From parallel sequence representations to calligraphic control: a conspiracy of neural circuits

Bias and sensitivity of proprioception of a passively felt hand path with and without a secondary task

Previously, we observed changes in the scale, rotation, and location of drawn shapes when subjects simultaneously performed a secondary task, but not in the shape or proportion of the drawing. We suggested the secondary task impacted motor planning and execution or proprioception of the primary task. To isolate for proprioceptive effects, here we used the same secondary task during passive shape perception. A robotic manipulandum moved the subject's hand around the perimeter of a template shape and then a test shape differing in size, proportion, or location. Subjects also performed the same primary task while simultaneously performing a secondary task of reporting the orientation of right or left tilted arrows. We compared the performance between single and dual task, and different workspaces. In single-task conditions, subjects perceived scale, location, and proportion very close to the actual (all biases under 1 cm). A secondary task only increased the uncertainty range for judgment of scale, with no other effect. Subjects judged shapes in the centered workspace to be smaller and closer relative to the template compared with those in the peripheral workspace, although in that workspace, it was more difficult to discern changes in the proportion of the shape. The result for scale in the current passive paradigm is not different from our active study in which efference copy was available. This suggests that the scale parameters of the shape, whether actively or passively encountered, are disrupted by task interference at the level of proprioception or sensory integration rather than motor planning and execution.

Computational perspectives on forebrain microcircuits implicated in reinforcement learning, action selection, and cognitive control

Abundant new information about signaling pathways in forebrain microcircuits presents many challenges, and opportunities for discovery, to computational neuroscientists who strive to bridge from microcircuits to flexible cognition and action. Accurate treatment of microcircuit pathways is especially critical for creating models that correctly predict the outcomes of candidate neurological therapies. Recent models are trying to specify how cortical circuits that enable planning and voluntary actions interact with adaptive subcortical microcircuits in the basal ganglia. The basal ganglia are strongly implicated in reinforcement learning, and in all behavior and cognition over which the frontal lobes exert flexible control. The persisting role of the basal ganglia shows that ancient vertebrate designs for motivated action selection proved adaptable enough to support many "modern" behavioral innovations, including fluent generation of language and speech. This paper summarizes how recent models have incorporated realistic representations of microcircuit features, and have begun to trace their computational implications. Also summarized are recent empirical discoveries that provide guidance regarding how to formulate the rules for synaptic modification that govern learning in cortico-striatal pathways. Such efforts are contributing to an emerging synthesis based on an interlocking set of computational hypotheses regarding cortical interactions with basal ganglia and thalamic nuclei. These hypotheses specify how specialized microcircuits solve learning and control problems inherent to the brain's parallel design.