contribution of sublinear and supralinear dendritic integration to neuronal computations

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ID: 166653
2015
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Abstract
Nonlinear dendritic integration is thought to increase the computational ability of neurons. Most studies focus on how supralinear summation of excitatory synaptic responses arising from clustered inputs within single dendrites result in the enhancement of neuronal firing, enabling simple computations such as feature detection. Recent reports have shown that sublinear summation is also a prominent dendritic operation, extending the range of subthreshold input-output transformations conferred by dendrites. Like supralinear operations, sublinear dendritic operations also increase the repertoire of neuronal computations, but feature extraction requires different synaptic connectivity strategies for each of these operations. In this article we will review the experimental and theoretical findings describing the biophysical determinants of the three primary classes of dendritic operations: linear, sublinear, and supralinear. We then review a Boolean algebra-based analysis of simplified neuron models, which provides insight into how dendritic operations influence neuronal computations. We highlight how neuronal computations are critically dependent on the interplay of dendritic properties (morphology and voltage-gated channel expression), spiking threshold and distribution of synaptic inputs carrying particular sensory features. Finally, we describe how global (scattered) and local (clustered) integration strategies permit the implementation of similar classes of computations, one example being the object feature binding problem.
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etran-van-minh2015frontierscontribution Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Alexandra eTran-Van-Minh;Alexandra eTran-Van-Minh;Romain Daniel Cazé;Romain Daniel Cazé;Therese eAbrahamsson;Therese eAbrahamsson;Therese eAbrahamsson;Laurence eCathala;Boris S. Gutkin;Boris S. Gutkin;David A. DiGregorio;David A. DiGregorio
Journal macromolecular bioscience
Year 2015
DOI
10.3389/fncel.2015.00067
URL
http://journal.frontiersin.org/Journal/10.3389/fncel.2015.00067/full
Keywords
neural computation neuropsychiatry biological psychiatry boolean analysisneurosciences

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