• Dijk, D.-J. & Archer, S. N. Light, Sleep, and Circadian Rhythms: Together Again. PLOS Biol. 7, e1000145 (2009).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wager-Smith, K. & Kay, S. A. Circadian rhythm genetics: from flies to mice to humans. Nat. Genet. 26, 23–27 (2000).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Mistlberger, R. E. & Skene, D. J. Social influences on mammalian circadian rhythms: animal and human studies. Biol. Rev. 79, 533–556 (2004).

    Article 
    PubMed 

    Google Scholar
     

  • Schmidt, C., Collette, F., Cajochen, C. & Peigneux, P. A time to think: Circadian rhythms in human cognition. Cogn. Neuropsychol. 24, 755–789 (2007).

    Article 
    PubMed 

    Google Scholar
     

  • Casiraghi, L. et al. Moonstruck sleep: Synchronization of human sleep with the moon cycle under field conditions. Sci. Adv. 7, eabe0465 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cordi, M. et al. Lunar cycle effects on sleep and the file drawer problem. Curr. Biol. 24, R549–R550 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Cajochen, C. et al. Evidence that the Lunar Cycle Influences Human Sleep. Curr. Biol. 23, 1485–1488 (2013).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • James, A. The validity of ‘;biorhythmic’ theory questioned. Br. J. Psychol. 75, 197–200 (1984).

    Article 
    PubMed 

    Google Scholar
     

  • Persinger, M. A., Cooke, W. J. & Janes, J. T. No Evidence for Relationship between Biorhythms and Industrial Accidents. Percept. Mot. Skills 46, 423–426 (1978).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Peveto, N. The Relationship of Biorhythms to Academic Performance in Reading. LSU Hist. Diss. Theses (1980) https://doi.org/10.31390/gradschool_disstheses.3577.

  • Owen, C., Tarantello, C., Jones, M. & Tennant, C. Lunar Cycles and Violent Behaviour. Aust. N. Z. J. Psychiatry 32, 496–499 (1998).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Laverty, W. H. & Kelly, I. W. Cyclical Calendar and Lunar Patterns in Automobile Property Accidents and Injury Accidents. Percept. Mot. Skills 86, 299–302 (1998).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Ichino, A. & Moretti, E. Biological Gender Differences, Absenteeism, and the Earnings Gap. Am. Econ. J. Appl. Econ. 1, 183–218 (2009).

    Article 

    Google Scholar
     

  • Shansky, R. M. Are hormones a “female problem” for animal research? Science 364, 825–826 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Pletzer, B., Harris, T.-A., Scheuringer, A. & Hidalgo-Lopez, E. The cycling brain: menstrual cycle related fluctuations in hippocampal and fronto-striatal activation and connectivity during cognitive tasks. Neuropsychopharmacology 44, 1867–1875 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Clare, A. W. Invited review hormones, behaviour and the menstrual cycle. J. Psychosom. Res. 29, 225–233 (1985).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Baud, M. O. et al. Multi-day rhythms modulate seizure risk in epilepsy. Nat. Commun. 9, 88 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Karoly, P. J. et al. Cycles in epilepsy. Nat. Rev. Neurol. 1–18 (2021) https://doi.org/10.1038/s41582-021-00464-1.

  • Leguia, M. G. et al. Seizure Cycles in Focal Epilepsy. JAMA Neurol. 78, 454–463 (2021).

    Article 
    PubMed 

    Google Scholar
     

  • Wehr, T. A. Bipolar mood cycles and lunar tidal cycles. Mol. Psychiatry 23, 923–931 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Huber, R. & Ghosh, A. Large cognitive fluctuations surrounding sleep in daily living. iScience 24, 102159 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Golder, S. A. & Macy, M. W. Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures. Science 333, 1878–1881 (2011).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Leise, T. L. Wavelet analysis of circadian and ultradian behavioral rhythms. J. Circadian Rhythms 11, 5 (2013).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cazelles, B., Cazelles, K. & Chavez, M. Wavelet analysis in ecology and epidemiology: impact of statistical tests. J. R. Soc. Interface 11, 20130585 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wehr, T. A. & Helfrich-Förster, C. Longitudinal observations call into question the scientific consensus that humans are unaffected by lunar cycles. BioEssays 43, 2100054 (2021).

    Article 

    Google Scholar
     

  • Bennett, C. C., Ross, M. K., Baek, E., Kim, D. & Leow, A. D. Smartphone accelerometer data as a proxy for clinical data in modeling of bipolar disorder symptom trajectory. Npj Digit. Med. 5, 1–10 (2022).

    Article 

    Google Scholar
     

  • Alfalahi, H. et al. Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: a systematic review and meta-analysis. Sci. Rep. 12, 7690 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ceolini, E. et al. A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease. iScience 25, 104792 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Duckrow, R. B., Ceolini, E., Zaveri, H. P., Brooks, C. & Ghosh, A. Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy. iScience 24, 102538 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Westbrook, A. et al. Striatal dopamine synthesis capacity reflects smartphone social activity. iScience 24, 102497 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vazquez, A. Impact of memory on human dynamics. Phys. Stat. Mech. Its Appl. 373, 747–752 (2007).

    Article 

    Google Scholar
     

  • Barabási, A.-L. The origin of bursts and heavy tails in human dynamics. Nature 435, 207–211 (2005).

    Article 
    PubMed 

    Google Scholar
     

  • Oliveira, J. G. & Barabási, A.-L. Darwin and Einstein correspondence patterns. Nature 437, 1251–1251 (2005).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Malmgren, R. D., Stouffer, D. B., Motter, A. E. & Amaral, L. A. N. A Poissonian explanation for heavy tails in e-mail communication. Proc. Natl Acad. Sci. 105, 18153–18158 (2008).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pfister, J.-P. & Ghosh, A. Generalized priority-based model for smartphone screen touches. Phys. Rev. E 102, 012307 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Brennan, M., Palaniswami, M. & Kamen, P. Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability? IEEE Trans. Biomed. Eng. 48, 1342–1347 (2001).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Rodieck, R. W., Kiang, N. Y.-S. & Gerstein, G. L. Some Quantitative Methods for the Study of Spontaneous Activity of Single Neurons. Biophys. J. 2, 351–368 (1962).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ceolini, E., Kock, R., Band, G. P. H., Stoet, G. & Ghosh, A. Temporal clusters of age-related behavioral alterations captured in smartphone touchscreen interactions. iScience 25, 104791 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pernet, C. R., Chauveau, N., Gaspar, C. & Rousselet, G. A. LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data. Comput. Intell. Neurosci. https://www.hindawi.com/journals/cin/2011/831409/ (2011) https://doi.org/10.1155/2011/831409.

  • Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).

    Article 
    PubMed 

    Google Scholar
     

  • Eagle, N. & Pentland, A. S. Eigenbehaviors: identifying structure in routine. Behav. Ecol. Sociobiol. 63, 1057–1066 (2009).

    Article 

    Google Scholar
     

  • Lee, D. D. & Seung, H. S. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Brunet, J.-P., Tamayo, P., Golub, T. R. & Mesirov, J. P. Metagenes and molecular pattern discovery using matrix factorization. Proc. Natl Acad. Sci. 101, 4164–4169 (2004).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Karoly, P. J. et al. Epileptic Seizure Cycles: Six Common Clinical Misconceptions. Front. Neurol. 12, 720328 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Karoly, P. J. et al. Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study. eBioMedicine 72, 103619 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bachleitner, W., Kempinger, L., Wülbeck, C., Rieger, D. & Helfrich-Förster, C. Moonlight shifts the endogenous clock of Drosophila melanogaster. Proc. Natl Acad. Sci. 104, 3538–3543 (2007).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bernard, C. Circadian/multidien Molecular Oscillations and Rhythmicity of Epilepsy (MORE). Epilepsia 62, S49–S68 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Novák, B. & Tyson, J. J. Design principles of biochemical oscillators. Nat. Rev. Mol. Cell Biol. 9, 981–991 (2008).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lugo, C. A. & McKane, A. J. Quasicycles in a spatial predator-prey model. Phys. Rev. E 78, 051911 (2008).

    Article 

    Google Scholar
     

  • Nisbet, R. M. & Gurney, W. S. C. A simple mechanism for population cycles. Nature 263, 319–320 (1976).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Esmaeili, S., Hastings, A., Abbott, K. C., Machta, J. & Nareddy, V. R. Noise-induced versus intrinsic oscillation in ecological systems. Ecol. Lett. 25, 814–827 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Reinberg, A. E., Dejardin, L., Smolensky, M. H. & Touitou, Y. Seven-day human biological rhythms: An expedition in search of their origin, synchronization, functional advantage, adaptive value and clinical relevance. Chronobiol. Int. 34, 162–191 (2017).

    Article 
    PubMed 

    Google Scholar
     

  • Zwan, M. D. et al. Dutch Brain Research Registry for study participant recruitment: Design and first results. Alzheimers Dement. Transl. Res. Clin. Interv. 7, e12132 (2021).


    Google Scholar
     

  • Borger, J. N., Huber, R. & Ghosh, A. Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions. Npj Digit. Med. 2, 1–8 (2019).

    Article 

    Google Scholar
     

  • Balerna, M. & Ghosh, A. The details of past actions on a smartphone touchscreen are reflected by intrinsic sensorimotor dynamics. Npj Digit. Med. 1, 4 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wu, S. et al. Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks. Proc. Natl Acad. Sci. 113, 4290–4295 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rouyer, T., Fromentin, J.-M., Stenseth, N. C. & Cazelles, B. Analysing multiple time series and extending significance testing in wavelet analysis. Mar. Ecol. Prog. Ser. 359, 11–23 (2008).

    Article 

    Google Scholar
     

  • link

    By admin

    Leave a Reply

    Your email address will not be published. Required fields are marked *