activity
20202026
most citedNeuro-GPT: Towards A Foundation Model for EEG

6 citations · 9 across the 12 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

eess.SP2025

Informed Bootstrap Augmentation Improves EEG Decoding

Woojae Jeong, Wenhui Cui, Kleanthis Avramidis +3

Electroencephalography (EEG) offers detailed access to neural dynamics but remains constrained by noise and trial-by-trial variability, limiting decoding performance in data-restri…

eess.SP2025

A Point Process Model of Skin Conductance Responses in a Stroop Task for Predicting Depression and Suicidal Ideation

Kleanthis Avramidis, Myzelle Hughes, Idan A Blank +5

Accurate identification of mental health biomarkers can enable earlier detection and objective assessment of compromised mental well-being. In this study, we analyze electrodermal…

physics.med-ph2025

High-Resolution Directional Depth Electrodes: Open-Source FEM Lead-Field Modeling, Characterization, and Validation

Takfarinas Medani, Jace Willis, Chris Wright +7

Depth electrodes used in stereoelectroencephalography (sEEG) and deep-brain stimulation (DBS) are essential tools for neural recording and stimulation. Traditional designs have lim…

q-bio.NC2025

Time-Resolved EEG Decoding of Semantic Processing Reveals Altered Neural Dynamics in Depression and Suicidality

Woojae Jeong, Aditya Kommineni, Kleanthis Avramidis +15

Depression and suicidality affect cognitive and emotional processes, yet objective, task-evoked neural readouts of mental health remain limited. We investigated the spatiotemporal…

cs.LG2025

Neural Responses to Affective Sentences Reveal Signatures of Depression

Aditya Kommineni, Woojae Jeong, Kleanthis Avramidis +13

Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core fu…

eess.IV2025

A Feasibility Study of Task-Based fMRI at 0.55 T

Parsa Razmara, Takfarinas Medani, Anand A. Joshi +6

0.55T MRI offers advantages compared to conventional field strengths, including reduced susceptibility artifacts and better compatibility with simultaneous EEG recordings. However,…

cs.LG2025

Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements

Kleanthis Avramidis, Woojae Jeong, Aditya Kommineni +14

Identifying physiological and behavioral markers for mental health conditions is a longstanding challenge in psychiatry. Depression and suicidal ideation, in particular, lack objec…