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Review
. 2018 Dec;43(13):2499-2503.
doi: 10.1038/s41386-018-0172-z. Epub 2018 Aug 2.

Digital devices and continuous telemetry: opportunities for aligning psychiatry and neuroscience

Justin T Baker  1 , Laura T Germine  1 , Kerry J Ressler  1 , Scott L Rauch  1 , William A Carlezon Jr  2
Affiliations
Review

Digital devices and continuous telemetry: opportunities for aligning psychiatry and neuroscience

Justin T Baker et al. Neuropsychopharmacology. 2018 Dec.
No abstract available

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Conflict of interest statement

JTB serves as a consultant for Pear Therapeutics and Niraxx Therapeutics, LTG serves as a consultant for 23andme, and KJR is on the Scientific Advisory Board for Resilience Therapeutics and serves as a consultant for Biogen. The other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Citations for the terms “digital technology” and “psychiatry” over the past five years show similar trends as the terms “fMRI” and “psychiatry” in 1999, expressed as number per 1000 Medline citations
Fig. 2
Fig. 2
Revisiting the Mental Status Exam (MSE) in an era of digital phenotyping. Traditional psychiatry may undergo a radical transformation of the most fundamental means of assessment, as digital tools pave the way for more efficient, naturalistic capture of an individual’s mental status through continuous analysis of device-based interactions. Figure created by S. Rauch, L. Germine & N. Mirin, and presented at the Technology in Psychiatry Summit, Boston MA, USA, 06 Nov 2017; https://www.youtube.com/watch?v=gFwN08HzRwMt=42s
Fig. 3
Fig. 3
Use of continuous data to predict behavior. In the example depicted, with behavior B serving as the reference (“Seed”) Event, machine learning algorithms may be able to identify antecedents (i.e., Event A, which could be a behavior, an EEG signature, a temperature fluctuation, etc) that would have been predictive of Event B, and future behaviors (i.e., Event C) that are predictable on the basis of Event B (or the combination of Events A and B). Maximizing the timeframe between events within which predictions are reliable is critical and could be life-saving in neuropsychiatric conditions such as suicide or substance abuse
Fig. 4
Fig. 4
Digital MSE for rodents, using end points that are objective, continuous, and translational. Research in laboratory animals is increasingly employing temporally dense behavioral recordings alongside neural data in ways that could translate to the human MSE. Sleep, diurnal and circadian rhythms, locomotor activity, and vocalizations can routinely be studied as a function of targeted interventions to expose new relationships among genes, circuits, systems, and complex behavior. Vocalizations courtesy of Galen Missig; VV: vehicle control; PL: perinatal immune-activated
See this image and copyright information in PMC

References

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