28 citations · 49 across the 5 of their papers we have counts for
5 papers
Bayesian Inference of Psychometric Variables From Brain and Behavior in Implicit Association Tests
Christian A. Kothe, Sean Mullen, Michael V. Bronstein +7
Objective. We establish a principled method for inferring mental health related psychometric variables from neural and behavioral data using the Implicit Association Test (IAT) as…
Latent Variable Double Gaussian Process Model for Decoding Complex Neural Data
Navid Ziaei, Joshua J. Stim, Melanie D. Goodman-Keiser +4
Non-parametric models, such as Gaussian Processes (GP), show promising results in the analysis of complex data. Their applications in neuroscience data have recently gained tractio…
A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data
Navid Ziaei, Behzad Nazari, Uri T. Eden +2
Extracting meaningful information from high-dimensional data poses a formidable modeling challenge, particularly when the data is obscured by noise or represented through different…
A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC
Uisub Shin, Cong Ding, Virginia Woods +2
Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter…
Multi-Modal Neuroimaging Analysis and Visualization Tool (MMVT)
O. Felsenstein, N. Peled, E. Hahn +14
Sophisticated visualization tools are essential for the presentation and exploration of human neuroimaging data. While two-dimensional orthogonal views of neuroimaging data are con…