scholarly journals Influence of previous information on self-assessment in the sensory-motor task

2018 ◽  
Vol 19 (3) ◽  
pp. 267-276
Author(s):  
K. Švátora
1997 ◽  
Vol 36 (04/05) ◽  
pp. 322-325
Author(s):  
A. Terao ◽  
T. Hasbroucq ◽  
I. Mouret ◽  
J. Seal ◽  
M. Akamatsu

Abstract:Single neuron activities from cortical areas of a monkey were recorded while performing a sensory-motor task (a choice reaction time task). Quantitative trial-by-trial analysis revealed that the timing of peak activity exhibited large variation from trial to trial, compared to the variation in the behavioral reaction time of the task. Therefore, we developed a multi-unit dynamic neural network model to investigate the effects of structure of neural connections on the variation of the timing of peak activity. Computer simulation of the model showed that, even though the units are connected in a cascade fashion, a wide variation exists in the timing of peak activity of neurons because of parallel organization of neural network within each unit.


Author(s):  
Florian Lanz ◽  
Véronique Moret ◽  
Eric Michel Rouiller ◽  
Gérard Loquet

2019 ◽  
Vol 116 (13) ◽  
pp. 6482-6490 ◽  
Author(s):  
Josef Faller ◽  
Jennifer Cummings ◽  
Sameer Saproo ◽  
Paul Sajda

Our state of arousal can significantly affect our ability to make optimal decisions, judgments, and actions in real-world dynamic environments. The Yerkes–Dodson law, which posits an inverse-U relationship between arousal and task performance, suggests that there is a state of arousal that is optimal for behavioral performance in a given task. Here we show that we can use online neurofeedback to shift an individual’s arousal from the right side of the Yerkes–Dodson curve to the left toward a state of improved performance. Specifically, we use a brain–computer interface (BCI) that uses information in the EEG to generate a neurofeedback signal that dynamically adjusts an individual’s arousal state when they are engaged in a boundary-avoidance task (BAT). The BAT is a demanding sensory-motor task paradigm that we implement as an aerial navigation task in virtual reality and which creates cognitive conditions that escalate arousal and quickly results in task failure (e.g., missing or crashing into the boundary). We demonstrate that task performance, measured as time and distance over which the subject can navigate before failure, is significantly increased when veridical neurofeedback is provided. Simultaneous measurements of pupil dilation and heart-rate variability show that the neurofeedback indeed reduces arousal. Our work demonstrates a BCI system that uses online neurofeedback to shift arousal state and increase task performance in accordance with the Yerkes–Dodson law.


1999 ◽  
Vol 841 (1-2) ◽  
pp. 170-183 ◽  
Author(s):  
Donatella Carretta ◽  
Anne Hervé-Minvielle ◽  
Victoria M Bajo ◽  
Alessandro E.P Villa ◽  
Eric M Rouiller

1964 ◽  
Vol 18 (3) ◽  
pp. 753-762 ◽  
Author(s):  
Paul A. Obrist ◽  
Shannon I. Hallman ◽  
Donald M. Wood

Author(s):  
Hiroshi Ono ◽  
Joseph P. O'Reilly

Adaptation to underwater distance distortion was investigated as a function of three sensory-motor tasks and exposure time. The tasks differed in terms of the extent to which visual feedback during the reaching response was provided. Eighteen experienced divers served as subjects. Each subject performed the three sensory-motor tasks and also observed another subject performing the tasks. Underwater distance perception was measured after each sensory-motor task and observing period. Adaptation occurred when the subjects performed the tasks but not when they were observing. The different sensory-motor tasks produced different amounts of adaptation. An argument is made that visually predirected reaching responses (no feedback) would produce greater adaptation than visually guided (feedback) reaching responses.


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