Literature DB >> 33681725

Large cognitive fluctuations surrounding sleep in daily living.

Reto Huber1, Arko Ghosh2.   

Abstract

Cognitive output and physical activity levels fluctuate surrounding sleep. The ubiquitous digitization of behavior via smartphones is a promising avenue for addressing how these fluctuations occur in daily living. Here, we logged smartphone touchscreen interactions to proxy cognitive fluctuations and contrasted these to physical activity patterns logged on wrist-worn actigraphy. We found that both cognitive and physical activities were dominated by diurnal (∼24 h) and infra-radian (∼7 days) rhythms. The proxy measures of cognitive performance-tapping speed, unlocking speed, and app locating speed-contained lower-powered diurnal rhythm than physical activity. The difference between cognitive and physical activity was vivid during bedtime as people continued to interact with their smartphones at physical rest. The cognitive performance measures in this period were worse than those in the hour before or after bedtime. We suggest that the rhythms underlying cognitive activity in the real world are distinct from those underlying physical activity, and this discord may be a hallmark of modern human behavior.
© 2021 The Authors.

Entities:  

Keywords:  Behavioral Neuroscience; Biological Sciences; Cognitive Neuroscience; Neuroscience

Year:  2021        PMID: 33681725      PMCID: PMC7918275          DOI: 10.1016/j.isci.2021.102159

Source DB:  PubMed          Journal:  iScience        ISSN: 2589-0042


  6 in total

1.  Spontaneous motor tempo over the course of a week: the role of the time of the day, chronotype, and arousal.

Authors:  David Hammerschmidt; Clemens Wöllner
Journal:  Psychol Res       Date:  2022-02-06

2.  A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease.

Authors:  Enea Ceolini; Iris Brunner; Johanna Bunschoten; Marian H J M Majoie; Roland D Thijs; Arko Ghosh
Journal:  iScience       Date:  2022-08-05

3.  Temporal clusters of age-related behavioral alterations captured in smartphone touchscreen interactions.

Authors:  Enea Ceolini; Ruchella Kock; Guido P H Band; Gijsbert Stoet; Arko Ghosh
Journal:  iScience       Date:  2022-08-05

4.  Disentangling personalized treatment effects from "time-of-the-day" confounding in mobile health studies.

Authors:  Elias Chaibub Neto; Thanneer M Perumal; Abhishek Pratap; Aryton Tediarjo; Brian M Bot; Lara Mangravite; Larsson Omberg
Journal:  PLoS One       Date:  2022-08-04       Impact factor: 3.752

5.  Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy.

Authors:  Robert B Duckrow; Enea Ceolini; Hitten P Zaveri; Cornell Brooks; Arko Ghosh
Journal:  iScience       Date:  2021-05-13

6.  Spontaneous Motor Tempo: Investigating Psychological, Chronobiological, and Demographic Factors in a Large-Scale Online Tapping Experiment.

Authors:  David Hammerschmidt; Klaus Frieler; Clemens Wöllner
Journal:  Front Psychol       Date:  2021-06-22
  6 in total

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