Dissociating the contributions of independent corticostriatal systems to visual categorization learning through the use of reinforcement learning modeling and Granger causality modeling.

We dissociated the contributions to learning of four corticostriatal "loops" (interacting striatal and cortical regions): motor (putamen and motor cortex), visual (posterior caudate and visual cortex), executive (anterior caudate and prefrontal cortex), and motivational (ventral striatum and ventromedial frontal cortex). Subjects learned to categorize individual repeated images into one of two arbitrary categories via trial and error. We identified (1) regions sensitive to correct categorization, categorization learning, and feedback valence; (2) regions sensitive to prediction error (violation of feedback expectancy) and reward prediction (expected feedback associated with category response) using reinforcement learning modeling; and (3) directed influences between regions using Granger causality modeling. Each loop showed a unique pattern of sensitivity to each of these factors. Both the motor and visual loops were involved in acquisition of categorization ability: activity during correct categorization increased across learning and was sensitive to reward prediction. However, the posterior caudate received directed influence from visual cortex, whereas the putamen exerted directed influence on motor cortex. The motivational and executive loops were involved in feedback processing: both regions were sensitive to feedback valence, which interacted with learning across scans. However, the motivational loop activity reflected prediction error, whereas executive loop activity reflected reward prediction, consistent with the executive loop role in integrating reward and action. Granger causality modeling found directed influences between striatal and cortical regions within each loop. Across loops, the motor loop exerted directed influence on the executive loop which is consistent with the role of the executive loop in integrating feedback with stimulus-response history.

Dissociation between striatal regions while learning to categorize via feedback and via observation.

Convergent evidence from functional imaging and from neuropsychological studies of basal ganglia disorders indicates that the striatum is involved in learning to categorize visual stimuli with feedback. However, it is unclear which cognitive process or processes involved in categorization is or are responsible for striatal recruitment; different regions of the striatum have been linked to feedback processing and to acquisition of stimulus-category associations. We examined the effect of the presence of feedback during learning on striatal recruitment by comparing feedback learning with observational learning of an information integration task. In the feedback task, participants were shown a stimulus, made a button press response, and then received feedback as to whether they had made the correct response. In the observational task, participants were given the category label before the stimulus appeared and then made a button press indicating the correct category membership. A region-of-interest analysis was used to examine activity in three regions of the striatum: the head of the caudate, body and tail of the caudate, and the putamen. Activity in the left head of the caudate was modulated by the presence of feedback: The magnitude of activation change was greater during feedback learning than during observational learning. In contrast, the bilateral body and tail of the caudate and the putamen were active to a similar degree in both feedback and observational learning. This pattern of results supports a functional dissociation between regions of the striatum, such that the head of the caudate is involved in feedback processing, whereas the body and tail of the caudate and the putamen are involved in learning stimulus-category associations. The hippocampus was active bilaterally during both feedback and observational learning, indicating potential parallel involvement with the striatum in information integration category learning.

Dynamics of frontal, striatal, and hippocampal systems during rule learning.

We examined interactions between frontal, striatal, and hippocampal systems during a rule-learning task. Nineteen healthy young adults solved multiple rule-learning problems requiring hypothesis testing while functional magnetic resonance images were obtained. Activity in the head of the caudate peaked early after the beginning of each problem and then dropped rapidly. In contrast, activity in prefrontal cortex areas reached peak values later. These results are in accordance with theories suggesting that the striatum identifies the behavioral context necessary for the frontal lobe to select an appropriate strategy. Striatal and hippocampal systems showed antagonistic patterns of activity: Activation in the anterior hippocampus decreased, whereas caudate activity increased. Good learners showed higher activity in the body and tail of the caudate than poor learners, whereas learning success correlated negatively with activity in the hippocampus. Activation in the head of the caudate correlated negatively with hippocampal activation, indicating a potential mechanism for hippocampal activity reduction.

The roles of the caudate nucleus in human classification learning.

The caudate nucleus is commonly active when learning relationships between stimuli and responses or categories. Previous research has not differentiated between the contributions to learning in the caudate and its contributions to executive functions such as feedback processing. We used event-related functional magnetic resonance imaging while participants learned to categorize visual stimuli as predicting "rain" or "sun." In each trial, participants viewed a stimulus, indicated their prediction via a button press, and then received feedback. Conditions were defined on the bases of stimulus-outcome contingency (deterministic, probabilistic, and random) and feedback (negative and positive). A region of interest analysis was used to examine activity in the head of the caudate, body/tail of the caudate, and putamen. Activity associated with successful learning was localized in the body and tail of the caudate and putamen; this activity increased as the stimulus-outcome contingencies were learned. In contrast, activity in the head of the caudate and ventral striatum was associated most strongly with processing feedback and decreased across trials. The left superior frontal gyrus was more active for deterministic than probabilistic stimuli; conversely, extrastriate visual areas were more active for probabilistic than deterministic stimuli. Overall, hippocampal activity was associated with receiving positive feedback but not with correct classification. Successful learning correlated positively with activity in the body and tail of the caudate nucleus and negatively with activity in the hippocampus.

Striatal activity in concept learning.

Striatal learning systems have been implicated in learning relationships between visual stimuli and outcomes. In the present study, the activity of the striatum during visual concept learning in humans was examined by using functional magnetic resonance imaging (fMRI). Participants performed three concept-learning tasks and a baseline task. The participants were trained to criterion before fMRI scanning on two tasks, verbal and implicit. In the verbal task, classification could be performed on the basis of a simple verbal rule, but in the implicit task, there was no simple verbal rule. The novel-implicit learning task, in which an implicit structure was used, was not encountered by the participants before scanning. Across all three concept-learning tasks, there was significant activation in the striatum, in comparison with the baseline task. The striatum was recruited similarly in classification when the participants had different levels of expertise (novel-implicit vs. verbal and implicit) and were able to verbalize their learning to different degrees (verbal vs. implicit and novel-implicit). There was left lateral occipital activation when learning was implicit (implicit and novel-implicit), but not when learning was easily verbalized (verbal).