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Neurology International
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The Evolving Role of EEG in Neurological Disorders: Advanced Techniques...
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The Evolving Role of EEG in Neurological Disorders: Advanced Techniques and Future Directions

A special issue of Neurology International (ISSN 2035-8377).

Deadline for manuscript submissions: 15 July 2026 | Viewed by 2677

Special Issue Editors

Dr. Angelica Quercia

E-Mail Website
Guest Editor
Clinical Neurophysiology Research Unit, IRCCS, Oasi Research Institute, 94018 Troina, Italy
Interests: HD-EEG; sleep physiology; neuroplasticity; TMS-EEG
Special Issues, Collections and Topics in MDPI journals
Dr. Irene Aricò

E-Mail Website
Guest Editor
Sleep Medicine Center, University Hospital "G. Martino", Messina, Italy
Interests: EEG; sleep medicine; epilepsy; neurological disorders; polysomnography; TMS

Special Issue Information

Dear Colleagues,

We invite you to submit your research work to our Special Issue, entitled “The Evolving Role of EEG in Neurological Disorders: Advanced Techniques and Future Directions”. While conventional EEG remains a pillar in clinical neurology, this Special Issue aims to explore and present the significant evolution of EEG methodologies and their growing impact on the diagnosis and treatment of neurological disorders. This Special Issue will primarily focus on the introduction of high-density EEG (HD-EEG) to investigate neurological dysfunction in clinical practice. Original research articles and comprehensive reviews that deepen the clinical applications of advanced EEG in specific neurological disorders (e.g., epilepsy, Alzheimer's disease, Parkinson's, stroke, and sleep disorders) are welcome as contributions. Moreover, in the clinical landscape, the role of combined techniques, particularly the integration of EEG with both neuroimaging and neurophysiological methods, is emerging with increasing prominence. Therefore, articles focusing on this topic will be highly welcomed for submission. Papers exploring machine learning approaches, emerging technologies, predictive modeling, and the translation of research findings into clinical practice are also appreciated. We look forward to receiving high-quality submissions that collectively illustrate the growing and expanding role of advanced EEG techniques in improving diagnostic accuracy and therapeutic outcomes for patients.

Dr. Angelica Quercia
Dr. Irene Aricò
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Neurology International is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • EEG
  • HD-EEG
  • neurological disorders
  • multimodal neurophysiology
  • translational research

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Published Papers (1 paper)

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13 pages, 1289 KB  
Article
Delta Power in SLC6A1-Related Neurodevelopmental Disorder: Operationalizing Quantitative EEG Metrics for Biomarker Development
by Hamza Dahshi, Marie Varnet, Kimberly Goodspeed, Jacob Tiller, Dallas Armstrong and Deepa Sirsi
Neurol. Int. 2026, 18(3), 58; https://doi.org/10.3390/neurolint18030058 - 18 Mar 2026
Viewed by 1784
Abstract
Introduction: SLC6A1-related neurodevelopmental disorder (SLC6A1-NDD) is an epileptic encephalopathy linked to mutations in the SLC6A1 gene and is characterized by early-onset seizures and developmental delays. Despite the growing recognition of SLC6A1 as a major cause of early-onset epilepsy, the electrophysiological changes associated with [...] Read more.
Introduction: SLC6A1-related neurodevelopmental disorder (SLC6A1-NDD) is an epileptic encephalopathy linked to mutations in the SLC6A1 gene and is characterized by early-onset seizures and developmental delays. Despite the growing recognition of SLC6A1 as a major cause of early-onset epilepsy, the electrophysiological changes associated with the disorder remain inadequately characterized. This study aims to identify electrophysiological biomarkers of SLC6A1-NDD by characterizing EEG delta power using automated tools, EEGLAB (v2023.1) and Persyst 13, exploring age- and state-related effects. Methods: We analyzed EEG recordings from 20 patients with SLC6A1-NDD and 20 neurotypical age- and sex-matched controls using EEGLAB and Persyst, quantifying delta power and related metrics. The Wilcoxon signed-rank method tested for differences between patients and controls, area under the curve (AUC) values evaluated patient classifier models, and Pearson’s correlation assessed concordance between EEGLAB and Persyst. Results: Patients with SLC6A1-NDD exhibited significantly elevated delta power (19.4 ± 4.1) compared to controls (14.2 ± 3.0; p < 0.001). The mean delta power showed an age-dependent increasing trend in patients (b = 0.5), contrasting with a decline in controls (b = −1.0; p < 0.001). In Persyst, the frequency of delta activity above an optimized threshold best differentiated patients from controls in wake epochs (AUC = 0.93). Concordance between EEGLAB and Persyst was one-to-one but with moderate variability (R2 = 0.644; p < 0.001). Conclusions: Elevated delta power is a notable feature of SLC6A1-NDD. Cross-platform comparison demonstrates the feasibility of quantitative EEG analysis, while imperfect concordance highlights the need for pipeline standardization. Future work should validate these findings in larger cohorts and, as suitable reference data emerge, benchmark delta power metrics against age-matched children with other developmental and epileptic encephalopathies. Full article
(This article belongs to the Special Issue The Evolving Role of EEG in Neurological Disorders: Advanced Techniques and Future Directions)
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