Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

High-Level and Low-Level Awareness

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...

Role of Cerebellum and Prefrontal Cortex in Memory

Role of Cerebellum and Prefrontal Cortex in Memory

The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...

Biological Influences on Intelligence

Biological Influences on Intelligence

Intelligence is often thought to be linked to brain size, but the relationship is more complex than that. While brain size does correlate modestly with some abilities, like verbal skills, the connection is weaker for others, such as spatial reasoning. Other factors, like brain structure, also play crucial roles. For instance, despite Einstein's smaller-than-average brain, his parietal cortex, which is involved in spatial reasoning, was 15% wider, suggesting that neural density might matter...

You might also read

Related Articles

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

Sort by

Same author

Neuromorphic hierarchical modular reservoirs.

Nature communications·2026

Same author

Replicability of multivariate brain-behaviour associations depends on clinical profile.

Communications biology·2026

Same author

Aging and metabolism contribute separately to brain-body health.

PLoS biology·2026

Same author

Symptom Dimension-Specific Neurotransmitter Correlates of Psychopathology and Cognition in Early Psychosis.

bioRxiv : the preprint server for biology·2026

Same author

Effectiveness and safety of hyperbaric oxygen therapy for psychiatric disorders: A systematic review and meta-analysis.

Psychiatry and clinical neurosciences·2026

Same author

Linking human brain functional connectivity to underlying neurotransmission.

bioRxiv : the preprint server for biology·2026

Search research articles

Related Experiment Video

Updated: Jun 4, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

The brain selectively allocates energy to functional brain networks under cognitive control.

Majid Saberi^1,2, Jenny R Rieck³, Shamim Golafshan⁴

¹Neurosciences & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada. majidsa@umich.edu.

Scientific Reports

|December 31, 2024

Summary

Brain network energy increases during cognitive control tasks. This elevated energy is selectively allocated to sensory networks, enhancing processing flexibility and improving predictive models for cognitive tasks and age.

Keywords:

Brain biomarker Canonical functional networks Cognitive control Executive functions Functional connectivity Network energy Predictive modeling Structural balance theory

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

Related Experiment Videos

Last Updated: Jun 4, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

Area of Science:

Neuroscience
Complex Systems Science
Cognitive Science

Background:

Network energy, derived from structural balance theory in complex networks, offers a novel framework for analyzing brain function.
Understanding how the brain allocates energy across functional networks during cognitive tasks is crucial for elucidating neural mechanisms.

Purpose of the Study:

To assess the energy of functional brain networks under cognitive control using the network energy framework.
To investigate the allocation of network energy across canonical functional networks during various cognitive control tasks.
To evaluate the utility of network energy as a global network measure for predictive modeling.

Main Methods:

Functional magnetic resonance imaging (fMRI) data were acquired from subjects performing cognitive tasks (working memory, inhibitory control, cognitive flexibility) and during a task-free resting state.
Network energy was extracted from functional connectivity patterns derived from fMRI data.
Network energy was employed as a global network measure to improve predictive modeling performance.

Main Results:

Whole-brain network energy significantly increased during cognitive control tasks compared to the task-free resting state.
Elevated network energy was selectively allocated; sensory networks received more energy for processing flexibility, while efficient cognitive networks required less.
Network energy improved the performance of predictive models for classifying cognitive control tasks and predicting chronological age.

Conclusions:

The network energy framework provides a robust method for quantifying brain network dynamics during cognitive control.
Network energy serves as a valuable global network measure, enhancing predictive modeling capabilities.
Network energy shows significant potential as a biomarker for understanding brain mechanisms and neurological conditions.