Multiscale Modeling
multiscale modeling
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A Postdoc position is now available in the Dura-Bernal Lab at the State University of New York (SUNY) Downstate Health Sciences University (Brooklyn, New York), working on a new exciting multidisciplinary project entitled "Restoring motor function after spinal cord injury using multiscale modeling to decode neural latent dynamics from motor cortex EEG." The position is funded by New York State (NYS) Department of Health (DOH) Spinal Cord Injury Research program. The project aims to improve brain-machine interface decoders by combining multiscale modeling of motor cortex circuits, analysis of low-dimensional neural manifolds associated with behavior, and realistic simulation of EEG signals.
Bio-realistic multiscale modeling of cortical circuits
A central question in neuroscience is how the structure of brain circuits determines their activity and function. To explore this systematically, we developed a 230,000-neuron model of mouse primary visual cortex (area V1). The model integrates a broad array of experimental data:Distribution and morpho-electric properties of different neuron types in V1.
Multiscale modeling of brain states, from spiking networks to the whole brain
Modeling brain mechanisms is often confined to a given scale, such as single-cell models, network models or whole-brain models, and it is often difficult to relate these models. Here, we show an approach to build models across scales, starting from the level of circuits to the whole brain. The key is the design of accurate population models derived from biophysical models of networks of excitatory and inhibitory neurons, using mean-field techniques. Such population models can be later integrated as units in large-scale networks defining entire brain areas or the whole brain. We illustrate this approach by the simulation of asynchronous and slow-wave states, from circuits to the whole brain. At the mesoscale (millimeters), these models account for travelling activity waves in cortex, and at the macroscale (centimeters), the models reproduce the synchrony of slow waves and their responsiveness to external stimuli. This approach can also be used to evaluate the impact of sub-cellular parameters, such as receptor types or membrane conductances, on the emergent behavior at the whole-brain level. This is illustrated with simulations of the effect of anesthetics. The program codes are open source and run in open-access platforms (such as EBRAINS).
multiscale modeling coverage
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