AIMC Topic: Memory, Short-Term
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Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits.
NeuroImage
May 30, 2020
Accumulating evidence from whole brain functional magnetic resonance imaging (fMRI) suggests that the human brain at rest is functionally organized in a spatially and temporally constrained manner. However, because of their complexity, the fundamenta...
Working memory load-dependent changes in cortical network connectivity estimated by machine learning.
NeuroImage
May 1, 2020
Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to cha...
Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning.
PloS one
Mar 3, 2020
OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e...
Humans
Machine Learning
Female
Young Adult
Adult
Social Communication Disorder
Communication
Models, Psychological
Cognition
Male
Linguistics
Middle Aged
Schizophrenic Psychology
Case-Control Studies
Theory of Mind
Bayes Theorem
Executive Function
Memory, Short-Term
Schizophrenia
Neuropsychological Tests
Effect of recurrent infomax on the information processing capability of input-driven recurrent neural networks.
Neuroscience research
Feb 14, 2020
Reservoir computing is a framework for exploiting the inherent transient dynamics of recurrent neural networks (RNNs) as a computational resource. On the basis of this framework, much research has been conducted to evaluate the relationship between t...
Machine learning validation of EEG+tACS artefact removal.
Journal of neural engineering
Jan 24, 2020
OBJECTIVE: Electroencephalography (EEG) recorded during transcranial alternating current simulation (tACS) is highly desirable in order to investigate brain dynamics during stimulation, but is corrupted by large amplitude stimulation artefacts. Artef...
Assessing various sensorimotor and cognitive functions in people with epilepsy is feasible with robotics.
Epilepsy & behavior : E&B
Jan 7, 2020
BACKGROUND: Epilepsy is a common neurological disorder characterized by recurrent seizures, along with comorbid cognitive and psychosocial impairment. Current gold standards of assessment can quantify cognitive and motor performance, but may not capt...
Interpreting neural decoding models using grouped model reliance.
PLoS computational biology
Jan 6, 2020
Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. However, as a step towards bridging the gap between theory-driven cognitive neuroscience and data-driven decoding approaches, th...
Decoding and mapping task states of the human brain via deep learning.
Human brain mapping
Dec 9, 2019
Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requir...
Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.
Scientific reports
Nov 22, 2019
Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to class...
Electroencephalography
Epilepsy
Memory, Short-Term
Datasets as Topic
Task Performance and Analysis
Sensitivity and Specificity
Cognition
Unsupervised Machine Learning
Brain Mapping
Electrodes, Implanted
Electrophysiological Phenomena
Humans
Algorithms
Evoked Potentials
Brain
Verbal Behavior
Retrospective Studies
Electrocorticography
Biomedical Engineering
The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS?
International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Oct 19, 2019
The ability to identify reliable and sensitive physiological signatures of psychological dimensions is key to developing intelligent adaptive systems that may in turn help to mitigate human error in complex operations. The challenge of this endeavor ...
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