Search Results for author: Kafui Dzirasa

Found 7 papers, 1 papers with code

Directed Spectrum Measures Improve Latent Network Models Of Neural Populations

no code implementations NeurIPS 2021 Neil Gallagher, Kafui Dzirasa, David Carlson

We prove that it is compatible with the implicit assumptions of linear factor models, and we provide a method to estimate the DS.

Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity

1 code implementation10 Apr 2020 Austin Talbot, David Dunson, Kafui Dzirasa, David Carlson

Joint factor models for the predictors and outcomes are natural, but maximum likelihood estimates of these models can struggle in practice when there is model misspecification.

Dimensionality Reduction

Cross-Spectral Factor Analysis

no code implementations NeurIPS 2017 Neil Gallagher, Kyle R. Ulrich, Austin Talbot, Kafui Dzirasa, Lawrence Carin, David E. Carlson

To facilitate understanding of network-level synchronization between brain regions, we introduce a novel model of multisite low-frequency neural recordings, such as local field potentials (LFPs) and electroencephalograms (EEGs).

Targeting EEG/LFP Synchrony with Neural Nets

no code implementations NeurIPS 2017 Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E. Carlson

We consider the analysis of Electroencephalography (EEG) and Local Field Potential (LFP) datasets, which are “big” in terms of the size of recorded data but rarely have sufficient labels required to train complex models (e. g., conventional deep learning methods).

EEG

GP Kernels for Cross-Spectrum Analysis

no code implementations NeurIPS 2015 Kyle R. Ulrich, David E. Carlson, Kafui Dzirasa, Lawrence Carin

An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels.

Gaussian Processes Time Series

Analysis of Brain States from Multi-Region LFP Time-Series

no code implementations NeurIPS 2014 Kyle R. Ulrich, David E. Carlson, Wenzhao Lian, Jana S. Borg, Kafui Dzirasa, Lawrence Carin

The LFPs are modeled as a mixture of GPs, with state- and region-dependent mixture weights, and with the spectral content of the data encoded in GP spectral mixture covariance kernels.

Gaussian Processes Time Series

On the relations of LFPs & Neural Spike Trains

no code implementations NeurIPS 2014 David E. Carlson, Jana Schaich Borg, Kafui Dzirasa, Lawrence Carin

One of the goals of neuroscience is to identify neural networks that correlate with important behaviors, environments, or genotypes.

Dictionary Learning

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