AIMC Topic: Functional Neuroimaging
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Generative adversarial networks for reconstructing natural images from brain activity.
NeuroImage
Jul 20, 2018
We explore a method for reconstructing visual stimuli from brain activity. Using large databases of natural images we trained a deep convolutional generative adversarial network capable of generating gray scale photos, similar to stimuli presented du...
Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 16, 2018
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...
Prospective motion correction improves the sensitivity of fMRI pattern decoding.
Human brain mapping
Jun 8, 2018
We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in-bore optical camera to track an external marker attached to the participant via...
The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks.
NeuroImage
May 17, 2018
Visual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categ...
Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.
BMC medical informatics and decision making
Dec 20, 2017
BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal peop...
A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines.
Journal of neuroscience methods
Oct 7, 2017
BACKGROUND: Functional transcranial Doppler (fTCD) is an ultrasound based neuroimaging technique used to assess neural activation that occurs during a cognitive task through measuring velocity of cerebral blood flow.
Ultrasonography, Doppler, Transcranial
Neuropsychological Tests
Cerebrovascular Circulation
Space Perception
Imagination
Cognition
Support Vector Machine
Feasibility Studies
Rotation
Linear Models
Language
Rest
Female
Humans
Brain-Computer Interfaces
Young Adult
Brain
Wavelet Analysis
Male
Blood Flow Velocity
Functional Neuroimaging
Identification of autism spectrum disorder using deep learning and the ABIDE dataset.
NeuroImage. Clinical
Aug 30, 2017
The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imagi...
EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.
Consciousness and cognition
Nov 14, 2016
fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ E...
Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland.
Psychological medicine
Oct 25, 2016
BACKGROUND: While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning methods provide a tool to test whether some of such alterations could be used to differentiate an ind...
A Hybrid Multishape Learning Framework for Longitudinal Prediction of Cortical Surfaces and Fiber Tracts Using Neonatal Data.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Oct 2, 2016
Dramatic changes of the human brain during the first year of postnatal development are poorly understood due to their multifold complexity. In this paper, we present the first attempt to jointly predict, using neonatal data, the dynamic growth patter...
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