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
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: bioRxiV, 2018

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
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