Robert N. S. Sachdev

Orienting coordinates movements of the eyes, whiskers, nose, and other effectors, but how the superior colliculus (SC) recruits these components over time remains unclear. We combined unilateral optogenetic activation of SC GABAergic neurons with high-speed tracking of facial movements and Neuropixels recordings to examine SC-evoked orienting in head-fixed mice. Stimulation recruited movements of the whiskers, nose, eyes, and pupil. Horizontal eye and nose movements were directed contralateral to the stimulated hemisphere, whereas vertical eye movements, pupil dilation, and whisker protraction did not differ significantly between stimulation sides. Nose and whisker movements generally preceded eye movements, followed by slower pupil dilation, revealing a temporally organized response. Recordings from the SC contralateral to the stimulated hemisphere revealed heterogeneous neuronal responses comprising short-latency excitation and delayed excitation or inhibition. Short-latency excitation was similar on trials with and without evoked movements, whereas delayed excitation was greater on trials that evoked eye or nose movements. Neurons modulated during spontaneous nose movements showed corresponding optogenetically evoked responses, linking stimulation-induced activity to endogenous movement-related activity. Thus, activation of SC GABAergic neurons initiates evolving population activity that recruits a coordinated sequence of orienting movements.

Flexible learning relies on integrating sensory and contextual information to adjust behavioral output in different environments. The anterolateral motor cortex (ALM) is a frontal area critical for action selection in rodents. We found that inputs critical to decision-making converge on the apical tuft dendrites of layer 5b pyramidal neurons in ALM. We therefore investigated the role of these dendrites in a rule-switching paradigm. Activation of dendrite-inhibiting layer 1 interneurons impaired relearning, without affecting previously learned behavior. This inhibition profoundly suppressed global calcium activity in dendritic shafts but not local transients in spines, while additionally reducing burst firing. Moreover, excitatory synaptic inputs to tuft dendrites exhibited rule-dependent clustering. We conclude that dendritic calcium signaling is a key computational component of flexible learning.

Understanding how motor cortical circuits flexibly transform sensory and contextual information into behavior remains a central challenge. Whether neurons in primary vibrissal motor cortex (M1) multiplex across behaviors or are selectively engaged in context-specific actions is still unclear. To address this question, we trained mice on multiple vibrissal sensorimotor tasks, including a cue-triggered whisking-to-touch task and an air-puff–triggered licking task. Fast-spiking and regular-spiking neurons in layers 2/3 and 5 in vM1 responded robustly within ∼15 ms to air-puff stimulation. In contrast, these same neurons were only weakly modulated during goal-directed whisking-to-touch behavior. Unexpected air-puffs evoked responses in fewer neurons than expected stimuli. Trials in which stimulation elicited whisker movements produced smaller neural responses than trials without whisking. Stimulus-evoked activity in M1 was organized along a spectrum of response profiles with neurons exhibiting varying responses dynamics that cut across laminar and physiological distinctions. This organization of responses is consistent with context-dependent recruitment of M1 neurons. Together, these findings indicate that M1 activity is more closely associated with the selection of specific behavioral responses than with generalized sensory-motor encoding. Significance: How motor cortex links sensory input to behavior remains a central question in neuroscience. Do neurons that respond to vibrissal stimuli also participate in whisker-based behaviors, or do they reflect distinct functional states? Here, we show that activity in vM1 is context dependent. Across multiple behaviors, sensory inputs recruit different neuronal populations depending on behavioral context: air-puff stimuli evoke rapid and robust responses, whereas the same neurons are only weakly engaged during goal-directed whisking-to-touch. In addition, expected and unexpected stimuli activate partially distinct ensembles, and sensory responses are attenuated when stimuli directly trigger movement. These findings indicate that M1 does not uniformly encode sensory input; instead, activity reflects context-dependent action selection where neuronal populations are engaged according to behavioral demands.

Memory consolidation relies on activity-dependent neuronal plasticity, particularly in deep-layer cortical neurons that integrate long-range inputs from medial temporal lobe (MTL) structures. In the neocortex, apical tuft dendrites of layer 5b pyramidal neurons receive direct input from the MTL within cortical layer 1, and their activation is critical for associative learning. However, the molecular mechanisms that enable learning-induced plasticity in these neurons remain poorly understood. Here, we demonstrate that activity-dependent, mTORC1-regulated translation in layer 5b neurons contributes to learning and memory. Using in vivo paradigms such as exposure to an enriched environment (EE) and in vitro models of network activation by chemical long-term potentiation (cLTP), combined with cell type-specific translational profiling (RiboTag), we identify candidate mRNAs associated with experience-dependent plasticity. We further show that pharmacological inhibition of canonical mTORC1 signaling during memory-relevant tasks abrogated memory consolidation. Our findings identify the mTORC1 pathway as a central regulator of learning-induced protein translation and cortical plasticity.

A key function of the brain is to move the body through a rich, complex environment. When rodents engage with their environment, they move their whiskers as they extract tactile information. Even though the study of whisking has a long history, the details of individual whisker movements bilaterally, of nose movement, of stereotypy and variability in an active whisking to touch behavior are unknown. Here we trained five head-fixed male and 11 female mice in a go-cue task to move a whisker to touch a sensor. Our analysis of orofacial movements shows that mice specifically control movement of the whisker they use to touch and that as they move their whiskers, they move their nose and apply forces on the head post in a manner that reflects the behavioral epoch, i.e., whether go-cue triggered movement had begun or a whisker was touching the sensor. Importantly, mice control the setpoint, amplitude, and frequency of movement of whiskers bilaterally and individually. Additionally, even though mice achieved the goal of the task—to touch the sensor within 2 s—how they coordinated movement of the nose and forces on head post with movement of individual whiskers was stereotyped and related to the distance they needed to move a whisker to touch the sensor. Our work shows how stereotyped mouse behavior can be, and it emphasizes both the level of fine motor control mice can exert over individual whiskers and the extent of facial movements in a goal-directed whisking-to-touch task.

Behavioral responses to threat — such as fleeing, freezing, or fighting—can be innate, learned, and strongly shaped by context or competing goals. Here, we asked whether exposure to an ecologically relevant predator obligatorily elicits canonical defensive behaviors across behavioral contexts. We examined predator responses in mice across four experimental conditions: one novel head-fixed reward-driven foraging task and three established paradigms in freely moving animals. In the head-fixed condition, water-deprived mice were trained to walk on a treadmill controlling a virtual environment and water reward delivery and were subsequently exposed to a live rat positioned above the lick spout. Despite the presence of the predator, most mice (5 of 7) maintained foraging performance at baseline levels. However, individual mice exhibited significant, coordinated changes in running speed, pupil diameter, eye movements, and posture, indicating engagement with the threat. To assess how context influences predator responses, we exposed 36 naïve, freely moving mice to fear-inducing stimuli, including looming visual cues, rat odor, and a live rat. Even under these conditions, defensive behaviors were variable: only a subset of mice displayed avoidance or escape, and when presented with a freely moving rat, approximately half of the mice avoided the predator. Together, these findings show that predator threat does not elicit a uniform or obligatory defensive repertoire in mice. Instead, defensive responses are expressed flexibly, and are shaped by environmental constraints, task demands, and individual variability. These results challenge the assumption that innate fear behaviors are automatically triggered by predator encounters. Graphical Using a head-fixed, reward-based foraging task and complementary freely moving paradigms, we show that mouse responses to predator-related stimuli are variable and context dependent, with limited expression of canonical defensive behaviors such as freezing or flight.

Accurate assessment of post-stroke deficits is vital in translational research. Recent advances in machine learning provide unprecedented precision in quantifying rodent motor behavior post-stroke. However, the extent to which these tools can detect lesion-specific upper extremity deficits remains unclear. Using proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT), we assessed post-stroke impairments in mice through the Staircase test. Lesion locations were identified using 7T-MRI. Machine learning was applied to reconstruct kinematic trajectories using MouseReach , a data-processing toolbox. This yielded 30 refined outcome parameters effectively capturing motor deficits. Lesion reconstructions located ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval was altered in both cases but did not correlate with stroke volume or ischemia extent. Instead, cortical ischemia was characterized by increased hand slips and modified reaching success. Striatal ischemia led to progressively prolonged reach durations, mirroring delayed symptom onset in basal ganglia strokes. In summary, refined machine learning-based movement analysis revealed specific deficits in mice after cortical and striatal ischemia. These findings emphasize the importance of thorough behavioral profiling in preclinical stroke research to increase translational validity of behavioral assessments.

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

A key function of the brain is to move the body through a rich, complex environment. When rodents engage with their environment, they move their whiskers as they extract tactile information. Even though the study of whisking has a long history, the details of individual whisker movements bilaterally, of nose movement, of stereotypy and variability in an active whisking to touch task are unknown. Here we trained head fixed mice in a simple go-cue task to move a whisker on one side of the face to touch a sensor and tracked facial movements. Our analysis shows that mice specifically control movement of the whisker they use to touch and that as they move their whiskers, they move their nose and apply forces on the head-post in a manner that reflects the behavioral epoch, i.e. whether go cue triggered movement had begun, or a whisker was touching the sensor. Importantly, mice control the setpoint, amplitude and frequency of movement of whiskers bilaterally and individually. Additionally, even though mice achieved the goal of the task -- to touch the sensor within 2 seconds -- how they coordinated movement of the nose and forces on head post with movement of individual whiskers was stereotyped and related to the distance they needed to move a whisker to touch the sensor. Our work shows how stereotyped mouse behavior can be, and it emphasizes both the level of fine motor control mice can exert over individual whiskers and the extent of facial movements in a goal-directed whisking-to-touch task.

Navigation through complex environments requires motor planning, motor preparation, and the coordination between multiple sensory–motor modalities. For example, the stepping motion when we walk is coordinated with motion of the torso, arms, head, and eyes. In rodents, movement of the animal through the environment is coordinated with whisking. Even head-fixed mice navigating a plus maze position their whiskers asymmetrically with the bilateral asymmetry signifying the upcoming turn direction. Here we report that, in addition to moving their whiskers, on every trial mice also move their eyes conjugately in the direction of the upcoming turn. Not only do mice move their eyes, but they coordinate saccadic eye movement with the asymmetric positioning of the whiskers. Our analysis shows that asymmetric positioning of whiskers predicted the turn direction that mice will make at an earlier stage than eye movement. Consistent with these results, our observations also revealed that whisker asymmetry increases before saccadic eye movement. Importantly, this work shows that when rodents plan for active behavior, their motor plans can involve both eye and whisker movement. We conclude that, when mice are engaged in and moving through complex real-world environments, their behavioral state can be read out in the movement of both their whiskers and eyes.