This title appears in the Scientific Report :
2019
Please use the identifier:
http://hdl.handle.net/2128/23035 in citations.
Towards a neuronal network model of macaque visuomotor cortices
Towards a neuronal network model of macaque visuomotor cortices
Introduction. Visuomotor interactions in the cortex of higher mammals remain poorly understood. Toexplore the relationship of visuomotor dynamics to the underlying network structure we are developinga layer-resolved multi-area model of all vision- and motor-related cortical areas of macaque. The mod...
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Personal Name(s): | Morales-Gregorio, Aitor (Corresponding author) |
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Dabrowska, Paulina / van Meegen, Alexander / Pronold, Jari / Bakker, Rembrandt / Senk, Johanna / Diesmann, Markus / Grün, Sonja / van Albada, Sacha | |
Contributing Institute: |
Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Imprint: |
2019
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Conference: | INM-ICS Retreat, Julich (Germany), 2019-06-25 - 2019-06-26 |
Document Type: |
Poster |
Research Program: |
Human Brain Project Specific Grant Agreement 2 GRK 2416: MultiSenses-MultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration Heterogenität von Zytoarchitektur, Chemoarchitektur und Konnektivität in einem großskaligen Computermodell der menschlichen Großhirnrinde Theory, modelling and simulation Connectivity and Activity |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Introduction. Visuomotor interactions in the cortex of higher mammals remain poorly understood. Toexplore the relationship of visuomotor dynamics to the underlying network structure we are developinga layer-resolved multi-area model of all vision- and motor-related cortical areas of macaque. The modelextends an existing visual multi-area model [1,2], which represents each cortical area by a full-densitymodel of a cortical microcircuit [3].Motor cortex microcircuit. Motor areas differ crucially from visual cortex: they have a less prominentlayer 4, a far lower neuron density and different internal connectivity. Therefore, we are working on the pa-rameterization of a new motor microcircuit. The new microcircuit will incorporate the available experimentaldata for layer-resolved neuron density, internal connectivity and subcortical connectivity. Since not all pa-rameters have been measured for the macaque motor cortex, we rely on data from other species (mouse,rat, cat) and other cortical areas (somatosensory, parietal), especially for the inter-layer connectivity. Toovercome the limitations of the structural measurements, we will use a genetic algorithm to optimize themodel parameters within biological ranges. The optimization algorithm will maximize the similarity betweenthe simulated activity and layer-resolved resting-state electrophysiological recordings from macaque motorcortex, under a validation framework [4]. The validation procedure will enable the assessment of the modelsensitivity and help determine which parameter families lead to similar dynamics.Full-scale multi-area model. Microcircuits optimized to represent the different motor areas will be in-tegrated into the visual multi-area model to obtain an extended visuomotor model. We will use axonaltract-tracing data to describe the long-range cortico-cortical connectivity, characterized by the connectionprobability and source/target laminar patterns between any two cortical areas. For the missing data, wewill complement the experimental measurements with statistical predictions based on intrinsic relationshipsbetween the cortical structure (such as white matter distance, log ratio of neuron density and layer thick-ness) and the connectivity, for all known existing connections from the CoCoMac database [5]. Additionally,topological predictive methods will be used, when the existence of connections is unknown. The resultingmodel will be tested against electrophysiological recordings from visual, parietal and motor areas from avisuomotor experiment with macaques [6].References:[1] M. Schmidt, R. Bakker, C. C. Hilgetag, M. Diesmann, and S. J. van Albada. Multi-scale account of the network structure ofmacaque visual cortex. Brain Structure and Function, Apr. 2018.[2] M. Schmidt, R. Bakker, K. Shen, G. Bezgin, M. Diesmann, and S. J. van Albada. A multi-scale layer-resolved spikingnetwork model of resting-state dynamics in macaque visual cortical areas. PLOS Computational Biology, 14(10):e1006359,oct 2018.[3] T. C. Potjans and M. Diesmann. The cell-type specific cortical microcircuit: Relating structure and activity in a full-scalespiking network model. 24(3):785–806, Dec. 2014.[4] R. Gutzen, M. von Papen, G. Trensch, P. Quaglio, S. Grün, and M. Denker. Reproducible neural network simulations:Statistical meth-ods for model validation on the level of network activity data. Frontiers in Neuroinformatics, 12:90, 2018.[5] R. Bakker, W. Thomas, and M. Diesmann. CoCoMac 2.0 and the future of tract-tracing databases. 6:30, 2012.[6] M. J. de Haan, T. Brochier, S. Grün, A. Riehle, and F. V. Barthélemy. Real-time visuomotor behavior and electrophysiologyrecording setup for use with humans and monkeys. Journal of Neurophysiology, 120(2):539– 552, 2018. PMID: 29718806. |