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      Specialized coding of sensory, motor, and cognitive variables in VTA dopamine neurons

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          Abstract

          There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward 1 and reward-predicting cues 1, 2 , but also to other variables such as distance to reward 3 , movements 49 , and behavioral choices 10, 11 . Based on these findings, a major open question is how the responses to these diverse variables are organized across the population of DA neurons. In other words, do individual DA neurons multiplex multiple variables, or are subsets of neurons specialized in encoding specific behavioral variables? The reason that this fundamental question has been difficult to resolve is that recordings from large populations of individual DA neurons have not been performed in a behavioral task with sufficient complexity to examine these diverse variables simultaneously. To address this gap, we used 2-photon calcium imaging through an implanted lens to record activity of >300 midbrain DA neurons in the ventral tegmental area (VTA) during a complex decision-making task. As mice navigated in a virtual reality (VR) environment, DA neurons encoded an array of sensory, motor, and cognitive variables. These responses were functionally clustered, such that subpopulations of neurons transmitted information about a subset of behavioral variables, in addition to encoding reward. These functional clusters were spatially organized, such that neighboring neurons were more likely to be part of the same cluster. Taken together with the topography between DA neurons and their projections, this specialization and anatomical organization may aid downstream circuits in correctly interpreting the wide range of signals transmitted by DA neurons.

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          Most cited references28

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          Spatio-temporal correlations and visual signalling in a complete neuronal population.

          Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.
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            Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning.

            Natural rewards and drugs of abuse can alter dopamine signaling, and ventral tegmental area (VTA) dopaminergic neurons are known to fire action potentials tonically or phasically under different behavioral conditions. However, without technology to control specific neurons with appropriate temporal precision in freely behaving mammals, the causal role of these action potential patterns in driving behavioral changes has been unclear. We used optogenetic tools to selectively stimulate VTA dopaminergic neuron action potential firing in freely behaving mammals. We found that phasic activation of these neurons was sufficient to drive behavioral conditioning and elicited dopamine transients with magnitudes not achieved by longer, lower-frequency spiking. These results demonstrate that phasic dopaminergic activity is sufficient to mediate mammalian behavioral conditioning.
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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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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                3 May 2019
                29 May 2019
                June 2019
                10 April 2020
                : 570
                : 7762
                : 509-513
                Affiliations
                [1 ]Princeton Neuroscience Institute, Princeton University, Princeton NJ 08544
                [2 ]Department of Psychology, Princeton University, Princeton NJ 08544
                [3 ]Department of Molecular Biology, Princeton University, Princeton NJ 08544
                Author notes

                Contributions

                B.E., D.W.T. and I.B.W. conceived the project. B.E., J.F., J.C., W.F., S.O. collected data. B.E., W.F., J.C., S.O., and H.J. analyzed data. S.Y.T. and S.A.K. provided technical training. N.D., D.W.T. and I.B.W. advised on the data analysis. B.E. and I.B.W. wrote the paper.

                [* ]Correspondence: iwitten@ 123456princeton.edu
                Article
                NIHMS1528531
                10.1038/s41586-019-1261-9
                7147811
                31142844
                eeb05cf6-f03c-460c-ac8b-252f9308aa56

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