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      Widespread State-Dependent Shifts in Cerebellar Activity in Locomoting Mice

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          Abstract

          Excitatory drive enters the cerebellum via mossy fibers, which activate granule cells, and climbing fibers, which activate Purkinje cell dendrites. Until now, the coordinated regulation of these pathways has gone unmonitored in spatially resolved neuronal ensembles, especially in awake animals. We imaged cerebellar activity using functional two-photon microscopy and extracellular recording in awake mice locomoting on an air-cushioned spherical treadmill. We recorded from putative granule cells, molecular layer interneurons, and Purkinje cell dendrites in zone A of lobule IV/V, representing sensation and movement from trunk and limbs. Locomotion was associated with widespread increased activity in granule cells and interneurons, consistent with an increase in mossy fiber drive. At the same time, dendrites of different Purkinje cells showed increased co-activation, reflecting increased synchrony of climbing fiber activity. In resting animals, aversive stimuli triggered increased activity in granule cells and interneurons, as well as increased Purkinje cell co-activation that was strongest for neighboring dendrites and decreased smoothly as a function of mediolateral distance. In contrast with anesthetized recordings, no 1–10 Hz oscillations in climbing fiber activity were evident. Once locomotion began, responses to external stimuli in all three cell types were strongly suppressed. Thus climbing and mossy fiber representations can shift together within a fraction of a second, reflecting in turn either movement-associated activity or external stimuli.

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          Most cited references 68

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          A theory of cerebellar cortex.

           D. W. M. Marr (1969)
          1. A detailed theory of cerebellar cortex is proposed whose consequence is that the cerebellum learns to perform motor skills. Two forms of input-output relation are described, both consistent with the cortical theory. One is suitable for learning movements (actions), and the other for learning to maintain posture and balance (maintenance reflexes).2. It is known that the cells of the inferior olive and the cerebellar Purkinje cells have a special one-to-one relationship induced by the climbing fibre input. For learning actions, it is assumed that:(a) each olivary cell responds to a cerebral instruction for an elemental movement. Any action has a defining representation in terms of elemental movements, and this representation has a neural expression as a sequence of firing patterns in the inferior olive; and(b) in the correct state of the nervous system, a Purkinje cell can initiate the elemental movement to which its corresponding olivary cell responds.3. Whenever an olivary cell fires, it sends an impulse (via the climbing fibre input) to its corresponding Purkinje cell. This Purkinje cell is also exposed (via the mossy fibre input) to information about the context in which its olivary cell fired; and it is shown how, during rehearsal of an action, each Purkinje cell can learn to recognize such contexts. Later, when the action has been learnt, occurrence of the context alone is enough to fire the Purkinje cell, which then causes the next elemental movement. The action thus progresses as it did during rehearsal.4. It is shown that an interpretation of cerebellar cortex as a structure which allows each Purkinje cell to learn a number of contexts is consistent both with the distributions of the various types of cell, and with their known excitatory or inhibitory natures. It is demonstrated that the mossy fibre-granule cell arrangement provides the required pattern discrimination capability.5. The following predictions are made.(a) The synapses from parallel fibres to Purkinje cells are facilitated by the conjunction of presynaptic and climbing fibre (or post-synaptic) activity.(b) No other cerebellar synapses are modifiable.(c) Golgi cells are driven by the greater of the inputs from their upper and lower dendritic fields.6. For learning maintenance reflexes, 2(a) and 2(b) are replaced by2'. Each olivary cell is stimulated by one or more receptors, all of whose activities are usually reduced by the results of stimulating the corresponding Purkinje cell.7. It is shown that if (2') is satisfied, the circuit receptor --> olivary cell --> Purkinje cell --> effector may be regarded as a stabilizing reflex circuit which is activated by learned mossy fibre inputs. This type of reflex has been called a learned conditional reflex, and it is shown how such reflexes can solve problems of maintaining posture and balance.8. 5(a), and either (2) or (2') are essential to the theory: 5(b) and 5(c) are not absolutely essential, and parts of the theory could survive the disproof of either.
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            Imaging large-scale neural activity with cellular resolution in awake, mobile mice.

            We report a technique for two-photon fluorescence imaging with cellular resolution in awake, behaving mice with minimal motion artifact. The apparatus combines an upright, table-mounted two-photon microscope with a spherical treadmill consisting of a large, air-supported Styrofoam ball. Mice, with implanted cranial windows, are head restrained under the objective while their limbs rest on the ball's upper surface. Following adaptation to head restraint, mice maneuver on the spherical treadmill as their heads remain motionless. Image sequences demonstrate that running-associated brain motion is limited to approximately 2-5 microm. In addition, motion is predominantly in the focal plane, with little out-of-plane motion, making the application of a custom-designed Hidden-Markov-Model-based motion correction algorithm useful for postprocessing. Behaviorally correlated calcium transients from large neuronal and astrocytic populations were routinely measured, with an estimated motion-induced false positive error rate of <5%.
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              Intracellular dynamics of hippocampal place cells during virtual navigation

              Hippocampal place cells encode spatial information in rate and temporal codes. To examine the mechanisms underlying hippocampal coding, we measured the intracellular dynamics of place cells by combining in vivo whole cell recordings with a virtual reality system. Head-restrained mice, running on a spherical treadmill, interacted with a computer-generated visual environment to perform spatial behaviors. Robust place cell activity was present during movement along a virtual linear track. From whole cell recordings, we identified three subthreshold signatures of place fields: (1) an asymmetric ramp-like depolarization of the baseline membrane potential; (2) an increase in the amplitude of intracellular theta oscillations; and, (3) a phase precession of the intracellular theta oscillation relative to the extracellularly-recorded theta rhythm. These intracellular dynamics underlie the primary features of place cell rate and temporal codes. The virtual reality system developed here will enable new experimental approaches to study the neural circuits underlying navigation.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                3 August 2012
                : 7
                : 8
                Affiliations
                [1 ]Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America
                [2 ]Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America
                [3 ]Lewis-Sigler Center for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
                Tokyo Medical and Dental University, Japan
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                [¤a]

                Current address: School of Engineering, Brown University, Providence, Rhode Island, United States of America

                [¤b]

                Current address: Department of Neurobiology, Northwestern University, Evanston, Illinois, United States of America

                [¤c]

                Current address: Netherlands Institute for Neuroscience, Amsterdam, The Netherlands

                Conceived and designed the experiments: IO DAD TMH DWT SSW. Performed the experiments: IO DAD TMH. Analyzed the data: IO DAD TMH. Contributed reagents/materials/analysis tools: IO DAD. Wrote the paper: IO SSW.

                Article
                PONE-D-12-14122
                10.1371/journal.pone.0042650
                3411825
                22880068

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 16
                Funding
                This study was funded by (1) National Institute of Health grants NS045193 (SW) and NS068148 (DT, SW) http://www.nih.gov (2) Autism Speaks postdoctoral award (IO) http://autismspeaks.org (3) Robert Leet and Clara Guthrie Patterson Trust (DD) https://www.bankofamerica.com/philanthropic/foundation.action?fnId=106 (4) W.M. Keck Foundation Distinguished Young Investigator (SW). http://wmkeck.org. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Anatomy and Physiology
                Neurological System
                Sensory Physiology
                Computational Biology
                Computational Neuroscience
                Sensory Systems
                Model Organisms
                Animal Models
                Mouse
                Neuroscience
                Neuroimaging
                Calcium Imaging
                Motor Systems

                Uncategorized

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