Simulating Cognitive & Behavioural Changes via Neural Network Models
An ongoing research paper exploring how different human mental illnesses can be modelled and simulated within artificial neural networks. The study measures behavioural patterns and performance metrics under conditions that mimic disorders such as depression, ADHD, anxiety, and schizophrenia.

Research questions:
• How do simulated neurochemical imbalances alter a network's decision-making and task performance?
• Can ANN weight distributions model the cognitive load shifts seen in clinical populations?
• What behavioural signatures emerge when simulating disorder-specific inhibitory deficits or reward-pathway disruptions?

Methodology combines computational neuroscience, reinforcement learning, and psychological behavioural models.

My Work& Code

My Work
& Code