Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks
KC Chuang, S Ramakrishnapillai, K Kirby… - … Workshop on Machine …, 2023 - Springer
Joint decomposition of functional magnetic resonance imaging (fMRI) time series into time
courses of neural activity events and hemodynamic response functions (HRF) can enable …
courses of neural activity events and hemodynamic response functions (HRF) can enable …
Mixture components inference for sparse regression: introduction and application for estimation of neuronal signal from fMRI BOLD
Sparse linear regression methods including the well-known LASSO and the Dantzig selector
have become ubiquitous in the engineering practice, including in medical imaging. Among …
have become ubiquitous in the engineering practice, including in medical imaging. Among …
BRAD: Software for BRain Activity Detection from hemodynamic response
Background and objective: Precise estimation of neuronal activity from neuroimaging data is
one of the central challenges of the application of noninvasive neuroimaging methods. One …
one of the central challenges of the application of noninvasive neuroimaging methods. One …
Arend WA Van Gemmert¹, Lydia Bazzano, and Owen T. Carmichael2 D 1 Louisiana State University, Baton Rouge, LA, USA kchuan1@ lsu. edu 2 Pennington …
KC Chuang, S Ramakrishnapillai¹… - Machine Learning in …, 2023 - books.google.com
Joint decomposition of functional magnetic resonance imaging (fMRI) time series into time
courses of neural activity events and hemodynamic response functions (HRF) can enable …
courses of neural activity events and hemodynamic response functions (HRF) can enable …
Estimating sparse neuronal signal from hemodynamic response: the mixture components inference approach
The approximate knowledge of the hemodynamic response to neuronal activity is widely
used in statistical testing of effects of external stimulation, but has also been applied to …
used in statistical testing of effects of external stimulation, but has also been applied to …
autohrf-an R package for generating data-informed event models for general linear modeling of task-based fMRI data
The analysis of task-related fMRI data at the level of individual participants is commonly
based on general linear modeling (GLM), which allows us to estimate the extent to which the …
based on general linear modeling (GLM), which allows us to estimate the extent to which the …
Robust brain state decoding using bidirectional long short term memory networks in functional MRI
Decoding brain states of the underlying cognitive processes via learning discriminative
feature representations has recently gained a lot of interest in brain imaging studies …
feature representations has recently gained a lot of interest in brain imaging studies …
Statistická analýza časoprostorových procesů
P Anna - 2020 - dspace.cvut.cz
Tato disertační práce se zabývá časoprostorovými procesy a jejich aplikacemi na dva reálné
problémy. Prvním z nich je proces korespondence mezi úřady a soukromými osobami …
problémy. Prvním z nich je proces korespondence mezi úřady a soukromými osobami …
Statistical Analysis of the Spatiotemporal Processes
A Pidnebesna - 2020 - search.proquest.com
Tato disertační práce se zabývá časoprostorovými procesy a jejich aplikacemi na dva reálné
problémy. Prvním z nich je proces korespondence mezi úřady a soukromými os-obami …
problémy. Prvním z nich je proces korespondence mezi úřady a soukromými os-obami …
[PDF][PDF] BRAD: software for BRain Activity Detection from hemodynamic
Abstract Background and Objective: Precise estimation of neuronal activity from
neuroimaging data is one of the central challenges of the application of noninvasive …
neuroimaging data is one of the central challenges of the application of noninvasive …