Dinnerwear? Dinner! Where? A novel brain network for making decisions
With nearly 100 pairs of sneakers staring me in the face every morning, I have a pretty difficult time choosing the ideal centerpiece for the day's trappings. Guys with more conservative wardrobes (think Barack Obama, Steve Jobs, and Mark Zuckerberg) have said they wear the same or very similar outfits every single day to preserve their cognitive effort for more important decisions than what to wear to work. In essence, it's much easier to select an outfit when you have fewer options to consider. And honestly, those guys just may have been on to something.
For those of us who don't run countries or Fortune 500 companies, consider the more common dilemma of picking one restaurant to eat at from dozens of appetizing choices. Then, think of how mentally exhausting it is to select a meal when you're handed a menu as thick as a phone book—if you dinosaurs remember those things. At the end of the day, we usually have to put on clothes and eat, so it makes sense that we can learn to effectively and efficiently make decisions that require us to focus our attention on the aspects of decisions that we value more in spite of distractions that we value less.
What these examples also suggest is that we can dynamically combine various pieces of information, including details about our available options and the different value that each option has. When more options are brought to our attention, the consequences of our decisions can become increasingly uncertain. However, choices with more rewarding outcomes direct our attention to features of those choices that will increase the likelihood of successful decisions in the future--like the place in my closet where I put my favorite shoes, or the section of a menu where you picked an entree you loved the last time you visited a restaurant. So, whether we are constructing the consummate ensemble of clothing or cuisine, we learn how to refine our decisions by incorporating information about more rewarding choices amid distracting options with less desirable results.
Ultimately, the ability to assimilate different types of attentional and reward information can partly influence the choices that we learn to make. This leads to one of many questions that interests us in the Cognitive Axon (CoAx) Lab: when we learn to make choices, how do the structural connections in our brain support the integration of many kinds of information that are processed in different regions?
Previous research looking at nonhuman primate (e.g., monkey) neuroanatomy, which is quite similar to humans, has shown that connections from different areas at the cortical surface of the brain do overlap and interdigitate in the same areas within the striatum. These deep forebrain regions serve as the primary inputs to the basal ganglia. The striatal nuclei sit near the center of the brain, but towards the front, and are linked to many cognitive functions including reward, decision making, motor control, and language, to name a few.
One line of research has shown that orbitofrontal areas (associated with evaluating the success and failure of decisions) located on the underside of the brain just above the eyes, send connections to the same striatal regions as prefrontal areas (associated with making decisions), which are located along the outer sides of the brain almost directly above the orbitofrontal cortex in the frontal lobe. This pattern of connectivity has been proposed as one way that the brain can integrate information to assess the outcome of decisions.
Separate studies observed connections from parietal areas, near the rear of the brain, ending in the same striatal areas as connections from prefrontal cortex. Given the involvement of parietal cortex in spatial attention, it is thought to play a strong role in directing attention to parts of the environment that are relevant to performing a task. Through overlapping connectivity, parietal cortex may help focus attention on important aspects of the choices that are being tracked by prefrontal cortex, thereby facilitating decision making.
Yet, despite all this work on overlapping pairwise connectivity, the particular three-way convergence of prefrontal, orbitofrontal and posterior parietal projections had not been previously demonstrated in humans or nonhuman primates. That is, until now.
In work recently published in the Journal of Neuroscience, "Converging structural and functional connectivity of orbitofrontal, dorsolateral prefrontal, and posterior parietal cortex in the human striatum", Dr. Timothy Verstynen (CoAx Lab PI) and I identified a novel network of brain connections that may integrate reward and attention information during decision making. Using an advanced MRI technique called diffusion spectrum imaging, we were able to visualize the underlying white matter pathways of 60 neurologically healthy adult participants. With this method we observed, for the first time in the human brain, long range white matter connections from disparate areas of prefrontal, orbitofrontal, and parietal cortex that converged in the same regions of the striatum.
But do these structural connections mean that these areas are really communicating with each other? To answer this, we used resting state fMRI data, where we looked at our participants' brain activity while they lay silently in the scanner without any other external stimuli being presented to them. By analyzing resting state fMRI data, we can get a sense for which brain regions are functionally connected. More specifically, we can infer which areas may be talking to each other based on whether they show similar levels of activity at the same time when nothing necessarily interesting is going on in the outside world.
Indeed, we found the striatal regions--dubbed "convergence zones"--that showed the tripartite overlap of structural connections were also functionally connected to the trio of cortical areas that we investigated. Interestingly, the convergence zones were located in areas of the striatum that have also been implicated in reinforcement learning.
Together, our findings highlight a plausible network of brain connections that may integrate reward signals with visuospatial attention information to influence learning during decision making. This could have some potentially important implications. From a clinical standpoint, we may be able to gain a deeper understanding of how visuospatial reinforcement learning may break down due to damage to this network, like the gradual depletion of striatal neurons that occurs in Parkinson's disease. More generally, having demonstrated this particular pattern of structural and functional connectivity, further probing of this network may yield greater insight to the dynamic, integrative mechanisms that underlie reward-based learning when visual distractions interfere with action decisions.
So next time you find yourself pondering the perfect outfit or picking an ideal meal, give your brain some credit for learning how to make your everyday decisions a little bit easier, and hopefully better, every time.