Epilepsy
is a common neurological condition that can occur in anyone at any age.
Electroencephalogram (EEG) signals of non-focal (NF) and focal (F)
types contain brain activity information that ...
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The problem of increasing the slice resolution of functional
MRI (fMRI) images without a loss in signal-to-noise ratio is
considered. In standard fMRI experiments,...
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Why Python?
Python is rapidly becoming the standard language for data analysis,
visualization and automated workflow building.
It is a free and open-source software that is relatively easy to pi...
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IntroductionDuring
the past decades, there has been an increasing interest in tracking
brain network fluctuations in health and disease by means of resting
state functional magnetic resonance im...
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Vision science, particularly machine vision, has been revolutionized by
introducing large-scale image datasets and statistical learning
approaches. Yet, human neuroimaging studies of visual percep...
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Due to the nature of fMRI acquisition protocols, slices cannot be acquired simultaneously, and as a result, are temporally misaligned from each other. To correct from this misalignment, preprocessing ...
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A Practical Guide to Understanding and Evaluating fMRI Studies
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In the interest of full-disclosure and to be as open-data/source as
possible, we are including links to our data reported in published
articles.
For our meta-analysis projects, we have incl...
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Bayesian RSA builds a generative model for fMRI data which include a
covariance structure as estimation target. The covariance structure
specifies the distribution by which the unknown spatial neu...
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Analysis and interpretation of
functional MRI (fMRI) data have traditionally been based on identifying
areas of significance on a thresholded statistical map of the entire
imaged brain volume. T...
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An introduction to Nilearn FMRI package
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We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP) dat...
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OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedbacktraining based on activity, connectivity and multivariate pattern analysis
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Background. The choice of preprocessing pipeline introduces variability in neuroimaging analyses that affects the reproducibility of scientific findings
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Signal-to-noise ratio, the ratio between signal and noise, is a quantity that has been well established for MRI data but is still subject of ongoing debate and confusion when it comes to fMRI data. fM...
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