@article {67657, title = {Disrupting cortico-cerebellar communication impairs dexterity.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Jul 29}, abstract = {

To control reaching, the nervous system must generate large changes in muscle activation to drive the limb toward the target, and must also make smaller adjustments for precise and accurate behavior. Motor cortex controls the arm through projections to diverse targets across the central nervous system, but it has been challenging to identify the roles of cortical projections to specific targets. Here, we selectively disrupt cortico-cerebellar communication in the mouse by optogenetically stimulating the pontine nuclei in a cued reaching task. This perturbation did not typically block movement initiation, but degraded the precision, accuracy, duration, or success rate of the movement. Correspondingly, cerebellar and cortical activity during movement were largely preserved, but differences in hand velocity between control and stimulation conditions predicted from neural activity were correlated with observed velocity differences. These results suggest that while the total output of motor cortex drives reaching, the cortico-cerebellar loop makes small adjustments that contribute to the successful execution of this dexterous movement.

}, issn = {2050-084X}, doi = {10.7554/eLife.65906}, author = {Guo, Jian-Zhong and Sauerbrei, Britton A and Cohen, Jeremy D and Mischiati, Matteo and Graves, Austin R and Pisanello, Ferruccio and Branson, Kristin M and Hantman, Adam W} } @article {65259, title = {Cortical pattern generation during dexterous movement is input-driven.}, journal = {Nature}, volume = {577}, year = {2020}, month = {2020 Jan 16}, pages = {386-91}, abstract = {

The motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centres. Local cortical dynamics are thought to shape these patterns throughout movement execution. External inputs have been implicated in setting the initial state of the motor cortex, but they may also have a pattern-generating role. Here we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching or failed to generate this pattern. The difference in these two outcomes was probably a result of external inputs. We directly investigated the role of inputs by inactivating the thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly interacting brain regions.

}, issn = {1476-4687}, doi = {10.1038/s41586-019-1869-9}, author = {Sauerbrei, Britton A and Guo, Jian-Zhong and Cohen, Jeremy D and Mischiati, Matteo and Guo, Wendy and Kabra, Mayank and Verma, Nakul and Mensh, Brett and Branson, Kristin and Hantman, Adam W} } @article {65792, title = {The Statistical Structure of the Hippocampal Code for Space as a Function of Time, Context, and Value.}, journal = {Cell}, volume = {183}, year = {2020}, month = {2020 Oct 29}, pages = {620-35}, abstract = {

Hippocampal activity represents many behaviorally important variables, including context, an animal{\textquoteright}s location within a given environmental context, time, and reward. Using longitudinal calcium imaging in mice, multiple large virtual environments, and differing reward contingencies, we derived a unified probabilistic model of CA1 representations centered on a single feature-the field propensity. Each cell{\textquoteright}s propensity governs how many place fields it has per unit space, predicts its reward-related activity, and is preserved across distinct environments and over months. Propensity is broadly distributed-with many low, and some very high, propensity cells-and thus strongly shapes hippocampal representations. This results in a range of spatial codes, from sparse to dense. Propensity varied \~{}10-fold between adjacent cells in salt-and-pepper fashion, indicating substantial functional differences within a presumed cell type. Intracellular recordings linked propensity to cell excitability. The stability of each cell{\textquoteright}s propensity across conditions suggests this fundamental property has anatomical, transcriptional, and/or developmental origins.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2020.09.024}, author = {Lee, Jae Sung and Briguglio, John J and Cohen, Jeremy D and Romani, Sandro and Lee, Albert K} } @article {64905, title = {Visually guided behavior and optogenetically induced learning in head-fixed flies exploring a virtual landscape.}, journal = {Current Biology : CB}, year = {2019}, month = {2019 Apr 29}, abstract = {

Studying the intertwined roles of sensation, experience, and directed action in navigation has been facilitated by the development of virtual reality (VR) environments for head-fixed animals, allowing for quantitative measurements of behavior in well-controlled conditions. VR has long featured in studies of Drosophila melanogaster, but these experiments have typically allowed the fly to change only its heading in a visual scene and not its position. Here we explore how flies move in two dimensions (2D) using a visual VR environment that more closely captures an animal{\textquoteright}s experience during free behavior. We show that flies{\textquoteright} 2D interaction with landmarks cannot be automatically derived from their orienting behavior under simpler one-dimensional (1D) conditions. Using novel paradigms, we then demonstrate that flies in 2D VR adapt their behavior in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies exploring a 2D VR respond to optogenetic activation of sugar-sensing neurons by initiating a local search, which appears not to rely on visual landmarks. Visual landmarks can, however, help flies to avoid areas in VR where they experience an aversive, optogenetically generated heat stimulus. By coupling aversive virtual heat to the flies{\textquoteright} presence near visual landmarks of specific shapes, we elicit selective learned avoidance of those landmarks. Thus, we demonstrate that head-fixed flies adaptively navigate in 2D virtual environments, but their reliance on visual landmarks is context dependent. These behavioral paradigms set the stage for interrogation of the fly brain circuitry underlying flexible navigation in complex multisensory environments.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2019.04.033}, author = {Haberkern, Hannah and Basnak, Melanie A and Ahanonu, Biafra and Schauder, David and Cohen, Jeremy D and Bolstad, Mark and Bruns, Christopher and Jayaraman, Vivek} } @article {48670, title = {Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments.}, journal = {eLife}, volume = {6}, year = {2017}, month = {2017 Jul 25}, abstract = {

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude - often suddenly - during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience - both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage.

}, issn = {2050-084X}, doi = {10.7554/eLife.23040}, author = {Cohen, Jeremy D and Bolstad, Mark and Lee, Albert K} } @article {48558, title = {Mesoscale-duration activated states gate spiking in response to fast rises in membrane voltage in the awake brain.}, journal = {Journal of Neurophysiology}, volume = {118}, year = {2017}, month = {2017 May 31}, pages = {1270-91}, abstract = {

Seconds-scale network states, affecting many neurons within a network, modulate neural activity by complementing fast integration of neuron-specific inputs that arrive in the milliseconds before spiking. Non-rhythmic subthreshold dynamics at intermediate timescales, however, are less well-characterized. We found, using automated whole cell patch clamping in vivo, that spikes recorded in CA1 and barrel cortex in awake mice are often preceded not only by monotonic voltage rises lasting milliseconds, but also by more gradual (lasting 10s-100s of ms) depolarizations. The latter exert a gating function on spiking, in a fashion that depends on the gradual rise duration: the probability of spiking was higher for longer gradual rises, even controlling for the amplitude of the gradual rises. Barrel cortex double-autopatch recordings show that gradual rises are shared across some but not all neurons. The gradual rises may represent a new kind of state, intermediate both in timescale and in proportion of neurons participating, which gates a neuron{\textquoteright}s ability to respond to subsequent inputs.

}, issn = {1522-1598}, doi = {10.1152/jn.00116.2017}, author = {Singer, Annabelle C and Talei Franzesi, Giovanni and Kodandaramaiah, Suhasa B and Flores, Francisco J and Cohen, Jeremy D and Lee, Albert K and B{\"o}rgers, Christoph and Forest, Craig R and Kopell, Nancy J and Boyden, Edward S} } @article {45062, title = {Natural whisker-guided behavior by head-fixed mice in tactile virtual reality.}, journal = {Journal of Neuroscience}, volume = {34}, year = {2014}, month = {2014 Jul 16}, pages = {9537-50}, abstract = {

During many natural behaviors the relevant sensory stimuli and motor outputs are difficult to quantify. Furthermore, the high dimensionality of the space of possible stimuli and movements compounds the problem of experimental control. Head fixation facilitates stimulus control and movement tracking, and can be combined with techniques for recording and manipulating neural activity. However, head-fixed mouse behaviors are typically trained through extensive instrumental conditioning. Here we present a whisker-based, tactile virtual reality system for head-fixed mice running on a spherical treadmill. Head-fixed mice displayed natural movements, including running and rhythmic whisking at 16 Hz. Whisking was centered on a set point that changed in concert with running so that more protracted whisking was correlated with faster running. During turning, whiskers moved in an asymmetric manner, with more retracted whisker positions in the turn direction and protracted whisker movements on the other side. Under some conditions, whisker movements were phase-coupled to strides. We simulated a virtual reality tactile corridor, consisting of two moveable walls controlled in a closed-loop by running speed and direction. Mice used their whiskers to track the walls of the winding corridor without training. Whisker curvature changes, which cause forces in the sensory follicles at the base of the whiskers, were tightly coupled to distance from the walls. Our behavioral system allows for precise control of sensorimotor variables during natural tactile navigation.

}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0712-14.2014}, author = {Sofroniew, Nicholas J and Cohen, Jeremy D and Lee, Albert K and Svoboda, Karel} }