Abstract
By comparison to the functional metrics available in other medical disciplines, conventional measures of neuropsychiatric and neurodegenerative disorders have several limitations. They are obtrusive, requiring a subject to break from their normal routine. They are episodic and provide sparse snapshots of a patient only at the time of the assessment. They require subjects to perform a task outside of the context of everyday behavior. And lastly, they are poorly scalable, taxing limited resources. We present validation studies that demonstrate the clinical efficacy of a new approach in reproducing gold-standard neuropsychological measures. We discuss the neuroscience constructs and mathematical underpinnings of cognition and mood measurement from human-computer interaction data. We conclude with a discussion on four areas that we predict will be impacted by these new clinical measurements: (i) understanding of the interdependency between cognition and mood; (ii) nosology of psychiatric illnesses; (iii) drug discovery; and (iv) delivery of healthcare services.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Andone I, Błaszkiewicz K, Eibes M et al (2016) How age and gender affect smartphone usage. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing adjunct—UbiComp ’16. Heidelberg, Germany, 12–16 September 2016
Barshan E, Ghodsi A, Azimifar Z, Zolghadri Jahromi M (2011) Supervised principal component analysis: visualization, classification and regression on subspaces and submanifolds. Pattern Recognit 44(7):1357–1371. https://doi.org/10.1016/j.patcog.2010.12.015
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol 57(1):289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Bergmeir C, Hyndman RJ, Koo B (2018) A note on the validity of cross-validation for evaluating autoregressive time series prediction. Comput Stat Data Anal 120:70–83. https://doi.org/10.1016/j.csda.2017.11.003
Botwinick J, Thompson LW (1966) Premotor and motor components of reaction time. J Exp Psychol 71(1):9–15. https://doi.org/10.1037/h0022634
Business Wire (2017) BlackThorn Therapeutics announces innovative clinical collaboration agreement with Mindstrong Health. https://www.businesswire.com/news/home/20170607005392/en/BlackThorn-Therapeutics-Announces-Innovative-Clinical-Collaboration-Agreement
ClinicalTrials.gov (2017) Testing the value of smartphone assessments of people with mood disorders. A pilot, exploratory, longitudinal study (Identifier No. NCT03429361). https://clinicaltrials.gov/ct2
Dagum P (2018a) The long journey to digital brain biomarkers. npj Digital Medicine. https://npjdigitalmedcommunity.nature.com/users/89405-paul-dagum/posts/31757-the-long-journey-to-digital-brain-health
Dagum P (2018b) Digital biomarkers of cognitive function. NPJ Digit Med 1(1):10. https://doi.org/10.1038/s41746-018-0018-4
Insel TR (2017) Digital phenotyping: technology for a new science of behavior. JAMA Netw 318(13):1215–1216. https://doi.org/10.1001/jama.2017.11295
Keedwell PA, Andrew C, Williams SCR et al (2005) The neural correlates of anhedonia in major depressive disorder. Biol Psychiatry 58(11):843–853. https://doi.org/10.1016/j.biopsych.2005.05.019
Kerchner GA, Dougherty RF, Dagum P (2015) Unobtrusive neuropsychological monitoring from smart phone use behavior. Alzheimers Dement 11(7):272–273. https://doi.org/10.1016/j.jalz.2015.07.358
Kubiak T, Smyth JM (2019) Connecting domains—ecological momentary assessment in a mobile sensing framework. Mobile sensing and psychoinformatics. Springer, Berlin, pp x–x
Madrid A, Smith D, Alvarez-Horine S et al (2017) Assessing anhedonia with quantitative tasks and digital and patient reported measures in a multi-center double-blind trial with BTRX-246040 for the treatment of major depressive disorder. Neuropsychopharmacology 43:372–372
Markowetz A, Błaszkiewicz K, Montag C et al (2014) Psycho-informatics: big data shaping modern psychometrics. Med Hypotheses 82(4):405–411. https://doi.org/10.1016/j.mehy.2013.11.030
Montag C, Elhai JD, Dagum P (2021) On blurry boundaries when defining digital biomarkers: how much biology needs to be in a digital biomarker? Front Psych 12:1690. https://doi.org/10.3389/112fpsyt.2021.740292
Montag C, Elhai JD, Dagum P (2023) Defining Digital Biomarkers. In: Baumeister H, Montag C (eds) Digital phenotyping and mobile sensing: new developments in psychoinformatics. Springer International Publishing
PR Newswire (2018) Mindstrong Health and Takeda partner to explore development of digital biomarkers for mental health conditions. https://www.prnewswire.com/news-releases/mindstrong-health-and-takeda-partner-to-explore-development-of-digital-biomarkers-for-mental-health-conditions-300604553.html
Smith DG, Saljooqi K, Alvarez-Horine S et al (2018) Exploring novel behavioral tasks and digital phenotyping technologies as adjuncts to a clinical trial of BTRX-246040. International Society of CNS Clinical Trials and Methodology
Staples P, Ouyang M, Dougherty RF et al (2018) Supervised kernel PCA for longitudinal data. arXiv preprint arXiv:180806638
Statistica (2019) StatSoft EUROPE. www.statistica.com
Strauss E, Sherman E, Spreen O (2006) A compendium of neuropsychological tests. Administration, norms, and commentary, 3rd edn. Oxford University Press, New York
Winkler AM, Ridgway GR, Webster MA et al (2014) Permutation inference for the general linear model. Neuroimage 92:381–397. https://doi.org/10.1016/j.neuroimage.2014.01.060
Conflict of Interest
Paul Dagum is the founder of Mindstrong Health, a company developing digital phenotyping products for mental healthcare delivery. He served as its Chief Executive Officer from its founding in 2013 through October 2019 and was granted five U.S. patents on digital phenotyping and digital biomarkers. Dagum is currently co-founder and CEO of Applied Cognition developing diagnostic and therapeutic solutions for Alzheimer’s disease. Dagum owns stock in Mindstrong Health and in Applied Cognition.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Dagum, P. (2023). Digital Brain Biomarkers of Human Cognition and Mood. In: Montag, C., Baumeister, H. (eds) Digital Phenotyping and Mobile Sensing. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-98546-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-98546-2_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-98545-5
Online ISBN: 978-3-030-98546-2
eBook Packages: EngineeringEngineering (R0)