Literature DB >> 8463838

Thalamocortical response transformations in simulated whisker barrels.

H T Kyriazi1, D J Simons.   

Abstract

Layer IV of rodent somatosensory cortex contains identifiable networks of neurons, called "barrels," that are related one-to-one to individual whiskers on the face. A previous study (Simons and Carvell, 1989) described differences between the response properties of thalamic and cortical vibrissa neurons and proposed that these transformations can be explained by several features of barrel anatomy and physiology: nonlinear neuronal properties, strongly responsive inhibitory and less responsive excitatory neurons, convergent thalamic inputs to cells of both types, and interconnections among barrel neurons. In the present study these features were incorporated into a computational model in order to test their explanatory power quantitatively. The relative numbers of excitatory and inhibitory cells and the relative numbers of synapses of thalamic and intrabarrel origin were chosen to be consistent with available light and electron microscopic data. Known functional differences between excitatory and inhibitory barrel neurons were simulated through differences in spike activation functions, refractory periods, postsynaptic potential decay rates, and synaptic strengths. The model network was activated by spike trains recorded previously from thalamic neurons in response to three different whisker deflection protocols, and output, which consisted of spikes generated by the simulated neurons, was compared to data from our previous neurophysiological experiments. For each type of whisker stimulus, the same set of parameter values yielded accurate simulations of the cortical response. Realistic output was obtained under conditions where each barrel cell integrated excitatory and inhibitory synaptic inputs from a number of thalamic and other barrel neurons and where the ratios between network excitation, network inhibition, and thalamic excitation were approximately constant. Several quantities are defined that may be generally useful in characterizing neuronal networks. One important implication of the results is that thalamic relay neurons not only provide essential drive to the cortex but could, by changing their tonic activities, also directly regulate the tonic inhibition present in the cortex and thereby modulate cortical receptive field properties.

Mesh:

Year:  1993        PMID: 8463838      PMCID: PMC6576731     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  28 in total

1.  A model of ocular dominance column development by competition for trophic factor: effects of excess trophic factor with monocular deprivation and effects of antagonist of trophic factor.

Authors:  A E Harris; G B Ermentrout; S L Small
Journal:  J Comput Neurosci       Date:  2000 May-Jun       Impact factor: 1.621

2.  Analysis of variance study of the rat cortical layer 4 barrel and layer 5b neurones.

Authors:  Muneyuki Ito; Miyuki Kato
Journal:  J Physiol       Date:  2002-03-01       Impact factor: 5.182

3.  Functional independence of layer IV barrels.

Authors:  Nora Laaris; Asaf Keller
Journal:  J Neurophysiol       Date:  2002-02       Impact factor: 2.714

4.  Thalamocortical angular tuning domains within individual barrels of rat somatosensory cortex.

Authors:  Randy M Bruno; Vivek Khatri; Peter W Land; Daniel J Simons
Journal:  J Neurosci       Date:  2003-10-22       Impact factor: 6.167

5.  A point process analysis of sensory encoding.

Authors:  Garrett B Stanley; Roxanna M Webber
Journal:  J Comput Neurosci       Date:  2003 Nov-Dec       Impact factor: 1.621

6.  Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model.

Authors:  Elena Phoka; Mark Wildie; Simon R Schultz; Mauricio Barahona
Journal:  J Comput Neurosci       Date:  2012-03-09       Impact factor: 1.621

7.  A quantitative population model of whisker barrels: re-examining the Wilson-Cowan equations.

Authors:  D J Pinto; J C Brumberg; D J Simons; G B Ermentrout
Journal:  J Comput Neurosci       Date:  1996-09       Impact factor: 1.621

8.  Encoding whisker deflection velocity within the rodent barrel cortex using phase-delayed inhibition.

Authors:  Runjing Liu; Mainak Patel; Badal Joshi
Journal:  J Comput Neurosci       Date:  2014-10-05       Impact factor: 1.621

9.  Modeling the emergence of whisker direction maps in rat barrel cortex.

Authors:  Stuart P Wilson; Judith S Law; Ben Mitchinson; Tony J Prescott; James A Bednar
Journal:  PLoS One       Date:  2010-01-22       Impact factor: 3.240

10.  Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminar-electrode recordings in the rat barrel system.

Authors:  Patrick Blomquist; Anna Devor; Ulf G Indahl; Istvan Ulbert; Gaute T Einevoll; Anders M Dale
Journal:  PLoS Comput Biol       Date:  2009-03-27       Impact factor: 4.475

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