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.
1 code implementation • 10 Apr 2020 • Austin Talbot, David Dunson, Kafui Dzirasa, David Carlson
Targeted stimulation of the brain has the potential to treat mental illnesses.
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).
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).
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.
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.
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.