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Psychomotor Performance

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Brain oscillatory correlates of visuomotor adaptive learning.

NeuroImage
Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory feedback in response to movement errors. Although adaptation operates within individual movements on a trial-to-trial basis, it can also undergo learn...

Abstraction and analogy-making in artificial intelligence.

Annals of the New York Academy of Sciences
Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite a long history of research on constructing artificial intelligence (AI) systems with...

Differentiating Motor Coordination in Children with Cerebral Palsy and Typically Developing Populations Through Exploratory Factor Analysis of Robotic Assessments.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
General motor and executive functions are integral for tasks of daily living and are typically assessed when quantifying impairment of an individual. Robotic tasks offer highly repeatable and objective measures of motor and cognitive function. Additi...

Deep learning for sex classification in resting-state and task functional brain networks from the UK Biobank.

NeuroImage
Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. Whil...

Coordination of top-down influence on V1 responses by interneurons and brain rhythms.

Bio Systems
Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the re...

Generative Adversarial Networks-Based Data Augmentation for Brain-Computer Interface.

IEEE transactions on neural networks and learning systems
The performance of a classifier in a brain-computer interface (BCI) system is highly dependent on the quality and quantity of training data. Typically, the training data are collected in a laboratory where the users perform tasks in a controlled envi...

Explaining distortions in metacognition with an attractor network model of decision uncertainty.

PLoS computational biology
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that mo...

Decoding with confidence: Statistical control on decoder maps.

NeuroImage
In brain imaging, decoding is widely used to infer relationships between brain and cognition, or to craft brain-imaging biomarkers of pathologies. Yet, standard decoding procedures do not come with statistical guarantees, and thus do not give confide...

Exploring differences for motor imagery using Teager energy operator-based EEG microstate analyses.

Journal of integrative neuroscience
In this paper, the differences between two motor imagery tasks are captured through microstate parameters (occurrence, duration and coverage, and mean spatial correlation (Mspatcorr)) derived from a novel method based on electroencephalogram microsta...