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Characterization of mind wandering using fNIRS.

Durantin G, Dehais F, Delorme A - Front Syst Neurosci (2015)

Bottom Line: Functional near infrared spectroscopy is a non-invasive neuroimaging technique that has never been used so far to measure MW.We observed significant activations over the medial prefrontal cortex (mPFC) during MW, a brain region associated with the default mode network (DMN). fNIRS data were used to classify MW data above chance level.In line with previous brain-imaging studies, our results confirm the ability of fNIRS to detect Default Network activations in the context of MW.

View Article: PubMed Central - PubMed

Affiliation: Département Conception des Véhicules Aérospatiaux, Institut Supérieur de l'Aéronautique et de l'Espace Toulouse, France ; Centre de Recherche Cerveau et Cognition, Universite de Toulouse UPS, Toulouse, France ; CNRS, CerCo Toulouse, France.

ABSTRACT
Assessing whether someone is attending to a task has become important for educational and professional applications. Such attentional drifts are usually termed mind wandering (MW). The purpose of the current study is to test to what extent a recent neural imaging modality can be used to detect MW episodes. Functional near infrared spectroscopy is a non-invasive neuroimaging technique that has never been used so far to measure MW. We used the Sustained Attention to Response Task (SART) to assess when subjects attention leaves a primary task. Sixteen-channel fNIRS data were collected over frontal cortices. We observed significant activations over the medial prefrontal cortex (mPFC) during MW, a brain region associated with the default mode network (DMN). fNIRS data were used to classify MW data above chance level. In line with previous brain-imaging studies, our results confirm the ability of fNIRS to detect Default Network activations in the context of MW.

No MeSH data available.


Accuracy per subject obtained for classification of SART Error vs. SART No Error trials.
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Figure 6: Accuracy per subject obtained for classification of SART Error vs. SART No Error trials.

Mentions: We used data from only 11 subjects to classify SART Error and SART No Error trials, keeping only the subjects who made at least 10 errors, so we would have enough trials to train and test the classifier. Out of the 11 subjects, 7 of them had a classification accuracy superior to 60%. A Wilcoxon sign test showed that this result was unlikely to occur by chance (p < 0.016; degree of freedom of 10). Results are summarized in Table 1, and Figure 6 shows the individual accuracy results.


Characterization of mind wandering using fNIRS.

Durantin G, Dehais F, Delorme A - Front Syst Neurosci (2015)

Accuracy per subject obtained for classification of SART Error vs. SART No Error trials.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4374461&req=5

Figure 6: Accuracy per subject obtained for classification of SART Error vs. SART No Error trials.
Mentions: We used data from only 11 subjects to classify SART Error and SART No Error trials, keeping only the subjects who made at least 10 errors, so we would have enough trials to train and test the classifier. Out of the 11 subjects, 7 of them had a classification accuracy superior to 60%. A Wilcoxon sign test showed that this result was unlikely to occur by chance (p < 0.016; degree of freedom of 10). Results are summarized in Table 1, and Figure 6 shows the individual accuracy results.

Bottom Line: Functional near infrared spectroscopy is a non-invasive neuroimaging technique that has never been used so far to measure MW.We observed significant activations over the medial prefrontal cortex (mPFC) during MW, a brain region associated with the default mode network (DMN). fNIRS data were used to classify MW data above chance level.In line with previous brain-imaging studies, our results confirm the ability of fNIRS to detect Default Network activations in the context of MW.

View Article: PubMed Central - PubMed

Affiliation: Département Conception des Véhicules Aérospatiaux, Institut Supérieur de l'Aéronautique et de l'Espace Toulouse, France ; Centre de Recherche Cerveau et Cognition, Universite de Toulouse UPS, Toulouse, France ; CNRS, CerCo Toulouse, France.

ABSTRACT
Assessing whether someone is attending to a task has become important for educational and professional applications. Such attentional drifts are usually termed mind wandering (MW). The purpose of the current study is to test to what extent a recent neural imaging modality can be used to detect MW episodes. Functional near infrared spectroscopy is a non-invasive neuroimaging technique that has never been used so far to measure MW. We used the Sustained Attention to Response Task (SART) to assess when subjects attention leaves a primary task. Sixteen-channel fNIRS data were collected over frontal cortices. We observed significant activations over the medial prefrontal cortex (mPFC) during MW, a brain region associated with the default mode network (DMN). fNIRS data were used to classify MW data above chance level. In line with previous brain-imaging studies, our results confirm the ability of fNIRS to detect Default Network activations in the context of MW.

No MeSH data available.