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Related Concept Videos

Vision01:24

Vision

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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Topographical Estimation of Visual Population Receptive Fields by fMRI
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Spontaneous Fluctuations in Visual Cortical Responses Influence Population Coding Accuracy.

Diego A Gutnisky1,2, Charles B Beaman1, Sergio E Lew1,3

  • 1Department of Neurobiology and Anatomy, University of Texas-Houston Medical School, Houston, TX 77030, USA.

Cerebral Cortex (New York, N.Y. : 1991)
|January 9, 2016
PubMed
Summary
This summary is machine-generated.

Ongoing brain activity, or neuronal context, significantly impacts how visual information is processed. A low prestimulus state in neurons enhances the brain

Keywords:
correlationsnetworksspontaneousvisual cortex

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Sensory Coding

Background:

  • Neuronal network state influences information processing in the cerebral cortex.
  • The role of ongoing activity in adult visual cortex feature coding remains unclear.
  • Prestimulus activity may act as a critical factor in determining neuronal context.

Purpose of the Study:

  • To investigate how information encoded by primary visual cortex (V1) neurons depends on prestimulus activity.
  • To determine if ongoing activity influences the coding of visual features in adult V1.
  • To explore the impact of neuronal network states on sensory coding accuracy.

Main Methods:

  • Recording neuronal activity in the primary visual cortex (V1).
  • Analyzing the relationship between prestimulus activity states and stimulus feature discrimination.
  • Measuring population-level network discrimination accuracy based on prestimulus activity distributions.

Main Results:

  • Individual neurons in a low prestimulus state show enhanced discrimination of visual features like orientation.
  • Evoked responses are reduced in the low prestimulus state, but discrimination capacity is higher.
  • Network discrimination accuracy improves when neurons are in a low prestimulus state.

Conclusions:

  • The distribution of ongoing activity states creates an internal context that dynamically filters stimuli.
  • This internal context modulates the accuracy of sensory coding in the visual cortex.
  • Recurrent network models support the dynamic control of excitation and inhibition by ongoing activity.