Literature DB >> 16953202

Inside the brain of a neuron.

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


  68 in total

1.  Effect of geometrical irregularities on propagation delay in axonal trees.

Authors:  Y Manor; C Koch; I Segev
Journal:  Biophys J       Date:  1991-12       Impact factor: 4.033

Review 2.  Cellular basis of working memory.

Authors:  P S Goldman-Rakic
Journal:  Neuron       Date:  1995-03       Impact factor: 17.173

3.  Critical role of axonal A-type K+ channels and axonal geometry in the gating of action potential propagation along CA3 pyramidal cell axons: a simulation study.

Authors:  I L Kopysova; D Debanne
Journal:  J Neurosci       Date:  1998-09-15       Impact factor: 6.167

4.  Dendritic integration and its role in computing image velocity.

Authors:  S Single; A Borst
Journal:  Science       Date:  1998-09-18       Impact factor: 47.728

Review 5.  Encoding and retrieval of episodic memories: role of cholinergic and GABAergic modulation in the hippocampus.

Authors:  M E Hasselmo; B P Wyble; G V Wallenstein
Journal:  Hippocampus       Date:  1996       Impact factor: 3.899

6.  The role of dendrites in auditory coincidence detection.

Authors:  H Agmon-Snir; C E Carr; J Rinzel
Journal:  Nature       Date:  1998-05-21       Impact factor: 49.962

Review 7.  Action potential initiation and backpropagation in neurons of the mammalian CNS.

Authors:  G Stuart; N Spruston; B Sakmann; M Häusser
Journal:  Trends Neurosci       Date:  1997-03       Impact factor: 13.837

8.  Action-potential propagation gated by an axonal I(A)-like K+ conductance in hippocampus.

Authors:  D Debanne; N C Guérineau; B H Gähwiler; S M Thompson
Journal:  Nature       Date:  1997-09-18       Impact factor: 49.962

Review 9.  The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs.

Authors:  W R Softky; C Koch
Journal:  J Neurosci       Date:  1993-01       Impact factor: 6.167

10.  Ca2+ accumulations in dendrites of neocortical pyramidal neurons: an apical band and evidence for two functional compartments.

Authors:  R Yuste; M J Gutnick; D Saar; K R Delaney; D W Tank
Journal:  Neuron       Date:  1994-07       Impact factor: 17.173

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  13 in total

1.  Somatodendritic integration under increased network activity in layer 5 pyramidal cells of the somatosensory cortex.

Authors:  Florian B Neubauer; Thomas Berger
Journal:  Pflugers Arch       Date:  2007-10-20       Impact factor: 3.657

2.  A propagating ERKII switch forms zones of elevated dendritic activation correlated with plasticity.

Authors:  Sriram M Ajay; Upinder S Bhalla
Journal:  HFSP J       Date:  2007-04-18

Review 3.  Beyond faithful conduction: short-term dynamics, neuromodulation, and long-term regulation of spike propagation in the axon.

Authors:  Dirk Bucher; Jean-Marc Goaillard
Journal:  Prog Neurobiol       Date:  2011-06-17       Impact factor: 11.685

Review 4.  Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

Authors:  Simo Vanni; Fariba Sharifian; Hanna Heikkinen; Ricardo Vigário
Journal:  J Neurophysiol       Date:  2015-05-13       Impact factor: 2.714

5.  Parameter estimation of a spiking silicon neuron.

Authors:  Alexander Russell; Kevin Mazurek; Stefan Mihalaş; Ernst Niebur; Ralph Etienne-Cummings
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2012-04       Impact factor: 3.833

Review 6.  Molecular and cellular approaches to memory allocation in neural circuits.

Authors:  Alcino J Silva; Yu Zhou; Thomas Rogerson; Justin Shobe; J Balaji
Journal:  Science       Date:  2009-10-16       Impact factor: 47.728

7.  Complex intrinsic membrane properties and dopamine shape spiking activity in a motor axon.

Authors:  Aleksander W Ballo; Dirk Bucher
Journal:  J Neurosci       Date:  2009-04-22       Impact factor: 6.167

8.  Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

Authors:  Eleftheria Kyriaki Pissadaki; Kyriaki Sidiropoulou; Martin Reczko; Panayiota Poirazi
Journal:  PLoS Comput Biol       Date:  2010-12-16       Impact factor: 4.475

9.  Semantic processing of English sentences using statistical computation based on neurophysiological models.

Authors:  Marcia T Mitchell
Journal:  Front Physiol       Date:  2015-05-22       Impact factor: 4.566

10.  Inter-synaptic learning of combination rules in a cortical network model.

Authors:  Frédéric Lavigne; Francis Avnaïm; Laurent Dumercy
Journal:  Front Psychol       Date:  2014-08-28
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