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

68
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....
68
Modeling in Therapy01:26

Modeling in Therapy

86
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...
86
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K

You might also read

Related Articles

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

Sort by
Same author

PSMA PET/CT-Targeted Biopsy in Men with Negative or Equivocal Multiparametric MRI and Exploratory Dynamic Total-Body PET: The FUPERMAN Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine·2026
Same author

The Copetti Sign in Suspected Renal Colic: Association with Distal Ureteral Stones in a Prospective Pilot Cohort.

Healthcare (Basel, Switzerland)·2026
Same author

Tailoring the right "MIST" for the right patient.

Minerva urology and nephrology·2026
Same author

Enhancing ARPI therapy in HSPC: who, when and why?

Minerva urology and nephrology·2026
Same author

Amoxicillin bone penetration in patients with medication-related osteonecrosis of the jaw: A preliminary study.

International journal of antimicrobial agents·2026
Same author

Study design and rationale of the Visualizing Subclinical Myocardial Changes with Shear Wave Elastography in Dilated Cardiomyopathy (VISUALIZE-DCM) trial.

European heart journal. Imaging methods and practice·2026

Related Experiment Video

Updated: Jul 8, 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

10.4K

Rethinking Theta/Beta Ratio in ADHD through Functional Data Analysis.

Lorenzo Bianchi, Erica Espinosa, Jacopo Lazzari

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel Functional Data Analysis method for ADHD diagnosis, achieving 76.65% accuracy. The approach uses electroencephalography (EEG) data to objectively differentiate between neurotypical and ADHD individuals.

    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

    15.7K
    Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
    12:21

    Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

    Published on: September 12, 2011

    25.2K

    Related Experiment Videos

    Last Updated: Jul 8, 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

    10.4K
    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

    15.7K
    Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
    12:21

    Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

    Published on: September 12, 2011

    25.2K

    Area of Science:

    • Neuroscience
    • Biostatistics
    • Medical Technology

    Background:

    • Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder.
    • Current ADHD diagnosis relies on clinical criteria (e.g., DSM-5) and lacks objective biomarkers.
    • Existing electroencephalography (EEG) methods, like the Theta-Beta Ratio, are insufficient for reliable ADHD diagnosis.

    Purpose of the Study:

    • To develop and validate a new objective methodology for classifying neurotypical and ADHD subjects.
    • To explore the utility of Functional Data Analysis (FDA) for analyzing EEG signals in ADHD.
    • To identify statistically significant EEG features for ADHD detection.

    Main Methods:

    • EEG signals were decomposed into frequency bands using wavelet decomposition.
    • Power Spectral Densities (PSDs) of each band were computed and represented as functions via spline interpolation.
    • Permutation ANOVA was used to assess feature relevance, followed by classification using Bagging trees, Random Forest, and AdaBoost.

    Main Results:

    • The FDA method successfully identified distinct patterns in PSDs between neurotypical and ADHD groups.
    • Statistically significant features were confirmed, aligning with existing literature.
    • AdaBoost classification achieved the highest accuracy of 76.65%.

    Conclusions:

    • The proposed Functional Data Analysis methodology offers a promising objective approach for ADHD classification.
    • Extracted EEG features demonstrate relevance for differentiating ADHD from neurotypical individuals.
    • This method has the potential to improve ADHD diagnosis accuracy.