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Co-operative populations of neurons: mean field models of mesoscopic brain activity

Liley, D. T. J., Foster, B. L. and Bojak, I. (2012) Co-operative populations of neurons: mean field models of mesoscopic brain activity. In: Le Nov`ere, N. (ed.) Computational Systems Neurobiology. Springer, Dordrecht, pp. 317-364. ISBN 9789400738577

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To link to this item DOI: 10.1007/978-94-007-3858-4_11


Item Type:Book or Report Section
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Centre for Integrative Neuroscience and Neurodynamics (CINN)
No Reading authors. Back catalogue items
ID Code:32498
Publisher:Springer
Publisher Statement:While the basic units of computation in the brain are the neuronal cells, their sheer number, complexity of structural organisation and widespread connectivity make it difficult, if not impossible, to perform realistic simulations of activity at millimetre range or beyond. Furthermore, it is becoming increasingly clear that a range of non-neuronal and stochastic factors influence neuronal excitability, and must be taken into account when developing models and theories of brain function. One answer to the these persistent difficulties is to model cortical tissue not as a network of spike-based enumerable neurons, but to take inspiration from statistical physics and model directly the bulk properties of the populations constituting the cortical tissue. Such an approach proves compatible with many experimental recording techniques and has led to a successful class of so-called “mean field theories” that, when constrained by meaningful physiological and anatomical parameterisations, reveal a rich repertoire of biologically plausible and predictive dynamics. The aim of this chapter is to outline the historical genesis of this important modelling framework, and to detail its many successes in accounting for the experimentally observed neuronal population activity in cortex.

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