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

Neuroplasticity

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

You might also read

Related Articles

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

Sort by

Same author

Nightly variations in sleep quality and next-day cognitive performance: an in-home study in healthy older adults.

Frontiers in aging neuroscience·2026

Same author

Modulating sleep: slow oscillation and spindle stimulation effects on physiology and memory.

NPJ science of learning·2026

Same author

The effectiveness of auditory stimulation in sleep varies with thalamocortical spindle phase.

NeuroImage·2025

Same author

Exploring Deep Magnetoencephalography via Thalamo-Cortical Sleep Spindles.

Human brain mapping·2025

Same author

Neurophysiological effects of targeting sleep spindles with closed-loop auditory stimulation.

Sleep advances : a journal of the Sleep Research Society·2025

Same author

Sleep State Influences Early Sound Encoding at Cortical But Not Subcortical Levels.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2025

Same journal

The causal efficacy of consciousness: a neuroscientific analysis and explanation.

Frontiers in human neuroscience·2026

Same journal

Temporal-oscillatory entrainment: a multi-timescale framework for rhythmic coordination from neural to social frequencies.

Frontiers in human neuroscience·2026

Same journal

Role of AQP4 in ameliorating heat stress-induced cellular injury in a cell line model through active heat acclimation.

Frontiers in human neuroscience·2026

Same journal

Correction: Cognitive state monitoring for neuroadaptive information visualization.

Frontiers in human neuroscience·2026

Same journal

The synthetic self-hypothesis: dopaminergic redirection through self-face recognition in stuttering therapy.

Frontiers in human neuroscience·2026

Same journal

A randomised, placebo-controlled, triple-blind clinical trial to investigate the efficacy of <i>Ginkgo biloba</i> extract EGb 761<sup>®</sup> in cognitive impairment associated with post COVID-19 syndrome-the EGb COCOS protocol.

Frontiers in human neuroscience·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 7, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Task decomposition: a framework for comparing diverse training models in human brain plasticity studies.

Emily B J Coffey¹, Sibylle C Herholz

¹Montreal Neurological Institute, McGill University Montreal, QC, Canada ; International Laboratory for Brain, Music and Sound Research, Université de Montreal Montreal, QC, Canada.

Frontiers in Human Neuroscience

|October 12, 2013

Summary

This summary is machine-generated.

Neuroplasticity research faces challenges comparing diverse training tasks. A new method deconstructs task requirements, aiding comparisons and guiding future brain plasticity study designs.

Keywords:

MRI expertise multisensory learning plasticity training

More Related Videos

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

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

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

Published on: September 22, 2014

Related Experiment Videos

Last Updated: May 7, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

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

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

Published on: September 22, 2014

Area of Science:

Neuroscience
Cognitive Science
Neuroimaging

Background:

Training studies compare neurophysiology before and after expertise acquisition to model brain reorganization.
Existing research struggles to link behavioral changes from task training to specific brain modifications due to diverse training paradigms.

Purpose of the Study:

To propose a novel method for characterizing and deconstructing complex training task requirements.
To facilitate meaningful comparisons between different training paradigms in neuroimaging studies.
To identify gaps in current training protocols and guide the design of future research.

Main Methods:

Developing a framework to analyze and break down the cognitive and motor demands of complex training tasks.
Applying this framework to structural and functional neuroimaging data from expertise acquisition studies.

Main Results:

The proposed method provides a systematic way to compare diverse training paradigms.
It aids in identifying specific cognitive and neural components underlying skill acquisition.
Facilitates the understanding of how task demands relate to observed brain changes.

Conclusions:

A standardized method for task deconstruction is crucial for advancing brain plasticity research.
This approach enhances the comparability of neuroimaging studies on learning and expertise.
It offers a roadmap for designing more targeted and effective training protocols to study brain reorganization.