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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,...
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.
Visual Agnosia01:12

Visual Agnosia

Visual agnosia is a condition characterized by the inability to recognize visually presented objects despite having normal vision. For instance, a person with visual agnosia can describe the shape and color of an object but cannot identify or name it. This impairment does not affect their visual field, acuity, color vision, brightness discrimination, language, or memory. An example of this condition in a social setting is someone at a dinner party asking for "that silver thing with a round end"...

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Related Experiment Video

Updated: Jun 2, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Object decoding with attention in inferior temporal cortex.

Ying Zhang1, Ethan M Meyers, Narcisse P Bichot

  • 1Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Proceedings of the National Academy of Sciences of the United States of America
|May 11, 2011
PubMed
Summary
This summary is machine-generated.

Visual attention mechanisms enhance object recognition in cluttered scenes by restoring neural activity patterns. However, salient non-attended objects can override these top-down attentional effects.

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Related Experiment Videos

Last Updated: Jun 2, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

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Published on: June 17, 2019

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Visual Perception

Background:

  • Object recognition in cluttered environments relies on attentional mechanisms.
  • Physiological correlates of attention, like enhanced neural responses, are known in the visual cortex.
  • The population-level impact of attention on object information remains unclear.

Purpose of the Study:

  • To investigate how attention modulates neural population information about objects in cluttered scenes.
  • To determine if attention-related neural changes significantly impact object recognition.
  • To assess the interplay between top-down attention and bottom-up saliency.

Main Methods:

  • Monkeys were trained to covertly deploy visual attention to peripheral objects.
  • Information about object identity and position was decoded from neural populations (∼200 neurons) in the inferior temporal cortex using a pattern classifier.
  • Neural activity patterns were analyzed before and after attention deployment.

Main Results:

  • Before attention, object information was significantly reduced in cluttered displays compared to isolated objects.
  • Attending to an object restored its neural activity pattern, approaching that of an isolated object.
  • Bottom-up saliency of non-attended objects could override top-down attentional enhancements.

Conclusions:

  • Attentional mechanisms play a crucial role in restoring object information at the neural population level for recognition.
  • Neural decoding methods can quantify the impact of attention on object representation.
  • Future research can utilize this method to explore other attentional modulations in object recognition.