Literature DB >> 35719312

All neurons can perform linearly non-separable computations.

Romain D Cazé1.   

Abstract

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturation due to interacting synapses. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with interacting synapses has more computational capacity than without. Because all neurons have one or more layer, we show that all neurons can potentially implement linearly non-separable computations. Copyright:
© 2022 Cazé RD.

Entities:  

Keywords:  Dendrites; computation; linearly non-separable; neuroscience

Mesh:

Year:  2021        PMID: 35719312      PMCID: PMC9198478.3          DOI: 10.12688/f1000research.53961.3

Source DB:  PubMed          Journal:  F1000Res        ISSN: 2046-1402


  8 in total

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Authors:  Jeffrey S Diamond
Journal:  Nat Neurosci       Date:  2002-04       Impact factor: 24.884

2.  Pyramidal neuron as two-layer neural network.

Authors:  Panayiota Poirazi; Terrence Brannon; Bartlett W Mel
Journal:  Neuron       Date:  2003-03-27       Impact factor: 17.173

3.  Computational subunits in thin dendrites of pyramidal cells.

Authors:  Alon Polsky; Bartlett W Mel; Jackie Schiller
Journal:  Nat Neurosci       Date:  2004-05-23       Impact factor: 24.884

4.  Thin dendrites of cerebellar interneurons confer sublinear synaptic integration and a gradient of short-term plasticity.

Authors:  Therese Abrahamsson; Laurence Cathala; Ko Matsui; Ryuichi Shigemoto; David A Digregorio
Journal:  Neuron       Date:  2012-03-21       Impact factor: 17.173

5.  Dendritic action potentials and computation in human layer 2/3 cortical neurons.

Authors:  Albert Gidon; Timothy Adam Zolnik; Pawel Fidzinski; Felix Bolduan; Athanasia Papoutsi; Panayiota Poirazi; Martin Holtkamp; Imre Vida; Matthew Evan Larkum
Journal:  Science       Date:  2020-01-03       Impact factor: 47.728

6.  Non-additive coupling enables propagation of synchronous spiking activity in purely random networks.

Authors:  Raoul-Martin Memmesheimer; Marc Timme
Journal:  PLoS Comput Biol       Date:  2012-04-19       Impact factor: 4.475

7.  Challenging the point neuron dogma: FS basket cells as 2-stage nonlinear integrators.

Authors:  Alexandra Tzilivaki; George Kastellakis; Panayiota Poirazi
Journal:  Nat Commun       Date:  2019-08-14       Impact factor: 14.919

8.  Passive dendrites enable single neurons to compute linearly non-separable functions.

Authors:  Romain Daniel Cazé; Mark Humphries; Boris Gutkin
Journal:  PLoS Comput Biol       Date:  2013-02-28       Impact factor: 4.475

  8 in total

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