| Autor: |
Wamsley EJ; Furman University, Greenville, SC., Summer T; Furman University, Greenville, SC. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of cognitive neuroscience [J Cogn Neurosci] 2020 Sep; Vol. 32 (9), pp. 1714-1734. Date of Electronic Publication: 2020 Jun 12. |
| DOI: |
10.1162/jocn_a_01587 |
| Abstrakt: |
Moments of inattention to our surroundings may be essential to optimal cognitive functioning. Here, we investigated the hypothesis that humans spontaneously switch between two opposing attentional states during wakefulness-one in which we attend to the external environment (an "online" state) and one in which we disengage from the sensory environment to focus our attention internally (an "offline" state). We created a data-driven model of this proposed alternation between "online" and "offline" attentional states in humans, on a seconds-level timescale. Participants ( n = 34) completed a sustained attention to response task while undergoing simultaneous high-density EEG and pupillometry recording and intermittently reporting on their subjective experience. "Online" and "offline" attentional states were initially defined using a cluster analysis applied to multimodal measures of (1) EEG spectral power, (2) pupil diameter, (3) RT, and (4) self-reported subjective experience. We then developed a classifier that labeled trials as belonging to the online or offline cluster with >95% accuracy, without requiring subjective experience data. This allowed us to classify all 5-sec trials in this manner, despite the fact that subjective experience was probed on only a small minority of trials. We report evidence of statistically discriminable "online" and "offline" states matching the hypothesized characteristics. Furthermore, the offline state strongly predicted memory retention for one of two verbal learning tasks encoded immediately prior. Together, these observations suggest that seconds-timescale alternation between online and offline states is a fundamental feature of wakefulness and that this may serve a memory processing function. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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