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

High-Level and Low-Level Awareness01:19

High-Level and Low-Level Awareness

Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
Subconsciousness and No Awareness01:15

Subconsciousness and No Awareness

The concept of subconscious awareness refers to the processing of information below the level of conscious thought, which significantly influences both behaviors and decisions. It is also known as waking subconscious awareness. This complex level of cognition operates without the direct awareness of the individual, facilitating rapid and simultaneous handling of multiple information streams.
An illustrative example of subconscious processing is its role in problem-solving. Often, individuals...

You might also read

Related Articles

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

Sort by
Same author

Stress-Lensed Electrochemical Sintering Enables Fast and Stable Lithium-Silicon Alloy Chemistry in All-Solid-State Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

DEEP-GYRALNET: ENABLING MACHINE LEARNING IN GYRAL FOLDING PATTERN EXTRACTION ON CORTICAL SURFACE.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same author

LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Breathing New Life into Small Object Detection with Detection-Oriented Rectification.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction.

Science advances·2026
Same author

Community-level modeling of gyral folding patterns for robust and anatomically informed individualized brain mapping.

NeuroImage·2026

Related Experiment Video

Updated: May 15, 2026

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies
10:09

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

Published on: September 22, 2014

Characterization of task-free/task-performance brain states.

Xin Zhang1, Lei Guo, Xiang Li

  • 1School of Automation, Northwestern Polytechnical University, Xi'an, China.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|January 5, 2013
PubMed
Summary

This study introduces a new method to distinguish brain states using functional connectivity patterns. It found that while resting-state fMRI and task-based fMRI patterns differ, some overlap suggests subjects may not be in their intended states.

More Related Videos

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
10:33

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis

Published on: June 20, 2012

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen
07:52

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen

Published on: October 5, 2020

Related Experiment Videos

Last Updated: May 15, 2026

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies
10:09

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

Published on: September 22, 2014

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
10:33

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis

Published on: June 20, 2012

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen
07:52

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen

Published on: October 5, 2020

Area of Science:

  • Neuroscience
  • Brain Imaging
  • Functional Connectivity

Background:

  • Resting-state fMRI (R-fMRI) and task-based fMRI (T-fMRI) are used to study brain activity during rest and tasks.
  • Challenges exist in ensuring subjects are truly in task-free or task-performance states during scans.
  • Accurate characterization of brain states is crucial for reliable fMRI research.

Purpose of the Study:

  • To develop a novel approach for differentiating task-free and task-performance brain states.
  • To identify distinct functional connectivity patterns associated with each state.
  • To assess the reliability of R-fMRI and T-fMRI in reflecting intended cognitive states.

Main Methods:

  • Utilized whole-brain quasi-stable connectivity patterns (WQCP) to represent brain functional states.
  • Applied sparse coding to learn atomic connectivity patterns (ACP) from R-fMRI and T-fMRI training data.
  • Compared learned ACPs between resting-state and task-based fMRI datasets.

Main Results:

  • Learned ACPs for R-fMRI and T-fMRI datasets were substantially different, as hypothesized.
  • A notable overlap in ACPs was observed between R-fMRI and T-fMRI datasets.
  • This overlap indicates potential deviations from intended task-free or task-performance states during scans.

Conclusions:

  • The novel approach effectively distinguishes between task-free and task-performance brain states based on connectivity patterns.
  • Overlapping ACPs suggest that subjects' mental states during fMRI scans may not always align with experimental conditions.
  • This finding highlights the need for improved methods to verify cognitive states during fMRI acquisition.