A comprehensive investigation into EEG spectral analysis for ADHD brain dominance

Vandana Joshi; Nirali Nanavati; Vandana Joshi; Nirali Nanavati

doi:10.3934/Neuroscience.2026017

AIMS Neuroscience

2026, Volume 13, Issue 3: 389-414. doi: 10.3934/Neuroscience.2026017

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Research article

A comprehensive investigation into EEG spectral analysis for ADHD brain dominance

Vandana Joshi ^,,
Nirali Nanavati

Computer Engineering Department, Sarvajanik College of Engineering & Technology, Surat, Gujarat, India

Received: 31 December 2025 Revised: 18 March 2026 Accepted: 31 March 2026 Published: 08 July 2026

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that significantly impacts the cognitive functions and behaviour of individuals. It is characterized by abnormal brain lateralization in key brain regions linked to attention and cognitive control. This study aimed to explore and analyze the brainwave patterns linked to left and right brain dominance in ADHD, ADHD subtype, and control group using electroencephalography (EEG) spectral features, which have not been investigated in prior studies. Our study examined variations in alpha, beta, theta, and other frequency bands between the brain's left and right hemispheres, employing methodologies like EEG recordings with topographical views and statistical tests. The Asymmetric Index findings suggest a differential power spectrum density (PSD) pattern in ADHD subjects, with a higher average PSD in the right brain (RB) during working states and in the left brain (LB) during resting states. In addition, our corroborative study also uncovered that in ADHD subjects, theta and alpha waves are more dominant in the left hemispheric region, irrespective of the task state, and theta waves are notably prominent in the frontal region. The results of our novel study, supported by statistical analyses and topographical views, not only enhance our understanding of ADHD but also open avenues for more targeted and effective approaches in diagnosing and understanding the neurobiological underpinnings of ADHD and its subtypes.
- attention deficit hyperactivity disorder (ADHD),
- electroencephalography (EEG), spectral analysis,
- brain dominance
Citation: Vandana Joshi, Nirali Nanavati. A comprehensive investigation into EEG spectral analysis for ADHD brain dominance[J]. AIMS Neuroscience, 2026, 13(3): 389-414. doi: 10.3934/Neuroscience.2026017

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Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that significantly impacts the cognitive functions and behaviour of individuals. It is characterized by abnormal brain lateralization in key brain regions linked to attention and cognitive control. This study aimed to explore and analyze the brainwave patterns linked to left and right brain dominance in ADHD, ADHD subtype, and control group using electroencephalography (EEG) spectral features, which have not been investigated in prior studies. Our study examined variations in alpha, beta, theta, and other frequency bands between the brain's left and right hemispheres, employing methodologies like EEG recordings with topographical views and statistical tests. The Asymmetric Index findings suggest a differential power spectrum density (PSD) pattern in ADHD subjects, with a higher average PSD in the right brain (RB) during working states and in the left brain (LB) during resting states. In addition, our corroborative study also uncovered that in ADHD subjects, theta and alpha waves are more dominant in the left hemispheric region, irrespective of the task state, and theta waves are notably prominent in the frontal region. The results of our novel study, supported by statistical analyses and topographical views, not only enhance our understanding of ADHD but also open avenues for more targeted and effective approaches in diagnosing and understanding the neurobiological underpinnings of ADHD and its subtypes.

Data availability statement

The data used in this research is publicly available on the following website:
• Dataset 1: https://doi.org/10.6084/m9.figshare.c.4933326
• Dataset 2: [49] Last Accessed Dec 2021
• Dataset 3: https://osf.io/4285y/
• Dataset 4: https://doi.org/10.6084/m9.figshare.c.4933326.v1
• Dataset 5: Last access Dec 2021: https://github.com/brainhack-school2020/ADHDsubtypes project OR https://github.com/brainhack-school2020/ADHDsubtypes project/tree/master.

Conflict of interest

The authors declare that they have no conflicts of interest.

Authors' contributions

Dr. Vandana Joshi: Led the conceptualization and methodology of the study. conducted the investigation, data curation, formal analysis, and prepared the original manuscript draft. Dr. Nirali Nanavati: Provided supervision and validation. contributed to the study methodology, critical review and editing and structuring of the manuscript. All authors read and approved the final manuscript.

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