Cortical layering is a hallmark of the mammalian neocortex and a major determinant of local synaptic circuit organization in sensory systems. In motor cortex, the laminar organization of cortical circuits has not been resolved, yet their input-output operations are crucial for motor control. Here, we developed a general approach for estimating layer-specific connectivity in cortical circuits, and applied it to mouse motor cortex. From these data we computed a laminar presynaptic→postsynaptic connectivity matrix, W post,pre , revealing a complement of stereotypic pathways dominated by layer 2 outflow to deeper layers. Network modeling predicted, and experiments with disinhibited slices confirmed, that stimuli targeting upper but not lower cortical layers effectively evoked network-wide events. Thus, in motor cortex, descending excitation from a preamplifier-like network of upper-layer neurons drives output neurons in lower layers. Our analysis provides a quantitative wiring diagram framework for further investigation of the excitatory networks mediating cortical mechanisms of motor control.Motor cortex is centrally involved in mammalian motor behavior and the cortical control of movement. Motor cortex has long been studied in terms of its motor output, and much is known about how corticospinal neuron activity correlates with movement. The large-scale networks linking motor cortex with other cortical and subcortical motor systems are also well characterized. Multiple long-range excitatory input pathways converge on primary somatic motor cortex (M1). These include corticocortical projections (carrying ipsi-and contralateral sensorimotor information), thalamocortical projections (carrying cerebellar and basal ganglionic information via the thalamic ventrolateral nucleus, as well as sensory and other information via multiple additional thalamocortical pathways), and neuromodulatory projections from brainstem and other areas (reviewed in 1 ). Major outputs from M1 include projections to spinal/bulbar motor centers, striatum, thalamus, subthalamus, red nucleus, and pons. All excitatory neurons in M1 are pyramidal neurons projecting to one or several of these long-distance targets. Corticofugal outflow to the pyramidal/extrapyramidal motor systems and thalamus originates primarily from cells in middle and deeper layers, while corticocortical connections arise from cells in both upper and deeper layers.

Genetically encoded voltage indicators (GEVIs) enable monitoring of neuronal activity at high spatial and temporal resolution. However, the utility of existing GEVIs has been limited by the brightness and photostability of fluorescent proteins and rhodopsins. We engineered a GEVI, called Voltron, that uses bright and photostable synthetic dyes instead of protein-based fluorophores, thereby extending the number of neurons imaged simultaneously in vivo by a factor of 10 and enabling imaging for significantly longer durations relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In the mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously over a 15-minute period of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.

Active sensation requires the convergence of external stimuli with representations of body movements. We used mouse behavior, electrophysiology and optogenetics to dissect the temporal interactions between whisker movement, neural activity, and sensation of touch. We photostimulated layer 4 activity in single barrels in closed-loop with whisking. Mimicking touch-related neural activity caused illusory perception of an object at a particular location, but scrambling the timing of spikes over one whisking cycle (tens of milliseconds) did not abolish the illusion, indicating that knowledge of instantaneous whisker position is unnecessary for discriminating object locations. Illusions were induced only during bouts of directed whisking, when mice expected touch, and in the relevant barrel. Reducing activity biased behavior consistent with a spike count code for object detection at a particular location. Our results show that mice integrate coding of touch with movement over timescales of a whisking bout to produce perception of active touch.

Highlights d Spikes were recorded from cortical E, FS, SST, and VIP neurons during active touch d Whisking and touch activate FS neurons in the VPM thalamorecipient layers d Touch activates SST neurons with a delay d VIP neurons are excited during whisking