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

Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

558
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
558
Cognitive Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists01:30

Cognitive Enhancers: Cholinesterase Inhibitors and NMDA Receptor Antagonists

354
Cognitive enhancers, also known as "smart drugs," are substances used to enhance memory, mental alertness, and concentration. These can be natural or synthetic and improve cognition in conditions like Alzheimer's disease (AD) and other neurodegenerative diseases. Some common examples include caffeine, amphetamines, methylphenidate, modafinil, arecoline, donepezil, vortioxetine, and piracetam. These enhancers work on the principle of synaptic plasticity and altered circuit function.
354

You might also read

Related Articles

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

Sort by
Same author

Kynurenine metabolites unchanged after multinutrient supplementation in children with ADHD: a secondary data analysis from the MADDY study.

Journal of neural transmission (Vienna, Austria : 1996)·2026
Same author

The interplay between selective attention and summary statistics.

The Behavioral and brain sciences·2025
Same author

From symptom-based heterogeneity to mechanism-based profiling in youth ADHD: the promise of computational psychiatry.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2025
Same author

A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty.

bioRxiv : the preprint server for biology·2025
Same author

A selective sampling account of forming numerosity representations.

Psychological review·2025
Same author

Gut microbiome changes with micronutrient supplementation in children with attention-deficit/hyperactivity disorder: the MADDY study.

Gut microbes·2025

Related Experiment Video

Updated: Nov 24, 2025

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol
13:09

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol

Published on: April 1, 2018

10.6K

Improving neurocognitive testing using computational psychiatry-A systematic review for ADHD.

Nadja R Ging-Jehli1, Roger Ratcliff1, L Eugene Arnold2

  • 1Department of Psychology, The Ohio State University.

Psychological Bulletin
|December 28, 2020
PubMed
Summary

Computational models enhance understanding of attention-deficit/hyperactivity disorder (ADHD) cognitive traits. Integrating these models with neurophysiological measures reveals ADHD endophenotype characteristics, improving research and clinical tools.

More Related Videos

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD
10:02

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

16.3K
The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

6.1K

Related Experiment Videos

Last Updated: Nov 24, 2025

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol
13:09

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol

Published on: April 1, 2018

10.6K
Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD
10:02

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

16.3K
The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

6.1K

Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Psychiatry

Background:

  • Computational models and cognitive tests are vital for understanding attention-deficit/hyperactivity disorder (ADHD).
  • Existing research often struggles to capture subtle cognitive differences in ADHD endophenotypes due to test sensitivity and analysis limitations.

Purpose of the Study:

  • To synthesize findings from 50 studies using computational models and cognitive tests for ADHD.
  • To summarize insights from diffusion decision, absolute accumulator, and ex-Gaussian models in ADHD research.
  • To identify areas for improving cognitive testing utility in ADHD research.

Main Methods:

  • Systematic review of 50 studies on cognitive tests and computational models for ADHD.
  • Analysis of diffusion decision models, absolute accumulator models, and ex-Gaussian distribution models.
  • Discussion of sample characteristics, neurophysiological measures, and cognitive psychology integration.

Main Results:

  • Computational models refine understanding of ADHD cognitive concepts like processing speed and inhibition.
  • Integrating computational models with sample characteristics and neurophysiological data supports ADHD endophenotype-specific cognitive traits.
  • Current methods often lack sensitivity to detect subtle cognitive differences in ADHD.

Conclusions:

  • Recommendations are provided for cognitive testing, computational modeling, and electrophysiological measures.
  • Enhanced tools are proposed for ADHD research and clinical practice.
  • Further research should address limitations in test sensitivity and analysis methods for ADHD endophenotypes.