Jove
Visualize
Contact Us
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 Concept Videos

Multicompartment Models: Overview01:14

Multicompartment Models: Overview

290
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
290

You might also read

Related Articles

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

Sort by
Same author

Multifocal Noninvasive Deep Brain Stimulation to Enhance Cognition in Mild Cognitive Impairment: A Crossover Trial.

JAMA network open·2026
Same author

Transcranial Temporal Interference Stimulation: A Brief Review of Architectures, Circuits, and Application Challenges.

IEEE open journal of engineering in medicine and biology·2026
Same author

Generalisation of training-induced recovery in occipital stroke: neurochemical and fMRI correlates.

bioRxiv : the preprint server for biology·2026
Same author

Real-time reinforcement for human-machine interface control.

Neuron·2026
Same author

Temporal interference stimulation for deep brain neuromodulation in humans.

Nature biomedical engineering·2026
Same author

A novel multidimensional dynamic difficulty adjustment algorithm: Use case in a cognitive training video game.

Psychological methods·2026

Related Experiment Video

Updated: Oct 11, 2025

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

9.6K

Functional segregation within the dorsal frontoparietal network: a multimodal dynamic causal modeling study.

Estelle Raffin1,2, Adrien Witon1,2,3, Roberto F Salamanca-Giron1,2

  • 1Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, EPFL, Geneva CH-1201, Switzerland.

Cerebral Cortex (New York, N.Y. : 1991)
|December 5, 2021
PubMed
Summary

Brain networks for motion discrimination involve different areas based on task demands and decision-making. Lower visual areas handle initial processing, while higher areas integrate information for complex perceptual decisions.

Keywords:
Dynamic Causal Modelingelectroencephalographyfunctional magnetic resonance imagingmotion discriminationmultimodal neuroimaging

More Related Videos

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.4K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.2K

Related Experiment Videos

Last Updated: Oct 11, 2025

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

9.6K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.4K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.2K

Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Visual Perception

Background:

  • Motion direction discrimination involves complex brain interactions.
  • Stimulus-driven (exogenous) and decision-driven (endogenous) factors influence visual processing at various hierarchical levels.

Purpose of the Study:

  • To investigate how task demand and perceptual decision-making modulate neural activity in the motion discrimination network.
  • To differentiate the roles of lower and higher visual areas in processing motion direction.

Main Methods:

  • Utilized electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) in healthy participants performing a motion discrimination task.
  • Applied Dynamic Causal Modeling (DCM) to EEG (DCM-ERP) and fMRI (DCM-fMRI) data to model effective connectivity.
  • Independently modeled the impact of exogenous (task demand) and endogenous (perceptual decision-making) factors.

Main Results:

  • Task demand influenced connections between early visual areas (V1) and motion-sensitive areas (V5).
  • With practice, higher visual areas became more involved, as shown by DCM-fMRI.
  • Perceptual decision-making modulated higher-level areas (e.g., V5 to Frontal Eye Fields), correlating with task performance.

Conclusions:

  • Lower visual network levels support early, feature-based response selection, particularly before learning strategies are established.
  • Perceptual decision-making operates at higher visual hierarchy levels, integrating sensory input with the subject's internal state.