Ahmed A. Moustafa

This paper introduces a deep spiking neural network for detecting auditory spatial attention from single-trial EEG, achieving 90% accuracy with 10% data.

This paper introduces a neuroscience-inspired spiking neural network with feedback inhibition that enhances pattern separation and demonstrates its application in cognitive robotics.

This study quantifies hypoxia's impact on cognitive performance across domains using 46 studies, finding significant impairments in processing speed, long-term storage, and psychomotor speed.

The paper examines how aperiodic EEG activity relates to verbal fluency performance across adulthood, finding that smaller offsets correlate with poorer performance and greater aperiodic activity correlates with better performance.

This study evaluates the test-retest reliability of SpecParam in measuring EEG activity across different conditions and finds good reliability for aperiodic parameters and some periodic parameters, but poor reliability in eyes-open resting conditions.

The paper examines resting EEG activity in Parkinson's Disease patients on and off medication, finding medication-invariant differences in aperiodic activity that contribute to neural correlates of the disorder.

This paper introduces a spiking neural network for detecting auditory spatial attention from single-trial EEG data, achieving 90% accuracy with only 10% of the data.

This paper introduces a brain-inspired neural network with non-synaptic memory for handwritten digit classification, achieving 86% accuracy using full training data.

This paper develops a spiking neural network that learns hand-written digits from few examples, inspired by neuroscience mechanisms, and achieves efficient learning with minimal training data.

The paper investigates how structural network topology changes correlate with hallucinatory behavior severity in Parkinson’s disease using graph theory and connectivity analysis.

This study uses a hierarchical drift diffusion model to show that Parkinson’s disease patients with visual hallucinations have slower sensory evidence accumulation, suggesting impaired bottom-up processing and increased reliance on top-down influences.