Detection of atypical attentional behaviors in young subjects.

BACKGROUND: Vigilance ability refers to the accuracy and speed with which a person performs a cognitive-motor task, either voluntarily (endogenous mode) or following a warning stimulus (exogenous mode). In the context of a force production task, our study focuses on the impact of the states of vigilance by proposing an original approach that allows distinguishing between good (inlier) and poor (outlier) participants. We assume that the use of an external signal and duration of the temporal preparation (foreperiod) increase the speed and the precision of motor responses. Our objective is particularly challenging in the context of a limited dataset with a high level of noise. NEW METHOD: Our original methodological approach consists of coupling the RANSAC (RANdom SAmple Consensus) algorithm with a statistical machine learning algorithm to handle noise. COMPARISON WITH EXISTING METHODS: Our clustering approach, based on the coupling of RANSAC methodology with ensemble classifiers, overcomes the limitations of conventional supervised algorithms that are either not robust to outliers (such as K-Nearest Neighbors) and/or not adapted to few-shot learning (such as Support Vector Machines and Artificial Neural Networks). RESULTS: The clustering results were validated in terms of reaction time distributions and force error distributions with respect to participant groups. We show that the use of an external signal and duration of the temporal preparation (foreperiod) increase the speed and the precision of motor responses. CONCLUSION: Our study has allowed us to detect atypical attentional patterns and succeeds in separating the inliers from the outliers.

Influence of Mental Training of Attentional Control on Autonomic Arousal Within the Framework of the Temporal Preparation of a Force Task.

While temporal preparation has frequently been examined through the manipulation of foreperiods, the role of force level during temporal preparation remains underexplored. In our study, we propose to manipulate mental training of attentional control in order to shed light on the role of the force level and autonomic nervous system in the temporal preparation of an action. Forty subjects, divided into mental training group (n = 20) and without mental training group (n = 20), participated in this study. The influence of the attentional control and force levels on the autonomic nervous system were measured using the skin conductance response and the heart rate variability; the accuracy of the motor responses was measured using a method derived from machine learning. Behaviorally, only the mental training group reinforced its motor and attentional control. When using short foreperiod durations and high force level, motor and attentional control decreased, consistent with the dominant sympathetic system. This resulted in an increased anticipation rate of responses with a higher reaction time compared to the long foreperiods duration and low force level, in which the reaction time significantly decreased, with enhancement of the expected force level, showing consistency with the dominant parasympathetic system. Interestingly, results revealed a predictive relationship between the sympathovagal balance and motor and attentional control during the long foreperiods and low force level. Finally, results demonstrate that attentional mental training leads to the reinforcement of interactions between the autonomic nervous system and attentional processes which are involved in the temporal preparation of a force task.