Oscillations and Synchrony in Large-scale Cortical Network Models

Intrinsic neuronal and circuit properties control the responses of large ensembles of neurons by creating spatiotemporal patterns of activity that are used for sensory processing, memory formation, and other cognitive tasks. The modeling of such systems requires computationally efficient single-neur...

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Bibliographic Details
Published in:Journal of biological physics 2008-08, Vol.34 (3-4), p.279-299
Main Authors: Rulkov, Nikolai F, Bazhenov, Maxim
Format: Article
Language:English
Subjects:
Biochemistry
Biological and Medical Physics
Biophysics
Complex Fluids and Microfluidics
Complex Systems
Cortical network
Gamma oscillations
Large-scale model
Neural networks
Neuron
Neurons
Neurosciences
Original Paper
Physics
Physics and Astronomy
Soft and Granular Matter
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Summary:Intrinsic neuronal and circuit properties control the responses of large ensembles of neurons by creating spatiotemporal patterns of activity that are used for sensory processing, memory formation, and other cognitive tasks. The modeling of such systems requires computationally efficient single-neuron models capable of displaying realistic response properties. We developed a set of reduced models based on difference equations (map-based models) to simulate the intrinsic dynamics of biological neurons. These phenomenological models were designed to capture the main response properties of specific types of neurons while ensuring realistic model behavior across a sufficient dynamic range of inputs. This approach allows for fast simulations and efficient parameter space analysis of networks containing hundreds of thousands of neurons of different types using a conventional workstation. Drawing on results obtained using large-scale networks of map-based neurons, we discuss spatiotemporal cortical network dynamics as a function of parameters that affect synaptic interactions and intrinsic states of the neurons.
ISSN:0092-0606
1573-0689
DOI:10.1007/s10867-008-9079-y