Ahmad Mayeli

Publications : 23
Aldex : 30
H-index : 4
Citations : 53

Circadian Rhythm Changes in Healthy Aging and Mild Cognitive Impairment

Ahmadreza Keihani et 3 al.

Nov 20, 2022 in Advanced Biosystems
This article provides a narrative review of the most relevant findings of circadian rhythm changes/disruptions in four domains, which involve rest activity rhythm (RAR), core body temperature (CBT), melatonin, and cortisol in patients with mild cognitive impairment (MCI) relative to healthy aging individuals. The relationships between normal aging and MCI related changes in circadian rhythms relat...

Automated Pipeline for EEG Artifact Reduction (APPEAR) Recorded during fMRI

Ahmad Mayeli, Jerzy Bodurka et 9 al.

Dec 11, 2019 in Arxiv
Objective . EEG data collected during fMRI acquisition are contaminated with MRI gradients and ballistocardiogram (BCG) artifacts, in addition to artifacts of physiological origin. There have been several attempts for reducing these artifacts with manual and time-consuming pre-processing, which may result in biasing EEG data due to variations in selecting steps order, parameters, and classificatio...


Brain Sciences, Vol. 12, Pages 233: Examining First Night Effect on Sleep Parameters with hd EEG in Healthy Individuals

Ahmad Mayeli et 4 al.

Feb 8, 2022 in Brain Sciences
Difficulty sleeping in a novel environment is a common phenomenon that is often described as the first night effect (FNE). Previous works have found FNE on sleep architecture and sleep power spectra parameters, especially during non rapid eye movement (NREM) sleep. However, the impact of FNE on sleep parameters, including local differences in electroencephalographic (EEG) activity across nights, h...


Canonical EEG Microstates Transitions Reflect Switching Among BOLD Resting State Networks and Predict fMRI Signal.

Obada Al Zoubi et 15 al.

Dec 22, 2021 in Journal of neural engineering
Electroencephalography microstates (EEG-ms), which reflect a large topographical representation of coherent electrophysiological brain activity, are widely adopted to study cognitive processes mechanisms and aberrant alterations in brain disorders. EEG-ms topographies are quasi-stable lasting between 60-120 milliseconds. Some evidence suggests that EEG-ms are the electrophysiological signature of ...

Default Mode Network Remodels Frontoparietal Network in Self-Referential Task

Genevieve Yang, Jerzy Bodurka et 3 al.

Jan 1, 2020 in Biological Psychiatry


Obada Al Zoubi, Jerzy Bodurka et 5 al.

Jan 1, 2018 in 2018 IEEE Global Conference on Signal and Information Processing
Electroencephalography (EEG) has been widely used in human brain research. Several techniques in EEG relies on analyzing the topographical distribution of the data. One of the most common analysis is EEG microstates (EEG-ms). EEG-ms reflects the stable topographical representation of EEG signal lasting a few dozen milliseconds. EEG-ms were associated with resting state fMRI networks and related me...

An automatic ICA-based method for removing artifacts from EEG data acquired during fMRI in real time

Ahmad Mayeli, Jerzy Bodurka et 3 al.

Jan 1, 2015 in 2015 41st Annual Northeast Biomedical Engineering Conference
Simultaneous EEG-fMRI recording provides complementary advantages with regard to the temporal and spatial resolution of neuronal activity measurements. However, raw EEG data collected during fMRI experiments are contaminated by imaging and ballistocardiographic (BCG) artifacts in addition to muscle, ocular, and other EEG artifacts. We describe a new method developed based on independent component ...


Sleep abnormalities in individuals at clinical high risk for psychosis.

Ahmad Mayeli et 6 al.

Jan 1, 2021 in Journal of psychiatric research
Youth at clinical high risk (CHR) represent a unique population enriched for precursors of major psychiatric disorders. Sleep disturbances are consistently reported in CHR individuals. However, there is a dearth of studies investigating quantifiable objective measures of sleep dysfunction in CHR youth. In this study, sleep high density (hd)-EEG recordings were collected in twenty-two CHR and twent...

Hierarchical Fusion Evolving Spiking Neural Network for Adaptive Learning

Obada Al Zoubi et 4 al.

Jan 1, 2018 in 2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing
A majority of machine learning (ML) approaches functions in offline or batch modes, which limits their application to adaptive environments. Thus, developing algorithms that work in adaptive and dynamic environments is the subject of ongoing research. Such algorithms require to learn not only from new samples (online learning), but also from novel and unseen before knowledge. Here, we introduce th...

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