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

Functions of Connective Tissues01:17

Functions of Connective Tissues

16.9K
Connective tissues perform a broad range of functions in the body. Their primary function is to connect and link different tissues in the body and act as packaging material between tissues. The areolar tissue, a connective tissue prototype, commonly cements various tissue types in diverse body organs. In contrast, adipose tissue cushions internal organs while insulating the body from heat loss.
Hard connective tissues, such as bones and cartilage, provide structure and support to the body.
16.9K
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

2.1K
Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
2.1K
Machines01:19

Machines

581
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
581
Machines: Problem Solving II01:30

Machines: Problem Solving II

673
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
673
Dietary Connections01:23

Dietary Connections

62.1K
In biological systems, most metabolic pathways are interconnected. The cellular respiration processes that convert glucose to ATP—such as glycolysis, pyruvate oxidation, and the citric acid cycle—tie into those that break down other organic compounds. As a result, various foods—from apples to cheese to guacamole—end up as ATP. In addition to carbohydrates, food also contains proteins and lipids—such as cholesterol and fats. All of these organic compounds are used...
62.1K
Machines: Problem Solving I01:22

Machines: Problem Solving I

717
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
717

You might also read

Related Articles

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

Sort by
Same author

[Big data approaches in psychiatry: examples in depression research].

Der Nervenarzt·2017
Same author

True and false splenic artery aneurysm on endoscopic ultrasonography: Two-case analysis.

Endoscopic ultrasound·2015
Same author

Co-activation based parcellation of the human frontal pole.

NeuroImage·2015
Same author

The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis.

Brain structure & function·2014
Same author

ALE meta-analysis on facial judgments of trustworthiness and attractiveness.

Brain structure & function·2010
Same author

Enhanced soluble interleukin-5 receptor alpha expression in nasal polyposis.

Allergy·2003

Related Experiment Video

Updated: Feb 7, 2026

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K

GraphVar 2.0: A user-friendly toolbox for machine learning on functional connectivity measures.

L Waller1, A Brovkin2, L Dorfschmidt2

  • 1Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Germany.

Journal of Neuroscience Methods
|July 21, 2018
PubMed
Summary
This summary is machine-generated.

GraphVar 2.0 enhances functional brain connectivity analysis with customizable machine learning models. This user-friendly toolbox makes complex neuroimaging data accessible for broader research applications.

Keywords:
Computational neuroscienceDecodingElastic netEncodingFunctional connectivityGraph theoryLinear SVMATLABMachine learningModel performanceNested Cross validationPrecision psychiatryReproducibilityToolbox

More Related Videos

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

379
High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
08:39

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

Published on: July 8, 2014

25.9K

Related Experiment Videos

Last Updated: Feb 7, 2026

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K
A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

379
High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
08:39

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

Published on: July 8, 2014

25.9K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Brain Connectivity Analysis

Background:

  • GraphVar, a MATLAB toolbox, previously offered graph analyses for functional brain connectivity.
  • This work introduces GraphVar 2.0, an extension with advanced decoding model capabilities.

Purpose of the Study:

  • To introduce GraphVar 2.0, an extension for comprehensive functional brain connectivity analysis.
  • To enable customizable machine learning model exploration across various connectivity measures and variables.

Main Methods:

  • GraphVar 2.0 integrates machine learning (ML) for model construction, validation, and exploration.
  • It supports customizable ML across graph measures, connectivity matrices, and imported variables, alongside parametric/nonparametric testing.

Main Results:

  • The extension provides flexible ML across diverse neuroimaging data.
  • Features include network construction, graph-theoretical analyses, GLM, and customizable ML model building.

Conclusions:

  • GraphVar 2.0 offers a user-friendly, all-in-one interface for encoding and decoding models.
  • It enhances accessibility to big data neuroscience for a wider range of investigators.