Literature DB >> 24709598

Molecular computation in neurons: a modeling perspective.

Upinder S Bhalla1.   

Abstract

Neurons perform far more computations than the conventional framework of summation and propagation of electrical signals from dendrite to soma to axon. There is an enormous and largely hidden layer of molecular computation, and many aspects of neuronal plasticity have been modeled in chemical terms. Memorable events impinge on a neuron as special input patterns, and the neuron has to decide if it should 'remember' this event. This pattern-decoding decision is mediated by kinase cascades and signaling networks over millisecond to hour-long timescales. The process of cellular memory itself is rooted in molecular changes that give rise to life-long, stable physiological changes. Modeling studies show how cascades of synaptic molecular switches can achieve this, despite stochasticity and molecular turnover. Such biochemically detailed models form a valuable conceptual framework to assimilate the complexities of chemical signaling in neuronal computation.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2013        PMID: 24709598     DOI: 10.1016/j.conb.2013.11.006

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  12 in total

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Review 2.  Computational models in the age of large datasets.

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5.  Inward rectifier potassium (Kir) current in dopaminergic periglomerular neurons of the mouse olfactory bulb.

Authors:  Mirta Borin; Alex Fogli Iseppe; Angela Pignatelli; Ottorino Belluzzi
Journal:  Front Cell Neurosci       Date:  2014-08-08       Impact factor: 5.505

6.  Dendritic trafficking faces physiologically critical speed-precision tradeoffs.

Authors:  Alex H Williams; Cian O'Donnell; Terrence J Sejnowski; Timothy O'Leary
Journal:  Elife       Date:  2016-12-30       Impact factor: 8.140

Review 7.  Dopaminergic Neurones in the Main Olfactory Bulb: An Overview from an Electrophysiological Perspective.

Authors:  Angela Pignatelli; Ottorino Belluzzi
Journal:  Front Neuroanat       Date:  2017-02-14       Impact factor: 3.856

8.  Biologically based neural circuit modelling for the study of fear learning and extinction.

Authors:  Satish S Nair; Denis Paré; Aleksandra Vicentic
Journal:  NPJ Sci Learn       Date:  2016-11-09

9.  Synaptic mechanisms of interference in working memory.

Authors:  Zachary P Kilpatrick
Journal:  Sci Rep       Date:  2018-05-18       Impact factor: 4.379

10.  Competition for synaptic building blocks shapes synaptic plasticity.

Authors:  Jochen Triesch; Anh Duong Vo; Anne-Sophie Hafner
Journal:  Elife       Date:  2018-09-17       Impact factor: 8.140

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