Pairwise Ising Model Analysis of Human Cortical Neuron Recordings View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017-10-24

AUTHORS

Trang-Anh Nghiem , Olivier Marre , Alain Destexhe , Ulisse Ferrari

ABSTRACT

During wakefulness and deep sleep brain states, cortical neural networks show a different behavior, with the second characterized by transients of high network activity. To investigate their impact on neuronal behavior, we apply a pairwise Ising model analysis by inferring the maximum entropy model that reproduces single and pairwise moments of the neuron’s spiking activity. In this work we first review the inference algorithm introduced in Ferrari, Phys. Rev. E (2016) [1]. We then succeed in applying the algorithm to infer the model from a large ensemble of neurons recorded by multi-electrode array in human temporal cortex. We compare the Ising model performance in capturing the statistical properties of the network activity during wakefulness and deep sleep. For the latter, the pairwise model misses relevant transients of high network activity, suggesting that additional constraints are necessary to accurately model the data. More... »

PAGES

257-264

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-68445-1_30

DOI

http://dx.doi.org/10.1007/978-3-319-68445-1_30

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092381011


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