Specialized and spatially organized coding of sensory, motor, and cognitive variables in midbrain dopamine neurons
  • Authors: Ben Engelhard, Joel Finkelstein, Julia Cox, Weston  Fleming, Hee Jae Jang, Sharon Ornelas, Sue Ann Koay, Stephan Thiberge, Nathaniel Daw, David Tank,  Ilana Witten

Publication: Nature, 2019

There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward and reward-predicting cues but also to other variables such as distance to reward, movements and behavioral choices. 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.

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Brigitte Stark
Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience
  • Authors: Emily L Mackevicius, Andrew H Bahle, Alex H Williams, Shijie Gu, Natalia I Denisenko, Mark S Goldman, Michale S Fee

Publication: eLIFE, 2019

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox—called seqNMF—with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral datas. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

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Brigitte Stark
CaImAn: An open source tool for scalable Calcium Imaging data Analysis
  • Authors: Andrea Giovannucci , Johannes Friedrich, Pat Gunn, Jérémie Kalfon, Brandon L Brown, Sue Ann Koay, Jiannis Taxidis, Farzaneh Najafi, Jeffrey L Gauthier, Pengcheng Zhou, Baljit S Khakh, David W Tank, Dmitri B Chklovskii, Eftychios A Pnevmatikakis

Publication: eLIFE, 2019

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. 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 scalability 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 and combined a corpus of manual 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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Cerebellar disruption impairs working memory during evidence accumulation
  • Authors: Ben Deverett, Mikhail Kislin, David W. Tank, Samuel S.-H. Wang

Publication: biorxiv, 2019

To select actions based on sensory evidence, animals must create and manipulate representations of stimulus information in memory. We found that during accumulation of somatosensory evidence, optogenetic manipulation of cerebellar Purkinje cells reduced the accuracy of subsequent memory-guided decisions and caused mice to downweight prior information. Behavioral deficits were consistent with the addition of noise and leak to the evidence accumulation process, suggesting the cerebellum can influence the maintenance of working memory contents.

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Brigitte Stark
Imaging Cortical Dynamics in GCaMP Transgenic Rats with a Head-Mounted Widefield Macroscope
  • Authors: Benjamin Scott, Stephan Y. Thiberge, Caiying Guo, D. Gowanlock R. Tervo, Carlos D. Brody, Alla Y. Karpova, David W. Tank

Publication: NEURO, 2018

Widefield imaging of calcium dynamics is an emerging method for mapping regional neural activity but is currently limited to restrained animals. Here we describe cScope, a head-mounted widefield macroscope developed to image large-scale cortical dynamics in rats during natural behavior. cScope provides a 7.8 × 4 mm field of view and dual illumination paths for both fluorescence and hemodynamic correction and can be fabricated at low cost using readily attainable components. We also report the development of Thy-1 transgenic rat strains with widespread neuronal expression of the calcium indicator GCaMP6f. We combined these two technologies to image large-scale calcium dynamics in the dorsal neocortex during a visual evidence accumulation task. Quantitative analysis of task-related dynamics revealed multiple regions having neural signals that encode behavioral choice and sensory evidence. Our results provide a new transgenic resource for calcium imaging in rats and extend the domain of head-mounted microscopes to larger-scale cortical dynamics.

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Brigitte Stark
Cerebellar involvement in an evidence-accumulation decision-making task
  • Authors: Ben Deverett, Sue Ann Koay, Marlies Oostland,  Samuel S-H Wang

Publication: e LIFE, 2018

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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Brigitte Stark
An Accumulation-of-Evidence Task Using Visual Pulses for Mice Navigating in Virtual Reality
  • Authors: Lucas Pinto, Sue A. Koay, Ben Engelhard, Alice M. Yoon, Ben Deverett, Stephan Y. Thiberge, Ilana B. Witten, David W. Tank, and Carlos D. Brody

Publication: frontiers in Behavioral Neuroscience, 2018

The gradual accumulation of sensory evidence is a crucial component of perceptual decision making, but its neural mechanisms are still poorly understood. Given the wide availability of genetic and optical tools for mice, they can be useful model organisms for the study of these phenomena; however, behavioral tools are largely lacking. Here, we describe a new evidence-accumulation task for head-fixed mice navigating in a virtual reality (VR) environment. As they navigate down the stem of a virtual T-maze, they see brief pulses of visual evidence on either side, and retrieve a reward on the arm with the highest number of pulses.

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Faction Studio Team