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Patterson Gentile C, Spitschan M, Taskin HO, Bock AS, Aguirre GK. Temporal Sensitivity for Achromatic and Chromatic Flicker across the Visual Cortex. J Neurosci 2024; 44:e1395232024. [PMID: 38621997 PMCID: PMC11112647 DOI: 10.1523/jneurosci.1395-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 04/17/2024] Open
Abstract
The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic postreceptoral channels. The goal of the current study was to determine temporal sensitivity across the three postreceptoral channels in subcortical and cortical regions involved in human vision. We measured functional magnetic resonance imaging (fMRI) responses at 7 T from three participants (two males, one female) viewing a high-contrast, flickering, spatially uniform wide field (∼140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L + M + S, L - M, and S - (L + M) cone combinations. These measurements were used to create temporal sensitivity functions of the primary visual cortex (V1) across eccentricity and spatially averaged responses from the lateral geniculate nucleus (LGN), and the V2/V3, hV4, and V3A/B regions. fMRI responses reflected the known properties of the visual system, including higher peak temporal sensitivity to achromatic versus chromatic stimuli and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. The comparison of measured cortical responses to a model of the integrated retinal output to our stimuli demonstrates that extensive filtering and amplification are applied to postretinal signals.
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Affiliation(s)
- Carlyn Patterson Gentile
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Neurology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104
| | - Manuel Spitschan
- Translational Sensory & Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany
- Chronobiology & Health, TUM School of Medicine and Health (TUM MH), Technical University of Munich, Munich 80992, Germany
| | - Huseyin O Taskin
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Andrew S Bock
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Geoffrey K Aguirre
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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2
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Graves AJ, Danoff JS, Kim M, Brindley SR, Skyberg AM, Giamberardino SN, Lynch ME, Straka BC, Lillard TS, Gregory SG, Connelly JJ, Morris JP. Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults. Sci Rep 2024; 14:9646. [PMID: 38671048 PMCID: PMC11053089 DOI: 10.1038/s41598-024-60311-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 04/21/2024] [Indexed: 04/28/2024] Open
Abstract
While chronological age is a strong predictor for health-related risk factors, it is an incomplete metric that fails to fully characterize the unique aging process of individuals with different genetic makeup, neurodevelopment, and environmental experiences. Recent advances in epigenomic array technologies have made it possible to generate DNA methylation-based biomarkers of biological aging, which may be useful in predicting a myriad of cognitive abilities and functional brain network organization across older individuals. It is currently unclear which cognitive domains are negatively correlated with epigenetic age above and beyond chronological age, and it is unknown if functional brain organization is an important mechanism for explaining these associations. In this study, individuals with accelerated epigenetic age (i.e. AgeAccelGrim) performed worse on tasks that spanned a wide variety of cognitive faculties including both fluid and crystallized intelligence (N = 103, average age = 68.98 years, 73 females, 30 males). Additionally, fMRI connectome-based predictive models suggested a mediating mechanism of functional connectivity on epigenetic age acceleration-cognition associations primarily in medial temporal lobe and limbic structures. This research highlights the important role of epigenetic aging processes on the development and maintenance of healthy cognitive capacities and function of the aging brain.
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Affiliation(s)
| | | | - Minah Kim
- University of Virginia, Charlottesville, USA
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3
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Wiersch L, Friedrich P, Hamdan S, Komeyer V, Hoffstaedter F, Patil KR, Eickhoff SB, Weis S. Sex classification from functional brain connectivity: Generalization to multiple datasets. Hum Brain Mapp 2024; 45:e26683. [PMID: 38647035 PMCID: PMC11034006 DOI: 10.1002/hbm.26683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 03/19/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
Machine learning (ML) approaches are increasingly being applied to neuroimaging data. Studies in neuroscience typically have to rely on a limited set of training data which may impair the generalizability of ML models. However, it is still unclear which kind of training sample is best suited to optimize generalization performance. In the present study, we systematically investigated the generalization performance of sex classification models trained on the parcelwise connectivity profile of either single samples or compound samples of two different sizes. Generalization performance was quantified in terms of mean across-sample classification accuracy and spatial consistency of accurately classifying parcels. Our results indicate that the generalization performance of parcelwise classifiers (pwCs) trained on single dataset samples is dependent on the specific test samples. Certain datasets seem to "match" in the sense that classifiers trained on a sample from one dataset achieved a high accuracy when tested on the respected other one and vice versa. The pwCs trained on the compound samples demonstrated overall highest generalization performance for all test samples, including one derived from a dataset not included in building the training samples. Thus, our results indicate that both a large sample size and a heterogeneous data composition of a training sample have a central role in achieving generalizable results.
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Affiliation(s)
- Lisa Wiersch
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Patrick Friedrich
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Sami Hamdan
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Vera Komeyer
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
- Department of Biology, Faculty of Mathematics and Natural SciencesHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Felix Hoffstaedter
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Kaustubh R. Patil
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Simon B. Eickhoff
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Susanne Weis
- Institute of Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
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4
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Rosmarin DH, Kumar P, Kaufman CC, Drury M, Harper D, Forester BP. Neurobiological correlates of religious coping among older adults with and without mood disorders: An exploratory study. Psychiatry Res Neuroimaging 2024; 341:111812. [PMID: 38631136 DOI: 10.1016/j.pscychresns.2024.111812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/14/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024]
Abstract
In this study, 32 older adults with and without mood disorders completed resting-state functional Magnetic Resonance Imaging and measures of demographics, spirituality/religion, positive and negative religious coping, and depression. Group Independent Component Analysis identified and selected three a priori resting state networks [cingulo-opercular salience (cSN), central executive (CEN) and Default Mode Networks (DMN)] within the Triple Network Mode. We investigated associations of religious coping with within- and between-network connectivity, controlling for age. Insular connectivity within the cSN was associated with negative religious coping. Religious coping was associated with anti-correlation between the DMN and CEN even when controlling for depression.
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Affiliation(s)
- David H Rosmarin
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States.
| | - Poornima Kumar
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Laboratory for Translational and Affective Neuroscience, McLean Hospital, Belmont, MA, United States
| | - Caroline C Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States
| | - Mia Drury
- Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States
| | - David Harper
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Geriatric Psychiatry Research Program, McLean Hospital, Belmont, MA, United States
| | - Brent P Forester
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Geriatric Psychiatry Research Program, McLean Hospital, Belmont, MA, United States; Tufts Medical Center, Tufts University School of Medicine, United States
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Wiersch L, Friedrich P, Hamdan S, Komeyer V, Hoffstaedter F, Patil KR, Eickhoff SB, Weis S. Sex classification from functional brain connectivity: Generalization to multiple datasets Generalizability of sex classifiers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.30.555495. [PMID: 37693374 PMCID: PMC10491190 DOI: 10.1101/2023.08.30.555495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Machine learning (ML) approaches are increasingly being applied to neuroimaging data. Studies in neuroscience typically have to rely on a limited set of training data which may impair the generalizability of ML models. However, it is still unclear which kind of training sample is best suited to optimize generalization performance. In the present study, we systematically investigated the generalization performance of sex classification models trained on the parcelwise connectivity profile of either single samples or a compound sample containing data from four different datasets. Generalization performance was quantified in terms of mean across-sample classification accuracy and spatial consistency of accurately classifying parcels. Our results indicate that generalization performance of pwCs trained on single dataset samples is dependent on the specific test samples. Certain datasets seem to "match" in the sense that classifiers trained on a sample from one dataset achieved a high accuracy when tested on the respected other one and vice versa. The pwC trained on the compound sample demonstrated overall highest generalization performance for all test samples, including one derived from a dataset not included in building the training samples. Thus, our results indicate that a big and heterogenous training sample comprising data of multiple datasets is best suited to achieve generalizable results.
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Affiliation(s)
- Lisa Wiersch
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Patrick Friedrich
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Sami Hamdan
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Vera Komeyer
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Department of Biology, Faculty of Mathematics and Natural Sciences, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Susanne Weis
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
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Boecker H, Daamen M, Maurer A, Bodensohn L, Werkhausen J, Lohaus M, Manunzio C, Manunzio U, Radbruch A, Attenberger U, Dukart J, Upadhyay N. Fractional amplitude of low-frequency fluctuations associated with μ-opioid and dopamine receptor distributions in the central nervous system after high-intensity exercise bouts. FRONTIERS IN NEUROIMAGING 2024; 3:1332384. [PMID: 38455686 PMCID: PMC10917966 DOI: 10.3389/fnimg.2024.1332384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 01/29/2024] [Indexed: 03/09/2024]
Abstract
Introduction Dopaminergic, opiod and endocannabinoid neurotransmission are thought to play an important role in the neurobiology of acute exercise and, in particular, in mediating positive affective responses and reward processes. Recent evidence indicates that changes in fractional amplitude of low-frequency fluctuations (zfALFF) in resting-state functional MRI (rs-fMRI) may reflect changes in specific neurotransmitter systems as tested by means of spatial correlation analyses. Methods Here, we investigated this relationship at different exercise intensities in twenty young healthy trained athletes performing low-intensity (LIIE), high-intensity (HIIE) interval exercises, and a control condition on three separate days. Positive And Negative Affect Schedule (PANAS) scores and rs-fMRI were acquired before and after each of the three experimental conditions. Respective zfALFF changes were analyzed using repeated measures ANOVAs. We examined the spatial correspondence of changes in zfALFF before and after training with the available neurotransmitter maps across all voxels and additionally, hypothesis-driven, for neurotransmitter maps implicated in the neurobiology of exercise (dopaminergic, opiodic and endocannabinoid) in specific brain networks associated with "reward" and "emotion." Results Elevated PANAS Positive Affect was observed after LIIE and HIIE but not after the control condition. HIIE compared to the control condition resulted in differential zfALFF decreases in precuneus, temporo-occipital, midcingulate and frontal regions, thalamus, and cerebellum, whereas differential zfALFF increases were identified in hypothalamus, pituitary, and periaqueductal gray. The spatial alteration patterns in zfALFF during HIIE were positively associated with dopaminergic and μ-opioidergic receptor distributions within the 'reward' network. Discussion These findings provide new insight into the neurobiology of exercise supporting the importance of reward-related neurotransmission at least during high-intensity physical activity.
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Affiliation(s)
- Henning Boecker
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Marcel Daamen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
- Clinical Research, German Center for Neurodegenerative Diseases (DZNE) Bonn, Bonn, Germany
| | - Angelika Maurer
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Luisa Bodensohn
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Judith Werkhausen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Marvin Lohaus
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Christian Manunzio
- Sportsmedicine, Department of Paediatric Cardiology, University Hospital Bonn, Bonn, Germany
| | - Ursula Manunzio
- Sportsmedicine, Department of Paediatric Cardiology, University Hospital Bonn, Bonn, Germany
| | | | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Neeraj Upadhyay
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
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7
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Gentile CP, Spitschan M, Taskin HO, Bock AS, Aguirre GK. Temporal sensitivity for achromatic and chromatic flicker across the visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.24.550403. [PMID: 37546951 PMCID: PMC10402088 DOI: 10.1101/2023.07.24.550403] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic post-receptoral channels. Beyond the retina, RGC outputs are subject to filtering and normalization along the geniculo-striate pathway, ultimately producing the properties of human vision. The goal of the current study was to determine temporal sensitivity across the three post-receptoral channels in subcortical and cortical regions involved in vision. We measured functional magnetic resonance imaging (MRI) responses at 7 Tesla from three participants (two males, one female) viewing a high-contrast, flickering, spatially-uniform wide field (~140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L+M+S, L-M, and S-[L+M] cone combinations. These measurements were used to create temporal sensitivity functions of primary visual cortex (V1) across eccentricity, and spatially averaged responses from lateral geniculate nucleus (LGN), V2/V3, hV4, and V3A/B. Functional MRI responses reflected known properties of the visual system, including higher peak temporal sensitivity to achromatic vs. chromatic stimuli, and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. Comparison of measured cortical responses to a model of integrated retinal output to our stimuli demonstrates that extensive filtering and amplification is applied to post-retinal signals.
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Affiliation(s)
- Carlyn Patterson Gentile
- University of Pennsylvania, Department of Neurology
- Children's Hospital of Philadelphia, Department of Neurology
| | - Manuel Spitschan
- Translational Sensory & Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Chronobiology & Health, TUM Department of Sport and Health Sciences (TUM SG), Technical University of Munich, Munich, Germany
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8
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Jirsaraie RJ, Palma AM, Small SL, Sandman CA, Davis EP, Baram TZ, Stern H, Glynn LM, Yassa MA. Prenatal Exposure to Maternal Mood Entropy Is Associated With a Weakened and Inflexible Salience Network in Adolescence. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:207-216. [PMID: 37611745 PMCID: PMC10881896 DOI: 10.1016/j.bpsc.2023.08.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Fetal exposure to maternal mood dysregulation influences child cognitive and emotional development, which may have long-lasting implications for mental health. However, the neurobiological alterations associated with this dimension of adversity have yet to be explored. Here, we tested the hypothesis that fetal exposure to entropy, a novel index of dysregulated maternal mood, would predict the integrity of the salience network, which is involved in emotional processing. METHODS A sample of 138 child-mother pairs (70 females) participated in this prospective longitudinal study. Maternal negative mood level and entropy (an index of variable and unpredictable mood) were assessed 5 times during pregnancy. Adolescents engaged in a functional magnetic resonance imaging task that was acquired between 2 resting-state scans. Changes in network integrity were analyzed using mixed-effect and latent growth curve models. The amplitude of low frequency fluctuations was analyzed to corroborate findings. RESULTS Prenatal maternal mood entropy, but not mood level, was associated with salience network integrity. Both prenatal negative mood level and entropy were associated with the amplitude of low frequency fluctuations of the salience network. Latent class analysis yielded 2 profiles based on changes in network integrity across all functional magnetic resonance imaging sequences. The profile that exhibited little variation in network connectivity (i.e., inflexibility) consisted of adolescents who were exposed to higher negative maternal mood levels and more entropy. CONCLUSIONS These findings suggest that fetal exposure to maternal mood dysregulation is associated with a weakened and inflexible salience network. More broadly, they identify maternal mood entropy as a novel marker of early adversity that exhibits long-lasting associations with offspring brain development.
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Affiliation(s)
- Robert J Jirsaraie
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, California; Department of Neurobiology and Behavior, University of California, Irvine, Irvine, California
| | - Anton M Palma
- Department of Statistics, University of California, Irvine, Irvine, California
| | - Steven L Small
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas
| | - Curt A Sandman
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, California
| | - Elysia Poggi Davis
- Department of Psychology, University of Denver, Denver, Colorado; Department of Pediatrics, University of California, Irvine, Irvine, California
| | - Tallie Z Baram
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, California; Department of Pediatrics, University of California, Irvine, Irvine, California; Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, California
| | - Hal Stern
- Department of Statistics, University of California, Irvine, Irvine, California
| | - Laura M Glynn
- Department of Psychology, Chapman University, Orange, California.
| | - Michael A Yassa
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, California; Department of Neurobiology and Behavior, University of California, Irvine, Irvine, California; Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, California; Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, California.
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Mandino F, Shen X, Desrosiers-Gregoire G, O'Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty MM, Strittmatter SM, Lake EM. Aging-Dependent Loss of Connectivity in Alzheimer's Model Mice with Rescue by mGluR5 Modulator. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.15.571715. [PMID: 38260465 PMCID: PMC10802481 DOI: 10.1101/2023.12.15.571715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD ( App NL-G-F /hMapt ), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.
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10
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O'Connor D, Markicevic M, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair MC, Constable RT, Lake EMR, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. Nat Commun 2024; 15:229. [PMID: 38172111 PMCID: PMC10764905 DOI: 10.1038/s41467-023-44363-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.
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Affiliation(s)
- Hadi Vafaii
- Department of Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Marija Markicevic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xinxin Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Section of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Mallar Chakravarty
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA.
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA.
- Maryland Neuroimaging Center, University of Maryland, College Park, MD, 20742, USA.
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11
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Li X, Naveed Iqbal Qureshi M, Laplante DP, Elgbeili G, Paquin V, Lee Jones S, King S, Rosa-Neto P. Decreased amygdala-sensorimotor connectivity mediates the association between prenatal stress and broad autism phenotype in young adults: Project Ice Storm. Stress 2024; 27:2293698. [PMID: 38131654 DOI: 10.1080/10253890.2023.2293698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Studies show that prenatal maternal stress (PNMS) is related to risk for child autism, and to atypical amygdala functional connectivity in the autistic child. Yet, it remains unclear whether amygdala functional connectivity mediates the association between PNMS and autistic traits, particularly in young adult offspring. We recruited women who were pregnant during, or within 3 months of, the 1998 Quebec ice storm crisis, and assessed three aspects of PNMS: objective hardship (events experienced during the ice storm), subjective distress (post-traumatic stress symptoms experienced as a result of the ice storm) and cognitive appraisal. At age 19, 32 young adults (21 females) self-reported their autistic-like traits (i.e., aloof personality, pragmatic language impairment and rigid personality), and underwent structural MRI and resting-state functional MRI scans. Seed-to-voxel analyses were conducted to map the amygdala functional connectivity network. Mediation analyses were implemented with bootstrapping of 20,000 resamplings. We found that greater maternal objective hardship was associated with weaker functional connectivity between the left amygdala and the right postcentral gyrus, which was then associated with more pragmatic language impairment. Greater maternal subjective distress was associated with weaker functional connectivity between the right amygdala and the left precentral gyrus, which was then associated with more aloof personality. Our results demonstrate that the long-lasting effect of PNMS on offspring autistic-like traits may be mediated by decreased amygdala-sensorimotor circuits. The differences between amygdala-sensory and amygdala-motor pathways mediating different aspects of PNMS on different autism phenotypes need to be studied further.
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Affiliation(s)
- Xinyuan Li
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Canada
| | - David P Laplante
- Centre for Child Development and Mental Health, Lady Davis Institute-Jewish General Hospital, Montreal, Canada
| | | | - Vincent Paquin
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Sherri Lee Jones
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Suzanne King
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Pedro Rosa-Neto
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
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12
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Li X, Qureshi MNI, Laplante DP, Elgbeili G, Jones SL, Long X, Paquin V, Bezgin G, Lussier F, King S, Rosa-Neto P. Atypical brain structure and function in young adults exposed to disaster-related prenatal maternal stress: Project Ice Storm. J Neurosci Res 2023; 101:1849-1863. [PMID: 37732456 DOI: 10.1002/jnr.25246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 08/29/2023] [Accepted: 09/04/2023] [Indexed: 09/22/2023]
Abstract
Studies have shown that prenatal maternal stress (PNMS) affects brain structure and function in childhood. However, less research has examined whether PNMS effects on brain structure and function extend to young adulthood. We recruited women who were pregnant during or within 3 months following the 1998 Quebec ice storm, assessed their PNMS, and prospectively followed-up their children. T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI were obtained from 19-year-old young adults with (n = 39) and without (n = 65) prenatal exposure to the ice storm. We examined between-group differences in gray matter volume (GMV), surface area (SA), and cortical thickness (CT). We used the brain regions showing between-group GMV differences as seeds to compare between-group functional connectivity. Within the Ice Storm group, we examined (1) associations between PNMS and the atypical GMV, SA, CT, and functional connectivity, and (2) moderation by timing of exposure. Primarily, we found that, compared to Controls, the Ice Storm youth had larger GMV and higher functional connectivity of the anterior cingulate cortex, the precuneus, the left occipital pole, and the right hippocampus; they also had larger CT, but not SA, of the left occipital pole. Within the Ice Storm group, maternal subjective distress during preconception and mid-to-late pregnancy was associated with atypical left occipital pole CT. These results suggest the long-lasting impact of disaster-related PNMS on child brain structure and functional connectivity. Our study also indicates timing-specific effects of the subjective aspect of PNMS on occipital thickness.
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Affiliation(s)
- Xinyuan Li
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
| | - David P Laplante
- Centre for Child Development and Mental Health, Lady Davis Institute-Jewish General Hospital, Montreal, Quebec, Canada
| | | | - Sherri Lee Jones
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Xiangyu Long
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Vincent Paquin
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Gleb Bezgin
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Firoza Lussier
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Suzanne King
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Pedro Rosa-Neto
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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13
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Cai Z, von Ellenrieder N, Koupparis A, Khoo HM, Ikemoto S, Tanaka M, Abdallah C, Rammal S, Dubeau F, Gotman J. Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling. Hum Brain Mapp 2023; 44:5982-6000. [PMID: 37750611 PMCID: PMC10619415 DOI: 10.1002/hbm.26490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/16/2023] [Accepted: 09/07/2023] [Indexed: 09/27/2023] Open
Abstract
Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null-hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty-two epilepsy patients who underwent EEG-fMRI and subsequent surgery were included in this study. A conventional voxel-wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel-wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long-lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel-wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG-fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies.
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Affiliation(s)
- Zhengchen Cai
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
| | | | | | - Hui Ming Khoo
- Department of NeurosurgeryOsaka University Graduate School of MedicineSuitaJapan
| | - Satoru Ikemoto
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
| | - Masataka Tanaka
- Department of NeurosurgeryYao Municipal HospitalYao‐cityOsakaJapan
| | - Chifaou Abdallah
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
| | - Saba Rammal
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
| | - Francois Dubeau
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
| | - Jean Gotman
- The Neuro (Montreal Neurological Institute‐Hospital)McGill UniversityMontrealQuebecCanada
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14
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Tanguay AFN, Palombo DJ, Love B, Glikstein R, Davidson PSR, Renoult L. The shared and unique neural correlates of personal semantic, general semantic, and episodic memory. eLife 2023; 12:e83645. [PMID: 37987578 PMCID: PMC10662951 DOI: 10.7554/elife.83645] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/25/2023] [Indexed: 11/22/2023] Open
Abstract
One of the most common distinctions in long-term memory is that between semantic (i.e., general world knowledge) and episodic (i.e., recollection of contextually specific events from one's past). However, emerging cognitive neuroscience data suggest a surprisingly large overlap between the neural correlates of semantic and episodic memory. Moreover, personal semantic memories (i.e., knowledge about the self and one's life) have been studied little and do not easily fit into the standard semantic-episodic dichotomy. Here, we used fMRI to record brain activity while 48 participants verified statements concerning general facts, autobiographical facts, repeated events, and unique events. In multivariate analysis, all four types of memory involved activity within a common network bilaterally (e.g., frontal pole, paracingulate gyrus, medial frontal cortex, middle/superior temporal gyrus, precuneus, posterior cingulate, angular gyrus) and some areas of the medial temporal lobe. Yet the four memory types differentially engaged this network, increasing in activity from general to autobiographical facts, from autobiographical facts to repeated events, and from repeated to unique events. Our data are compatible with a component process model, in which declarative memory types rely on different weightings of the same elementary processes, such as perceptual imagery, spatial features, and self-reflection.
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Affiliation(s)
- Annick FN Tanguay
- School of Psychology, University of OttawaOttawaCanada
- School of Psychology, University of East AngliaNorwichUnited Kingdom
| | - Daniela J Palombo
- Department of Psychology, University of British ColumbiaVancouverCanada
| | - Brittany Love
- School of Psychology, University of OttawaOttawaCanada
| | | | | | - Louis Renoult
- School of Psychology, University of East AngliaNorwichUnited Kingdom
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15
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Yu T, Cai LY, Torrisi S, Vu AT, Morgan VL, Goodale SE, Ramadass K, Meisler SL, Lv J, Warren AEL, Englot DJ, Cutting L, Chang C, Gore JC, Landman BA, Schilling KG. Distortion correction of functional MRI without reverse phase encoding scans or field maps. Magn Reson Imaging 2023; 103:18-27. [PMID: 37400042 PMCID: PMC10528451 DOI: 10.1016/j.mri.2023.06.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/27/2023] [Accepted: 06/28/2023] [Indexed: 07/05/2023]
Abstract
Functional magnetic resonance images (fMRI) acquired using echo planar sequences typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may cause geometric mismatch with structural images and affect subsequent quantification and localization of brain function. State-of-the art distortion correction methods (for example, using FSL's topup or AFNI's 3dQwarp algorithms) require the collection of additional scans - either field maps or images with reverse phase encoding directions (i.e., blip-up/blip-down acquisitions) - to estimate and correct distortions. However, not all imaging protocols acquire these additional data and thus cannot take advantage of these post-acquisition corrections. In this study, we aim to enable state-of-the art processing of historical or limited datasets that do not include specific sequences for distortion correction by using only the acquired functional data and a single commonly acquired structural image. To achieve this, we synthesize an undistorted image with contrast similar to the fMRI data and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach, named SynBOLD-DisCo (Synthetic BOLD contrast for Distortion Correction), and show that this distortion correction process yields fMRI data that are geometrically similar to non-distorted structural images, with distortion correction virtually equivalent to acquisitions that do contain both blip-up/blip-down images. Our method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation and integration into existing fMRI preprocessing pipelines.
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Affiliation(s)
- Tian Yu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Salvatore Torrisi
- San Francisco VA Health Care System, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - An Thanh Vu
- San Francisco VA Health Care System, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah E Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Steven L Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA, USA
| | - Jinglei Lv
- School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia; Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Aaron E L Warren
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Laurie Cutting
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Special Education, Vanderbilt University, Nashville, TN, USA; Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Catie Chang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
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16
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Dickie EW, Shahab S, Hawco C, Miranda D, Herman G, Argyelan M, Ji JL, Jeyachandra J, Anticevic A, Malhotra AK, Voineskos AN. Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography. Hum Brain Mapp 2023; 44:5153-5166. [PMID: 37605827 PMCID: PMC10502662 DOI: 10.1002/hbm.26453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 07/05/2023] [Accepted: 08/01/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles. METHODS We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT). RESULTS The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected). CONCLUSION Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.
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Affiliation(s)
- Erin W. Dickie
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
| | - Saba Shahab
- Department of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Colin Hawco
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
| | - Dayton Miranda
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Gabrielle Herman
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Miklos Argyelan
- Psychiatry Research, The Zucker Hillside HospitalGlen CoveNew YorkUSA
- Institute of Behavioral Science, Feinstein Institutes for Medical ResearchManhassetNew YorkUSA
- Donald and Barbara Zucker School of Medicine at Hofstra/NorthwellHempsteadNew YorkUSA
| | - Jie Lisa Ji
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
| | - Jerrold Jeyachandra
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Alan Anticevic
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
| | - Anil K. Malhotra
- Psychiatry Research, The Zucker Hillside HospitalGlen CoveNew YorkUSA
- Institute of Behavioral Science, Feinstein Institutes for Medical ResearchManhassetNew YorkUSA
- Donald and Barbara Zucker School of Medicine at Hofstra/NorthwellHempsteadNew YorkUSA
| | - Aristotle N. Voineskos
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
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17
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Cascone AD, Calabro F, Foran W, Larsen B, Nugiel T, Parr AC, Tervo-Clemmens B, Luna B, Cohen JR. Brain tissue iron neurophysiology and its relationship with the cognitive effects of dopaminergic modulation in children with and without ADHD. Dev Cogn Neurosci 2023; 63:101274. [PMID: 37453207 PMCID: PMC10372187 DOI: 10.1016/j.dcn.2023.101274] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/03/2023] [Accepted: 07/06/2023] [Indexed: 07/18/2023] Open
Abstract
Children with attention-deficit/hyperactivity disorder (ADHD) exhibit impairments in response inhibition. These impairments are ameliorated by modulating dopamine (DA) via the administration of rewards or stimulant medication like methylphenidate (MPH). It is currently unclear whether intrinsic DA availability impacts these effects of dopaminergic modulation on response inhibition. Thus, we estimated intrinsic DA availability using magnetic resonance-based assessments of basal ganglia and thalamic tissue iron in 36 medication-naïve children with ADHD and 29 typically developing (TD) children (8-12 y) who underwent fMRI scans and completed standard and rewarded go/no-go tasks. Children with ADHD additionally participated in a double-blind, randomized, placebo-controlled, crossover MPH challenge. Using linear regressions covarying for age and sex, we determined there were no group differences in brain tissue iron. We additionally found that higher putamen tissue iron was associated with worse response inhibition performance in all participants. Crucially, we observed that higher putamen and caudate tissue iron was associated with greater responsivity to MPH, as measured by improved task performance, in participants with ADHD. These results begin to clarify the role of subcortical brain tissue iron, a measure associated with intrinsic DA availability, in the cognitive effects of reward- and MPH-related dopaminergic modulation in children with ADHD and TD children.
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Affiliation(s)
- Arianna D Cascone
- Neuroscience Curriculum, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Finnegan Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bart Larsen
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tehila Nugiel
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brenden Tervo-Clemmens
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jessica R Cohen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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18
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Fotiadis P, Cieslak M, He X, Caciagli L, Ouellet M, Satterthwaite TD, Shinohara RT, Bassett DS. Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex. Nat Commun 2023; 14:6115. [PMID: 37777569 PMCID: PMC10542365 DOI: 10.1038/s41467-023-41686-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 09/08/2023] [Indexed: 10/02/2023] Open
Abstract
Recent work has demonstrated that the relationship between structural and functional connectivity varies regionally across the human brain, with reduced coupling emerging along the sensory-association cortical hierarchy. The biological underpinnings driving this expression, however, remain largely unknown. Here, we postulate that intracortical myelination and excitation-inhibition (EI) balance mediate the heterogeneous expression of structure-function coupling (SFC) and its temporal variance across the cortical hierarchy. We employ atlas- and voxel-based connectivity approaches to analyze neuroimaging data acquired from two groups of healthy participants. Our findings are consistent across six complementary processing pipelines: 1) SFC and its temporal variance respectively decrease and increase across the unimodal-transmodal and granular-agranular gradients; 2) increased myelination and lower EI-ratio are associated with more rigid SFC and restricted moment-to-moment SFC fluctuations; 3) a gradual shift from EI-ratio to myelination as the principal predictor of SFC occurs when traversing from granular to agranular cortical regions. Collectively, our work delivers a framework to conceptualize structure-function relationships in the human brain, paving the way for an improved understanding of how demyelination and/or EI-imbalances induce reorganization in brain disorders.
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Affiliation(s)
- Panagiotis Fotiadis
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Matthew Cieslak
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xiaosong He
- Department of Psychology, University of Science and Technology of China, Hefei, Anhui, 230026, China
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mathieu Ouellet
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Physics & Astronomy, 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.
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19
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Lee SM, Kim S, Jeong JH, Hong CH, Park YK, Na HR, Song HS, Park HK, Choi M, Chun BO, Choi SH, Lee JM, Moon SY. Impact of a multidomain lifestyle intervention on white matter integrity: the SUPERBRAIN exploratory sub-study. Front Aging Neurosci 2023; 15:1242295. [PMID: 37799622 PMCID: PMC10548201 DOI: 10.3389/fnagi.2023.1242295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/31/2023] [Indexed: 10/07/2023] Open
Abstract
In the South Korean study to prevent cognitive impairment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN), we evaluated the impact of a 24-week facility-based multidomain intervention (FMI) and home-based MI (HMI) on white matter integrity. Among 152 participants, aged 60-79 years without dementia but with ≥1 modifiable dementia risk factor, 19 FMI, 20 HMI, and 16 controls underwent brain MRI at baseline and 24 weeks. Between the intervention and control groups, we compared changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) at regions-of-interest (ROI) including the cingulum cingulate gyrus (CgC), cingulum hippocampus (CgH), superior longitudinal fasciculus (SLF), as well as the uncinate fasciculus (UF). In addition, correlations between total and standard scores cognitive domains of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or serum brain-derived neurotrophic factor (BDNF) and changes in brain image measures were evaluated at a statistical significance level of p < 0.05 (uncorrected for multiple corrections). The FA, MD, AD, and RD at each ROI at the baseline were not different among groups after Bonferroni correction. In the statistical analysis using two-way repeated measures ANOVA, any significant difference in longitudinal changes in the FA, MD, AD, and RD was not revealed. The statistical analysis, among the significant regions in paired t-test of the intervention group, compared with the control group, the FMI, HMI, and intervention group yielded significantly more beneficial effects on the AD of the CgC. In addition, longitudinal AD changes of the left CgC correlated with the BDNF changes (r = 0.280, p = 0.048). In this study, enhanced cognitive reserve after the multidomain lifestyle intervention could be revealed by changes in brain imaging for white matter integrity.
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Affiliation(s)
- Sun Min Lee
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Sohui Kim
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University School of Medicine, Seoul, Republic of Korea
| | - Chang Hyung Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Yoo Kyoung Park
- Department of Medical Nutrition, Graduate School of East-West Medical Nutrition, Kyung Hee University, Suwon, Republic of Korea
| | - Hae Ri Na
- Department of Neurology, Bobath Memorial Hospital, Seongnam, Republic of Korea
| | - Hong-Sun Song
- Department of Sports Sciences, Korea Institute of Sports Science, Seoul, Republic of Korea
| | - Hee Kyung Park
- Division of Psychiatry, University College London, London, United Kingdom
| | | | - Buong-O Chun
- Graduate School of Physical Education, College of Arts and Physical Education, Myongji University, Yongin, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Republic of Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea
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20
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Torabian S, Vélez N, Sochat V, Halchenko YO, Grossman ED. The PyMVPA BIDS-App: a robust multivariate pattern analysis pipeline for fMRI data. Front Neurosci 2023; 17:1233416. [PMID: 37694123 PMCID: PMC10483824 DOI: 10.3389/fnins.2023.1233416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/04/2023] [Indexed: 09/12/2023] Open
Abstract
With the advent of multivariate pattern analysis (MVPA) as an important analytic approach to fMRI, new insights into the functional organization of the brain have emerged. Several software packages have been developed to perform MVPA analysis, but deploying them comes with the cost of adjusting data to individual idiosyncrasies associated with each package. Here we describe PyMVPA BIDS-App, a fast and robust pipeline based on the data organization of the BIDS standard that performs multivariate analyses using powerful functionality of PyMVPA. The app runs flexibly with blocked and event-related fMRI experimental designs, is capable of performing classification as well as representational similarity analysis, and works both within regions of interest or on the whole brain through searchlights. In addition, the app accepts as input both volumetric and surface-based data. Inspections into the intermediate stages of the analyses are available and the readability of final results are facilitated through visualizations. The PyMVPA BIDS-App is designed to be accessible to novice users, while also offering more control to experts through command-line arguments in a highly reproducible environment.
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Affiliation(s)
- Sajjad Torabian
- Visual Perception and Neuroimaging Lab, Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States
| | - Natalia Vélez
- Computational Cognitive Neuroscience Lab, Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Vanessa Sochat
- Lawrence Livermore National Laboratory, Livermore, CA, United States
| | - Yaroslav O. Halchenko
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States
| | - Emily D. Grossman
- Visual Perception and Neuroimaging Lab, Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States
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21
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Andrushko JW, Rinat S, Greeley B, Larssen BC, Jones CB, Rubino C, Denyer R, Ferris JK, Campbell KL, Neva JL, Boyd LA. Improved processing speed and decreased functional connectivity in individuals with chronic stroke after paired exercise and motor training. Sci Rep 2023; 13:13652. [PMID: 37608062 PMCID: PMC10444837 DOI: 10.1038/s41598-023-40605-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/14/2023] [Indexed: 08/24/2023] Open
Abstract
After stroke, impaired motor performance is linked to an increased demand for cognitive resources. Aerobic exercise improves cognitive function in neurologically intact populations and may be effective in altering cognitive function post-stroke. We sought to determine if high-intensity aerobic exercise paired with motor training in individuals with chronic stroke alters cognitive-motor function and functional connectivity between the dorsolateral prefrontal cortex (DLPFC), a key region for cognitive-motor processes, and the sensorimotor network. Twenty-five participants with chronic stroke were randomly assigned to exercise (n = 14; 66 ± 11 years; 4 females), or control (n = 11; 68 ± 8 years; 2 females) groups. Both groups performed 5-days of paretic upper limb motor training after either high-intensity aerobic exercise (3 intervals of 3 min each, total exercise duration of 23-min) or watching a documentary (control). Resting-state fMRI, and trail making test part A (TMT-A) and B were recorded pre- and post-intervention. Both groups showed implicit motor sequence learning (p < 0.001); there was no added benefit of exercise for implicit motor sequence learning (p = 0.738). The exercise group experienced greater overall cognitive-motor improvements measured with the TMT-A. Regardless of group, the changes in task score, and dwell time during TMT-A were correlated with a decrease in DLPFC-sensorimotor network functional connectivity (task score: p = 0.025; dwell time: p = 0.043), which is thought to reflect a reduction in the cognitive demand and increased automaticity. Aerobic exercise may improve cognitive-motor processing speed post-stroke.
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Affiliation(s)
- Justin W Andrushko
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Shie Rinat
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Graduate Program in Rehabilitation Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Brian Greeley
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Beverley C Larssen
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Christina B Jones
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Graduate Program in Rehabilitation Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Cristina Rubino
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Graduate Program in Rehabilitation Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Ronan Denyer
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Graduate Program in Neuroscience, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Jennifer K Ferris
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Graduate Program in Rehabilitation Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Kristin L Campbell
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Jason L Neva
- Faculty of Medicine, School of Kinesiology and Physical Activity Sciences, University of Montreal, Montreal, QC, H3T 1J4, Canada
- Research Center of the Montreal Geriatrics Institute (CRIUGM), Montreal, QC, Canada
| | - Lara A Boyd
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
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22
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Devrome M, Van Laere K, Koole M. Multiplex core of the human brain using structural, functional and metabolic connectivity derived from hybrid PET-MR imaging. FRONTIERS IN NEUROIMAGING 2023; 2:1115965. [PMID: 37645694 PMCID: PMC10461102 DOI: 10.3389/fnimg.2023.1115965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 07/06/2023] [Indexed: 08/31/2023]
Abstract
With the increasing success of mapping brain networks and availability of multiple MR- and PET-based connectivity measures, the need for novel methodologies to unravel the structure and function of the brain at multiple spatial and temporal scales is emerging. Therefore, in this work, we used hybrid PET-MR data of healthy volunteers (n = 67) to identify multiplex core nodes in the human brain. First, monoplex networks of structural, functional and metabolic connectivity were constructed, and consequently combined into a multiplex SC-FC-MC network by linking the same nodes categorically across layers. Taking into account the multiplex nature using a tensorial approach, we identified a set of core nodes in this multiplex network based on a combination of eigentensor centrality and overlapping degree. We introduced a coreness coefficient, which mitigates the effect of modeling parameters to obtain robust results. The proposed methodology was applied onto young and elderly healthy volunteers, where differences observed in the monoplex networks persisted in the multiplex as well. The multiplex core showed a decreased contribution to the default mode and salience network, while an increased contribution to the dorsal attention and somatosensory network was observed in the elderly population. Moreover, a clear distinction in eigentensor centrality was found between young and elderly healthy volunteers.
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Affiliation(s)
- Martijn Devrome
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
- Division of Nuclear Medicine, Universitair Ziekenhuis (UZ) Leuven, Leuven, Belgium
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
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23
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Melis M, Schroyen G, Blommaert J, Leenaerts N, Smeets A, Van Der Gucht K, Sunaert S, Deprez S. The Impact of Mindfulness on Functional Brain Connectivity and Peripheral Inflammation in Breast Cancer Survivors with Cognitive Complaints. Cancers (Basel) 2023; 15:3632. [PMID: 37509292 PMCID: PMC10377401 DOI: 10.3390/cancers15143632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/06/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Cancer-related cognitive impairment (CRCI) has been linked to functional brain changes and inflammatory processes. Hence, interventions targeting these underlying mechanisms are needed. In this study, we investigated the effects of a mindfulness-based intervention on brain function and inflammatory profiles in breast cancer survivors with CRCI. METHODS Female breast cancer survivors reporting cognitive complaints (n = 117) were randomly assigned to a mindfulness-based intervention (n = 43), physical training (n = 36), or waitlist control condition (n = 38). Region-of-interest (ROI) and graph theory analyses of resting state functional MRI data were performed to study longitudinal group differences in functional connectivity and organization in the default mode, dorsal attention, salience, and frontoparietal network. Additionally, bead-based immunoassays were used to investigate the differences in inflammatory profiles on serum samples. Measures were collected before, immediately after and three months post-intervention. RESULTS No ROI-to-ROI functional connectivity changes were identified. Compared to no intervention, graph analysis showed a larger decrease in clustering coefficient after mindfulness and physical training. Additionally, a larger increase in global efficiency after physical training was identified. Furthermore, the physical training group showed a larger decrease in an inflammatory profile compared to no intervention (IL-12p70, IFN-γ, IL-1β, and IL-8). CONCLUSION Both mindfulness and physical training induced changes in the functional organization of networks related to attention, emotion processing, and executive functioning. While both interventions reduced functional segregation, only physical training increased functional integration of the neural network. In conclusion, physical training had the most pronounced effects on functional network organization and biomarkers of inflammation, two mechanisms that might be involved in CRCI.
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Affiliation(s)
- Michelle Melis
- Department of Imaging and Pathology, Translational MRI, Catholic University Leuven, 1000 Brussels, Belgium
- Research Foundation Flanders (FWO), 1000 Brussels, Belgium
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Leuven Cancer Institute, Catholic University Leuven, 3000 Leuven, Belgium
| | - Gwen Schroyen
- Department of Imaging and Pathology, Translational MRI, Catholic University Leuven, 1000 Brussels, Belgium
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Leuven Cancer Institute, Catholic University Leuven, 3000 Leuven, Belgium
| | - Jeroen Blommaert
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Leuven Cancer Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Department of Oncology, Gynecological Oncology, Catholic University Leuven, 3000 Leuven, Belgium
| | - Nicolas Leenaerts
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Department of Neurosciences, Mind-Body Research, Catholic University Leuven, 3000 Leuven, Belgium
| | - Ann Smeets
- Leuven Cancer Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Department of Oncology, Surgical Oncology, Catholic University Leuven, 3000 Leuven, Belgium
- Department of Surgical Oncology, Multidisciplinary Breast Center, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Katleen Van Der Gucht
- Tilburg School of Social and Behavioral Sciences, Tilburg University, 5037 AB Tilburg, The Netherlands
- Leuven Mindfulness Centre, Faculty of Psychology and Educational Sciences, Catholic University Leuven, 3000 Leuven, Belgium
- Neuromodulation Laboratory, Biomedical Sciences Group, Department of Rehabilitation Sciences, Catholic University Leuven, 3000 Leuven, Belgium
| | - Stefan Sunaert
- Department of Imaging and Pathology, Translational MRI, Catholic University Leuven, 1000 Brussels, Belgium
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Department of Radiology, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Sabine Deprez
- Department of Imaging and Pathology, Translational MRI, Catholic University Leuven, 1000 Brussels, Belgium
- Leuven Brain Institute, Catholic University Leuven, 3000 Leuven, Belgium
- Leuven Cancer Institute, Catholic University Leuven, 3000 Leuven, Belgium
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24
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Kreilkamp BAK, Stier C, Rauf EH, Martin P, Ethofer S, Lerche H, Kotikalapudi R, Marquetand J, Dechent P, Focke NK. Multi-spectral diffusion MRI mega-analysis in genetic generalized epilepsy: Relation to outcomes. Neuroimage Clin 2023; 39:103474. [PMID: 37441820 PMCID: PMC10509527 DOI: 10.1016/j.nicl.2023.103474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/15/2023]
Abstract
BACKGROUND AND OBJECTIVES Genetic generalized epilepsy (GGE) is the most common form of generalized epilepsy. Although individual patients with GGE typically present without structural alterations, group differences have been demonstrated in GGE and some GGE subtypes like juvenile myoclonic epilepsy (GGE-JME). Previous studies usually involved only small cohorts from single centers and therefore could not assess imaging markers of multiple GGE subtypes. METHODS We performed a diffusion MRI mega-analysis in 192 participants consisting of 126 controls and 66 patients with GGE from four different cohorts and two different epilepsy centers. We applied whole-brain multi-site harmonization and analyzed fractional anisotropy (FA), as well as mean, radial and axial diffusivity (MD/RD/AD) to assess differences between controls, patients with GGE and the common GGE subtypes, i.e. GGE with generalized tonic-clonic seizures only (GGE-GTCS), GGE-JME and absence epilepsy (GGE-AE). We also analyzed relationships with patients' response to anti-seizure-medication (ASM). RESULTS Relative to controls, we identified decreased anisotropy and increased RD in patients with GGE. We found no significant effects of disease duration, age of onset or seizure frequency on diffusion metrics. Patients with JME had increased MD and RD when compared to controls, while patients with GGE-GTCS showed decreased MD/AD when compared to controls. Compared to patients with GGE-AE, patients with GGE-GTCS had lower AD/MD. Compared to patients with GGE-GTCS, patients with GGE-JME had higher MD/RD and AD. Moreover, we found lower FA in patients with refractory when compared to patients with non-refractory GGE in the right cortico-spinal tract, but no significant differences in patients with active versus controlled epilepsy. DISCUSSION We provide evidence that clinically defined GGE as a whole and GGE-subtypes harbor marked microstructural differences detectable with diffusion MRI. Moreover, we found an association between microstructural changes and treatment resistance. Our findings have important implications for future full-resolution multi-site studies when assessing GGE, its subtypes and ASM refractoriness.
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Affiliation(s)
| | - Christina Stier
- Clinic for Neurology, University Medical Center Göttingen, Göttingen, Germany; Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University of Tübingen, Tübingen, Germany.
| | - Erik H Rauf
- Clinic for Neurology, University Medical Center Göttingen, Göttingen, Germany.
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University of Tübingen, Tübingen, Germany.
| | - Silke Ethofer
- Department of Neurosurgery, University of Tübingen, Tübingen, Germany.
| | - Holger Lerche
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University of Tübingen, Tübingen, Germany.
| | - Raviteja Kotikalapudi
- Laboratory for Predictive Neuroimaging, University of Duisburg-Essen, Essen, Germany
| | - Justus Marquetand
- Department of Neurology and Epileptology, Hertie Institute of Clinical Brain Research, University of Tübingen, Tübingen, Germany; Department of Neural Dynamics and Magnetoencephalography, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; MEG-Center, University of Tübingen, Tübingen, Germany.
| | - Peter Dechent
- Department of Cognitive Neurology, University Medical Center Göttingen, Göttingen, Germany.
| | - Niels K Focke
- Clinic for Neurology, University Medical Center Göttingen, Göttingen, Germany.
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25
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Wehrheim MH, Faskowitz J, Sporns O, Fiebach CJ, Kaschube M, Hilger K. Few temporally distributed brain connectivity states predict human cognitive abilities. Neuroimage 2023:120246. [PMID: 37364742 DOI: 10.1016/j.neuroimage.2023.120246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 06/19/2023] [Accepted: 06/21/2023] [Indexed: 06/28/2023] Open
Abstract
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities - which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
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Affiliation(s)
- Maren H Wehrheim
- Department of Psychology, Goethe University Frankfurt, D-60323 Frankfurt am Main, Germany; Department of Computer Science, Goethe University Frankfurt, D-60325 Frankfurt am Main, Germany.
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405.
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405.
| | - Christian J Fiebach
- Department of Psychology, Goethe University Frankfurt, D-60323 Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, D-60528 Frankfurt am Main, Germany.
| | - Matthias Kaschube
- Department of Computer Science, Goethe University Frankfurt, D-60325 Frankfurt am Main, Germany; Frankfurt Institute for Advanced Studies, D-60438 Frankfurt am Main, Germany.
| | - Kirsten Hilger
- Department of Psychology, Goethe University Frankfurt, D-60323 Frankfurt am Main, Germany; Department of Psychology I, Julius Maximilian University, D-97070 Würzburg, Germany.
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26
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Bao Q, Xie W, Otikovs M, Xia L, Xie H, Liu X, Liu K, Zhang Z, Chen F, Zhou X, Liu C. Unsupervised cycle-consistent network using restricted subspace field map for removing susceptibility artifacts in EPI. Magn Reson Med 2023; 90:458-472. [PMID: 37052369 DOI: 10.1002/mrm.29653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/19/2023] [Accepted: 03/14/2023] [Indexed: 04/14/2023]
Abstract
PURPOSE To design an unsupervised deep neural model for correcting susceptibility artifacts in single-shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications. METHODS This work proposes an unsupervised cycle-consistent model based on the restricted subspace field map to take advantage of both the deep learning (DL) and the reverse polarity-gradient (RPG) method for single-shot EPI. The proposed model consists of three main components: (1) DLRPG neural network (DLRPG-net) to obtain field maps based on a pair of images acquired with reversed phase encoding; (2) spin physical model-based modules to obtain the corrected undistorted images based on the learned field map; and (3) cycle-consistency loss between the input images and back-calculated images from each cycle is explored for network training. In addition, the field maps generated by DLRPG-net belong to a restricted subspace, which is a span of predefined cubic splines to ensure the smoothness of the field maps and avoid blurring in the corrected images. This new method is trained and validated on both preclinical and clinical datasets for diffusion MRI. RESULTS The proposed network could effectively generate smooth field maps and correct susceptibility artifacts in single-shot EPI. Simulated and in vivo preclinical/clinical experiments demonstrated that our method outperforms the state-of-the-art susceptibility artifact correction methods. Furthermore, the ablation experiments of the cycle-consistent network and the restricted subspace in generating field maps did show the advantages of DLRPG-net. CONCLUSION The proposed method (DLRPG-net) can effectively correct susceptibility artifacts for preclinical and clinical single-shot EPI sequences.
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Affiliation(s)
- Qingjia Bao
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
| | - Weida Xie
- School of Information Engineering, Wuhan University of Technology, Wuhan, People's Republic of China
| | | | - Liyang Xia
- School of Information Engineering, Wuhan University of Technology, Wuhan, People's Republic of China
| | - Han Xie
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
| | - Xinjie Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
| | - Kewen Liu
- School of Information Engineering, Wuhan University of Technology, Wuhan, People's Republic of China
| | - Zhi Zhang
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
| | - Fang Chen
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
- University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology-Optics Valley Laboratory, Hubei, 430074, People's Republic of China
| | - Chaoyang Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, 430071, People's Republic of China
- University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology-Optics Valley Laboratory, Hubei, 430074, People's Republic of China
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27
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Feher da Silva C, Lombardi G, Edelson M, Hare TA. Rethinking model-based and model-free influences on mental effort and striatal prediction errors. Nat Hum Behav 2023:10.1038/s41562-023-01573-1. [PMID: 37012365 DOI: 10.1038/s41562-023-01573-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 02/27/2023] [Indexed: 04/05/2023]
Abstract
A standard assumption in neuroscience is that low-effort model-free learning is automatic and continuously used, whereas more complex model-based strategies are only used when the rewards they generate are worth the additional effort. We present evidence refuting this assumption. First, we demonstrate flaws in previous reports of combined model-free and model-based reward prediction errors in the ventral striatum that probably led to spurious results. More appropriate analyses yield no evidence of model-free prediction errors in this region. Second, we find that task instructions generating more correct model-based behaviour reduce rather than increase mental effort. This is inconsistent with cost-benefit arbitration between model-based and model-free strategies. Together, our data indicate that model-free learning may not be automatic. Instead, humans can reduce mental effort by using a model-based strategy alone rather than arbitrating between multiple strategies. Our results call for re-evaluation of the assumptions in influential theories of learning and decision-making.
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Affiliation(s)
| | - Gaia Lombardi
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Micah Edelson
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Todd A Hare
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland.
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Montez DF, Van AN, Miller RL, Seider NA, Marek S, Zheng A, Newbold DJ, Scheidter K, Feczko E, Perrone AJ, Miranda-Dominguez O, Earl EA, Kay BP, Jha AK, Sotiras A, Laumann TO, Greene DJ, Gordon EM, Tisdall MD, van der Kouwe A, Fair DA, Dosenbach NUF. Using synthetic MR images for distortion correction. Dev Cogn Neurosci 2023; 60:101234. [PMID: 37023632 PMCID: PMC10106483 DOI: 10.1016/j.dcn.2023.101234] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 03/07/2023] [Accepted: 03/16/2023] [Indexed: 04/07/2023] Open
Abstract
Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.
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Affiliation(s)
- David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America.
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Ryland L Miller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, New York University Langone Medical Center, New York, NY 10016, United States of America
| | - Kristen Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Anders J Perrone
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Psychiatry, Oregon Health and Science University, Portland, OR 97239, United States of America
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Eric A Earl
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Psychiatry, Oregon Health and Science University, Portland, OR 97239, United States of America
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Abhinav K Jha
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Aristeidis Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Institute for Informatics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, La Jolla CA 92093, United States of America
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Andre van der Kouwe
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, United States of America; Department of Radiology, Harvard Medical School, Boston, MA 02115, United States of America
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America; Institute of Child Development, University of Minnesota Medical School, Minneapolis, MN 55455, United States of America
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
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D'Mello AM, Frosch IR, Meisler SL, Grotzinger H, Perrachione TK, Gabrieli JDE. Diminished Repetition Suppression Reveals Selective and Systems-Level Face Processing Differences in ASD. J Neurosci 2023; 43:1952-1962. [PMID: 36759192 PMCID: PMC10027049 DOI: 10.1523/jneurosci.0608-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 01/24/2023] [Accepted: 01/28/2023] [Indexed: 02/11/2023] Open
Abstract
Repeated exposure to a stimulus results in reduced neural response, or repetition suppression, in brain regions responsible for processing that stimulus. This rapid accommodation to repetition is thought to underlie learning, stimulus selectivity, and strengthening of perceptual expectations. Importantly, reduced sensitivity to repetition has been identified in several neurodevelopmental, learning, and psychiatric disorders, including autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by challenges in social communication and repetitive behaviors and restricted interests. Reduced ability to exploit or learn from repetition in ASD is hypothesized to contribute to sensory hypersensitivities, and parallels several theoretical frameworks claiming that ASD individuals show difficulty using regularities in the environment to facilitate behavior. Using fMRI in autistic and neurotypical human adults (females and males), we assessed the status of repetition suppression across two modalities (vision, audition) and with four stimulus categories (faces, objects, printed words, and spoken words). ASD individuals showed domain-specific reductions in repetition suppression for face stimuli only, but not for objects, printed words, or spoken words. Reduced repetition suppression for faces was associated with greater challenges in social communication in ASD. We also found altered functional connectivity between atypically adapting cortical regions and higher-order face recognition regions, and microstructural differences in related white matter tracts in ASD. These results suggest that fundamental neural mechanisms and system-wide circuits are selectively altered for face processing in ASD and enhance our understanding of how disruptions in the formation of stable face representations may relate to higher-order social communication processes.SIGNIFICANCE STATEMENT A common finding in neuroscience is that repetition results in plasticity in stimulus-specific processing regions, reflecting selectivity and adaptation (repetition suppression [RS]). RS is reduced in several neurodevelopmental and psychiatric conditions including autism spectrum disorder (ASD). Theoretical frameworks of ASD posit that reduced adaptation may contribute to associated challenges in social communication and sensory processing. However, the scope of RS differences in ASD is unknown. We examined RS for multiple categories across visual and auditory domains (faces, objects, printed words, spoken words) in autistic and neurotypical individuals. We found reduced RS in ASD for face stimuli only and altered functional connectivity and white matter microstructure between cortical face-recognition areas. RS magnitude correlated with social communication challenges among autistic individuals.
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Affiliation(s)
- Anila M D'Mello
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Isabelle R Frosch
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Steven L Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, Massachusetts, 02115
| | - Hannah Grotzinger
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Tyler K Perrachione
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, Massachusetts 02215
| | - John D E Gabrieli
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
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30
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Modulation of amygdala activity for emotional faces due to botulinum toxin type A injections that prevent frowning. Sci Rep 2023; 13:3333. [PMID: 36849797 PMCID: PMC9971043 DOI: 10.1038/s41598-023-29280-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 02/01/2023] [Indexed: 03/01/2023] Open
Abstract
According to the facial feedback hypothesis, when we see an angry or happy face, we contract or flex the relevant muscles to recreate the expression to assist in identifying and experiencing the emotion reflected. We investigated the facial feedback hypothesis by using botulinum toxin type A (onabotulinumtoxinA; onabotA) injections to induce temporary paralysis in the glabellar muscles (responsible for frowning) and measured functional brain activity during the processing of emotional faces. Ten females viewed pictures of happy and angry faces during two functional magnetic resonance imaging (fMRI) scan sessions: one prior (Pre) to onabotA and one following (Active) onabotA injections. We found Pre vs. Active onabotA modulation of activity in the amygdala for both happy and angry faces, as well as modulation of activity in the fusiform gyrus for happy faces. Consistent with our predictions, preventing frowning through inhibition of glabellar muscle contraction altered amygdala processing for emotional faces. The modulation of amygdala and fusiform gyrus activity following onabotA may reflect compensatory processes in a neuroanatomical circuit involved in emotional processing that is engaged when facial feedback is impaired. These data contribute to a growing literature suggesting that inhibition of glabellar muscle contraction alters neural activity for emotional processing.Clinical Trials.gov registration number: NCT03373162.
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Li X, Qureshi MNI, Laplante DP, Elgbeili G, Jones SL, King S, Rosa-Neto P. Neural correlates of disaster-related prenatal maternal stress in young adults from Project Ice Storm: Focus on amygdala, hippocampus, and prefrontal cortex. Front Hum Neurosci 2023; 17:1094039. [PMID: 36816508 PMCID: PMC9929467 DOI: 10.3389/fnhum.2023.1094039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 01/11/2023] [Indexed: 02/04/2023] Open
Abstract
Background Studies have shown that prenatal maternal stress alters volumes of the amygdala and hippocampus, and alters functional connectivity between the amygdala and prefrontal cortex. However, it remains unclear whether prenatal maternal stress (PNMS) affects volumes and functional connectivity of these structures at their subdivision levels. Methods T1-weighted MRI and resting-state functional MRI were obtained from 19-year-old young adult offspring with (n = 39, 18 male) and without (n = 65, 30 male) exposure to PNMS deriving from the 1998 ice storm. Volumes of amygdala nuclei, hippocampal subfields and prefrontal subregions were computed, and seed-to-seed functional connectivity analyses were conducted. Results Compared to controls, young adult offspring exposed to disaster-related PNMS had larger volumes of bilateral whole amygdala, driven by the lateral, basal, central, medial, cortical, accessory basal nuclei, and corticoamygdaloid transition; larger volumes of bilateral whole hippocampus, driven by the CA1, HATA, molecular layer, fissure, tail, CA3, CA4, and DG; and larger volume of the prefrontal cortex, driven by the left superior frontal. Inversely, young adult offspring exposed to disaster-related PNMS had lower functional connectivity between the whole amygdala and the prefrontal cortex (driven by bilateral frontal poles, the left superior frontal and left caudal middle frontal); and lower functional connectivity between the hippocampal tail and the prefrontal cortex (driven by the left lateral orbitofrontal). Conclusion These results suggest the possibility that effects of disaster-related PNMS on structure and function of subdivisions of offspring amygdala, hippocampus and prefrontal cortex could persist into young adulthood.
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Affiliation(s)
- Xinyuan Li
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada,Mental Health and Society Division, Douglas Mental Health University Institute, Montreal, QC, Canada,Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David P. Laplante
- Centre for Child Development and Mental Health, Lady Davis Institute-Jewish General Hospital, Montreal, QC, Canada
| | - Guillaume Elgbeili
- Mental Health and Society Division, Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Sherri Lee Jones
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Suzanne King
- Mental Health and Society Division, Douglas Mental Health University Institute, Montreal, QC, Canada,Department of Psychiatry, McGill University, Montreal, QC, Canada,*Correspondence: Suzanne King,
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada,Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
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32
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De Rosa AP, Esposito F, Valsasina P, d'Ambrosio A, Bisecco A, Rocca MA, Tommasin S, Marzi C, De Stefano N, Battaglini M, Pantano P, Cirillo M, Tedeschi G, Filippi M, Gallo A. Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative. J Neurol 2023; 270:1047-1066. [PMID: 36350401 PMCID: PMC9886598 DOI: 10.1007/s00415-022-11479-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/11/2022]
Abstract
The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.
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Affiliation(s)
- Alessandro Pasquale De Rosa
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy.
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
| | - Alessandro d'Ambrosio
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy
| | - Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università, 30, 00185, Rome, Italy
| | - Chiara Marzi
- Institute of Applied Physics "Nello Cararra" (IFAC), National Research Council (CNR), Via Madonna del Piano, 10, Sesto Fiorentino, 50019, Florence, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università, 30, 00185, Rome, Italy
| | - Mario Cirillo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
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Azor AM, Sharp DJ, Jolly AE, Bourke NJ, Hellyer PJ. Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations. PLoS One 2022; 17:e0268233. [PMID: 36480567 PMCID: PMC9731501 DOI: 10.1371/journal.pone.0268233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 04/25/2022] [Indexed: 12/13/2022] Open
Abstract
Diffusion weighted imaging (DWI) is key in clinical neuroimaging studies. In recent years, DWI has undergone rapid evolution and increasing applications. Diffusion magnetic resonance imaging (dMRI) is widely used to analyse group-level differences in white matter (WM), but suffers from limitations that can be particularly impactful in clinical groups where 1) structural abnormalities may increase erroneous inter-subject registration and 2) subtle differences in WM microstructure between individuals can be missed. It also lacks standardization protocols for analyses at the subject level. Region of Interest (ROI) analyses in native diffusion space can help overcome these challenges, with manual segmentation still used as the gold standard. However, robust automated approaches for the analysis of ROI-extracted native diffusion characteristics are limited. Subject-Specific Diffusion Segmentation (SSDS) is an automated pipeline that uses pre-existing imaging analysis methods to carry out WM investigations in native diffusion space, while overcoming the need to interpolate diffusion images and using an intermediate T1 image to limit registration errors and guide segmentation. SSDS is validated in a cohort of healthy subjects scanned three times to derive test-retest reliability measures and compared to other methods, namely manual segmentation and tract-based spatial statistics as an example of group-level method. The performance of the pipeline is further tested in a clinical population of patients with traumatic brain injury and structural abnormalities. Mean FA values obtained from SSDS showed high test-retest and were similar to FA values estimated from the manual segmentation of the same ROIs (p-value > 0.1). The average dice similarity coefficients (DSCs) comparing results from SSDS and manual segmentations was 0.8 ± 0.1. Case studies of TBI patients showed robustness to the presence of significant structural abnormalities, indicating its potential clinical application in the identification and diagnosis of WM abnormalities. Further recommendation is given regarding the tracts used with SSDS.
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Affiliation(s)
- Adriana M. Azor
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom
- Dyson School of Design Engineering, Imperial College London, South Kensington Campus, London, United Kingdom
- The Royal British Legion, Centre for Blast Injury Studies, Imperial College London, South Kensington Campus, London, United Kingdom
- * E-mail: (AMA); (DJS)
| | - David J. Sharp
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom
- Dyson School of Design Engineering, Imperial College London, South Kensington Campus, London, United Kingdom
- Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, United Kingdom
- * E-mail: (AMA); (DJS)
| | - Amy E. Jolly
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom
- Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, United Kingdom
| | - Niall J. Bourke
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom
| | - Peter J. Hellyer
- Centre for Neuroimaging Sciences, King’s College London, London, United Kingdom
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Coulborn S, Fernández-Espejo D. Prefrontal tDCS is unable to modulate mind wandering propensity or underlying functional or effective brain connectivity. Sci Rep 2022; 12:18021. [PMID: 36289366 PMCID: PMC9606118 DOI: 10.1038/s41598-022-22893-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 10/20/2022] [Indexed: 01/24/2023] Open
Abstract
There is conflicting evidence over the ability to modulate mind-wandering propensity with anodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (prefrontal tDCS). Here, 20 participants received 20-min of active and sham prefrontal tDCS while in the MRI scanner, in two separate sessions (counterbalanced). In each session, they completed two runs of a sustained attention to response task (before and during tDCS), which included probes recording subjective responses of mind-wandering. We assessed the effects of tDCS on behavioural responses as well as functional and effective dynamics, via dynamic functional network connectivity (dFNC) and dynamic causal modelling analyses over regions of the default mode, salience and executive control networks. Behavioural results provided substantial evidence in support of no effect of tDCS on task performance nor mind-wandering propensity. Similarly, we found no effect of tDCS on frequency (how often) or dwell time (time spent) of underlying brain states nor effective connectivity. Overall, our results suggest that prefrontal tDCS is unable to modulate mind-wandering propensity or influence underlying brain function. This expands previous behavioural replication failures in suggesting that prefrontal tDCS may not lead to even subtle (i.e., under a behavioural threshold) changes in brain activity during self-generated cognition.
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Affiliation(s)
- Sean Coulborn
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, UK ,grid.6572.60000 0004 1936 7486Centre for Human Brain Health, University of Birmingham, Birmingham, UK ,grid.47840.3f0000 0001 2181 7878University of California, Berkeley, USA
| | - Davinia Fernández-Espejo
- grid.6572.60000 0004 1936 7486School of Psychology, University of Birmingham, Birmingham, UK ,grid.6572.60000 0004 1936 7486Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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Fazal Z, Gomez DEP, Llera A, Marques JPRF, Beck T, Poser BA, Norris DG. A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T. Hum Brain Mapp 2022; 44:82-93. [PMID: 36196782 PMCID: PMC9783458 DOI: 10.1002/hbm.26081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 08/05/2022] [Accepted: 08/16/2022] [Indexed: 02/05/2023] Open
Abstract
A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.
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Affiliation(s)
- Zahra Fazal
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | - Daniel E. P. Gomez
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMassachusettsUSA
- Present address:
Department of Biomedical EngineeringBoston UniversityBostonMassachusettsUSA
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | - José P. R. F. Marques
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | | | - Benedikt A. Poser
- Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtNetherlands
| | - David G. Norris
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO‐Weltkulturerbe Zollverein, Leitstand Kokerei ZollvereinEssenGermany
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36
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Hofstetter S, Dumoulin SO. Assessing the ecological validity of numerosity-selective neuronal populations with real-world natural scenes. iScience 2022; 25:105267. [PMID: 36274951 PMCID: PMC9579010 DOI: 10.1016/j.isci.2022.105267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 07/18/2022] [Accepted: 09/26/2022] [Indexed: 11/21/2022] Open
Abstract
Animals and humans are able to quickly and effortlessly estimate the number of items in a set: their numerosity. Numerosity perception is thought to be critical to behavior, from feeding to escaping predators to human mathematical cognition. Virtually, all scientific studies on numerosity mechanisms use well controlled but artificial stimuli to isolate the numerosity dimension from other physical quantities. Here, we probed the ecological validity of these artificial stimuli and evaluate whether an important component in numerosity processing, the numerosity-selective neural populations, also respond to numerosity of items in real-world natural scenes. Using 7T MRI and natural images from a wide range of categories, we provide evidence that the numerosity-tuned neuronal populations show numerosity-selective responses when viewing images from a real-world natural scene. Our findings strengthen the role of numerosity-selective neurons in numerosity perception and provide an important link to their function in numerosity perception in real-world settings.
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Affiliation(s)
- Shir Hofstetter
- The Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands,Department of Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands,Corresponding author
| | - Serge O. Dumoulin
- The Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands,Department of Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands,Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands,Department of Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands,Corresponding author
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37
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Harnett NG, Finegold KE, Lebois LAM, van Rooij SJH, Ely TD, Murty VP, Jovanovic T, Bruce SE, House SL, Beaudoin FL, An X, Zeng D, Neylan TC, Clifford GD, Linnstaedt SD, Germine LT, Bollen KA, Rauch SL, Haran JP, Storrow AB, Lewandowski C, Musey PI, Hendry PL, Sheikh S, Jones CW, Punches BE, Kurz MC, Swor RA, Hudak LA, Pascual JL, Seamon MJ, Harris E, Chang AM, Pearson C, Peak DA, Domeier RM, Rathlev NK, O'Neil BJ, Sergot P, Sanchez LD, Miller MW, Pietrzak RH, Joormann J, Barch DM, Pizzagalli DA, Sheridan JF, Harte SE, Elliott JM, Kessler RC, Koenen KC, McLean SA, Nickerson LD, Ressler KJ, Stevens JS. Structural covariance of the ventral visual stream predicts posttraumatic intrusion and nightmare symptoms: a multivariate data fusion analysis. Transl Psychiatry 2022; 12:321. [PMID: 35941117 PMCID: PMC9360028 DOI: 10.1038/s41398-022-02085-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/14/2022] [Accepted: 07/20/2022] [Indexed: 01/16/2023] Open
Abstract
Visual components of trauma memories are often vividly re-experienced by survivors with deleterious consequences for normal function. Neuroimaging research on trauma has primarily focused on threat-processing circuitry as core to trauma-related dysfunction. Conversely, limited attention has been given to visual circuitry which may be particularly relevant to posttraumatic stress disorder (PTSD). Prior work suggests that the ventral visual stream is directly related to the cognitive and affective disturbances observed in PTSD and may be predictive of later symptom expression. The present study used multimodal magnetic resonance imaging data (n = 278) collected two weeks after trauma exposure from the AURORA study, a longitudinal, multisite investigation of adverse posttraumatic neuropsychiatric sequelae. Indices of gray and white matter were combined using data fusion to identify a structural covariance network (SCN) of the ventral visual stream 2 weeks after trauma. Participant's loadings on the SCN were positively associated with both intrusion symptoms and intensity of nightmares. Further, SCN loadings moderated connectivity between a previously observed amygdala-hippocampal functional covariance network and the inferior temporal gyrus. Follow-up MRI data at 6 months showed an inverse relationship between SCN loadings and negative alterations in cognition in mood. Further, individuals who showed decreased strength of the SCN between 2 weeks and 6 months had generally higher PTSD symptom severity over time. The present findings highlight a role for structural integrity of the ventral visual stream in the development of PTSD. The ventral visual stream may be particularly important for the consolidation or retrieval of trauma memories and may contribute to efficient reactivation of visual components of the trauma memory, thereby exacerbating PTSD symptoms. Potentially chronic engagement of the network may lead to reduced structural integrity which becomes a risk factor for lasting PTSD symptoms.
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Affiliation(s)
- Nathaniel G Harnett
- Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | | | - Lauren A M Lebois
- Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Timothy D Ely
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Vishnu P Murty
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Steven E Bruce
- Department of Psychological Sciences, University of Missouri - St. Louis, St. Louis, MO, USA
| | - Stacey L House
- Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Francesca L Beaudoin
- Department of Emergency Medicine & Department of Health Services, Policy, and Practice, The Alpert Medical School of Brown University, Rhode Island Hospital and The Miriam Hospital, Providence, RI, USA
| | - Xinming An
- Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Donglin Zeng
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas C Neylan
- Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Sarah D Linnstaedt
- Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura T Germine
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
- The Many Brains Project, Belmont, MA, USA
| | - Kenneth A Bollen
- Department of Psychology and Neuroscience & Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Scott L Rauch
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, McLean Hospital, Belmont, MA, USA
| | - John P Haran
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Alan B Storrow
- Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Paul I Musey
- Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Phyllis L Hendry
- Department of Emergency Medicine, University of Florida College of Medicine-Jacksonville, Jacksonville, FL, USA
| | - Sophia Sheikh
- Department of Emergency Medicine, University of Florida College of Medicine-Jacksonville, Jacksonville, FL, USA
| | - Christopher W Jones
- Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, NJ, USA
| | - Brittany E Punches
- Department of Emergency Medicine, Ohio State University College of Medicine, Columbus, OH, USA
- Ohio State University College of Nursing, Columbus, OH, USA
| | - Michael C Kurz
- Department of Emergency Medicine, University of Alabama School of Medicine, Birmingham, AL, USA
- Department of Surgery, Division of Acute Care Surgery, University of Alabama School of Medicine, Birmingham, AL, USA
- Center for Injury Science, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert A Swor
- Department of Emergency Medicine, Oakland University William Beaumont School of Medicine, Rochester, MI, USA
| | - Lauren A Hudak
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Jose L Pascual
- Department of Surgery, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mark J Seamon
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, Division of Traumatology, Surgical Critical Care and Emergency Surgery, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Anna M Chang
- Department of Emergency Medicine, Jefferson University Hospitals, Philadelphia, PA, USA
| | - Claire Pearson
- Department of Emergency Medicine, Wayne State University, Ascension St. John Hospital, Detroit, MI, USA
| | - David A Peak
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Robert M Domeier
- Department of Emergency Medicine, Saint Joseph Mercy Hospital, Ypsilanti, MI, USA
| | - Niels K Rathlev
- Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA, USA
| | - Brian J O'Neil
- Department of Emergency Medicine, Wayne State University, Detroit Receiving Hospital, Detroit, MI, USA
| | - Paulina Sergot
- Department of Emergency Medicine, McGovern Medical School, University of Texas Health, Houston, TX, USA
| | - Leon D Sanchez
- Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Emergency Medicine, Harvard Medical School, Boston, MA, USA
| | - Mark W Miller
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Robert H Pietrzak
- National Center for PTSD, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Jutta Joormann
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Diego A Pizzagalli
- Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - John F Sheridan
- Division of Biosciences, Ohio State University College of Dentistry, Columbus, OH, USA
- Institute for Behavioral Medicine Research, OSU Wexner Medical Center, Columbus, OH, USA
| | - Steven E Harte
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - James M Elliott
- Kolling Institute, University of Sydney, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Northern Sydney Local Health District, New South Wales, Australia
- Physical Therapy & Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Karestan C Koenen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Samuel A McLean
- Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Trauma Recovery, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lisa D Nickerson
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Imaging Center, McLean Hospital, Belmont, MA, USA
| | - Kerry J Ressler
- Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Jennifer S Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
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38
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Cohen SS, Tottenham N, Baldassano C. Developmental changes in story-evoked responses in the neocortex and hippocampus. eLife 2022; 11:69430. [PMID: 35787304 PMCID: PMC9328767 DOI: 10.7554/elife.69430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
How does the representation of naturalistic life events change with age? Here, we analyzed fMRI data from 414 children and adolescents (5–19 years) as they watched a narrative movie. In addition to changes in the degree of inter-subject correlation (ISC) with age in sensory and medial parietal regions, we used a novel measure (between-group ISC) to reveal age-related shifts in the responses across the majority of the neocortex. Over the course of development, brain responses became more discretized into stable and coherent events and shifted earlier in time to anticipate upcoming perceived event transitions, measured behaviorally in an age-matched sample. However, hippocampal responses to event boundaries actually decreased with age, suggesting a shifting division of labor between episodic encoding processes and schematic event representations between the ages of 5 and 19.
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Affiliation(s)
- Samantha S Cohen
- Department of Psychology, Columbia University, New York, United States
| | - Nim Tottenham
- Department of Psychology, Columbia University, New York, United States
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Schneider R, Matusche B, Ladopoulos T, Ayzenberg I, Biesalski AS, Gold R, Bellenberg B, Lukas C. Quantification of individual remyelination during short-term disease course by synthetic magnetic resonance imaging. Brain Commun 2022; 4:fcac172. [PMID: 35938071 PMCID: PMC9351729 DOI: 10.1093/braincomms/fcac172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 03/21/2022] [Accepted: 06/25/2022] [Indexed: 11/29/2022] Open
Abstract
MRI is an important diagnostic tool for evaluation of myelin content in multiple sclerosis and other CNS diseases, being especially relevant for studies investigating remyelinating pharmacotherapies. In this study, we evaluated a new synthetic MRI–based myelin estimation in methylenetetrahydrofolate reductase deficiency as a treatable primary demyelinating disorder and compared this method with established diffusion tensor imaging in both methylenetetrahydrofolate reductase deficiency patients and healthy controls. This is the first synthetic MRI–based in vivo evaluation of treatment-associated remyelination. 1.5 T synthetic MRI and 3 T diffusion MRI were obtained from three methylenetetrahydrofolate reductase deficiency patients at baseline and 6 months after therapy initiation, as well as from age-matched healthy controls (diffusion tensor imaging: n = 14, synthetic MRI: n = 9). Global and regional synthetic MRI parameters (myelin volume fraction, proton density, and relaxation rates) were compared with diffusion metrics (fractional anisotropy, mean/radial/axial diffusivity) and related to healthy controls by calculating z-scores and z-deviation maps. Whole-brain myelin (% of intracranial volume) of the index patient was reduced to 6 versus 10% in healthy controls, which recovered to a nonetheless subnormal level of 6.6% following initiation of high-dosage betaine. Radial diffusivity was higher at baseline compared with healthy controls (1.34 versus 0.79 × 10−3 mm2/s), recovering at follow-up (1.19 × 10−3 mm2/s). The index patient’s lesion volume diminished by 58% under treatment. Regional analysis within lesion area and atlas-based regions revealed lower mean myelin volume fraction (12.7Baseline/14.71Follow-up%) and relaxation rates, higher proton density, as well as lower fractional anisotropy and higher radial diffusivity (1.08 × 10−3Baseline/0.94 × 10−3Follow-up) compared with healthy controls. The highest z-scores were observed for myelin volume fraction in the posterior thalamic radiation, with greater deviation from controls at baseline and reduced deviation at follow-up. Z-deviations of diffusion metrics were less pronounced for radial and mean diffusivity than for myelin volume fraction. Z-maps for myelin volume fraction of the index patient demonstrated high deviation within and beyond lesion areas, among others in the precentral and postcentral gyrus, as well as in the cerebellum, and partial remission of these alterations at follow-up, while radial diffusivity demonstrated more widespread deviations in supra- and infratentorial regions. Concordant changes of myelin volume fraction and radial diffusivity after treatment initiation, accompanied by dramatic clinical and paraclinical improvement, indicate the consistency of the methods, while myelin volume fraction seems to characterize remyelinated regions more specifically. Synthetic MRI–based myelin volume fraction provides myelin estimation consistent with changes of diffusion metrics to monitor short-term myelin changes on individual patient level.
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Affiliation(s)
- Ruth Schneider
- Department of Neurology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Britta Matusche
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Theodoros Ladopoulos
- Department of Neurology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Ilya Ayzenberg
- Department of Neurology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Anne Sophie Biesalski
- Department of Neurology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Ralf Gold
- Department of Neurology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, St Josef Hospital, Ruhr-University Bochum , 44791 Bochum , Germany
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40
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Gunther KE, Petrie D, Pearce AL, Fuchs BA, Pérez-Edgar K, Keller KL, Geier C. Heterogeneity in PFC-amygdala connectivity in middle childhood, and concurrent interrelations with inhibitory control and anxiety symptoms. Neuropsychologia 2022; 174:108313. [PMID: 35798067 DOI: 10.1016/j.neuropsychologia.2022.108313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 10/17/2022]
Abstract
The prefrontal cortex (PFC) is a key brain area in considering adaptive regulatory behaviors. This includes regulatory projections to regions of the limbic system such as the amygdala, where the nature of functional connections may confer lower risk for anxiety disorders. The PFC is also associated with behaviors like executive functioning. Inhibitory control is a behavior encompassed by executive functioning and is generally viewed favorably for adaptive socioemotional development. Yet, some research suggests that high levels of inhibitory control may actually be a risk factor for some maladaptive developmental outcomes, like anxiety disorders. In a sample of 51 children ranging from 7 to 9 years old, we examined resting state functional connectivity between regions of the PFC and the amygdala. We used Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) to identify and characterize data-driven subgroups of individuals with similar networks of connectivity between these brain regions. Generated subgroups were collapsed into children characterized by the presence or absence of recovered connections between the PFC and amygdala. For subsets of children with available data (N = 38-44), we then tested whether inhibitory control, as measured by a stop signal task, moderated the relation between these subgroups and child-reported anxiety symptoms. We found an inverse relation between stop-signal reaction times and reported count of anxiety symptoms when covarying for connectivity group, suggesting that greater inhibitory control was actually related to greater anxiety symptoms, but only when accounting for patterns of PFC-amygdala connectivity. These data suggest that there is a great deal of heterogeneity in the nature of functional connections between the PFC and amygdala during this stage of development. The findings also provide support for the notion of high levels of inhibitory control as a risk factor for anxiety, but trait-level biopsychosocial factors may be important to consider in assessing the nature of risk.
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41
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Miletić S, Keuken MC, Mulder M, Trampel R, de Hollander G, Forstmann BU. 7T functional MRI finds no evidence for distinct functional subregions in the subthalamic nucleus during a speeded decision-making task. Cortex 2022; 155:162-188. [DOI: 10.1016/j.cortex.2022.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 03/18/2022] [Accepted: 06/07/2022] [Indexed: 11/03/2022]
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42
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Poudel R, Tobia MJ, Riedel MC, Salo T, Flannery JS, Hill-Bowen LD, Dick AS, Laird AR, Parra CM, Sutherland MT. Risky decision-making strategies mediate the relationship between amygdala activity and real-world financial savings among individuals from lower income households: A pilot study. Behav Brain Res 2022; 428:113867. [PMID: 35385783 PMCID: PMC10739684 DOI: 10.1016/j.bbr.2022.113867] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 03/06/2022] [Accepted: 03/28/2022] [Indexed: 11/19/2022]
Abstract
Lower financial savings among individuals experiencing adverse social determinants of health (SDoH) increases vulnerabilities during times of crisis. SDoH including low socioeconomic status (low-SES) influence cognitive abilities as well as health and life outcomes that may perpetuate poverty and disparities. Despite evidence suggesting a role for financial growth in minimizing SDoH-related disparities and vulnerabilities, neurobiological mechanisms linked with financial behavior remain to be elucidated. As such, we examined the relationships between brain activity during decision-making (DM), laboratory-based task performance, and money savings behavior. Participants (N = 24, 14 females) from low-SES households (income<$20,000/year) underwent fMRI scanning while performing the Balloon Analogue Risk Task (BART), a DM paradigm probing risky- and strategic-DM processes. Participants also completed self-report instruments characterizing relevant personality characteristics and then engaged in a community outreach financial program where amount of money saved was tracked over a 6-month period. Regarding BART-related brain activity, we observed expected activity in regions implicated in reward and emotional processing including the amygdala. Regarding brain-behavior relationships, we found that laboratory-based BART performance mediated the impact of amygdala activity on real-world behavior. That is, elevated amygdala activity was linked with BART strategic-DM which, in turn, was linked with more money saved after 6 months. In exploratory analyses, this mediation was moderated by emotion-related personality characteristics such that, only individuals reporting lower alexithymia demonstrated a relationship between amygdala activity and savings. These outcomes suggest that DM-related amygdala activity and/or emotion-related personality characteristics may provide utility as an endophenotypic marker of individual's financial savings behavior.
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Affiliation(s)
- Ranjita Poudel
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Michael J Tobia
- Department of Physics, Florida International University, Miami, FL, United States
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL, United States
| | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Jessica S Flannery
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Lauren D Hill-Bowen
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Anthony S Dick
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, United States
| | - Carlos M Parra
- College of Business, Florida International University, Miami, FL, United States
| | - Matthew T Sutherland
- Department of Psychology, Florida International University, Miami, FL, United States.
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43
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Baldi S, Michielse S, Vriend C, van den Heuvel MP, van den Heuvel OA, Schruers KRJ, Goossens L. Abnormal white-matter rich-club organization in obsessive-compulsive disorder. Hum Brain Mapp 2022; 43:4699-4709. [PMID: 35735129 PMCID: PMC9491289 DOI: 10.1002/hbm.25984] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/24/2022] [Accepted: 06/03/2022] [Indexed: 11/09/2022] Open
Abstract
Rich‐club organization is key to efficient global neuronal signaling and integration of information. Alterations interfere with higher‐order cognitive processes, and are common to several psychiatric and neurological conditions. A few studies examining the structural connectome in obsessive–compulsive disorder (OCD) suggest lower efficiency of information transfer across the brain. However, it remains unclear whether this is due to alterations in rich‐club organization. In the current study, the structural connectome of 28 unmedicated OCD patients, 8 of their unaffected siblings and 28 healthy controls was reconstructed by means of diffusion‐weighted imaging and probabilistic tractography. Topological and weighted measures of rich‐club organization and connectivity were computed, alongside global and nodal measures of network integration and segregation. The relationship between clinical scores and network properties was explored. Compared to healthy controls, OCD patients displayed significantly lower topological and weighted rich‐club organization, allocating a smaller fraction of all connection weights to the rich‐club core. Global clustering coefficient, local efficiency, and clustering of nonrich club nodes were significantly higher in OCD patients. Significant three‐group differences emerged, with siblings displaying highest and lowest values in different measures. No significant correlation with any clinical score was found. Our results suggest weaker structural connectivity between rich‐club nodes in OCD patients, possibly resulting in lower network integration in favor of higher network segregation. We highlight the need of looking at network‐based alterations in brain organization and function when investigating the neurobiological basis of this disorder, and stimulate further research into potential familial protective factors against the development of OCD.
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Affiliation(s)
- Samantha Baldi
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Stijn Michielse
- Department of Neurosurgery, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Chris Vriend
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Odile A van den Heuvel
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Koen R J Schruers
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Liesbet Goossens
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
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Begnoche JP, Schilling KG, Boyd BD, Cai LY, Taylor WD, Landman BA. EPI susceptibility correction introduces significant differences far from local areas of high distortion. Magn Reson Imaging 2022; 92:1-9. [DOI: 10.1016/j.mri.2022.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 05/01/2022] [Accepted: 05/22/2022] [Indexed: 11/16/2022]
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Zamani Esfahlani F, Faskowitz J, Slack J, Mišić B, Betzel RF. Local structure-function relationships in human brain networks across the lifespan. Nat Commun 2022; 13:2053. [PMID: 35440659 PMCID: PMC9018911 DOI: 10.1038/s41467-022-29770-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 03/29/2022] [Indexed: 12/13/2022] Open
Abstract
A growing number of studies have used stylized network models of communication to predict brain function from structure. Most have focused on a small set of models applied globally. Here, we compare a large number of models at both global and regional levels. We find that globally most predictors perform poorly. At the regional level, performance improves but heterogeneously, both in terms of variance explained and the optimal model. Next, we expose synergies among predictors by using pairs to jointly predict FC. Finally, we assess age-related differences in global and regional coupling across the human lifespan. We find global decreases in the magnitude of structure-function coupling with age. We find that these decreases are driven by reduced coupling in sensorimotor regions, while higher-order cognitive systems preserve local coupling with age. Our results describe patterns of structure-function coupling across the cortex and how this may change with age.
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Affiliation(s)
- Farnaz Zamani Esfahlani
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Jonah Slack
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA.
- Cognitive Science Program, Indiana University, Bloomington, IN, 47405, USA.
- Network Science Institute, Indiana University, Bloomington, IN, 47405, USA.
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46
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Hong JS, Hermann I, Zöllner FG, Schad LR, Wang SJ, Lee WK, Chen YL, Chang Y, Wu YT. Acceleration of Magnetic Resonance Fingerprinting Reconstruction Using Denoising and Self-Attention Pyramidal Convolutional Neural Network. SENSORS 2022; 22:s22031260. [PMID: 35162007 PMCID: PMC8838455 DOI: 10.3390/s22031260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/27/2022] [Accepted: 02/05/2022] [Indexed: 02/01/2023]
Abstract
Magnetic resonance fingerprinting (MRF) based on echo-planar imaging (EPI) enables whole-brain imaging to rapidly obtain T1 and T2* relaxation time maps. Reconstructing parametric maps from the MRF scanned baselines by the inner-product method is computationally expensive. We aimed to accelerate the reconstruction of parametric maps for MRF-EPI by using a deep learning model. The proposed approach uses a two-stage model that first eliminates noise and then regresses the parametric maps. Parametric maps obtained by dictionary matching were used as a reference and compared with the prediction results of the two-stage model. MRF-EPI scans were collected from 32 subjects. The signal-to-noise ratio increased significantly after the noise removal by the denoising model. For prediction with scans in the testing dataset, the mean absolute percentage errors between the standard and the final two-stage model were 3.1%, 3.2%, and 1.9% for T1, and 2.6%, 2.3%, and 2.8% for T2* in gray matter, white matter, and lesion locations, respectively. Our proposed two-stage deep learning model can effectively remove noise and accurately reconstruct MRF-EPI parametric maps, increasing the speed of reconstruction and reducing the storage space required by dictionaries.
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Affiliation(s)
- Jia-Sheng Hong
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; (J.-S.H.); (W.-K.L.)
| | - Ingo Hermann
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany; (I.H.); (F.G.Z.); (L.R.S.)
| | - Frank Gerrit Zöllner
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany; (I.H.); (F.G.Z.); (L.R.S.)
| | - Lothar R. Schad
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany; (I.H.); (F.G.Z.); (L.R.S.)
| | - Shuu-Jiun Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei 112, Taiwan;
- College of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Wei-Kai Lee
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; (J.-S.H.); (W.-K.L.)
| | - Yung-Lin Chen
- Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; (Y.-L.C.); (Y.C.)
| | - Yu Chang
- Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; (Y.-L.C.); (Y.C.)
| | - Yu-Te Wu
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; (Y.-L.C.); (Y.C.)
- Correspondence:
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Harnett NG, Stevens JS, Fani N, van Rooij SJH, Ely TD, Michopoulos V, Hudak L, Rothbaum AO, Hinrichs R, Winters SJ, Jovanovic T, Rothbaum BO, Nickerson LD, Ressler KJ. Acute Posttraumatic Symptoms Are Associated With Multimodal Neuroimaging Structural Covariance Patterns: A Possible Role for the Neural Substrates of Visual Processing in Posttraumatic Stress Disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:129-138. [PMID: 33012681 PMCID: PMC7954466 DOI: 10.1016/j.bpsc.2020.07.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 07/10/2020] [Accepted: 07/31/2020] [Indexed: 02/03/2023]
Abstract
BACKGROUND Although aspects of brain morphology have been associated with chronic posttraumatic stress disorder (PTSD), limited work has investigated multimodal patterns in brain morphology that are linked to acute posttraumatic stress severity. In the present study, we utilized multimodal magnetic resonance imaging to investigate if structural covariance networks (SCNs) assessed acutely following trauma were linked to acute posttraumatic stress severity. METHODS Structural magnetic resonance imaging data were collected around 1 month after civilian trauma exposure in 78 participants. Multimodal magnetic resonance imaging data fusion was completed to identify combinations of SCNs, termed structural covariance profiles (SCPs), related to acute posttraumatic stress severity collected at 1 month. Analyses assessed the relationship between participant SCP loadings, acute posttraumatic stress severity, the change in posttraumatic stress severity from 1 to 12 months, and depressive symptoms. RESULTS We identified an SCP that reflected greater gray matter properties of the anterior temporal lobe, fusiform face area, and visual cortex (i.e., the ventral visual stream) that varied curvilinearly with acute posttraumatic stress severity and the change in PTSD symptom severity from 1 to 12 months. The SCP was not associated with depressive symptoms. CONCLUSIONS We identified combinations of multimodal SCNs that are related to variability in PTSD symptoms in the early aftermath of trauma. The identified SCNs may reflect patterns of neuroanatomical organization that provide unique insight into acute posttraumatic stress. Furthermore, these multimodal SCNs may be potential candidates for neural markers of susceptibility to both acute posttraumatic stress and the future development of PTSD.
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Affiliation(s)
- Nathaniel G. Harnett
- Division of Depression and Anxiety, McLean Hospital,Department of Psychiatry, Harvard Medical School,Address correspondence to: Nathaniel G. Harnett, Ph.D., McLean Hospital, Mailstop 212, 115 Mill St, Belmont MA, 02478; Kerry J. Ressler, M.D., Ph.D
| | | | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University
| | | | - Timothy D. Ely
- Department of Psychiatry and Behavioral Sciences, Emory University
| | | | - Lauren Hudak
- Department of Emergency Medicine, Emory University
| | - Alex O. Rothbaum
- Department of Psychological Sciences, Case Western Reserve University
| | - Rebecca Hinrichs
- Department of Psychiatry and Behavioral Sciences, Emory University
| | - Sterling J. Winters
- Department of Psychiatry and Behavioral Sciences, Emory University,Department of Psychiatry and Behavioral Neuroscience, Wayne State University
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Sciences, Emory University,Department of Psychiatry and Behavioral Neuroscience, Wayne State University
| | | | - Lisa D. Nickerson
- Department of Psychiatry, Harvard Medical School,Applied Neuroimaging Statistics Laboratory, McLean Hospital
| | - Kerry J. Ressler
- Division of Depression and Anxiety, McLean Hospital,Department of Psychiatry, Harvard Medical School,Department of Psychiatry and Behavioral Sciences, Emory University,Address correspondence to: Nathaniel G. Harnett, Ph.D., McLean Hospital, Mailstop 212, 115 Mill St, Belmont MA, 02478; Kerry J. Ressler, M.D., Ph.D
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Zadbood A, Nastase S, Chen J, Norman KA, Hasson U. Neural representations of naturalistic events are updated as our understanding of the past changes. eLife 2022; 11:79045. [PMID: 36519530 PMCID: PMC9842385 DOI: 10.7554/elife.79045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 12/01/2022] [Indexed: 12/23/2022] Open
Abstract
The brain actively reshapes our understanding of past events in light of new incoming information. In the current study, we ask how the brain supports this updating process during the encoding and recall of naturalistic stimuli. One group of participants watched a movie ('The Sixth Sense') with a cinematic 'twist' at the end that dramatically changed the interpretation of previous events. Next, participants were asked to verbally recall the movie events, taking into account the new 'twist' information. Most participants updated their recall to incorporate the twist. Two additional groups recalled the movie without having to update their memories during recall: one group never saw the twist; another group was exposed to the twist prior to the beginning of the movie, and thus the twist information was incorporated both during encoding and recall. We found that providing participants with information about the twist beforehand altered neural response patterns during movie-viewing in the default mode network (DMN). Moreover, presenting participants with the twist at the end of the movie changed the neural representation of the previously-encoded information during recall in a subset of DMN regions. Further evidence for this transformation was obtained by comparing the neural activation patterns during encoding and recall and correlating them with behavioral signatures of memory updating. Our results demonstrate that neural representations of past events encoded in the DMN are dynamically integrated with new information that reshapes our understanding in natural contexts.
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Affiliation(s)
- Asieh Zadbood
- Department of Psychology, Columbia UniversityNew YorkUnited States
| | - Samuel Nastase
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
| | - Janice Chen
- Department of Psychological and Brain Sciences, Johns Hopkins UniversityBaltimoreUnited States
| | - Kenneth A Norman
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
| | - Uri Hasson
- Princeton Neuroscience Institute and Department of Psychology, Princeton UniversityPrincetonUnited States
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49
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Flannery JS, Riedel MC, Salo T, Poudel R, Laird AR, Gonzalez R, Sutherland MT. HIV infection is linked with reduced error-related default mode network suppression and poorer medication management abilities. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110398. [PMID: 34224796 PMCID: PMC8380727 DOI: 10.1016/j.pnpbp.2021.110398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 06/07/2021] [Accepted: 06/29/2021] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Brain activity linked with error processing has rarely been examined among persons living with HIV (PLWH) despite importance for monitoring and modifying behaviors that could lead to adverse health outcomes (e.g., medication non-adherence, drug use, risky sexual practices). Given that cannabis (CB) use is prevalent among PLWH and impacts error processing, we assessed the influence of HIV serostatus and chronic CB use on error-related brain activity while also considering associated implications for everyday functioning and clinically-relevant disease management behaviors. METHODS A sample of 109 participants, stratified into four groups by HIV and CB (HIV+/CB+, n = 32; HIV+/CB-, n = 27; HIV-/CB+, n = 28; HIV-/CB-, n = 22), underwent fMRI scanning while completing a modified Go/NoGo paradigm called the Error Awareness Task (EAT). Participants also completed a battery of well-validated instruments including a subjective report of everyday cognitive failures and an objective measure of medication management abilities. RESULTS Across all participants, we observed expected error-related anterior insula (aI) activation which correlated with better task performance (i.e., less errors) and, among HIV- participants, fewer self-reported cognitive failures. Regarding awareness, greater insula activation as well as greater posterior cingulate cortex (PCC) deactivation were notably linked with aware (vs. unaware) errors. Regarding group effects, unlike HIV- participants, PLWH displayed a lack of error-related deactivation in two default mode network (DMN) regions (i.e., PCC, medial prefrontal cortex [mPFC]). No CB main or interaction effects were detected. Across all participants, reduced error-related PCC deactivation correlated with reduced medication management abilities and PCC deactivation mediated the effect of HIV on such abilities. More lifetime CB use was linked with reduced error-related mPFC deactivation among HIV- participants and poorer medication management across CB users. CONCLUSIONS These results demonstrate that insufficient error-related DMN suppression linked with HIV infection, as well as chronic CB use among HIV- participants, has real-world consequences for medication management behaviors. We speculate that insufficient DMN suppression may reflect an inability to disengage task irrelevant mental operations, ultimately hindering error monitoring and behavior modification.
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Affiliation(s)
| | | | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL
| | - Ranjita Poudel
- Department of Psychology, Florida International University, Miami, FL
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL
| | - Raul Gonzalez
- Department of Psychology, Florida International University, Miami, FL
| | - Matthew T. Sutherland
- Department of Psychology, Florida International University, Miami, FL,Correspondence: Matthew T. Sutherland, Ph.D., Florida International University, Department of Psychology, AHC-4, RM 312, 11299 S.W. 8th St, Miami, FL 33199, , 305-348-7962
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50
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Loo C, Lee ACH, Buchsbaum BR. Multivariate FMRI Signatures of Learning in a Hebb Repetition Paradigm With Tone Sequences. Front Neurol 2021; 12:674275. [PMID: 34912281 PMCID: PMC8666569 DOI: 10.3389/fneur.2021.674275] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 11/08/2021] [Indexed: 11/24/2022] Open
Abstract
Important information from the environment often arrives to the brain in temporally extended sequences. Language, music, actions, and complex events generally unfold over time. When such informational sequences exceed the limited capacity of working memory, the human brain relies on its ability to accumulate information in long-term memory over several encounters with a complex stimulus. A longstanding question in psychology and neuroscience is whether the neural structures associated with working memory storage—often viewed as capacity limited and temporary—have any builtin ability to store information across longer temporal delays. According to the classic Hebbian dual memory theory, temporally local “activity traces” underlie immediate perception and working memory, whereas “structural traces” undergird long-term learning. Here we examine whether brain structures known to be involved in working maintenance of auditory sequences, such as area Spt, also show evidence of memory persistence across trials. We used representational similarity analysis (RSA) and the Hebb repetition paradigm with supracapacity tonal sequences to test whether repeated sequences have distinguishable multivoxel activity patterns in the auditory-motor networks of the brain. We found that, indeed, area Spt and other nodes of the auditory dorsal stream show multivoxel patterns for tone sequences that become gradually more distinct with repetition during working memory for supracapacity tone-sequences. The findings suggest that the structures are important for working memory are not “blank slates,” wiped clean from moment to moment, but rather encode information in a way can lead to cross-trial persistence.
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Affiliation(s)
- Corey Loo
- Rotman Research Institute, Baycrest, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Andy C H Lee
- Rotman Research Institute, Baycrest, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Bradley R Buchsbaum
- Rotman Research Institute, Baycrest, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
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