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

Modeling in Therapy01:26

Modeling in Therapy

139
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
139

You might also read

Related Articles

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

Sort by
Same author

The interplay between selective attention and summary statistics.

The Behavioral and brain sciences·2025
Same author

A selective sampling account of forming numerosity representations.

Psychological review·2025
Same author

Using diffusion models for symbolic numeracy tasks to examine aging effects.

Journal of experimental psychology. Learning, memory, and cognition·2024
Same author

Beyond discrete-choice options.

Trends in cognitive sciences·2024
Same author

Parsing memory and nonmemory contributions to age-related declines in mnemonic discrimination performance: a hierarchical Bayesian diffusion decision modeling approach.

Learning & memory (Cold Spring Harbor, N.Y.)·2023
Same author

Reexamining the effects of speed-accuracy instructions with a diffusion-model-based analysis.

Journal of experimental psychology. Learning, memory, and cognition·2023
Same journal

What can we learn from studying replay in humans?

Trends in cognitive sciences·2026
Same journal

Rethinking reciprocity.

Trends in cognitive sciences·2026
Same journal

Misinformation as strategy: Epistemic consequences and the undermining of shared truth.

Trends in cognitive sciences·2026
Same journal

Geographical psychology: Spatial variation in psychological phenomena and their consequences.

Trends in cognitive sciences·2026
Same journal

Multi-brain neurofeedback: what are we training for?

Trends in cognitive sciences·2026
Same journal

The developing vocal self.

Trends in cognitive sciences·2026
See all related articles

Related Experiment Video

Updated: Aug 27, 2025

Assessment of Spontaneous Alternation, Novel Object Recognition and Limb Clasping in Transgenic Mouse Models of Amyloid-β and Tau Neuropathology
10:02

Assessment of Spontaneous Alternation, Novel Object Recognition and Limb Clasping in Transgenic Mouse Models of Amyloid-β and Tau Neuropathology

Published on: May 28, 2017

27.0K

Can neuropsychological testing be improved with model-based approaches?

Roger Ratcliff1, Gail McKoon1

  • 1The Ohio State University, Columbus, OH, USA.

Trends in Cognitive Sciences
|September 24, 2022
PubMed
Summary
This summary is machine-generated.

Cognitive psychology and computational modeling offer limited insights into current neuropsychological tests. Bridging this gap can significantly advance assessment methods and understanding of cognitive constructs.

Keywords:
cognitive modelingneuropsychological testingresponse time

More Related Videos

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

58.1K
Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage
06:46

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage

Published on: August 4, 2018

12.3K

Related Experiment Videos

Last Updated: Aug 27, 2025

Assessment of Spontaneous Alternation, Novel Object Recognition and Limb Clasping in Transgenic Mouse Models of Amyloid-β and Tau Neuropathology
10:02

Assessment of Spontaneous Alternation, Novel Object Recognition and Limb Clasping in Transgenic Mouse Models of Amyloid-β and Tau Neuropathology

Published on: May 28, 2017

27.0K
The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

58.1K
Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage
06:46

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage

Published on: August 4, 2018

12.3K

Area of Science:

  • Neuropsychology
  • Cognitive Psychology
  • Computational Modeling

Background:

  • Neuropsychological testing has seen minimal influence from cognitive psychology and computational modeling for over five decades.
  • A significant disconnect exists between the aims of neuropsychological tests and the cognitive constructs they purport to measure.

Purpose of the Study:

  • To highlight the underutilization of cognitive psychology and modeling in neuropsychological assessment.
  • To discuss research at the intersection of testing and modeling.
  • To illustrate opportunities for advancing neuropsychological evaluation.

Main Methods:

  • Review of studies examining the integration of cognitive psychology principles and computational modeling within neuropsychological testing paradigms.
  • Analysis of the relationship between established neuropsychological tests and the underlying cognitive constructs.

Main Results:

  • Identified a persistent gap between cognitive psychological theory, computational modeling, and current neuropsychological assessment practices.
  • Demonstrated through case studies the potential for modeling to refine and validate neuropsychological measures.
  • Highlighted specific research areas where synergy between testing and modeling can yield significant advancements.

Conclusions:

  • Integrating cognitive psychology and computational modeling into neuropsychological testing offers substantial potential for improvement.
  • Addressing the disconnect between tests and constructs is crucial for enhancing the validity and utility of neuropsychological assessments.
  • Future research should focus on developing and validating tests informed by cognitive theory and computational approaches.