Literature DB >> 12890788

Response to contrast of electrophysiologically defined cell classes in primary visual cortex.

Diego Contreras1, Larry Palmer.   

Abstract

Information processing in the visual cortex is critically dependent on the input-output relationships of its component neurons. The transformation of synaptic inputs into spike trains depends in turn on the host of intrinsic membrane properties expressed by neurons, which define established electrophysiological cell classes in the neocortex. Here we studied, with intracellular recordings in vivo, how the electrophysiological cell classes in the primary visual cortex transform an increasing input, represented by stimulus contrast, into membrane depolarization and trains of action potentials. We used contrast as input because, regardless of their stimulus selectivity, primary visual cortical cells increase their firing rates in response to increases in luminance contrast. We found that both the spike rate response and the membrane potential response are best described by the hyperbolic ratio function when compared with linear, power, and logarithmic functions. In addition, both responses show similar parameter values and similar residual variance from the fits to all four functions. We also found that changes in membrane potential are similar, but firing rates differ strongly, between the established electrophysiological cell classes: fast spiking neurons show the highest firing rates, followed by fast rhythmic bursting, and regular spiking (RS) cells. In addition, among complex cells, RS cells from supragranular layers fired at higher rates than RS cells from infragranular layers. Finally, we show that the differences in firing rates between cell classes arise from differences in the slope of the relationship between membrane potential and spike rate.

Entities:  

Mesh:

Year:  2003        PMID: 12890788      PMCID: PMC6740720     

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


  48 in total

1.  Isolating early cortical generators of visual-evoked activity: a systems identification approach.

Authors:  Jeremy W Murphy; Simon P Kelly; John J Foxe; Edmund C Lalor
Journal:  Exp Brain Res       Date:  2012-05-29       Impact factor: 1.972

2.  Layer-specific excitation/inhibition balances during neuronal synchronization in the visual cortex.

Authors:  Hillel Adesnik
Journal:  J Physiol       Date:  2018-01-24       Impact factor: 5.182

3.  Receptive field structure varies with layer in the primary visual cortex.

Authors:  Luis M Martinez; Qingbo Wang; R Clay Reid; Cinthi Pillai; José-Mañuel Alonso; Friedrich T Sommer; Judith A Hirsch
Journal:  Nat Neurosci       Date:  2005-02-13       Impact factor: 24.884

4.  Nonlinear local electrovascular coupling. I: A theoretical model.

Authors:  Jorge J Riera; Xiaohong Wan; Juan Carlos Jimenez; Ryuta Kawashima
Journal:  Hum Brain Mapp       Date:  2006-11       Impact factor: 5.038

5.  Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex.

Authors:  Jessica A Cardin; Larry A Palmer; Diego Contreras
Journal:  J Neurosci       Date:  2007-09-26       Impact factor: 6.167

6.  Lack of orientation and direction selectivity in a subgroup of fast-spiking inhibitory interneurons: cellular and synaptic mechanisms and comparison with other electrophysiological cell types.

Authors:  Lionel G Nowak; Maria V Sanchez-Vives; David A McCormick
Journal:  Cereb Cortex       Date:  2007-08-23       Impact factor: 5.357

7.  Layer 4 in primary visual cortex of the awake rabbit: contrasting properties of simple cells and putative feedforward inhibitory interneurons.

Authors:  Jun Zhuang; Carl R Stoelzel; Yulia Bereshpolova; Joseph M Huff; Xiaojuan Hei; Jose-Manuel Alonso; Harvey A Swadlow
Journal:  J Neurosci       Date:  2013-07-10       Impact factor: 6.167

8.  Common rules guide comparisons of speed and direction of motion in the dorsolateral prefrontal cortex.

Authors:  Cory R Hussar; Tatiana Pasternak
Journal:  J Neurosci       Date:  2013-01-16       Impact factor: 6.167

9.  Intracellular, In Vivo, Dynamics of Thalamocortical Synapses in Visual Cortex.

Authors:  Madineh Sedigh-Sarvestani; Leif Vigeland; Ivan Fernandez-Lamo; M Morgan Taylor; Larry A Palmer; Diego Contreras
Journal:  J Neurosci       Date:  2017-04-24       Impact factor: 6.167

10.  Flexibility of sensory representations in prefrontal cortex depends on cell type.

Authors:  Cory R Hussar; Tatiana Pasternak
Journal:  Neuron       Date:  2009-12-10       Impact factor: 17.173

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