PhD Scientific Days 2025

Poster Session I. - Q: Neurosciences

1/f Slope and Alpha Peak Frequency as Early Electrophysiological Markers of Mild Cognitive Impairment

Előadó neve

Lányi Orsolya, MSc

Neptun code

JXJAR0

Előadó munkahelye

Semmelweis University, Department of Psychiatry and Psychotherapy

Előadó telefonszáma

+36705766901

Előadó e-mail címe

orsolya.lanyi@phd.semmelweis.hu

Az előadás címe

1/f Slope and Alpha Peak Frequency as Early Electrophysiological Markers of Mild Cognitive Impairment

Szerző(k) neve és munkahelye

Orsolya Lányi¹, Gábor Csukly¹

1: Semmelweis University, Department of Psychiatry and Psychotherapy

Bemutatás módja

Poszter

Szekció

Poster Session I. - Q: Neurosciences

Language of the presentation

English

Preferred session

Neurosciences

Összefoglaló szövege

Introduction:
Dementia, particularly Alzheimer's Disease, continues to pose a significant burden on the healthcare systems worldwide. Therefore, there is an urgent need to identify early biomarkers of cognitive decline easily accessible in everyday clinical practice. The aperiodic component of the EEG signal (1/f slope) and the individual alpha peak frequency (IAPF) have emerged as promising non-invasive markers of early detection.
Aims:
This study aims to identify EEG markers sensitive to the early detection of cognitive decline in Mild Cognitive Impairment (MCI). Specifically, we aim to investigate if the 1/f slope and the IAPF differ between MCI and healthy aging, and whether these EEG markers are associated with visual working memory performance measured by the Paired Associates Learning (PAL) task.
Methods:
31 MCI patients (17 non-amnestic MCI, aged 58-82, and 14 amnestic MCI, aged 55-79) and 16 healthy elderly individuals (aged 51-83) were recruited at the Semmelweis University, Department of Psychiatry. All participants completed a comprehensive neuropsychological assessment. Resting-state EEG (64-channel Neuroscan) was recorded under both eyes-open and eyes-closed conditions (4 minutes each). In addition, participants completed the PAL task during EEG recording. EEG data were preprocessed using EEGLAB, and the aperiodic exponent and individual alpha peak frequency were extracted using the SpecParam toolbox in Python.
Results:
Preliminary results confirm lower individual alpha peak frequency in MCI compared to the healthy control group, with more prominent slowing among the amnestic group. The exponent of the resting-state 1/f slope shows a slight decrease in both amnestic and non-amnestic MCI, and a flattened slope is associated with age.
Conclusion:
Our results are indicative of the utility of resting-state EEG markers for the early detection of increased dementia risk and cognitive decline. Flattened aperiodic slope and slowed alpha rhythm may reflect increased neural noise and excitability in MCI. Further analysis is conducted to study the association between the aperiodic component of the EEG signal and visual working memory.
Funding:
Supported by the 2024-2.1.1-eköp-2024-00004 university research scholarship programme of the ministry for culture and innovation from the source of the national research, development and innovation fund.

University

Semmelweis University

Supervisor

Dr. Gábor Csukly

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

phd.section.field

in doctoral studies after complex exam (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

7997

Start

16:54

End

17:00