Quantitative <scp>EEG</scp> Insights Into A Hundred Adult <scp>ADHD</scp> Patients: A Deep Dive Into Test of Variables of Attention (<scp>TOVA</scp>) Correlations and Attention Dynamics

The findings highlight that attention performance in ADHD is shaped by age, neuropsychological factors, and qEEG-measured brain activity. Higher attention scores correlate with better TOVA results, particularly in response time and error rates. Age-related declines in attention align with reductions in theta-to-beta and delta-to-beta ratios. Predictive modeling underscores the value of combining TOVA and qEEG to identify key predictors like response time variability, omission errors, and specific beta and delta activity. This integration enhances the evaluation of attention deficits and brain dynamics, benefiting both clinical and research applications.

Authors

Institutions

Publication Details

Journal
CNS Neuroscience & Therapeutics
Published
2025-03-01
DOI
https://doi.org/10.1111/cns.70304
Primary Topic
Attention Deficit Hyperactivity Disorder
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative EEG Insights Into A Hundred Adult ADHD Patients: A Deep Dive Into Test of Variables of Attention (TOVA) Correlations and Attention Dynamics

Elvan Çiftçi, Zeynep Betul
CNS Neuroscience & Therapeutics
Attention Deficit Hyperactivity Disorder
article

Quantitative EEG Insights Into A Hundred Adult ADHD Patients: A Deep Dive Into Test of Variables of Attention (TOVA) Correlations and Attention Dynamics

Elvan Çiftçi, Zeynep Betul
article en

Abstract

The findings highlight that attention performance in ADHD is shaped by age, neuropsychological factors, and qEEG-measured brain activity. Higher attention scores correlate with better TOVA results, particularly in response time and error rates. Age-related declines in attention align with reductions in theta-to-beta and delta-to-beta ratios. Predictive modeling underscores the value of combining TOVA and qEEG to identify key predictors like response time variability, omission errors, and specific beta and delta activity. This integration enhances the evaluation of attention deficits and brain dynamics, benefiting both clinical and research applications.

CNS Neuroscience & TherapeuticsVol. 31(3)
Üsküdar University (TR)
Openalex Percentile: Top 94%
Attention Deficit Hyperactivity Disorder
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantitative <scp>EEG</scp> Insights Into A Hundred Adult <scp>ADHD</scp> Patients: A Deep Dive Into Test of Variables of Attention (<scp>TOVA</scp>) Correlations and Attention Dynamics — Elvan Çiftçi, Zeynep Betul · CNS Neuroscience & Therapeutics (2025) | TGRS Research Map | TGRS