Ahmed M. T. Raslan

This study uses intracranial recordings to investigate the Triple Code Model of numerical cognition, finding distinct neural correlates for different numerical representations.

The paper identifies modular organization in human superior temporal gyrus for phoneme processing using high-density micro-arrays.

The paper introduces a high-channel-count flexible electrode for deep brain recording, capable of capturing single-unit activity from up to 128 channels.

This paper shows that high-frequency ripples synchronize cortical activity across distant brain regions during sleep, waking, and memory recall, supporting the binding-by-synchrony theory.

The paper uses machine learning to classify movement-related oscillations in sEEG recordings, identifying new patterns and brain regions involved in movement.

The paper identifies auditory salience detection in the posterior superior temporal region using intracranial EEG during speech and noise tasks, showing sustained and recurrent responses to paired stimuli.

The paper identifies three distinct classes of cortical activity using high-density microelectrodes, showing they are modulated by stimuli and present across species.