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

Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
Correlations02:20

Correlations

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
The Representativeness Heuristic02:13

The Representativeness Heuristic

The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
Correlation of Experimental Data01:23

Correlation of Experimental Data

Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity, and...

You might also read

Related Articles

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

Sort by
Same author

Proximity as a Ground-Truth Proxy for Training Texture Discrimination and Segmentation.

bioRxiv : the preprint server for biology·2026
Same author

Principles of Local and Global Grouping that Underlie Segmentation of Natural Texture Images.

bioRxiv : the preprint server for biology·2026
Same author

Integrating Machine Learning Interatomic Potentials with MMPBSA for Accurate Protein-Ligand Binding Free Energy Calculations.

The journal of physical chemistry. B·2026
Same author

Quantifying task-relevant representational similarity using decision variable correlation.

ArXiv·2026
Same author

Independent Encoding of Orientation and Mean Luminance by Mouse Visual Cortex.

eNeuro·2026
Same author

Elevated THOC5 expression in liver cancer and its implications for tumor progression and therapeutic response.

Frontiers in medicine·2025
Same journal

Distributionally Robust Feature Selection.

Advances in neural information processing systems·2026
Same journal

On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution.

Advances in neural information processing systems·2026
Same journal

Unlocking hidden biomolecular conformational landscapes in diffusion models at inference time.

Advances in neural information processing systems·2026
Same journal

JADE: Joint Alignment and Deep Embedding for Multi-Slice Spatial Transcriptomics.

Advances in neural information processing systems·2026
Same journal

Learning to Route: Per-Sample Adaptive Routing for Multimodal Multitask Prediction.

Advances in neural information processing systems·2026
Same journal

Emergence and Evolution of Interpretable Concepts in Diffusion Models.

Advances in neural information processing systems·2026
See all related articles

Related Experiment Video

Updated: May 26, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Quantifying Task-relevant Similarities in Representations Using Decision Variable Correlations.

Yu Eric Qian1, Wilson S Geisler2, Xue-Xin Wei1

  • 1Department of Neuroscience, The University of Texas at Austin.

Advances in Neural Information Processing Systems
|May 25, 2026
PubMed
Summary
This summary is machine-generated.

We introduce decision variable correlation (DVC) to compare how brains and AI models make decisions. AI models show similar internal decision strategies to each other but diverge from monkey brain activity.

More Related Videos

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

Related Experiment Videos

Last Updated: May 26, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Computer Vision

Background:

  • Previous research has explored similarities between neural activity in the visual cortex and deep neural networks (DNNs).
  • Existing studies present conflicting findings regarding the degree of representational similarity between biological vision and DNNs.
  • A need exists for methods that specifically assess task-relevant decision strategies, not just general representational alignment.

Purpose of the Study:

  • To introduce and validate a novel metric, decision variable correlation (DVC), for comparing decision strategies between observers (brains or models).
  • To investigate the task-relevant representational similarity between monkey visual cortex (V4/IT) and DNNs trained for image classification.
  • To assess how factors like network performance, adversarial training, and dataset size affect this similarity.

Main Methods:

  • Developed decision variable correlation (DVC) to quantify image-by-image correlation of decoded decisions from internal representations.
  • Collected neural recordings from monkey V4/IT during a classification task.
  • Utilized various deep neural network models trained on image classification tasks, including those with adversarial training and large-scale pre-training.

Main Results:

  • Model-model and monkey-monkey decision strategy similarities were comparable.
  • Model-monkey decision strategy similarity was consistently lower than both model-model and monkey-monkey similarities.
  • Decision variable correlation (DVC) decreased as network performance on ImageNet-1k increased.
  • Adversarial training and large-scale pre-training did not enhance model-monkey similarity in task-relevant dimensions.

Conclusions:

  • Decision variable correlation (DVC) effectively captures task-relevant information, offering a new perspective on comparing decision strategies.
  • Task-relevant representations in monkey V4/IT diverge from those learned by standard image classification DNNs.
  • Current training paradigms for DNNs do not fully bridge the gap in decision-making strategies compared to biological visual systems.