Al Saqib Majumder

My current research focuses on Targeted Memory Reactivation (TMR) and its potential to influence memory consolidation during rapid eye movement (REM) sleep.

I am investigating whether pairing a serial reaction time task with emotional cueing can enhance learning when followed by TMR during sleep. In parallel, I am exploring the application of machine learning classifiers to electroencephalography (EEG) data in order to detect memory-related neural patterns.

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My broader academic interests lie at the intersection of neuroscience and artificial intelligence, with a particular focus on understanding the computational mechanisms underlying memory and attention. By integrating experimental methods with computational modelling, I aim to contribute to a deeper understanding of cognition and the brain's capacity for adaptive learning.

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