Multiple models to capture the variability in biological neurons and networks.

Abstract:

:How tightly tuned are the synaptic and intrinsic properties that give rise to neuron and circuit function? Experimental work shows that these properties vary considerably across identified neurons in different animals. Given this variability in experimental data, this review describes some of the complications of building computational models to aid in understanding how system dynamics arise from the interaction of system components. We argue that instead of trying to build a single model that captures the generic behavior of a neuron or circuit, it is beneficial to construct a population of models that captures the behavior of the population that provided the experimental data. Studying a population of models with different underlying structure and similar behaviors provides opportunities to discover unsuspected compensatory mechanisms that contribute to neuron and network function.

journal_name

Nat Neurosci

journal_title

Nature neuroscience

authors

Marder E,Taylor AL

doi

10.1038/nn.2735

subject

Has Abstract

pub_date

2011-02-01 00:00:00

pages

133-8

issue

2

eissn

1097-6256

issn

1546-1726

pii

nn.2735

journal_volume

14

pub_type

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