Results 1 to 10 of about 3,878 (155)

A novel technique for delineating the effect of variation in the learning rate on the neural correlates of reward prediction errors in model-based fMRI [PDF]

Frontiers in Psychology, 2023
IntroductionComputational models play an increasingly important role in describing variation in neural activation in human neuroimaging experiments, including evaluating individual differences in the context of psychiatric neuroimaging.
Henry W. Chase
doaj   +2 more sources

Second derivative General Linear Method in Nordsieck form

Journal of Numerical Analysis and Approximation Theory, 2019
This paper considers the construction of second derivative general linear methods (SD-GLM) from hybrid LMM and their transformation to Nordsieck GLM. How the Runge-Kutta starters for the methods can be derived are given.
Robert I. Okuonghae, Monday Ndidi Oziegbe Ikhile   +1 more
doaj   +7 more sources

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Frontiers in Neuroscience, 2022
The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation.
Parviz Ghaderi, Parviz Ghaderi, Marjan Nosouhi, Mislav Jordanic, Hamid Reza Marateb, Hamid Reza Marateb, Miguel Angel Mañanas, Miguel Angel Mañanas, Dario Farina   +8 more
doaj   +1 more source

Pros and cons of using the informed basis set to account for hemodynamic response variability with developmental data

Frontiers in Neuroscience, 2016
Conventional analysis of functional magnetic resonance imaging (fMRI) data using the general linear model (GLM) employs a neural model convolved with a canonical hemodynamic response function (HRF) peaking 5s after stimulation. Incorporation of a further
Fabien Cignetti, Fabien Cignetti, Emilie Salvia, Emilie Salvia, Jean-Luc Anton, Marie-Helene Grosbras, Marie-Helene Grosbras, Christine Assaiante, Christine Assaiante   +8 more
doaj   +1 more source

A New SDIMSIM Methods with Optimized Region of Stability and Sustainable Development with Applications On Neutrosophic Data [PDF]

Neutrosophic Sets and Systems
General Linear Methods (GLMs) were introduced as logical extensions of the conventional Runge–Kutta and linear multistep methods. In the scenario when second derivatives, in addition to first derivatives, can be computed, a GLM modification known as ...
A.Y. J. Almasoodi, Mohammed Kadhim Mohsin, Sarah A.AL-Ameedee, Mohammed Amer Shanyoor   +3 more
doaj   +1 more source

Optimized statistical parametric mapping procedure for NIRS data contaminated by motion artifacts

Brain Informatics, 2017
This study investigated the spatial distribution of brain activity on body schema (BS) modification induced by natural body motion using two versions of a hand-tracing task.
Satoshi Suzuki
doaj   +1 more source

Optimizing short-channel regression in fNIRS: an empirical evaluation with ecological audiovisual stimuli. [PDF]

Neurophotonics
Lemaire Y, Barone P, Strelnikov K, Deguine O, Caclin A, Ginzburg J.   +5 more
europepmc   +1 more source

Nonlinear kernel-based fMRI activation detection. [PDF]

Front Neuroimaging
Han C, Yang Z, Zhuang X, Cordes D.
europepmc   +1 more source

Determining disease attributes from epidemic trajectories. [PDF]

Infect Dis Model
Rast MP, Rast LI.
europepmc   +1 more source

Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy. [PDF]

BME Front
Takahashi Y, Soda T, Tomita H, Yamashita Y.   +3 more
europepmc   +1 more source