Modeling Dopamine Circuitry in Learning and ADHD

Summary

Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder, with symptoms ranging from difficulty focusing to severe social and academic impairments. Current treatments, primarily stimulant medications like methylphenidate, target symptoms rather than underlying causes and may have side effects, including addiction. Given the role of dopamine in ADHD, computational modeling offers a valuable approach to understanding its biophysical mechanisms. This project reviews the biological basis of ADHD and develops a Python-based computational model focused on dopaminergic neuron interactions and dopamine synaptic concentration. By incorporating existing models and literature, we created a dopamine-specific model simulating the effects of dopamine transporter (DAT) activity on synaptic current. Our findings suggest that ADHD patients exhibit lower synaptic currents than healthy individuals, and while stimulant medication improves these currents, it does not fully restore them to normal levels. This work highlights the potential of computational models in neuroscience research, providing insights into ADHD and informing future treatment strategies.