Psychology, Neuroscience, and Bears, Oh My: Understanding Motivation as a Team Effort
From bearded philosophers' musings on consciousness to neuroscientists' papers employing modern techniques to study neurons, I've always been interested in how we have come to understand the brain. With this interest came a curiosity in the strengths and weaknesses each discipline has to offer in terms of solving the ever-evolving puzzle that is the center of our nervous system. If I have learned anything from this curiosity, it is this: if we are going to figure out exactly how the brain works, it is going to take a group effort. No single discipline will get all the way there by itself, but each has something meaningful to contribute. Take, for example, our social science research in Motivate Lab. The way that we have come to understand and explore this complexity is by looking at, you guessed it: motivation. Specifically, this research concerns boosting student motivation and achievement in educational settings. We often try to do so by supporting students in finding value in their education - our intervention activities help them make personally meaningful connections between their coursework and their immediate and future lives. This may seem pretty straightforward but, spoiler alert: it's not.
One challenge? How can we best help find this value? Should we ask students to write an essay about the value of a subject? Have them sit through a presentation about motivation and then have a subsequent discussion? Pass out friendly cat posters with punny yet inspirational quotes? Even after we’ve decided which approach to take, one small problem still remains: how can we even measure if this increased student motivation? Typically, we look at a wide range of things that may provide us with some insight, including self-reported interest in class, academic achievement, or essays students have written about their courses. But who is to say whether any one (or a combination) of those things measures motivation?
To complicate things further, motivation itself is not a particularly straightforward concept. There are many different factors that go into student motivation such as home life, the school environment, and even factors as fickle as emotions on any given day. With such questions in mind, motivational research in social psychology can be really challenging and frustrating. There isn’t an easily quantifiable measure of motivation nor a quick fix. No device exists that can tell us that a given student has 52.4 motivation units for math and there isn’t a solution as simple as taking a motivation boosting pill.
The difficulties inherent to measuring psychological motivation in our work can make the more neurobiological aspects of the brain seem more appealing. For example, we could simply identify certain areas of the brain that are attributed to motivation and then study what causes an increase in blood flow or electrical activity to them. This increased activity would mean increased motivation. Thus, finding out how to increase activity means finding how to increase motivation. Easy, right?! Not quite…
First, just like in our research, it is hard to define what is really meant by “motivation.” In actuality, there isn’t a single neuron or brain center that, so far, has been found to completely control everything involved with what we know as motivation. However, the midbrain dopamine system is one area in the brain that researchers believe plays a heavy hand in motivation. To many people, dopamine may ring a bell as the “reward” chemical. Specifically, this chemical cues positive sensations during certain tasks or behaviors. Reward plays a pretty crucial role in motivation in the sense that, all else being equal, the more reward there is for a task the more you will be motivated to continue to do it. But, as I came to find out, even something as seemingly straightforward as the dopamine reward pathway is not so simple.
Schultz and colleagues (1993) studied this pathway by flashing a light to cue monkeys to pull a lever and, if they completed this task, rewarding them with sugary juice. While this was going on, researchers recorded electrical activity from individual dopamine neurons in their brain. As they came to find out, after learning that the light meant juice, the monkeys’ dopamine neurons would fire most frequently not when actually receiving the rewarding juice, as we might’ve expected, but rather when the signal light turned on. If dopamine firing simply equaled receiving reward, then the neurons should have fired most frequently when receiving the juice no matter what the light was doing. As they concluded, dopamine neurons fired not for reward itself but instead for when a reward is predicted. If the relationship between dopamine and reward in a controlled environment where the motivation was something as simple as juice, you can imagine just how complex measure individual student motivation might be! Such complications in the dopamine system means fashioning a brain-scanning device to a student to measure its firing while a student goes about his school day won’t get us those motivation units that we so desire to find more than anything else we currently work with.
As any teacher could probably tell you, simply giving rewards to students like a piece of candy after every “A” they receive won’t do the trick to motivate students. As Daw and Shohamy point out in their article “The Cognitive Neuroscience of Motivation and Learning” (2008), motivation also must involve many other brain areas to account for the much more long-term “goal-directed” motivation. In other words, students set goals for what they want out of school and life and optimally use such goals to self-motivate and inform behavior. Thus, in terms of studying motivation from a neuroscience perspective, motivation must also then, at the least, include memory systems that store these goals and selection systems that choose which goals/behaviors best fit their current situation. These “zoomed-in” measures and methods quickly become quite “zoomed-out” and complicated the more you try and fully incorporate motivation from a student perspective.
Ultimately, it is pretty impossible to escape the complicated interactions involved in motivation, no matter how you cut the cake. Both psychology and neuroscience have their own set of similar and distinct challenges, but each produce important discoveries and paint the picture of just how mysterious and amazing the brain really is. Motivation provides just one insight into the incredible complexity of the brain. Ultimately, it is going to take a team effort to slowly put the pieces together from different sides of the brain puzzle. Neuroscience will help us best understand the cogs behind the scenes while psychological work like we do in Motivate Lab will better get at what happens once those cogs start turning. There is still so much more to understand and uncover about the complicated supercomputer that is the brain and I am excited to hopefully have a hand in putting one more piece of that puzzle in its place. How hard could it be?
Josh Davis is a 4th year at the University of Virginia seeking a double major in Psychology and Cognitive Science with a concentration in Neuroscience. His work in Motivate Lab mainly focuses on assisting in qualitative data processing, literature reviews, and distracting his coworkers with his hilarious jokes. When Josh isn’t nerding out over the intersections of neurobiology and psychology, you can find him at the front of the UVA Marching Band as drum major or eating at the local Chipotle.
Daw, N. D., & Shohamy, D. (2008). The cognitive neuroscience of motivation and learning. Social Cognition, 26(5), 593-620.
Schultz, W., Apicella, P., & Ljungberg, T. (1993). Responses of monkey dopamine neurons to reward and conditioned stimuli during successive steps of learning a delayed response task. Journal of Neuroscience, 13(3), 900-913.