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

Biological Clocks and Seasonal Responses

Biological Clocks and Seasonal Responses

The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.

You might also read

Related Articles

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

Sort by

Same author

Home-Court Advantage and the Associations of Travel and Jet Lag with Team Performance in the Women's National Basketball Association (WNBA).

Sports medicine - open·2026

Same author

The interactions between sleep difficulties and clinical features in children with rare genetic syndromes: a structural equation modelling approach.

BMC pediatrics·2026

Same author

Levelling up digital mental health: from proliferation to precision.

The British journal of psychiatry : the journal of mental science·2026

Same author

Optimizing Athlete Travel for Performance: A Scientific Blueprint for Athletes, Coaches, and Sports Medicine Staff.

Sports medicine (Auckland, N.Z.)·2026

Same author

The future of epilepsy care in the United Kingdom: A roadmap for technology-enabled transformation.

Epilepsia open·2026

Same author

A Digital Intervention for Capturing Real-Time Health Data for Epilepsy Seizure Forecasting: Protocol for the ATMOSPHERE Study.

JMIR research protocols·2026

Search research articles

Related Experiment Video

Updated: Jul 26, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World

Published on: April 7, 2020

Classification of human chronotype based on fMRI network-based statistics.

Sophie L Mason^1,2, Leandro Junges², Wessel Woldman²

¹School of Mathematics, College of Engineering and Physical Sciences, University of Birmingham, Birmingham, United Kingdom.

Frontiers in Neuroscience

|June 21, 2023

Summary

Chronotype, or an individual's internal body clock, influences brain networks. Extreme chronotypes show distinct functional brain network differences, impacting cognition and mental health.

Keywords:

chronotype (morningness-eveningness)classifier fMRI functional connectivity functional networks graph theory network-based statistical (NBS) analysis

More Related Videos

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

fMRI Validation of fNIRS Measurements During a Naturalistic Task

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

Related Experiment Videos

Last Updated: Jul 26, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World

Published on: April 7, 2020

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

fMRI Validation of fNIRS Measurements During a Naturalistic Task

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

Area of Science:

Neuroscience
Chronobiology
Cognitive Science

Background:

Chronotype, the alignment of internal circadian rhythms with the 24-hour light-dark cycle, is linked to mental health and cognitive function.
Late chronotypes are associated with higher depression risk and impaired cognitive performance during typical work hours.
The neural basis connecting circadian physiology, brain networks, cognition, and mental health remains unclear.

Purpose of the Study:

To investigate if functional brain networks contain information differentiable by chronotype.
To determine how chronotype-related brain network differences change throughout the day.
To explore the potential of brain network analysis for classifying extreme chronotypes.

Main Methods:

Utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 16 early and 22 late chronotype individuals.
Developed a classification framework using Network Based-Statistics (NBS) to analyze brain network differences.
Collected data across three scanning sessions to assess temporal changes.

Main Results:

Identified distinct subnetworks that differ between extreme chronotypes at various times of day.
Achieved high classification accuracy (97.3%) for distinguishing chronotypes in the evening.
Demonstrated that classification accuracy varies across scanning sessions, highlighting temporal dynamics.

Conclusions:

Functional brain network differences are associated with extreme chronotypes.
These findings suggest that chronotype is embedded within brain network organization.
Further research can elucidate the relationship between physiology, brain networks, and mental health conditions.