Cell-Type-Specific Outcome Representation in the Primary Motor Cortex.

Adaptive movements are critical for animal survival. To guide future actions, the brain monitors various outcomes, including achievement of movement and appetitive goals. The nature of these outcome signals and their neuronal and network realization in the motor cortex (M1), which directs skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in the murine forelimb M1. We found two populations of layer 2-3 neurons, termed success- and failure-related neurons, that develop with training, and report end results of trials. In these neurons, prolonged responses were recorded after success or failure trials independent of reward and kinematics. In addition, the initial state of layer 5 pyramidal tract neurons contained a memory trace of the previous trial's outcome. Intertrial cortical activity was needed to learn new task requirements. These M1 layer-specific performance outcome signals may support reinforcement motor learning of skilled behavior.

Cortical pattern generation during dexterous movement is input-driven.

The motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centres1. Local cortical dynamics are thought to shape these patterns throughout movement execution2-4. External inputs have been implicated in setting the initial state of the motor cortex5,6, 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 failed to generate this pattern. The difference in these two outcomes was probably a result of external inputs. We directly investigated the role of inputs by inactivating the 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.

A repeated molecular architecture across thalamic pathways.

The thalamus is the central communication hub of the forebrain and provides the cerebral cortex with inputs from sensory organs, subcortical systems and the cortex itself. Multiple thalamic regions send convergent information to each cortical region, but the organizational logic of thalamic projections has remained elusive. Through comprehensive transcriptional analyses of retrogradely labeled thalamic neurons in adult mice, we identify three major profiles of thalamic pathways. These profiles exist along a continuum that is repeated across all major projection systems, such as those for vision, motor control and cognition. The largest component of gene expression variation in the mouse thalamus is topographically organized, with features conserved in humans. Transcriptional differences between these thalamic neuronal identities are tied to cellular features that are critical for function, such as axonal morphology and membrane properties. Molecular profiling therefore reveals covariation in the properties of thalamic pathways serving all major input modalities and output targets, thus establishing a molecular framework for understanding the thalamus.

Thalamus provides layer 4 of primary visual cortex with orientation- and direction-tuned inputs.

Understanding the functions of a brain region requires knowing the neural representations of its myriad inputs, local neurons and outputs. Primary visual cortex (V1) has long been thought to compute visual orientation from untuned thalamic inputs, but very few thalamic inputs have been measured in any mammal. We determined the response properties of ∼ 28,000 thalamic boutons and ∼ 4,000 cortical neurons in layers 1-5 of awake mouse V1. Using adaptive optics that allows accurate measurement of bouton activity deep in cortex, we found that around half of the boutons in the main thalamorecipient L4 carried orientation-tuned information and that their orientation and direction biases were also dominant in the L4 neuron population, suggesting that these neurons may inherit their selectivity from tuned thalamic inputs. Cortical neurons in all layers exhibited sharper tuning than thalamic boutons and a greater diversity of preferred orientations. Our results provide data-rich constraints for refining mechanistic models of cortical computation.