8 papers
From Video to EEG: Adapting Joint Embedding Predictive Architecture to Uncover Saptiotemporal Dynamics in Brain Signal Analysis
Amirabbas Hojjati, Lu Li, Ibrahim Hameed +3
EEG signals capture brain activity with high temporal and low spatial resolution, supporting applications such as neurological diagnosis, cognitive monitoring, and brain-computer i…
Explainability of Complex AI Models with Correlation Impact Ratio
Poushali Sengupta, Rabindra Khadka, Sabita Maharjan +5
Complex AI systems make better predictions but often lack transparency, limiting trustworthiness, interpretability, and safe deployment. Common post hoc AI explainers, such as LIME…
Saccade crossing avoidance as a visual search strategy
Alex Szorkovszky, Rujeena Mathema, Pedro Lencastre +2
Although visual search appears largely random, several oculomotor biases exist such that the likelihoods of saccade directions and lengths depend on the previous scan path. Compare…
EEG-MSAF: An Interpretable Microstate Framework uncovers Default-Mode Decoherence in Early Neurodegeneration
Mohammad Mehedi Hasan, Pedro G. Lind, Hernando Ombao +2
Dementia (DEM) is a growing global health challenge, underscoring the need for early and accurate diagnosis. Electroencephalography (EEG) provides a non-invasive window into brain…
DREAMS: A python framework for Training Deep Learning Models on EEG Data with Model Card Reporting for Medical Applications
Rabindra Khadka, Pedro G Lind, Anis Yazidi +1
Electroencephalography (EEG) provides a non-invasive way to observe brain activity in real time. Deep learning has enhanced EEG analysis, enabling meaningful pattern detection for…
Examining Reject Relations in Stimulus Equivalence Simulations
Alexis Carrillo, Asieh Abolpour Mofrad, Anis Yazidi +1
Simulations offer a valuable tool for exploring stimulus equivalence (SE), yet the potential of reject relations to disrupt the assessment of equivalence class formation is content…