Attention-Deficit/Hyperactive Disorder is a well studied but poorly understood disorder. Given that the underlying neurological mechanisms involved in the disorder have yet to be established, diagnosis is dependent upon behavioural markers. However, recent research has begun to associate a dopamine system dysfunction with ADHD; though, consensus on the nature of dopamine’s role in ADHD has yet to be established. Here, I use a computational modelling approach to investigate two opposing theories of the dopaminergic dysfunction in ADHD. The hyper-active dopamine theory posits that ADHD is associated with a midbrain dopamine system that produces abnormally large prediction errors signals; whereas the dynamic developmental theory argues that abnormally small prediction errors give rise to ADHD. Given that these two theories center on the size of prediction errors encoded by the midbrain dopamine system, I have formally investigated the implications of each theory within the framework of temporal-difference learning, a reinforcement learning algorithm demonstrated to model midbrain dopamine activity. The results presented in this thesis suggest that neither theory provides a good account for the behaviour of children and animal models of ADHD. Instead, my results suggest ADHD is the result of asymmetrically effective reinforcement learning signals encoded by the midbrain dopamine system. More specifically, the model presented here reproduced behaviours associated with ADHD when positive prediction errors were more effective than negative prediction errors. The biological sources of this asymmetry are considered, as are other computational models of ADHD.
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/2078 |
| Date | 14 January 2010 |
| Creators | Cockburn, Jeffrey |
| Contributors | Holroyd, Clay Brian, Jahnke, Jens H. |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
Page generated in 0.0018 seconds