Results 261 to 270 of about 64,815 (293)

AI-Driven Multimodal Brain-State Decoding for Personalized Closed-Loop TENS: A Comprehensive Review. [PDF]

Brain Sci
Du J, Luo S, Shi P.
europepmc   +1 more source

Editorial: Neuromuscular and kinematic dynamics in human movement adaptation. [PDF]

Front Hum Neurosci
Singh RE, Davies JL, Purcell C.
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Increased detection sensitivity in fMRI by adaptive filtering.

, 2001
Friman, Ola, Lundberg, Peter, Borga, Magnus, Cedefamn, Jonny, Knutsson, Hans   +4 more
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Adaptive Smoothing Applied to fMRI Data

Proceedings of the 4th International Joint Conference on Computational Intelligence, 2012
IJCCI ...
Bartés i Serrallonga, Manel, Serra Grabulosa, Josep M., Adan, Ana, Falcón, Carles, Bargalló, Núria, Solé-Casals, Jordi   +5 more
openaire   +3 more sources

Orientation-Tuned fMRI Adaptation in Human Visual Cortex

Journal of Neurophysiology, 2005
Adaptation is a general property of almost all neural systems and has been a longstanding tool of psychophysics because of its power to isolate and temporarily reduce the contribution of specific neural populations. Recently, adaptation designs have been extensively applied in functional MRI (fMRI) studies to infer neural selectivity in specific ...
Fang, Fang, Scott O, Murray, Daniel, Kersten, Sheng, He   +3 more
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Spatially Adaptive Kernels for Adaptive Spatial Filtering of fMRI Data

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
Making use of neighborhood time series is an effective way of noise reduction in fMRI data. However the conventional averaging methods blur activated areas. In this paper, a filter with adaptive kernel is designed such that its kernel size and direction are defined at each voxel.
V. Taimouri, G.-A. Hossein-Zadeh, H. Soltanian-Zadeh   +2 more
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Group-level adaptive-analysis of task fMRI data

ISMRM Annual Meeting, 2023
A task-fMRI group-level analysis method is proposed to incorporate spatial covariance structures in fMRI data using the subject-level steerable filter smoothing with various full-wide-half-maximums followed by a group-level one-step optimization. Subject-level smoothed time series are further orthogonalized to guarantee non-overlapped contributions to ...
Xiaowei Zhuang, Zhengshi Yang, Tim Curran, Rajesh Nandy, Mark Lowe, Dietmar Cordes   +5 more
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Rotational Invariance in Adaptive fMRI Data Analysis

2006 International Conference on Image Processing, 2006
It has previously been shown that canonical correlation analysis (CCA) works well for detecting neural activity in fMRI data. This is due to the ability of CCA to perform simultaneous temporal modeling and adaptive spatial filtering of the data. In this paper, we demonstrate that our previously proposed method for CCA-based fMRI data analysis does not ...
Joakim Rydell, Hans Knutsson, Magnus Borga   +2 more
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An Adaptive Regression Mixture Model for fMRI Cluster Analysis

IEEE Transactions on Medical Imaging, 2013
Functional magnetic resonance imaging (fMRI) has become one of the most important techniques for studying the human brain in action. A common problem in fMRI analysis is the detection of activated brain regions in response to an experimental task. In this work we propose a novel clustering approach for addressing this issue using an adaptive regression
Vangelis P, Oikonomou, Konstantinos, Blekas   +1 more
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Data from: Color contrast adaptation: fMRI fails to predict behavioral adaptation

2019
Work published as: Goddard E, Chang DHF, Hess RF, Mullen KT (2019) Color contrast adaptation: fMRI fails to predict behavioral adaptation. Neuroimage (accepted July 2019). DOI: https://doi.org/10.1016/j.neuroimage.2019.116032. Please cite this paper if you use the data on this project.
Goddard, Erin, Mullen, Kathy
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