| Literature DB >> 16953202 |
Kyriaki Sidiropoulou1, Eleftheria Kyriaki Pissadaki, Panayiota Poirazi.
Abstract
For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials only in response to suprathreshold stimuli. Although modelling studies predicted that single neurons constitute a much more powerful computational entity, able to perform an array of nonlinear calculations, this possibility was not explored experimentally until the discovery of active mechanisms in the dendrites of most neuron types. Here, we review several modelling studies that have addressed information processing in single neurons, starting with those characterizing the arithmetic of different dendritic components, to those tackling neuronal integration at the cell body and, finally, those analysing the computational abilities of the axon. We present modelling predictions along with supporting experimental data in an effort to highlight the significant contribution of modelling work to enhancing our understanding of single-neuron arithmetic.Mesh:
Year: 2006 PMID: 16953202 PMCID: PMC1559659 DOI: 10.1038/sj.embor.7400789
Source DB: PubMed Journal: EMBO Rep ISSN: 1469-221X Impact factor: 8.807