Learning and plasticity in the human brain

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The primary goals of this research are i) to establish how learning impacts the structure and function of the brain, and ii) to determine how learning can be modulated by factors such as feedback (positive or negative). Over the past year we have focused on both of these goals. 1) Impact of learning on brain structure and function (NCT00001360) Over the past few years, we have been conducting a long-term longitudinal study of participants learning different tasks (e.g. motor sequences, spatial layout) to determine how structural properties of the brain (gray matter, white matter) change over time. Over a period of four weeks, participants were trained in two different tasks and we collected extensive functional and structural MRI data over the course of training. While previous studies have identified structural changes associated with learning, even over the course of a couple of hours, our initial findings have highlighted a potential confound that needs to be accounted for in such studies. Specifically, we have found that the structural and functional measures obtained with MRI fluctuate according to the time of day. Structurally, we observed decreases in cortical thickness and increases in ventricular volume as well as increases in free water volume fraction that is associated with an increase in cerebrospinal fluid. Functionally, we observed changes in resting state connectivity in similar regions to those where we observed structural changes. Collectively, these results suggest that the diurnal fluctuations in MRI measures that we detected have an underlying physiological basis and may reflect the impact of the circadian rhythm. Interestingly, these fluctuations appear to be modulated by training and we are trying to establish what additional structural and functional changes occur with training above and beyond these time-of-day effects. With the motor sequence task we find that, following training, sensorimotor networks show changes in their functional connectivity. In contrast, with the spatial layout task, hippocampal networks that have been associated with navigation change. Critically, these changes are observed even when we factor out any changes that might reflect simply the time of day. Overall, our study provides further support for the idea that resting state connectivity can provide meaningful insights regarding the offline brain processes that contribute to skill acquisition and suggest that task-specific changes in particular networks underlie learning above and beyond any changes due to circadian fluctuations. Further, our study highlights the importance of controlling for factors such as time of day in studies of learning and plasticity. 2) Impact of feedback on learning (NCT00001360) We have been investigating the impact of feedback (positive, negative) on motor learning. Groups of participants were trained on one of two different motor tasks and either provided with positive, negative or neutral (uninformative) feedback. Training occurred in the MRI scanner and we measured fMRI activity before, during and after training. Behaviorally, we found that the impact of feedback is dependent on the task. In a sequence learning task we find that punishment improves online performance, whereas in a purely motoric force tracking task, we observe the opposite effect. In terms of brain activity, we found that reward and punishment differentially affected the functional connectivity of premotor cortex (PMC, a region known to be critical for learning of sequencing skills) in a task-specific manner. For a serial reaction time task (pushing a sequence of buttons in response to visual cues), training with reward increased PMC connectivity with cerebellum and striatum, while training with punishment increased PMC-medial temporal lobe connectivity. For a force tracking task (sqeezing a bar to control the movement of a cursor on the screen), training with control feedback and reward increased PMC connectivity with parietal and temporal cortices, while training with punishment increased PMC connectivity with ventral striatum. While the results from the two experiments overlapped in some brain areas, including ventral pallidum, temporal lobe, and cerebellum, these regions showed diverging patterns of results across the two tasks for the different feedback conditions. Collectively, these findings suggest that reward and punishment influence spontaneous brain activity after training, and that the regions implicated depend on the task learned. Establishing the nature, degree and consequences of plasticity in the adult cortex provides important insights into the potential for rehabilitative brain therapies following injury or dysfunction in the nervous system.