1
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Martin KAC, Sägesser FD. A strong direct link from the layer 3/4 border to layer 6 of cat primary visual cortex. Brain Struct Funct 2024; 229:1397-1415. [PMID: 38753019 PMCID: PMC11176106 DOI: 10.1007/s00429-024-02806-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 05/05/2024] [Indexed: 06/15/2024]
Abstract
The cat primary visual cortex (V1) is a cortical area for which we have one of the most detailed estimates of the connection 'weights' (expressed as number of synapses) between different neural populations in different layers (Binzegger et al in J Neurosci 24:8441-8453, 2004). Nevertheless, the majority of excitatory input sources to layer 6, the deepest layer in a local translaminar excitatory feedforward loop, was not accounted for by the known neuron types used to generate the quantitative Binzegger diagram. We aimed to fill this gap by using a retrograde tracer that would label neural cell bodies in and outside V1 that directly connect to layer 6 of V1. We found that more than 80% of labeled neurons projecting to layer 6 were within V1 itself. Our data indicate that a substantial fraction of the missing input is provided by a previously unidentified population of layer 3/4 border neurons, laterally distributed and connecting more strongly to layer 6 than the typical superficial layer pyramidal neurons considered by Binzegger et al. (Binzegger et al in J Neurosci 24:8441-8453, 2004). This layer 3/4 to layer 6 connection may be a parallel route to the layer 3 - layer 5 - layer 6 feedforward pathway, be associated with the fast-conducting, movement-related Y pathway and provide convergent input from distant (5-10 degrees) regions of the visual field.
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2
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Pailthorpe BA. Network analysis of marmoset cortical connections reveals pFC and sensory clusters. Front Neuroanat 2024; 18:1403170. [PMID: 38933918 PMCID: PMC11199858 DOI: 10.3389/fnana.2024.1403170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/10/2024] [Indexed: 06/28/2024] Open
Abstract
A new analysis is presented of the retrograde tracer measurements of connections between anatomical areas of the marmoset cortex. The original normalisation of raw data yields the fractional link weight measure, FLNe. That is re-examined to consider other possible measures that reveal the underlying in link weights. Predictions arising from both are used to examine network modules and hubs. With inclusion of the in weights the InfoMap algorithm identifies eight structural modules in marmoset cortex. In and out hubs and major connector nodes are identified using module assignment and participation coefficients. Time evolving network tracing around the major hubs reveals medium sized clusters in pFC, temporal, auditory and visual areas; the most tightly coupled and significant of which is in the pFC. A complementary viewpoint is provided by examining the highest traffic links in the cortical network, and reveals parallel sensory flows to pFC and via association areas to frontal areas.
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Affiliation(s)
- Bernard A. Pailthorpe
- Brain Dynamics Group, School of Physics, The University of Sydney, Sydney, NSW, Australia
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3
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Spillmann L. Watercolor spreading in Bridget Riley's and Piet Mondrian's op-art placed in the context of recent watercolor studies. J Vis 2024; 24:15. [PMID: 38913017 PMCID: PMC11204060 DOI: 10.1167/jov.24.6.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 05/17/2024] [Indexed: 06/25/2024] Open
Abstract
The watercolor effect (WCE) is a striking visual illusion elicited by a bichromatic double contour, such as a light orange and a dark purple, hugging each other on a white background. Color assimilation, emanating from the lighter contour, spreads onto the enclosed surface area, thereby tinting it with a chromatic veil, not unlike a weak but real color. Map makers in the 17th century utilized the WCE to better demarcate the shape of adjoining states, while 20th-century artist Bridget Riley created illusory watercolor as part of her op-art. Today's visual scientists study the WCE for its filling-in properties and strong figure-ground segregation. This review emphasizes the superior strength of the WCE for grouping and figure-ground organization vis-à-vis the classical Gestalt factors of Max Wertheimer (1923), thereby inspiring a notion of form from induced color. It also demonstrates that a thin chromatic line, flanking the inside of a black Mondrian-type pattern, induces the WCE across a large white surface area. Phenomenological, psychophysical, and neurophysiological approaches are reviewed.
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Affiliation(s)
- Lothar Spillmann
- Department of Neurology, University of Freiburg, Freiburg, Germany
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4
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Magrou L, Joyce MKP, Froudist-Walsh S, Datta D, Wang XJ, Martinez-Trujillo J, Arnsten AFT. The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition. Cereb Cortex 2024; 34:bhae174. [PMID: 38771244 PMCID: PMC11107384 DOI: 10.1093/cercor/bhae174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/29/2024] [Accepted: 04/08/2024] [Indexed: 05/22/2024] Open
Abstract
The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.
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Affiliation(s)
- Loïc Magrou
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Mary Kate P Joyce
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Sean Froudist-Walsh
- School of Engineering Mathematics and Technology, University of Bristol, Bristol, BS8 1QU, United Kingdom
| | - Dibyadeep Datta
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Xiao-Jing Wang
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Julio Martinez-Trujillo
- Departments of Physiology and Pharmacology, and Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 3K7, Canada
| | - Amy F T Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
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5
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Yin J, Xu G, Xie H, Liu Y, Dou Z, Shao B, Li Z. Effects of different frequencies music on cortical responses and functional connectivity in patients with minimal conscious state. JOURNAL OF BIOPHOTONICS 2024; 17:e202300427. [PMID: 38303080 DOI: 10.1002/jbio.202300427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/04/2023] [Accepted: 12/19/2023] [Indexed: 02/03/2024]
Abstract
The objective of this study was to investigate brain activation and functional network patterns during musical interventions in different frequency bands using functional near-infrared spectroscopy, and to provide a basis for more effective music therapy strategy selection for patients in minimally conscious state (MCS). Twenty six MCS patients and 20 healthy people were given music intervention with low frequency (31-180 Hz), medium frequency (180-4k Hz), and high frequency (4k-22k Hz) audio. In MCS patients, low frequency music intervention induced activation of left prefrontal cortex and left primary sensory cortex (S1), also a left-hemisphere lateralization effect of dorsolateral prefrontal cortex (DLPFC). And the functional connectivity of right DLPFC-right S1 was significantly improved by high frequency music intervention. The low frequency and high frequency music may contribute more than medium frequency music to the recovery of consciousness. This study also validated the effectiveness of fNIRS in studies of brain function in MCS patients.
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Affiliation(s)
- Jiahui Yin
- School of Physical Education, Shanghai University of Sport, Shanghai, China
| | - Gongcheng Xu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Hui Xie
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Ying Liu
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, China
| | - Zulin Dou
- Department of Rehabilitation Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Bin Shao
- School of Physical Education, Shanghai University of Sport, Shanghai, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, China
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6
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Lewis CM, Wunderle T, Fries P. Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589006. [PMID: 38645050 PMCID: PMC11030389 DOI: 10.1101/2024.04.11.589006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.
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7
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Molnár F, Horvát S, Ribeiro Gomes AR, Martinez Armas J, Molnár B, Ercsey-Ravasz M, Knoblauch K, Kennedy H, Toroczkai Z. Predictability of cortico-cortical connections in the mammalian brain. Netw Neurosci 2024; 8:138-157. [PMID: 38562298 PMCID: PMC10861169 DOI: 10.1162/netn_a_00345] [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: 08/02/2022] [Accepted: 10/23/2023] [Indexed: 04/04/2024] Open
Abstract
Despite a five order of magnitude range in size, the brains of mammals share many anatomical and functional characteristics that translate into cortical network commonalities. Here we develop a machine learning framework to quantify the degree of predictability of the weighted interareal cortical matrix. Partial network connectivity data were obtained with retrograde tract-tracing experiments generated with a consistent methodology, supplemented by projection length measurements in a nonhuman primate (macaque) and a rodent (mouse). We show that there is a significant level of predictability embedded in the interareal cortical networks of both species. At the binary level, links are predictable with an area under the ROC curve of at least 0.8 for the macaque. Weighted medium and strong links are predictable with an 85%-90% accuracy (mouse) and 70%-80% (macaque), whereas weak links are not predictable in either species. These observations reinforce earlier observations that the formation and evolution of the cortical network at the mesoscale is, to a large extent, rule based. Using the methodology presented here, we performed imputations on all area pairs, generating samples for the complete interareal network in both species. These are necessary for comparative studies of the connectome with minimal bias, both within and across species.
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Affiliation(s)
- Ferenc Molnár
- Department of Physics, University of Notre Dame, Notre Dame, IN, USA
| | - Szabolcs Horvát
- Center for Systems Biology Dresden, Dresden, Germany
- Max Planck Institute for Cell Biology and Genetics, Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
- Department of Computer Science, Reykjavik University, Reykjavík, Iceland
| | - Ana R. Ribeiro Gomes
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute, Bron, France
| | | | - Botond Molnár
- Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj-Napoca, Romania
- Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania
- Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
| | - Mária Ercsey-Ravasz
- Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania
- Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
| | - Kenneth Knoblauch
- National Centre for Optics, Vision and Eye Care, Faculty of Health and Social Sciences, University of South-Eastern Norway, Kongsberg, Norway
| | - Henry Kennedy
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Zoltan Toroczkai
- Department of Physics, University of Notre Dame, Notre Dame, IN, USA
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8
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Wright J, Bourke P. Markov Blankets and Mirror Symmetries-Free Energy Minimization and Mesocortical Anatomy. ENTROPY (BASEL, SWITZERLAND) 2024; 26:287. [PMID: 38667842 PMCID: PMC11049374 DOI: 10.3390/e26040287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024]
Abstract
A theoretical account of development in mesocortical anatomy is derived from the free energy principle, operating in a neural field with both Hebbian and anti-Hebbian neural plasticity. An elementary structural unit is proposed, in which synaptic connections at mesoscale are arranged in paired patterns with mirror symmetry. Exchanges of synaptic flux in each pattern form coupled spatial eigenmodes, and the line of mirror reflection between the paired patterns operates as a Markov blanket, so that prediction errors in exchanges between the pairs are minimized. The theoretical analysis is then compared to the outcomes from a biological model of neocortical development, in which neuron precursors are selected by apoptosis for cell body and synaptic connections maximizing synchrony and also minimizing axonal length. It is shown that this model results in patterns of connection with the anticipated mirror symmetries, at micro-, meso- and inter-arial scales, among lateral connections, and in cortical depth. This explains the spatial organization and functional significance of neuron response preferences, and is compatible with the structural form of both columnar and noncolumnar cortex. Multi-way interactions of mirrored representations can provide a preliminary anatomically realistic model of cortical information processing.
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Affiliation(s)
- James Wright
- Centre for Brain Research, and Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland 1010, New Zealand
| | - Paul Bourke
- School of Social Sciences, Faculty of Arts, Business, Law and Education, University of Western Australia, Perth, WA 6009, Australia
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9
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Orsher Y, Rom A, Perel R, Lahini Y, Blinder P, Shein-Idelson M. Sequentially activated discrete modules appear as traveling waves in neuronal measurements with limited spatiotemporal sampling. eLife 2024; 12:RP92254. [PMID: 38451063 PMCID: PMC10942589 DOI: 10.7554/elife.92254] [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] [Indexed: 03/08/2024] Open
Abstract
Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.
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Affiliation(s)
- Yuval Orsher
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
| | - Ariel Rom
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Rotem Perel
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
| | - Yoav Lahini
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Pablo Blinder
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Mark Shein-Idelson
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
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10
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Assimopoulos S, Warrington S, Bryant KL, Pszczolkowski S, Jbabdi S, Mars RB, Sotiropoulos SN. Generalising XTRACT tractography protocols across common macaque brain templates. Brain Struct Funct 2024:10.1007/s00429-024-02760-0. [PMID: 38388696 DOI: 10.1007/s00429-024-02760-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/09/2024] [Indexed: 02/24/2024]
Abstract
Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human-macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates.
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Affiliation(s)
- Stephania Assimopoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Shaun Warrington
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Katherine L Bryant
- Laboratoire de Psychologie Cognitive, Aix-Marseille Université, Marseille, France
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stefan Pszczolkowski
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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11
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Davis ZW, Busch A, Stewerd C, Muller L, Reynolds J. Horizontal cortical connections shape intrinsic traveling waves into feature-selective motifs that regulate perceptual sensitivity. RESEARCH SQUARE 2024:rs.3.rs-3830199. [PMID: 38260448 PMCID: PMC10802692 DOI: 10.21203/rs.3.rs-3830199/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Intrinsic, ongoing fluctuations of cortical activity form traveling waves that modulate the gain of sensory-evoked responses and perceptual sensitivity. Several lines of evidence suggest that intrinsic traveling waves (iTWs) may arise, in part, from the coordination of synaptic activity through the recurrent horizontal connectivity within cortical areas, which include long range patchy connections that link neurons with shared feature preferences. In a spiking network model with anatomical topology that incorporates feature-selective patchy connections, which we call the Balanced Patchy Network (BPN), we observe repeated iTWs, which we refer to as motifs. In the model, motifs stem from fluctuations in the excitability of like-tuned neurons that result from shifts in E/I balance as action potentials traverse these patchy connections. To test if feature-selective motifs occur in vivo, we examined data previously recorded using multielectrode arrays in Area MT of marmosets trained to perform a threshold visual detection task. Using a newly developed method for comparing the similarity of wave patterns we found that some iTWs can be grouped into motifs. As predicted by the BPN, many of these motifs are feature selective, exhibiting direction-selective modulations in ongoing spiking activity. Further, motifs modulate the gain of the response evoked by a target and perceptual sensitivity to the target if the target matches the preference of the motif. These results provide evidence that iTWs are shaped by the patterns of horizontal fiber projections in the cortex and that patchy connections enable iTWs to regulate neural and perceptual sensitivity in a feature selective manner.
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Affiliation(s)
- Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA. 92037
- Department of Ophthalmology and Visual Science, University of Utah, SLC, UT, USA 84112
| | - Alexandria Busch
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - Christopher Stewerd
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - Lyle Muller
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - John Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA. 92037
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12
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Dura-Bernal S, Griffith EY, Barczak A, O'Connell MN, McGinnis T, Moreira JVS, Schroeder CE, Lytton WW, Lakatos P, Neymotin SA. Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics. Cell Rep 2023; 42:113378. [PMID: 37925640 PMCID: PMC10727489 DOI: 10.1016/j.celrep.2023.113378] [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: 09/07/2022] [Revised: 09/05/2023] [Accepted: 10/19/2023] [Indexed: 11/07/2023] Open
Abstract
We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.
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Affiliation(s)
- Salvador Dura-Bernal
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Erica Y Griffith
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Annamaria Barczak
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Monica N O'Connell
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Tammy McGinnis
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Joao V S Moreira
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Departments of Psychiatry and Neurology, Columbia University Medical Center, New York, NY, USA
| | - William W Lytton
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Kings County Hospital Center, Brooklyn, NY, USA
| | - Peter Lakatos
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Samuel A Neymotin
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department Psychiatry, NYU Grossman School of Medicine, New York, NY, USA.
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13
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Benigno GB, Budzinski RC, Davis ZW, Reynolds JH, Muller L. Waves traveling over a map of visual space can ignite short-term predictions of sensory input. Nat Commun 2023; 14:3409. [PMID: 37296131 PMCID: PMC10256723 DOI: 10.1038/s41467-023-39076-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
Recent analyses have found waves of neural activity traveling across entire visual cortical areas in awake animals. These traveling waves modulate the excitability of local networks and perceptual sensitivity. The general computational role of these spatiotemporal patterns in the visual system, however, remains unclear. Here, we hypothesize that traveling waves endow the visual system with the capacity to predict complex and naturalistic inputs. We present a network model whose connections can be rapidly and efficiently trained to predict individual natural movies. After training, a few input frames from a movie trigger complex wave patterns that drive accurate predictions many frames into the future solely from the network's connections. When the recurrent connections that drive waves are randomly shuffled, both traveling waves and the ability to predict are eliminated. These results suggest traveling waves may play an essential computational role in the visual system by embedding continuous spatiotemporal structures over spatial maps.
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Affiliation(s)
- Gabriel B Benigno
- Department of Mathematics, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- Western Academy for Advanced Research, Western University, London, ON, Canada
| | - Roberto C Budzinski
- Department of Mathematics, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- Western Academy for Advanced Research, Western University, London, ON, Canada
| | - Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - John H Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lyle Muller
- Department of Mathematics, Western University, London, ON, Canada.
- Brain and Mind Institute, Western University, London, ON, Canada.
- Western Academy for Advanced Research, Western University, London, ON, Canada.
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14
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Abstract
The Entangled Brain (Pessoa, L., 2002. MIT Press) promotes the idea that we need to understand the brain as a complex, entangled system. Why does the complex systems perspective, one that entails emergent properties, matter for brain science? In fact, many neuroscientists consider these ideas a distraction. We discuss three principles of brain organization that inform the question of the interactional complexity of the brain: (1) massive combinatorial anatomical connectivity; (2) highly distributed functional coordination; and (3) networks/circuits as functional units. To motivate the challenges of mapping structure and function, we discuss neural circuits illustrating the high anatomical and functional interactional complexity typical in the brain. We discuss potential avenues for testing for network-level properties, including those relying on distributed computations across multiple regions. We discuss implications for brain science, including the need to characterize decentralized and heterarchical anatomical-functional organization. The view advocated has important implications for causation, too, because traditional accounts of causality provide poor candidates for explanation in interactionally complex systems like the brain given the distributed, mutual, and reciprocal nature of the interactions. Ultimately, to make progress understanding how the brain supports complex mental functions, we need to dissolve boundaries within the brain-those suggested to be associated with perception, cognition, action, emotion, motivation-as well as outside the brain, as we bring down the walls between biology, psychology, mathematics, computer science, philosophy, and so on.
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15
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Dowdall JR, Vinck M. Coherence fails to reliably capture inter-areal interactions in bidirectional neural systems with transmission delays. Neuroimage 2023; 271:119998. [PMID: 36863546 PMCID: PMC7614400 DOI: 10.1016/j.neuroimage.2023.119998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/05/2023] [Accepted: 02/27/2023] [Indexed: 03/04/2023] Open
Abstract
Accurately measuring and quantifying the underlying interactions between brain areas is crucial for understanding the flow of information in the brain. Of particular interest in the field of electrophysiology is the analysis and characterization of the spectral properties of these interactions. Coherence and Granger-Geweke causality are well-established, commonly used methods for quantifying inter-areal interactions, and are thought to reflect the strength of inter-areal interactions. Here we show that the application of both methods to bidirectional systems with transmission delays is problematic, especially for coherence. Under certain circumstances, coherence can be completely abolished despite there being a true underlying interaction. This problem occurs due to interference caused in the computation of coherence, and is an artifact of the method. We motivate an understanding of the problem through computational modelling and numerical simulations. In addition, we have developed two methods that can recover the true bidirectional interactions in the presence of transmission delays.
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Affiliation(s)
- Jarrod Robert Dowdall
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany; Robarts Research Institute, Western University, London, Ontario, Canada.
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University, Nijmegen, The Netherlands.
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16
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Wang Y, Royer J, Park BY, Vos de Wael R, Larivière S, Tavakol S, Rodriguez-Cruces R, Paquola C, Hong SJ, Margulies DS, Smallwood J, Valk SL, Evans AC, Bernhardt BC. Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain. Cereb Cortex 2023; 33:1782-1798. [PMID: 35596951 PMCID: PMC9977370 DOI: 10.1093/cercor/bhac172] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry. METHODS We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections. RESULTS Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture. CONCLUSIONS By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.
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Affiliation(s)
- Yezhou Wang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Department of Data Science, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, South Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea
| | - Daniel S Margulies
- Cognitive Neuroanatomy Lab, Integrative Neuroscience and Cognition Centre, University of Paris and CRNS, INCC - UMR 8002, Rue des Saint-Pères 75006, Paris
| | - Jonathan Smallwood
- Department of Psychology, Queen's University, 62 Arch Street, Humphrey Hall, Room 232 Kingston, Ontario K7L 3N6, Canada
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A. Leipzig D-04103, Germany.,Institute of Systems Neuroscience, Heinrich Heine University, Moorenstr. 5, Düsseldorf 40225, Germany
| | - Alan C Evans
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
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17
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Angular gyrus: an anatomical case study for association cortex. Brain Struct Funct 2023; 228:131-143. [PMID: 35906433 DOI: 10.1007/s00429-022-02537-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/05/2022] [Indexed: 01/07/2023]
Abstract
The angular gyrus is associated with a spectrum of higher order cognitive functions. This mini-review undertakes a broad survey of putative neuroanatomical substrates, guided by the premise that area-specific specializations derive from a combination of extrinsic connections and intrinsic area properties. Three levels of spatial resolution are discussed: cellular, supracellular connectivity, and synaptic micro-scale, with examples necessarily drawn mainly from experimental work with nonhuman primates. A significant factor in the functional specialization of the human parietal cortex is the pronounced enlargement. In addition to "more" cells, synapses, and connections, however, the heterogeneity itself can be considered an important property. Multiple anatomical features support the idea of overlapping and temporally dynamic membership in several brain wide subnetworks, but how these features operate in the context of higher cognitive functions remains for continued investigations.
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18
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Jang YH, Kim H, Lee JY, Ahn JH, Chung AW, Lee HJ. Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants. Cereb Cortex 2022; 33:5507-5523. [PMID: 36408630 DOI: 10.1093/cercor/bhac438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.
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Affiliation(s)
- Yong Hun Jang
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Hyuna Kim
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Joo Young Lee
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Ja-Hye Ahn
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
| | - Ai Wern Chung
- Harvard Medical School Fetal Neonatal-Neuroimaging and Developmental Science Center, Boston Children’s Hospital, , Boston, MA 02115 , USA
- Harvard Medical School Department of Pediatrics, Boston Children’s Hospital, , Boston, MA 02115 , USA
| | - Hyun Ju Lee
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
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19
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Tiddia G, Golosio B, Albers J, Senk J, Simula F, Pronold J, Fanti V, Pastorelli E, Paolucci PS, van Albada SJ. Fast Simulation of a Multi-Area Spiking Network Model of Macaque Cortex on an MPI-GPU Cluster. Front Neuroinform 2022; 16:883333. [PMID: 35859800 PMCID: PMC9289599 DOI: 10.3389/fninf.2022.883333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/02/2022] [Indexed: 11/29/2022] Open
Abstract
Spiking neural network models are increasingly establishing themselves as an effective tool for simulating the dynamics of neuronal populations and for understanding the relationship between these dynamics and brain function. Furthermore, the continuous development of parallel computing technologies and the growing availability of computational resources are leading to an era of large-scale simulations capable of describing regions of the brain of ever larger dimensions at increasing detail. Recently, the possibility to use MPI-based parallel codes on GPU-equipped clusters to run such complex simulations has emerged, opening up novel paths to further speed-ups. NEST GPU is a GPU library written in CUDA-C/C++ for large-scale simulations of spiking neural networks, which was recently extended with a novel algorithm for remote spike communication through MPI on a GPU cluster. In this work we evaluate its performance on the simulation of a multi-area model of macaque vision-related cortex, made up of about 4 million neurons and 24 billion synapses and representing 32 mm2 surface area of the macaque cortex. The outcome of the simulations is compared against that obtained using the well-known CPU-based spiking neural network simulator NEST on a high-performance computing cluster. The results show not only an optimal match with the NEST statistical measures of the neural activity in terms of three informative distributions, but also remarkable achievements in terms of simulation time per second of biological activity. Indeed, NEST GPU was able to simulate a second of biological time of the full-scale macaque cortex model in its metastable state 3.1× faster than NEST using 32 compute nodes equipped with an NVIDIA V100 GPU each. Using the same configuration, the ground state of the full-scale macaque cortex model was simulated 2.4× faster than NEST.
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Affiliation(s)
- Gianmarco Tiddia
- Department of Physics, University of Cagliari, Monserrato, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Cagliari, Monserrato, Italy
| | - Bruno Golosio
- Department of Physics, University of Cagliari, Monserrato, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Cagliari, Monserrato, Italy
- *Correspondence: Bruno Golosio
| | - Jasper Albers
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Johanna Senk
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
| | - Francesco Simula
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
| | - Jari Pronold
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Viviana Fanti
- Department of Physics, University of Cagliari, Monserrato, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Cagliari, Monserrato, Italy
| | - Elena Pastorelli
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
| | | | - Sacha J. van Albada
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
- Faculty of Mathematics and Natural Sciences, Institute of Zoology, University of Cologne, Cologne, Germany
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20
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Ainsworth M, Wu Z, Browncross H, Mitchell AS, Bell AH, Buckley MJ. Frontopolar cortex shapes brain network structure across prefrontal and posterior cingulate cortex. Prog Neurobiol 2022; 217:102314. [DOI: 10.1016/j.pneurobio.2022.102314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 04/08/2022] [Accepted: 07/01/2022] [Indexed: 11/16/2022]
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21
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Oldham S, Fulcher BD, Aquino K, Arnatkevičiūtė A, Paquola C, Shishegar R, Fornito A. Modeling spatial, developmental, physiological, and topological constraints on human brain connectivity. SCIENCE ADVANCES 2022; 8:eabm6127. [PMID: 35658036 PMCID: PMC9166341 DOI: 10.1126/sciadv.abm6127] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 04/14/2022] [Indexed: 05/10/2023]
Abstract
The complex connectivity of nervous systems is thought to have been shaped by competitive selection pressures to minimize wiring costs and support adaptive function. Accordingly, recent modeling work indicates that stochastic processes, shaped by putative trade-offs between the cost and value of each connection, can successfully reproduce many topological properties of macroscale human connectomes measured with diffusion magnetic resonance imaging. Here, we derive a new formalism that more accurately captures the competing pressures of wiring cost minimization and topological complexity. We further show that model performance can be improved by accounting for developmental changes in brain geometry and associated wiring costs, and by using interregional transcriptional or microstructural similarity rather than topological wiring rules. However, all models struggled to capture topographical (i.e., spatial) network properties. Our findings highlight an important role for genetics in shaping macroscale brain connectivity and indicate that stochastic models offer an incomplete account of connectome organization.
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Affiliation(s)
- Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Murdoch Children’s Research Institute, Melbourne, VIC, Australia
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Sydney, NSW, Australia
| | - Kevin Aquino
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- School of Physics, The University of Sydney, Sydney, NSW, Australia
| | - Aurina Arnatkevičiūtė
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | - Casey Paquola
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
| | - Rosita Shishegar
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- The Australian e-Health Research Centre, CSIRO, Melbourne, VIC, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
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22
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Arcaro MJ, Livingstone MS, Kay KN, Weiner KS. The retrocalcarine sulcus maps different retinotopic representations in macaques and humans. Brain Struct Funct 2022; 227:1227-1245. [PMID: 34921348 PMCID: PMC9046316 DOI: 10.1007/s00429-021-02427-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 11/09/2021] [Indexed: 11/30/2022]
Abstract
Primate cerebral cortex is highly convoluted with much of the cortical surface buried in sulcal folds. The origins of cortical folding and its functional relevance have been a major focus of systems and cognitive neuroscience, especially when considering stereotyped patterns of cortical folding that are shared across individuals within a primate species and across multiple species. However, foundational questions regarding organizing principles shared across species remain unanswered. Taking a cross-species comparative approach with a careful consideration of historical observations, we investigate cortical folding relative to primary visual cortex (area V1). We identify two macroanatomical structures-the retrocalcarine and external calcarine sulci-in 24 humans and 6 macaque monkeys. We show that within species, these sulci are identifiable in all individuals, fall on a similar part of the V1 retinotopic map, and thus, serve as anatomical landmarks predictive of functional organization. Yet, across species, the underlying eccentricity representations corresponding to these macroanatomical structures differ strikingly across humans and macaques. Thus, the correspondence between retinotopic representation and cortical folding for an evolutionarily old structure like V1 is species-specific and suggests potential differences in developmental and experiential constraints across primates.
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Affiliation(s)
- Michael J Arcaro
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, 19146, USA
| | | | - Kendrick N Kay
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Kevin S Weiner
- Department of Psychology, University of California, Berkeley, Berkeley, CA, 94720, USA.
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, 94720, USA.
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23
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Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights. Proc Natl Acad Sci U S A 2022; 119:2110274119. [PMID: 35110401 PMCID: PMC8832993 DOI: 10.1073/pnas.2110274119] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2021] [Indexed: 11/18/2022] Open
Abstract
A cardinal feature of the neocortex is the progressive increase of the spatial receptive fields along the cortical hierarchy. Recently, theoretical and experimental findings have shown that the temporal response windows also gradually enlarge, so that early sensory neural circuits operate on short timescales whereas higher-association areas are capable of integrating information over a long period of time. While an increased receptive field is accounted for by spatial summation of inputs from neurons in an upstream area, the emergence of timescale hierarchy cannot be readily explained, especially given the dense interareal cortical connectivity known in the modern connectome. To uncover the required neurobiological properties, we carried out a rigorous analysis of an anatomically based large-scale cortex model of macaque monkeys. Using a perturbation method, we show that the segregation of disparate timescales is defined in terms of the localization of eigenvectors of the connectivity matrix, which depends on three circuit properties: 1) a macroscopic gradient of synaptic excitation, 2) distinct electrophysiological properties between excitatory and inhibitory neuronal populations, and 3) a detailed balance between long-range excitatory inputs and local inhibitory inputs for each area-to-area pathway. Our work thus provides a quantitative understanding of the mechanism underlying the emergence of timescale hierarchy in large-scale primate cortical networks.
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24
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Revisiting horizontal connectivity rules in V1: from like-to-like towards like-to-all. Brain Struct Funct 2022; 227:1279-1295. [PMID: 35122520 DOI: 10.1007/s00429-022-02455-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 01/03/2022] [Indexed: 01/15/2023]
Abstract
Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the similar length scale for the regularity found in cortical orientation maps, the currently accepted theoretical standpoint is that these maps are underpinned by a like-to-like connectivity rule: horizontal axons connect preferentially to neurons with similar preferred orientation. However, there is reason to doubt the rule's explanatory power, since a growing number of quantitative studies show that the like-to-like connectivity preference and bias mostly observed at short-range scale, are highly variable on a neuron-to-neuron level and depend on the origin of the presynaptic neuron. Despite the wide availability of published data, the accepted model of visual processing has never been revised. Here, we review three lines of independent evidence supporting a much-needed revision of the like-to-like connectivity rule, ranging from anatomy to population functional measures, computational models and to theoretical approaches. We advocate an alternative, distance-dependent connectivity rule that is consistent with new structural and functional evidence: from like-to-like bias at short horizontal distance to like-to-all at long horizontal distance. This generic rule accounts for the observed high heterogeneity in interactions between the orientation and retinotopic domains, that we argue is necessary to process non-trivial stimuli in a task-dependent manner.
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25
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Xu R, Bichot NP, Takahashi A, Desimone R. The cortical connectome of primate lateral prefrontal cortex. Neuron 2022; 110:312-327.e7. [PMID: 34739817 PMCID: PMC8776613 DOI: 10.1016/j.neuron.2021.10.018] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/09/2021] [Accepted: 10/11/2021] [Indexed: 01/21/2023]
Abstract
The lateral prefrontal cortex (LPFC) of primates plays an important role in executive control, but how it interacts with the rest of the cortex remains unclear. To address this, we densely mapped the cortical connectome of LPFC, using electrical microstimulation combined with functional MRI (EM-fMRI). We found isomorphic mappings between LPFC and five major processing domains composing most of the cerebral cortex except early sensory and motor areas. An LPFC grid of ∼200 stimulation sites topographically mapped to separate grids of activation sites in the five domains, coarsely resembling how the visual cortex maps the retina. The temporal and parietal maps largely overlapped in LPFC, suggesting topographically organized convergence of the ventral and dorsal streams, and the other maps overlapped at least partially. Thus, the LPFC contains overlapping, millimeter-scale maps that mirror the organization of major cortical processing domains, supporting LPFC's role in coordinating activity within and across these domains.
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Affiliation(s)
- Rui Xu
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Narcisse P Bichot
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Atsushi Takahashi
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert Desimone
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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26
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Thivierge JP, Pilzak A. Estimating null and potent modes of feedforward communication in a computational model of cortical activity. Sci Rep 2022; 12:742. [PMID: 35031628 PMCID: PMC8760251 DOI: 10.1038/s41598-021-04684-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 12/15/2021] [Indexed: 11/08/2022] Open
Abstract
Communication across anatomical areas of the brain is key to both sensory and motor processes. Dimensionality reduction approaches have shown that the covariation of activity across cortical areas follows well-delimited patterns. Some of these patterns fall within the "potent space" of neural interactions and generate downstream responses; other patterns fall within the "null space" and prevent the feedforward propagation of synaptic inputs. Despite growing evidence for the role of null space activity in visual processing as well as preparatory motor control, a mechanistic understanding of its neural origins is lacking. Here, we developed a mean-rate model that allowed for the systematic control of feedforward propagation by potent and null modes of interaction. In this model, altering the number of null modes led to no systematic changes in firing rates, pairwise correlations, or mean synaptic strengths across areas, making it difficult to characterize feedforward communication with common measures of functional connectivity. A novel measure termed the null ratio captured the proportion of null modes relayed from one area to another. Applied to simultaneous recordings of primate cortical areas V1 and V2 during image viewing, the null ratio revealed that feedforward interactions have a broad null space that may reflect properties of visual stimuli.
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Affiliation(s)
- Jean-Philippe Thivierge
- School of Psychology, University of Ottawa, Ottawa, ON, Canada.
- Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, Canada.
| | - Artem Pilzak
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
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27
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Li X, Zhu Q, Vanduffel W. Submillimeter fMRI reveals an extensive, fine-grained and functionally-relevant scene-processing network in monkeys. Prog Neurobiol 2022; 211:102230. [DOI: 10.1016/j.pneurobio.2022.102230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/20/2021] [Accepted: 01/26/2022] [Indexed: 11/27/2022]
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28
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Schneider M, Broggini AC, Dann B, Tzanou A, Uran C, Sheshadri S, Scherberger H, Vinck M. A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power. Neuron 2021; 109:4050-4067.e12. [PMID: 34637706 PMCID: PMC8691951 DOI: 10.1016/j.neuron.2021.09.037] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 07/14/2021] [Accepted: 09/17/2021] [Indexed: 11/21/2022]
Abstract
Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.
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Affiliation(s)
- Marius Schneider
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | | | - Athanasia Tzanou
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Swathi Sheshadri
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Hansjörg Scherberger
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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29
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He Z, Du L, Huang Y, Jiang X, Lv J, Guo L, Zhang S, Zhang T. Gyral Hinges Account for the Highest Cost and the Highest Communication Capacity in a Corticocortical Network. Cereb Cortex 2021; 32:3359-3376. [PMID: 34875041 DOI: 10.1093/cercor/bhab420] [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: 06/18/2021] [Revised: 10/22/2021] [Accepted: 10/23/2021] [Indexed: 12/11/2022] Open
Abstract
Prior studies reported the global structure of brain networks exhibits the "small-world" and "rich-world" attributes. However, the underlying structural and functional architecture highlighted by these graph theory findings hasn't been explicitly related to the morphology of the cortex. This could be attributed to the lower resolution of used folding patterns, such as gyro-sulcal patterns. By defining a novel gyral folding pattern, termed gyral hinge (GH), which is the conjunction of ordinary gyri from multiple directions, we found GHs possess the highest length and cost in the white matter fiber connective network, and the shortest paths in the network tend to travel through GHs in their middle part. Based on these findings, we would hypothesize GHs could reside in the centers of a network core, thereby accounting for the highest cost and the highest communication capacity in a corticocortical network. The following results further support our hypothesis: 1) GHs possess stronger functional network integration capacity. 2) Higher cost is found on the connection with GHs to hinges and GHs to GHs. 3) Moving GHs introduces higher extra network cost. Our findings and hypotheses could reveal a profound relationship among the cortical folding patterns, axonal wiring architectures, and brain functions.
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Affiliation(s)
- Zhibin He
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lei Du
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Ying Huang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jinglei Lv
- School of Biomedical Engineering, Sydney Imaging, Brain and Mind Centre, The University of Sydney, Camperdown, NSW 2050, Australia
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shu Zhang
- School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
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30
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Vezoli J, Vinck M, Bosman CA, Bastos AM, Lewis CM, Kennedy H, Fries P. Brain rhythms define distinct interaction networks with differential dependence on anatomy. Neuron 2021; 109:3862-3878.e5. [PMID: 34672985 PMCID: PMC8639786 DOI: 10.1016/j.neuron.2021.09.052] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 08/10/2021] [Accepted: 09/24/2021] [Indexed: 11/08/2022]
Abstract
Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent. Thus, the rhythms defined distinct interaction networks. Importantly, networks of coherence and GC were not explained by the spatial distributions of the strengths of the rhythms. Those networks, particularly the GC networks, contained clear modules, with typically one dominant rhythm per module. To understand how this distinctiveness and modularity arises on a common anatomical backbone, we correlated, across 91 area pairs, the metrics of functional interaction with those of anatomical projection strength. Anatomy was primarily related to coherence and GC, with the largest effect sizes for GC. The correlation differed markedly between rhythms, being less pronounced for the beta and strongest for the gamma rhythm.
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Affiliation(s)
- Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with the Max Planck Society, 60528 Frankfurt, Germany.
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with the Max Planck Society, 60528 Frankfurt, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University, 6525 AJ Nijmegen, the Netherlands
| | - Conrado Arturo Bosman
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, 6525 EN Nijmegen, the Netherlands; Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - André Moraes Bastos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with the Max Planck Society, 60528 Frankfurt, Germany; Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37240, USA
| | - Christopher Murphy Lewis
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with the Max Planck Society, 60528 Frankfurt, Germany; Brain Research Institute, University of Zurich, Zurich 8057, Switzerland
| | - Henry Kennedy
- Université Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, Shanghai 200031, China
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with the Max Planck Society, 60528 Frankfurt, Germany; Donders Institute for Brain, Cognition, and Behaviour, Radboud University, 6525 EN Nijmegen, the Netherlands.
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31
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Franken TP, Reynolds JH. Columnar processing of border ownership in primate visual cortex. eLife 2021; 10:72573. [PMID: 34845986 PMCID: PMC8631947 DOI: 10.7554/elife.72573] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 10/28/2021] [Indexed: 11/26/2022] Open
Abstract
To understand a visual scene, the brain segregates figures from background by assigning borders to foreground objects. Neurons in primate visual cortex encode which object owns a border (border ownership), but the underlying circuitry is not understood. Here, we used multielectrode probes to record from border ownership-selective units in different layers in macaque visual area V4 to study the laminar organization and timing of border ownership selectivity. We find that border ownership selectivity occurs first in deep layer units, in contrast to spike latency for small stimuli in the classical receptive field. Units on the same penetration typically share the preferred side of border ownership, also across layers, similar to orientation preference. Units are often border ownership-selective for a range of border orientations, where the preferred sides of border ownership are systematically organized in visual space. Together our data reveal a columnar organization of border ownership in V4 where the earliest border ownership signals are not simply inherited from upstream areas, but computed by neurons in deep layers, and may thus be part of signals fed back to upstream cortical areas or the oculomotor system early after stimulus onset. The finding that preferred border ownership is clustered and can cover a wide range of spatially contiguous locations suggests that the asymmetric context integrated by these neurons is provided in a systematically clustered manner, possibly through corticocortical feedback and horizontal connections. To understand a visual scene, the brain needs to identify objects and distinguish them from background. A border marks the transition from object to background, but to differentiate which side of the border belongs to the object and which to background, the brain must integrate information across space. An early signature of this computation is that brain cells signal which side of a border is ‘owned’ by an object, also known as border ownership. But how the brain computes border ownership remains unknown. The optic nerve is a cable-like group of nerve cells that transmits information from the eye to the brain’s visual processing areas and into the visual cortex. This flow of information is often described as traveling in a feedforward direction, away from the eyes to progressively more specialized areas in the visual cortex. However, there are also numerous feedback connections in the brain, running backward from more specialized to less specialized cortical areas. To better understand the role of these feedforward and feedback circuits in the visual processing of object borders, Franken and Reynolds made use of their stereotyped projection patterns across the cortex layers. Feedforward connections terminate in the middle layers of a cortical area, whereas feedback connections terminate in upper and lower layers. Since time is required for information to traverse the cortical layers, dissecting the timing of border ownership signals may reveal if border ownership is computed in a feedforward or feedback manner. To find out more, electrodes were used to record neural activity in the upper, middle and lower layers of the visual cortex of two rhesus monkeys as they were presented with a set of abstract scenes composed of simple shapes on a background. This revealed that cells signaling border ownership in deep layers of the cortex did so before the signals appeared in the middle layer. This suggests that feedback rather than feedforward is required to compute border ownership. Moreover, Franken and Reynolds found evidence that cells that prefer the same side of border ownership are clustered in columns, showing how these neural circuits are organized within the visual cortex. In summary, Franken and Reynolds found that the circuits of the primate brain that compute border ownership occur as columns, in which cells in deep layers signal border ownership first, suggesting that border ownership relies on feedback from more specialized areas. A better understanding of how feedback in the brain works to process visual information helps us appreciate what happens when these systems are impaired.
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Affiliation(s)
- Tom P Franken
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States
| | - John H Reynolds
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States
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32
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Ahmadian Y, Miller KD. What is the dynamical regime of cerebral cortex? Neuron 2021; 109:3373-3391. [PMID: 34464597 PMCID: PMC9129095 DOI: 10.1016/j.neuron.2021.07.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 01/13/2023]
Abstract
Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron's excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size with the factors that cancel, rather than tight, meaning that the net input is very small relative to the canceling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas.
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Affiliation(s)
- Yashar Ahmadian
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, and Department of Neuroscience, College of Physicians and Surgeons and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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33
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Yakushev I, Ripp I, Wang M, Savio A, Schutte M, Lizarraga A, Bogdanovic B, Diehl-Schmid J, Hedderich DM, Grimmer T, Shi K. Mapping covariance in brain FDG uptake to structural connectivity. Eur J Nucl Med Mol Imaging 2021; 49:1288-1297. [PMID: 34677627 PMCID: PMC8921091 DOI: 10.1007/s00259-021-05590-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 10/11/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE Inter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDGcov) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDGcov is underlied by actual structural connectivity via white matter fiber tracts. In this study, we quantified the degree of spatial overlap between FDGcov and structural connectivity networks. METHODS We retrospectively analyzed neuroimaging data from 303 subjects, both patients with suspected neurodegenerative disorders and healthy individuals. For each subject, structural magnetic resonance, diffusion tensor imaging, and FDG-PET data were available. The images were spatially normalized to a standard space and segmented into 62 anatomical regions using a probabilistic atlas. Sparse inverse covariance estimation was employed to estimate FDGcov. Structural connectivity was measured by streamline tractography through fiber assignment by continuous tracking. RESULTS For the whole brain, 55% of detected connections were found to be convergent, i.e., present in both FDGcov and structural networks. This metric for random networks was significantly lower, i.e., 12%. Convergent were 80% of intralobe connections and only 30% of interhemispheric interlobe connections. CONCLUSION Structural connectivity via white matter fiber tracts is a relevant substrate of FDGcov, underlying around a half of connections at the whole brain level. Short-range white matter tracts appear to be a major substrate of intralobe FDGcov connections.
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Affiliation(s)
- Igor Yakushev
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany.
- Klinikum rechts der Isar, School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Munich, Germany.
| | - Isabelle Ripp
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
- Klinikum rechts der Isar, School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Munich, Germany
| | - Min Wang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai, China
| | - Alex Savio
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
| | - Michael Schutte
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
- Department Biology II, Ludwig Maximilian University of Munich, Munich, Germany
| | - Aldana Lizarraga
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
- Klinikum rechts der Isar, School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Munich, Germany
| | - Borjana Bogdanovic
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dennis M Hedderich
- Department of Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Kuangyu Shi
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany
- Department of Nuclear Medicine, University Hospital Bern, Bern, Switzerland
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34
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Davis ZW, Benigno GB, Fletterman C, Desbordes T, Steward C, Sejnowski TJ, H Reynolds J, Muller L. Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states. Nat Commun 2021; 12:6057. [PMID: 34663796 PMCID: PMC8523565 DOI: 10.1038/s41467-021-26175-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 09/17/2021] [Indexed: 11/25/2022] Open
Abstract
Studies of sensory-evoked neuronal responses often focus on mean spike rates, with fluctuations treated as internally-generated noise. However, fluctuations of spontaneous activity, often organized as traveling waves, shape stimulus-evoked responses and perceptual sensitivity. The mechanisms underlying these waves are unknown. Further, it is unclear whether waves are consistent with the low rate and weakly correlated “asynchronous-irregular” dynamics observed in cortical recordings. Here, we describe a large-scale computational model with topographically-organized connectivity and conduction delays relevant to biological scales. We find that spontaneous traveling waves are a general property of these networks. The traveling waves that occur in the model are sparse, with only a small fraction of neurons participating in any individual wave. Consequently, they do not induce measurable spike correlations and remain consistent with locally asynchronous irregular states. Further, by modulating local network state, they can shape responses to incoming inputs as observed in vivo. Spontaneous traveling cortical waves shape neural responses. Using a large-scale computational model, the authors show that transmission delays shape locally asynchronous spiking dynamics into traveling waves without inducing correlations and boost responses to external input, as observed in vivo.
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Affiliation(s)
- Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Gabriel B Benigno
- Department of Applied Mathematics, Western University, London, ON, Canada.,Brain and Mind Institute, Western University, London, ON, Canada
| | | | - Theo Desbordes
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - John H Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Lyle Muller
- Department of Applied Mathematics, Western University, London, ON, Canada. .,Brain and Mind Institute, Western University, London, ON, Canada.
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35
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Zhang C, Cai H, Xu X, Li Q, Li X, Zhao W, Qian Y, Zhu J, Yu Y. Genetic Architecture Underlying Differential Resting-state Functional Connectivity of Subregions Within the Human Visual Cortex. Cereb Cortex 2021; 32:2063-2078. [PMID: 34607357 DOI: 10.1093/cercor/bhab335] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/17/2021] [Accepted: 08/22/2021] [Indexed: 11/12/2022] Open
Abstract
The human visual cortex is a heterogeneous entity that has multiple subregions showing substantial variability in their functions and connections. We aimed to identify genes associated with resting-state functional connectivity (rsFC) of visual subregions using transcriptome-neuroimaging spatial correlations in discovery and validation datasets. Results showed that rsFC of eight visual subregions were associated with expression measures of eight gene sets, which were specifically expressed in brain tissue and showed the strongest correlations with visual behavioral processes. Moreover, there was a significant divergence in these gene sets and their functional features between medial and lateral visual subregions. Relative to those associated with lateral subregions, more genes associated with medial subregions were found to be enriched for neuropsychiatric diseases and more diverse biological functions and pathways, and to be specifically expressed in multiple types of neurons and immune cells and during the middle and late stages of cortical development. In addition to shared behavioral processes, lateral subregion associated genes were uniquely correlated with high-order cognition. These findings of commonalities and differences in the identified rsFC-related genes and their functional features across visual subregions may improve our understanding of the functional heterogeneity of the visual cortex from the perspective of underlying genetic architecture.
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Affiliation(s)
- Cun Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Xiaotao Xu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Qian Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Xueying Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
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36
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Zendrikov D, Paraskevov A. Emergent population activity in metric-free and metric networks of neurons with stochastic spontaneous spikes and dynamic synapses. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2020.11.073] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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37
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Siu C, Balsor J, Merlin S, Federer F, Angelucci A. A direct interareal feedback-to-feedforward circuit in primate visual cortex. Nat Commun 2021; 12:4911. [PMID: 34389710 PMCID: PMC8363744 DOI: 10.1038/s41467-021-24928-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 07/08/2021] [Indexed: 11/15/2022] Open
Abstract
The mammalian sensory neocortex consists of hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits. Several theories of hierarchical computation ascribe the bulk of the computational work of the cortex to looped FF-FB circuits between pairs of cortical areas. However, whether such corticocortical loops exist remains unclear. In higher mammals, individual FF-projection neurons send afferents almost exclusively to a single higher-level area. However, it is unclear whether FB-projection neurons show similar area-specificity, and whether they influence FF-projection neurons directly or indirectly. Using viral-mediated monosynaptic circuit tracing in macaque primary visual cortex (V1), we show that V1 neurons sending FF projections to area V2 receive monosynaptic FB inputs from V2, but not other V1-projecting areas. We also find monosynaptic FB-to-FB neuron contacts as a second motif of FB connectivity. Our results support the existence of FF-FB loops in primate cortex, and suggest that FB can rapidly and selectively influence the activity of incoming FF signals.
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Affiliation(s)
- Caitlin Siu
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Justin Balsor
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Sam Merlin
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
- Medical Science, School of Science, Western Sydney University, Campbelltown, NSW, Australia
| | - Frederick Federer
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA
| | - Alessandra Angelucci
- Department of Ophthalmology and Visual Science, Moran Eye Institute, University of Utah, Salt Lake City, UT, USA.
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38
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Theodoni P, Majka P, Reser DH, Wójcik DK, Rosa MGP, Wang XJ. Structural Attributes and Principles of the Neocortical Connectome in the Marmoset Monkey. Cereb Cortex 2021; 32:15-28. [PMID: 34274966 PMCID: PMC8634603 DOI: 10.1093/cercor/bhab191] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 05/23/2021] [Accepted: 06/01/2021] [Indexed: 12/12/2022] Open
Abstract
The marmoset monkey has become an important primate model in Neuroscience. Here, we characterize salient statistical properties of interareal connections of the marmoset cerebral cortex, using data from retrograde tracer injections. We found that the connectivity weights are highly heterogeneous, spanning 5 orders of magnitude, and are log-normally distributed. The cortico-cortical network is dense, heterogeneous and has high specificity. The reciprocal connections are the most prominent and the probability of connection between 2 areas decays with their functional dissimilarity. The laminar dependence of connections defines a hierarchical network correlated with microstructural properties of each area. The marmoset connectome reveals parallel streams associated with different sensory systems. Finally, the connectome is spatially embedded with a characteristic length that obeys a power law as a function of brain volume across rodent and primate species. These findings provide a connectomic basis for investigations of multiple interacting areas in a complex large-scale cortical system underlying cognitive processes.
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Affiliation(s)
- Panagiota Theodoni
- Center for Neural Science, New York University, New York, NY 10003, USA.,New York University Shanghai, Shanghai 200122, China.,NYU-ECNU Institute of Brain and Cognitive Science at New York University Shanghai, Shanghai 200062, China
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw 02-093, Poland.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - David H Reser
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Graduate Entry Medicine Program, Monash Rural Health-Churchill, Monash University, Churchill, VIC 3842, Australia
| | - Daniel K Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw 02-093, Poland
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY 10003, USA
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Ribeiro Gomes AR, Olivier E, Killackey HP, Giroud P, Berland M, Knoblauch K, Dehay C, Kennedy H. Refinement of the Primate Corticospinal Pathway During Prenatal Development. Cereb Cortex 2021; 30:656-671. [PMID: 31343065 DOI: 10.1093/cercor/bhz116] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 05/08/2019] [Accepted: 05/08/2019] [Indexed: 11/14/2022] Open
Abstract
Perturbation of the developmental refinement of the corticospinal (CS) pathway leads to motor disorders. While non-primate developmental refinement is well documented, in primates invasive investigations of the developing CS pathway have been confined to neonatal and postnatal stages when refinement is relatively modest. Here, we investigated the developmental changes in the distribution of CS projection neurons in cynomolgus monkey (Macaca fascicularis). Injections of retrograde tracer at cervical levels of the spinal cord at embryonic day (E) 95 and E105 show that: (i) areal distribution of back-labeled neurons is more extensive than in the neonate and dense labeling is found in prefrontal, limbic, temporal, and occipital cortex; (ii) distributions of contralateral and ipsilateral projecting CS neurons are comparable in terms of location and numbers of labeled neurons, in contrast to the adult where the contralateral projection is an order of magnitude higher than the ipsilateral projection. Findings from one largely restricted injection suggest a hitherto unsuspected early innervation of the gray matter. In the fetus there was in addition dense labeling in the central nucleus of the amygdala, the hypothalamus, the subthalamic nucleus, and the adjacent region of the zona incerta, subcortical structures with only minor projections in the adult control.
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Affiliation(s)
- Ana Rita Ribeiro Gomes
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France
| | - Etienne Olivier
- Institute of Neuroscience, Université Catholique de Louvain, Belgium
| | - Herbert P Killackey
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Pascale Giroud
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France
| | - Michel Berland
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France
| | - Kenneth Knoblauch
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France
| | - Colette Dehay
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France
| | - Henry Kennedy
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute, Bron, France.,Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai, China
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40
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Gong H, Yuan N, Shen Z, Tang C, Shipp S, Qian L, Lu Y, Andolina IM, Zhang S, Wu J, Yang H, Wang W. Transduction catalysis: Doxorubicin amplifies rAAV-mediated gene expression in the cortex of higher-order vertebrates. iScience 2021; 24:102685. [PMID: 34195565 PMCID: PMC8233199 DOI: 10.1016/j.isci.2021.102685] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/24/2021] [Accepted: 06/01/2021] [Indexed: 12/26/2022] Open
Abstract
Rapid and efficient gene transduction via recombinant adeno-associated viruses (rAAVs) is highly desirable across many basic and clinical research domains. Here, we report that vector co-infusion with doxorubicin, a clinical anti-cancer drug, markedly enhanced rAAV-mediated transgene expression in the cerebral cortex across mammalian species (cat, mouse, and macaque), acting throughout the time period examined and detectable at just three days after transfection. This enhancement showed serotype generality, being common to all rAAV serotypes tested (2, 8, 9, and PHP.eB) and was observed both locally and at remote locations consistent with doxorubicin undergoing retrograde axonal transport. All these effects were observed at doses matching human blood plasma levels in clinical therapy and lacked detectable cytotoxicity as assessed by cell morphology, activity, apoptosis, and behavioral testing. Altogether, this study identifies an effective means to improve the capability and scope of in vivo rAAV applications, amplifying cell transduction at doxorubicin concentrations paralleling medical practice.
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Affiliation(s)
- Hongliang Gong
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nini Yuan
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhiming Shen
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Cheng Tang
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Stewart Shipp
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Liling Qian
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yiliang Lu
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ian Max Andolina
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shenghai Zhang
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai 200031, China
| | - Jihong Wu
- Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai 200031, China
| | - Hui Yang
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,Shanghai Center for Brain and Brain-Inspired Intelligence Technology, Shanghai 200031, China
| | - Wei Wang
- Institute of Neuroscience, the Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,Shanghai Center for Brain and Brain-Inspired Intelligence Technology, Shanghai 200031, China
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41
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Yeh CH, Jones DK, Liang X, Descoteaux M, Connelly A. Mapping Structural Connectivity Using Diffusion MRI: Challenges and Opportunities. J Magn Reson Imaging 2021; 53:1666-1682. [PMID: 32557893 PMCID: PMC7615246 DOI: 10.1002/jmri.27188] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 04/21/2020] [Accepted: 04/21/2020] [Indexed: 12/13/2022] Open
Abstract
Diffusion MRI-based tractography is the most commonly-used technique when inferring the structural brain connectome, i.e., the comprehensive map of the connections in the brain. The utility of graph theory-a powerful mathematical approach for modeling complex network systems-for analyzing tractography-based connectomes brings important opportunities to interrogate connectome data, providing novel insights into the connectivity patterns and topological characteristics of brain structural networks. When applying this framework, however, there are challenges, particularly regarding methodological and biological plausibility. This article describes the challenges surrounding quantitative tractography and potential solutions. In addition, challenges related to the calculation of global network metrics based on graph theory are discussed.Evidence Level: 5Technical Efficacy: Stage 1.
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Affiliation(s)
- Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Child and Adolescent Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Xiaoyun Liang
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Alan Connelly
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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42
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Byrne Á, Ross J, Nicks R, Coombes S. Mean-Field Models for EEG/MEG: From Oscillations to Waves. Brain Topogr 2021; 35:36-53. [PMID: 33993357 PMCID: PMC8813727 DOI: 10.1007/s10548-021-00842-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 04/21/2021] [Indexed: 11/24/2022]
Abstract
Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.
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Affiliation(s)
- Áine Byrne
- School of Mathematics and Statistics, Science Centre, University College Dublin, South Belfield, Dublin 4, Ireland.
| | - James Ross
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Rachel Nicks
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Stephen Coombes
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
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43
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Is the primary visual cortex necessary for blindsight-like behavior? Review of transcranial magnetic stimulation studies in neurologically healthy individuals. Neurosci Biobehav Rev 2021; 127:353-364. [PMID: 33965459 DOI: 10.1016/j.neubiorev.2021.04.038] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 04/28/2021] [Accepted: 04/29/2021] [Indexed: 12/20/2022]
Abstract
The visual pathways that bypass the primary visual cortex (V1) are often assumed to support visually guided behavior in humans in the absence of conscious vision. This conclusion is largely based on findings on patients: V1 lesions cause blindness but sometimes leave some visually guided behaviors intact-this is known as blindsight. With the aim of examining how well the findings on blindsight patients generalize to neurologically healthy individuals, we review studies which have tried to uncover transcranial magnetic stimulation (TMS) induced blindsight. In general, these studies have failed to demonstrate a completely unconscious blindsight-like capacity in neurologically healthy individuals. A possible exception to this is TMS-induced blindsight of stimulus presence or location. Because blindsight in patients is often associated with some form of introspective access to the visual stimulus, and blindsight may be associated with neural reorganization, we suggest that rather than revealing a dissociation between visually guided behavior and conscious seeing, blindsight may reflect preservation or partial recovery of conscious visual perception after the lesion.
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44
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Hayashi T, Hou Y, Glasser MF, Autio JA, Knoblauch K, Inoue-Murayama M, Coalson T, Yacoub E, Smith S, Kennedy H, Van Essen DC. The nonhuman primate neuroimaging and neuroanatomy project. Neuroimage 2021; 229:117726. [PMID: 33484849 PMCID: PMC8079967 DOI: 10.1016/j.neuroimage.2021.117726] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/13/2020] [Accepted: 01/02/2021] [Indexed: 11/29/2022] Open
Abstract
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
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Affiliation(s)
- Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan; Department of Neurobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yujie Hou
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Neuroscience and Radiology, Washington University Medical School, St Louis, MO USA
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Kenneth Knoblauch
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | | | - Tim Coalson
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA
| | - Stephen Smith
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henry Kennedy
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai, China
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
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45
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Frey BM, Petersen M, Schlemm E, Mayer C, Hanning U, Engelke K, Fiehler J, Borof K, Jagodzinski A, Gerloff C, Thomalla G, Cheng B. White matter integrity and structural brain network topology in cerebral small vessel disease: The Hamburg city health study. Hum Brain Mapp 2021; 42:1406-1415. [PMID: 33289924 PMCID: PMC7927298 DOI: 10.1002/hbm.25301] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 11/08/2020] [Accepted: 11/16/2020] [Indexed: 12/13/2022] Open
Abstract
Cerebral small vessel disease is a common finding in the elderly and associated with various clinical sequelae. Previous studies suggest disturbances in the integration capabilities of structural brain networks as a mediating link between imaging and clinical presentations. To what extent cerebral small vessel disease might interfere with other measures of global network topology is not well understood. Connectomes were reconstructed via diffusion weighted imaging in a sample of 930 participants from a population based epidemiologic study. Linear models were fitted testing for an association of graph-theoretical measures reflecting integration and segregation with both the Peak width of Skeletonized Mean Diffusivity (PSMD) and the load of white matter hyperintensities of presumed vascular origin (WMH). The latter were subdivided in periventricular and deep for an analysis of localisation-dependent correlations of cerebral small vessel disease. The median WMH volume was 0.6 mL (1.4) and the median PSMD 2.18 mm2 /s x 10-4 (0.5). The connectomes showed a median density of 0.880 (0.030), the median values for normalised global efficiency, normalised clustering coefficient, modularity Q and small-world propensity were 0.780 (0.045), 1.182 (0.034), 0.593 (0.026) and 0.876 (0.040) respectively. An increasing burden of cerebral small vessel disease was significantly associated with a decreased integration and increased segregation and thus decreased small-worldness of structural brain networks. Even in rather healthy subjects increased cerebral small vessel disease burden is accompanied by topological brain network disturbances. Segregation parameters and small-worldness might as well contribute to the understanding of the known clinical sequelae of cerebral small vessel disease.
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Affiliation(s)
- Benedikt M. Frey
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Marvin Petersen
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Eckhard Schlemm
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Carola Mayer
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Uta Hanning
- Department of Diagnostic and Interventional NeuroradiologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Kristin Engelke
- Department of Diagnostic and Interventional NeuroradiologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Jens Fiehler
- Department of Diagnostic and Interventional NeuroradiologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Katrin Borof
- Epidemiological study centerUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Annika Jagodzinski
- Epidemiological study centerUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of General and Interventional CardiologyUniversity Heart and Vascular CenterHamburgGermany
| | - Christian Gerloff
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Götz Thomalla
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Bastian Cheng
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
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46
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Chavane F, Contreras D. Like a clock in the rabbit's visual cortex. eLife 2021; 10:65581. [PMID: 33538694 PMCID: PMC7861611 DOI: 10.7554/elife.65581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 01/28/2021] [Indexed: 11/23/2022] Open
Abstract
Three rules govern the connectivity between neurons in the thalamus and inhibitory neurons in the visual cortex of rabbits.
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Affiliation(s)
- Frédéric Chavane
- Institut de Neurosciences de la Timone, UMR 7289, CNRS and the Faculté de Médecine, Aix-Marseille Université, Marseille, France.,Faculté de Médecine, Aix-Marseille Université, Marseille, France
| | - Diego Contreras
- Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, United States
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47
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Vezoli J, Magrou L, Goebel R, Wang XJ, Knoblauch K, Vinck M, Kennedy H. Cortical hierarchy, dual counterstream architecture and the importance of top-down generative networks. Neuroimage 2021; 225:117479. [PMID: 33099005 PMCID: PMC8244994 DOI: 10.1016/j.neuroimage.2020.117479] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 09/29/2020] [Accepted: 10/15/2020] [Indexed: 12/18/2022] Open
Abstract
Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from multiple hierarchical levels to their target areas show remarkable consistency, allowing the construction of a cortical hierarchy based on a principle of hierarchical distance. The statistical modeling that is applied to structure can also be applied to laminar differences in the oscillatory coherence between areas thereby determining a functional hierarchy of the cortex. Close examination of the anatomy of inter-areal connectivity reveals a dual counterstream architecture with well-defined distance-dependent feedback and feedforward pathways in both the supra- and infragranular layers, suggesting a multiplicity of feedback pathways with well-defined functional properties. These findings are consistent with feedback connections providing a generative network involved in a wide range of cognitive functions. A dynamical model constrained by connectivity data sheds insight into the experimentally observed signatures of frequency-dependent Granger causality for feedforward versus feedback signaling. Concerted experiments capitalizing on recent technical advances and combining tract-tracing, high-resolution fMRI, optogenetics and mathematical modeling hold the promise of a much improved understanding of lamina-constrained mechanisms of neural computation and cognition. However, because inter-areal interactions involve cortical layers that have been the target of important evolutionary changes in the primate lineage, these investigations will need to include human and non-human primate comparisons.
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Affiliation(s)
- Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Loïc Magrou
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, the Netherlands
| | - Xiao-Jing Wang
- Center for Neural Science, New York University (NYU), New York, NY 10003, USA
| | - Kenneth Knoblauch
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany.
| | - Henry Kennedy
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai 200031, China.
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48
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Developmental outcomes of early adverse care on amygdala functional connectivity in nonhuman primates. Dev Psychopathol 2021; 32:1579-1596. [PMID: 33427167 DOI: 10.1017/s0954579420001133] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Despite the strong link between childhood maltreatment and psychopathology, the underlying neurodevelopmental mechanisms are poorly understood and difficult to disentangle from heritable and prenatal factors. This study used a translational macaque model of infant maltreatment in which the adverse experience occurs in the first months of life, during intense maturation of amygdala circuits important for stress and emotional regulation. Thus, we examined the developmental impact of maltreatment on amygdala functional connectivity (FC) longitudinally, from infancy through the juvenile period. Using resting state functional magnetic resonance imaging (MRI) we performed amygdala-prefrontal cortex (PFC) region-of-interest and exploratory whole-brain amygdala FC analyses. The latter showed (a) developmental increases in amygdala FC with many regions, likely supporting increased processing of socioemotional-relevant stimuli with age; and (b) maltreatment effects on amygdala coupling with arousal and stress brain regions (locus coeruleus, laterodorsal tegmental area) that emerged with age. Maltreated juveniles showed weaker FC than controls, which was negatively associated with infant hair cortisol concentrations. Findings from the region-of-interest analysis also showed weaker amygdala FC with PFC regions in maltreated animals than controls since infancy, whereas bilateral amygdala FC was stronger in maltreated animals. These effects on amygdala FC development may underlie the poor behavioral outcomes associated with this adverse experience.
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De Castro V, Smith AT, Beer AL, Leguen C, Vayssière N, Héjja-Brichard Y, Audurier P, Cottereau BR, Durand JB. Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys. Cereb Cortex 2021; 31:1347-1364. [PMID: 33067998 PMCID: PMC7786354 DOI: 10.1093/cercor/bhaa301] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 08/12/2020] [Accepted: 09/11/2020] [Indexed: 12/27/2022] Open
Abstract
In humans, the posterior cingulate cortex contains an area sensitive to visual cues to self-motion. This cingulate sulcus visual area (CSv) is structurally and functionally connected with several (multi)sensory and (pre)motor areas recruited during locomotion. In nonhuman primates, electrophysiology has shown that the cingulate cortex is also related to spatial navigation. Recently, functional MRI in macaque monkeys identified a cingulate area with similar visual properties to human CSv. In order to bridge the gap between human and nonhuman primate research, we examined the structural and functional connectivity of putative CSv in three macaque monkeys adopting the same approach as in humans based on diffusion MRI and resting-state functional MRI. The results showed that putative monkey CSv connects with several visuo-vestibular areas (e.g., VIP/FEFsem/VPS/MSTd) as well as somatosensory cortex (e.g., dorsal aspects of areas 3/1/2), all known to process sensory signals that can be triggered by self-motion. Additionally, strong connections are observed with (pre)motor areas located in the dorsal prefrontal cortex (e.g., F3/F2/F1) and within the anterior cingulate cortex (e.g., area 24). This connectivity pattern is strikingly reminiscent of that described for human CSv, suggesting that the sensorimotor control of locomotion relies on similar organizational principles in human and nonhuman primates.
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Affiliation(s)
- V De Castro
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - A T Smith
- Department of Psychology, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - A L Beer
- Institut für Psychologie, Universität Regensburg, 93053 Regensburg, Germany
| | - C Leguen
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - N Vayssière
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - Y Héjja-Brichard
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - P Audurier
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - B R Cottereau
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
| | - J B Durand
- Université de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientifique, Toulouse Cedex, France
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Boutin V, Franciosini A, Chavane F, Ruffier F, Perrinet L. Sparse deep predictive coding captures contour integration capabilities of the early visual system. PLoS Comput Biol 2021; 17:e1008629. [PMID: 33497381 PMCID: PMC7864399 DOI: 10.1371/journal.pcbi.1008629] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 02/05/2021] [Accepted: 12/12/2020] [Indexed: 11/20/2022] Open
Abstract
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to process context-dependent information in the early visual cortex. While numerous models have accounted for feedback effects at either neural or representational level, none of them were able to bind those two levels of analysis. Is it possible to describe feedback effects at both levels using the same model? We answer this question by combining Predictive Coding (PC) and Sparse Coding (SC) into a hierarchical and convolutional framework applied to realistic problems. In the Sparse Deep Predictive Coding (SDPC) model, the SC component models the internal recurrent processing within each layer, and the PC component describes the interactions between layers using feedforward and feedback connections. Here, we train a 2-layered SDPC on two different databases of images, and we interpret it as a model of the early visual system (V1 & V2). We first demonstrate that once the training has converged, SDPC exhibits oriented and localized receptive fields in V1 and more complex features in V2. Second, we analyze the effects of feedback on the neural organization beyond the classical receptive field of V1 neurons using interaction maps. These maps are similar to association fields and reflect the Gestalt principle of good continuation. We demonstrate that feedback signals reorganize interaction maps and modulate neural activity to promote contour integration. Third, we demonstrate at the representational level that the SDPC feedback connections are able to overcome noise in input images. Therefore, the SDPC captures the association field principle at the neural level which results in a better reconstruction of blurred images at the representational level.
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Affiliation(s)
- Victor Boutin
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
- Aix Marseille Univ, CNRS, ISM, Marseille, France
| | | | - Frederic Chavane
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
| | | | - Laurent Perrinet
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
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