We present a machine learning-based system for automatically computing interpretable, quantitative measures of animal behavior. Through our interactive system, users encode their intuition about behavior by annotating a small set of video frames. These manual labels are converted into classifiers that can automatically annotate behaviors in screen-scale data sets. Our general-purpose system can create a variety of accurate individual and social behavior classifiers for different organisms, including mice and adult and larval Drosophila.

Motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centers 1. Local cortical dynamics are thought to shape these patterns throughout movement execution 2-4. External inputs have been implicated in setting the initial state of motor cortex 5,6 , but they may also have a pattern-generating role. Here, we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching, or it failed to generate this pattern. The difference in these two outcomes was likely due to external inputs. We directly investigated the role of inputs by inactivating thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly-interacting brain regions. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Behavioral choices that ignore prior experience promote exploration and unpredictability but are seemingly at odds with the brain's tendency to use experience to optimize behavioral choice. Indeed, when faced with virtual competitors, primates resort to strategic counter prediction rather than to stochastic choice. Here, we show that rats also use history- and model-based strategies when faced with similar competitors but can switch to a "stochastic" mode when challenged with a competitor that they cannot defeat by counter prediction. In this mode, outcomes associated with an animal's actions are ignored, and normal engagement of anterior cingulate cortex (ACC) is suppressed. Using circuit perturbations in transgenic rats, we demonstrate that switching between strategic and stochastic behavioral modes is controlled by locus coeruleus input into ACC. Our findings suggest that, under conditions of uncertainty about environmental rules, changes in noradrenergic input alter ACC output and prevent erroneous beliefs from guiding decisions, thus enabling behavioral variation. PAPERCLIP: