Keisuke Sehara

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.

The BraiDyn-BC (Brain Dynamics underlying emergence of Behavioral Change) Database offers an extensive, multimodal dataset that links wide-field calcium imaging of the mouse neocortex to comprehensive behavioral measurements during an operant conditioning task. This dataset includes 15 sessions spanning two weeks of motor skill learning, in which 25 mice were trained to pull a lever to obtain water rewards. Simultaneous high-speed videography captures body, facial, and eye movements, and environmental parameters are monitored. The dataset also features resting-state cortical activity and sensory-evoked responses, enhancing its utility for both learning-related and sensory-driven neural dynamics studies. Data are formatted in accordance with the Neurodata Without Borders (NWB) standard, ensuring compatibility with existing analysis tools and adherence to the FAIR principles. This resource enables in-depth investigations into the neural mechanisms underlying behavior and learning. The platform encourages collaborative research, supporting the exploration of rapid within-session learning effects, long-term behavioral adaptations, and neural circuit dynamics.

Neural activity across the dorsal neocortex of rodents is dominated by orofacial and limb movements, irrespective of whether the movements are task-relevant or task-irrelevant. To examine the extent to which movements and a primitive cognitive signal, i.e., reward expectancy, modulate the activity of multiple cortical areas in primates, we conducted unprecedented wide-field one-photon calcium imaging of frontoparietal and auditory cortices in common marmosets while they performed a classical conditioning task with two auditory cues associated with different reward probabilities. Licking, eye movement, and hand movement strongly modulated the neuronal activity after cue presentation in the motor and somatosensory cortices in accordance with the somatotopy. By contrast, the posterior parietal cortex and primary auditory cortex did not show much influence from licking. Licking increased the activity in the caudal part of the dorsal premotor cortex, but decreased the activity in the central and lateral parts of the rostral part of the dorsal premotor cortex (PMdr). Reward expectancy that was separable from both spontaneous and goal-directed movements was mainly represented in the medial part of PMdr. Our results suggest that the influence of movement on primate cortical activity varies across areas and movement types, and that the premotor cortex processes motor and cognitive information in different ways within further subdivided areas.

The use of head fixation has become routine in systems neuroscience. However, whether the behavior changes with head fixation, whether animals can learn aspects of a task while freely moving and transfer this knowledge to the head fixed condition, has not been examined in much detail. Here, we used a novel floating platform, the “Air-Track”, which simulates free movement in a real-world environment to address the effect of head fixation and developed methods to accelerate training of behavioral tasks for head fixed mice. We trained mice in a Y maze two choice discrimination task. One group was trained while head fixed and compared to a separate group that was pre-trained while freely moving and then trained on the same task while head fixed. Pre-training significantly reduced the time needed to relearn the discrimination task while head fixed. Freely moving and head fixed mice displayed similar behavioral patterns, however, head fixation significantly slowed movement speed. The speed of movement in the head fixed mice depended on the weight of the platform. We conclude that home-cage pre-training improves learning performance of head fixed mice and that while head fixation obviously limits some aspects of movement, the patterns of behavior observed in head fixed and freely moving mice are similar.

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.

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 often coordinated with whisking. Here we trained head fixed mice – navigating a floating Airtrack plus maze – to overcome their directional preference and use cues indicating the direction of movement expected in each trial. Once cued, mice had to move backward out of a lane, then turn in the correct direction, and enter a new lane. In this simple paradigm, as mice begin to move backward, they position their whiskers asymmetrically: whiskers on one side of the face protract, and on the other side they retract. This asymmetry reflected the turn direction. Additionally, on each trial, mice move their eyes conjugately in the direction of the upcoming turn. Not only do they move their eyes, but saccadic eye movement is coordinated with the asymmetric positioning of the whiskers. Our analysis shows that the asymmetric positioning of the whiskers predicts the direction of turn that mice will make at an earlier stage than eye movement does. We conclude that, when mice move or plan to move in complex real-world environments, their motor plan and behavioral state can be read out in the movement of both their whiskers and eyes. Significance statement Natural behavior occurs in multiple sensory and motor dimensions. When we move through our environment we coordinate the movement of our body, head, eyes and limbs. Here we show that when mice navigate a maze, they move their whiskers and eyes; they position their whiskers asymmetrically, and use saccadic eye movements. The position of the eyes and whiskers predicts the direction mice will turn in. This work suggests that when mice move through their environment, they coordinate the visual-motor and somatosensory-motor systems.

Computer vision approaches have made significant inroads into offline tracking of behavior and estimating animal poses. In particular, because of their versatility, deep-learning approaches have been gaining attention in behavioral tracking without any markers. Here, we developed an approach using DeepLabCut for real-time estimation of movement. We trained a deep-neural network (DNN) offline with high-speed video data of a mouse whisking, then transferred the trained network to work with the same mouse, whisking in real-time. With this approach, we tracked the tips of three whiskers in an arc and converted positions into a TTL output within behavioral time scales, i.e., 10.5 ms. With this approach, it is possible to trigger output based on movement of individual whiskers, or on the distance between adjacent whiskers. Flexible closed-loop systems like the one we have deployed here can complement optogenetic approaches and can be used to directly manipulate the relationship between movement and neural activity.

A central function of the brain is to plan, predict, and imagine the effect of movement in a dynamically changing environment. Here we show that in mice head-fixed in a plus-maze, floating on air, and trained to pick lanes based on visual stimuli, the asymmetric movement, and position of whiskers on the two sides of the face signals whether the animal is moving, turning, expecting reward, or licking. We show that (1) whisking asymmetry is coordinated with behavioral state, and that behavioral state can be decoded and predicted based on asymmetry, (2) even in the absence of tactile input, whisker positioning and asymmetry nevertheless relate to behavioral state, and (3) movement of the nose correlates with asymmetry, indicating that facial expression of the mouse is itself correlated with behavioral state. These results indicate that the movement of whiskers, a behavior that is not instructed or necessary in the task, can inform an observer about what a mouse is doing in the maze. Thus, the position of these mobile tactile sensors reflects a behavioral and movement-preparation state of the mouse.SIGNIFICANCE STATEMENTBehavior is a sequence of movements, where each movement can be related to or can trigger a set of other actions. Here we show that, in mice, the movement of whiskers (tactile sensors used to extract information about texture and location of objects) is coordinated with and predicts the behavioral state of mice: that is, what mice are doing, where they are in space, and where they are in the sequence of behaviors.