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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.
Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role of...

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Related Experiment Video

Updated: May 30, 2026

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

Decoding of faces and face components in face-sensitive human visual cortex.

David F Nichols1, Lisa R Betts, Hugh R Wilson

  • 1Centre for Vision Research, York University Toronto, ON, Canada.

Frontiers in Psychology
|August 12, 2011
PubMed
Summary
This summary is machine-generated.

This study used fMRI to investigate how the human brain processes faces. Whole faces are primarily represented in the fusiform cortex (FFA), while facial components are processed in the occipitotemporal cortex (OFA).

Keywords:
face perceptionfunctional magnetic resonance imagingfusiform face areamulti-voxel pattern classificationoccipital face areavision

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Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
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Last Updated: May 30, 2026

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
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Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
07:08

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Visual Neuroscience

Background:

  • Understanding face encoding in the human brain is a significant challenge in visual neuroscience.
  • Previous research suggests specialized brain regions for face processing, but the precise organization remains debated.

Purpose of the Study:

  • To investigate the neural representation of whole faces versus facial components in the human brain.
  • To determine the distinct roles of the fusiform cortex (FFA) and occipitotemporal cortex (OFA) in face perception.

Main Methods:

  • Functional magnetic resonance imaging (fMRI) was employed to measure brain activity.
  • Multi-class linear pattern classifiers with a leave-one-scan-out procedure were used to analyze activation patterns.
  • Brain responses to whole faces, internal facial features, and external head outlines were discriminated.

Main Results:

  • Evidence for spatially distributed processing of faces and their components in face-sensitive visual cortex.
  • Whole faces showed disproportionate representation in the fusiform cortex (FFA).
  • Facial components (internal features and external outline) demonstrated disproportionate representation in the occipitotemporal cortex (OFA).

Conclusions:

  • The findings suggest functional clustering within both FFA and OFA for face processing.
  • The OFA appears specialized for processing facial components, while the FFA is specialized for processing whole faces.
  • This research advances our understanding of the neural architecture underlying human face perception.