Robert E. Kass
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View article: Identifying interactions across brain areas while accounting for individual-neuron dynamics with a Transformer-based variational autoencoder
Identifying interactions across brain areas while accounting for individual-neuron dynamics with a Transformer-based variational autoencoder Open
Advances in large-scale recording technologies now enable simultaneous measurements from multiple brain areas, offering new opportunities to study signal transmission across interacting components of neural circuits. However, neural respon…
View article: Relative timing and coupling of neural population bursts in large-scale recordings from multiple neuron populations
Relative timing and coupling of neural population bursts in large-scale recordings from multiple neuron populations Open
The onset of a sensory stimulus elicits transient bursts of activity in neural populations, which are presumed to convey information about the stimulus to downstream populations. The time at which these synchronized bursts reach their peak…
View article: Simultaneous Inference in Multiple Matrix-Variate Graphs for High-Dimensional Neural Recordings
Simultaneous Inference in Multiple Matrix-Variate Graphs for High-Dimensional Neural Recordings Open
As large-scale neural recordings become common, many neuroscientific investigations are focused on identifying functional connectivity from spatio-temporal measurements in two or more brain areas across multiple sessions. Spatial-temporal …
View article: Oscillating neural circuits: Phase, amplitude, and the complex normal distribution
Oscillating neural circuits: Phase, amplitude, and the complex normal distribution Open
Multiple oscillating time series are typically analyzed in the frequency domain, where coherence is usually said to represent the magnitude of the correlation between two signals at a particular frequency. The correlation being referenced …
View article: Identification of interacting neural populations: methods and statistical considerations
Identification of interacting neural populations: methods and statistical considerations Open
As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidenc…
View article: A biophysical and statistical modeling paradigm for connecting neural physiology and function
A biophysical and statistical modeling paradigm for connecting neural physiology and function Open
To understand single neuron computation, it is necessary to know how specific physiological parameters affect neural spiking patterns that emerge in response to specific stimuli. Here we present a computational pipeline combining biophysic…
View article: A Conversation with Stephen M. Stigler
A Conversation with Stephen M. Stigler Open
Stephen M. Stigler received his Ph.D. in Statistics from the University of California, Berkeley, with a dissertation on the asymptotic distribution of linear functions of order statistics. Starting in 1967, he taught at the University of W…
View article: Population burst propagation across interacting areas of the brain
Population burst propagation across interacting areas of the brain Open
We developed a novel statistical method for identifying coordinated propagation of activity across populations of spiking neurons, with high temporal accuracy. Using simultaneous recordings from three visual areas we document precise timin…
View article: Population Burst Propagation Across Interacting Areas of the Brain: Supporting Information
Population Burst Propagation Across Interacting Areas of the Brain: Supporting Information Open
For many perceptual and behavioral tasks, a prominent feature of neural spike trains involves high firing rates across relatively short intervals of time. We call these events ``population bursts.” Because during a population burst informa…
View article: Neuromatch Academy: a 3-week, online summer school in computational neuroscience
Neuromatch Academy: a 3-week, online summer school in computational neuroscience Open
Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was
\ndesigned as an online summer school to cover the basics of computational neuroscience
\nin three weeks. The materials cover dominant and emerging computati…
View article: Cross-population coupling of neural activity based on Gaussian process current source densities
Cross-population coupling of neural activity based on Gaussian process current source densities Open
Because local field potentials (LFPs) arise from multiple sources in different spatial locations, they do not easily reveal coordinated activity across neural populations on a trial-to-trial basis. As we show here, however, once disparate …
View article: Latent Cross-population Dynamic Time-series Analysis of High-dimensional Neural Recordings
Latent Cross-population Dynamic Time-series Analysis of High-dimensional Neural Recordings Open
An important problem in analysis of neural data is to characterize interactions across brain regions from high-dimensional multiple-electrode recordings during a behavioral experiment. Lead-lag effects indicate possible directional flows o…
View article: Cross-Population Amplitude Coupling in High-Dimensional Oscillatory Neural Time Series
Cross-Population Amplitude Coupling in High-Dimensional Oscillatory Neural Time Series Open
Neural oscillations have long been considered important markers of interaction across brain regions, yet identifying coordinated oscillatory activity from high-dimensional multiple-electrode recordings remains challenging. We sought to qua…
View article: Cross-population coupling of neural activity based on Gaussian process current source densities
Cross-population coupling of neural activity based on Gaussian process current source densities Open
Because local field potentials (LFPs) arise from multiple sources in different spatial locations, they do not easily reveal coordinated activity across neural populations on a trial-to-trial basis. As we show here, however, once disparate …
View article: Teaching Computation in Neuroscience: Notes on the 2019 Society for Neuroscience Professional Development Workshop on Teaching.
Teaching Computation in Neuroscience: Notes on the 2019 Society for Neuroscience Professional Development Workshop on Teaching. Open
The 2019 Society for Neuroscience Professional Development Workshop on Teaching reviewed current tools, approaches, and examples for teaching computation in neuroscience. Robert Kass described the statistical foundations that students need…
View article: MEG_EEG_data_viewing_scene_pictures
MEG_EEG_data_viewing_scene_pictures Open
This data set includes MEG and EEG data while the same participants view 362 scene images. Each image is shown 3-6 to 6 and the single-trial evoked responses were averaged across the repetitions.`EEG.zip` and `MEG.zip` contain the EEG and …
View article: Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings.
Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings. Open
High-dimensional neural recordings across multiple brain regions can be used to establish functional connectivity with good spatial and temporal resolution. We designed and implemented a novel method, Latent Dynamic Factor Analysis of High…
View article: Torus graphs for multivariate phase coupling analysis
Torus graphs for multivariate phase coupling analysis Open
Angular measurements are often modeled as circular random variables, where there are natural circular analogues of moments, including correlation. Because a product of circles is a torus, a d-dimensional vector of circular random variables…
View article: TORUS GRAPHS FOR MULTIVARIATE PHASE COUPLING ANALYSISa
TORUS GRAPHS FOR MULTIVARIATE PHASE COUPLING ANALYSISa Open
Angular measurements are often modeled as circular random variables, where there are natural circular analogues of moments, including correlation. Because a product of circles is a torus, a d-dimensional vector of circular random variables…
View article: Exploring spatiotemporal neural dynamics of the human visual cortex
Exploring spatiotemporal neural dynamics of the human visual cortex Open
The human visual cortex is organized in a hierarchical manner. Although previous evidence supporting this hypothesis has been accumulated, specific details regarding the spatiotemporal information flow remain open. Here we present detailed…
View article: MEG_scene_data
MEG_scene_data Open
Preprocessed data related to the manuscript "Exploring spatio-temporal neural dynamics of the human visual cortex". Data description and related code can be found at github.com/YingYang/MEG_Scene/blob/master/README.md
View article: Exploring spatio-temporal neural dynamics of the human visual cortex
Exploring spatio-temporal neural dynamics of the human visual cortex Open
The human visual cortex is organized in a hierarchical manner. Although a significant body of evidence has been accumulated in support of this hypothesis, specific details regarding the spatial and temporal information flow remain open. He…
View article: Detecting multivariate cross-correlation between brain regions
Detecting multivariate cross-correlation between brain regions Open
The problem of identifying functional connectivity from multiple time series data recorded in each of two or more brain areas arises in many neuroscientific investigations. For a single stationary time series in each of two brain areas sta…
View article: Adjusted regularization in latent graphical models: Application to multiple-neuron spike count data
Adjusted regularization in latent graphical models: Application to multiple-neuron spike count data Open
A major challenge in contemporary neuroscience is to analyze data from large numbers of neurons recorded simultaneously across many experimental replications (trials), where the data are counts of neural firing events, and one of the basic…
View article: Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data Open
In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal a…
View article: Author response: Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
Author response: Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data Open
Article Figures and data Abstract Introduction Results Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract In vivo calcium imaging through microendoscopic lense…
View article: Computational Neuroscience: Mathematical and Statistical Perspectives
Computational Neuroscience: Mathematical and Statistical Perspectives Open
Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, …