P, Shimony JS, Kay BP, Marek S, Norris SA, Gratton C, Sylvester CM, Power JD, Liston C, Greene DJ, Roland JL, Petersen SE, Raichle ME, Laumann TO, Fair DA, Dosenbach NUF. A somato-cognitive action network alternates with effector regions in motor cortex. Nature 2023; 617:351-359. [PMID: 37076628 PMCID: PMC10172144 DOI: 10.1038/s41586-023-05964-2] [Citation(s) in RCA: 74] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/16/2023] [Indexed: 04/21/2023]
Abstract
Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.
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Affiliation(s)
- Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
| | - Aishwarya Rajesh
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Ashley Nielsen
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, New York University Langone Medical Center, New York, NY, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Ryland L Miller
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Immanuel Elbau
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Madison
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Michael J Myers
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Carolina Badke D'Andrea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Matthew Feigelis
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Julian S B Ramirez
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Deanna M Barch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Christopher D Smyser
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Kelly N Botteron
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Peter Brunner
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott A Norris
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Caterina Gratton
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Steven E Petersen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Marcus E Raichle
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, 55455, United States
| | - Nico U F Dosenbach
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA.
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA.
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA.
- Program in Occupational Therapy, Washington University in St. Louis, St Louis, MO, USA.
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10
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Fetcho RN, Hall BS, Estrin DJ, Walsh AP, Schuette PJ, Kaminsky J, Singh A, Roshgodal J, Bavley CC, Nadkarni V, Antigua S, Huynh TN, Grosenick L, Carthy C, Komer L, Adhikari A, Lee FS, Rajadhyaksha AM, Liston C. Regulation of social interaction in mice by a frontostriatal circuit modulated by established hierarchical relationships. Nat Commun 2023; 14:2487. [PMID: 37120443 PMCID: PMC10148889 DOI: 10.1038/s41467-023-37460-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 03/17/2023] [Indexed: 05/01/2023] Open
Abstract
Social hierarchies exert a powerful influence on behavior, but the neurobiological mechanisms that detect and regulate hierarchical interactions are not well understood, especially at the level of neural circuits. Here, we use fiber photometry and chemogenetic tools to record and manipulate the activity of nucleus accumbens-projecting cells in the ventromedial prefrontal cortex (vmPFC-NAcSh) during tube test social competitions. We show that vmPFC-NAcSh projections signal learned hierarchical relationships, and are selectively recruited by subordinate mice when they initiate effortful social dominance behavior during encounters with a dominant competitor from an established hierarchy. After repeated bouts of social defeat stress, this circuit is preferentially activated during social interactions initiated by stress resilient individuals, and plays a necessary role in supporting social approach behavior in subordinated mice. These results define a necessary role for vmPFC-NAcSh cells in the adaptive regulation of social interaction behavior based on prior hierarchical interactions.
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Affiliation(s)
- Robert N Fetcho
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY, USA
| | - Baila S Hall
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - David J Estrin
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Alexander P Walsh
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Peter J Schuette
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jesse Kaminsky
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Ashna Singh
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Jacob Roshgodal
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Charlotte C Bavley
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Viraj Nadkarni
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Susan Antigua
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Thu N Huynh
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Logan Grosenick
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Camille Carthy
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Lauren Komer
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Avishek Adhikari
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Francis S Lee
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Anjali M Rajadhyaksha
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA.
- Weill Cornell Autism Research Program, New York, NY, USA.
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
- Weill Cornell Autism Research Program, New York, NY, USA.
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11
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Weissman CR, Bermudes RA, Voigt J, Liston C, Williams N, Blumberger DM, Fitzgerald PB, Daskalakis ZJ. Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Depression: Mismatch of Evidence and Insurance Coverage Policies in the United States. J Clin Psychiatry 2023; 84. [PMID: 37103918 DOI: 10.4088/jcp.22com14575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Affiliation(s)
- Cory R Weissman
- Department of Psychiatry, University of California San Diego, La Jolla, California
- Corresponding author: Cory R. Weissman, MD, Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92161
| | | | - Jeffrey Voigt
- Medical Device Consultants of Ridgewood, LLC, Ridgewood, New Jersey
| | - Conor Liston
- Department of Psychiatry, Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York
| | - Nolan Williams
- Stanford Brain Stimulation Laboratory, Stanford University, Stanford, California
| | - Daniel M Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Campbell Family Research Institute, Centre for Addiction and Mental Health and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Paul B Fitzgerald
- Australian National University School of Medicine and Psychology, Canberra, Australia
| | - Zafiris J Daskalakis
- Department of Psychiatry, University of California San Diego, La Jolla, California
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12
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Buch AM, Vértes PE, Seidlitz J, Kim SH, Grosenick L, Liston C. Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder. Nat Neurosci 2023; 26:650-663. [PMID: 36894656 DOI: 10.1038/s41593-023-01259-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/17/2023] [Indexed: 03/11/2023]
Abstract
The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.
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Affiliation(s)
- Amanda M Buch
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - So Hyun Kim
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Autism and the Developing Brain, Weill Cornell Medicine, White Plains, NY, USA
- School of Psychology, Korea University, Seoul, South Korea
| | - Logan Grosenick
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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13
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Lynch CJ, Elbau IG, Zhu S, Ayaz A, Bukhari H, Power JD, Liston C. Precision mapping and transcranial magnetic stimulation of individual-specific functional brain networks in humans. STAR Protoc 2023; 4:102118. [PMID: 36853696 PMCID: PMC9958066 DOI: 10.1016/j.xpro.2023.102118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/18/2022] [Accepted: 01/29/2023] [Indexed: 02/16/2023] Open
Abstract
Spatial targeting in transcranial magnetic stimulation protocols does not typically account for the idiosyncratic functional organization of individual human brains. Here, we provide a protocol for implementing targeted functional network stimulation (TANS), which accounts for each individual's unique functional neuroanatomy and cortical folding patterns. Using an example dataset, we describe how to create a head model and estimate the best coil placement and stimulation intensity to minimize off-target effects. For complete details on the use and execution of this protocol, please refer to Lynch et al. (2022).1.
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Affiliation(s)
- Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA.
| | - Immanuel G Elbau
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA
| | - Shasha Zhu
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA
| | - Aliza Ayaz
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA
| | - Hussain Bukhari
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY, USA.
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14
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Rahn R, Liston C. Not immune to stress: LBP's link to depression. Immunity 2023; 56:469-471. [PMID: 36921572 DOI: 10.1016/j.immuni.2023.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
Investigators have long suspected a link between inflammation and depression, but the underlying mechanisms are not well understood. Fang et al. report that lipopolysaccharide-binding protein regulates monoamine biosynthesis and might be a missing link and potential therapeutic target for inflammation-associated depressive behaviors.
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Affiliation(s)
- Rachel Rahn
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
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15
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Elbau IG, Lynch CJ, Downar J, Vila-Rodriguez F, Power JD, Solomonov N, Daskalakis ZJ, Blumberger DM, Liston C. Functional Connectivity Mapping for rTMS Target Selection in Depression. Am J Psychiatry 2023; 180:230-240. [PMID: 36855880 DOI: 10.1176/appi.ajp.20220306] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
OBJECTIVE Repetitive transcranial magnetic stimulation (rTMS) protocols increasingly use subgenual anterior cingulate cortex (sgACC) functional connectivity to individualize treatment targets. However, the efficacy of this approach is unclear, with conflicting findings and varying effect sizes across studies. Here, the authors investigated the effect of the stimulation site's functional connectivity with the sgACC (sgACC-StimFC) on treatment outcome to rTMS in 295 patients with major depression. METHODS The reliability and accuracy of estimating sgACC functional connectivity were validated with data from individuals who underwent extensive functional MRI testing. Electric field modeling was used to analyze associations between sgACC-StimFC and clinical improvement using standardized assessments and to evaluate sources of heterogeneity. RESULTS An imputation-based method provided reliable and accurate sgACC functional connectivity estimates. Treatment responses weakly but robustly correlated with sgACC-StimFC (r=-0.16), but only when the stimulated cortex was identified using electric field modeling. Surprisingly, this association was driven by patients with strong global signal fluctuations stemming from a specific periodic respiratory pattern (r=-0.49). CONCLUSIONS Functional connectivity between the sgACC and the stimulated cortex was correlated with individual differences in treatment outcomes, but the association was weaker than those observed in previous studies and was accentuated in a subgroup of patients with distinct, respiration-related signal patterns in their scans. These findings indicate that in a large representative sample of patients with major depressive disorder, individual differences in sgACC-StimFC explained only ∼3% of the variance in outcomes, which may limit the utility of existing sgACC-based targeting protocols. However, these data also provide strong evidence for a true-albeit small-effect and highlight opportunities for incorporating additional functional connectivity measures to generate models of rTMS response with enhanced predictive power.
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Affiliation(s)
- Immanuel G Elbau
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Charles J Lynch
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Jonathan Downar
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Fidel Vila-Rodriguez
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Jonathan D Power
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Nili Solomonov
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Zafiris J Daskalakis
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Daniel M Blumberger
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York (Elbau, Lynch, Power, Solomonov, Liston); Department of Psychiatry and Institute of Medical Science, Faculty of Medicine, University of Toronto, and Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto (Downar, Blumberger); Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver (Vila-Rodriguez); Department of Psychiatry, University of California, San Diego (Daskalakis)
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16
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Babij R, Ferrer C, Donatelle A, Wacks S, Buch AM, Niemeyer JE, Ma H, Duan ZRS, Fetcho RN, Che A, Otsuka T, Schwartz TH, Huang BS, Liston C, De Marco García NV. Gabrb3 is required for the functional integration of pyramidal neuron subtypes in the somatosensory cortex. Neuron 2023; 111:256-274.e10. [PMID: 36446382 PMCID: PMC9852093 DOI: 10.1016/j.neuron.2022.10.037] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 08/30/2022] [Accepted: 10/27/2022] [Indexed: 11/29/2022]
Abstract
Dysfunction of gamma-aminobutyric acid (GABA)ergic circuits is strongly associated with neurodevelopmental disorders. However, it is unclear how genetic predispositions impact circuit assembly. Using in vivo two-photon and widefield calcium imaging in developing mice, we show that Gabrb3, a gene strongly associated with autism spectrum disorder (ASD) and Angelman syndrome (AS), is enriched in contralaterally projecting pyramidal neurons and is required for inhibitory function. We report that Gabrb3 ablation leads to a developmental decrease in GABAergic synapses, increased local network synchrony, and long-lasting enhancement in functional connectivity of contralateral-but not ipsilateral-pyramidal neuron subtypes. In addition, Gabrb3 deletion leads to increased cortical response to tactile stimulation at neonatal stages. Using human transcriptomics and neuroimaging datasets from ASD subjects, we show that the spatial distribution of GABRB3 expression correlates with atypical connectivity in these subjects. Our studies reveal a requirement for Gabrb3 during the emergence of interhemispheric circuits for sensory processing.
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Affiliation(s)
- Rachel Babij
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA.,Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY 10021, USA
| | - Camilo Ferrer
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Alexander Donatelle
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Sam Wacks
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Amanda M Buch
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - James E Niemeyer
- Department of Neurological Surgery, Weill Cornell Medicine, New-York Presbyterian Hospital, New York, NY 10021, USA
| | - Hongtao Ma
- Department of Neurological Surgery, Weill Cornell Medicine, New-York Presbyterian Hospital, New York, NY 10021, USA
| | - Zhe Ran S Duan
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA.,Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY 10021, USA
| | - Robert N Fetcho
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA.,Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY 10021, USA
| | - Alicia Che
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA.,Current affiliation: Department of Psychiatry, Yale School of Medicine, New Haven, CT 06519, USA
| | - Takumi Otsuka
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Theodore H Schwartz
- Department of Neurological Surgery, Weill Cornell Medicine, New-York Presbyterian Hospital, New York, NY 10021, USA
| | - Ben S Huang
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Conor Liston
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Natalia V De Marco García
- Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA.,Lead Contact,Correspondence to
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17
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Lynch CJ, Elbau IG, Ng TH, Wolk D, Zhu S, Ayaz A, Power JD, Zebley B, Gunning FM, Liston C. Automated optimization of TMS coil placement for personalized functional network engagement. Brain Stimul 2023. [DOI: 10.1016/j.brs.2023.01.224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
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18
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Witztum J, Singh A, Zhang R, Johnson M, Liston C. An automated platform for Assessing Working Memory and prefrontal circuit function. Neurobiol Stress 2023; 24:100518. [PMID: 36970451 PMCID: PMC10033752 DOI: 10.1016/j.ynstr.2023.100518] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 01/02/2023] [Accepted: 01/23/2023] [Indexed: 01/27/2023] Open
Abstract
Working memory is a process for actively maintaining and updating task-relevant information, despite interference from competing inputs, and is supported in part by sustained activity in prefrontal cortical pyramidal neurons and coordinated interactions with inhibitory interneurons, which may serve to regulate interference. Chronic stress has potent effects on working memory performance, possibly by interfering with these interactions or by disrupting long-range inputs from key upstream brain regions. Still, the mechanisms by which chronic stress disrupts working memory are not well understood, due in part to a need for scalable, easy-to-implement behavioral assays that are compatible with two-photon calcium imaging and other tools for recording from large populations of neurons. Here, we describe the development and validation of a platform that was designed specifically for automated, high-throughput assessments of working memory and simultaneous two-photon imaging in chronic stress studies. This platform is relatively inexpensive and easy to build; fully automated and scalable such that one investigator can test relatively large cohorts of animals concurrently; fully compatible with two-photon imaging, yet also designed to mitigate head-fixation stress; and can be easily adapted for other behavioral paradigms. Our validation data confirm that mice could be trained to perform a delayed response working memory task with relatively high-fidelity over the course of ∼15 days. Two-photon imaging data validate the feasibility of recording from large populations of cells during working memory tasks performance and characterizing their functional properties. Activity patterns in >70% of medial prefrontal cortical neurons were modulated by at least one task feature, and a majority of cells were engaged by multiple task features. We conclude with a brief literature review of the circuit mechanisms supporting working memory and their disruption in chronic stress states-highlighting directions for future research enabled by this platform.
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19
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Lynch CJ, Elbau IG, Ng TH, Wolk D, Zhu S, Ayaz A, Power JD, Zebley B, Gunning FM, Liston C. Automated optimization of TMS coil placement for personalized functional network engagement. Neuron 2022; 110:3263-3277.e4. [PMID: 36113473 DOI: 10.1016/j.neuron.2022.08.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/20/2022] [Accepted: 08/05/2022] [Indexed: 12/11/2022]
Abstract
Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.
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Affiliation(s)
- Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA.
| | - Immanuel G Elbau
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Tommy H Ng
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Danielle Wolk
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Shasha Zhu
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Aliza Ayaz
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Benjamin Zebley
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Faith M Gunning
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA.
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20
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Talishinsky A, Downar J, Vértes PE, Seidlitz J, Dunlop K, Lynch CJ, Whalley H, McIntosh A, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Liston C. Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression. Nat Commun 2022; 13:5692. [PMID: 36171190 PMCID: PMC9519925 DOI: 10.1038/s41467-022-32617-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 08/09/2022] [Indexed: 12/02/2022] Open
Abstract
The neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8, a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation.
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Affiliation(s)
- Aleksandr Talishinsky
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan Downar
- Krembil Research Institute and Centre for Mental Health, University Health Network, Toronto, ON, USA.
- Department of Psychiatry, University of Toronto, Toronto, ON, USA.
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharine Dunlop
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Heather Whalley
- Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew McIntosh
- Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies Lab and Department of Psychiatry, University of British Columbia, Vancouver, BC, USA
| | | | - Daniel M Blumberger
- Department of Psychiatry, University of Toronto, Toronto, ON, USA
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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21
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Yadav N, Noble C, Niemeyer JE, Terceros A, Victor J, Liston C, Rajasethupathy P. Prefrontal feature representations drive memory recall. Nature 2022; 608:153-160. [PMID: 35831504 PMCID: PMC9577479 DOI: 10.1038/s41586-022-04936-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 06/06/2022] [Indexed: 02/03/2023]
Abstract
Memory formation involves binding of contextual features into a unitary representation1-4, whereas memory recall can occur using partial combinations of these contextual features. The neural basis underlying the relationship between a contextual memory and its constituent features is not well understood; in particular, where features are represented in the brain and how they drive recall. Here, to gain insight into this question, we developed a behavioural task in which mice use features to recall an associated contextual memory. We performed longitudinal imaging in hippocampus as mice performed this task and identified robust representations of global context but not of individual features. To identify putative brain regions that provide feature inputs to hippocampus, we inhibited cortical afferents while imaging hippocampus during behaviour. We found that whereas inhibition of entorhinal cortex led to broad silencing of hippocampus, inhibition of prefrontal anterior cingulate led to a highly specific silencing of context neurons and deficits in feature-based recall. We next developed a preparation for simultaneous imaging of anterior cingulate and hippocampus during behaviour, which revealed robust population-level representation of features in anterior cingulate, that lag hippocampus context representations during training but dynamically reorganize to lead and target recruitment of context ensembles in hippocampus during recall. Together, we provide the first mechanistic insights into where contextual features are represented in the brain, how they emerge, and how they access long-range episodic representations to drive memory recall.
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Affiliation(s)
- Nakul Yadav
- Laboratory of Neural Dynamics and Cognition, The Rockefeller University, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Chelsea Noble
- Laboratory of Neural Dynamics and Cognition, The Rockefeller University, New York, NY, USA
| | - James E Niemeyer
- Laboratory of Neural Dynamics and Cognition, The Rockefeller University, New York, NY, USA
- Department of Neurological Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Andrea Terceros
- Laboratory of Neural Dynamics and Cognition, The Rockefeller University, New York, NY, USA
| | - Jonathan Victor
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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22
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Abstract
Depression is an episodic form of mental illness characterized by mood state transitions with poorly understood neurobiological mechanisms. Antidepressants reverse the effects of stress and depression on synapse function, enhancing neurotransmission, increasing plasticity, and generating new synapses in stress-sensitive brain regions. These properties are shared to varying degrees by all known antidepressants, suggesting that synaptic remodeling could play a key role in depression pathophysiology and antidepressant function. Still, it is unclear whether and precisely how synaptogenesis contributes to mood state transitions. Here, we review evidence supporting an emerging model in which depression is defined by a distinct brain state distributed across multiple stress-sensitive circuits, with neurons assuming altered functional properties, synapse configurations, and, importantly, a reduced capacity for plasticity and adaptation. Antidepressants act initially by facilitating plasticity and enabling a functional reconfiguration of this brain state. Subsequently, synaptogenesis plays a specific role in sustaining these changes over time.
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Affiliation(s)
- Puja K Parekh
- Department of Psychiatry and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York, USA;
| | - Shane B Johnson
- Department of Psychiatry and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York, USA;
| | - Conor Liston
- Department of Psychiatry and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York, USA;
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23
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Allen M, Huang BS, Notaras MJ, Lodhi A, Barrio-Alonso E, Lituma PJ, Wolujewicz P, Witztum J, Longo F, Chen M, Greening DW, Klann E, Ross ME, Liston C, Colak D. Astrocytes derived from ASD individuals alter behavior and destabilize neuronal activity through aberrant Ca 2+ signaling. Mol Psychiatry 2022; 27:2470-2484. [PMID: 35365802 PMCID: PMC9135629 DOI: 10.1038/s41380-022-01486-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 02/01/2022] [Accepted: 02/11/2022] [Indexed: 01/08/2023]
Abstract
The cellular mechanisms of autism spectrum disorder (ASD) are poorly understood. Cumulative evidence suggests that abnormal synapse function underlies many features of this disease. Astrocytes regulate several key neuronal processes, including the formation of synapses and the modulation of synaptic plasticity. Astrocyte abnormalities have also been identified in the postmortem brain tissue of ASD individuals. However, it remains unclear whether astrocyte pathology plays a mechanistic role in ASD, as opposed to a compensatory response. To address this, we combined stem cell culturing with transplantation techniques to determine disease-specific properties inherent to ASD astrocytes. We demonstrate that ASD astrocytes induce repetitive behavior as well as impair memory and long-term potentiation when transplanted into the healthy mouse brain. These in vivo phenotypes were accompanied by reduced neuronal network activity and spine density caused by ASD astrocytes in hippocampal neurons in vitro. Transplanted ASD astrocytes also exhibit exaggerated Ca2+ fluctuations in chimeric brains. Genetic modulation of evoked Ca2+ responses in ASD astrocytes modulates behavior and neuronal activity deficits. Thus, this study determines that astrocytes derived from ASD iPSCs are sufficient to induce repetitive behavior as well as cognitive deficit, suggesting a previously unrecognized primary role for astrocytes in ASD.
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Affiliation(s)
- Megan Allen
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Ben S Huang
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.,Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Michael J Notaras
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Aiman Lodhi
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Estibaliz Barrio-Alonso
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Pablo J Lituma
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Paul Wolujewicz
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Jonathan Witztum
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Francesco Longo
- Center for Neural Science, New York University, New York, NY, USA
| | - Maoshan Chen
- Molecular Proteomics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.,Baker Department of Cardiometabolic Health, The University of Melbourne, Melbourne, VIC, Australia.,Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, VIC, Australia.,Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - David W Greening
- Molecular Proteomics, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.,Baker Department of Cardiometabolic Health, The University of Melbourne, Melbourne, VIC, Australia.,Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, VIC, Australia.,Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Eric Klann
- Center for Neural Science, New York University, New York, NY, USA
| | - M Elizabeth Ross
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Conor Liston
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.,Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Dilek Colak
- Center for Neurogenetics, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA. .,Gale and Ira Drukier Institute for Children's Health, Weill Cornell Medicine, Cornell University, New York, NY, USA.
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24
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Stujenske JM, O'Neill PK, Fernandes-Henriques C, Nahmoud I, Goldburg SR, Singh A, Diaz L, Labkovich M, Hardin W, Bolkan SS, Reardon TR, Spellman TJ, Salzman CD, Gordon JA, Liston C, Likhtik E. Prelimbic cortex drives discrimination of non-aversion via amygdala somatostatin interneurons. Neuron 2022; 110:2258-2267.e11. [PMID: 35397211 DOI: 10.1016/j.neuron.2022.03.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/31/2021] [Accepted: 03/11/2022] [Indexed: 11/20/2022]
Abstract
The amygdala and prelimbic cortex (PL) communicate during fear discrimination retrieval, but how they coordinate discrimination of a non-threatening stimulus is unknown. Here, we show that somatostatin (SOM) interneurons in the basolateral amygdala (BLA) become active specifically during learned non-threatening cues and desynchronize cell firing by blocking phase reset of theta oscillations during the safe cue. Furthermore, we show that SOM activation and desynchronization of the BLA is PL-dependent and promotes discrimination of non-threat. Thus, fear discrimination engages PL-dependent coordination of BLA SOM responses to non-threatening stimuli.
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Affiliation(s)
- Joseph M Stujenske
- Department of Psychiatry, Weill Cornell Medical College, New York, NY 10065, USA.
| | - Pia-Kelsey O'Neill
- Department of Psychiatry, Columbia University, New York, NY 10027, USA; The Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University, New York, NY 10027, USA; Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Carolina Fernandes-Henriques
- Biology Program, The Graduate Center, City University of New York, New York, NY 10016, USA; Department of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA
| | - Itzick Nahmoud
- Wayne State University School of Medicine, Detroit, MI 48201, USA
| | | | - Ashna Singh
- Department of Psychiatry, Weill Cornell Medical College, New York, NY 10065, USA
| | - Laritza Diaz
- Charles E. Schmidt College of Medicine, Boca Raton, FL 33431, USA
| | | | | | - Scott S Bolkan
- Princeton Neuroscience Institute, Princeton, New Jersey 08540, USA
| | | | - Timothy J Spellman
- Department of Neuroscience, UConn School of Medicine, Farmington, CT 06032, USA
| | - C Daniel Salzman
- Department of Psychiatry, Columbia University, New York, NY 10027, USA; The Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University, New York, NY 10027, USA; Department of Neuroscience, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Sciences, Columbia University, New York, NY 10027, USA; New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, USA
| | - Joshua A Gordon
- National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medical College, New York, NY 10065, USA
| | - Ekaterina Likhtik
- Biology Program, The Graduate Center, City University of New York, New York, NY 10016, USA; Department of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.
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25
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 372] [Impact Index Per Article: 186.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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26
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Jaywant A, Dunlop K, Victoria LW, Oberlin L, Lynch CJ, Respino M, Kuceyeski A, Scult M, Hoptman MJ, Liston C, O’Dell MW, Alexopoulos GS, Perlis RH, Gunning FM. Estimated Regional White Matter Hyperintensity Burden, Resting State Functional Connectivity, and Cognitive Functions in Older Adults. Am J Geriatr Psychiatry 2022; 30:269-280. [PMID: 34412936 PMCID: PMC8799753 DOI: 10.1016/j.jagp.2021.07.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/24/2021] [Accepted: 07/22/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE White matter hyperintensities (WMH) are linked to deficits in cognitive functioning, including cognitive control and memory; however, the structural, and functional mechanisms are largely unknown. We investigated the relationship between estimated regional disruptions to white matter fiber tracts from WMH, resting state functional connectivity (RSFC), and cognitive functions in older adults. DESIGN Cross-sectional study. SETTING Community. PARTICIPANTS Fifty-eight cognitively-healthy older adults. MEASUREMENTS Tasks of cognitive control and memory, structural MRI, and resting state fMRI. We estimated the disruption to white matter fiber tracts from WMH and its impact on gray matter regions in the cortical and subcortical frontoparietal network, default mode network, and ventral attention network by overlaying each subject's WMH mask on a normative tractogram dataset. We calculated RSFC between nodes in those same networks. We evaluated the interaction of regional WMH burden and RSFC in predicting cognitive control and memory. RESULTS The interaction of estimated regional WMH burden and RSFC in cortico-striatal regions of the default mode network and frontoparietal network was associated with delayed recall. Models predicting working memory, cognitive inhibition, and set-shifting were not significant. CONCLUSION Findings highlight the role of network-level structural and functional alterations in resting state networks that are related to WMH and impact memory in older adults.
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Affiliation(s)
- Abhishek Jaywant
- Department of Psychiatry, Weill Cornell Medicine,Department of Rehabilitation Medicine, Weill Cornell Medicine
| | - Katharine Dunlop
- Department of Psychiatry, Weill Cornell Medicine,Feil Family Brain and Mind Research Institute, Weill Cornell Medicine
| | - Lindsay W. Victoria
- Department of Psychiatry, Weill Cornell Medicine,Weill Cornell Institute of Geriatric Psychiatry
| | - Lauren Oberlin
- Department of Psychiatry, Weill Cornell Medicine,Weill Cornell Institute of Geriatric Psychiatry
| | - Charles J. Lynch
- Department of Psychiatry, Weill Cornell Medicine,Feil Family Brain and Mind Research Institute, Weill Cornell Medicine
| | - Matteo Respino
- Department of Psychiatry, Weill Cornell Medicine,Weill Cornell Institute of Geriatric Psychiatry
| | | | | | - Matthew J. Hoptman
- Nathan Kline Institute for Psychiatric Research,Department of Psychiatry, New York University School of Medicine
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine,Feil Family Brain and Mind Research Institute, Weill Cornell Medicine
| | | | - George S. Alexopoulos
- Department of Psychiatry, Weill Cornell Medicine,Weill Cornell Institute of Geriatric Psychiatry
| | - Roy H. Perlis
- Harvard Medical School/Massachusetts General Hospital
| | - Faith M. Gunning
- Department of Psychiatry, Weill Cornell Medicine,Weill Cornell Institute of Geriatric Psychiatry
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Abstract
Psychiatric disease is one of the greatest health challenges of our time. The pipeline for conceptually novel therapeutics remains low, in part because uncovering the biological mechanisms of psychiatric disease has been difficult. We asked experts researching different aspects of psychiatric disease: what do you see as the major urgent questions that need to be addressed? Where are the next frontiers, and what are the current hurdles to understanding the biological basis of psychiatric disease?
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28
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Milham M, Petkov C, Belin P, Ben Hamed S, Evrard H, Fair D, Fox A, Froudist-Walsh S, Hayashi T, Kastner S, Klink C, Majka P, Mars R, Messinger A, Poirier C, Schroeder C, Shmuel A, Silva AC, Vanduffel W, Van Essen DC, Wang Z, Roe AW, Wilke M, Xu T, Aarabi MH, Adolphs R, Ahuja A, Alvand A, Amiez C, Autio J, Azadi R, Baeg E, Bai R, Bao P, Basso M, Behel AK, Bennett Y, Bernhardt B, Biswal B, Boopathy S, Boretius S, Borra E, Boshra R, Buffalo E, Cao L, Cavanaugh J, Celine A, Chavez G, Chen LM, Chen X, Cheng L, Chouinard-Decorte F, Clavagnier S, Cléry J, Colcombe SJ, Conway B, Cordeau M, Coulon O, Cui Y, Dadarwal R, Dahnke R, Desrochers T, Deying L, Dougherty K, Doyle H, Drzewiecki CM, Duyck M, Arachchi WE, Elorette C, Essamlali A, Evans A, Fajardo A, Figueroa H, Franco A, Freches G, Frey S, Friedrich P, Fujimoto A, Fukunaga M, Gacoin M, Gallardo G, Gao L, Gao Y, Garside D, Garza-Villarreal EA, Gaudet-Trafit M, Gerbella M, Giavasis S, Glen D, Ribeiro Gomes AR, Torrecilla SG, Gozzi A, Gulli R, Haber S, Hadj-Bouziane F, Fujimoto SH, Hawrylycz M, He Q, He Y, Heuer K, Hiba B, Hoffstaedter F, Hong SJ, Hori Y, Hou Y, Howard A, de la Iglesia-Vaya M, Ikeda T, Jankovic-Rapan L, Jaramillo J, Jedema HP, Jin H, Jiang M, Jung B, Kagan I, Kahn I, Kiar G, Kikuchi Y, Kilavik B, Kimura N, Klatzmann U, Kwok SC, Lai HY, Lamberton F, Lehman J, Li P, Li X, Li X, Liang Z, Liston C, Little R, Liu C, Liu N, Liu X, Liu X, Lu H, Loh KK, Madan C, Magrou L, Margulies D, Mathilda F, Mejia S, Meng Y, Menon R, Meunier D, Mitchell A, Mitchell A, Murphy A, Mvula T, Ortiz-Rios M, Ortuzar Martinez DE, Pagani M, Palomero-Gallagher N, Pareek V, Perkins P, Ponce F, Postans M, Pouget P, Qian M, Ramirez J“B, Raven E, Restrepo I, Rima S, Rockland K, Rodriguez NY, Roger E, Hortelano ER, Rosa M, Rossi A, Rudebeck P, Russ B, Sakai T, Saleem KS, Sallet J, Sawiak S, Schaeffer D, Schwiedrzik CM, Seidlitz J, Sein J, Sharma J, Shen K, Sheng WA, Shi NS, Shim WM, Simone L, Sirmpilatze N, Sivan V, Song X, Tanenbaum A, Tasserie J, Taylor P, Tian X, Toro R, Trambaiolli L, Upright N, Vezoli J, Vickery S, Villalon J, Wang X, Wang Y, Weiss AR, Wilson C, Wong TY, Woo CW, Wu B, Xiao D, Xu AG, Xu D, Xufeng Z, Yacoub E, Ye N, Ying Z, Yokoyama C, Yu X, Yue S, Yuheng L, Yumeng X, Zaldivar D, Zhang S, Zhao Y, Zuo Z. Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging. Neuron 2022; 110:16-20. [PMID: 34731649 DOI: 10.1016/j.neuron.2021.10.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/30/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
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Dunlop K, Dua A, Liston C. A comparison of symptom-specific resting state functional connectivity biomarkers of 10 Hz and iTBS-rTMS in treatment-resistant depression. Brain Stimul 2021. [DOI: 10.1016/j.brs.2021.10.406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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30
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Elbau IG, Lynch CJ, Downar J, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Liston C. Effect of E-field based sgACC connectivity on rTMS outcome in the THREE-D trial. Brain Stimul 2021. [DOI: 10.1016/j.brs.2021.10.201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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31
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Zebley B, Wolk D, McAllister M, Lynch CJ, Mikofsky R, Liston C. Individual Differences in the Affective Response to Pandemic-related Stressors in COVID-19 Healthcare Workers. Biol Psychiatry Glob Open Sci 2021; 1:336-344. [PMID: 34704087 PMCID: PMC8529885 DOI: 10.1016/j.bpsgos.2021.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/12/2021] [Accepted: 08/27/2021] [Indexed: 11/16/2022] Open
Abstract
Background We investigated the evolving prevalence of mood and anxiety symptoms among healthcare workers from May, 2020 to January, 2021; risk factors for adverse outcomes; and characteristic modes of affective responses to pandemic-related stressors. Methods 2,307 healthcare workers (78.9% female, modal age 25-34) participated in an online survey assessing depression (Patient Health Questionnaire [PHQ-9]) and anxiety symptoms (Generalized Anxiety Disorder scale [GAD-7]), demographic variables, and self-reported impact of pandemic-related stressors. 334 subjects were reassessed ∼6 months later. Results The prevalence of clinically significant depression and anxiety was 45.3% and 43.3%, respectively, and a majority (59.9%-62.9%) of those individuals had persistent significant symptoms at 6-month follow-up. Younger age, female gender, and specific occupations (support staff > nurses > physicians) were associated with increased depressive and anxiety symptoms. The most important risk factors were social isolation and fear of contracting COVID-19. The prevalence of clinically significant mood and anxiety symptoms increased by 39.8% from May, 2020 to January, 2021. PHQ-9 and GAD-7 scores were highly correlated and associated with nearly identical risk factors, suggesting that they are not capturing independent constructs in this sample. Principal components analysis identified seven orthogonal symptom domains with unique risk factors. Conclusions Clinically significant mood and anxiety symptoms are highly prevalent and persistent among healthcare workers, and are associated with numerous risk factors, the strongest of which are related to pandemic stressors and potentially modifiable. Interventions aimed at reducing social isolation and mitigating the impact of fear of infection warrant further study.
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Affiliation(s)
- Benjamin Zebley
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
| | - Danielle Wolk
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
| | - Mary McAllister
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
| | - Charles J Lynch
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
| | - Rachel Mikofsky
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine
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32
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Sydnor VJ, Larsen B, Bassett DS, Alexander-Bloch A, Fair DA, Liston C, Mackey AP, Milham MP, Pines A, Roalf DR, Seidlitz J, Xu T, Raznahan A, Satterthwaite TD. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron 2021; 109:2820-2846. [PMID: 34270921 PMCID: PMC8448958 DOI: 10.1016/j.neuron.2021.06.016] [Citation(s) in RCA: 191] [Impact Index Per Article: 63.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/24/2021] [Accepted: 06/11/2021] [Indexed: 12/11/2022]
Abstract
The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY 10962, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, NIMH Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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33
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Solomonov N, Lee J, Banerjee S, Flückiger C, Kanellopoulos D, Gunning FM, Sirey JA, Liston C, Raue PJ, Hull TD, Areán PA, Alexopoulos GS. Modifiable predictors of nonresponse to psychotherapies for late-life depression with executive dysfunction: a machine learning approach. Mol Psychiatry 2021; 26:5190-5198. [PMID: 32651477 PMCID: PMC8120667 DOI: 10.1038/s41380-020-0836-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 05/11/2020] [Accepted: 07/01/2020] [Indexed: 01/24/2023]
Abstract
The study aimed to: (1) Identify distinct trajectories of change in depressive symptoms by mid-treatment during psychotherapy for late-life depression with executive dysfunction; (2) examine if nonresponse by mid-treatment predicted poor response at treatment end; and (3) identify baseline characteristics predicting an early nonresponse trajectory by mid-treatment. A sample of 221 adults 60 years and older with major depression and executive dysfunction were randomized to 12 weeks of either problem-solving therapy or supportive therapy. We used Latent Growth Mixture Models (LGMM) to detect subgroups with distinct trajectories of change in depression by mid-treatment (6th week). We conducted regression analyses with LGMM subgroups as predictors of response at treatment end. We used random forest machine learning algorithms to identify baseline predictors of LGMM trajectories. We found that ~77.5% of participants had a declining trajectory of depression in weeks 0-6, while the remaining 22.5% had a persisting depression trajectory, with no treatment differences. The LGMM trajectories predicted remission and response at treatment end. A random forests model with high prediction accuracy (80%) showed that the strongest modifiable predictors of the persisting depression trajectory were low perceived social support, followed by high neuroticism, low treatment expectancy, and low perception of the therapist as accepting. Our results suggest that modifiable risk factors of early nonresponse to psychotherapy can be identified at the outset of treatment and addressed with targeted personalized interventions. Therapists may focus on increasing meaningful social interactions, addressing concerns related to treatment benefits, and creating a positive working relationship.
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Affiliation(s)
- Nili Solomonov
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
| | - Jihui Lee
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
- Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, NY, USA
| | - Samprit Banerjee
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
- Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, NY, USA
| | | | - Dora Kanellopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
| | - Faith M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
| | - Jo Anne Sirey
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA
| | - Conor Liston
- Feil Family Brain Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Patrick J Raue
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Thomas D Hull
- Teachers College, Columbia University, New York, NY, USA
- TalkSpace, New York, NY, USA
| | - Patricia A Areán
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - George S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA.
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Gutzeit V, Munguba H, Kristt M, Thukral S, Liston C, Broichhagen J, Levitz J. Optical Interrogation of Metabotropic Glutamate Receptor‐Mediated Modulation of Cortical Circuits using Optimized Photoswitchable Tethered Ligands. FASEB J 2021. [DOI: 10.1096/fasebj.2021.35.s1.04254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Abstract
Rapidly developing approaches to acquiring and analyzing densely-sampled, single-subject fMRI data have opened new avenues for understanding the neurobiological basis of individual differences in behavior and could allow fMRI to become a more clinically useful tool. Here, we review briefly key insights from these precision functional mapping studies and a highlight significant barrier to their clinical translation. Specifically, that reliable delineation of functional brain networks in individual humans can require hours of resting-state fMRI data per-subject. We found recently that multi-echo fMRI improves the test-retest reliability of resting-state functional connectivity measurements, mitigating the need for acquiring large quantities of per -subject data. Because the benefits of multi-echo acquisitions are most pronounced in clinically important but artifact-prone brain regions, such as the subgenual cingulate and structures deep in the subcortex, this approach has the potential to increase the impact of precision functional mapping routines in both healthy and clinical populations.
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Affiliation(s)
- Charles J Lynch
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69 Street, Box 240, New York, NY 10021
| | - Immanuel Elbau
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69 Street, Box 240, New York, NY 10021
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69 Street, Box 240, New York, NY 10021
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Spellman T, Svei M, Kaminsky J, Manzano-Nieves G, Liston C. Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring. Cell 2021; 184:2750-2766.e17. [PMID: 33861951 DOI: 10.1016/j.cell.2021.03.047] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 02/16/2021] [Accepted: 03/23/2021] [Indexed: 12/20/2022]
Abstract
Cognitive flexibility, the ability to alter strategy according to changing stimulus-response-reward relationships, is critical for updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what role PFC neurons play to support set-shifting. Using optogenetics and two-photon calcium imaging, we demonstrate that medial PFC activity does not bias sensorimotor responses during set-shifting, but rather enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface, where afferent input from the anterior cingulate cortex was denser. These findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring.
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Affiliation(s)
- Timothy Spellman
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
| | - Malka Svei
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Jesse Kaminsky
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Gabriela Manzano-Nieves
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
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Gutzeit VA, Acosta-Ruiz A, Munguba H, Häfner S, Landra-Willm A, Mathes B, Mony J, Yarotski D, Börjesson K, Liston C, Sandoz G, Levitz J, Broichhagen J. A fine-tuned azobenzene for enhanced photopharmacology in vivo. Cell Chem Biol 2021; 28:1648-1663.e16. [PMID: 33735619 DOI: 10.1016/j.chembiol.2021.02.020] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/23/2020] [Accepted: 02/23/2021] [Indexed: 12/15/2022]
Abstract
Despite the power of photopharmacology for interrogating signaling proteins, many photopharmacological systems are limited by their efficiency, speed, or spectral properties. Here, we screen a library of azobenzene photoswitches and identify a urea-substituted "azobenzene-400" core that offers bistable switching between cis and trans with improved kinetics, light sensitivity, and a red-shift. We then focus on the metabotropic glutamate receptors (mGluRs), neuromodulatory receptors that are major pharmacological targets. Synthesis of "BGAG12,400," a photoswitchable orthogonal, remotely tethered ligand (PORTL), enables highly efficient, rapid optical agonism following conjugation to SNAP-tagged mGluR2 and permits robust optical control of mGluR1 and mGluR5 signaling. We then produce fluorophore-conjugated branched PORTLs to enable dual imaging and manipulation of mGluRs and highlight their power in ex vivo slice and in vivo behavioral experiments in the mouse prefrontal cortex. Finally, we demonstrate the generalizability of our strategy by developing an improved soluble, photoswitchable pore blocker for potassium channels.
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Affiliation(s)
- Vanessa A Gutzeit
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Amanda Acosta-Ruiz
- Biochemistry, Cell and Molecular Biology Graduate Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Hermany Munguba
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Stephanie Häfner
- Université Cote d'Azur, CNRS, INSERM, iBV, Nice, France; Laboratories of Excellence, Ion Channel Science and Therapeutics, Nice, France
| | - Arnaud Landra-Willm
- Université Cote d'Azur, CNRS, INSERM, iBV, Nice, France; Laboratories of Excellence, Ion Channel Science and Therapeutics, Nice, France
| | - Bettina Mathes
- Department of Chemical Biology, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany
| | - Jürgen Mony
- Department of Chemistry and Molecular Biology, University of Gothenburg, 41296 Gothenburg, Sweden
| | - Dzianis Yarotski
- Department of Chemical Biology, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany
| | - Karl Börjesson
- Department of Chemistry and Molecular Biology, University of Gothenburg, 41296 Gothenburg, Sweden
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
| | - Guillaume Sandoz
- Université Cote d'Azur, CNRS, INSERM, iBV, Nice, France; Laboratories of Excellence, Ion Channel Science and Therapeutics, Nice, France
| | - Joshua Levitz
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY 10065, USA; Biochemistry, Cell and Molecular Biology Graduate Program, Weill Cornell Medicine, New York, NY 10065, USA; Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA.
| | - Johannes Broichhagen
- Department of Chemical Biology, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany; Department of Chemical Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie, 13125 Berlin, Germany.
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Li A, Jing D, Dellarco DV, Hall BS, Yang R, Heilberg RT, Huang C, Liston C, Casey BJ, Lee FS. Role of BDNF in the development of an OFC-amygdala circuit regulating sociability in mouse and human. Mol Psychiatry 2021; 26:955-973. [PMID: 30992540 PMCID: PMC6883137 DOI: 10.1038/s41380-019-0422-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 03/17/2019] [Accepted: 04/03/2019] [Indexed: 01/29/2023]
Abstract
Social deficits are common in many psychiatric disorders. However, due to inadequate tools for manipulating circuit activity in humans and unspecific paradigms for modeling social behaviors in rodents, our understanding of the molecular and circuit mechanisms mediating social behaviors remains relatively limited. Using human functional neuroimaging and rodent fiber photometry, we identified a mOFC-BLA projection that modulates social approach behavior and influences susceptibility to social anxiety. In humans and knock-in mice with a loss of function BDNF SNP (Val66Met), the functionality of this circuit was altered, resulting in social behavioral changes in human and mice. We further showed that the development of this circuit is disrupted in BDNF Met carriers due to insufficient BDNF bioavailability, specifically during a peri-adolescent timeframe. These findings define one mechanism by which social anxiety may stem from altered maturation of orbitofronto-amygdala projections and identify a developmental window in which BDNF-based interventions may have therapeutic potential.
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Affiliation(s)
- Anfei Li
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, New York, NY, USA
| | - Deqiang Jing
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Danielle V Dellarco
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, New York, NY, USA
| | - Baila S Hall
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Ruirong Yang
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Ross T Heilberg
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Chienchun Huang
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - B J Casey
- Department of Psychology, Yale University, New Haven, CT, USA.
| | - Francis S Lee
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, New York, NY, USA.
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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Manzano-Nieves G, Liston C. Psychedelics re-engineered for potential use in the clinic. Nature 2020; 589:358-359. [PMID: 33299163 DOI: 10.1038/d41586-020-03404-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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40
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Lynch CJ, Power JD, Scult MA, Dubin M, Gunning FM, Liston C. Rapid Precision Functional Mapping of Individuals Using Multi-Echo fMRI. Cell Rep 2020; 33:108540. [PMID: 33357444 PMCID: PMC7792478 DOI: 10.1016/j.celrep.2020.108540] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 10/15/2020] [Accepted: 11/25/2020] [Indexed: 12/20/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) is widely used in cognitive and clinical neuroscience, but long-duration scans are currently needed to reliably characterize individual differences in functional connectivity (FC) and brain network topology. In this report, we demonstrate that multi-echo fMRI can improve the reliability of FC-based measurements. In four densely sampled individual humans, just 10 min of multi-echo data yielded better test-retest reliability than 30 min of single-echo data in independent datasets. This effect is pronounced in clinically important brain regions, including the subgenual cingulate, basal ganglia, and cerebellum, and is linked to three biophysical signal mechanisms (thermal noise, regional variability in the rate of T2* decay, and S0-dependent artifacts) with spatially distinct influences. Together, these findings establish the potential utility of multi-echo fMRI for rapid precision mapping using experimentally and clinically tractable scan times and will facilitate longitudinal neuroimaging of clinical populations. Lynch et al. demonstrate that the test-retest reliability of resting-state connectivity measurements can be improved using multi-echo fMRI. This effect is pronounced in clinically important brain regions and could help facilitate precision mapping of functional brain networks in healthy people and patient populations.
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Affiliation(s)
- Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Matthew A Scult
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Marc Dubin
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Faith M Gunning
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
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Campbell BC, Nabel EM, Murdock MH, Lao-Peregrin C, Tsoulfas P, Blackmore MG, Lee FS, Liston C, Morishita H, Petsko GA. mGreenLantern: a bright monomeric fluorescent protein with rapid expression and cell filling properties for neuronal imaging. Proc Natl Acad Sci U S A 2020; 117:30710-30721. [PMID: 33208539 PMCID: PMC7720163 DOI: 10.1073/pnas.2000942117] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Although ubiquitous in biological studies, the enhanced green and yellow fluorescent proteins (EGFP and EYFP) were not specifically optimized for neuroscience, and their underwhelming brightness and slow expression in brain tissue limits the fidelity of dendritic spine analysis and other indispensable techniques for studying neurodevelopment and plasticity. We hypothesized that EGFP's low solubility in mammalian systems must limit the total fluorescence output of whole cells, and that improving folding efficiency could therefore translate into greater brightness of expressing neurons. By introducing rationally selected combinations of folding-enhancing mutations into GFP templates and screening for brightness and expression rate in human cells, we developed mGreenLantern, a fluorescent protein having up to sixfold greater brightness in cells than EGFP. mGreenLantern illuminates neurons in the mouse brain within 72 h, dramatically reducing lag time between viral transduction and imaging, while its high brightness improves detection of neuronal morphology using widefield, confocal, and two-photon microscopy. When virally expressed to projection neurons in vivo, mGreenLantern fluorescence developed four times faster than EYFP and highlighted long-range processes that were poorly detectable in EYFP-labeled cells. Additionally, mGreenLantern retains strong fluorescence after tissue clearing and expansion microscopy, thereby facilitating superresolution and whole-brain imaging without immunohistochemistry. mGreenLantern can directly replace EGFP/EYFP in diverse systems due to its compatibility with GFP filter sets, recognition by EGFP antibodies, and excellent performance in mouse, human, and bacterial cells. Our screening and rational engineering approach is broadly applicable and suggests that greater potential of fluorescent proteins, including biosensors, could be unlocked using a similar strategy.
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Affiliation(s)
- Benjamin C Campbell
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY 10021;
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021
| | - Elisa M Nabel
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Mitchell H Murdock
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021
| | - Cristina Lao-Peregrin
- Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY 10021
| | - Pantelis Tsoulfas
- Department of Biomedical Sciences, Marquette University, Milwaukee, WI 53211
| | - Murray G Blackmore
- Department of Neurological Surgery, Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL 33136
| | - Francis S Lee
- Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY 10021
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, Cornell University, New York, NY 10021
- Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY 10021
| | - Conor Liston
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY 10021
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021
- Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY 10021
- Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, Cornell University, New York, NY 10021
| | - Hirofumi Morishita
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Gregory A Petsko
- Helen and Robert Appel Alzheimer's Disease Research Institute, Weill Cornell Medicine, New York, NY 10021;
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021
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Azevedo EP, Tan B, Pomeranz LE, Ivan V, Fetcho R, Schneeberger M, Doerig KR, Liston C, Friedman JM, Stern SA. A limbic circuit selectively links active escape to food suppression. eLife 2020; 9:58894. [PMID: 32894221 PMCID: PMC7476759 DOI: 10.7554/elife.58894] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 08/19/2020] [Indexed: 02/06/2023] Open
Abstract
Stress has pleiotropic physiologic effects, but the neural circuits linking stress to these responses are not well understood. Here, we describe a novel population of lateral septum neurons expressing neurotensin (LSNts) in mice that are selectively tuned to specific types of stress. LSNts neurons increase their activity during active escape, responding to stress when flight is a viable option, but not when associated with freezing or immobility. Chemogenetic activation of LSNts neurons decreases food intake and body weight, without altering locomotion and anxiety. LSNts neurons co-express several molecules including Glp1r (glucagon-like peptide one receptor) and manipulations of Glp1r signaling in the LS recapitulates the behavioral effects of LSNts activation. Activation of LSNts terminals in the lateral hypothalamus (LH) also decreases food intake. These results show that LSNts neurons are selectively tuned to active escape stress and can reduce food consumption via effects on hypothalamic pathways.
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Affiliation(s)
- Estefania P Azevedo
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Bowen Tan
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Lisa E Pomeranz
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Violet Ivan
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Robert Fetcho
- Department of Psychiatry, Weill Cornell Medical College-New York Presbyterian Hospital, New York, United States
| | - Marc Schneeberger
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Katherine R Doerig
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medical College-New York Presbyterian Hospital, New York, United States
| | - Jeffrey M Friedman
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States.,Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Sarah A Stern
- Laboratory of Molecular Genetics, The Rockefeller University, New York, United States
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Liston C. Estimating Psychiatric Outcomes in First Responders. JAMA Netw Open 2020; 3:e2018678. [PMID: 32990733 DOI: 10.1001/jamanetworkopen.2020.18678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York
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44
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Solomonov N, Victoria LW, Dunlop K, Respino M, Hoptman MJ, Zilcha-Mano S, Oberlin L, Liston C, Areán PA, Gunning FM, Alexopoulos GS. Resting State Functional Connectivity and Outcomes of Psychotherapies for Late-Life Depression. Am J Geriatr Psychiatry 2020; 28:859-868. [PMID: 32376080 PMCID: PMC7369214 DOI: 10.1016/j.jagp.2020.04.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 04/14/2020] [Accepted: 04/14/2020] [Indexed: 02/01/2023]
Abstract
BACKGROUND Problem solving therapy (PST) and "Engage," a reward-exposure" based therapy, are important treatment options for late-life depression, given modest efficacy of antidepressants in this disorder. Abnormal function of the reward and default mode networks has been observed during depressive episodes. This study examined whether resting state functional connectivity (rsFC) of reward and DMN circuitries is associated with treatment outcomes. METHODS Thirty-two older adults with major depression (mean age = 72.7) were randomized to 9-weeks of either PST or "Engage." We assessed rsFC at baseline and week 6. We placed seeds in three a priori regions of interest: subgenual anterior cingulate cortex (sgACC), dorsal anterior cingulate cortex (dACC), and nucleus accumbens (NAcc). Outcome measures included the Hamilton Depression Rating Scale (HAMD) and the Behavioral Activation for Depression Scale (BADS). RESULTS In both PST and "Engage," higher rsFC between the sgACC and middle temporal gyrus at baseline was associated with greater improvement in depression severity (HAMD). Preliminary findings suggested that in "Engage" treated participants, lower rsFC between the dACC and dorsomedial prefrontal cortex at baseline was associated with HAMD improvement. Finally, in Engage only, increased rsFC from baseline to week 6 between NAcc and Superior Parietal Cortex was associated with increased BADS scores. CONCLUSION The results suggest that patients who present with higher rsFC between the sgACC and a structure within the DMN may benefit from behavioral psychotherapies for late life depression. "Engage" may lead to increased rsFC within the reward system reflecting a reconditioning of the reward systems by reward exposure.
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Affiliation(s)
- Nili Solomonov
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine (NS, LWV, LO, FMG, and GSA), White Plains, NY.
| | - Lindsay W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine (NS, LWV, LO, FMG, and GSA), White Plains, NY
| | - Katharine Dunlop
- Feil Family Brain Mind Research Institute, Weill Cornell Medicine (KD and CL), New York, NY
| | | | - Matthew J Hoptman
- The Nathan S. Kline Institute for Psychiatric Research (MJH), Orangeburg, NY; New York University School of Medicine (MJH), New York, NY
| | - Sigal Zilcha-Mano
- Columbia University (SZM), New York, NY; Haifa University (SZM), Haifa, Israel
| | - Lauren Oberlin
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine (NS, LWV, LO, FMG, and GSA), White Plains, NY
| | - Conor Liston
- Feil Family Brain Mind Research Institute, Weill Cornell Medicine (KD and CL), New York, NY
| | - Patricia A Areán
- Department of Psychiatry and Behavioral Sciences (PAA), University of Washington School of Medicine, Seattle, WA
| | - Faith M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine (NS, LWV, LO, FMG, and GSA), White Plains, NY
| | - George S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine (NS, LWV, LO, FMG, and GSA), White Plains, NY
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Lynch CJ, Gunning FM, Liston C. Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes. Biol Psychiatry 2020; 88:83-94. [PMID: 32171465 DOI: 10.1016/j.biopsych.2020.01.012] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 12/13/2019] [Accepted: 01/18/2020] [Indexed: 12/17/2022]
Abstract
Depression is a highly heterogeneous syndrome that bears only modest correlations with its biological substrates, motivating a renewed interest in rethinking our approach to diagnosing depression for research purposes and new efforts to discover subtypes of depression anchored in biology. Here, we review the major causes of diagnostic heterogeneity in depression, with consideration of both clinical symptoms and behaviors (symptomatology and trajectory of depressive episodes) and biology (genetics and sexually dimorphic factors). Next, we discuss the promise of using data-driven strategies to discover novel subtypes of depression based on functional neuroimaging measures, including dimensional, categorical, and hybrid approaches to parsing diagnostic heterogeneity and understanding its biological basis. The merits of using resting-state functional magnetic resonance imaging functional connectivity techniques for subtyping are considered along with a set of technical challenges and potential solutions. We conclude by identifying promising future directions for defining neurobiologically informed depression subtypes and leveraging them in the future for predicting treatment outcomes and informing clinical decision making.
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Affiliation(s)
- Charles J Lynch
- Brain and Mind Research Institute and Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Faith M Gunning
- Brain and Mind Research Institute and Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Conor Liston
- Brain and Mind Research Institute and Department of Psychiatry, Weill Cornell Medicine, New York, New York.
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Abstract
The search for more effective treatments for depression is a long-standing primary objective in both psychiatry and translational neuroscience. From initial models centered on neurochemical deficits, such as the monoamine hypothesis, research toward this goal has shifted toward a focus on network and circuit models to explain how key nodes in the limbic system and beyond interact to produce persistent shifts in affective states. To build these models, researchers have turned to two complementary approaches: neuroimaging studies in human patients (and their healthy counterparts) and neurophysiology studies in animal models, facilitated in large part by optogenetic and chemogenetic techniques. As the authors discuss, functional neuroimaging studies in humans have included largely task-oriented experiments, which have identified brain regions differentially activated during processing of affective stimuli, and resting-state functional MRI experiments, which have identified brain-wide networks altered in depressive states. Future work in this area will build on a multisite approach, assembling large data sets across diverse populations, and will also leverage the statistical power afforded by longitudinal imaging studies in patient samples. Translational studies in rodents have used optogenetic and chemogenetic tools to identify not just nodes but also connections within the networks of the limbic system that are both critical and permissive for the expression of motivated behavior and affective phenotypes. Future studies in this area will exploit mesoscale imaging and multisite electrophysiology recordings to construct network models with cell-type specificity and high statistical power, identifying candidate circuit and molecular pathways for therapeutic intervention.
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Affiliation(s)
- Timothy Spellman
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York
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47
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Linkous A, Balamatsias D, Snuderl M, Edwards L, Miyaguchi K, Milner T, Reich B, Cohen-Gould L, Storaska A, Nakayama Y, Schenkein E, Singhania R, Cirigliano S, Magdeldin T, Lin Y, Nanjangud G, Chadalavada K, Pisapia D, Liston C, Fine HA. Modeling Patient-Derived Glioblastoma with Cerebral Organoids. Cell Rep 2020; 26:3203-3211.e5. [PMID: 30893594 DOI: 10.1016/j.celrep.2019.02.063] [Citation(s) in RCA: 238] [Impact Index Per Article: 59.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 11/14/2018] [Accepted: 02/15/2019] [Indexed: 12/11/2022] Open
Abstract
The prognosis of patients with glioblastoma (GBM) remains dismal, with a median survival of approximately 15 months. Current preclinical GBM models are limited by the lack of a "normal" human microenvironment and the inability of many tumor cell lines to accurately reproduce GBM biology. To address these limitations, we have established a model system whereby we can retro-engineer patient-specific GBMs using patient-derived glioma stem cells (GSCs) and human embryonic stem cell (hESC)-derived cerebral organoids. Our cerebral organoid glioma (GLICO) model shows that GSCs home toward the human cerebral organoid and deeply invade and proliferate within the host tissue, forming tumors that closely phenocopy patient GBMs. Furthermore, cerebral organoid tumors form rapidly and are supported by an interconnected network of tumor microtubes that aids in the invasion of normal host tissue. Our GLICO model provides a system for modeling primary human GBM ex vivo and for high-throughput drug screening.
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Affiliation(s)
- Amanda Linkous
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | | | - Matija Snuderl
- Division of Neuropathology, Department of Pathology, NYU Langone Medical Center and Medical School, New York, NY, USA
| | - Lincoln Edwards
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Ken Miyaguchi
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Teresa Milner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Batsheva Reich
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Leona Cohen-Gould
- Department of Biochemistry, Weill Cornell Medicine, New York, NY, USA
| | - Andrew Storaska
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Yasumi Nakayama
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Emily Schenkein
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Richa Singhania
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | | | - Tarig Magdeldin
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Ying Lin
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Gouri Nanjangud
- Memorial Sloan Kettering Cancer Center Molecular Cytogenetics Core, New York, NY, USA
| | - Kalyani Chadalavada
- Memorial Sloan Kettering Cancer Center Molecular Cytogenetics Core, New York, NY, USA
| | - David Pisapia
- Department of Pathology & Laboratory Medicine, NewYork-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Howard A Fine
- Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, NewYork-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA.
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Gutzeit VA, Ruiz AA, Kristt M, Liston C, Broichhagen J, Levitz J. Branched Photoswitchable Tethered Ligands for Optical Interrogation of Metabotropic Glutamate Receptor‐Mediated Modulation of Prefrontal Cortex Circuits. FASEB J 2020. [DOI: 10.1096/fasebj.2020.34.s1.05430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Abstract
In this issue of Neuron, Greene et al. (2020) identify zones of network specificity and multi-network integration in the basal ganglia and thalamus of individual human subjects. Such information could aid in the development of personalized and more effective brain stimulation therapies for neuropsychiatric disorders.
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Affiliation(s)
- Charles J Lynch
- Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69(th) Street, Box 204, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, 413 East 69(th) Street, Box 204, New York, NY 10021, USA
| | - Conor Liston
- Brain and Mind Research Institute, Weill Cornell Medicine, 413 East 69(th) Street, Box 204, New York, NY 10021, USA; Department of Psychiatry, Weill Cornell Medicine, 413 East 69(th) Street, Box 204, New York, NY 10021, USA.
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50
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Respino M, Hoptman MJ, Victoria LW, Alexopoulos GS, Solomonov N, Stein AT, Coluccio M, Morimoto SS, Blau CJ, Abreu L, Burdick KE, Liston C, Gunning FM. Cognitive Control Network Homogeneity and Executive Functions in Late-Life Depression. Biol Psychiatry Cogn Neurosci Neuroimaging 2020; 5:213-221. [PMID: 31901436 PMCID: PMC7010539 DOI: 10.1016/j.bpsc.2019.10.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 10/09/2019] [Accepted: 10/26/2019] [Indexed: 12/16/2022]
Abstract
BACKGROUND Late-life depression is characterized by network abnormalities, especially within the cognitive control network. We used alternative functional connectivity approaches, regional homogeneity (ReHo) and network homogeneity, to investigate late-life depression functional homogeneity. We examined the association between cognitive control network homogeneity and executive functions. METHODS Resting-state functional magnetic resonance imaging data were analyzed for 33 older adults with depression and 43 healthy control subjects. ReHo was performed as the correlation between each voxel and the 27 neighbor voxels. Network homogeneity was calculated as global brain connectivity restricted to 7 networks. T-maps were generated for group comparisons. We measured cognitive performance and executive functions with the Dementia Rating Scale, Trail-Making Test (A and B), Stroop Color Word Test, and Digit Span Test. RESULTS Older adults with depression showed increased ReHo in the bilateral dorsal anterior cingulate cortex (dACC) and the right middle temporal gyrus, with no significant findings for network homogeneity. Hierarchical linear regression models showed that higher ReHo in the dACC predicted better performance on Trail-Making Test B (p < .001; R2 = .49), Digit Span Backward (p < .05; R2 = .23), and Digit Span Total (p < .05; R2 = .23). Used as a seed, the dACC cluster of higher ReHo showed lower functional connectivity with bilateral precuneus. CONCLUSIONS Higher ReHo within the dACC and right middle temporal gyrus distinguish older adults with depression from control subjects. The correlations with executive function performance support increased ReHo in the dACC as a meaningful measure of the organization of the cognitive control network and a potential compensatory mechanism. Lower functional connectivity between the dACC and the precuneus in late-life depression suggests that clusters of increased ReHo may be functionally segregated.
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Affiliation(s)
- Matteo Respino
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Matthew J Hoptman
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York
| | - Lindsay W Victoria
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - George S Alexopoulos
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Nili Solomonov
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Aliza T Stein
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Maria Coluccio
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Sarah Shizuko Morimoto
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Chloe J Blau
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York
| | - Lila Abreu
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Katherine E Burdick
- Department of Psychiatry, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Conor Liston
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York
| | - Faith M Gunning
- Department of Psychiatry, Joan & Sanford I. Weill Medical College of Cornell University, New York.
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