9 research outputs found

    A Scalable Automated Diagnostic Feature Extraction System for EEGs

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    Researchers using Electroencephalograms (“EEGs”) to diagnose clinical outcomes often run into computational complexity problems. In particular, extracting complex, sometimes nonlinear, features from a large number of time-series often require large amounts of processing time. In this paper we describe a distributed system that leverages modern cloud-based technologies and tools and demonstrate that it can effectively, and efficiently, undertake clinical research. Specifically we compare three types of clusters, showing their relative costs (in both time and money) to develop a distributed machine learning pipeline for predicting gestation time based on features extracted from these EEGs

    Neural and behavioral measures suggest that cognitive and affective functioning interactions mediate risk for psychosis-proneness symptoms in youth with chromosome 22q11.2 deletion syndrome.

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    Behavioral components of chromosome 22q11.2 deletion syndrome (22q), caused by the most common human microdeletion, include cognitive and adaptive functioning impairments, heightened anxiety, and an elevated risk of schizophrenia. We investigated how interactions between executive function and the largely overlooked factor of emotion regulation might relate to the incidence of symptoms of psychotic thinking in youth with 22q. We measured neural activity with event-related potentials (ERPs) in variants of an inhibitory function (Go/No-Go) experimental paradigm that presented affective or non-affective stimuli. The study replicated inhibition impairments in the 22q group that were amplified in the presence of stimuli with negative, more than positive affective salience. Importantly, the anterior N2 conflict monitoring ERP significantly increased when youth with 22q viewed angry and happy facial expressions, unlike the typically developing participants. This suggests that youth with 22q may require greater conflict monitoring resources when controlling their behavior in response to highly salient social signals. This evidence of both behavioral and neurophysiological differences in affectively influenced inhibitory function suggests that frequently anxious youth with 22q may struggle more with cognitive control in emotionally charged social settings, which could influence their risk of developing symptoms of psychosis
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