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Estimating endogenous changes in task performance from EEG.

Touryan J, Apker G, Lance BJ, Kerick SE, Ries AJ, McDowell K - Front Neurosci (2014)

Bottom Line: For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant.The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30).These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity.

View Article: PubMed Central - PubMed

Affiliation: U.S. Army Research Laboratory, Human Research and Engineering Directorate Aberdeen Proving Ground, MD, USA.

ABSTRACT
Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance. Here, we explore the potential for extending an established method to generate continuous estimates of behavioral performance from ongoing neural activity; evaluating the extended method by applying it to the original task domain, simulated driving; and generalizing the method by applying it to a BCI-relevant perceptual discrimination task. Specifically, we used EEG log power spectra and sequential forward floating selection (SFFS) to estimate endogenous changes in behavior in both a simulated driving task and a perceptual discrimination task. For the driving task the average correlation coefficient between the actual and estimated lane deviation was 0.37 ± 0.22 (μ ± σ). For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant. The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30). These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity.

No MeSH data available.


Related in: MedlinePlus

Experimental overview. (A) Experiment timeline including calibration, driving, and RSVP tasks (note that the order of the driving and RSVP tasks alternate between participants). Vertical black lines indicate block intervals where fatigue surveys were administered. (B) Screenshot of driving simulator. (C) RSVP paradigm and example images. Figure adapted from Touryan et al. (2013a).
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Figure 1: Experimental overview. (A) Experiment timeline including calibration, driving, and RSVP tasks (note that the order of the driving and RSVP tasks alternate between participants). Vertical black lines indicate block intervals where fatigue surveys were administered. (B) Screenshot of driving simulator. (C) RSVP paradigm and example images. Figure adapted from Touryan et al. (2013a).

Mentions: Twenty-five participants were recruited from the general population. They ranged in age from 21 to 57 (μ = 34.6) and included ten males. Twenty-one of the participants were right handed, two were left handed, and two were ambidextrous. All individuals participated in a single multi-hour session containing three phases and received compensation of $20 per hour. The voluntary, fully informed consent of the persons used in this research was obtained as required by Title 32, Part 219 of the Code of Federal Regulations and Army Regulation 70-25. The investigator adhered to the policies for the protection of human subjects as prescribed in AR 70-25. None of the participants were excluded from the analysis due to noise, movement artifacts, or low behavioral performance. The study design involved 3 tasks (Figure 1): calibration, driving, and rapid serial visual presentation (RSVP). The calibration session was always performed first but the order of the driving and RSVP alternated for each participant.


Estimating endogenous changes in task performance from EEG.

Touryan J, Apker G, Lance BJ, Kerick SE, Ries AJ, McDowell K - Front Neurosci (2014)

Experimental overview. (A) Experiment timeline including calibration, driving, and RSVP tasks (note that the order of the driving and RSVP tasks alternate between participants). Vertical black lines indicate block intervals where fatigue surveys were administered. (B) Screenshot of driving simulator. (C) RSVP paradigm and example images. Figure adapted from Touryan et al. (2013a).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4061490&req=5

Figure 1: Experimental overview. (A) Experiment timeline including calibration, driving, and RSVP tasks (note that the order of the driving and RSVP tasks alternate between participants). Vertical black lines indicate block intervals where fatigue surveys were administered. (B) Screenshot of driving simulator. (C) RSVP paradigm and example images. Figure adapted from Touryan et al. (2013a).
Mentions: Twenty-five participants were recruited from the general population. They ranged in age from 21 to 57 (μ = 34.6) and included ten males. Twenty-one of the participants were right handed, two were left handed, and two were ambidextrous. All individuals participated in a single multi-hour session containing three phases and received compensation of $20 per hour. The voluntary, fully informed consent of the persons used in this research was obtained as required by Title 32, Part 219 of the Code of Federal Regulations and Army Regulation 70-25. The investigator adhered to the policies for the protection of human subjects as prescribed in AR 70-25. None of the participants were excluded from the analysis due to noise, movement artifacts, or low behavioral performance. The study design involved 3 tasks (Figure 1): calibration, driving, and rapid serial visual presentation (RSVP). The calibration session was always performed first but the order of the driving and RSVP alternated for each participant.

Bottom Line: For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant.The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30).These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity.

View Article: PubMed Central - PubMed

Affiliation: U.S. Army Research Laboratory, Human Research and Engineering Directorate Aberdeen Proving Ground, MD, USA.

ABSTRACT
Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance. Here, we explore the potential for extending an established method to generate continuous estimates of behavioral performance from ongoing neural activity; evaluating the extended method by applying it to the original task domain, simulated driving; and generalizing the method by applying it to a BCI-relevant perceptual discrimination task. Specifically, we used EEG log power spectra and sequential forward floating selection (SFFS) to estimate endogenous changes in behavior in both a simulated driving task and a perceptual discrimination task. For the driving task the average correlation coefficient between the actual and estimated lane deviation was 0.37 ± 0.22 (μ ± σ). For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant. The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30). These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity.

No MeSH data available.


Related in: MedlinePlus