AIMC Topic: Behavior

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Automated identification for autism severity level: EEG analysis using empirical mode decomposition and second order difference plot.

Behavioural brain research
BACKGROUND: Previous automated EEG-based diagnosis of autism spectrum disorders (ASD) using various nonlinear EEG analysis methods were limited to distinguish only children with ASD from those normally developed without approaching their autistic fea...

An empirical evaluation of multivariate lesion behaviour mapping using support vector regression.

Human brain mapping
Multivariate lesion behaviour mapping based on machine learning algorithms has recently been suggested to complement the methods of anatomo-behavioural approaches in cognitive neuroscience. Several studies applied and validated support vector regress...

Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Recent studies documented the importance of individuality and heterogeneity in care planning. In practice, varying behavioral responses are revealed in patients' care management (CM) records. However, today's care programs are structured around popul...

Cumulative inhibition in neural networks.

Cognitive processing
We show how a multi-resolution network can model the development of acuity and coarse-to-fine processing in the mammalian visual cortex. The network adapts to input statistics in an unsupervised manner, and learns a coarse-to-fine representation by u...

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.

Nature neuroscience
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis ca...

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

NeuroImage
Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accura...

The Relationship between Robot's Nonverbal Behaviour and Human's Likability Based on Human's Personality.

Scientific reports
At current state, although robotics technology has been immensely developed, the uncertainty to completely engage in human-robot interaction is still growing among people. Many current studies then started to concern about human factors that might in...

Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.

Informatics for health & social care
Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, communication, cognitive, and social skills and abilities. Despite being diagnosed with ASD, some individuals exhibit outstanding scholastic, non-academic, ...

Search for an Appropriate Behavior within the Emotional Regulation in Virtual Creatures Using a Learning Classifier System.

Computational intelligence and neuroscience
Emotion regulation is a process by which human beings control emotional behaviors. From neuroscientific evidence, this mechanism is the product of conscious or unconscious processes. In particular, the mechanism generated by a conscious process needs...

Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association.

Acta neurologica Belgica
Alzheimer's disease (AD) is a highly prevalent condition and its prevalence is expected to further increase due to the aging of the general population. It is obvious that the diagnosis of AD has implications for driving. Finally, driving discussions ...