AIMC Topic: Psychomotor Performance
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Image memorability is predicted by discriminability and similarity in different stages of a convolutional neural network.
Learning & memory (Cold Spring Harbor, N.Y.)
Nov 16, 2020
The features of an image can be represented at multiple levels-from its low-level visual properties to high-level meaning. What drives some images to be memorable while others are forgettable? We address this question across two behavioral experiment...
Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging.
Human brain mapping
Nov 13, 2020
Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the abil...
Adult
Male
Deep Learning
Functional Neuroimaging
Adolescent
Humans
Machine Learning
Female
Young Adult
Schizophrenia
Outcome Assessment, Health Care
Psychomotor Performance
Dorsolateral Prefrontal Cortex
Executive Function
Bipolar Disorder
Support Vector Machine
Follow-Up Studies
Magnetic Resonance Imaging
The use of machine learning improves the assessment of drug-induced driving behaviour.
Accident; analysis and prevention
Oct 27, 2020
RATIONALE: Car-driving performance is negatively affected by the intake of alcohol, tranquillizers, sedatives and sleep deprivation. Although several studies have shown that the standard deviation of the lateral position on the road (SDLP) is sensiti...
fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.
NeuroImage
Sep 5, 2020
Deep-learning methods based on deep neural networks (DNNs) have recently been successfully utilized in the analysis of neuroimaging data. A convolutional neural network (CNN) is a type of DNN that employs a convolution kernel that covers a local area...
Machine-learning approach to predict on-road driving ability in healthy older people.
Psychiatry and clinical neurosciences
Jul 20, 2020
AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who...
Robotic assessment of rapid motor decision making in children with perinatal stroke.
Journal of neuroengineering and rehabilitation
Jul 14, 2020
BACKGROUND: Activities of daily living frequently require children to make rapid decisions and execute desired motor actions while inhibiting unwanted actions. Children with hemiparetic cerebral palsy due to perinatal stroke may have deficits in exec...
Robotics-assisted visual-motor training influences arm position sense in three-dimensional space.
Journal of neuroengineering and rehabilitation
Jul 14, 2020
BACKGROUND: Performing activities of daily living depends, among other factors, on awareness of the position and movements of limbs. Neural injuries, such as stroke, might negatively affect such an awareness and, consequently, lead to degrading the q...
Decoding attention control and selection in visual spatial attention.
Human brain mapping
Jun 16, 2020
Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by appl...
Single-Trial EEG Responses Classified Using Latency Features.
International journal of neural systems
Jun 2, 2020
Covert attention has been repeatedly shown to impact on EEG responses after single and repeated practice sessions. Machine learning techniques are increasingly adopted to classify single-trial EEG responses thereby primarily relying on amplitude-base...
The interplay between multisensory integration and perceptual decision making.
NeuroImage
May 23, 2020
Facing perceptual uncertainty, the brain combines information from different senses to make optimal perceptual decisions and to guide behavior. However, decision making has been investigated mostly in unimodal contexts. Thus, how the brain integrates...
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