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      Optimizing the Performance of the Visual P300-Speller Through Active Mental Tasks Based on Color Distinction and Modulation of Task Difficulty

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          Abstract

          Objective: P300-speller is the most commonly used brain-computer interface (BCI) for providing a means of communication to patients with amyotrophic lateral sclerosis. However, the performance of the P300-speller BCI is still inadequate. We investigated whether the performance of P300-speller can be further improved by increasing the mental effort required of the user.

          Methods: We designed two active mental tasks for a P300-speller based on a differently colored smiling cartoon-face paradigm. The tasks were based on color distinction, and their difficulty was modulated. One of the active mental tasks (DC task) required participants to focus on and distinguish the color of a target, while the other task (CN + DC task) required participants to simultaneously count the number of times a target flashed and distinguish its color.

          Results: The amplitudes of the event-related potentials (ERPs) in both DC and CN + DC tasks were higher than that in the CN task. The significant difference in the amplitudes between the DC and CN tasks was observed around the parietal-central area from 440 to 800 ms (late positive component, LPC), and that between the CN + DC and CN tasks was observed around the left-frontal and right-frontal areas from 320 to 480 ms (P3a) and the parietal-central area from 480 to 800 ms (P3b and LPC). The latency of the P300 potential in the CN + DC task was significantly longer than that in the CN task at F3, Fz, F4, C4, Pz, and P4 ( P < 0.05). Offline ( P < 0.05 at superposing once, twice, and thrice) and online ( P < 0.001) classification results showed that the average accuracies in the CN + DC task were significantly greater than that in the CN task. Similar results were found for online information transfer rates (ITRs; P < 0.001). In addition, we found that the average online accuracies in the DC task were greater than those in the CN task, although the difference was not statistically significant ( P = 0.051).

          Significance: The active mental task based on task difficulty modulation can significantly improve the performance of the P300-speller, and that based on color distinction shows a trend of improved performance.

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          Most cited references41

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          Brain potentials in affective picture processing: covariation with autonomic arousal and affective report

          Emotionally arousing picture stimuli evoked scalp-recorded event-related potentials. A late, slow positive voltage change was observed, which was significantly larger for affective than neutral stimuli. This positive shift began 200-300 ms after picture onset, reached its maximum amplitude approximately 1 s after picture onset, and was sustained for most of a 6-s picture presentation period. The positive increase was not related to local probability of content type, but was accentuated for pictures that prompted increased autonomic responses and reports of greater affective arousal (e.g. erotic or violent content). These results suggest that the late positive wave indicates a selective processing of emotional stimuli, reflecting the activation of motivational systems in the brain.
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            Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

            This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., 'locked-in' patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min.
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              An efficient P300-based brain-computer interface for disabled subjects.

              A brain-computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In other words, a BCI allows users to act on their environment by using only brain-activity, without using peripheral nerves and muscles. In this paper, we present a BCI that achieves high classification accuracy and high bitrates for both disabled and able-bodied subjects. The system is based on the P300 evoked potential and is tested with five severely disabled and four able-bodied subjects. For four of the disabled subjects classification accuracies of 100% are obtained. The bitrates obtained for the disabled subjects range between 10 and 25bits/min. The effect of different electrode configurations and machine learning algorithms on classification accuracy is tested. Further factors that are possibly important for obtaining good classification accuracy in P300-based BCI systems for disabled subjects are discussed.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                17 April 2019
                2019
                : 13
                : 130
                Affiliations
                School of Computer Science and Technology, Changchun University of Science and Technology , Changchun, China
                Author notes

                Edited by: Srikantan S. Nagarajan, University of California, San Francisco, United States

                Reviewed by: Sung Chan Jun, Gwangju Institute of Science and Technology, South Korea; Jing Jin, East China University of Science and Technology, China

                *Correspondence: Qi Li liqi@ 123456cust.edu.cn
                Article
                10.3389/fnhum.2019.00130
                6478661
                31057381
                a0467d4d-c794-41dc-8821-d4ce1b45c435
                Copyright © 2019 Li, Lu, Gao and Yang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 October 2018
                : 28 March 2019
                Page count
                Figures: 12, Tables: 2, Equations: 1, References: 43, Pages: 14, Words: 8395
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 61773076 and 61806025
                Categories
                Neuroscience
                Original Research

                Neurosciences
                brain-computer interface,visual p300-speller,active mental task,color distinction,task difficulty

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