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Objects are grouped into categories through a complex combination of statistical and structural regularities. We sought to better understand the neural responses to the structural features of object categories that result from implicit learning. Adult participants were exposed to 32 object categories that contained three structural properties: frequency, variability, and co-occurrences, during an implicit learning task. After this exposure, participants completed a recognition task and were then presented with blocks of learned object categories during fMRI sessions. Analyses were performed by extracting data from ROIs placed throughout the fusiform gyri and lateral occipital cortex and comparing the effects of the different structural properties throughout the ROIs. Behaviorally, we found that symbol category recognition was supported by frequency, but not variability. Neurally, we found that sensitivity to object categories was greater in the right hemisphere and increased as ROIs were moved posteriorly. Frequency and variability altered the brain activation while processing object categories, although the presence of learned co-occurrences did not. Moreover, variability and co-occurrence interacted as a function of ROI, with the posterior fusiform gyrus being most sensitive to this relationship. This result suggests that variability may guide the learner to relevant co-occurrences and this is supported by the posterior ventral temporal cortex. Broadly, our results suggest that the internal features of the categories themselves are key factors in the category learning system. [ABSTRACT FROM AUTHOR]

Complex visual–motor behaviors dominate human–environment interactions. Letter production, writing individual letters by hand, is an example of a complex visual–motor behavior composed of numerous behavioral components, including the required motor movements and the percepts that those motor movements create. By manipulating and isolating components of letter production, we provide experimental evidence that this complex visual–motor behavior is supported by a widespread neural system that is composed of smaller subsystems related to different sensorimotor components. Adult participants hand-printed letters with and without "ink" on an MR-safe digital writing tablet, perceived static and dynamic representations of their own handwritten letters, and perceived typeface letters during fMRI scanning. Our results can be summarized by three main findings: (1) Frontoparietal systems were associated with the motor component of letter production, whereas temporo-parietal systems were more associated with the visual component. (2) The more anterior regions of the left intraparietal sulcus were more associated with the motor component, whereas the more posterior regions were more associated with the visual component, with an area of visual–motor overlap in the posterior intraparietal sulcus. (3) The left posterior intraparietal sulcus and right fusiform gyrus responded similarly to both visual and motor components, and both regions also responded more during the perception of one's own handwritten letters compared with perceiving typed letters. These findings suggest that the neural systems recruited during complex visual–motor behaviors are composed of a set of interrelated sensorimotor subsystems that support the full behavior in different ways and, furthermore, that some of these subsystems can be rerecruited during passive perception in the absence of the full visual–motor behavior. [ABSTRACT FROM AUTHOR]

Our experience with the world commonly involves physical interaction with objects enabling us to learn associations between multisensory information perceived during an event and our actions that create an event. The interplay among active interactions during learning and multisensory integration of object properties is not well understood. To better understand how action might enhance multisensory associative recognition, we investigated the interplay among motor and perceptual systems after active learning. Fifteen participants were included in an fMRI study during which they learned visuo-auditory-motor associations between novel objects and the sounds they produce, either through self-generated actions on the objects (active learning) or by observing an experimenter produce the actions (passive learning). Immediately after learning, behavioral and BOLD fMRI measures were collected while perceiving the objects used during unisensory and multisensory training in associative perception and recognition tasks. Active learning was faster and led to more accurate recognition of audiovisual associations than passive learning. Functional ROI analyses showed that in motor, somatosensory, and cerebellar regions there was greater activation during both the perception and recognition of actively learned associations. Finally, functional connectivity between visual- and motor-related processing regions was enhanced during the presentation of actively learned audiovisual associations. Overall, the results of the current study clarify and extend our own previous work [Butler, A. J., James, T. W., & Harman James, K. Enhanced multisensory integration and motor reactivation after active motor learning of audiovisual associations. Journal of Cognitive Neuroscience, 23, 3515-3528, 2011] by providing several novel findings and highlighting the task-based nature of motor reactivation and retrieval after active learning. [ABSTRACT FROM AUTHOR]

Everyday experience affords us many opportunities to learn about objects through multiple senses using physical interaction. Previous work has shown that active motor learning of unisensory items enhances memory and leads to the involvement of motor systems during subsequent perception. However, the impact of active motor learning on subsequent perception and recognition of associations among multiple senses has not been investigated. Twenty participants were included in an fMRI study that explored the impact of active motor learning on subsequent processing of unisensory and multisensory stimuli. Participants were exposed to visuo-motor associations between novel objects and novel sounds either through self-generated actions on the objects or by observing an experimenter produce the actions. Immediately after exposure, accuracy, RT, and BOLD fMRI measures were collected with unisensory and multisensory stimuli in associative perception and recognition tasks. Response times during audiovisual associative and unisensory recognition were enhanced by active learning, as was accuracy during audiovisual associative recognition. The difference in motor cortex activation between old and new associations was greater for the active than the passive group. Furthermore, functional connectivity between visual and motor cortices was stronger after active learning than passive learning. Active learning also led to greater activation of the fusiform gyrus during subsequent unisensory visual perception. Finally, brain regions implicated in audiovisual integration (e.g., STS) showed greater multisensory gain after active learning than after passive learning. Overall, the results show that active motor learning modulates the processing of multisensory associations. [ABSTRACT FROM AUTHOR]