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

Biological Influences on Intelligence01:30

Biological Influences on Intelligence

272
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...
272
Measures of Intelligence01:29

Measures of Intelligence

7.9K
Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
7.9K
Binet's Contribution to Measures of Intelligence01:23

Binet's Contribution to Measures of Intelligence

1.4K
Alfred Binet, along with his student Théophile Simon, was tasked by the French Ministry of Education in 1904 to create a method for identifying students who struggled to learn through conventional classroom instruction. This initiative aimed to address overcrowding by placing such students in specialized schools. Binet and Simon developed an intelligence test comprising 30 tasks, ranging from simple commands, like touching one's nose or ear, to more complex tasks, such as drawing...
1.4K
Brain Imaging01:14

Brain Imaging

400
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...
400
Environmental Influences on Intelligence01:29

Environmental Influences on Intelligence

510
Despite the strong genetic influence on traits like intelligence, environmental factors significantly shape outcomes. For example, while over 90% of height variation is due to genetic differences, environmental factors such as nutrition also have a notable impact. Similarly, for intelligence, changes in a child's surroundings can significantly alter their IQ. Research shows that enriched environments boost children's academic success and help them develop key cognitive skills. Children...
510
Triarchic Theory of Intelligence01:24

Triarchic Theory of Intelligence

9.1K
Robert Sternberg's triarchic theory of intelligence posits that intelligence is composed of three distinct but interrelated components: analytical, creative, and practical intelligence.
9.1K

You might also read

Related Articles

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

Sort by
Same author

Effects of <i>Lactobacillus plantarum</i> P9 Probiotics on Defecation and Quality of Life of Individuals with Chronic Constipation: Protocol for a Randomized, Double-Blind, Placebo-Controlled Clinical Trial.

Evidence-based complementary and alternative medicine : eCAM·2022
Same author

Super-taxon in human microbiome are identified to be associated with colorectal cancer.

BMC bioinformatics·2022
Same author

Pre-IVF treatment with a GnRH antagonist in women with endometriosis (PREGNANT): study protocol for a prospective, double-blind, placebo-controlled trial.

BMJ open·2022
Same author

Comparative genomic analysis revealed genetic divergence between Bifidobacterium catenulatum subspecies present in infant versus adult guts.

BMC microbiology·2022
Same author

Probiotics synergized with conventional regimen in managing Parkinson's disease.

NPJ Parkinson's disease·2022
Same author

Protocol of a randomized, double-blind, placebo-controlled study of the effect of probiotics on the gut microbiome of patients with gastro-oesophageal reflux disease treated with rabeprazole.

BMC gastroenterology·2022

Related Experiment Video

Updated: Oct 19, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.0K

TENSOR QUANTILE REGRESSION WITH APPLICATION TO ASSOCIATION BETWEEN NEUROIMAGES AND HUMAN INTELLIGENCE.

B Y Cai Li1, Heping Zhang1

  • 1Department of Biostatistics, Yale University.

The Annals of Applied Statistics
|September 27, 2021
PubMed
Summary

This study introduces a robust tensor quantile regression model for analyzing human intelligence using magnetic resonance imaging (MRI) data. The method identifies brain regions linked to cognitive abilities and can predict cognitive impairment risk.

Keywords:
Brain imagingconditional quantilefluid intelligencegeneralized Lasso regularizationpiece-wise smoothnesstensor regression

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.9K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.6K

Related Experiment Videos

Last Updated: Oct 19, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.0K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.9K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.6K

Area of Science:

  • Neuroscience
  • Biostatistics
  • Medical Imaging

Background:

  • Human intelligence is typically measured using psychometric tests, yielding continuous, often non-normally distributed cognitive scores.
  • Magnetic resonance imaging (MRI) offers detailed insights into brain structure and its relationship with cognitive abilities.
  • Existing linear regression models for scalar-on-image analysis may be sensitive to outliers and normality assumption violations in cognitive data.

Purpose of the Study:

  • To propose a robust tensor quantile regression model as an alternative to traditional scalar-on-image linear regression for intelligence studies.
  • To incorporate spatial information from brain structures using low-rankness and piece-wise smoothness within a regularized regression framework.
  • To identify specific brain subregions associated with different quantiles of human intelligence.

Main Methods:

  • Developed a tensor quantile regression model to handle non-normal, heavy-tailed cognitive scores.
  • Incorporated spatial information of brain structures via tensor decomposition and a generalized Lasso penalty.
  • Employed an efficient alternating direction method of multipliers (ADMM) algorithm for model component estimation.

Main Results:

  • The tensor quantile regression model demonstrated robust performance in numerical studies.
  • Application to the Human Connectome Project data revealed prognostic value for cognitive impairment risk.
  • Identified specific brain regions associated with quantiles of fluid intelligence, including prefrontal cortex, anterior cingulate cortex, and insular cortex.

Conclusions:

  • Tensor quantile regression provides a powerful and flexible tool for neuroimaging studies of human intelligence.
  • The model can serve as a prognostic indicator for cognitive decline.
  • This approach successfully maps distinct brain regions to specific levels of fluid intelligence, offering novel insights into cognitive neuroscience.