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The behavioral and neural basis of empathic blame.

Scientific reports
Mature moral judgments rely both on a perpetrator's intent to cause harm, and also on the actual harm caused-even when unintended. Much prior research asks how intent information is represented neurally, but little asks how even unintended harms infl...

Continuous sweep versus discrete step protocols for studying effects of wearable robot assistance magnitude.

Journal of neuroengineering and rehabilitation
BACKGROUND: Different groups developed wearable robots for walking assistance, but there is still a need for methods to quickly tune actuation parameters for each robot and population or sometimes even for individual users. Protocols where parameters...

Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India.

Social psychiatry and psychiatric epidemiology
BACKGROUND: There are limited data on the use of artificial intelligence methods for the diagnosis of dementia in epidemiological studies in low- and middle-income country (LMIC) settings. A culture and education fair battery of cognitive tests was d...

Preliminary testing by adults of a haptics-assisted robot platform designed for children with physical impairments to access play.

Assistive technology : the official journal of RESNA
Development of children's cognitive and perceptual skills depends heavily on object exploration and experience in their physical world. For children who have severe physical impairments, one of the biggest concerns is the loss of opportunities for me...

Identifying incipient dementia individuals using machine learning and amyloid imaging.

Neurobiology of aging
Identifying individuals destined to develop Alzheimer's dementia within time frames acceptable for clinical trials constitutes an important challenge to design studies to test emerging disease-modifying therapies. Although amyloid-β protein is the co...

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increa...

Machine learning methods to predict child posttraumatic stress: a proof of concept study.

BMC psychiatry
BACKGROUND: The care of traumatized children would benefit significantly from accurate predictive models for Posttraumatic Stress Disorder (PTSD), using information available around the time of trauma. Machine Learning (ML) computational methods have...

The impact of goal-oriented task design on neurofeedback learning for brain-computer interface control.

Medical & biological engineering & computing
Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain-computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented ta...

Detection of lithospermate B in rat plasma at the nanogram level by LC/MS in multi reaction monitoring mode.

Journal of food and drug analysis
Low bioavailability and high binding affinity to plasma proteins led to the difficulty for the quantitative detection of lithospermate B (LSB) in plasma. This study aimed to develop a protocol for detecting LSB in plasma. A method was employed to qua...

Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy: A computational study.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically evolve in time. We aim to improve the understanding of pathophysiological mechanisms underlying these EEG abnormalities.