Literature DB >> 16771655

Dynamic gain changes during attentional modulation.

Arun P Sripati1, Kenneth O Johnson.   

Abstract

Attention causes a multiplicative effect on firing rates of cortical neurons without affecting their selectivity (Motter, 1993; McAdams & Maunsell, 1999a) or the relationship between the spike count mean and variance (McAdams & Maunsell, 1999b). We analyzed attentional modulation of the firing rates of 144 neurons in the secondary somatosensory cortex (SII) of two monkeys trained to switch their attention between a tactile pattern recognition task and a visual task. We found that neurons in SII cortex also undergo a predominantly multiplicative modulation in firing rates without affecting the ratio of variance to mean firing rate (i.e., the Fano factor). Furthermore, both additive and multiplicative components of attentional modulation varied dynamically during the stimulus presentation. We then used a standard conductance-based integrate-and-fire model neuron to ascertain which mechanisms might account for a multiplicative increase in firing rate without affecting the Fano factor. Six mechanisms were identified as biophysically plausible ways that attention could modify the firing rate: spike threshold, firing rate adaptation, excitatory input synchrony, synchrony between all inputs, membrane leak resistance, and reset potential. Of these, only a change in spike threshold or in firing rate adaptation affected model firing rates in a manner compatible with the observed neural data. The results indicate that only a limited number of biophysical mechanisms can account for observed attentional modulation.

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Mesh:

Year:  2006        PMID: 16771655      PMCID: PMC1839043          DOI: 10.1162/neco.2006.18.8.1847

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  34 in total

1.  Effects of attention on the reliability of individual neurons in monkey visual cortex.

Authors:  C J McAdams; J H Maunsell
Journal:  Neuron       Date:  1999-08       Impact factor: 17.173

2.  Impact of correlated inputs on the output of the integrate- and-fire model.

Authors:  J Feng; D Brown
Journal:  Neural Comput       Date:  2000-03       Impact factor: 2.026

3.  Modulation of oscillatory neuronal synchronization by selective visual attention.

Authors:  P Fries; J H Reynolds; A E Rorie; R Desimone
Journal:  Science       Date:  2001-02-23       Impact factor: 47.728

4.  Competitive mechanisms subserve attention in macaque areas V2 and V4.

Authors:  J H Reynolds; L Chelazzi; R Desimone
Journal:  J Neurosci       Date:  1999-03-01       Impact factor: 6.167

5.  Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input.

Authors:  A N Burkitt; H Meffin; D B Grayden
Journal:  Biol Cybern       Date:  2003-06-05       Impact factor: 2.086

6.  The analysis of visual motion: a comparison of neuronal and psychophysical performance.

Authors:  K H Britten; M N Shadlen; W T Newsome; J A Movshon
Journal:  J Neurosci       Date:  1992-12       Impact factor: 6.167

Review 7.  Attentional modulation of visual processing.

Authors:  John H Reynolds; Leonardo Chelazzi
Journal:  Annu Rev Neurosci       Date:  2004       Impact factor: 12.449

8.  A computational analysis of the relationship between neuronal and behavioral responses to visual motion.

Authors:  M N Shadlen; K H Britten; W T Newsome; J A Movshon
Journal:  J Neurosci       Date:  1996-02-15       Impact factor: 6.167

9.  Influence of low and high frequency inputs on spike timing in visual cortical neurons.

Authors:  L G Nowak; M V Sanchez-Vives; D A McCormick
Journal:  Cereb Cortex       Date:  1997-09       Impact factor: 5.357

10.  Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex.

Authors:  D A McCormick; B W Connors; J W Lighthall; D A Prince
Journal:  J Neurophysiol       Date:  1985-10       Impact factor: 2.714

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  10 in total

Review 1.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

Review 2.  Does attention play a role in dynamic receptive field adaptation to changing acoustic salience in A1?

Authors:  Jonathan B Fritz; Mounya Elhilali; Stephen V David; Shihab A Shamma
Journal:  Hear Res       Date:  2007-01-16       Impact factor: 3.208

3.  Context-dependent modulation of functional connectivity: secondary somatosensory cortex to prefrontal cortex connections in two-stimulus-interval discrimination tasks.

Authors:  Stephanie S Chow; Ranulfo Romo; Carlos D Brody
Journal:  J Neurosci       Date:  2009-06-03       Impact factor: 6.167

4.  Spatial representation and cognitive modulation of response variability in the lateral intraparietal area priority map.

Authors:  Annegret L Falkner; Michael E Goldberg; B Suresh Krishna
Journal:  J Neurosci       Date:  2013-10-09       Impact factor: 6.167

5.  Attention directed by expectations enhances receptive fields in cortical area MT.

Authors:  Geoffrey M Ghose; David W Bearl
Journal:  Vision Res       Date:  2009-10-09       Impact factor: 1.886

6.  Temporally evolving gain mechanisms of attention in macaque area V4.

Authors:  Ilaria Sani; Elisa Santandrea; Maria Concetta Morrone; Leonardo Chelazzi
Journal:  J Neurophysiol       Date:  2017-05-03       Impact factor: 2.714

7.  Attention Selectively Gates Afferent Signal Transmission to Area V4.

Authors:  Iris Grothe; David Rotermund; Simon David Neitzel; Sunita Mandon; Udo Alexander Ernst; Andreas K Kreiter; Klaus Richard Pawelzik
Journal:  J Neurosci       Date:  2018-04-04       Impact factor: 6.167

8.  A Stable Population Code for Attention in Prefrontal Cortex Leads a Dynamic Attention Code in Visual Cortex.

Authors:  Adam C Snyder; Byron M Yu; Matthew A Smith
Journal:  J Neurosci       Date:  2021-09-28       Impact factor: 6.167

9.  Real Time Multiplicative Memory Amplification Mediated by Whole-Cell Scaling of Synaptic Response in Key Neurons.

Authors:  Iris Reuveni; Sourav Ghosh; Edi Barkai
Journal:  PLoS Comput Biol       Date:  2017-01-19       Impact factor: 4.475

10.  Single and Multiple Change Point Detection in Spike Trains: Comparison of Different CUSUM Methods.

Authors:  Lena Koepcke; Go Ashida; Jutta Kretzberg
Journal:  Front Syst Neurosci       Date:  2016-06-22
  10 in total

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