AIMC Topic: Neuropsychological Tests

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Decoding intracranial EEG data with multiple kernel learning method.

Journal of neuroscience methods
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...

Therapeutic effects of dog visits in nursing homes for the elderly.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Previous studies have suggested that visiting dogs can have positive effects on elderly people in nursing homes. We wanted to study the effects of biweekly dog visits on sleep patterns and the psychiatric well-being of elderly people.

Spatially regularized machine learning for task and resting-state fMRI.

Journal of neuroscience methods
BACKGROUND: Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades.

Test-retest reliability of KINARM robot sensorimotor and cognitive assessment: in pediatric ice hockey players.

Journal of neuroengineering and rehabilitation
BACKGROUND: Better diagnostic and prognostic tools are needed to address issues related to early diagnosis and management of concussion across the continuum of aging but particularly in children and adolescents. The purpose of the current study was t...

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers.

Biomedical engineering online
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionna...

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

International journal of geriatric psychiatry
OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate ...

Exploring the dynamics of design fluency in children with and without ADHD using artificial neural networks.

Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence
The neuropsychology of attention deficit/hyperactivity disorder (ADHD) has been extensively studied, with a general focus on global performance measures of executive function. In this study, we compared how global (i.e., endpoint) versus process (i.e...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

Journal of affective disorders
BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning mo...

Fractal analysis for cognitive impairment classification in DAVF using machine learning.

Biomedical physics & engineering express
. Intracranial dural arteriovenous fistula (DAVF) is an acquired vascular condition involving abnormal connections between dural arteries and veins without intervening capillary beds. Cognitive impairment is a common symptom in DAVFs, often linked to...