The Sensorimotor Basis of Whisker-Guided Anteroposterior Object Localization in Head-Fixed Mice

Whisking and locomotion are jointly represented in superior colliculus neurons

Active sensation requires the brain to interpret external stimuli against an ongoing estimate of body position. While internal estimates of body position are often ascribed to the cerebral cortex, we examined the midbrain superior colliculus (SC), due to its close relationship with the sensory periphery as well as higher, motor-related brain regions. Using high-density electrophysiology and movement tracking, we discovered that the on-going kinematics of whisker motion and locomotion speed accurately predict the firing rate of mouse SC neurons. Neural activity was best predicted by movements occurring either in the past, present, or future, indicating that the SC population continuously estimates a trajectory of self-motion. A combined representation of slow and fast whisking features predicted absolute whisker angle at high temporal resolution. Sensory reafference played at least a partial role in shaping this feature tuning. Taken together, these data indicate that the SC contains a joint representation of whisking and locomotor features that is potentially useful in guiding complex orienting movements involving the face and limbs.

Syngap1 Promotes Cognitive Function through Regulation of Cortical Sensorimotor Dynamics

Perception, a cognitive construct, emerges through sensorimotor integration (SMI). The genetic mechanisms that shape SMI required for perception are unknown. Here, we demonstrate in mice that expression of the autism/intellectual disability gene, Syngap1, in cortical excitatory neurons is required for formation of somatomotor networks that promote SMI-mediated perception. Cortical Syngap1 expression was necessary and sufficient for setting tactile sensitivity, sustaining tactile object exploration, and promoting tactile learning. Mice with deficient Syngap1 expression exhibited impaired neural dynamics induced by exploratory touches within a cortical-thalamic network known to promote attention and perception. Disrupted neuronal dynamics were associated with circuit-specific long-range synaptic connectivity abnormalities. Our data support a model where autonomous Syngap1 expression in cortical excitatory neurons promotes cognitive abilities through assembly of circuits that integrate temporally-overlapping sensory and motor signals, a process that promotes perception and attention. These data provide systems-level insights into the robust association between Syngap1 expression and cognitive ability.

Whisker kinematics in the cerebellum

The whisker system is widely used as a model system for understanding sensorimotor integration. Purkinje cells in the crus regions of the cerebellum have been reported to linearly encode whisker midpoint, but it is unknown whether the paramedian and simplex lobules as well as their target neurons in the cerebellar nuclei also encode whisker kinematics and if so which ones. Elucidating how these kinematics are represented throughout the cerebellar hemisphere is essential for understanding how the cerebellum coordinates multiple sensorimotor modalities. Exploring the cerebellar hemisphere of mice using optogenetic stimulation, we found that whisker movements can be elicited by stimulation of Purkinje cells in not only crus1 and crus2, but also in the paramedian lobule and lobule simplex; activation of cells in the medial paramedian lobule had on average the shortest latency, whereas that of cells in lobule simplex elicited similar kinematics as those in crus1 and crus2. During spontaneous whisking behaviour, simple spike activity correlated in general better with velocity than position of the whiskers, but it varied between protraction and retraction as well as per lobule. The cerebellar nuclei neurons targeted by the Purkinje cells showed similar activity patterns characterized by a wide variety of kinematic signals, yet with a dominance for velocity. Taken together, our data indicate that whisker movements are much more prominently and diversely represented in the cerebellar cortex and nuclei than assumed, highlighting the rich repertoire of cerebellar control in the kinematics of movements that can be engaged during coordination. KEY POINTS: Excitation of Purkinje cells throughout the cerebellar hemispheres induces whisker movement, with the shortest latency and longest duration within the paramedian lobe. Purkinje cells have differential encoding for the fast and slow components of whisking. Purkinje cells encode not only the position but also the velocity of whiskers. Purkinje cells with high sensitivity for whisker velocity are preferentially located in the medial part of lobule simplex, crus1 and lateral paramedian. In the downstream cerebellar nuclei, neurons with high sensitivity for whisker velocity are located at the intersection between the medial and interposed nucleus.

Interchangeable Role of Motor Cortex and Reafference for the Stable Execution of an Orofacial Action

Animals interact with their environment through mechanically active, mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability or prehension would be profoundly impeded. The nervous system may keep track of the position of a sensorimotor organ via two complementary feedback mechanisms-peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training male rats to place one of their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, except in the absence of peripheral reafference to maintain motor stability. Finally, the red nucleus, which receives descending inputs from motor cortex and cerebellum and projects to facial motoneurons, is critically involved in the execution of the vibrissa positioning task. All told, our results point toward the existence of an internal model that requires either peripheral reafference or motor cortex to optimally drive voluntary motion.SIGNIFICANCE STATEMENT How does an animal know where a mechanically active, mobile sensor lies relative to its body? We address this basic question in sensorimotor integration using the motion of the vibrissae in rats. We show that rats can learn to reliably position their vibrissae in the absence of sensory feedback or in the absence of motor cortex. Yet, when both sensory feedback and motor cortex are absent, motor precision is degraded. This suggests the existence of an internal model able to operate in closed- and open-loop modes, requiring either motor cortex or sensory feedback to maintain motor stability.

Demonstration of three-dimensional contact point determination and contour reconstruction during active whisking behavior of an awake rat

The rodent vibrissal (whisker) system has been studied for decades as a model of active touch sensing. There are no sensors along the length of a whisker; all sensing occurs at the whisker base. Therefore, a large open question in many neuroscience studies is how an animal could estimate the three-dimensional (3D) location at which a whisker makes contact with an object. In the present work we simulated the shape of a real rat whisker to demonstrate the existence of several unique mappings from triplets of mechanical signals at the whisker base to the three-dimensional whisker-object contact point. We then used high speed video to record whisker deflections as an awake rat whisked against a peg, and used the mechanics resulting from those deflections to extract the contact points along the peg surface. These results demonstrate that measurement of specific mechanical triplets at the base of a biological whisker can enable 3D contact point determination during natural whisking behavior. The approach is viable even though the biological whisker has non-ideal, non-planar curvature, and even given the rat’s real-world choices of whisking parameters. Visual intuition for the quality of the approach is provided in a video that shows the contour of the peg gradually emerging during active whisking behavior.

Sensorimotor strategies and neuronal representations for shape discrimination

Humans and other animals can identify objects by active touch, requiring the coordination of exploratory motion and tactile sensation. Both the motor strategies and neural representations employed could depend on the subject's goals. We developed a shape discrimination task that challenged head-fixed mice to discriminate concave from convex shapes. Behavioral decoding revealed that mice did this by comparing contacts across whiskers. In contrast, a separate group of mice performing a shape detection task simply summed up contacts over whiskers. We recorded populations of neurons in the barrel cortex, which processes whisker input, and found that individual neurons across the cortical layers encoded touch, whisker motion, and task-related signals. Sensory representations were task-specific: during shape discrimination, but not detection, neurons responded most to behaviorally relevant whiskers, overriding somatotopy. Thus, sensory cortex employs task-specific representations compatible with behaviorally relevant computations.

Of mice and monkeys: Somatosensory processing in two prominent animal models

Our understanding of the neural basis of somatosensation is based largely on studies of the whisker system of mice and rats and the hands of macaque monkeys. Results across these animal models are often interpreted as providing direct insight into human somatosensation. Work on these systems has proceeded in parallel, capitalizing on the strengths of each model, but has rarely been considered as a whole. This lack of integration promotes a piecemeal understanding of somatosensation. Here, we examine the functions and morphologies of whiskers of mice and rats, the hands of macaque monkeys, and the somatosensory neuraxes of these three species. We then discuss how somatosensory information is encoded in their respective nervous systems, highlighting similarities and differences. We reflect on the limitations of these models of human somatosensation and consider key gaps in our understanding of the neural basis of somatosensation.

Predicting Grating Orientations With Cross-Frequency Coupling and Least Absolute Shrinkage and Selection Operator in V1 and V4 of Rhesus Monkeys

Orientation selectivity, as an emergent property of neurons in the visual cortex, is of critical importance in the processing of visual information. Characterizing the orientation selectivity based on neuronal firing activities or local field potentials (LFPs) is a hot topic of current research. In this paper, we used cross-frequency coupling and least absolute shrinkage and selection operator (LASSO) to predict the grating orientations in V1 and V4 of two rhesus monkeys. The experimental data were recorded by utilizing two chronically implanted multi-electrode arrays, which were placed, respectively, in V1 and V4 of two rhesus monkeys performing a selective visual attention task. The phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC) were employed to characterize the cross-frequency coupling of LFPs under sinusoidal grating stimuli with different orientations. Then, a LASSO logistic regression model was constructed to predict the grating orientation based on the strength of PAC and AAC. Moreover, the cross-validation method was used to evaluate the performance of the model. It was found that the average accuracy of the prediction based on the combination of PAC and AAC was 73.9%, which was higher than the predicting accuracy with PAC or AAC separately. In conclusion, a LASSO logistic regression model was introduced in this study, which can predict the grating orientations with relatively high accuracy by using PAC and AAC together. Our results suggest that the principle behind the LASSO model is probably an alternative direction to explore the mechanism for generating orientation selectivity.

Independent representations of self-motion and object location in barrel cortex output

During active tactile exploration, the dynamic patterns of touch are transduced to electrical signals and transformed by the brain into a mental representation of the object under investigation. This transformation from sensation to perception is thought to be a major function of the mammalian cortex. In primary somatosensory cortex (S1) of mice, layer 5 (L5) pyramidal neurons are major outputs to downstream areas that influence perception, decision-making, and motor control. We investigated self-motion and touch representations in L5 of S1 with juxtacellular loose-seal patch recordings of optogenetically identified excitatory neurons. We found that during rhythmic whisker movement, 54 of 115 active neurons (47%) represented self-motion. This population was significantly more modulated by whisker angle than by phase. Upon active touch, a distinct pattern of activity was evoked across L5, which represented the whisker angle at the time of touch. Object location was decodable with submillimeter precision from the touch-evoked spike counts of a randomly sampled handful of these neurons. These representations of whisker angle during self-motion and touch were independent, both in the selection of which neurons were active and in the angle-tuning preference of coactive neurons. Thus, the output of S1 transiently shifts from a representation of self-motion to an independent representation of explored object location during active touch.

An optimized acetylcholine sensor for monitoring in vivo cholinergic activity

The ability to directly measure acetylcholine (ACh) release is an essential step toward understanding its physiological function. Here we optimized the GRAB_ACh (GPCR-activation-based ACh) sensor to achieve substantially improved sensitivity in ACh detection, as well as reduced downstream coupling to intracellular pathways. The improved version of the ACh sensor retains the subsecond response kinetics, physiologically relevant affinity and precise molecular specificity for ACh of its predecessor. Using this sensor, we revealed compartmental ACh signals in the olfactory center of transgenic flies in response to external stimuli including odor and body shock. Using fiber photometry recording and two-photon imaging, our ACh sensor also enabled sensitive detection of single-trial ACh dynamics in multiple brain regions in mice performing a variety of behaviors.

Behavioral and Neural Bases of Tactile Shape Discrimination Learning in Head-Fixed Mice

Tactile shape recognition requires the perception of object surface angles. We investigate how neural representations of object angles are constructed from sensory input and how they reorganize across learning. Head-fixed mice learned to discriminate object angles by active exploration with one whisker. Calcium imaging of layers 2-4 of the barrel cortex revealed maps of object-angle tuning before and after learning. Three-dimensional whisker tracking demonstrated that the sensory input components that best discriminate angles (vertical bending and slide distance) also have the greatest influence on object-angle tuning. Despite the high turnover in active ensemble membership across learning, the population distribution of object-angle tuning preferences remained stable. Angle tuning sharpened, but only in neurons that preferred trained angles. This was correlated with a selective increase in the influence of the most task-relevant sensory component on object-angle tuning. These results show how discrimination training enhances stimulus selectivity in the primary somatosensory cortex while maintaining perceptual stability.

Touch: Fluctuating Waves of Perception

Does sensory input flow into the brain as a stream, or does it come in waves? New research shows that tactile information in the cortex rises and falls in phase with the forward and back motion of whiskers during surface exploration.

Cortical Coding of Whisking Phase during Surface Whisking

In rodent whisker sensation, whisker position signals, including whisking phase, are integrated with touch signals to enable spatially accurate tactile perception, but other functions of phase coding are unclear. We investigate how phase coding affects the neural coding of surface features during surface whisking. In mice performing rough-smooth discrimination, S1 units exhibit much stronger phase tuning during surface whisking than in prior studies of whisking in air. Among putative pyramidal cells, preferred phase tiles phase space, but protraction phases are strongly over-represented. Fast-spiking units are nearly all protraction tuned. This protraction bias increases the coding of stick-slip whisker events during protraction, suggesting that surface features are preferentially encoded during protraction. Correspondingly, protraction-tuned units encode rough-smooth texture better than retraction-tuned units and encode the precise spatial location of surface ridges with higher acuity. This suggests that protraction is the main information-gathering phase for high-resolution surface features, with phase coding organized to support this function.

Context-Dependent Sensory Processing across Primary and Secondary Somatosensory Cortex

To interpret the environment, our brain must evaluate external stimuli against internal representations from past experiences. How primary (S1) and secondary (S2) somatosensory cortices process stimuli depending on recent experiences is unclear. Using simultaneous multi-area population imaging of projection neurons and focal optogenetic inactivation, we studied mice performing a whisker-based working memory task. We find that activity reflecting a current stimulus, the recollection of a previous stimulus (cued recall), and the stimulus category are distributed across S1 and S2. Despite this overlapping representation, S2 is important for processing cued recall responses and transmitting these responses to S1. S2 network properties differ from S1, wherein S2 persistently encodes cued recall and the stimulus category under passive conditions. Although both areas encode the stimulus category, only information in S1 is important for task performance through pathways that do not necessarily include S2. These findings reveal both distributed and segregated roles for S1 and S2 in context-dependent sensory processing.

Generalization of Object Localization From Whiskers to Other Body Parts in Freely Moving Rats

Rats can be trained to associate relative spatial locations of objects with the spatial location of rewards. Here we ask whether rats can localize static silent objects with other body parts in the dark, and if so with what resolution. We addressed these questions in trained rats, whose interactions with the objects were tracked at high-resolution before and after whisker trimming. We found that rats can use other body parts, such as trunk and ears, to localize objects. Localization resolution with non-whisking body parts (henceforth, ‘body’) was poorer than that obtained with whiskers, even when left with a single whisker at each side. Part of the superiority of whiskers was obtained via the use of multiple contacts. Transfer from whisker to body localization occurred within one session, provided that body contacts with the objects occurred before whisker trimming, or in the next session otherwise. This transfer occurred whether temporal cues were used for discrimination or when discrimination was based on spatial cues alone. Rats’ decision in each trial was based on the sensory cues acquired in that trial and on decisions and reward locations in previous trials. When sensory cues were acquired by body contacts, rat decisions relied more on the reward location in previous trials. Overall, the results suggest that rats can generalize the idea of relative object location across different body parts, while preferring to rely on whiskers-based localization, which occurs earlier and conveys higher resolution.