Dr. Clay Holroyd

Professor, Department of Psychology
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Phone: (250) 472-4490
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Research area: neurobiological mechanisms of cognitive control

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Research Profile

The connection between learning, dopamine and Attention Deficit Hyperactivity Disorder

What do schizophrenia, drug addictions and Attention-deficit Hyperactivity Disorder (ADHD) have in common? They are all conditions (and there are many others) where the mesolimbic dopamine system of the brain is thought to be “out of whack.” Such an unscientific phrase is somewhat justified since the regulation of dopamine in the average person is so poorly understood, never mind what is happening on a bad day at the detox centre or a good day for a boy on Ritalin.

Historically, the role of the mesolimbic dopamine system was thought of as a collection of pleasure centres in the brain that give feelings of pleasure and reward when stimulated by dopamine, and for that reason, the system is often informally called the dopamine reward system. However, cognitive neuroscientists like UVic’s Dr. Clay Holroyd are starting to realize some of the subtleties of the system that make this name out of date. Holroyd is among a growing group of psychologists who believe the main role of the mesolimbic dopamine system is as a learning tool: it allows the brain to pick out the relevant behaviour (even in a long series of actions) that is connected to a desired or undesired consequence. In other words, the mesolimbic dopamine system is crucial for learning from one’s successes and mistakes.

This new understanding of the role of dopamine has refocused research into learning disabilities. For instance, it is now commonly thought that ADHD is related to the mesolimbic dopamine system. One compelling reason for this idea is that the drug methylphenidate eases ADHD’s symptoms of hyperactivity and inability to focus. Methylphenidate, commonly known under the brand name Ritalin, acts by blocking the reuptake of dopamine, increasing the amount available to areas of the brain associated with feelings of reward.

Holroyd’s team specializes in studying the connection between dopamine and learning dysfunction in a wide range of disorders such as Parkinson’s and schizophrenia, mostly by measuring brain activity and through computational modelling. Recently they turned their attention to ADHD. By measuring brain activity, Holroyd showed that children with ADHD respond more strongly to positive and negative feedback during learning exercises after they were given money. This is important because of a common observation about ADHD kids: they seem to respond better to immediate concrete rewards like money, as opposed to abstract long-term rewards typically associated with the pleasure of learning.

To back up a little, the key to all of Holroyd’s recent studies is the fact that he developed a way to measure neurons responding to dopamine in human brains using an indirect, noninvasive method. Holroyd uses a technique called Event Related Potentials (ERPs) that uses a mesh cap laced with electrodes to measure brain activity at a person’s scalp. The technique averages total electrical brain activity and subtracts background, so that one can detect a voltage spike or dip (called an ERP component) that is related to a specific brain task.

Holroyd has shown that there are several specific ERP components that occur during computer learning exercises, milliseconds after a person either detects an error, or gets unexpected negative or positive feedback. He believes these ERP components are elicited when dopamine is received in the Anterior Cingulate Cortex (ACC). He proposes that the ACC is akin to a “corporate leader”: it doesn’t stoop to the handle daily tasks, but if it sees something that needs changing, it steps in with a change in direction. In other words, the ACC receives high levels of dopamine when things are going better than expected or low levels of dopamine when things are going worse than expected. It responds by instructing other parts of the brain to modify behaviour. He proposes this could provide a mechanism for people to learn from feedback (probably one of several learning mechanisms that work together).

In his ADHD study, Holroyd set out to see if these ERP components were different in children with ADHD than in average children. He compared 14 boys with ADHD to 13 typical boys. He measured their ERPs, while the boys played a computer maze game that gave positive feedback (an apple symbol, representing money that accrued for a payout later in the game) and negative feedback (an orange, meaning, sorry, try again).

The game, designed by grad student Travis Baker, was presented as logical to the boys, but in fact, it was random, so the boys’ brains gave strong ERP components associated with negative feedback when they did not find the fruit they were expecting. To keep the boys’ interested in the game, which after all, was not very rewarding, halfway through the game the children were paid out the money they had earned thus far, about $5. A second payment was made at the end.

Holroyd expected the children with ADHD to have either larger or smaller ERP components than the control group, showing they were responding differently to feedback. Instead, he found no significant difference between the two groups.

However, Holroyd’s team unexpectedly found a difference in the trend of responses before and after the money. The boys with ADHD responded more strongly to feedback after the cash payout, while the control group responded less strongly as the game progressed, despite the cash. The control group of boys seemed to be losing interest. It was if their brains stopped predicting what fruit it would see, and stopped being surprised when it saw one fruit, when it expected the other.

So what was going on with the ADHD children? Holroyd thinks that these results are consistent with the idea that the ADHD kids respond more strongly when the money is in front of them. He is currently refining the study, so the effect of the type and timing of a concrete award can be tested.

Holroyd’s work outlines some of the complexities of the dopamine reward system. He thinks the idea of simply “too much” or “too little” dopamine is too simplistic. Indeed, one of Holroyd’s grad students, Jeff Coburn, is using computer neural networks to model learning based on various prevailing computational theories of the dopamine system.

So far, Coburn has showed that uniformly raising or lowering dopamine responses to positive and negative feedback does not explain the behaviour of ADHD kids.

Instead, his results show that the dopamine signal in children with ADHD must be asymmetrical – the positive response to rewards must be larger than the negative response to errors (whereas in typical children, the positive and negative signals are the same size). This suggests that hyperactivity arises in part because kids with ADHD learn irrelevant behaviors (from the large positive signals) that are never “pruned away” (because of the reduced negative signals). In other words, what seems like hyperactivity is actually random behaviour accidentally re-enforced.