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Towards the neural population doctrine
TLDR
Neural populations are understood to be the essential unit of computation in many brain regions, a classic idea that has been given new life. Expand
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BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos
TLDR
We introduce a probabilistic framework for the analysis of behavioral video and neural activity. Expand
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Point process models show temporal dependencies of basal ganglia nuclei under Deep Brain Stimulation
TLDR
Deep Brain Stimulation (DBS) is an effective treatment for patients with Parkinsons disease, but its impact on basal ganglia nuclei is not fully understood. Expand
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A Novel Variational Family for Hidden Nonlinear Markov Models
TLDR
We propose a novel variational inference framework for the explicit modeling of time series, Variational Inference for Nonlinear Dynamics (VIND), that is able to uncover nonlinear observation and transition functions from sequential data. Expand
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Aggregate Input-Output Models of Neuronal Populations
TLDR
An extraordinary amount of electrophysiological data has been collected from various brain nuclei to help us understand how neural activity in one region influences another region. Expand
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Modulations in the oscillatory activity of the Globus Pallidus internus neurons during a behavioral task-A point process analysis
TLDR
The behavioral state of a subject is hypothesized to be reflected in the oscillatory modulations of the spiking activity of certain groups of neurons. Expand
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Weighted Population Code for low power neuromorphic image classification
TLDR
We present a novel spike coding scheme named Weighted Population Code (WPC). Expand
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A systematic approach to selecting task relevant neurons
TLDR
This paper proposes a systematic approach for neuron selection that captures the contribution of stimulus to spiking activity while taking into account task-irrelevant intrinsic dynamics that affect firing rates. Expand
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Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data
TLDR
We introduce Localized semi-Nonnegative Matrix Factorization (Lo-caNMF), a method that efficiently decomposes widefield video data into meaningful spatial and temporal components that can be mapped onto well-defined brain regions. Expand
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Performance Limitations in Sensorimotor Control: Tradeoffs between Neural Computation and Accuracy in Tracking Fast Movements
TLDR
We use feedback control principles to quantify performance limitations of the sensorimotor control system (SCS) to track fast periodic movements, including skipped cycles, overshoot and undershoot. Expand
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