AIMC Topic: Functional Neuroimaging
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Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.
Human brain mapping
Oct 1, 2019
Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity ...
Cortical Tracking of Surprisal during Continuous Speech Comprehension.
Journal of cognitive neuroscience
Sep 3, 2019
Speech comprehension requires rapid online processing of a continuous acoustic signal to extract structure and meaning. Previous studies on sentence comprehension have found neural correlates of the predictability of a word given its context, as well...
Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization.
Schizophrenia research
Aug 6, 2019
BACKGROUND: The recent deep learning-based studies on the classification of schizophrenia (SCZ) using MRI data rely on manual extraction of feature vector, which destroys the 3D structure of MRI data. In order to both identify SCZ and find relevant b...
A visual encoding model based on deep neural networks and transfer learning for brain activity measured by functional magnetic resonance imaging.
Journal of neuroscience methods
Jun 27, 2019
BACKGROUND: Building visual encoding models to accurately predict visual responses is a central challenge for current vision-based brain-machine interface techniques. To achieve high prediction accuracy on neural signals, visual encoding models shoul...
Human visual cortical gamma reflects natural image structure.
NeuroImage
Jun 24, 2019
Many studies have reported visual cortical gamma-band activity related to stimulus processing and cognition. Most respective studies used artificial stimuli, and the few studies that used natural stimuli disagree. Electrocorticographic (ECoG) recordi...
3D-CNN based discrimination of schizophrenia using resting-state fMRI.
Artificial intelligence in medicine
Jun 22, 2019
MOTIVATION: This study reports a framework to discriminate patients with schizophrenia and normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain. Resting-state functional MRI data from a total of 144 subjects (72 pat...
A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy.
NeuroImage
Jun 14, 2019
In the analysis of functional Near-Infrared Spectroscopy (fNIRS) signals from real-world scenarios, artifact rejection is essential. However, currently there exists no gold-standard. Although a plenitude of methodological approaches implicitly assume...
Common spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface.
Journal of neuroscience methods
Apr 1, 2019
BACKGROUND: Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR)....
Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data.
International journal of neural systems
Mar 3, 2019
Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). Fluorodeo...
Task activations produce spurious but systematic inflation of task functional connectivity estimates.
NeuroImage
Dec 28, 2018
Most neuroscientific studies have focused on task-evoked activations (activity amplitudes at specific brain locations), providing limited insight into the functional relationships between separate brain locations. Task-state functional connectivity (...
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