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Related Concept Videos

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.
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
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...
Somatosensory, Motor, and Association Cortex01:23

Somatosensory, Motor, and Association Cortex

The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at the...

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Related Experiment Video

Updated: May 17, 2026

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

Dynamic causal modelling of lateral interactions in the visual cortex.

D A Pinotsis1, D S Schwarzkopf1, V Litvak1

  • 1The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK.

Neuroimage
|November 7, 2012
PubMed
Summary

This study introduces a dynamic causal model using neural fields to estimate cortical macrocolumn width from non-invasive brain activity. Findings correlate macrocolumn size with peak gamma frequency in human visual cortex.

Keywords:
ConnectivityDynamic causal modellingElectrophysiologyMEGNeural field theoryVisual cortex

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Area of Science:

  • Computational neuroscience
  • Neuroimaging
  • Brain modeling

Background:

  • Dynamic Causal Modelling (DCM) traditionally uses neural mass models.
  • Neural field models offer a more detailed representation of cortical microcircuitry.
  • Non-invasive data analysis requires robust models for source activity mapping.

Purpose of the Study:

  • To develop and apply a dynamic causal model based on neural field models for analyzing non-invasive brain data.
  • To investigate the mapping from cortical surface activity to single-channel signals.
  • To estimate the spatial parameters, specifically the width, of cortical macrocolumns using electromagnetic signals.

Main Methods:

  • Utilized Amari-type neural field models incorporating canonical microcircuit (CMC) architecture with layered neuronal populations.
  • Employed dynamic causal modelling (DCM) to disambiguate between neural mass and neural field models.
  • Analyzed magnetoencephalography (MEG) data from human visual cortex, focusing on steady-state spectral activity.

Main Results:

  • Demonstrated that DCM with neural fields can address microcircuitry and lateral interactions, unlike neural mass models.
  • Successfully estimated the width of cortical macrocolumns using non-invasive electromagnetic signals.
  • Showed a correlation between estimated macrocolumn size and peak gamma frequency in the visual cortex.

Conclusions:

  • Neural field-based DCM provides quantitative characterization of spatially extended cortical dynamics.
  • Macrocolumnar width is a significant determinant of neuronal dynamics, including peak gamma frequency.
  • This approach offers insights into cortical micro-architecture and synaptic parameters from non-invasive measurements.