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

Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Cerebellum: Anatomical Regions01:17

Cerebellum: Anatomical Regions

The cerebellum, also known as the "little brain," is located in the posterior cranial fossa, inferior to the tentorium cerebelli and dorsal to the brainstem. It plays a significant role in motor control, coordination, and proprioception.
Cerebellar Structure
Externally, the cerebellum features a highly convoluted surface with numerous folia (narrow ridges) separated by shallow sulci (grooves). The cerebellum is divided into two hemispheres by a thin median structure known as the vermis. The...
Cerebrospinal Fluid01:21

Cerebrospinal Fluid

Cerebrospinal fluid (CSF) is a colorless liquid that flows around the brain and the spinal cord, playing a vital role in the protection, support, and overall function of the central nervous system (CNS). CSF production, circulation, and absorption are tightly regulated processes essential for the brain and spinal cord to function properly.
CSF Production
CSF is produced mainly in the choroid plexus, a network of capillaries and ependymal cells located within the ventricular system of the brain.
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's proficiency in drug...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

You might also read

Related Articles

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

Sort by
Same author

Comparison of safety and feasibility of on-clamp versus off-clamp robotic partial nephrectomy.

Urologia·2026
Same author

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same author

Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Specific metabolic rate and body weight regulation: racial and ethnic differences in mass-independent energy expenditure.

Journal of endocrinological investigation·2026
Same author

Serum as an alternative to plasma for determining the ApoE4 phenotype using Pan-ApoE and ApoE4 chemiluminescent enzyme immunoassays.

Clinical chemistry and laboratory medicine·2026
Same author

From 'senile dementia' to NOVAS: the evolution of dementia classification.

Brain : a journal of neurology·2026

Related Experiment Video

Updated: May 12, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K

Cerebellocerebral connectivity predicts body mass index: a new open-source Python-based framework for

Tobias Bachmann1, Karsten Mueller2,3, Simon N A Kusnezow4

  • 1Department of Neurology, University of Leipzig Medical Center, Leipzig 04103, Germany.

Gigascience
|March 12, 2025
PubMed
Summary
This summary is machine-generated.

Obesity alters cerebellocerebral connectivity, impacting cognitive functions. Task-related brain network changes predict body mass index (BMI), suggesting a neurobiological basis for obesity-related cognitive deficits.

Keywords:
BMIHuman Connectome Project (HCP)Pythoncerebellumconnectome-based predictive modelingfunctional magnetic resonance imaging (fMRI)

More Related Videos

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
11:50

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Published on: February 4, 2022

3.9K
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

967

Related Experiment Videos

Last Updated: May 12, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K
A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
11:50

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Published on: February 4, 2022

3.9K
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

967

Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Obesity Research

Background:

  • The cerebellum, a key brain structure, shows alterations in obesity.
  • Obesity affects higher cognitive functions, involving cerebellocerebral pathways.
  • Investigating the link between body mass index (BMI) and cerebellocerebral connectivity is crucial.

Purpose of the Study:

  • To explore the relationship between body mass index (BMI) and cerebellocerebral connectivity.
  • To identify specific brain networks associated with BMI.
  • To understand the neurobiological underpinnings of obesity-related cognitive impairments.

Main Methods:

  • Utilized the Human Connectome Project dataset (fMRI, behavioral data).
  • Employed connectome-based predictive modeling (CPM) for cerebellocerebral connectivity.
  • Developed an open-source Python framework for data-driven analysis with cross-validation.

Main Results:

  • Cerebellocerebral connectivity significantly predicted BMI.
  • Task-general connectivity was a more reliable BMI predictor than resting-state or individual task fMRI.
  • Predictive networks overlapped with frontoparietal, somatomotor, salience, and default mode networks.
  • An inverse overlap was observed between BMI-predictive and cognition-predictive networks.

Conclusions:

  • Obesity is associated with specific alterations in cerebellocerebral connectivity, particularly during task execution.
  • These alterations implicate brain networks vital for task performance.
  • Findings suggest a neurobiological basis for how obesity adversely affects cognitive task performance.