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  Neuronal and hemodynamic events from fMRI time-series

Rajapakse, J., Kruggel, F. J., Zysset, S., & von Cramon, D. Y. (1998). Neuronal and hemodynamic events from fMRI time-series. Journal of Advanced Computational Intelligence, 2(6), 185-194. doi:10.20965/jaciii.1998.p0185.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-3A2D-B Version Permalink: http://hdl.handle.net/21.11116/0000-0003-3A2E-A
Genre: Journal Article

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 Creators:
Rajapakse, Jagath1, Author              
Kruggel, Frithjof J.2, Author              
Zysset, Stefan2, Author              
von Cramon, D. Yves2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634574              

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Free keywords: Functional magnetic resonance imaging; Hemodynamics; Neuronal responses; Vascular coupling; Hemodynamic modulating function
 Abstract: Time-series provided by high-resolution functional MR imaging (fMRI) bear rich information of underlying physiological processes and associated hemodynamic events of human brain activation during sensory and cognitive stimulation. A computational model to represent neuronal and hemodynamic events in fMRI time-series is presented where the transient neuronal activities are modeled with exponential functions and coupling between neuronal response and hemodynamic response is approximated by a linear convolution. The hemodynamic parameters, namely lag and dispersion, and neuronal parameters, namely rise time and fall time, quantitate some of the neuronal and hemodynamic events following a sensory, motor, or cognitive task. Methods to estimate neuronal responses with hemodynamic demodulation and parameters assuming exponential transient changes are presented. Experiments with simulated time-series demonstrate the robustness of the parameter estimation scheme and with fMRI data obtained in a memory retrieval task is used to illustrate how the model parameters can improve detection of relevant activation in fMRI. This paper highlights the potentials of fMRI to study neuronal populations and the use of the proposed model in identifying neurophysiological events of brain function.

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Language(s): eng - English
 Dates: 1998-05-011998-08-271998-12-20
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.20965/jaciii.1998.p0185
 Degree: -

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Title: Journal of Advanced Computational Intelligence
Source Genre: Journal
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Pages: - Volume / Issue: 2 (6) Sequence Number: - Start / End Page: 185 - 194 Identifier: -