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Sensory navigation results from coordinated transitions between distinct behavioral programs. During chemotaxis in the Drosophila melanogaster larva, the detection of positive odor gradients extends runs while negative gradients promote stops and turns. This algorithm represents a foundation for the control of sensory navigation across phyla. In the present work, we identified an olfactory descending neuron, PDM-DN, which plays a pivotal role in the organization of stops and turns in response to the detection of graded changes in odor concentrations. Artificial activation of this descending neuron induces deterministic stops followed by the initiation of turning maneuvers through head casts. Using electron microscopy, we reconstructed the main pathway that connects the PDM-DN neuron to the peripheral olfactory system and to the pre-motor circuit responsible for the actuation of forward peristalsis. Our results set the stage for a detailed mechanistic analysis of the sensorimotor conversion of graded olfactory inputs into action selection to perform goal-oriented navigation. This work was initiated as part of the multi-lab Larval Olympiad conducted at the Janelia Research Campus. We are in debt to the work of S Reid (Louis lab) during the initial phase of the screen. We thank I Andrade, A Fushiki, J Jonaitis, I Larderet, P Schegel, C Schneider-Mizell and M Zwart for contributing to the EM reconstruction. We thank H Aberle for glutamate antibodies, as well as V Jayaraman, A Nern, S Pulver, G Rubin and J. Simpson for sharing fly lines. We thank V Jayaraman and R Francoville for training and access to the functional imaging setup. ML and DT acknowledges support of the Spanish Ministry of Economy and Competitiveness (MICINN and BFU2011-26208), ‘Centro de Excelencia Severo Ochoa 2013–2017’, the CERCA Programme/Generalitat de Catalunya, the EMBL/CRG Systems Biology Program and the University of California, Santa Barbara. IT was supported by the Marie Curie FP7 Programme through FLiACT (ITN). AK was supported by the ‘La Caixa’ International PhD Programme. JT, MZ and AC acknowledge funding from the Howard Hughes Medical Institute.

Over the last half century, work with flies, bees, and moths have revealed a number of visual guidance strategies for controlling different aspects of flight. Some algorithms, such as the use of pattern velocity in forward flight, are employed by all insects studied so far, and are used to control multiple flight tasks such as regulation of speed, measurement of distance, and positioning through narrow passages. Although much attention has been devoted to long-range navigation and homing in birds, until recently, very little was known about how birds control flight in a moment-to-moment fashion. A bird that flies rapidly through dense foliage to land on a branch—as birds often do—engages in a veritable three-dimensional slalom, in which it has to continually dodge branches and leaves, and find, and possibly even plan a collision-free path to the goal in real time. Each mode of flight from take-off to goal could potentially involve a different visual guidance algorithm. Here, we briefly review strategies for visual guidance of flight in insects, synthesize recent work from short-range visual guidance in birds, and offer a general comparison between the two groups of organisms.

The smooth pursuit eye movement system incorporates various control features enabling adaptation to specific tracking situations. In this work, we analyzed the interplay between two of these mechanisms: gain control and predictive pursuit. We tested human responses to high-frequency perturbations during step-ramp pursuit, as well as the pursuit of a periodically moving target. For the latter task, we found a nonlinear interaction between perturbation response and carrier acceleration. Responses to perturbations where the initial perturbation acceleration was contradirectional to carrier acceleration increased with carrier velocity, in a manner similar to that observed during step-ramp pursuit. In contrast, responses to perturbations with ipsidirectional initial perturbation and carrier acceleration were large for all carrier velocities. Modeling the pursuit system suggests that gain control and short-term prediction are separable elements. The observed effect may be explained by combining the standard gain control mechanism with a derivative-based short-term predictive mechanism. The nonlinear interaction between perturbation and carrier acceleration can be reproduced by assuming a signal saturation, which is acting on the derivative of the target velocity signal. Our results therefore argue for the existence of an internal estimate of target acceleration as a basis for a simple yet efficient short-term predictive mechanism.

A fundamental question in sensorimotor control concerns the transformation of spatial signals from the retina into eye and head motor commands required for accurate gaze shifts. Here, we investigated these transformations by identifying the spatial codes embedded in visually evoked and movement-related responses in the frontal eye fields (FEFs) during head-unrestrained gaze shifts. Monkeys made delayed gaze shifts to the remembered location of briefly presented visual stimuli, with delay serving to dissociate visual and movement responses. A statistical analysis of nonparametric model fits to response field data from 57 neurons (38 with visual and 49 with movement activities) eliminated most effector-specific, head-fixed, and space-fixed models, but confirmed the dominance of eye-centered codes observed in head-restrained studies. More importantly, the visual response encoded target location, whereas the movement response mainly encoded the final position of the imminent gaze shift (including gaze errors). This spatiotemporal distinction between target and gaze coding was present not only at the population level, but even at the single-cell level. We propose that an imperfect visual-motor transformation occurs during the brief memory interval between perception and action, and further transformations from the FEF's eye-centered gaze motor code to effector-specific codes in motor frames occur downstream in the subcortical areas.

The neural circuits in the optic tectum of Xenopus tadpoles are selectively responsive to looming visual stimuli that resemble objects approaching the animal at a collision trajectory. This selectivity is required for adaptive collision avoidance behavior in this species, but its underlying mechanisms are not known. In particular, it is still unclear how the balance between the recurrent spontaneous network activity and the newly arriving sensory flow is set in this structure, and to what degree this balance is important for collision detection. Also, despite the clear indication for the presence of strong recurrent excitation and spontaneous activity, the exact topology of recurrent feedback circuits in the tectum remains elusive. In this study we take advantage of recently published detailed cell-level data from tadpole tectum to build an informed computational model of it, and investigate whether dynamic activation in excitatory recurrent retinotopic networks may on its own underlie collision detection. We consider several possible recurrent connectivity configurations and compare their performance for collision detection under different levels of spontaneous neural activity. We show that even in the absence of inhibition, a retinotopic network of quickly inactivating spiking neurons is naturally selective for looming stimuli, but this selectivity is not robust to neuronal noise, and is sensitive to the balance between direct and recurrent inputs. We also describe how homeostatic modulation of intrinsic properties of individual tectal cells can change selectivity thresholds in this network, and qualitatively verify our predictions in a behavioral experiment in freely swimming tadpoles.

All animals use olfactory information to perform tasks essential to their survival. Odors typically activate multiple olfactory receptor neuron (ORN) classes and are therefore represented by the patterns of active ORNs. How the patterns of active ORN classes are decoded to drive behavior is under intense investigation. In this study, using Drosophila as a model system, we investigate the logic by which odors modulate locomotion. We designed a novel behavioral arena in which we could examine a fly’s locomotion under precisely controlled stimulus condition. In this arena, in response to similarly attractive odors, flies modulate their locomotion differently implying that odors have a more diverse effect on locomotion than was anticipated. Three features underlie odor-guided locomotion: First, in response to odors, flies modulate a surprisingly large number of motor parameters. Second, similarly attractive odors elicit changes in different motor programs. Third, different ORN classes modulate different subset of motor parameters. DOI: http://dx.doi.org/10.7554/eLife.11092.001, eLife digest Humans rely chiefly on vision to understand and navigate the world around them. But for many organisms, the world is dominated by their sense of smell. For these animals, everyday activities, like finding food, depend on being able to change behavior based on odor-based cues. To meet the challenges of detecting and discriminating between different odors, animals have many odorant receptors that bind to the odors, which are found on olfactory receptor neurons (ORNs). Each odor activates multiple ORNs, and different odors activate different combinations of ORNs. But it is not clear how activities from different classes of ORN are combined to create the perception of an odor or to guide behavior. Now, Jung et al. have investigated the logic by which odors can alter a fruit fly’s movements. The olfactory system of the fruit fly is organized along similar lines to that of a mammal, but is much simpler. Moreover, many genetic tools are available in fruit flies to allow neuroscientists to activate and inactivate specific neurons and assess the effect this has on behavior. The results suggest that odor-guided movement in fruit flies has two noteworthy features. Firstly, in the presence of odors, flies alter their walking in unexpectedly large number of ways. Therefore, one needs to consider many different factors, or “motor parameters”, to describe how odors affect a fly’s movement. For instance, instead of just walking faster or slower, a fly can change how long it stops (stop duration), how long it runs (run duration) and how fast it runs (run speed) – all of which will affect overall speed. Secondly, a single class of ORN can strongly affect some parameters (like run duration) without affecting others (like stop duration). These data indicate that the neural circuits involved have a modular organization in which each ORN class affects a subset of motor parameters, and each motor parameter is affected by a subset of ORN classes. These findings were largely unexpected. Jung et al.’s study focused on attractive odors. Future work will study repulsive odors to investigate if similar results are seen when studying repulsion versus attraction. DOI: http://dx.doi.org/10.7554/eLife.11092.002

Active eye movements can be exploited to build a visuomotor representation of the surrounding environment. Maintaining and improving such representation requires to update the internal model involved in the generation of eye movements. From this perspective, action and perception are thus tightly coupled and interdependent. In this work, we encoded the internal model for oculomotor control with an adaptive filter inspired by the functionality of the cerebellum. Recurrent loops between a feed-back controller and the internal model allow our system to perform accurate binocular saccades and create an implicit representation of the nearby space. Simulation results show that this recurrent architecture outperforms classical feedback-error-learning in terms of both accuracy and sensitivity to system parameters. The proposed approach was validated implementing the framework on an anthropomorphic robotic head. Saccadic movements are used to create a representation of the space.Accurate saccades are generated by a model of the cerebellum.A recurrent architecture is employed instead of the classical feed-back error learning.Proposed solution outperforms feedback-error-learning.Framework has been implemented successfully on humanoid robot.

© 2015 Davare, Zénon, Desmurget and Olivier. To reach for an object, we must convert its spatial location into an appropriate motor command, merging movement direction and amplitude. In humans, it has been suggested that this visuo-motor transformation occurs in a dorsomedial parieto-frontal pathway, although the causal contribution of the areas constituting the “reaching circuit” remains unknown. Here we used transcranial magnetic stimulation (TMS) in healthy volunteers to disrupt the function of either the medial intraparietal area (mIPS) or dorsal premotor cortex (PMd), in each hemisphere. The task consisted in performing step-tracking movements with the right wrist towards targets located in different directions and eccentricities; targets were either visible for the whole trial (Target-ON) or flashed for 200 ms (Target-OFF). Left and right mIPS disruption led to errors in the initial direction of movements performed towards contralateral targets. These errors were corrected online in the Target-ON condition but when the target was flashed for 200 ms, mIPS TMS manifested as a larger endpoint spreading. In contrast, left PMd virtual lesions led to higher acceleration and velocity peaks—two parameters typically used to probe the planned movement amplitude—irrespective of the target position, hemifield and presentation condition; in the Target-OFF condition, left PMd TMS induced overshooting and increased the endpoint dispersion along the axis of the target direction. These results indicate that left PMd intervenes in coding amplitude during movement preparation. The critical TMS timings leading to errors in direction and amplitude were different, namely 160–100 ms before movement onset for mIPS and 100–40 ms for left PMd. TMS applied over right PMd had no significant effect. These results demonstrate that, during motor preparation, direction and amplitude of goal-directed movements are processed by different cortical areas, at distinct timings, and according to a specific hemispheric organization. ARC (Actions de Recherche Concertées, Communauté Française de Belgique); Fondation Médicale Reine Elisabeth (FMRE) and from the Fonds de la Recherche Scientifique (FNRS–FDP); BBSRC David Phillips fellowship (UK), the Royal Society (UK); FWO Odysseus project (Fonds WetenschappelijkOnderzoek,Belgium).AZisaSeniorResearch AssociatesupportedbyINNOVIRIS.

We investigated how haptic information on object geometry is encoded in the parietal operculum (OP) and is used for guiding object-directed motor acts in humans. We tested the effects of conditioning single-pulse transcranial magnetic stimulation (spTMS) applied to the left OP on corticospinal excitability assessed by a test spTMS applied to the ipsilateral motor cortex (M1) 5 ms after conditioning spTMS. Participants explored the size of a graspable object visually or haptically and waited for a go-signal to grasp it in the dark. They received TMS during the delay phase. In a separate group of participants performing the same task, conditioning spTMS was applied to the ventral premotor cortex (vPM) 7 ms before test spTMS. Results showed that conditioning TMS over OP modulated M1 output according to the information on object size that had been acquired haptically but not visually. Vice versa, conditioning TMS over vPM modulated M1 output according to information on object size acquired by vision but not haptically. Moreover spTMS over OP produced a significant modulation of the upcoming reaching behavior only when the object had been explored haptically. We show that OP contains a haptic memory of objects' macrogeometry and the appropriate motor plan for grasping them.

Driver behavior and vehicle-road kinematics have been shown to change over prolonged periods of driving; however, the interaction between these two indices has not been examined. Here we develop a measure that examines how drivers turn the steering wheel relative to heading error velocity, which the authors call the relative steering wheel compensation (RSWC). The RSWC transiently changes on a short time scale coincident with a verbal query embedded within the study paradigm. In contrast, more traditional variables are dynamic over longer time scales consistent with previous research. The results suggest drivers alter their behavioral output (steering wheel correction) relative to sensory input (vehicle heading error velocity) on a distinct temporal scale and may reflect an interaction of alerting and control.

Neural mechanisms underlying nociception and pain perception are considered to serve the ultimate goal of limiting tissue damage. However, since pain usually occurs in complex environments and situations that call for elaborate control over behavior, simple avoidance is insufficient to explain a range of mammalian pain responses, especially in the presence of competing goals. In this integrative review we propose a Predictive Regulation and Action (PRA) model of acute pain processing. It emphasizes evidence that the nervous system is organized to anticipate potential pain and to adjust behavior before the risk of tissue damage becomes critical. Regulatory processes occur on many levels, and can be dynamically influenced by local interactions or by modulation from other brain areas in the network. The PRA model centers on neural substrates supporting the predictive nature of pain processing, as well as on finely-calibrated yet versatile regulatory processes that ultimately affect behavior. We outline several operational categories of pain behavior, from spinally-mediated reflexes to adaptive voluntary action, situated at various neural levels. An implication is that neural processes that track potential tissue damage in terms of behavioral consequences are an integral part of pain perception.

The article explores the possibilities of formalizing and explaining the mechanisms that support spatial and social perspective alignment sustained over the duration of a social interaction. The basic proposed principle is that in social contexts the mechanisms for sensorimotor transformations and multisensory integration (learn to) incorporate information relative to the other actor(s), similar to the "re-calibration" of visual receptive fields in response to repeated tool use. This process aligns or merges the co-actors' spatial representations and creates a "Shared Action Space" supporting key computations of social interactions and joint actions; for example, the remapping between the coordinate systems and frames of reference of the co-actors, including perspective taking, the sensorimotor transformations required for lifting jointly an object, and the predictions of the sensory effects of such joint action. The social re-calibration is proposed to be based on common basis function maps and could constitute an optimal solution to sensorimotor transformation and multisensory integration in joint action or more in general social interaction contexts. However, certain situations such as discrepant postural and viewpoint alignment and associated differences in perspectives between the co-actors could constrain the process quite differently. We discuss how alignment is achieved in the first place, and how it is maintained over time, providing a taxonomy of various forms and mechanisms of space alignment and overlap based, for instance, on automaticity vs. control of the transformations between the two agents. Finally, we discuss the link between low-level mechanisms for the sharing of space and high-level mechanisms for the sharing of cognitive representations.

Understanding how an organism's nervous system transforms sensory input into behavioral outputs requires recording and manipulating its neural activity during unrestrained behavior. Here we present an instrument to simultaneously monitor and manipulate neural activity while observing behavior in a freely moving textit{Caenorhabditis elegans}. Neural activity is recorded optically from cells expressing a calcium indicator, GCaMP3. Neural activity is manipulated optically by illuminating targeted neurons expressing the optogenetic protein Channelrhodopsin. Real-time computer vision software tracks the animal's behavior and identifies the location of targeted neurons in the nematode as it crawls. Patterned illumination from a digital micromirror device is used to selectively illuminate subsets of neurons for either calcium imaging or optogenetic stimulation. Real-time computer vision software constantly updates the illumination pattern in response to the worm's movement and thereby allows for independent optical recording or activation of different neurons in the worm as it moves freely. We use the instrument to directly observe the relationship between sensory neuron activation, interneuron dynamics and locomotion in the worm's mechanosensory circuit. We record and compare calcium transients in the backward locomotion command interneurons AVA, in response to optical activation of the anterior mechanosensory neurons ALM, AVM or both.

Research conducted over the last decades has established that the medial part of posterior parietal cortex is crucial for controlling visually guided actions in human and non-human primates. Within this cortical sector there is area V6A, a crucial node of the parietofrontal network involved in arm movement control in both monkeys and humans. However, the encoding of action-in-depth by V6A cells had been not studied till recently. Recent neurophysiological studies show the existence in V6A neurons of signals related to the distance of targets from the eyes. These signals are integrated, often at the level of single cells, with information about the direction of gaze, thus encoding spatial location in 3D space. Moreover, 3D eye position signals seem to be further exploited at two additional levels of neural processing: a) in determining whether targets are located in the peripersonal space or not, and b) in shaping the spatial tuning of arm movement related activity towards reachable targets. These findings are in line with studies in putative homolog regions in humans and together point to a role of medial posterior parietal cortex in encoding both the vergence angle of the eyes and peripersonal space. Besides this role in spatial encoding also in depth, several findings demonstrate the involvement of this cortical sector in non-spatial processes.

Fitts' law describes the fundamental trade-off between movement accuracy and speed: it states that the duration of reaching movements is a function of target size (TS) and distance. While Fitts' law has been extensively studied in ergonomics and has guided the design of human-computer interfaces, there have been few studies on its neuronal correlates. To elucidate sensorimotor cortical activity underlying Fitts' law, we implanted two monkeys with multielectrode arrays in the primary motor (M1) and primary somatosensory (S1) cortices. The monkeys performed reaches with a joystick-controlled cursor toward targets of different size. The reaction time (RT), movement time, and movement velocity changed with TS, and M1 and S1 activity reflected these changes. Moreover, modifications of cortical activity could not be explained by changes of movement parameters alone, but required TS as an additional parameter. Neuronal representation of TS was especially prominent during the early RT period where it influenced the slope of the firing rate rise preceding movement initiation. During the movement period, cortical activity was correlated with movement velocity. Neural decoders were applied to simultaneously decode TS and motor parameters from cortical modulations. We suggest that sensorimotor cortex activity reflects the characteristics of both the movement and the target. Classifiers that extract these parameters from cortical ensembles could improve neuroprosthetic control.

Reach movement planning involves the representation of spatial target information in different reference frames. Neurons at parietal and premotor stages of the cortical sensorimotor system represent target information in eye- or hand-centered reference frames, respectively. How the different neuronal representations affect behavioral parameters of motor planning and control, i.e. which stage of neural representation is relevant for which aspect of behavior, is not obvious from the physiology. Here, we test with a behavioral experiment if different kinematic movement parameters are affected to a different degree by either an eye- or hand-reference frame. We used a generalized anti-reach task to test the influence of stimulus-response compatibility (SRC) in eye- and hand-reference frames on reach reaction times, movement times, and endpoint variability. While in a standard anti-reach task, the SRC is identical in the eye- and hand-reference frames, we could separate SRC for the two reference frames. We found that reaction times were influenced by the SRC in eye- and hand-reference frame. In contrast, movement times were only influenced by the SRC in hand-reference frame, and endpoint variability was only influenced by the SRC in eye-reference frame. Since movement time and endpoint variability are the result of planning and control processes, while reaction times are consequences of only the planning process, we suggest that SRC effects on reaction times are highly suited to investigate reference frames of movement planning, and that eye- and hand-reference frames have distinct effects on different phases of motor action and different kinematic movement parameters.

‘Sensorimotor transformations’ are processes whereby sensory information is used to generate motor commands. One example is the ‘visuomotor map’ that transforms visual information about objects to motor commands that activates various muscles during grasping movements. In the first study we quantified the relative impact (or ‘weighting’) of visual and haptic information on the sensorimotor transformation and investigated the principles that regulates the weighting process. To do this, we let subjects perform a task in which the object seen (visual object) and the object grasped (haptic object) were physically never the same. When the haptic object became larger or smaller than the visual object, subjects in the following trials automatically adapted their maximum grip aperture (MGA) when reaching for the object. The adaptation process was quicker and relied more on haptic information when the haptic objects increased in size than when they decreased in size. As such, sensory weighting is molded to avoid prehension error. In the second study we investigated the degree to which the visuomotor map could be modified. Normally, the relationship between the visual size of the object (VO) and the MGA can be expressed as a linear relationship, where MGA = a + b * VO. Our results demonstrate that subjects inter- and extrapolate in the visuomotor map (that is, they are reluctant to abandon the linear relationship) and that the offset (a) but not the slope (b) can be modified. In the third study, we investigated how a ‘new’ sensorimotor transformation can be established and modified. We therefore replaced the normal input of visual information about object size with auditory information, where the size of the object was log-linearly related to the frequency of a tone. Learning of an audiomotor map consisted of three distinct phases: during the first stage (~10-15 trials) there were no overt signs of learning. During the second stage there was a period of fast learning where the MGA became scaled to the size of the object until the third stage where the slope was constant. The purpose of the fourth study was to investigate the sensory basis for the aperture adaptation process. To do that, the forces acting between the fingertips and the object was measured as the subjects adapted. Our results indicate that information about when the fingers contacts the object, that is, the ‘timing’ of contact, is likely to be used by the CNS to encode an unexpected object size. Since injuries and disease can affect the sensorimotor transformations that controls the hand, knowledge about how these processes are established and modified may be used to develop techniques for sensory substitution and other rehabilitation strategies.

An important function of the brain is to interpret incoming sensory information from the outside world to guide adaptive behavior. Understanding how and where sensory information is transformed into motor commands in a context- and learning-dependent manner is a key question in neuroscience. Which cortical areas are responsible for sensory perception, decision-making and motor execution is still a matter of discussion. During my Ph.D. I attempted to disentangle the coding of sensory versus decision and motor information by neurons in different brain regions along the transformation path of whisker sensory stimuli to licking motor output during goal-directed behaviors in mice. To address this question I combined electrophysiological recording of a large population of neurons across multiple brain areas with fine monitoring of behavior and movements, as well as time-resolved optogenetic manipulations. I first explored the sequence of cortical activity involved in transforming a brief whisker stimulus into delayed licking in mice. With coauthors, we discovered two crucial features related to activity evoked by whisker deflection. Firstly, an enhanced excitation of the secondary whisker motor cortex suggested its important role in connecting whisker sensory processing to lick motor planning. Secondly, a transient reduction of activity in the orofacial sensorimotor cortex helped to suppress premature licking. During the delay period, we observed widespread cortical activity that largely correlated with anticipatory movements. However, when accounting for these movements, we identified sustained activity in the frontal cortex that was essential for licking in the response period. Our results highlight key cortical nodes involved in motor planning. We next categorized neurons as regular or fast spiking, which we validated by optotagging method. We investigated how their activity changes before and after mice learn a task. We observed opposite changes in the whisker-evoked activity of regular versus fast spiking neurons in primary and secondary whisker motor cortices, but similar changes in primary and secondary orofacial motor cortices. Hence, altered excitation and inhibition in local circuits, combined with changes in long-range synaptic inputs may underlie delayed sensory-to-motor transformation. Finally, I recorded and systematically compared the neuronal activity of the cortical sensory input area (primary somatosensory cortex), a presumably decision area (medial prefrontal cortex), and the motor output area (tongue and jaw primary motor cortex) in the psychophysical whisker detection task. We have uncovered that the representation of sensory information, decision-making, and motor action is not a discrete function of each individual brain region, but rather distributed and encoded across all three regions. We proposed that the decision to lick after the whisker stimulus is a gradual process that involves the flow of information from wS1 to mPFC and tjM1. Importantly, we also observed that signal processing failures can occur at any level of this information flow. These findings highlight the complexity and distributed nature of the neural processes underlying decision-making and sensorimotor transformation. In this thesis, I have presented various findings that add to the existing knowledge and shed light on the neural circuits and computations involved in sensorimotor transformation in the mammalian brain.

The brain processes sensory information in a context- and learning-dependent manner for adaptive behavior. Through reward-based learning, relevant sensory stimuli can become linked to execution of specific actions associated with positive outcomes. The neuronal circuits involved in such goal-directed sensory-to-motor transformations remain to be precisely determined. Studying simple learned sensorimotor transformations in head-restrained mice offers the opportunity for detailed measurements of cellular activity during task performance. Here, we trained mice to lick a reward spout in response to a whisker deflection and an auditory tone. Through two-photon calcium imaging of retrogradely labeled neurons, we found that neurons located in primary whisker somatosensory barrel cortex projecting to secondary whisker somatosensory cortex had larger calcium signals than neighboring neurons projecting to primary whisker motor cortex in response to whisker deflection and auditory stimulation, as well as before spontaneous licking. Longitudinal imaging of the same neurons revealed that these projection-specific responses were relatively stable across 3 days. In addition, the activity of neurons projecting to secondary whisker somatosensory cortex was more highly correlated than for neurons projecting to primary whisker motor cortex. The large and correlated activity of neurons projecting to secondary whisker somatosensory cortex might enhance the pathway-specific signaling of important sensory information contributing to task execution. Our data support the hypothesis that communication between primary and secondary somatosensory cortex might be an early critical step in whisker sensory perception. More generally, our data suggest the importance of investigating projection-specific neuronal activity in distinct populations of intermingled excitatory neocortical neurons during task performance.