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Camassa A, Barbero-Castillo A, Bosch M, Dasilva M, Masvidal-Codina E, Villa R, Guimerà-Brunet A, Sanchez-Vives MV. Chronic full-band recordings with graphene microtransistors as neural interfaces for discrimination of brain states. NANOSCALE HORIZONS 2024; 9:589-597. [PMID: 38329118 DOI: 10.1039/d3nh00440f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Brain states such as sleep, anesthesia, wakefulness, or coma are characterized by specific patterns of cortical activity dynamics, from local circuits to full-brain emergent properties. We previously demonstrated that full-spectrum signals, including the infraslow component (DC, direct current-coupled), can be recorded acutely in multiple sites using flexible arrays of graphene solution-gated field-effect transistors (gSGFETs). Here, we performed chronic implantation of 16-channel gSGFET arrays over the rat cerebral cortex and recorded full-band neuronal activity with two objectives: (1) to test the long-term stability of implanted devices; and (2) to investigate full-band activity during the transition across different levels of anesthesia. First, we demonstrate it is possible to record full-band signals with stability, fidelity, and spatiotemporal resolution for up to 5.5 months using chronic epicortical gSGFET implants. Second, brain states generated by progressive variation of levels of anesthesia could be identified as traditionally using the high-pass filtered (AC, alternating current-coupled) spectrogram: from synchronous slow oscillations in deep anesthesia through to asynchronous activity in the awake state. However, the DC signal introduced a highly significant improvement for brain-state discrimination: the DC band provided an almost linear information prediction of the depth of anesthesia, with about 85% precision, using a trained algorithm. This prediction rose to about 95% precision when the full-band (AC + DC) spectrogram was taken into account. We conclude that recording infraslow activity using gSGFET interfaces is superior for the identification of brain states, and further supports the preclinical and clinical use of graphene neural interfaces for long-term recordings of cortical activity.
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Affiliation(s)
- A Camassa
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - A Barbero-Castillo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - M Bosch
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - M Dasilva
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - E Masvidal-Codina
- Instituto de Microelectrónica de Barcelona (IMB-CNM, CSIC), Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Spain
| | - R Villa
- Instituto de Microelectrónica de Barcelona (IMB-CNM, CSIC), Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Spain
| | - A Guimerà-Brunet
- Instituto de Microelectrónica de Barcelona (IMB-CNM, CSIC), Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Spain
| | - M V Sanchez-Vives
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- ICREA, Barcelona, Spain
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Ao Y, Yang C, Drewes J, Jiang M, Huang L, Jing X, Northoff G, Wang Y. Spatiotemporal dedifferentiation of the global brain signal topography along the adult lifespan. Hum Brain Mapp 2023; 44:5906-5918. [PMID: 37800366 PMCID: PMC10619384 DOI: 10.1002/hbm.26484] [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: 11/12/2022] [Revised: 08/17/2023] [Accepted: 08/28/2023] [Indexed: 10/07/2023] Open
Abstract
Age-related variations in many regions and/or networks of the human brain have been uncovered using resting-state functional magnetic resonance imaging. However, these findings did not account for the dynamical effect the brain's global activity (global signal [GS]) causes on local characteristics, which is measured by GS topography. To address this gap, we tested GS topography including its correlation with age using a large-scale cross-sectional adult lifespan dataset (n = 492). Both GS topography and its variation with age showed frequency-specific patterns, reflecting the spatiotemporal characteristics of the dynamic change of GS topography with age. A general trend toward dedifferentiation of GS topography with age was observed in both spatial (i.e., less differences of GS between different regions) and temporal (i.e., less differences of GS between different frequencies) dimensions. Further, methodological control analyses suggested that although most age-related dedifferentiation effects remained across different preprocessing strategies, some were triggered by neuro-vascular coupling and physiological noises. Together, these results provide the first evidence for age-related effects on global brain activity and its topographic-dynamic representation in terms of spatiotemporal dedifferentiation.
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Affiliation(s)
- Yujia Ao
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Chengxiao Yang
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Jan Drewes
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Muliang Jiang
- First Affiliated HospitalGuangxi Medical UniversityNanningChina
| | - Lihui Huang
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Xiujuan Jing
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Yifeng Wang
- Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
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Cattarinussi G, Grimaldi DA, Sambataro F. Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies. Schizophr Bull 2023; 49:1494-1507. [PMID: 38029279 PMCID: PMC10686347 DOI: 10.1093/schbul/sbad044] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND HYPOTHESIS Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal. STUDY DESIGN A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP. STUDY RESULTS We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples. CONCLUSIONS Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
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Wang J, Zhang W, Xu H, Ellenbroek B, Dai J, Wang L, Yan C, Wang W. The Changes of Histone Methylation Induced by Adolescent Social Stress Regulate the Resting-State Activity in mPFC. RESEARCH (WASHINGTON, D.C.) 2023; 6:0264. [PMID: 38434244 PMCID: PMC10907022 DOI: 10.34133/research.0264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/15/2023] [Indexed: 03/05/2024]
Abstract
Early-life stress can lead to sustained alterations in regional resting-state brain functions, but the underlying molecular mechanism remains unclear. Stress can also induce sustained changes in epigenetic modifications across brain regions, which are not limited to a few genes; rather, they often tend to produce global levels of change. The functional implication of these changes also remains to be elucidated. We hypothesize that global epigenetic changes may partly modulate the resting-state functions of brain regions to influence behavior. To test this hypothesis, we used an adolescent social stress (ASS) model in mice and examined the relationship between epigenetic modifications and regional resting-state brain activity using resting-state functional magnetic resonance imaging (rs-fMRI). The results showed that, compared to the control mice, the stressed mice showed increased anxiety and social avoidance behaviors and greater levels of dimethylation of histone H3 at lysine 9 (H3K9me2) in the medial prefrontal cortex (mPFC). In addition, the resting-state activity represented by the amplitude of low-frequency fluctuation (ALFF) was significantly lower in the mPFC of stressed mice. To verify the relationship of H3K9me2 and ALFF, the specific inhibition of H3Kme2 was performed by using the drug UNC0642, which reversed the anxiety behavior induced by ASS and significantly increase the ALFF value of mPFC in both normal and ASS animals. Our study is the first to report an association between histone modifications and rs-fMRI findings, providing a new perspective for understanding of the significance of regional brain epigenetic changes and a possible molecular explanation for rs-fMRI findings.
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Affiliation(s)
- Jiesi Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Wei Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Hang Xu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Bart Ellenbroek
- School of Psychology, Victoria University of Wellington, Kelburn, Wellington 6012, New Zealand
| | - Jiajie Dai
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Li Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chaogan Yan
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Weiwen Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
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5
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Li M, He L, Zhang Z, Li Z, Zhu X, Jiao C, Hu D. The decoupling between hemodynamic parameters and neural activity implies a complex origin of spontaneous brain oscillations. Front Comput Neurosci 2023; 17:1214793. [PMID: 37583895 PMCID: PMC10423917 DOI: 10.3389/fncom.2023.1214793] [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: 04/30/2023] [Accepted: 07/18/2023] [Indexed: 08/17/2023] Open
Abstract
Introduction Spontaneous low-frequency oscillations play a key role in brain activity. However, the underlying mechanism and origin of low-frequency oscillations remain under debate. Methods Optical imaging and an electrophysiological recording system were combined to investigate spontaneous oscillations in the hemodynamic parameters and neuronal activity of awake and anesthetized mice after Nω-nitro-L-arginine methyl ester (L-NAME) administration. Results The spectrum of local field potential (LFP) signals was significantly changed by L-NAME, which was further corroborated by the increase in energy and spatial synchronization. The important finding was that L-NAME triggered regular oscillations in both LFP signals and hemodynamic signals. Notably, the frequency peak of hemodynamic signals can be different from that of LFP oscillations in awake mice. Discussion A model of the neurovascular system was proposed to interpret this mismatch of peak frequencies, supporting the view that spontaneous low-frequency oscillations arise from multiple sources.
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Affiliation(s)
| | | | | | | | | | | | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
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6
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Untiet V, Beinlich FRM, Kusk P, Kang N, Ladrón-de-Guevara A, Song W, Kjaerby C, Andersen M, Hauglund N, Bojarowska Z, Sigurdsson B, Deng S, Hirase H, Petersen NC, Verkhratsky A, Nedergaard M. Astrocytic chloride is brain state dependent and modulates inhibitory neurotransmission in mice. Nat Commun 2023; 14:1871. [PMID: 37015909 PMCID: PMC10073105 DOI: 10.1038/s41467-023-37433-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 03/15/2023] [Indexed: 04/06/2023] Open
Abstract
Information transfer within neuronal circuits depends on the balance and recurrent activity of excitatory and inhibitory neurotransmission. Chloride (Cl-) is the major central nervous system (CNS) anion mediating inhibitory neurotransmission. Astrocytes are key homoeostatic glial cells populating the CNS, although the role of these cells in regulating excitatory-inhibitory balance remains unexplored. Here we show that astrocytes act as a dynamic Cl- reservoir regulating Cl- homoeostasis in the CNS. We found that intracellular chloride concentration ([Cl-]i) in astrocytes is high and stable during sleep. In awake mice astrocytic [Cl-]i is lower and exhibits large fluctuation in response to both sensory input and motor activity. Optogenetic manipulation of astrocytic [Cl-]i directly modulates neuronal activity during locomotion or whisker stimulation. Astrocytes thus serve as a dynamic source of extracellular Cl- available for GABAergic transmission in awake mice, which represents a mechanism for modulation of the inhibitory tone during sustained neuronal activity.
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Affiliation(s)
- Verena Untiet
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark.
| | - Felix R M Beinlich
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Peter Kusk
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Ning Kang
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Antonio Ladrón-de-Guevara
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, 14627, USA
| | - Wei Song
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Celia Kjaerby
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Mie Andersen
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Natalie Hauglund
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Zuzanna Bojarowska
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Björn Sigurdsson
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Saiyue Deng
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, P.R. China
| | - Hajime Hirase
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Nicolas C Petersen
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Alexei Verkhratsky
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark.
- Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.
- Achucarro Centre for Neuroscience, IKERBASQUE, Basque Foundation for Science, Plaza Euskadi 5, 48009, Bilbao, Spain.
| | - Maiken Nedergaard
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Copenhagen, 2200, Copenhagen, Denmark.
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, 14642, USA.
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Kida T, Tanaka E, Kakigi R, Inui K. Brain-wide network analysis of resting-state neuromagnetic data. Hum Brain Mapp 2023; 44:3519-3540. [PMID: 36988453 DOI: 10.1002/hbm.26295] [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: 09/11/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
The present study performed a brain-wide network analysis of resting-state magnetoencephalograms recorded from 53 healthy participants to visualize elaborate brain maps of phase- and amplitude-derived graph-theory metrics at different frequencies. To achieve this, we conducted a vertex-wise computation of threshold-independent graph metrics by combining proportional thresholding and a conjunction analysis and applied them to a correlation analysis of age and brain networks. Source power showed a frequency-dependent cortical distribution. Threshold-independent graph metrics derived from phase- and amplitude-based connectivity showed similar or different distributions depending on frequency. Vertex-wise age-brain correlation maps revealed that source power at the beta band and the amplitude-based degree at the alpha band changed with age in local regions. The present results indicate that a brain-wide analysis of neuromagnetic data has the potential to reveal neurophysiological network features in the human brain in a resting state.
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Affiliation(s)
- Tetsuo Kida
- Higher Brain Function Unit, Department of Functioning and Disability, Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai, Japan
- Department of Functioning and Disability, Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai, Japan
- Department of Integrative Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Section of Brain Function Information, Supportive Center for Brain Research, National Institute for Physiological Sciences, Okazaki, Japan
| | - Emi Tanaka
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Ryusuke Kakigi
- Department of Integrative Physiology, National Institute for Physiological Sciences, Okazaki, Japan
| | - Koji Inui
- Department of Functioning and Disability, Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai, Japan
- Department of Integrative Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Section of Brain Function Information, Supportive Center for Brain Research, National Institute for Physiological Sciences, Okazaki, Japan
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Ghatak S, Nakamura T, Lipton SA. Aberrant protein S-nitrosylation contributes to hyperexcitability-induced synaptic damage in Alzheimer's disease: Mechanistic insights and potential therapies. Front Neural Circuits 2023; 17:1099467. [PMID: 36817649 PMCID: PMC9932935 DOI: 10.3389/fncir.2023.1099467] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/18/2023] [Indexed: 02/05/2023] Open
Abstract
Alzheimer's disease (AD) is arguably the most common cause of dementia in the elderly and is marked by progressive synaptic degeneration, which in turn leads to cognitive decline. Studies in patients and in various AD models have shown that one of the early signatures of AD is neuronal hyperactivity. This excessive electrical activity contributes to dysregulated neural network function and synaptic damage. Mechanistically, evidence suggests that hyperexcitability accelerates production of reactive oxygen species (ROS) and reactive nitrogen species (RNS) that contribute to neural network impairment and synapse loss. This review focuses on the pathways and molecular changes that cause hyperexcitability and how RNS-dependent posttranslational modifications, represented predominantly by protein S-nitrosylation, mediate, at least in part, the deleterious effects of hyperexcitability on single neurons and the neural network, resulting in synaptic loss in AD.
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Affiliation(s)
- Swagata Ghatak
- School of Biological Sciences, National Institute of Science Education and Research, Bhubaneswar, India
| | - Tomohiro Nakamura
- Neurodegeneration New Medicines Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, United States,*Correspondence: Tomohiro Nakamura,
| | - Stuart A. Lipton
- Neurodegeneration New Medicines Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, United States,Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, United States,Stuart A. Lipton,
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9
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Fukai T. Computational models of Idling brain activity for memory processing. Neurosci Res 2022; 189:75-82. [PMID: 36592825 DOI: 10.1016/j.neures.2022.12.024] [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: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 01/01/2023]
Abstract
Studying the underlying neural mechanisms of cognitive functions of the brain is one of the central questions in modern biology. Moreover, it has significantly impacted the development of novel technologies in artificial intelligence. Spontaneous activity is a unique feature of the brain and is currently lacking in many artificially constructed intelligent machines. Spontaneous activity may represent the brain's idling states, which are internally driven by neuronal networks and possibly participate in offline processing during awake, sleep, and resting states. Evidence is accumulating that the brain's spontaneous activity is not mere noise but part of the mechanisms to process information about previous experiences. A bunch of literature has shown how previous sensory and behavioral experiences influence the subsequent patterns of brain activity with various methods in various animals. It seems, however, that the patterns of neural activity and their computational roles differ significantly from area to area and from function to function. In this article, I review the various forms of the brain's spontaneous activity, especially those observed during memory processing, and some attempts to model the generation mechanisms and computational roles of such activities.
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Affiliation(s)
- Tomoki Fukai
- Okinawa Institute of Science and Technology, Tancha 1919-1, Onna-son, Okinawa 904-0495, Japan.
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10
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Perez TM, Glue P, Adhia DB, Navid MS, Zeng J, Dillingham P, Smith M, Niazi IK, Young CK, De Ridder D. Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders. Trials 2022; 23:949. [DOI: 10.1186/s13063-022-06863-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/22/2022] [Indexed: 11/18/2022] Open
Abstract
Abstract
Background
The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.
Methods
We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.
Discussion
This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.
Trial registration
Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.
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Li J, Feng P, Zhao L, Chen J, Du M, Song J, Wu Y. Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise. CHAOS (WOODBURY, N.Y.) 2022; 32:113121. [PMID: 36456345 DOI: 10.1063/5.0124123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/17/2022] [Indexed: 06/17/2023]
Abstract
Epilepsy is a neurological disorder with recurrent seizures, which convey complex dynamical characteristics including chaos and randomness. Until now, the underlying mechanism has not been fully elucidated, especially the bistable property beneath the epileptic random induction phenomena in certain conditions. Inspired by the recent finding that astrocyte GTPase-activating protein (G-protein)-coupled receptors could be involved in stochastic epileptic seizures, we proposed a neuron-astrocyte network model, incorporating the noise of the astrocytic second messenger, inositol triphosphate (IP3) that is modulated by G-protein-coupled receptor activation. Based on this model, we have statistically analyzed the transitions of epileptic seizures by performing repeatable simulation trials. Our simulation results show that the increase in the IP3 noise intensity induces depolarization-block epileptic seizures together with an increase in neuronal firing frequency, consistent with corresponding experiments. Meanwhile, the bistable states of the seizure dynamics were present under certain noise intensities, during which the neuronal firing pattern switches between regular sparse spiking and epileptic seizure states. This random presence of epileptic seizures is absent when the noise intensity continues to increase, accompanying with an increase in the epileptic depolarization block duration. The simulation results also shed light on the fact that calcium signals in astrocytes play significant roles in the pattern formations of the epileptic seizure. Our results provide a potential pathway for understanding the epileptic randomness in certain conditions.
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Affiliation(s)
- Jiajia Li
- College of Information and Control Engineering, Xi'an University of Architecture and Technology, Shaanxi, Xi'an 710055, China
| | - Peihua Feng
- State Key Laboratory for Strength and Vibration of Mechanical Structures, National Demonstration Center for Experimental Mechanics Education, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Liang Zhao
- College of Information and Control Engineering, Xi'an University of Architecture and Technology, Shaanxi, Xi'an 710055, China
| | - Junying Chen
- College of Information and Control Engineering, Xi'an University of Architecture and Technology, Shaanxi, Xi'an 710055, China
| | - Mengmeng Du
- School of Mathematics and Data Science, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Jian Song
- Department of Neurosurgery, Wuhan General Hospital of PLA, Wuhan 430070, China
| | - Ying Wu
- State Key Laboratory for Strength and Vibration of Mechanical Structures, National Demonstration Center for Experimental Mechanics Education, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China
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12
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Schilling KG, Li M, Rheault F, Ding Z, Anderson AW, Kang H, Landman BA, Gore JC. Anomalous and heterogeneous characteristics of the BOLD hemodynamic response function in white matter. Cereb Cortex Commun 2022; 3:tgac035. [PMID: 36196360 PMCID: PMC9519945 DOI: 10.1093/texcom/tgac035] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/09/2022] [Accepted: 08/12/2022] [Indexed: 01/12/2023] Open
Abstract
Detailed knowledge of the BOLD hemodynamic response function (HRF) is crucial for accurate analyses and interpretation of functional MRI data. Considerable efforts have been made to characterize the HRF in gray matter (GM), but much less attention has been paid to BOLD effects in white matter (WM). However, several recent reports have demonstrated reliable detection and analyses of WM BOLD signals both after stimulation and in a resting state. WM and GM differ in composition, energy requirements, and blood flow, so their neurovascular couplings also may well be different. We aimed to derive a comprehensive characterization of the HRF in WM across a population, including accurate measurements of its shape and its variation along and between WM pathways, using resting-state fMRI acquisitions. Our results show that the HRF is significantly different between WM and GM. Features of the HRF, such as a prominent initial dip, show strong relationships with features of the tissue microstructure derived from diffusion imaging, and these relationships differ between WM and GM, consistent with BOLD signal fluctuations reflecting different energy demands and neurovascular couplings in tissues of different composition and function. We also show that the HRF varies in shape significantly along WM pathways and is different between different WM pathways, suggesting the temporal evolution of BOLD signals after an event vary in different parts of the WM. These features of the HRF in WM are especially relevant for interpretation of the biophysical basis of BOLD effects in WM.
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Affiliation(s)
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
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13
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Fortel I, Butler M, Korthauer LE, Zhan L, Ajilore O, Sidiropoulos A, Wu Y, Driscoll I, Schonfeld D, Leow A. Inferring excitation-inhibition dynamics using a maximum entropy model unifying brain structure and function. Netw Neurosci 2022; 6:420-444. [PMID: 35733430 PMCID: PMC9205431 DOI: 10.1162/netn_a_00220] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/07/2021] [Indexed: 11/04/2022] Open
Abstract
Neural activity coordinated across different scales from neuronal circuits to large-scale brain networks gives rise to complex cognitive functions. Bridging the gap between micro- and macroscale processes, we present a novel framework based on the maximum entropy model to infer a hybrid resting-state structural connectome, representing functional interactions constrained by structural connectivity. We demonstrate that the structurally informed network outperforms the unconstrained model in simulating brain dynamics, wherein by constraining the inference model with the network structure we may improve the estimation of pairwise BOLD signal interactions. Further, we simulate brain network dynamics using Monte Carlo simulations with the new hybrid connectome to probe connectome-level differences in excitation-inhibition balance between apolipoprotein E (APOE)-ε4 carriers and noncarriers. Our results reveal sex differences among APOE-ε4 carriers in functional dynamics at criticality; specifically, female carriers appear to exhibit a lower tolerance to network disruptions resulting from increased excitatory interactions. In sum, the new multimodal network explored here enables analysis of brain dynamics through the integration of structure and function, providing insight into the complex interactions underlying neural activity such as the balance of excitation and inhibition.
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Affiliation(s)
- Igor Fortel
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Mitchell Butler
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Laura E. Korthauer
- Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
- Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Yichao Wu
- Department of Math, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, USA
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
| | - Dan Schonfeld
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Alex Leow
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
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14
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Kang J, Jiao Z, Qin Y, Wang Y, Wang J, Jin L, Feng J, Wang F, Tang Y, Gong X. Associations between polygenic risk scores and amplitude of low-frequency fluctuation of inferior frontal gyrus in schizophrenia. J Psychiatr Res 2022; 147:4-12. [PMID: 34999338 DOI: 10.1016/j.jpsychires.2021.12.043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 12/14/2021] [Accepted: 12/20/2021] [Indexed: 10/19/2022]
Abstract
Schizophrenia (SCZ) is a serious and complex mental disorder with high heritability. Polygenic risk score (PRS) is a useful tool calculating the accumulating effects of multiple common genetic variants of schizophrenia. The amplitude of low-frequency fluctuation (ALFF) is an efficient index to reflect spontaneous, intrinsic neuronal activity. Aberrant ALFF of brain regions were reported in schizophrenia frequently, but the relationship between PRS and ALFF has not been studied. In the present study, we compared PRS and ALFF in 101 schizophrenia patients and 106 age-matched healthy controls to test their associations with schizophrenia. Then, the correlation of PRS with ALFF was measured to reveal the effect of polygenic risk on brain activity in schizophrenia. We found that schizophrenia patients showed significant differences in PRS and ALFF compared with controls. Twenty-six brain regions showed significant difference of ALFF between schizophrenia cases and controls, of which left inferior frontal gyrus, triangular part (IFGtriang.L) showed increased activity in schizophrenia. PRS-SCZ was positively correlated with ALFF in IFGtriang.L in 57 non-chronic patients. Genes involved in synaptic organization and transmission, especially in glutamatergic synapse, were highly enriched in PRS-SCZ genes, suggesting the dysfunction of synapses in schizophrenia. These results help to understand the molecular mechanism underlying schizophrenia and related brain dysfunction.
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Affiliation(s)
- Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Zeyu Jiao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Yue Qin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Yi Wang
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- School of Life Sciences, Fudan University, Shanghai, China; Human Phoneme Institute, Fudan University, Shanghai, China
| | - Li Jin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
| | - Fei Wang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, China.
| | - Xiaohong Gong
- School of Life Sciences, Fudan University, Shanghai, China.
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15
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Jafarian A, Wykes RC. Impact of DC-Coupled Electrophysiological Recordings for Translational Neuroscience: Case Study of Tracking Neural Dynamics in Rodent Models of Seizures. Front Comput Neurosci 2022; 16:900063. [PMID: 35936824 PMCID: PMC9351053 DOI: 10.3389/fncom.2022.900063] [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: 03/19/2022] [Accepted: 06/15/2022] [Indexed: 11/29/2022] Open
Abstract
We propose that to fully understand biological mechanisms underlying pathological brain activity with transitions (e.g., into and out of seizures), wide-bandwidth electrophysiological recordings are important. We demonstrate the importance of ultraslow potential shifts and infraslow oscillations for reliable tracking of synaptic physiology, within a neural mass model, from brain recordings that undergo pathological phase transitions. We use wide-bandwidth data (direct current (DC) to high-frequency activity), recorded using epidural and penetrating graphene micro-transistor arrays in a rodent model of acute seizures. Using this technological approach, we capture the dynamics of infraslow changes that contribute to seizure initiation (active pre-seizure DC shifts) and progression (passive DC shifts). By employing a continuous-discrete unscented Kalman filter, we track biological mechanisms from full-bandwidth data with and without active pre-seizure DC shifts during paroxysmal transitions. We then apply the same methodological approach for tracking the same parameters after application of high-pass-filtering >0.3Hz to both data sets. This approach reveals that ultraslow potential shifts play a fundamental role in the transition to seizure, and the use of high-pass-filtered data results in the loss of key information in regard to seizure onset and termination dynamics.
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Affiliation(s)
- Amirhossein Jafarian
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, United Kingdom
| | - Rob C Wykes
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Nanomedicine Lab, University of Manchester, Manchester, United Kingdom
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16
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Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans. PLoS Comput Biol 2021; 17:e1009386. [PMID: 34613970 PMCID: PMC8494321 DOI: 10.1371/journal.pcbi.1009386] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 08/28/2021] [Indexed: 12/12/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically detailed nonlinear model to find appropriate complexity (Akaike information criterion) to fit functional near-infrared spectroscopy (fNIRS) based measure of blood volume changes, called cerebrovascular reactivity (CVR), to high-definition (HD) tDCS. The grey-box linear model was applied on the fNIRS-based CVR during the first 150 seconds of anodal HD-tDCS in eleven healthy humans. The grey-box linear models for each of the four nested pathways starting from tDCS scalp current density that perturbed synaptic potassium released from active neurons for Pathway 1, astrocytic transmembrane current for Pathway 2, perivascular potassium concentration for Pathway 3, and voltage-gated ion channel current on the smooth muscle cell for Pathway 4 were fitted to the total hemoglobin concentration (tHb) changes from optodes in the vicinity of 4x1 HD-tDCS electrodes as well as on the contralateral sensorimotor cortex. We found that the tDCS perturbation Pathway 3 presented the least mean square error (MSE, median <2.5%) and the lowest Akaike information criterion (AIC, median -1.726) from the individual grey-box linear model fitting at the targeted-region. Then, minimal realization transfer function with reduced-order approximations of the grey-box model pathways was fitted to the ensemble average tHb time series. Again, Pathway 3 with nine poles and two zeros (all free parameters), provided the best Goodness of Fit of 0.0078 for Chi-Square difference test of nested pathways. Therefore, our study provided a systems biology approach to investigate the initial transient hemodynamic response to tDCS based on fNIRS tHb data. Future studies need to investigate the steady-state responses, including steady-state oscillations found to be driven by calcium dynamics, where transcranial alternating current stimulation may provide frequency-dependent physiological entrainment for system identification. We postulate that such a mechanistic understanding from system identification of the hemodynamics response to transcranial electrical stimulation can facilitate adequate delivery of the current density to the neurovascular tissue under simultaneous portable imaging in various cerebrovascular diseases.
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17
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Ghatak S, Dolatabadi N, Gao R, Wu Y, Scott H, Trudler D, Sultan A, Ambasudhan R, Nakamura T, Masliah E, Talantova M, Voytek B, Lipton SA. NitroSynapsin ameliorates hypersynchronous neural network activity in Alzheimer hiPSC models. Mol Psychiatry 2021; 26:5751-5765. [PMID: 32467645 PMCID: PMC7704704 DOI: 10.1038/s41380-020-0776-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 04/27/2020] [Accepted: 05/01/2020] [Indexed: 12/18/2022]
Abstract
Beginning at early stages, human Alzheimer's disease (AD) brains manifest hyperexcitability, contributing to subsequent extensive synapse loss, which has been linked to cognitive dysfunction. No current therapy for AD is disease-modifying. Part of the problem with AD drug discovery is that transgenic mouse models have been poor predictors of potential human treatment. While it is undoubtedly important to test drugs in these animal models, additional evidence for drug efficacy in a human context might improve our chances of success. Accordingly, in order to test drugs in a human context, we have developed a platform of physiological assays using patch-clamp electrophysiology, calcium imaging, and multielectrode array (MEA) experiments on human (h)iPSC-derived 2D cortical neuronal cultures and 3D cerebral organoids. We compare hiPSCs bearing familial AD mutations vs. their wild-type (WT) isogenic controls in order to characterize the aberrant electrical activity in such a human context. Here, we show that these AD neuronal cultures and organoids manifest increased spontaneous action potentials, slow oscillatory events (~1 Hz), and hypersynchronous network activity. Importantly, the dual-allosteric NMDAR antagonist NitroSynapsin, but not the FDA-approved drug memantine, abrogated this hyperactivity. We propose a novel model of synaptic plasticity in which aberrant neural networks are rebalanced by NitroSynapsin. We propose that hiPSC models may be useful for screening drugs to treat hyperexcitability and related synaptic damage in AD.
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Affiliation(s)
- Swagata Ghatak
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA.,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Nima Dolatabadi
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA.,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Richard Gao
- Cognitive Science, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Yin Wu
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Henry Scott
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Dorit Trudler
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA.,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Abdullah Sultan
- Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Rajesh Ambasudhan
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA.,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Tomohiro Nakamura
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Eliezer Masliah
- Department of Pathology, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.,National Institute on Aging, NIH, Bethesda, MD, 20892, USA
| | - Maria Talantova
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA.,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA
| | - Bradley Voytek
- Cognitive Science, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.,Kavli Institute of Brain and Mind and Halicioglu Data Science Institute, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Stuart A Lipton
- Neuroscience Translational Center and Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, 92037, USA. .,Neurodegenerative Disease Center, Scintillon Institute, San Diego, CA, 92121, USA. .,Department of Neurosciences, School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.
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18
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Lei T, Liao X, Chen X, Zhao T, Xu Y, Xia M, Zhang J, Xia Y, Sun X, Wei Y, Men W, Wang Y, Hu M, Zhao G, Du B, Peng S, Chen M, Wu Q, Tan S, Gao JH, Qin S, Tao S, Dong Q, He Y. Progressive Stabilization of Brain Network Dynamics during Childhood and Adolescence. Cereb Cortex 2021; 32:1024-1039. [PMID: 34378030 DOI: 10.1093/cercor/bhab263] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/14/2022] Open
Abstract
Functional brain networks require dynamic reconfiguration to support flexible cognitive function. However, the developmental principles shaping brain network dynamics remain poorly understood. Here, we report the longitudinal development of large-scale brain network dynamics during childhood and adolescence, and its connection with gene expression profiles. Using a multilayer network model, we show the temporally varying modular architecture of child brain networks, with higher network switching primarily in the association cortex and lower switching in the primary regions. This topographical profile exhibits progressive maturation, which manifests as reduced modular dynamics, particularly in the transmodal (e.g., default-mode and frontoparietal) and sensorimotor regions. These developmental refinements mediate age-related enhancements of global network segregation and are linked with the expression profiles of genes associated with the enrichment of ion transport and nucleobase-containing compound transport. These results highlight a progressive stabilization of brain dynamics, which expand our understanding of the neural mechanisms that underlie cognitive development.
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Affiliation(s)
- Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Xiaodan Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yunman Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xiaochen Sun
- Department of Linguistics, Beijing Language and Culture University, Beijing 100083, China
| | - Yongbin Wei
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Mingming Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Bin Du
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Siya Peng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Menglu Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.,Chinese Institute for Brain Research, Beijing 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.,Chinese Institute for Brain Research, Beijing 102206, China
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19
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Raut RV, Snyder AZ, Mitra A, Yellin D, Fujii N, Malach R, Raichle ME. Global waves synchronize the brain's functional systems with fluctuating arousal. SCIENCE ADVANCES 2021; 7:7/30/eabf2709. [PMID: 34290088 PMCID: PMC8294763 DOI: 10.1126/sciadv.abf2709] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 06/04/2021] [Indexed: 05/04/2023]
Abstract
We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure ("functional connectivity") of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.
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Affiliation(s)
- Ryan V Raut
- Department of Radiology, Washington University, St. Louis, MO 63110, USA.
| | - Abraham Z Snyder
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Psychiatry, Stanford University, Stanford, CA 94305, USA
| | - Dov Yellin
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Naotaka Fujii
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Rafael Malach
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Marcus E Raichle
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
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20
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Habas C. Functional Connectivity of the Cognitive Cerebellum. Front Syst Neurosci 2021; 15:642225. [PMID: 33897382 PMCID: PMC8060696 DOI: 10.3389/fnsys.2021.642225] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/11/2021] [Indexed: 12/19/2022] Open
Abstract
Anatomical tracing, human clinical data, and stimulation functional imaging have firmly established the major role of the (neo-)cerebellum in cognition and emotion. Telencephalization characterized by the great expansion of associative cortices, especially the prefrontal one, has been associated with parallel expansion of the neocerebellar cortex, especially the lobule VII, and by an increased number of interconnections between these two cortical structures. These anatomical modifications underlie the implication of the neocerebellum in cognitive control of complex motor and non-motor tasks. In humans, resting state functional connectivity has been used to determine a thorough anatomo-functional parcellation of the neocerebellum. This technique has identified central networks involving the neocerebellum and subserving its cognitive function. Neocerebellum participates in all intrinsic connected networks such as central executive, default mode, salience, dorsal and ventral attentional, and language-dedicated networks. The central executive network constitutes the main circuit represented within the neocerebellar cortex. Cerebellar zones devoted to these intrinsic networks appear multiple, interdigitated, and spatially ordered in three gradients. Such complex neocerebellar organization enables the neocerebellum to monitor and synchronize the main networks involved in cognition and emotion, likely by computing internal models.
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Affiliation(s)
- Christophe Habas
- Service de NeuroImagerie, Centre Hospitalier National d'Ophtalmologie des 15-20, Paris, France
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21
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Redolfi N, Lodovichi C. Spontaneous Afferent Activity Carves Olfactory Circuits. Front Cell Neurosci 2021; 15:637536. [PMID: 33767612 PMCID: PMC7985084 DOI: 10.3389/fncel.2021.637536] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 02/08/2021] [Indexed: 12/11/2022] Open
Abstract
Electrical activity has a key role in shaping neuronal circuits during development. In most sensory modalities, early in development, internally generated spontaneous activity sculpts the initial layout of neuronal wiring. With the maturation of the sense organs, the system relies more on sensory-evoked electrical activity. Stimuli-driven neuronal discharge is required for the transformation of immature circuits in the specific patterns of neuronal connectivity that subserve normal brain function. The olfactory system (OS) differs from this organizational plan. Despite the important role of odorant receptors (ORs) in shaping olfactory topography, odor-evoked activity does not have a prominent role in refining neuronal wiring. On the contrary, afferent spontaneous discharge is required to achieve and maintain the specific diagram of connectivity that defines the topography of the olfactory bulb (OB). Here, we provide an overview of the development of olfactory topography, with a focus on the role of afferent spontaneous discharge in the formation and maintenance of the specific synaptic contacts that result in the topographic organization of the OB.
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Affiliation(s)
- Nelly Redolfi
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| | - Claudia Lodovichi
- Department of Biomedical Sciences, University of Padua, Padua, Italy.,Neuroscience Institute CNR, Padua, Italy.,Veneto Institute of Molecular Medicine, Padua, Italy.,Padova Neuroscience Center, University of Padua, Padua, Italy
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22
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Hubbard NA, Turner MP, Sitek KR, West KL, Kaczmarzyk JR, Himes L, Thomas BP, Lu H, Rypma B. Resting cerebral oxygen metabolism exhibits archetypal network features. Hum Brain Mapp 2021; 42:1952-1968. [PMID: 33544446 PMCID: PMC8046048 DOI: 10.1002/hbm.25352] [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: 07/28/2020] [Revised: 12/04/2020] [Accepted: 01/12/2021] [Indexed: 12/23/2022] Open
Abstract
Standard magnetic resonance imaging approaches offer high‐resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low‐frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual‐echo, pseudocontinuous arterial spin labeling, and blood‐oxygen‐level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain‐wide, CMRO2 low‐frequency fluctuations were subjected to graph‐based and voxel‐wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small‐world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel‐wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting‐state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital‐visual). These are the first findings to support the use of calibration‐derived CMRO2 low‐frequency fluctuations for detecting brain‐wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration‐derived oxygen metabolism signals for examining the intrinsic organization of the human brain.
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Affiliation(s)
- Nicholas A Hubbard
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Monroe P Turner
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Kevin R Sitek
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, USA
| | - Kathryn L West
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Jakub R Kaczmarzyk
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Lyndahl Himes
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Binu P Thomas
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Hanzhang Lu
- Department of Radiology, John's Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Bart Rypma
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA.,Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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23
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Garcia-Cortadella R, Schwesig G, Jeschke C, Illa X, Gray AL, Savage S, Stamatidou E, Schiessl I, Masvidal-Codina E, Kostarelos K, Guimerà-Brunet A, Sirota A, Garrido JA. Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. Nat Commun 2021; 12:211. [PMID: 33431878 PMCID: PMC7801381 DOI: 10.1038/s41467-020-20546-w] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 12/08/2020] [Indexed: 01/29/2023] Open
Abstract
Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces.
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Affiliation(s)
- R Garcia-Cortadella
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain
| | - G Schwesig
- Bernstein Center for Computational Neuroscience Munich, Faculty of Medicine, Ludwig-Maximilians Universität München, Planegg-Martinsried, Germany
| | - C Jeschke
- Multi Channel Systems (MCS) GmbH, Reutlingen, Germany
| | - X Illa
- Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Anna L Gray
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK
| | - S Savage
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK
| | - E Stamatidou
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK
| | - I Schiessl
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - E Masvidal-Codina
- Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - K Kostarelos
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK
| | - A Guimerà-Brunet
- Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - A Sirota
- Bernstein Center for Computational Neuroscience Munich, Faculty of Medicine, Ludwig-Maximilians Universität München, Planegg-Martinsried, Germany.
| | - J A Garrido
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain.
- ICREA, Pg. Lluís Companys 23, 08010, Barcelona, Spain.
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24
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Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning. Mol Psychiatry 2021; 26:2991-3002. [PMID: 33005028 PMCID: PMC8505253 DOI: 10.1038/s41380-020-00892-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 08/27/2020] [Accepted: 09/15/2020] [Indexed: 12/31/2022]
Abstract
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.
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25
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Perez C, Felix L, Durry S, Rose CR, Ullah G. On the origin of ultraslow spontaneous Na + fluctuations in neurons of the neonatal forebrain. J Neurophysiol 2020; 125:408-425. [PMID: 33236936 DOI: 10.1152/jn.00373.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Spontaneous neuronal and astrocytic activity in the neonate forebrain is believed to drive the maturation of individual cells and their integration into complex brain-region-specific networks. The previously reported forms include bursts of electrical activity and oscillations in intracellular Ca2+ concentration. Here, we use ratiometric Na+ imaging to demonstrate spontaneous fluctuations in the intracellular Na+ concentration of CA1 pyramidal neurons and astrocytes in tissue slices obtained from the hippocampus of mice at postnatal days 2-4 (P2-4). These occur at very low frequency (∼2/h), can last minutes with amplitudes up to several millimolar, and mostly disappear after the first postnatal week. To further investigate their mechanisms, we model a network consisting of pyramidal neurons and interneurons. Experimentally observed Na+ fluctuations are mimicked when GABAergic inhibition in the simulated network is made depolarizing. Both our experiments and computational model show that blocking voltage-gated Na+ channels or GABAergic signaling significantly diminish the neuronal Na+ fluctuations. On the other hand, blocking a variety of other ion channels, receptors, or transporters including glutamatergic pathways does not have significant effects. Our model also shows that the amplitude and duration of Na+ fluctuations decrease as we increase the strength of glial K+ uptake. Furthermore, neurons with smaller somatic volumes exhibit fluctuations with higher frequency and amplitude. As opposed to this, larger extracellular to intracellular volume ratio observed in neonatal brain exerts a dampening effect. Finally, our model predicts that these periods of spontaneous Na+ influx leave neonatal neuronal networks more vulnerable to seizure-like states when compared with mature brain.NEW & NOTEWORTHY Spontaneous activity in the neonate forebrain plays a key role in cell maturation and brain development. We report spontaneous, ultraslow, asynchronous fluctuations in the intracellular Na+ concentration of neurons and astrocytes. We show that this activity is not correlated with the previously reported synchronous neuronal population bursting or Ca2+ oscillations, both of which occur at much faster timescales. Furthermore, extracellular K+ concentration remains nearly constant. The spontaneous Na+ fluctuations disappear after the first postnatal week.
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Affiliation(s)
- Carlos Perez
- Department of Physics, University of South Florida, Tampa, Florida
| | - Lisa Felix
- Faculty of Mathematics and Natural Sciences, Institute of Neurobiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Simone Durry
- Faculty of Mathematics and Natural Sciences, Institute of Neurobiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christine R Rose
- Faculty of Mathematics and Natural Sciences, Institute of Neurobiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ghanim Ullah
- Department of Physics, University of South Florida, Tampa, Florida
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26
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Wang Y, Zou Q, Ao Y, Liu Y, Ouyang Y, Wang X, Biswal B, Cui Q, Chen H. Frequency-dependent circuits anchored in the dorsal and ventral left anterior insula. Sci Rep 2020; 10:16394. [PMID: 33020498 PMCID: PMC7536237 DOI: 10.1038/s41598-020-73192-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Accepted: 09/08/2020] [Indexed: 11/08/2022] Open
Abstract
The hub role of the right anterior insula (AI) has been emphasized in cognitive neurosciences and been demonstrated to be frequency-dependently organized. However, the functional organization of left AI (LAI) has not been systematically investigated. Here we used 100 unrelated datasets from the Human Connectome Project to study the frequency-dependent organization of LAI along slow 6 to slow 1 bands. The broadband functional connectivity of LAI was similar to previous findings. In slow 6-slow 3 bands, both dorsal and ventral seeds in LAI were correlated to the salience network (SN) and language network (LN) and anti-correlated to the default mode network (DMN). However, these seeds were only correlated to the LAI in slow 2-slow 1 bands. These findings indicate that broadband and narrow band functional connections reflect different functional organizations of the LAI. Furthermore, the dorsal seed had a stronger connection with the LN and anti-correlation with DMN while the ventral seed had a stronger connection within the SN in slow 6-slow 3 bands. In slow 2-slow 1 bands, both seeds had stronger connections with themselves. These observations indicate distinctive functional organizations for the two parts of LAI. Significant frequency effect and frequency by seed interaction were also found, suggesting different frequency characteristics of these two seeds. The functional integration and functional segregation of LDAI and LVAI were further supported by their cognitive associations. The frequency- and seed-dependent functional organizations of LAI may enlighten future clinical and cognitive investigations.
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Affiliation(s)
- Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, China.
| | - Qijun Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, Chengdu, 611731, China
| | - Yujia Ao
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, China
| | - Yang Liu
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, China
| | - Yujie Ouyang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, China
| | - Xinqi Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, Chengdu, 611731, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, Chengdu, 611731, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, 607 Fenster Hall,University Height, Newark, NJ, 07102, USA
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, Chengdu, 611731, China.
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27
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Rasmussen R, O'Donnell J, Ding F, Nedergaard M. Interstitial ions: A key regulator of state-dependent neural activity? Prog Neurobiol 2020; 193:101802. [PMID: 32413398 PMCID: PMC7331944 DOI: 10.1016/j.pneurobio.2020.101802] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 03/24/2020] [Accepted: 03/26/2020] [Indexed: 02/08/2023]
Abstract
Throughout the nervous system, ion gradients drive fundamental processes. Yet, the roles of interstitial ions in brain functioning is largely forgotten. Emerging literature is now revitalizing this area of neuroscience by showing that interstitial cations (K+, Ca2+ and Mg2+) are not static quantities but change dynamically across states such as sleep and locomotion. In turn, these state-dependent changes are capable of sculpting neuronal activity; for example, changing the local interstitial ion composition in the cortex is sufficient for modulating the prevalence of slow-frequency neuronal oscillations, or potentiating the gain of visually evoked responses. Disturbances in interstitial ionic homeostasis may also play a central role in the pathogenesis of central nervous system diseases. For example, impairments in K+ buffering occur in a number of neurodegenerative diseases, and abnormalities in neuronal activity in disease models disappear when interstitial K+ is normalized. Here we provide an overview of the roles of interstitial ions in physiology and pathology. We propose the brain uses interstitial ion signaling as a global mechanism to coordinate its complex activity patterns, and ion homeostasis failure contributes to central nervous system diseases affecting cognitive functions and behavior.
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Affiliation(s)
- Rune Rasmussen
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
| | - John O'Donnell
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY, 14642, United States
| | - Fengfei Ding
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY, 14642, United States
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark; Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY, 14642, United States.
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28
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Okun M, Steinmetz NA, Lak A, Dervinis M, Harris KD. Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales. Cereb Cortex 2020; 29:2196-2210. [PMID: 30796825 PMCID: PMC6458908 DOI: 10.1093/cercor/bhz023] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/26/2019] [Accepted: 01/28/2019] [Indexed: 12/20/2022] Open
Abstract
Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms–1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons’ spiking activity and its coupling to local population rate and to arousal level across 0.01–100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons’ population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.
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Affiliation(s)
- Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK.,Institute of Neurology, University College London, London, UK
| | | | - Armin Lak
- Institute of Neurology, University College London, London, UK
| | - Martynas Dervinis
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
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29
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Aedo-Jury F, Schwalm M, Hamzehpour L, Stroh A. Brain states govern the spatio-temporal dynamics of resting-state functional connectivity. eLife 2020; 9:53186. [PMID: 32568067 PMCID: PMC7329332 DOI: 10.7554/elife.53186] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 06/18/2020] [Indexed: 01/08/2023] Open
Abstract
Previously, using simultaneous resting-state functional magnetic resonance imaging (fMRI) and photometry-based neuronal calcium recordings in the anesthetized rat, we identified blood oxygenation level-dependent (BOLD) responses directly related to slow calcium waves, revealing a cortex-wide and spatially organized correlate of locally recorded neuronal activity (Schwalm et al., 2017). Here, using the same techniques, we investigate two distinct cortical activity states: persistent activity, in which compartmentalized network dynamics were observed; and slow wave activity, dominated by a cortex-wide BOLD component, suggesting a strong functional coupling of inter-cortical activity. During slow wave activity, we find a correlation between the occurring slow wave events and the strength of functional connectivity between different cortical areas. These findings suggest that down-up transitions of neuronal excitability can drive cortex-wide functional connectivity. This study provides further evidence that changes in functional connectivity are dependent on the brain's current state, directly linked to the generation of slow waves.
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Affiliation(s)
- Felipe Aedo-Jury
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
| | - Miriam Schwalm
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States
| | - Lara Hamzehpour
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany
| | - Albrecht Stroh
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
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30
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Decoding Task-Specific Cognitive States with Slow, Directed Functional Networks in the Human Brain. eNeuro 2020; 7:ENEURO.0512-19.2019. [PMID: 32265196 PMCID: PMC7358332 DOI: 10.1523/eneuro.0512-19.2019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 12/12/2019] [Indexed: 12/02/2022] Open
Abstract
Flexible functional interactions among brain regions mediate critical cognitive functions. Such interactions can be measured using functional magnetic resonance imaging (fMRI) data either with instantaneous (zero-lag) or lag-based (time-lagged) functional connectivity. Because the fMRI hemodynamic response is slow, and is sampled at a timescale (seconds) several orders of magnitude slower than the underlying neural dynamics (milliseconds), simulation studies have shown that lag-based fMRI functional connectivity, measured with approaches like Granger–Geweke causality (GC), provides spurious and unreliable estimates of underlying neural interactions. Experimental verification of this claim is challenging because neural ground truth connectivity is often unavailable concurrently with fMRI recordings. Here we demonstrate that, despite these widely held caveats, GC networks estimated from fMRI recordings contain useful information for classifying task-specific cognitive states. We estimated instantaneous and lag-based GC functional connectivity networks using fMRI data from 1000 participants (Human Connectome Project database). A linear classifier, trained on either instantaneous or lag-based GC, reliably discriminated among seven different task and resting brain states, with >80% cross-validation accuracy. With network simulations, we demonstrate that instantaneous and lag-based GC exploited interactions at fast and slow timescales, respectively, to achieve robust classification. With human fMRI data, instantaneous and lag-based GC identified complementary, task–core networks. Finally, variations in GC connectivity explained inter-individual variations in a variety of cognitive scores. Our findings show that instantaneous and lag-based methods reveal complementary aspects of functional connectivity in the brain, and suggest that slow, directed functional interactions, estimated with fMRI, may provide useful markers of behaviorally relevant cognitive states.
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31
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Siems M, Siegel M. Dissociated neuronal phase- and amplitude-coupling patterns in the human brain. Neuroimage 2020; 209:116538. [PMID: 31935522 PMCID: PMC7068703 DOI: 10.1016/j.neuroimage.2020.116538] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 01/09/2020] [Accepted: 01/10/2020] [Indexed: 02/07/2023] Open
Abstract
Coupling of neuronal oscillations may reflect and facilitate the communication between neuronal populations. Two primary neuronal coupling modes have been described: phase-coupling and amplitude-coupling. Theoretically, both coupling modes are independent, but so far, their neuronal relationship remains unclear. Here, we combined MEG, source-reconstruction and simulations to systematically compare cortical amplitude-coupling and phase-coupling patterns in the human brain. Importantly, we took into account a critical bias of amplitude-coupling measures due to phase-coupling. We found differences between both coupling modes across a broad frequency range and most of the cortex. Furthermore, by combining empirical measurements and simulations we ruled out that these results were caused by methodological biases, but instead reflected genuine neuronal amplitude coupling. Our results show that cortical phase- and amplitude-coupling patterns are non-redundant, which may reflect at least partly distinct neuronal mechanisms. Furthermore, our findings highlight and clarify the compound nature of amplitude coupling measures.
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Affiliation(s)
- Marcus Siems
- Centre for Integrative Neuroscience, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; MEG Center, University of Tübingen, Germany; IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Germany.
| | - Markus Siegel
- Centre for Integrative Neuroscience, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; MEG Center, University of Tübingen, Germany.
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Abstract
To better understand how diet influences brain aging, we focus here on the presymptomatic period during which prevention may be most effective. Large-scale life span neuroimaging datasets show functional communication between brain regions destabilizes with age, typically starting in the late 40s, and that destabilization correlates with poorer cognition and accelerates with insulin resistance. Targeted experiments show that this biomarker for brain aging is reliably modulated with consumption of different fuel sources: Glucose decreases, and ketones increase the stability of brain networks. This effect replicated across both changes to total diet as well as fuel-specific calorie-matched bolus, producing changes in overall brain activity that suggest that network “switching” may reflect the brain’s adaptive response to conserve energy under resource constraint. Epidemiological studies suggest that insulin resistance accelerates progression of age-based cognitive impairment, which neuroimaging has linked to brain glucose hypometabolism. As cellular inputs, ketones increase Gibbs free energy change for ATP by 27% compared to glucose. Here we test whether dietary changes are capable of modulating sustained functional communication between brain regions (network stability) by changing their predominant dietary fuel from glucose to ketones. We first established network stability as a biomarker for brain aging using two large-scale (n = 292, ages 20 to 85 y; n = 636, ages 18 to 88 y) 3 T functional MRI (fMRI) datasets. To determine whether diet can influence brain network stability, we additionally scanned 42 adults, age < 50 y, using ultrahigh-field (7 T) ultrafast (802 ms) fMRI optimized for single-participant-level detection sensitivity. One cohort was scanned under standard diet, overnight fasting, and ketogenic diet conditions. To isolate the impact of fuel type, an independent overnight fasted cohort was scanned before and after administration of a calorie-matched glucose and exogenous ketone ester (d-β-hydroxybutyrate) bolus. Across the life span, brain network destabilization correlated with decreased brain activity and cognitive acuity. Effects emerged at 47 y, with the most rapid degeneration occurring at 60 y. Networks were destabilized by glucose and stabilized by ketones, irrespective of whether ketosis was achieved with a ketogenic diet or exogenous ketone ester. Together, our results suggest that brain network destabilization may reflect early signs of hypometabolism, associated with dementia. Dietary interventions resulting in ketone utilization increase available energy and thus may show potential in protecting the aging brain.
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Medel V, Valdés J, Castro S, Ossandón T, Boncompte G. Commentary: Amplification and Suppression of Distinct Brainwide Activity Patterns by Catecholamines. Front Behav Neurosci 2019; 13:217. [PMID: 31619976 PMCID: PMC6759507 DOI: 10.3389/fnbeh.2019.00217] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 09/02/2019] [Indexed: 12/29/2022] Open
Affiliation(s)
- Vicente Medel
- Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile.,Neurodynamics of Cognition Laboratory, Departamento de Psiquiatría, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Joaquín Valdés
- Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile.,Neurodynamics of Cognition Laboratory, Departamento de Psiquiatría, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Samy Castro
- Neural Dynamics Laboratory, Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaíso, Chile.,Programa de Doctorado en Ciencias, Mención Neurociencia, Universidad de Valparaíso, Valparaíso, Chile
| | - Tomás Ossandón
- Neurodynamics of Cognition Laboratory, Departamento de Psiquiatría, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Gonzalo Boncompte
- Neurodynamics of Cognition Laboratory, Departamento de Psiquiatría, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
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Rasmussen R, Nicholas E, Petersen NC, Dietz AG, Xu Q, Sun Q, Nedergaard M. Cortex-wide Changes in Extracellular Potassium Ions Parallel Brain State Transitions in Awake Behaving Mice. Cell Rep 2019; 28:1182-1194.e4. [PMID: 31365863 PMCID: PMC6790006 DOI: 10.1016/j.celrep.2019.06.082] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 06/01/2019] [Accepted: 06/24/2019] [Indexed: 12/21/2022] Open
Abstract
Brain state fluctuations modulate sensory processing, but the factors governing state-dependent neural activity remain unclear. Here, we tracked the dynamics of cortical extracellular K+ concentrations ([K+]o) during awake state transitions and manipulated [K+]o in slices, during visual processing, and during skilled motor execution. When mice transitioned from quiescence to locomotion, [K+]o increased by 0.6-1.0 mM in all cortical areas analyzed, and this preceded locomotion by 1 s. Emulating the state-dependent [K+]o increase in cortical slices caused neuronal depolarization and enhanced input-output transformation. In vivo, locomotion increased the gain of visually evoked responses in layer 2/3 of visual cortex; this effect was recreated by imposing a [K+]o increase. Elevating [K+]o in the motor cortex increased movement-induced neuronal spiking in layer 5 and improved motor performance. Thus, [K+]o increases in a cortex-wide state-dependent manner, and this [K+]o increase affects both sensory and motor processing through the dynamic modulation of neural activity.
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Affiliation(s)
- Rune Rasmussen
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
| | - Eric Nicholas
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Nicolas Caesar Petersen
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Andrea Grostøl Dietz
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Qiwu Xu
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Qian Sun
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA; Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
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35
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Nijs J, Leysen L, Vanlauwe J, Logghe T, Ickmans K, Polli A, Malfliet A, Coppieters I, Huysmans E. Treatment of central sensitization in patients with chronic pain: time for change? Expert Opin Pharmacother 2019; 20:1961-1970. [DOI: 10.1080/14656566.2019.1647166] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Jo Nijs
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Chronic pain rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital Brussels, Brussels, Belgium
| | - Laurence Leysen
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Johan Vanlauwe
- Department of Public Health (GEWE), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Tine Logghe
- Department of Orthopaedics, University Hospital Brussels, Brussels, Belgium
| | - Kelly Ickmans
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Chronic pain rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital Brussels, Brussels, Belgium
- Department of Physical and Rehabilitation Medicine, AZ Sint Dimpna hospital, Geel, Belgium
| | - Andrea Polli
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Physical and Rehabilitation Medicine, AZ Sint Dimpna hospital, Geel, Belgium
| | - Anneleen Malfliet
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Chronic pain rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital Brussels, Brussels, Belgium
- Department of Physical and Rehabilitation Medicine, AZ Sint Dimpna hospital, Geel, Belgium
- Research Foundation – Flanders (FWO), Brussels, Belgium
| | - Iris Coppieters
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Chronic pain rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital Brussels, Brussels, Belgium
- Research Foundation – Flanders (FWO), Brussels, Belgium
| | - Eva Huysmans
- Pain in Motion International Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Chronic pain rehabilitation, Department of Physical Medicine and Physiotherapy, University Hospital Brussels, Brussels, Belgium
- Department of Physical and Rehabilitation Medicine, AZ Sint Dimpna hospital, Geel, Belgium
- Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
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36
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Hou H, Sun B, Meng Q. Slow cortical potential signal classification using concave-convex feature. J Neurosci Methods 2019; 324:108303. [PMID: 31185416 DOI: 10.1016/j.jneumeth.2019.05.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Revised: 05/22/2019] [Accepted: 05/22/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND The classification of the slow cortical potential (SCP) signals plays a key role in a variety of research areas, including disease diagnostics, human-machine interaction, and education. The widely used classification methods, which combine multiple kinds of features, can be unsuitable in practical applications due to their low robustness to scenario changes. NEW METHOD A flexible concave-convex (C-C) feature is reported. The C-C feature is extracted by two steps: (1) the low-frequency node coefficients of the SCP signals are first extracted using wavelet packet decomposition; (2) then the underlying trend of the low-frequency node coefficients is estimated using third-order polynomial fitting, and the feature is constructed using the minimum and maximum second derivative values of the trend curve as |ymin| - ymax where y is the second derivative value. RESULTS Experimental results on real datasets reveal that our method with the single C-C feature exhibits high average classification accuracies (92.5% and 84.9% on the BCI competition II dataset Ia and the TJU dataset). The accuracy can be further improved (94.5% and 85.9%) by adding the commonly used mean voltage feature and using the naive Bayesian classifier, indicating the flexibility and scalability of the proposed method. COMPARISON WITH EXISTING METHODS The proposed C-C feature based method outperforms state-of-the-art (SOTA) multi-feature classification method from the perspective of classification accuracy. CONCLUSIONS The effectiveness of the C-C feature for SCP classification is validated. The proposed feature will represent a useful contribution to the SCP classification, balancing the strengths of traditional features and the proposed one.
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Affiliation(s)
- Huirang Hou
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Biao Sun
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China.
| | - Qinghao Meng
- Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China.
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González OC, Krishnan GP, Timofeev I, Bazhenov M. Ionic and synaptic mechanisms of seizure generation and epileptogenesis. Neurobiol Dis 2019; 130:104485. [PMID: 31150792 DOI: 10.1016/j.nbd.2019.104485] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 05/23/2019] [Accepted: 05/27/2019] [Indexed: 01/09/2023] Open
Abstract
The biophysical mechanisms underlying epileptogenesis and the generation of seizures remain to be better understood. Among many factors triggering epileptogenesis are traumatic brain injury breaking normal synaptic homeostasis and genetic mutations disrupting ionic concentration homeostasis. Impairments in these mechanisms, as seen in various brain diseases, may push the brain network to a pathological state characterized by increased susceptibility to unprovoked seizures. Here, we review recent computational studies exploring the roles of ionic concentration dynamics in the generation, maintenance, and termination of seizures. We further discuss how ionic and synaptic homeostatic mechanisms may give rise to conditions which prime brain networks to exhibit recurrent spontaneous seizures and epilepsy.
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Affiliation(s)
- Oscar C González
- Neurosciences Graduate Program, University of California, San Diego, CA 92093, United States of America; Department of Medicine, University of California, San Diego, CA 92093, United States of America
| | - Giri P Krishnan
- Department of Medicine, University of California, San Diego, CA 92093, United States of America
| | - Igor Timofeev
- Centre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), 2601 de la Canardière, Québec, QC, Canada; Department of Psychiatry and Neuroscience, Université Laval, Québec, QC, Canada
| | - Maxim Bazhenov
- Neurosciences Graduate Program, University of California, San Diego, CA 92093, United States of America; Department of Medicine, University of California, San Diego, CA 92093, United States of America.
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38
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Sudhakar SK, Choi TJ, Ahmed OJ. Biophysical Modeling Suggests Optimal Drug Combinations for Improving the Efficacy of GABA Agonists after Traumatic Brain Injuries. J Neurotrauma 2019; 36:1632-1645. [PMID: 30484362 PMCID: PMC6531909 DOI: 10.1089/neu.2018.6065] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Traumatic brain injuries (TBI) lead to dramatic changes in the surviving brain tissue. Altered ion concentrations, coupled with changes in the expression of membrane-spanning proteins, create a post-TBI brain state that can lead to further neuronal loss caused by secondary excitotoxicity. Several GABA receptor agonists have been tested in the search for neuroprotection immediately after an injury, with paradoxical results. These drugs not only fail to offer neuroprotection, but can also slow down functional recovery after TBI. Here, using computational modeling, we provide a biophysical hypothesis to explain these observations. We show that the accumulation of intracellular chloride ions caused by a transient upregulation of Na+-K+-2Cl- (NKCC1) co-transporters as observed following TBI, causes GABA receptor agonists to lead to excitation and depolarization block, rather than the expected hyperpolarization. The likelihood of prolonged, excitotoxic depolarization block is further exacerbated by the extremely high levels of extracellular potassium seen after TBI. Our modeling results predict that the neuroprotective efficacy of GABA receptor agonists can be substantially enhanced when they are combined with NKCC1 co-transporter inhibitors. This suggests a rational, biophysically principled method for identifying drug combinations for neuroprotection after TBI.
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Affiliation(s)
| | - Thomas J. Choi
- Department of Psychology, University of Michigan, Ann Arbor, Michigan
| | - Omar J. Ahmed
- Department of Psychology, University of Michigan, Ann Arbor, Michigan
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Department of Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan
- Department of Kresge Hearing Research Institute, University of Michigan, Ann Arbor, Michigan
- Department of Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, Michigan
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39
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Rosen BQ, Krishnan GP, Sanda P, Komarov M, Sejnowski T, Rulkov N, Ulbert I, Eross L, Madsen J, Devinsky O, Doyle W, Fabo D, Cash S, Bazhenov M, Halgren E. Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics. J Neurosci Methods 2019; 316:46-57. [PMID: 30300700 PMCID: PMC6380919 DOI: 10.1016/j.jneumeth.2018.10.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 10/03/2018] [Accepted: 10/04/2018] [Indexed: 11/16/2022]
Abstract
BACKGROUND Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain. METHOD We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors. RESULTS The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted. COMPARISON WITH EXISTING METHODS Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales. CONCLUSIONS This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.
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Affiliation(s)
- B Q Rosen
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States.
| | - G P Krishnan
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - P Sanda
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States; Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic.
| | - M Komarov
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - T Sejnowski
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; The Salk Institute, La Jolla, CA, United States.
| | - N Rulkov
- BioCiruits Institute, University of California, San Diego, La Jolla, CA, United States.
| | - I Ulbert
- Institute of Cognitive Neuroscience and Psychology, Hungarian Academy of Science, Budapest, Hungary; Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Budapest, Hungary.
| | - L Eross
- Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Budapest, Hungary; Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, Hungary.
| | - J Madsen
- Departments of Neurosurgery, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.
| | - O Devinsky
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY, United States.
| | - W Doyle
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY, United States.
| | - D Fabo
- Epilepsy Centrum, National Institute of Clinical Neurosciences, Budapest, Hungary.
| | - S Cash
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Medicine, University of California, San Diego, La Jolla, CA, United States; Departments of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - M Bazhenov
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - E Halgren
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Radiology, University of California, San Diego, La Jolla, CA, United States; Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.
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