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Cao P, Li Y, Dong Y, Tang Y, Xu G, Si Q, Chen C, Yao Y, Li R, Sui Y. Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder. J Affect Disord 2024; 363:269-281. [PMID: 39053628 DOI: 10.1016/j.jad.2024.07.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/25/2024] [Accepted: 07/14/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms. METHODS Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups. RESULTS Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively. CONCLUSION This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.
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Affiliation(s)
- Peiyu Cao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yuting Li
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huzhou Third People's Hospital, Huzhou 313000, Zhejiang, China
| | - Yingbo Dong
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yilin Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Guoxin Xu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Qi Si
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huai'an No. 3 People's Hospital, Huai'an 223001, Jiangsu, China
| | - Congxin Chen
- Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing 210000, Jiangsu, China
| | - Ye Yao
- Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Runda Li
- Vanderbilt University, Nashville 37240, TN, USA
| | - Yuxiu Sui
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China.
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2
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Fukushima M, Leibnitz K. Effects of packetization on communication dynamics in brain networks. Netw Neurosci 2024; 8:418-436. [PMID: 38952819 PMCID: PMC11142457 DOI: 10.1162/netn_a_00360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Computational studies in network neuroscience build models of communication dynamics in the connectome that help us understand the structure-function relationships of the brain. In these models, the dynamics of cortical signal transmission in brain networks are approximated with simple propagation strategies such as random walks and shortest path routing. Furthermore, the signal transmission dynamics in brain networks can be associated with the switching architectures of engineered communication systems (e.g., message switching and packet switching). However, it has been unclear how propagation strategies and switching architectures are related in models of brain network communication. Here, we investigate the effects of the difference between packet switching and message switching (i.e., whether signals are packetized or not) on the transmission completion time of propagation strategies when simulating signal propagation in mammalian brain networks. The results show that packetization in the connectome with hubs increases the time of the random walk strategy and does not change that of the shortest path strategy, but decreases that of more plausible strategies for brain networks that balance between communication speed and information requirements. This finding suggests an advantage of packet-switched communication in the connectome and provides new insights into modeling the communication dynamics in brain networks.
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Affiliation(s)
- Makoto Fukushima
- Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan
| | - Kenji Leibnitz
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
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3
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Totzek JF, Chakravarty MM, Joober R, Malla A, Shah JL, Raucher-Chéné D, Young AL, Hernaus D, Lepage M, Lavigne KM. Longitudinal inference of multiscale markers in psychosis: from hippocampal centrality to functional outcome. Mol Psychiatry 2024:10.1038/s41380-024-02549-x. [PMID: 38605172 DOI: 10.1038/s41380-024-02549-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 03/28/2024] [Accepted: 04/02/2024] [Indexed: 04/13/2024]
Abstract
Multiscale neuroscience conceptualizes mental illness as arising from aberrant interactions across and within multiple biopsychosocial scales. We leverage this framework to propose a multiscale disease progression model of psychosis, in which hippocampal-cortical dysconnectivity precedes impairments in episodic memory and social cognition, which lead to more severe negative symptoms and lower functional outcome. As psychosis represents a heterogeneous collection of biological and behavioral alterations that evolve over time, we further predict this disease progression for a subtype of the patient sample, with other patients showing normal-range performance on all variables. We sampled data from two cross-sectional datasets of first- and multi-episode psychosis, resulting in a sample of 163 patients and 119 non-clinical controls. To address our proposed disease progression model and evaluate potential heterogeneity, we applied a machine-learning algorithm, SuStaIn, to the patient data. SuStaIn uniquely integrates clustering and disease progression modeling and identified three patient subtypes. Subtype 0 showed normal-range performance on all variables. In comparison, Subtype 1 showed lower episodic memory, social cognition, functional outcome, and higher negative symptoms, while Subtype 2 showed lower hippocampal-cortical connectivity and episodic memory. Subtype 1 deteriorated from episodic memory to social cognition, negative symptoms, functional outcome to bilateral hippocampal-cortical dysconnectivity, while Subtype 2 deteriorated from bilateral hippocampal-cortical dysconnectivity to episodic memory and social cognition, functional outcome to negative symptoms. This first application of SuStaIn in a multiscale psychiatric model provides distinct disease trajectories of hippocampal-cortical connectivity, which might underlie the heterogeneous behavioral manifestations of psychosis.
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Affiliation(s)
- Jana F Totzek
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - M Mallar Chakravarty
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Ridha Joober
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - Ashok Malla
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - Jai L Shah
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - Delphine Raucher-Chéné
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - Alexandra L Young
- Department of Computer Science, University College London, London, United Kingdom
| | - Dennis Hernaus
- Department of Psychiatry & Neuropsychology, School for Mental Health and NeuroScience MHeNS, Maastricht University, Maastricht, The Netherlands
| | - Martin Lepage
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - Katie M Lavigne
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Douglas Research Centre, Montreal, QC, Canada.
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4
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Bunzeck N, Steiger TK, Krämer UM, Luedtke K, Marshall L, Obleser J, Tune S. Trajectories and contributing factors of neural compensation in healthy and pathological aging. Neurosci Biobehav Rev 2024; 156:105489. [PMID: 38040075 DOI: 10.1016/j.neubiorev.2023.105489] [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: 06/20/2023] [Revised: 11/07/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023]
Abstract
Neural degeneration is a hallmark of healthy aging and can be associated with specific cognitive impairments. However, neural degeneration per se is not matched by unremitting declines in cognitive abilities. Instead, middle-aged and older adults typically maintain surprisingly high levels of cognitive functioning, suggesting that the human brain can adapt to structural degeneration by neural compensation. Here, we summarize prevailing theories and recent empirical studies on neural compensation with a focus on often neglected contributing factors, such as lifestyle, metabolism and neural plasticity. We suggest that these factors moderate the relationship between structural integrity and neural compensation, maintaining psychological well-being and behavioral functioning. Finally, we discuss that a breakdown in neural compensation may pose a tipping point that distinguishes the trajectories of healthy vs pathological aging, but conjoint support from psychology and cognitive neuroscience for this alluring view is still scarce. Therefore, future experiments that target the concomitant processes of neural compensation and associated behavior will foster a comprehensive understanding of both healthy and pathological aging.
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Affiliation(s)
- Nico Bunzeck
- Department of Psychology, University of Lübeck, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Germany.
| | | | - Ulrike M Krämer
- Department of Psychology, University of Lübeck, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Germany; Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Kerstin Luedtke
- Institute of Health Sciences, Department of Physiotherapy, University of Lübeck, Germany
| | - Lisa Marshall
- Center of Brain, Behavior and Metabolism, University of Lübeck, Germany; Institute of Experimental and Clinical Pharmacology and Toxicology, University of Lübeck, Germany
| | - Jonas Obleser
- Department of Psychology, University of Lübeck, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Germany
| | - Sarah Tune
- Department of Psychology, University of Lübeck, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Germany
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5
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Wirth S. Encoding identity in the marmoset. Science 2023; 382:372-373. [PMID: 37883556 DOI: 10.1126/science.adk8413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Hippocampal cells integrate multisensory input to represent the identity of others.
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Affiliation(s)
- Sylvia Wirth
- Institut des Sciences Cognitives Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France
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6
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Avery SN, Rogers BP, McHugo M, Armstrong K, Blackford JU, Vandekar SN, Woodward ND, Heckers S. Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:979-989. [PMID: 37881573 PMCID: PMC10593896 DOI: 10.1016/j.bpsgos.2022.10.002] [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: 06/20/2022] [Revised: 08/17/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022] Open
Abstract
Background Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years. Methods We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model. Results Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration. Conclusions These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.
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Affiliation(s)
- Suzanne N. Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Baxter P. Rogers
- Vanderbilt University Institute of Imaging Sciences, Nashville, Tennessee
| | - Maureen McHugo
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kristan Armstrong
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Simon N. Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Neil D. Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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7
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Milisav F, Bazinet V, Iturria-Medina Y, Misic B. Resolving inter-regional communication capacity in the human connectome. Netw Neurosci 2023; 7:1051-1079. [PMID: 37781139 PMCID: PMC10473316 DOI: 10.1162/netn_a_00318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 04/03/2023] [Indexed: 10/03/2023] Open
Abstract
Applications of graph theory to the connectome have inspired several models of how neural signaling unfolds atop its structure. Analytic measures derived from these communication models have mainly been used to extract global characteristics of brain networks, obscuring potentially informative inter-regional relationships. Here we develop a simple standardization method to investigate polysynaptic communication pathways between pairs of cortical regions. This procedure allows us to determine which pairs of nodes are topologically closer and which are further than expected on the basis of their degree. We find that communication pathways delineate canonical functional systems. Relating nodal communication capacity to meta-analytic probabilistic patterns of functional specialization, we also show that areas that are most closely integrated within the network are associated with higher order cognitive functions. We find that these regions' proclivity towards functional integration could naturally arise from the brain's anatomical configuration through evenly distributed connections among multiple specialized communities. Throughout, we consider two increasingly constrained null models to disentangle the effects of the network's topology from those passively endowed by spatial embedding. Altogether, the present findings uncover relationships between polysynaptic communication pathways and the brain's functional organization across multiple topological levels of analysis and demonstrate that network integration facilitates cognitive integration.
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Affiliation(s)
- Filip Milisav
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Vincent Bazinet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Yasser Iturria-Medina
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
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8
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Deshpande SS, van Drongelen W. A Novel Quantitative Metric Based on a Complete and Unique Characterization of Neural Network Activity: 4D Shannon's Entropy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.15.557974. [PMID: 37745513 PMCID: PMC10516034 DOI: 10.1101/2023.09.15.557974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The human brain comprises an intricate web of connections that generate complex neural networks capable of storing and processing information. This information depends on multiple factors, including underlying network structure, connectivity, and interactions; and thus, methods to characterize neural networks typically aim to unravel and interpret a combination of these factors. Here, we present four-dimensional (4D) Shannon's entropy, a novel quantitative metric of network activity based on the Triple Correlation Uniqueness (TCU) theorem. Triple correlation, which provides a complete and unique characterization of the network, relates three nodes separated by up to four spatiotemporal lags. Here, we evaluate the 4D entropy from the spatiotemporal lag probability distribution function (PDF) of the network activity's triple correlation. Given a spike raster, we compute triple correlation by iterating over time and space. Summing the contributions to the triple correlation over each of the spatial and temporal lag combinations generates a unique 4D spatiotemporal lag distribution, from which we estimate a PDF and compute Shannon's entropy. To outline our approach, we first compute 4D Shannon's entropy from feedforward motif-class patterns in a simulated spike raster. We then apply this methodology to spiking activity recorded from rat cortical cultures to compare our results to previously published results of pairwise (2D) correlated spectral entropy over time. We find that while first- and second-order metrics of activity (spike rate and cross-correlation) show agreement with previously published results, our 4D entropy computation (which also includes third-order interactions) reveals a greater depth of underlying network organization compared to published pairwise entropy. Ultimately, because our approach is based on the TCU, we propose that 4D Shannon's entropy is a more complete tool for neural network characterization.
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Affiliation(s)
- Sarita S. Deshpande
- Medical Scientist Training Program, University of Chicago, Chicago, IL, United States of America
- Committee on Neurobiology, University of Chicago, Chicago, IL, United States of America
- Section of Pediatric Neurology, University of Chicago, Chicago, IL, United States of America
| | - Wim van Drongelen
- Committee on Neurobiology, University of Chicago, Chicago, IL, United States of America
- Section of Pediatric Neurology, University of Chicago, Chicago, IL, United States of America
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, United States of America
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9
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Liu ZQ, Shafiei G, Baillet S, Misic B. Spatially heterogeneous structure-function coupling in haemodynamic and electromagnetic brain networks. Neuroimage 2023; 278:120276. [PMID: 37451374 DOI: 10.1016/j.neuroimage.2023.120276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023] Open
Abstract
The relationship between structural and functional connectivity in the brain is a key question in connectomics. Here we quantify patterns of structure-function coupling across the neocortex, by comparing structural connectivity estimated using diffusion MRI with functional connectivity estimated using both neurophysiological (MEG-based) and haemodynamic (fMRI-based) recordings. We find that structure-function coupling is heterogeneous across brain regions and frequency bands. The link between structural and functional connectivity is generally stronger in multiple MEG frequency bands compared to resting state fMRI. Structure-function coupling is greater in slower and intermediate frequency bands compared to faster frequency bands. We also find that structure-function coupling systematically follows the archetypal sensorimotor-association hierarchy, as well as patterns of laminar differentiation, peaking in granular layer IV. Finally, structure-function coupling is better explained using structure-informed inter-regional communication metrics than using structural connectivity alone. Collectively, these results place neurophysiological and haemodynamic structure-function relationships in a common frame of reference and provide a starting point for a multi-modal understanding of structure-function coupling in the brain.
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Affiliation(s)
- Zhen-Qi Liu
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
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10
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Yang E, Milisav F, Kopal J, Holmes AJ, Mitsis GD, Misic B, Finn ES, Bzdok D. The default network dominates neural responses to evolving movie stories. Nat Commun 2023; 14:4197. [PMID: 37452058 PMCID: PMC10349102 DOI: 10.1038/s41467-023-39862-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story. The default network, associated with semantic information integration, is the most engaged during movie watching. Furthermore, we identify two mechanisms that underlie how the default network liaises with the amygdala and hippocampus. Our findings demonstrate effective approaches to understanding neural processes in everyday situations and their relation to conscious awareness.
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Affiliation(s)
- Enning Yang
- Department of Biomedical Engineering, TheNeuro-Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre (BIC), McGill University, Montreal, QC, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Filip Milisav
- Department of Biomedical Engineering, TheNeuro-Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre (BIC), McGill University, Montreal, QC, Canada
| | - Jakub Kopal
- Department of Biomedical Engineering, TheNeuro-Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre (BIC), McGill University, Montreal, QC, Canada
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Avram J Holmes
- Department of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, QC, Canada
| | - Bratislav Misic
- Department of Biomedical Engineering, TheNeuro-Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre (BIC), McGill University, Montreal, QC, Canada
| | - Emily S Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Danilo Bzdok
- Department of Biomedical Engineering, TheNeuro-Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre (BIC), McGill University, Montreal, QC, Canada.
- Mila-Quebec Artificial Intelligence Institute, Montreal, QC, Canada.
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11
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Bazinet V, Hansen JY, Vos de Wael R, Bernhardt BC, van den Heuvel MP, Misic B. Assortative mixing in micro-architecturally annotated brain connectomes. Nat Commun 2023; 14:2850. [PMID: 37202416 DOI: 10.1038/s41467-023-38585-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 05/08/2023] [Indexed: 05/20/2023] Open
Abstract
The wiring of the brain connects micro-architecturally diverse neuronal populations, but the conventional graph model, which encodes macroscale brain connectivity as a network of nodes and edges, abstracts away the rich biological detail of each regional node. Here, we annotate connectomes with multiple biological attributes and formally study assortative mixing in annotated connectomes. Namely, we quantify the tendency for regions to be connected based on the similarity of their micro-architectural attributes. We perform all experiments using four cortico-cortical connectome datasets from three different species, and consider a range of molecular, cellular, and laminar annotations. We show that mixing between micro-architecturally diverse neuronal populations is supported by long-distance connections and find that the arrangement of connections with respect to biological annotations is associated to patterns of regional functional specialization. By bridging scales of cortical organization, from microscale attributes to macroscale connectivity, this work lays the foundation for next-generation annotated connectomics.
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Affiliation(s)
- Vincent Bazinet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Martijn P van den Heuvel
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
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12
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Ekstrom AD, Hill PF. Spatial navigation and memory: A review of the similarities and differences relevant to brain models and age. Neuron 2023; 111:1037-1049. [PMID: 37023709 PMCID: PMC10083890 DOI: 10.1016/j.neuron.2023.03.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 02/27/2023] [Indexed: 04/07/2023]
Abstract
Spatial navigation and memory are often seen as heavily intertwined at the cognitive and neural levels of analysis. We review models that hypothesize a central role for the medial temporal lobes, including the hippocampus, in both navigation and aspects of memory, particularly allocentric navigation and episodic memory. While these models have explanatory power in instances in which they overlap, they are limited in explaining functional and neuroanatomical differences. Focusing on human cognition, we explore the idea of navigation as a dynamically acquired skill and memory as an internally driven process, which may better account for the differences between the two. We also review network models of navigation and memory, which place a greater emphasis on connections rather than the functions of focal brain regions. These models, in turn, may have greater explanatory power for the differences between navigation and memory and the differing effects of brain lesions and age.
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Affiliation(s)
- Arne D Ekstrom
- Department of Psychology, University of Arizona, 1503 E. University Blvd., Tucson, AZ 85719, USA; Evelyn McKnight Brain Institute, University of Arizona, 1503 E. University Blvd., Tucson, AZ 85719, USA.
| | - Paul F Hill
- Department of Psychology, University of Arizona, 1503 E. University Blvd., Tucson, AZ 85719, USA
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13
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Amer T, Davachi L. Extra-hippocampal contributions to pattern separation. eLife 2023; 12:e82250. [PMID: 36972123 PMCID: PMC10042541 DOI: 10.7554/elife.82250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/21/2023] [Indexed: 03/29/2023] Open
Abstract
Pattern separation, or the process by which highly similar stimuli or experiences in memory are represented by non-overlapping neural ensembles, has typically been ascribed to processes supported by the hippocampus. Converging evidence from a wide range of studies, however, suggests that pattern separation is a multistage process supported by a network of brain regions. Based on this evidence, considered together with related findings from the interference resolution literature, we propose the 'cortico-hippocampal pattern separation' (CHiPS) framework, which asserts that brain regions involved in cognitive control play a significant role in pattern separation. Particularly, these regions may contribute to pattern separation by (1) resolving interference in sensory regions that project to the hippocampus, thus regulating its cortical input, or (2) directly modulating hippocampal processes in accordance with task demands. Considering recent interest in how hippocampal operations are modulated by goal states likely represented and regulated by extra-hippocampal regions, we argue that pattern separation is similarly supported by neocortical-hippocampal interactions.
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Affiliation(s)
- Tarek Amer
- Department of Psychology, University of VictoriaVictoriaCanada
| | - Lila Davachi
- Department of Psychology, Columbia UniversityNew YorkUnited States
- Nathan Kline Research InstituteOrangeburgUnited States
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14
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Seghier ML. Multiple functions of the angular gyrus at high temporal resolution. Brain Struct Funct 2023; 228:7-46. [PMID: 35674917 DOI: 10.1007/s00429-022-02512-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 05/22/2022] [Indexed: 02/07/2023]
Abstract
Here, the functions of the angular gyrus (AG) are evaluated in the light of current evidence from transcranial magnetic/electric stimulation (TMS/TES) and EEG/MEG studies. 65 TMS/TES and 52 EEG/MEG studies were examined in this review. TMS/TES literature points to a causal role in semantic processing, word and number processing, attention and visual search, self-guided movement, memory, and self-processing. EEG/MEG studies reported AG effects at latencies varying between 32 and 800 ms in a wide range of domains, with a high probability to detect an effect at 300-350 ms post-stimulus onset. A three-phase unifying model revolving around the process of sensemaking is then suggested: (1) early AG involvement in defining the current context, within the first 200 ms, with a bias toward the right hemisphere; (2) attention re-orientation and retrieval of relevant information within 200-500 ms; and (3) cross-modal integration at late latencies with a bias toward the left hemisphere. This sensemaking process can favour accuracy (e.g. for word and number processing) or plausibility (e.g. for comprehension and social cognition). Such functions of the AG depend on the status of other connected regions. The much-debated semantic role is also discussed as follows: (1) there is a strong TMS/TES evidence for a causal semantic role, (2) current EEG/MEG evidence is however weak, but (3) the existing arguments against a semantic role for the AG are not strong. Some outstanding questions for future research are proposed. This review recognizes that cracking the role(s) of the AG in cognition is possible only when its exact contributions within the default mode network are teased apart.
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Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE. .,Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE.
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15
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Multiple traces and altered signal-to-noise in systems consolidation: Evidence from the 7T fMRI Natural Scenes Dataset. Proc Natl Acad Sci U S A 2022; 119:e2123426119. [PMID: 36279446 PMCID: PMC9636924 DOI: 10.1073/pnas.2123426119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
How do the neural correlates of recognition change over time? We study natural scene image recognition spanning a year with 7-Tesla functional magnetic resonance imaging (fMRI) of the human brain. We find that the medial temporal lobe (MTL) contribution to recognition persists over 200 d, supporting multiple-trace theory and contradicting a trace transfer (from MTL to cortex) point of view. We then test the hypothesis that the signal-to-noise ratio of traces increases over time, presumably a consequence of synaptic “desaturation” in the weeks following learning. The fMRI trace signature associates with the rate of removal of competing traces and reflects a time-related enhancement of image-feature selectivity. We conclude that multiple MTL traces and improved signal-to-noise may underlie systems-level memory consolidation. The brain mechanisms of memory consolidation remain elusive. Here, we examine blood-oxygen-level-dependent (BOLD) correlates of image recognition through the scope of multiple influential systems consolidation theories. We utilize the longitudinal Natural Scenes Dataset, a 7-Tesla functional magnetic resonance imaging human study in which ∼135,000 trials of image recognition were conducted over the span of a year among eight subjects. We find that early- and late-stage image recognition associates with both medial temporal lobe (MTL) and visual cortex when evaluating regional activations and a multivariate classifier. Supporting multiple-trace theory (MTT), parts of the MTL activation time course show remarkable fit to a 20-y-old MTT time-dynamical model predicting early trace intensity increases and slight subsequent interference (R2 > 0.90). These findings contrast a simplistic, yet common, view that memory traces are transferred from MTL to cortex. Next, we test the hypothesis that the MTL trace signature of memory consolidation should also reflect synaptic “desaturation,” as evidenced by an increased signal-to-noise ratio. We find that the magnitude of relative BOLD enhancement among surviving memories is positively linked to the rate of removal (i.e., forgetting) of competing traces. Moreover, an image-feature and time interaction of MTL and visual cortex functional connectivity suggests that consolidation mechanisms improve the specificity of a distributed trace. These neurobiological effects do not replicate on a shorter timescale (within a session), implicating a prolonged, offline process. While recognition can potentially involve cognitive processes outside of memory retrieval (e.g., re-encoding), our work largely favors MTT and desaturation as perhaps complementary consolidative memory mechanisms.
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16
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Favaretto C, Allegra M, Deco G, Metcalf NV, Griffis JC, Shulman GL, Brovelli A, Corbetta M. Subcortical-cortical dynamical states of the human brain and their breakdown in stroke. Nat Commun 2022; 13:5069. [PMID: 36038566 PMCID: PMC9424299 DOI: 10.1038/s41467-022-32304-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01–0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome. Favaretto et al. show that the brain rapidly alternates between transient connectivity patterns, with cortical regions flexibly synchronizing with two groups of subcortical regions, and that this dynamic is abnormal in stroke patients.
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Affiliation(s)
- Chiara Favaretto
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy.
| | - Michele Allegra
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy.,Department of Physics and Astronomy "Galileo Galilei", University of Padova, via Marzolo 8, 35131, Padova, Italy.,Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain.,Institució Catalana de Recerca I Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010, Barcelona, Catalonia, Spain
| | - Nicholas V Metcalf
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA.,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy. .,Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,VIMM, Venetian Institute of Molecular Medicine (VIMM), Biomedical Foundation, via Orus 2, 35129, Padova, Italy.
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17
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Buck G, Makowski C, Chakravarty MM, Misic B, Joober R, Malla A, Lepage M, Lavigne KM. Sex-specific associations in verbal memory brain circuitry in early psychosis. J Psychiatr Res 2022; 151:411-418. [PMID: 35594601 DOI: 10.1016/j.jpsychires.2022.05.006] [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: 11/25/2021] [Revised: 04/08/2022] [Accepted: 05/09/2022] [Indexed: 01/18/2023]
Abstract
Hippocampal circuitry and related cortical connections are altered in first episode psychosis (FEP) and are associated with verbal memory deficits, as well as positive and negative symptoms. There are robust sex differences in the clinical presentation of psychosis, including poorer verbal memory in male patients. Consideration of sex differences in hippocampal-cortical circuitry and their associations with different behavioral dimensions may be useful for understanding the underlying pathophysiology of verbal memory deficits and related symptomatology in psychosis. Here, we use a data-driven approach to simultaneously capture the complex links between sex, verbal memory, symptoms, and cortical-hippocampal brain metrics in FEP. Structural magnetic resonance imaging and behavioral data were acquired from 100 FEP patients (75 males, 25 females) and 87 controls (55 males, 32 females). Multivariate brain-behavior associations were examined in FEP using partial least squares to map sociodemographic, verbal memory, and clinical data onto brain morphometry. The analysis identified two sex-dependent patterns of verbal memory, symptoms, and brain structure. In male patients, verbal memory deficits and core psychotic symptoms were associated with both increased and decreased frontal and temporal cortical thickness and reductions in CA2/3 hippocampal subfield and fornix volumes. In female patients, fewer negative/depressive symptoms were associated with a more attenuated cortical thickness pattern and more diffuse reductions in hippocampal white matter regions. Taken together, the results contribute towards better understanding the underlying pathophysiology of psychosis by highlighting the unique contribution of specific hippocampal subfields and surrounding white matter and their connections with broader cortical networks in a sex-dependent manner.
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Affiliation(s)
- Gabriella Buck
- Douglas Mental Health University Institute, Montréal, Québec, Canada
| | - Carolina Makowski
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - M Mallar Chakravarty
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada; Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montréal, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada
| | - Ridha Joober
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Ashok Malla
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Katie M Lavigne
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada; Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.
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18
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Electroacupuncture Increases the Hippocampal Synaptic Transmission Efficiency and Long-Term Plasticity to Improve Vascular Cognitive Impairment. Mediators Inflamm 2022; 2022:5985143. [PMID: 35784174 PMCID: PMC9246579 DOI: 10.1155/2022/5985143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/02/2022] [Accepted: 05/18/2022] [Indexed: 11/18/2022] Open
Abstract
Studies have shown that electroacupuncture (EA) can effectively improve vascular cognitive impairment (VCI), but its mechanisms have not been clearly elucidated. This study is aimed at investigating the mechanisms underlying the effects of EA treatment on hippocampal synaptic transmission efficiency and plasticity in rats with VCI. Methods. Sprague–Dawley rats were subjected to VCI with bilateral common carotid occlusion (2VO). EA stimulation was applied to Baihui (GV20) and Shenting (GV24) acupoints for 30 min once a day, five times a week, for four weeks. Our study also included nonacupoint groups to confirm the specificity of EA therapy. The Morris water maze (MWM) was used to assess cognitive function. Electrophysiological techniques were used to detect the field characteristics of the hippocampal CA3–CA1 circuit in each group of rats, including input-output (I/O), paired-pulse facilitation ratios (PPR), field excitatory postsynaptic potential (fEPSP), and excitatory postsynaptic current (EPSC). The expression of synapse- and calcium-mediated signal transduction associated proteins was detected through western blotting. Results. The MWM behavioural results showed that EA significantly improved cognitive function in VCI model rats. EA increased the I/O curve of VCI model rats from 20 to 90 μA. No significant differences were observed in hippocampal PPR. The fEPSP of the hippocampal CA3–CA1 circuit was significantly increased after EA treatment compared with that after nonacupuncture treatment. We found that EA led to an increase in the EPSC amplitude and frequency, especially in the decay and rise times. In addition, the protein expression and phosphorylation levels of N-methyl-D-aspartate receptor 2B, α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor 1, and Ca2+-calmodulin-dependent protein kinase II increased to varying degrees in the hippocampus of VCI model rats. Conclusion. EA at GV20 and GV24 acupoints increased the basic synaptic transmission efficiency and synaptic plasticity of the hippocampal CA3–CA1 circuit, thereby improving learning and memory ability in rats with VCI.
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19
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Taniguchi A, Fukawa A, Yamakawa H. Hippocampal formation-inspired probabilistic generative model. Neural Netw 2022; 151:317-335. [DOI: 10.1016/j.neunet.2022.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 03/09/2022] [Accepted: 04/03/2022] [Indexed: 11/25/2022]
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20
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Saboo KV, Hu C, Varatharajah Y, Przybelski SA, Reid RI, Schwarz CG, Graff-Radford J, Knopman DS, Machulda MM, Mielke MM, Petersen RC, Arnold PM, Worrell GA, Jones DT, Jack Jr CR, Iyer RK, Vemuri P. Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging. Neuroimage 2022; 251:119020. [PMID: 35196565 PMCID: PMC9045384 DOI: 10.1016/j.neuroimage.2022.119020] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/20/2022] [Accepted: 02/17/2022] [Indexed: 12/02/2022] Open
Abstract
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adults at risk of cognitive decline. Using deep learning models augmented with a model-interpretation technique on data from 1432 Mayo Clinic Study of Aging participants, we identified a subset of brain structures that were most predictive of individualized cognitive trajectories and indicative of cognitively resilient vs. vulnerable individuals. Specifically, these structures explained why some participants were resilient to the deleterious effects of elevated brain amyloid and poor vascular health. Of these, medial temporal lobe and fornix, reflective of age and pathology-related degeneration, and corpus callosum, reflective of inter-hemispheric disconnection, accounted for 60% of the heterogeneity explained by the most predictive structures. Our results are valuable for identifying cognitively vulnerable individuals and for developing interventions for cognitive decline.
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21
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Surget A, Belzung C. Adult hippocampal neurogenesis shapes adaptation and improves stress response: a mechanistic and integrative perspective. Mol Psychiatry 2022; 27:403-421. [PMID: 33990771 PMCID: PMC8960391 DOI: 10.1038/s41380-021-01136-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 04/09/2021] [Accepted: 04/19/2021] [Indexed: 02/03/2023]
Abstract
Adult hippocampal neurogenesis (AHN) represents a remarkable form of neuroplasticity that has increasingly been linked to the stress response in recent years. However, the hippocampus does not itself support the expression of the different dimensions of the stress response. Moreover, the main hippocampal functions are essentially preserved under AHN depletion and adult-born immature neurons (abGNs) have no extrahippocampal projections, which questions the mechanisms by which abGNs influence functions supported by brain areas far from the hippocampus. Within this framework, we propose that through its computational influences AHN is pivotal in shaping adaption to environmental demands, underlying its role in stress response. The hippocampus with its high input convergence and output divergence represents a computational hub, ideally positioned in the brain (1) to detect cues and contexts linked to past, current and predicted stressful experiences, and (2) to supervise the expression of the stress response at the cognitive, affective, behavioral, and physiological levels. AHN appears to bias hippocampal computations toward enhanced conjunctive encoding and pattern separation, promoting contextual discrimination and cognitive flexibility, reducing proactive interference and generalization of stressful experiences to safe contexts. These effects result in gating downstream brain areas with more accurate and contextualized information, enabling the different dimensions of the stress response to be more appropriately set with specific contexts. Here, we first provide an integrative perspective of the functional involvement of AHN in the hippocampus and a phenomenological overview of the stress response. We then examine the mechanistic underpinning of the role of AHN in the stress response and describe its potential implications in the different dimensions accompanying this response.
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Affiliation(s)
- A Surget
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.
| | - C Belzung
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.
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22
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Zhou Y, Si X, Chen Y, Chao Y, Lin CP, Li S, Zhang X, Ming D, Li Q. Hippocampus- and Thalamus-Related Fiber-Specific White Matter Reductions in Mild Cognitive Impairment. Cereb Cortex 2021; 32:3159-3174. [PMID: 34891164 DOI: 10.1093/cercor/bhab407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/04/2021] [Accepted: 10/20/2021] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis of mild cognitive impairment (MCI) fascinates screening high-risk Alzheimer's disease (AD). White matter is found to degenerate earlier than gray matter and functional connectivity during MCI. Although studies reveal white matter degenerates in the limbic system for MCI, how other white matter degenerates during MCI remains unclear. In our method, regions of interest with a high level of resting-state functional connectivity with hippocampus were selected as seeds to track fibers based on diffusion tensor imaging (DTI). In this way, hippocampus-temporal and thalamus-related fibers were selected, and each fiber's DTI parameters were extracted. Then, statistical analysis, machine learning classification, and Pearson's correlations with behavior scores were performed between MCI and normal control (NC) groups. Results show that: 1) the mean diffusivity of hippocampus-temporal and thalamus-related fibers are significantly higher in MCI and could be used to classify 2 groups effectively. 2) Compared with normal fibers, the degenerated fibers detected by the DTI indexes, especially for hippocampus-temporal fibers, have shown significantly higher correlations with cognitive scores. 3) Compared with the hippocampus-temporal fibers, thalamus-related fibers have shown significantly higher correlations with depression scores within MCI. Our results provide novel biomarkers for the early diagnoses of AD.
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Affiliation(s)
- Yu Zhou
- School of Microelectronics, Tianjin University, Tianjin 300072, China
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China.,Institute of Applied Psychology, Tianjin University, Tianjin 300350, China
| | - Yuanyuan Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Yiping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan.,Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience Hsinchu City, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Xingjian Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin 300072, China
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23
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Uscătescu LC, Kronbichler L, Stelzig-Schöler R, Pearce BG, Said-Yürekli S, Reich LA, Weber S, Aichhorn W, Kronbichler M. Effective Connectivity of the Hippocampus Can Differentiate Patients with Schizophrenia from Healthy Controls: A Spectral DCM Approach. Brain Topogr 2021; 34:762-778. [PMID: 34482503 PMCID: PMC8556208 DOI: 10.1007/s10548-021-00868-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 08/22/2021] [Indexed: 12/01/2022]
Abstract
We applied spectral dynamic causal modelling (Friston et al. in Neuroimage 94:396–407. 10.1016/j.neuroimage.2013.12.009, 2014) to analyze the effective connectivity differences between the nodes of three resting state networks (i.e. default mode network, salience network and dorsal attention network) in a dataset of 31 male healthy controls (HC) and 25 male patients with a diagnosis of schizophrenia (SZ). Patients showed increased directed connectivity from the left hippocampus (LHC) to the: dorsal anterior cingulate cortex (DACC), right anterior insula (RAI), left frontal eye fields and the bilateral inferior parietal sulcus (LIPS & RIPS), as well as increased connectivity from the right hippocampus (RHC) to the: bilateral anterior insula (LAI & RAI), right frontal eye fields and RIPS. In SZ, negative symptoms predicted the connectivity strengths from the LHC to: the DACC, the left inferior parietal sulcus (LIPAR) and the RHC, while positive symptoms predicted the connectivity strengths from the LHC to the LIPAR and from the RHC to the LHC. These results reinforce the crucial role of hippocampus dysconnectivity in SZ pathology and its potential as a biomarker of disease severity.
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Affiliation(s)
- Lavinia Carmen Uscătescu
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
| | - Lisa Kronbichler
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | - Renate Stelzig-Schöler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | - Brandy-Gale Pearce
- Department of Psychiatry, Psychotherapy and Psychosomatics, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | - Sarah Said-Yürekli
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | | | - Stefanie Weber
- Department of Psychiatry, Psychotherapy and Psychosomatics, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | - Wolfgang Aichhorn
- Department of Psychiatry, Psychotherapy and Psychosomatics, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
| | - Martin Kronbichler
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical Centre, Paracelsus Medical University, Salzburg, Austria
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24
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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Amico E, Abbas K, Duong-Tran DA, Tipnis U, Rajapandian M, Chumin E, Ventresca M, Harezlak J, Goñi J. Toward an information theoretical description of communication in brain networks. Netw Neurosci 2021; 5:646-665. [PMID: 34746621 PMCID: PMC8567835 DOI: 10.1162/netn_a_00185] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 01/18/2021] [Indexed: 11/21/2022] Open
Abstract
Modeling communication dynamics in the brain is a key challenge in network neuroscience. We present here a framework that combines two measurements for any system where different communication processes are taking place on top of a fixed structural topology: path processing score (PPS) estimates how much the brain signal has changed or has been transformed between any two brain regions (source and target); path broadcasting strength (PBS) estimates the propagation of the signal through edges adjacent to the path being assessed. We use PPS and PBS to explore communication dynamics in large-scale brain networks. We show that brain communication dynamics can be divided into three main "communication regimes" of information transfer: absent communication (no communication happening); relay communication (information is being transferred almost intact); and transducted communication (the information is being transformed). We use PBS to categorize brain regions based on the way they broadcast information. Subcortical regions are mainly direct broadcasters to multiple receivers; Temporal and frontal nodes mainly operate as broadcast relay brain stations; visual and somatomotor cortices act as multichannel transducted broadcasters. This work paves the way toward the field of brain network information theory by providing a principled methodology to explore communication dynamics in large-scale brain networks.
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Affiliation(s)
- Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFL, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Kausar Abbas
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
| | - Duy Anh Duong-Tran
- School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
| | - Uttara Tipnis
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
| | | | - Evgeny Chumin
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Mario Ventresca
- School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Joaquín Goñi
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- School of Industrial Engineering, Purdue University, West Lafayette, IN, USA
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
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26
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Chatzikalymniou AP, Gumus M, Skinner FK. Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled. Hippocampus 2021; 31:982-1002. [PMID: 34086375 DOI: 10.1002/hipo.23364] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/08/2021] [Indexed: 01/18/2023]
Abstract
The wide variety of cell types and their biophysical complexities pose a challenge in our ability to understand oscillatory activities produced by cellular-based computational network models. This challenge stems from their high-dimensional and multiparametric natures. To overcome this, we implement a solution by linking minimal and detailed models of CA1 microcircuits that generate intrahippocampal (3-12 Hz) theta rhythms. We leverage insights from minimal models to guide explorations of more detailed models and obtain a cellular perspective of theta generation. Our findings distinguish the pyramidal cells as the theta rhythm initiators and reveal that their activity is regularized by the inhibitory cell populations, supporting a proposed hypothesis of an "inhibition-based tuning" mechanism. We find a strong correlation between input current to the pyramidal cells and the resulting local field potential theta frequency, indicating that intrinsic pyramidal cell properties underpin network frequency characteristics. This work provides a cellular-based foundation from which in vivo theta activities can be explored.
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Affiliation(s)
- Alexandra Pierri Chatzikalymniou
- Krembil Brain Institute, University Health Network, Toronto, Canada.,Department of Physiology, University of Toronto, Toronto, Canada
| | - Melisa Gumus
- Krembil Brain Institute, University Health Network, Toronto, Canada
| | - Frances K Skinner
- Krembil Brain Institute, University Health Network, Toronto, Canada.,Departments of Medicine (Neurology) and Physiology, University of Toronto, Toronto, Canada
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27
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Raj A. Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis. Brain Connect 2021; 11:799-814. [PMID: 33858198 DOI: 10.1089/brain.2020.0905] [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] [Indexed: 01/28/2023] Open
Abstract
Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.
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Affiliation(s)
- Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California, USA
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28
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Girardi-Schappo M, Fadaie F, Lee HM, Caldairou B, Sziklas V, Crane J, Bernhardt BC, Bernasconi A, Bernasconi N. Altered communication dynamics reflect cognitive deficits in temporal lobe epilepsy. Epilepsia 2021; 62:1022-1033. [PMID: 33705572 DOI: 10.1111/epi.16864] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/15/2021] [Accepted: 02/15/2021] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Although temporal lobe epilepsy (TLE) is recognized as a system-level disorder, little work has investigated pathoconnectomics from a dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested the hypothesis that network communication is abnormal in this condition, studied the interplay between hippocampal- and network-level disease effects, and assessed associations with cognition. METHODS We simulated signal spreading via a linear threshold model that temporally evolves on a structural graph derived from diffusion-weighted magnetic resonance imaging (MRI), comparing a homogeneous group of 31 patients with histologically proven hippocampal sclerosis to 31 age- and sex-matched healthy controls. We evaluated the modulatory effects of structural alterations of the neocortex and hippocampus on network dynamics. Furthermore, multivariate statistics addressed the relationship with cognitive parameters. RESULTS We observed a slowing of in- and out-spreading times across multiple areas bilaterally, indexing delayed information flow, with the strongest effects in ipsilateral frontotemporal regions, thalamus, and hippocampus. Effects were markedly reduced when controlling for hippocampal volume but not cortical thickness, underscoring the central role of the hippocampus in whole-brain disease expression. Multivariate analysis associated slower spreading time in frontoparietal, limbic, default mode, and subcortical networks with impairment across tasks tapping into sensorimotor, executive, memory, and verbal abilities. SIGNIFICANCE Moving beyond descriptions of static topology toward the formulation of brain dynamics, our work provides novel insight into structurally mediated network dysfunction and demonstrates that altered whole-brain communication dynamics contribute to common cognitive difficulties in TLE.
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Affiliation(s)
- Mauricio Girardi-Schappo
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Fatemeh Fadaie
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Hyo Min Lee
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Viviane Sziklas
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Joelle Crane
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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29
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Scaplen KM, Talay M, Fisher JD, Cohn R, Sorkaç A, Aso Y, Barnea G, Kaun KR. Transsynaptic mapping of Drosophila mushroom body output neurons. eLife 2021; 10:e63379. [PMID: 33570489 PMCID: PMC7877909 DOI: 10.7554/elife.63379] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 01/26/2021] [Indexed: 11/13/2022] Open
Abstract
The mushroom body (MB) is a well-characterized associative memory structure within the Drosophila brain. Analyzing MB connectivity using multiple approaches is critical for understanding the functional implications of this structure. Using the genetic anterograde transsynaptic tracing tool, trans-Tango, we identified divergent projections across the brain and convergent downstream targets of the MB output neurons (MBONs). Our analysis revealed at least three separate targets that receive convergent input from MBONs: other MBONs, the fan-shaped body (FSB), and the lateral accessory lobe (LAL). We describe, both anatomically and functionally, a multilayer circuit in which inhibitory and excitatory MBONs converge on the same genetic subset of FSB and LAL neurons. This circuit architecture enables the brain to update and integrate information with previous experience before executing appropriate behavioral responses. Our use of trans-Tango provides a genetically accessible anatomical framework for investigating the functional relevance of components within these complex and interconnected circuits.
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Affiliation(s)
- Kristin M Scaplen
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Department of Psychology, Bryant UniversitySmithfieldUnited States
- Center for Health and Behavioral Sciences, Bryant UniversitySmithfieldUnited States
| | - Mustafa Talay
- Department of Neuroscience, Brown UniversityProvidenceUnited States
| | - John D Fisher
- Department of Neuroscience, Brown UniversityProvidenceUnited States
| | - Raphael Cohn
- Laboratory of Neurophysiology and Behavior, The Rockefeller UniversityNew YorkUnited States
| | - Altar Sorkaç
- Department of Neuroscience, Brown UniversityProvidenceUnited States
| | - Yoshi Aso
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gilad Barnea
- Department of Neuroscience, Brown UniversityProvidenceUnited States
| | - Karla R Kaun
- Department of Neuroscience, Brown UniversityProvidenceUnited States
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30
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Liu ZQ, Zheng YQ, Misic B. Network topology of the marmoset connectome. Netw Neurosci 2020; 4:1181-1196. [PMID: 33409435 PMCID: PMC7781610 DOI: 10.1162/netn_a_00159] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/21/2020] [Indexed: 12/11/2022] Open
Abstract
The brain is a complex network of interconnected and interacting neuronal populations. Global efforts to understand the emergence of behavior and the effect of perturbations depend on accurate reconstruction of white matter pathways, both in humans and in model organisms. An emerging animal model for next-generation applied neuroscience is the common marmoset (Callithrix jacchus). A recent open respository of retrograde and anterograde tract tracing presents an opportunity to systematically study the network architecture of the marmoset brain (Marmoset Brain Architecture Project; http://www.marmosetbrain.org). Here we comprehensively chart the topological organization of the mesoscale marmoset cortico-cortical connectome. The network possesses multiple nonrandom attributes that promote a balance between segregation and integration, including near-minimal path length, multiscale community structure, a connective core, a unique motif composition, and multiple cavities. Altogether, these structural attributes suggest a link between network architecture and function. Our findings are consistent with previous reports across a range of species, scales, and reconstruction technologies, suggesting a small set of organizational principles universal across phylogeny. Collectively, these results provide a foundation for future anatomical, functional, and behavioral studies in this model organism.
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Affiliation(s)
- Zhen-Qi Liu
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Ying-Qiu Zheng
- Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
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31
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Seguin C, Tian Y, Zalesky A. Network communication models improve the behavioral and functional predictive utility of the human structural connectome. Netw Neurosci 2020; 4:980-1006. [PMID: 33195945 PMCID: PMC7655041 DOI: 10.1162/netn_a_00161] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 08/03/2020] [Indexed: 12/11/2022] Open
Abstract
The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (a) used to perform predictions of five data-driven behavioral dimensions and (b) correlated to resting-state functional connectivity (FC). While FC was the most accurate predictor of behavior, communication models, in particular communicability and navigation, improved the performance of structural connectomes. Communication also strengthened structure-function coupling, with the navigation and shortest paths models leading to 35-65% increases in association strength with FC. We combined behavioral and functional results into a single ranking that provides insight into which communication models may more faithfully recapitulate underlying neural signaling patterns. Comparing results across multiple connectome mapping pipelines suggested that modeling polysynaptic communication is particularly beneficial in sparse high-resolution connectomes. We conclude that network communication models can augment the functional and behavioral predictive utility of the human structural connectome.
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Affiliation(s)
- Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Ye Tian
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Department of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
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32
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Hao Y, Graham D. Creative destruction: Sparse activity emerges on the mammal connectome under a simulated communication strategy with collisions and redundancy. Netw Neurosci 2020; 4:1055-1071. [PMID: 33195948 PMCID: PMC7655042 DOI: 10.1162/netn_a_00165] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 08/14/2020] [Indexed: 01/22/2023] Open
Abstract
Signal interactions in brain network communication have been little studied. We describe how nonlinear collision rules on simulated mammal brain networks can result in sparse activity dynamics characteristic of mammalian neural systems. We tested the effects of collisions in "information spreading" (IS) routing models and in standard random walk (RW) routing models. Simulations employed synchronous agents on tracer-based mesoscale mammal connectomes at a range of signal loads. We find that RW models have high average activity that increases with load. Activity in RW models is also densely distributed over nodes: a substantial fraction is highly active in a given time window, and this fraction increases with load. Surprisingly, while IS models make many more attempts to pass signals, they show lower net activity due to collisions compared to RW, and activity in IS increases little as function of load. Activity in IS also shows greater sparseness than RW, and sparseness decreases slowly with load. Results hold on two networks of the monkey cortex and one of the mouse whole-brain. We also find evidence that activity is lower and more sparse for empirical networks compared to degree-matched randomized networks under IS, suggesting that brain network topology supports IS-like routing strategies.
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Affiliation(s)
- Yan Hao
- Department of Mathematics and Computer Science, Hobart & William Smith Colleges Geneva, NY, USA
| | - Daniel Graham
- Department of Psychology, Hobart & William Smith Colleges Geneva, NY, USA
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33
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Vézquez-Rodríguez B, Liu ZQ, Hagmann P, Misic B. Signal propagation via cortical hierarchies. Netw Neurosci 2020; 4:1072-1090. [PMID: 33195949 PMCID: PMC7657265 DOI: 10.1162/netn_a_00153] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 06/15/2020] [Indexed: 12/16/2022] Open
Abstract
The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting-state functional MRI networks. Structural networks were reconstructed from diffusion spectrum imaging and topological shortest paths among all brain regions were computed. Sequences of nodes encountered along a path were then labeled by their hierarchical position, tracing out path motifs. We find that the cortical hierarchy guides communication in the network. Specifically, nodes are more likely to forward signals to nodes closer in the hierarchy and cover a range of unimodal and transmodal regions, potentially enriching or diversifying signals en route. We also find evidence of systematic detours, particularly in attention networks, where communication is rerouted. Altogether, the present work highlights how the cortical hierarchy shapes signal exchange and imparts behaviorally relevant communication patterns in brain networks. In the present report we asked how signals travel on brain networks and what types of nodes they potentially visit en route. We traced individual path motifs to investigate the propensity of communication paths to explore the putative unimodal-transmodal cortical hierarchy. We find that the architecture of the network promotes signaling via the hierarchy, suggesting a link between the structure and function of the network. Importantly, we also find instances where detours are promoted, particularly as paths traverse attention-related networks. Finally, information about hierarchical position aids navigation in some parts of the network, over and above spatial location. Altogether, the present results touch on several emerging themes in network neuroscience, including the nature of structure-function relationships, network communication and the role of cortical hierarchies.
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Affiliation(s)
- Bertha Vézquez-Rodríguez
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Zhen-Qi Liu
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
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34
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Makowski C, Lewis JD, Khundrakpam B, Tardif CL, Palaniyappan L, Joober R, Malla A, Shah JL, Bodnar M, Chakravarty MM, Evans AC, Lepage M. Altered hippocampal centrality and dynamic anatomical covariance of intracortical microstructure in first episode psychosis. Hippocampus 2020; 30:1058-1072. [PMID: 32485018 DOI: 10.1002/hipo.23215] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/27/2020] [Accepted: 04/28/2020] [Indexed: 12/23/2022]
Abstract
Hippocampal circuitry has been posited to be fundamental to positive symptoms in psychosis, but its contributions to other factors important for outcome remains unclear. We hypothesized that longitudinal changes in the hippocampal circuit and concomitant changes of intracortical microstructure are altered in first episode psychosis (FEP) patients and that such changes are associated with negative symptoms and verbal memory. Longitudinal brain scans (2-4 visits over 3-15 months) were acquired for 27 FEP and 29 age- and sex-matched healthy controls. Quantitative T1 maps, sensitive to myelin content, were used to sample the microstructure of the hippocampal subfields and output circuitry (fimbria, alveus, fornix, mammillary bodies), and intracortical regions. Dynamic anatomical covariance in pair-wise regional trajectories were assessed for each subject, and graph theory was used to calculate a participation coefficient metric that quantifies the similarity/divergence between hippocampal and intracortical microstructure. The mean participation coefficient of the hippocampus was significantly reduced in FEP patients compared with controls, reflecting differences in output hippocampal regions. Importantly, lower participation coefficient of the hippocampal circuit was associated with worse negative symptoms, a relationship that was mediated by changes in verbal memory. This study provides evidence for reduced hippocampal centrality in FEP and concomitant changes in intracortical anatomy. Myelin-rich output regions of the hippocampus may be an important biological trigger in early psychosis, with cascading effects on broader cortical networks and resultant clinical profiles.
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Affiliation(s)
- Carolina Makowski
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,McGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada.,Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - John D Lewis
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada
| | | | - Christine L Tardif
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Ridha Joober
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Ashok Malla
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Jai L Shah
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Michael Bodnar
- Royal Ottawa Mental Health Centre, University of Ottawa, Ottawa, Ontario, Canada
| | - M Mallar Chakravarty
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada.,Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Martin Lepage
- Department of Psychiatry, Douglas Mental Health University Institute, Verdun, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
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35
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Zhang H, Giannakopoulos P, Haller S, Lee SW, Qiu S, Shen D. Inter-Network High-Order Functional Connectivity (IN-HOFC) and its Alteration in Patients with Mild Cognitive Impairment. Neuroinformatics 2020; 17:547-561. [PMID: 30739281 DOI: 10.1007/s12021-018-9413-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Little is known about the high-order interactions among brain regions measured by the similarity of higher-order features (other than the raw blood-oxygen-level-dependent signals) which can characterize higher-level brain functional connectivity (FC). Previously, we proposed FC topographical profile-based high-order FC (HOFC) and found that this metric could provide supplementary information to traditional FC for early Alzheimer's disease (AD) detection. However, whether such findings apply to network-level brain functional integration is unknown. In this paper, we propose an extended HOFC method, termed inter-network high-order FC (IN-HOFC), as a useful complement to the traditional inter-network FC methods, for characterizing more complex organizations among the large-scale brain networks. In the IN-HOFC, both network definition and inter-network FC are defined in a high-order manner. To test whether IN-HOFC is more sensitive to cognition decline due to brain diseases than traditional inter-network FC, 77 mild cognitive impairments (MCIs) and 89 controls are compared among the conventional methods and our IN-HOFC. The result shows that IN-HOFCs among three temporal lobe-related high-order networks are dampened in MCIs. The impairment of IN-HOFC is especially found between the anterior and posterior medial temporal lobe and could be a potential MCI biomarker at the network level. The competing network-level low-order FC methods, however, either revealing less or failing to detect any group difference. This work demonstrates the biological meaning and potential diagnostic value of the IN-HOFC in clinical neuroscience studies.
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Affiliation(s)
- Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, CB#7513, 130 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | | | - Sven Haller
- Affidea CDRC - Centre Diagnostique Radiologique de Carouge, Carouge, Switzerland
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
- Department of Neuroradiology, University Hospital Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Seong-Whan Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Guangzhou, 510405, Guangdong, China.
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, CB#7513, 130 Mason Farm Road, Chapel Hill, NC, 27599, USA.
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea.
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36
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Ryan JD, Shen K, Kacollja A, Tian H, Griffiths J, Bezgin G, McIntosh AR. Modeling the influence of the hippocampal memory system on the oculomotor system. Netw Neurosci 2020; 4:217-233. [PMID: 32166209 PMCID: PMC7055646 DOI: 10.1162/netn_a_00120] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 12/04/2019] [Indexed: 01/12/2023] Open
Abstract
Visual exploration is related to activity in the hippocampus (HC) and/or extended medial temporal lobe system (MTL), is influenced by stored memories, and is altered in amnesic cases. An extensive set of polysynaptic connections exists both within and between the HC and oculomotor systems such that investigating how HC responses ultimately influence neural activity in the oculomotor system, and the timing by which such neural modulation could occur, is not trivial. We leveraged TheVirtualBrain, a software platform for large-scale network simulations, to model the functional dynamics that govern the interactions between the two systems in the macaque cortex. Evoked responses following the stimulation of the MTL and some, but not all, subfields of the HC resulted in observable responses in oculomotor regions, including the frontal eye fields, within the time of a gaze fixation. Modeled lesions to some MTL regions slowed the dissipation of HC signal to oculomotor regions, whereas HC lesions generally did not affect the rapid MTL activity propagation to oculomotor regions. These findings provide a framework for investigating how information represented by the HC/MTL may influence the oculomotor system during a fixation and predict how HC lesions may affect visual exploration.
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Affiliation(s)
- Jennifer D Ryan
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Kelly Shen
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Arber Kacollja
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Heather Tian
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - John Griffiths
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Gleb Bezgin
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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37
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Suárez LE, Markello RD, Betzel RF, Misic B. Linking Structure and Function in Macroscale Brain Networks. Trends Cogn Sci 2020; 24:302-315. [PMID: 32160567 DOI: 10.1016/j.tics.2020.01.008] [Citation(s) in RCA: 337] [Impact Index Per Article: 84.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/20/2020] [Accepted: 01/21/2020] [Indexed: 02/06/2023]
Abstract
Structure-function relationships are a fundamental principle of many naturally occurring systems. However, network neuroscience research suggests that there is an imperfect link between structural connectivity and functional connectivity in the brain. Here, we synthesize the current state of knowledge linking structure and function in macroscale brain networks and discuss the different types of models used to assess this relationship. We argue that current models do not include the requisite biological detail to completely predict function. Structural network reconstructions enriched with local molecular and cellular metadata, in concert with more nuanced representations of functions and properties, hold great potential for a truly multiscale understanding of the structure-function relationship.
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Affiliation(s)
- Laura E Suárez
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Richard F Betzel
- Psychological and Brain Sciences, Program in Neuroscience, Cognitive Science Program, Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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38
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Miller TD, Chong TTJ, Aimola Davies AM, Johnson MR, Irani SR, Husain M, Ng TWC, Jacob S, Maddison P, Kennard C, Gowland PA, Rosenthal CR. Human hippocampal CA3 damage disrupts both recent and remote episodic memories. eLife 2020; 9:e41836. [PMID: 31976861 PMCID: PMC6980860 DOI: 10.7554/elife.41836] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 12/05/2019] [Indexed: 12/31/2022] Open
Abstract
Neocortical-hippocampal interactions support new episodic (event) memories, but there is conflicting evidence about the dependence of remote episodic memories on the hippocampus. In line with systems consolidation and computational theories of episodic memory, evidence from model organisms suggests that the cornu ammonis 3 (CA3) hippocampal subfield supports recent, but not remote, episodic retrieval. In this study, we demonstrated that recent and remote memories were susceptible to a loss of episodic detail in human participants with focal bilateral damage to CA3. Graph theoretic analyses of 7.0-Tesla resting-state fMRI data revealed that CA3 damage disrupted functional integration across the medial temporal lobe (MTL) subsystem of the default network. The loss of functional integration in MTL subsystem regions was predictive of autobiographical episodic retrieval performance. We conclude that human CA3 is necessary for the retrieval of episodic memories long after their initial acquisition and functional integration of the default network is important for autobiographical episodic memory performance.
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Affiliation(s)
- Thomas D Miller
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Department of NeurologyRoyal Free HospitalLondonUnited Kingdom
| | - Trevor T-J Chong
- Monash Institute of Cognitive and Clinical NeurosciencesMonash UniversityClaytonAustralia
| | - Anne M Aimola Davies
- Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Research School of PsychologyAustralian National UniversityCanberraAustralia
| | - Michael R Johnson
- Division of Brain SciencesImperial College LondonLondonUnited Kingdom
| | - Sarosh R Irani
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - Masud Husain
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
| | - Tammy WC Ng
- Department of AnaesthesticsRoyal Free HospitalLondonUnited Kingdom
| | - Saiju Jacob
- Neurology Department, Queen Elizabeth Neuroscience CentreUniversity Hospitals of BirminghamBirminghamUnited Kingdom
| | - Paul Maddison
- Neurology DepartmentQueen’s Medical CentreNottinghamUnited Kingdom
| | - Christopher Kennard
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - Penny A Gowland
- Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUnited Kingdom
| | - Clive R Rosenthal
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
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39
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Clark R, Punzo G, Macdonald M. Network Communities of Dynamical Influence. Sci Rep 2019; 9:17590. [PMID: 31772210 PMCID: PMC6879613 DOI: 10.1038/s41598-019-53942-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/18/2019] [Indexed: 12/04/2022] Open
Abstract
Fuelled by a desire for greater connectivity, networked systems now pervade our society at an unprecedented level that will affect it in ways we do not yet understand. In contrast, nature has already developed efficient networks that can instigate rapid response and consensus when key elements are stimulated. We present a technique for identifying these key elements by investigating the relationships between a system's most dominant eigenvectors. This approach reveals the most effective vertices for leading a network to rapid consensus when stimulated, as well as the communities that form under their dynamical influence. In applying this technique, the effectiveness of starling flocks was found to be due, in part, to the low outdegree of every bird, where increasing the number of outgoing connections can produce a less responsive flock. A larger outdegree also affects the location of the birds with the most influence, where these influentially connected birds become more centrally located and in a poorer position to observe a predator and, hence, instigate an evasion manoeuvre. Finally, the technique was found to be effective in large voxel-wise brain connectomes where subjects can be identified from their influential communities.
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Affiliation(s)
- Ruaridh Clark
- Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow, United Kingdom.
| | - Giuliano Punzo
- Department of Automatic Control and Systems, University of Sheffield, Sheffield, United Kingdom
| | - Malcolm Macdonald
- Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow, United Kingdom
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40
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Mišic B, Betzel RF, Griffa A, de Reus MA, He Y, Zuo XN, van den Heuvel MP, Hagmann P, Sporns O, Zatorre RJ. Network-Based Asymmetry of the Human Auditory System. Cereb Cortex 2019; 28:2655-2664. [PMID: 29722805 PMCID: PMC5998951 DOI: 10.1093/cercor/bhy101] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 04/13/2018] [Indexed: 01/12/2023] Open
Abstract
Converging evidence from activation, connectivity, and stimulation studies suggests that auditory brain networks are lateralized. Here we show that these findings can be at least partly explained by the asymmetric network embedding of the primary auditory cortices. Using diffusion-weighted imaging in 3 independent datasets, we investigate the propensity for left and right auditory cortex to communicate with other brain areas by quantifying the centrality of the auditory network across a spectrum of communication mechanisms, from shortest path communication to diffusive spreading. Across all datasets, we find that the right auditory cortex is better integrated in the connectome, facilitating more efficient communication with other areas, with much of the asymmetry driven by differences in communication pathways to the opposite hemisphere. Critically, the primacy of the right auditory cortex emerges only when communication is conceptualized as a diffusive process, taking advantage of more than just the topologically shortest paths in the network. Altogether, these results highlight how the network configuration and embedding of a particular region may contribute to its functional lateralization.
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Affiliation(s)
- Bratislav Mišic
- Montréal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Richard F Betzel
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Griffa
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Marcel A de Reus
- Brain Center Rudolf Magnus, UMC Utrecht, Utrecht, The Netherlands
| | - Ye He
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, People's Republic of China.,Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Xi-Nian Zuo
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, People's Republic of China
| | | | - Patric Hagmann
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Robert J Zatorre
- Montréal Neurological Institute, McGill University, Montreal, Quebec, Canada
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41
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Abstract
The white matter architecture of brain networks promotes synchrony among neuronal populations, giving rise to richly patterned functional networks. Relating structure and function is a fundamental question for systems neuroscience, but the nature of the relationship is unknown. Here we examine the possibility that structure–function relationships are not uniform in the brain. We find that structure and function are closely aligned in unimodal cortex (primary sensory and motor regions), but diverge in transmodal cortex (default mode and salience networks). The divergence between structure and function closely follows representational and cytoarchitectonic hierarchies, reflecting a macroscale gradient. Our findings suggest structure and function are not uniformly related, but gradually decouple in parallel to this macroscale gradient. The white matter architecture of the brain imparts a distinct signature on neuronal coactivation patterns. Interregional projections promote synchrony among distant neuronal populations, giving rise to richly patterned functional networks. A variety of statistical, communication, and biophysical models have been proposed to study the relationship between brain structure and function, but the link is not yet known. In the present report we seek to relate the structural and functional connection profiles of individual brain areas. We apply a simple multilinear model that incorporates information about spatial proximity, routing, and diffusion between brain regions to predict their functional connectivity. We find that structure–function relationships vary markedly across the neocortex. Structure and function correspond closely in unimodal, primary sensory, and motor regions, but diverge in transmodal cortex, particularly the default mode and salience networks. The divergence between structure and function systematically follows functional and cytoarchitectonic hierarchies. Altogether, the present results demonstrate that structural and functional networks do not align uniformly across the brain, but gradually uncouple in higher-order polysensory areas.
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42
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Zhu F, Cizeron M, Qiu Z, Benavides-Piccione R, Kopanitsa MV, Skene NG, Koniaris B, DeFelipe J, Fransén E, Komiyama NH, Grant SGN. Architecture of the Mouse Brain Synaptome. Neuron 2018; 99:781-799.e10. [PMID: 30078578 PMCID: PMC6117470 DOI: 10.1016/j.neuron.2018.07.007] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 06/22/2018] [Accepted: 07/03/2018] [Indexed: 12/11/2022]
Abstract
Synapses are found in vast numbers in the brain and contain complex proteomes. We developed genetic labeling and imaging methods to examine synaptic proteins in individual excitatory synapses across all regions of the mouse brain. Synapse catalogs were generated from the molecular and morphological features of a billion synapses. Each synapse subtype showed a unique anatomical distribution, and each brain region showed a distinct signature of synapse subtypes. Whole-brain synaptome cartography revealed spatial architecture from dendritic to global systems levels and previously unknown anatomical features. Synaptome mapping of circuits showed correspondence between synapse diversity and structural and functional connectomes. Behaviorally relevant patterns of neuronal activity trigger spatiotemporal postsynaptic responses sensitive to the structure of synaptome maps. Areas controlling higher cognitive function contain the greatest synapse diversity, and mutations causing cognitive disorders reorganized synaptome maps. Synaptome technology and resources have wide-ranging application in studies of the normal and diseased brain.
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Affiliation(s)
- Fei Zhu
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; UCL Institute of Neurology, Queen Square, WC1N 3BG London, UK
| | - Mélissa Cizeron
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; Institut NeuroMyoGène, Université de Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5310, INSERM U-1217, 69008 Lyon, France
| | - Zhen Qiu
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Ruth Benavides-Piccione
- Instituto Cajal (CSIC) 28002 Madrid, Centro de Tecnología Biomédica (UPM) 28223 Madrid; CIBERNED, ISCIII, 28031 Madrid, Spain
| | - Maksym V Kopanitsa
- Synome Ltd, Babraham Research Campus, Cambridge CB22 3AT, UK; UK Dementia Research Institute, Imperial College London, London W12 0NN, UK
| | - Nathan G Skene
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; UCL Institute of Neurology, Queen Square, WC1N 3BG London, UK; Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Babis Koniaris
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Javier DeFelipe
- Instituto Cajal (CSIC) 28002 Madrid, Centro de Tecnología Biomédica (UPM) 28223 Madrid; CIBERNED, ISCIII, 28031 Madrid, Spain
| | - Erik Fransén
- Department of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
| | - Noboru H Komiyama
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Seth G N Grant
- Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.
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43
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Arnold AEGF, Ekstrom AD, Iaria G. Dynamic Neural Network Reconfiguration During the Generation and Reinstatement of Mnemonic Representations. Front Hum Neurosci 2018; 12:292. [PMID: 30079017 PMCID: PMC6062623 DOI: 10.3389/fnhum.2018.00292] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 07/02/2018] [Indexed: 01/03/2023] Open
Abstract
Mnemonic representations allow humans to re-experience the past or simulate future scenarios by integrating episodic features from memory. Theoretical models posit that mnemonic representations require dynamic processing between neural indexes in the hippocampus and areas of the cortex providing specialized information processing. However, it remains unknown whether global and local network topology varies as information is encoded into a mnemonic representation and subsequently reinstated. Here, we investigated the dynamic nature of memory networks while a representation of a virtual city is generated and reinstated during mental simulations. We find that the brain reconfigures from a state of heightened integration when encoding demands are highest, to a state of localized processing once representations are formed. This reconfiguration is associated with changes in hippocampal centrality at the intra- and inter-module level, decreasing its role as a connector hub between modules and within a hippocampal neighborhood as encoding demands lessen. During mental simulations, we found increased levels of hippocampal centrality within its local neighborhood coupled with decreased functional interactions between other regions of the neighborhood during highly vivid simulations, suggesting that information flow vis-à-vis the hippocampus is critical for high fidelity recapitulation of mnemonic representations.
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Affiliation(s)
- Aiden E G F Arnold
- Department of Psychology, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada.,Center for Neuroscience, University of California, Davis, Davis, CA, United States
| | - Arne D Ekstrom
- Center for Neuroscience, University of California, Davis, Davis, CA, United States.,Department of Psychology, University of California, Davis, Davis, CA, United States.,Neuroscience Graduate Group, University of California, Davis, Davis, CA, United States
| | - Giuseppe Iaria
- Department of Psychology, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
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44
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Riley JD, Chen EE, Winsell J, Davis EP, Glynn LM, Baram TZ, Sandman CA, Small SL, Solodkin A. Network specialization during adolescence: Hippocampal effective connectivity in boys and girls. Neuroimage 2018; 175:402-412. [PMID: 29649560 PMCID: PMC5978413 DOI: 10.1016/j.neuroimage.2018.04.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 04/04/2018] [Accepted: 04/08/2018] [Indexed: 12/15/2022] Open
Abstract
Adolescence is a complex period of concurrent mental and physical development that facilitates adult functioning at multiple levels. Despite the growing number of neuroimaging studies of cognitive development in adolescence focusing on regional activation patterns, there remains a paucity of information about the functional interactions across these participating regions that are critical for cognitive functioning, including memory. The current study used structural equation modeling (SEM) to determine how interactions among brain regions critical for memory change over the course of adolescence. We obtained functional MRI in 77 individuals aged 8-16 years old, divided into younger (ages 8-10) and older (ages > 11) cohorts, using an incidental encoding memory task to activate hippocampus formation and associated brain networks, as well as behavioral data on memory function. SEM was performed on the imaging data for four groups (younger girls, younger boys, older girls, and older boys) that were subsequently compared using a stacked model approach. Significant differences were seen between the models for these groups. Younger boys had a predominantly posterior distribution of connections originating in primary visual regions and terminating on multi-modal processing regions. In older boys, there was a relatively greater anterior connection distribution, with increased effective connectivity within association and multi-modal processing regions. Connection patterns in younger girls were similar to those of older boys, with a generally anterior-posterior distributed network among sensory, multi-modal, and limbic regions. In contrast, connections in older girls were widely distributed but relatively weaker. Memory performance increased with age, without a significant difference between the sexes. These findings suggest a progressive reorganization among brain regions, with a commensurate increase in efficiency of cognitive functioning, from younger to older individuals in both girls and boys, providing insight into the age- and gender-specific processes at play during this critical transition period.
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Affiliation(s)
- Jeffrey D Riley
- Department of Neurology, University of California Irvine, USA.
| | - E Elinor Chen
- Department of Anatomy & Neurobiology, University of California Irvine, USA
| | - Jessica Winsell
- Department of Anatomy & Neurobiology, University of California Irvine, USA
| | | | - Laura M Glynn
- Department of Psychology, Chapman University, USA; Department of Psychiatry & Human Behavior, University of California Irvine, USA
| | - Tallie Z Baram
- Department of Neurology, University of California Irvine, USA; Department of Anatomy & Neurobiology, University of California Irvine, USA; Department of Pediatrics, University of California Irvine, USA
| | - Curt A Sandman
- Department of Psychiatry & Human Behavior, University of California Irvine, USA
| | - Steven L Small
- Department of Neurology, University of California Irvine, USA
| | - Ana Solodkin
- Department of Neurology, University of California Irvine, USA; Department of Anatomy & Neurobiology, University of California Irvine, USA
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45
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Sanchez-Rodriguez LM, Iturria-Medina Y, Baines EA, Mallo SC, Dousty M, Sotero RC. Design of optimal nonlinear network controllers for Alzheimer's disease. PLoS Comput Biol 2018; 14:e1006136. [PMID: 29795548 PMCID: PMC5967700 DOI: 10.1371/journal.pcbi.1006136] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 04/12/2018] [Indexed: 12/26/2022] Open
Abstract
Brain stimulation can modulate the activity of neural circuits impaired by Alzheimer’s disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients’ biological variability. We used anatomical networks obtained from diffusion magnetic resonance images acquired by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) as mediators for the interaction between Duffing oscillators. The nonlinear nature of the brain dynamics is preserved, given that we extend the so-called state-dependent Riccati equation control to reflect the stimulation objective in the high-dimensional neural system. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. There are changes to the way stimulated regions are ranked in terms of the energetic cost of controlling the entire network, from a linear to a nonlinear approach. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks–namely, networks having low average shortest path length, high global efficiency–are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework. This work aims to close the knowledge gap between theory and experiment in brain stimulation. Previous modeling approaches for stimulation have overlooked the nonlinear dynamical nature of the brain and failed to shed light on efficient mechanisms for the exogenous control of the brain. Amid the current efforts for developing personalized medicine, we introduce a framework for producing tailored stimulation signals, based on individual neuroimaging data and innovative modeling. This is the first time, to our knowledge, that brain stimulation for the most common cause of dementia, Alzheimer’s disease, is theoretically addressed. Our approach leads to the identification of potential target regions and subjects to successfully respond to brain stimulation therapies and yields various disease-reverting signals. Although focused on Alzheimer’s in this study, our methodology could be applied to other clinical conditions characterized by abnormalities in brain dynamics, like epilepsy and Parkinson’s, the treatment of which can benefit from the use of optimal control strategies.
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Affiliation(s)
- Lazaro M. Sanchez-Rodriguez
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- * E-mail: (LMSR); (RCS)
| | - Yasser Iturria-Medina
- Department of Neurology & Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada
- Ludmer Centre for NeuroInformatics and Mental Health, Montreal, Quebec, Canada
| | - Erica A. Baines
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Sabela C. Mallo
- Departament of Developmental Psychology, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Mehdy Dousty
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Roberto C. Sotero
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- * E-mail: (LMSR); (RCS)
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46
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Geib BR, Stanley ML, Wing EA, Laurienti PJ, Cabeza R. Hippocampal Contributions to the Large-Scale Episodic Memory Network Predict Vivid Visual Memories. Cereb Cortex 2018; 27:680-693. [PMID: 26523034 DOI: 10.1093/cercor/bhv272] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A common approach in memory research is to isolate the function(s) of individual brain regions, such as the hippocampus, without addressing how those regions interact with the larger network. To investigate the properties of the hippocampus embedded within large-scale networks, we used functional magnetic resonance imaging and graph theory to characterize complex hippocampal interactions during the active retrieval of vivid versus dim visual memories. The study yielded 4 main findings. First, the right hippocampus displayed greater communication efficiency with the network (shorter path length) and became a more convergent structure for information integration (higher centrality measures) for vivid than dim memories. Second, vivid minus dim differences in our graph theory measures of interest were greater in magnitude for the right hippocampus than for any other region in the 90-region network. Moreover, the right hippocampus significantly reorganized its set of direct connections from dim to vivid memory retrieval. Finally, beyond the hippocampus, communication throughout the whole-brain network was more efficient (shorter global path length) for vivid than dim memories. In sum, our findings illustrate how multivariate network analyses can be used to investigate the roles of specific regions within the large-scale network, while also accounting for global network changes.
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Affiliation(s)
- Benjamin R Geib
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Matthew L Stanley
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Erik A Wing
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Paul J Laurienti
- Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Roberto Cabeza
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
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47
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48
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Worrell JC, Rumschlag J, Betzel RF, Sporns O, Mišić B. Optimized connectome architecture for sensory-motor integration. Netw Neurosci 2017; 1:415-430. [PMID: 30090872 PMCID: PMC6063718 DOI: 10.1162/netn_a_00022] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 07/05/2017] [Indexed: 01/15/2023] Open
Abstract
The intricate connectivity patterns of neural circuits support a wide repertoire of communication processes and functional interactions. Here we systematically investigate how neural signaling is constrained by anatomical connectivity in the mesoscale Drosophila (fruit fly) brain network. We use a spreading model that describes how local perturbations, such as external stimuli, trigger global signaling cascades that spread through the network. Through a series of simple biological scenarios we demonstrate that anatomical embedding potentiates sensory-motor integration. We find that signal spreading is faster from nodes associated with sensory transduction (sensors) to nodes associated with motor output (effectors). Signal propagation was accelerated if sensor nodes were activated simultaneously, suggesting a topologically mediated synergy among sensors. In addition, the organization of the network increases the likelihood of convergence of multiple cascades towards effector nodes, thereby facilitating integration prior to motor output. Moreover, effector nodes tend to coactivate more frequently than other pairs of nodes, suggesting an anatomically enhanced coordination of motor output. Altogether, our results show that the organization of the mesoscale Drosophila connectome imparts privileged, behaviorally relevant communication patterns among sensors and effectors, shaping their capacity to collectively integrate information. The complex network spanned by neurons and their axonal projections promotes a diverse set of functions. In the present report, we study how the topological organization of the fruit fly brain supports sensory-motor integration. Using a simple communication model, we demonstrate that the topology of this network allows efficient coordination among sensory and motor neurons. Our results suggest that brain network organization may profoundly shape the functional repertoire of this simple organism.
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Affiliation(s)
- Jacob C Worrell
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Jeffrey Rumschlag
- Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA, USA
| | - Richard F Betzel
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Bratislav Mišić
- Montréal Neurological Institute, McGill University, Montréal, Canada
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49
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Ekstrom AD, Huffman DJ, Starrett M. Interacting networks of brain regions underlie human spatial navigation: a review and novel synthesis of the literature. J Neurophysiol 2017; 118:3328-3344. [PMID: 28931613 PMCID: PMC5814720 DOI: 10.1152/jn.00531.2017] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 09/19/2017] [Accepted: 09/19/2017] [Indexed: 12/22/2022] Open
Abstract
Navigation is an inherently dynamic and multimodal process, making isolation of the unique cognitive components underlying it challenging. The assumptions of much of the literature on human spatial navigation are that 1) spatial navigation involves modality independent, discrete metric representations (i.e., egocentric vs. allocentric), 2) such representations can be further distilled to elemental cognitive processes, and 3) these cognitive processes can be ascribed to unique brain regions. We argue that modality-independent spatial representations, instead of providing exact metrics about our surrounding environment, more often involve heuristics for estimating spatial topology useful to the current task at hand. We also argue that egocentric (body centered) and allocentric (world centered) representations are better conceptualized as involving a continuum rather than as discrete. We propose a neural model to accommodate these ideas, arguing that such representations also involve a continuum of network interactions centered on retrosplenial and posterior parietal cortex, respectively. Our model thus helps explain both behavioral and neural findings otherwise difficult to account for with classic models of spatial navigation and memory, providing a testable framework for novel experiments.
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Affiliation(s)
- Arne D Ekstrom
- Center for Neuroscience, University of California , Davis, California
- Department of Psychology, University of California , Davis, California
- Neuroscience Graduate Group, University of California , Davis, California
| | - Derek J Huffman
- Center for Neuroscience, University of California , Davis, California
| | - Michael Starrett
- Center for Neuroscience, University of California , Davis, California
- Department of Psychology, University of California , Davis, California
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Wig GS. Segregated Systems of Human Brain Networks. Trends Cogn Sci 2017; 21:981-996. [DOI: 10.1016/j.tics.2017.09.006] [Citation(s) in RCA: 128] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/06/2017] [Accepted: 09/11/2017] [Indexed: 12/17/2022]
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