pi3: Depth Electrodes or Digital Biomarkers? The future of mood monitoring

Stereoelectroencephalography (SEEG) vs. Mindstrong Health

Mood Monitoring via Invasive Brain Recordings or Smartphone Swipes

Which Would You Choose?

That's not really a fair question. The ultimate goal of invasive recordings is one of direct intervention, by delivering targeted brain stimulation as a treatment. But first you have to establish a firm relationship between neural activity and mood. Well, um, smartphone swipes (the way you interact with your phone) aim to establish a firm relationship between your “digital phenotype” and your mood. And then refer you to an app for a precision intervention. Or to your therapist / psychiatrist, who has to buy into use of the digital phenotyping software.

On the invasive side of the question, DARPA has invested heavily in deep brain stimulation (DBS) as a treatment for many disorders – Post-Traumatic Stress Disorder (PTSD), Major Depression, Borderline Personality Disorder, General Anxiety Disorder, Traumatic Brain Injury, Substance Abuse/Addiction, Fibromyalgia/Chronic Pain, and memory loss. None of the work has led to effective treatments (yet?), but the DARPA research model has established large centers of collaborating scientists who record from the brains of epilepsy patients. And a lot of very impressive papers have emerged – some promising, others not so much.

One recent study (Kirkby et al., 2018) used machine learning to discover brain networks that encode variations in self-reported mood. The metric was coherence between amygdala and hippocampal activity in the β-frequency (13-30 Hz). I can't do justice to their work in the context of this post, but I'll let the authors' graphical abstract speak for itself (and leave questions like, why did it only work in 13 out of 21 of your participants? for later).

Mindstrong

Then along comes a startup tech company called Mindstrong, whose Co-Founder and President is none other than Dr. Thomas Insel, former director of NIMH, and one of the chief architects¹ of the Research Domain Criteria (RDoC), “a research framework for new approaches to investigating mental disorders” that eschews the DSM-5 diagnostic bible. The Appendix chronicles the timeline of Dr. Insel's evolution from “mindless” RDoC champion to “brainless” wearables/smartphone tech proselytizer.²

From Wired:

. . .

At Mindstrong, one of the first tests of the [“digital phenotype”] concept will be a study of how 600 people use their mobile phones, attempting to correlate keyboard use patterns with outcomes like depression, psychosis, or mania. “The complication is developing the behavioral features that are actionable and informative,” Insel says. “Looking at speed, looking at latency or keystrokes, looking at error—all of those kinds of things could prove to be interesting.”

Curiously, in their list of digital biomarkers, they differentiate between executive function and cognitive control — although their definitions were overlapping (see my previous post, Is executive function different from cognitive control? The results of an informal poll).

Mindstrong tracks five digital biomarkers associated with brain health: Executive function, cognitive control, working memory, processing speed, and emotional valence. These biomarkers are generated from patterns in smartphone use such as swipes, taps, and other touchscreen activities, and are scientifically validated to provide measurements of cognition and mood.

Whither RDoC?

NIMH established a mandate requiring that all clinical trials should postulate a neural circuit “mechanism” that would be responsible for any efficacious response. Thus, clinical investigators were forced to make up simplistic biological explanations for their psychosocial interventions:

“I hypothesize that the circuit mechanism for my elaborate new psychotherapy protocol which eliminates fear memories (e.g., specific phobias, PTSD) is implemented by down-regulation of amygdala activity while participants view pictures of fearful faces using the Hariri task.”

[a fictitious example]

I'm including a substantial portion of the February 27, 2014 text here because it's important.

NIMH is making three important changes to how we will fund clinical trials.

First, future trials will follow an experimental medicine approach in which interventions serve not only as potential treatments, but as probes to generate information about the mechanisms underlying a disorder. Trial proposals will need to identify a target or mediator; a positive result will require not only that an intervention ameliorated a symptom, but that it had a demonstrable effect on a target, such as a neural pathway implicated in the disorder or a key cognitive operation. While experimental medicine has become an accepted approach for drug development, we believe it is equally important for the development of psychosocial treatments. It offers us a way to understand the mechanisms by which these treatments are leading to clinical change. Moreover, a subset of the funding announcements will support clinical trials that evaluate the effectiveness or increase the clinical impact of pharmacological, somatic, psychosocial, rehabilitative, and combination interventions.

OK, so the target could be a key cognitive operation. But let's say your intervention is a Housing First initiative in homeless individuals with severe mental illness and co-morbid substance abuse. Your manipulation is to compare quality of life outcomes for Housing First with Assertive Community Treatment vs. Congregate Housing with on-site supports vs. treatment as usual. What is the key cognitive operation here? Fortunately, this project was funded by the Canadian government and did not need to compete for NIMH funding.

I think my ultimate issue is one of fundamental fairness. Is it OK to skate away from the wreckage and profit by making millions of dollars? From Wired:

“I spent 13 years at NIMH really pushing on the neuroscience and genetics of mental disorders, and when I look back on that I realize that while I think I succeeded at getting lots of really cool papers published by cool scientists at fairly large costs—I think $20 billion—I don’t think we moved the needle in reducing suicide, reducing hospitalizations, improving recovery for the tens of millions of people who have mental illness,” Insel says. “I hold myself accountable for that.”

But how? You've admitted to spending $20 billion on cool projects and cool papers and cool scientists who do basic research. This has great value. But the big mistakes were an unrealistic promise of treatments and cures, and the charade of forcing scientists who study C. elegans to explain how they're going to cure psychiatric disorders.

Footnotes

¹ Dr. Bruce Cuthbert was especially instrumental, as well as a large panel of experts. But since this post is about digital biomarkers, the former director of NIMH is the focus of RDoC here.

² The Insel archives of the late Dr. Mickey Nardo in his prolific blog, 1boringoldman.com, are a must-read. I also wish the late Dr. Barney Carroll was still here to issue his trenchant remarks and trademark witticisms.

Reference

Kirkby LA, Luongo FJ, Lee MB, Nahum M, Van Vleet TM, Rao VR, Dawes HE, Chang EF, Sohal VS. (2018). An Amygdala-Hippocampus Subnetwork that Encodes Variation in Human Mood. Cell 175(6):1688-1700.e14.

Additional Reading - Digital Phenotyping

Jain SH, Powers BW, Hawkins JB, Brownstein JS. (2015). The digital phenotype. Nat Biotechnol. 33(5):462-3. [usage of the term here means data mining of content such as Twitter and Google searches, rather than physical interactions with a smartphone]

Insel TR. (2017). Digital Phenotyping: Technology for a New Science of Behavior. JAMA 318(13):1215-1216. [smartphone swipes, NOT content: “Who would have believed that patterns of typing and scrolling could reveal individual fingerprints of performance, capturing our neurocognitive function continuously in the real world?”]

Insel TR. (2017). Join the disruptors of health science. Nature 551(7678):23-26. [conversion to the SF Bay Area/Silicon Valley mindset]. Key quote:

“But what struck me most on moving from the Beltway to the Bay Area was that, unlike pharma and biotech, tech companies enter biomedical and health research with a pedigree of software research and development, and a confident, even cocky, spirit of disruption and innovation. They have grown by learning how to move quickly from concept to execution. Software development may generate a minimally viable product within weeks. That product can be refined through ‘dogfooding’ (testing it on a few hundred employees, families or friends) in a month, then released to thousands of users for rapid iterative improvement.”

[is ‘dogfooding’ a real term?? if that's how you're going to test technology designed to help people with severe mental illnesses — without the input of the consumers themselves — YOU WILL BE DOOMED TO FAILURE.]

Philip P, De-Sevin E, Micoulaud-Franchi JA. (2018). Technology as a Tool for Mental Disorders. JAMA 319(5):504.

Insel TR. (2018). Technology as a Tool for Mental Disorders-Reply. JAMA 319(5):504.

Insel TR. (2018). Digital phenotyping: a global tool for psychiatry. World Psychiatry 17(3):276-277.

Appendix - a selective history of RDoC publications