Jove
Visualize
Contact Us

Related Concept Videos

Perception01:28

Perception

1.8K
Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...
1.8K
Vision01:24

Vision

61.5K
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.
61.5K
Sensory Perception: Organization of the Somatosensory System01:11

Sensory Perception: Organization of the Somatosensory System

12.5K
The somatosensory system is the central and peripheral nervous system component that senses and processes touch, pressure, pain, temperature, and body position or proprioception. The process of sensation takes place at three levels:
The receptor level:
The receptor level is the first stage of sensation. It involves the detection of a stimulus by specialized sensory receptors. The stimulus must arrive within the receptor's receptive field. Next, the receptor converts the energy of the...
12.5K
Parallel Processing01:20

Parallel Processing

888
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...
888
Visual System01:26

Visual System

2.3K
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...
2.3K
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

9.1K
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....
9.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Operando Cu Aggregation-Induced Spin State Modulation in Fe-Cu Single Atom Catalyst for Enhanced Tandem Electrochemical Nitrate Reduction Reaction.

Journal of the American Chemical Society·2026
Same author

Fe-Mediated Destabilization of Oxygen Intermediates Boosts Oxygen Evolution in Multimetallic Layered Double Hydroxides.

ACS applied materials & interfaces·2026
Same author

Ni Single-Atom Modulation of Ti-O Covalency Boosts Ammonia Oxidation Electrocatalysis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Ultra-Long Bi Nanowires Coupled With Tapered Si Microwires for Selective Photoelectrochemical CO<sub>2</sub>-to-Formate Conversion.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Oral toxicity evaluation of freeze-dried honeybee pupa powder (HDPp) in ICR mice: single-dose and 4-week repeated-dose studies.

Toxicological research·2025
Same author

Recurrent pattern completion drives the neocortical representation of sensory inference.

Nature neuroscience·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Apr 2, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.3K

The neural code of perceptual inference.

Hyeyoung Shin1

  • 1School of Biological Sciences, Seoul National University, Seoul, Republic of Korea. hyeyoung_shin@snu.ac.kr.

Molecular Brain
|April 1, 2026
PubMed
Summary

Perception relies on inference, using prior expectations to interpret sensory data. This review proposes evaluating the neural code for optimal perceptual inference, not just faithful sensory representation.

Keywords:
Bayesian inferenceDiscrimination vs. generalization tradeoffEfficiency vs. robustness tradeoffMarr’s three levelsPerceptual inference

More Related Videos

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

18.1K
Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus
10:43

Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus

Published on: April 21, 2023

4.5K

Related Experiment Videos

Last Updated: Apr 2, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

12.3K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

18.1K
Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus
10:43

Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus

Published on: April 21, 2023

4.5K

Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience

Background:

  • Perception is fundamentally an inferential process, integrating sensory evidence with prior expectations.
  • Current evaluations of the neural code for perception prioritize faithful sensory representation over optimal inference.
  • This conventional approach leads to biases in neural code assessment, favoring discriminability and efficiency over generalizability and robustness.

Purpose of the Study:

  • To propose a framework for evaluating the neural code of perception based on its capacity for perceptual inference.
  • To highlight the misalignment between the computational goal of perception and conventional methods of neural code assessment.

Main Methods:

  • This is a review article, synthesizing existing literature and theoretical concepts.
  • It proposes a conceptual shift in evaluating neural codes for perception.

Main Results:

  • Conventional evaluation metrics for neural codes are misaligned with the inferential nature of perception.
  • A new evaluation framework focusing on perceptual inference can address current biases.

Conclusions:

  • Re-evaluating the neural code for perception through the lens of inference is crucial.
  • This shift will lead to a more accurate understanding of neural mechanisms underlying perception and improve computational models.