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5 Publications

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    11/19/18 | Detecting and Correcting False Transients in Calcium Imaging
    Gauthier JL, Koay SA, Nieh EH, Tank DW, Pillow JW, Charles AS
    bioRxiv. 11/2018:. doi: 10.1101/473470

    Population recordings of calcium activity are a major source of insight into neural function. Large dataset sizes often require automated methods, but automation can introduce errors that are difficult to detect. Here we show that automatic time course estimation can sometimes lead to significant misattribution errors, in which fluorescence is ascribed to the wrong cell. Misattribution arises when the shapes of overlapping cells are imperfectly defined, or when entire cells or processes are not identified, and misattribution can even be produced by methods specifically designed to handle overlap. To diagnose this problem, we develop a transient-by-transient metric and a visualization tool that allow users to quickly assess the degree of misattribution in large populations. To filter out misattribution, we also design a robust estimator that explicitly accounts for contaminating signals in a generative model. Our methods can be combined with essentially any cell finding technique, empowering users to diagnose and correct at large scale a problem that has the potential to significantly alter scientific conclusions.

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    10/29/18 | Specialized and spatially organized coding of sensory, motor, and cognitive variables in midbrain dopamine neurons
    Engelhard B, Finkelstein J, Cox J, Fleming W, Jang HJ, Ornelas S, Koay SA, Thiberge S, Daw N, Tank DW, Witten IB
    bioRxiv. 10/2018:. doi: 10.1101/456194

    There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward 1,2 and reward-predicting cues 1,3,4, but also to other variables such as distance to reward 5, movements 6–11 and behavioral choices 12–15. 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 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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    08/13/18 | Cerebellar involvement in an evidence-accumulation decision-making task
    Deverett B, Koay SA, Oostland M, Wang SS
    eLife. 08/2018;7:. doi: 10.7554/eLife.36781

    To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Using a novel evidence-accumulation task for mice, we performed recording and perturbation studies of crus I of the lateral posterior cerebellum, which communicates bidirectionally with numerous forebrain regions. Cerebellar inactivation led to a reduction in the fraction of correct trials. Using two-photon fluorescence imaging of calcium, we found that Purkinje cell somatic activity contained choice/evidence-related information. Decision errors were represented by dendritic calcium spikes, which in other contexts are known to drive cerebellar plasticity. We propose that cerebellar circuitry may contribute to computations that support accurate performance in this perceptual decision-making task.

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    06/11/18 | A cerebellar role in evidence-guided decision-making
    Deverett B, Koay SA, Oostland M, Wang SS
    bioRxiv. 06/2018:. doi: 10.1101/343095

    To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Here we show that during perceptual decision-making over a period of seconds, decision-, sensory-, and error-related information converge on the lateral posterior cerebellum in crus I, a structure that communicates bidirectionally with numerous forebrain regions. We trained mice on a novel evidence-accumulation task and demonstrated that cerebellar inactivation reduces behavioral accuracy without impairing motor parameters of action. Using two-photon calcium imaging, we found that Purkinje cell somatic activity encoded choice- and evidence-related variables. Decision errors were represented by dendritic calcium spikes, which are known to drive plasticity. We propose that cerebellar circuitry may contribute to the set of distributed computations in the brain that support accurate perceptual decision-making.

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    06/05/18 | CalmAn: An open source tool for scalable Calcium Imaging data Analysis
    Giovannucci A, Friedrich J, Gunn P, Kalfon J, Koay SA, Taxidis J, Najafi F, Gauthier JL, Zhou P, Tank DW, Chklovskii D, Pnevmatikakis EA
    bioRxiv. 06/2018:. doi: 10.1101/339564

    Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. Here we present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good performance on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected a corpus of ground truth annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

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