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Related Concept Videos

Association Areas of the Cortex01:21

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
Vision01:24

Vision

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.
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex.

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Related Experiment Video

Updated: Jun 21, 2026

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns
09:42

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Published on: May 12, 2019

Attention improves object representation in visual cortical field potentials.

David Rotermund1, Katja Taylor, Udo A Ernst

  • 1Institute for Theoretical Physics, University of Bremen, Germany. davrot@neuro.uni-bremen.de

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|August 14, 2009
PubMed
Summary
This summary is machine-generated.

Selective attention enhances visual perception by making neural network states more distinct for different stimuli. This mechanism, observed in V4 and V1, explains behavioral improvements and is absent during errors.

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Last Updated: Jun 21, 2026

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Published on: August 1, 2018

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Visual Perception

Background:

  • Selective attention modulates neuronal responses, enhancing perception.
  • Mechanisms like signal strength or signal-to-noise ratio changes are proposed but not fully understood.
  • The precise contribution of attention-dependent cortical activity to perceptual improvement remains unclear.

Purpose of the Study:

  • To investigate how selective attention influences cortical activity in the visual cortex (V1 and V4) in monkeys.
  • To determine the neural mechanisms underlying attention-dependent perceptual improvements.
  • To differentiate between proposed mechanisms such as signal enhancement versus distinct network state changes.

Main Methods:

  • Monkeys were trained to discriminate shapes under selective attention.
  • Neuronal activity, specifically gamma-band power, was recorded from V1 and V4.
  • Analysis focused on information content about stimulus shape and its relation to attention and behavioral outcomes.

Main Results:

  • Gamma-band activity in V4 and V1 contained significant information about stimulus shape.
  • Attention considerably increased this information in V4 during successful trials, but not during errors.
  • The observed effect stemmed from enhanced differences in power spectral amplitude distributions, not signal-to-noise ratio or total power changes.

Conclusions:

  • Attention enhances perception by making distinct cortical network states more separable for different stimuli.
  • This distinctiveness of network states provides a novel neurophysiological explanation for attention-driven behavioral improvements.
  • The absence of this effect in error trials highlights its critical role in successful perception.