ArticlePDF Available

Naturalizing psychopathology—towards a quantitative real-world psychiatry

Authors:
Juha M Lahnakoski at Forschungszentrum Jülich
Juha M Lahnakoski
Simon B Eickhoff at Forschungszentrum Jülich
Simon B Eickhoff
Juergen Dukart at Forschungszentrum Jülich
Juergen Dukart
Leonhard Schilbach at Ludwig-Maximilians-Universität in Munich
Leonhard Schilbach
Download full-text PDF
Read full-text
Download citation
Available via license: CC BY 4.0
Content may be subject to copyright.
COMMENT OPEN
Naturalizing psychopathology—towards a quantitative real-
world psychiatry
Juha M. Lahnakoski
1,2
✉, Simon B. Eickhoff
1,2
, Juergen Dukart
1,2,5
and Leonhard Schilbach
3,4,5
© The Author(s) 2021
Molecular Psychiatry; https://doi.org/10.1038/s41380-021-01322-8
Psychiatric disorders continue to be on the rise around the globe.
Meanwhile, efforts and investments directed to early diagnosis
and appropriate interventions for mental health problems are
lagging resulting in ‘substantial loss of human capabilities and
avoidable suffering’[1]. A major component of our inability to
address mental health problems resides in the persistent lack of
objective measures for evaluating such difficulties in the daily life
of individuals, complicating the detection of clinically relevant
changes in the patients’well-being [2]. Similarly, most studies into
the neurobiology of psychiatric disorders lack a detailed descrip-
tion of individual functioning despite influential calls for
quantitative approaches to psychopathology.
Psychiatric conditions are often particularly reflected through,
and exacerbated by, difficulties in social functioning in everyday
life [3]. Yet, current diagnostic evaluations primarily take the form
of limited interactions in artificial clinical settings. While these
types of diagnostic procedures have clear clinical value, they are
often subjective and qualitative in nature. Reports provided by the
patient may suffer from memory biases and can also depend on
the rapport and trust between the patient and the clinician.
Concurrently, standardized questionnaires probe a limited set of
functional impairments and are administered only infrequently
during clinical consultations. With the slow onset and the non-
specific and transient nature of functional impairments in
psychiatric conditions, these limitations may prevent a more
comprehensive description and early detection of psychopathol-
ogy [1].
We argue that a thorough understanding of the real-world
manifestations and implicationsofpsychiatricdisordersisthe
key for the field to move towards the development of more
effective personalized assessments and interventions. To
address this, we outline a general multilevel framework for
deep behavioural phenotyping to guide the scientificinquiry
into the behavioural and neural mechanisms of psychopathol-
ogy and to delineate specific therapeutic interventions (Fig. 1).
This approach emphasises an objective and continuous evalua-
tion of psychopathology in everyday life and naturalistic social
interactions (green box, top left) to guide clinical practice and
scientific research.
The most debilitating symptoms of psychiatric disorders may
only manifest in everyday life, where patients must cope with
multiple aspects of life simultaneously (illustrated by the red scale
at the bottom of Fig. 1). Current technologies can enable detailed
and objective monitoring of the impact of mental health problems
on everyday life of the patient based on their natural behavioural
patterns. One way to achieve this is by measuring daily behaviour
using personal smart devices, often referred to as “digital
phenotyping”[4]. Using these devices, everyday life behaviour
can be assessed passively, for example by objectively measuring
the amount of physical activity or phone-based social interaction.
Moreover, temporal patterns of user interface inputs may provide
valuable insights into psychomotor symptoms such as agitation or
retardation.
Importantly, these passive measures of daily behaviour can be
complemented by subjective ecological momentary assess-
ments providing real-time self-reported measures of patients’
well-being. Such subjective momentary evaluations may prove
crucial to understanding changes in passively monitored
behavioural patterns. For example, while single passive mea-
sures may not be sufficiently discriminative, negative mood
evaluations in combination with reductions in locomotive
activity, social application usage and speed of typing may
represent early signs of a depressive episode. Detecting such
patterns offers a chance for early intervention to avoid
hospitalization (arrow 1. In Fig. 1).
While such digital phenotyping can address macroscopic
aspects of social and motor functioning, it lacks specificity for
assessing how these problems relate to difficulties the patients
face during real-life social interactions. To address this, recent
studies have started to objectively measure behaviour during
social interactions using motion tracking techniques to detect e.g.
individual differences related to interaction success [5] and
behavioural predictors for psychiatric disorders and therapeutic
outcomes [6]. Such tracking techniques can be used to evaluate
psychomotor symptoms in more detail based on face and whole-
body movements. Moreover, some of the symptoms or beha-
vioural tendencies of a person may manifest more strongly during
a dyadic real-time interaction rather than during interaction with a
digital user interface. In a clinical setting, such fine-grained
characterization of behaviour during dyadic interactions may
assist a clinician to reveal subtle early signs for interpersonal
difficulties before symptoms develop into a fully-fledged psychia-
tric disorder. Such behavioural measures can also be extremely
beneficial for elucidating the neurobiological underpinnings of
psychiatric disorders and the behavioural and neural mechanisms
of psychotherapeutic interventions (arrow 2. In Fig. 1). Moreover,
Received: 28 May 2021 Revised: 8 September 2021 Accepted: 24 September 2021
1
Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
2
Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine
University Düsseldorf, Düsseldorf, Germany.
3
LVR-Klinikum Düsseldorf, Düsseldorf, Germany.
4
Medical Faculty, Ludwig-Maximilians-Universität, München, Germany.
5
These
authors contributed equally: Juergen Dukart, Leonhard Schilbach. ✉email: j.lahnakoski@fz-juelich.de
www.nature.com/mp
Molecular Psychiatry
combining behavioural and physiological measurements during
immersive virtual reality may expand the behaviours that can be
evaluated, and have shown promise as generalizable predictors of
individual susceptibility to stress, which is an important contribut-
ing factor to psychiatric disorders [7].
To date, most studies focusing on the neural bases of
psychiatric disorders performed categorical comparisons of
psychiatric disorders while overlooking the extensive variability
in how the disorders manifest in individual patients. Whilst
replicable brain-based group differences appear to exist [8],
group-level effect sizes are often small and the measures may be
more indicative of the general level of psychopathology across
multiple disorders [9]. Progress in machine learning techniques
may improve the specificity of imaging-based biomarkers in the
future. However, it is also increasingly recognized that neurobio-
logical changes might be more strongly associated with
combinations of dimensions of psychopathology than general
clinical labels. Comprehensive behavioural phenotyping may help
uncover clinically relevant behavioural patterns and provide a
window into individual, rather than group-based, neurobiological
underpinnings of psychiatric disorders.
Several approaches could be used to measure the neurobiolo-
gical and physiological correlates of psychiatric disorders from
stable anatomical properties to short-term functional changes
during naturalistic experimental conditions (we illustrate some
options in Fig. 1). Behavioural symptoms are likely not equally
reflected at all levels of this continuum. For example, transient and
context-specific difficulties in social life may not be reflected as
anatomical differences at scales visible in standard anatomical MRI
images. By contrast, exposure to disorder-relevant stimuli may
elicit readily detectable activity differences. Conversely, these
differences may reflect the effect of the conditions while the
causes may lie in pathophysiological alterations at a different
scale. Thus, it is important to critically evaluate which measures
are most reflective of, and contributing to, psychopathology.
Such insights from combining behavioural and neuroimaging
markers of psychopathology may be key for detecting clinically
applicable biomarkers for psychiatric disorders that can feed back
into clinical practice (grey arrow in Fig. 1) and enable novel
insights into the brain mechanisms underlying individual psycho-
pathology [10].
REFERENCES
1. Patel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, et al. The Lancet
Commission on global mental health and sustainable development. Lancet.
2018;392:1553–98.
2. Insel TR. Digital phenotyping: technology for a new science of behavior. JAMA.
2017;318:1215–6.
3. Schilbach L. Towards a second-person neuropsychiatry. Philos Trans R Soc Lond B
Biol Sci. 2016;371:20150081.
4. Torous J, Kiang MV, Lorme J, Onnela J-P. New tools for new research in psychiatry:
a scalable and customizable platform to empower data driven smartphone
research. JMIR Ment Heal. 2016;3:e16.
5. Lahnakoski JM, Forbes PAG, McCall C, Schilbach L. Unobtrusive tracking of
interpersonal orienting and distance predicts the subjective quality of social
interactions. R Soc Open Sci. 2020;7:191815.
6. Ramseyer F, Tschacher W. Nonverbal synchrony of head- and body-movement in
psychotherapy: different signals have different associations with outcome. Front
Psychol. 2014;5.979.
7. Rodrigues J, Studer E, Streuber S, Meyer N, Sandi C. Locomotion in virtual
environments predicts cardiovascular responsiveness to subsequent stressful
challenges. Nat Commun. 2020;11:5904.
8. Holiga Š, Hipp JF, Chatham CH, Garces P, Spooren W, D’Ardhuy XL, et al. Patients
with autism spectrum disorders display reproducible functional connectivity
alterations. Sci Transl Med. 2019;11:eaat9223.
9. Elliott ML, Romer A, Knodt AR, Hariri AR. A Connectome-wide functional signature
of transdiagnostic risk for mental illness. Biol Psychiatry. 2018;84:452–9.
Fig. 1 Graphical summary of a framework for multiscale assessment of psychopathology. Our framework emphasizes deep behavioural
phenotyping in natural conditions of everyday life and minimally constrained interactions (green box, top left). These approaches can (1)
provide objective measures of daily functioning that can directly guide early detection and individual intervention strategies in the clinic, thus
helping with the limitations of in-clinic evaluations. Additionally, (2), the individual measures of daily functioning may help to uncover
neurobiological markers of the symptom dimensions without relying on heterogeneous disease labels. These findings may then feed back to
clinical practice.
J.M. Lahnakoski et al.
2
Molecular Psychiatry
1234567890();,:
10. Umbricht D, Abt M, Tamburri P, Chatham C, Holiga Š, Frank MJ, et al. Proof-of-
mechanism study of the PDE10 inhibitor RG7203 in patients with schizophrenia
and negative symptoms. Biol Psychiatry Glob Open Sci. 2021. https://doi.org/
10.1016/j.bpsgos.2021.03.001.
AUTHOR CONTRIBUTIONS
JML: Conceptualization, writing—original draft preparation, visualization. SBE:
Conceptualization, writing—review & editing. JD and LS: Contributed equally,
conceptualization, writing—review & editing, supervision.
FINANCIAL DISCLOSURES
Work was supported by a grant from the Max Planck Society for an Independent Max
Planck Research Group awarded to LS. SBE acknowledges support by the Helmholtz
Portfolio Theme “Supercomputing and Modeling for the Human Brain,”and the
European Union’s Horizon 2020 Research and Innovation Programme (Grant Nos.
785907 [HBP SGA2] and 945539 [HBP SGA3]). Open Access funding enabled and
organized by Projekt DEAL.
COMPETING INTERESTS
The authors declare no competing interests.
ADDITIONAL INFORMATION
Correspondence and requests for materials should be addressed to Juha M.
Lahnakoski.
Reprints and permission information is available at http://www.nature.com/
reprints
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims
in published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article’s Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly
from the copyright holder. To view a copy of this license, visit http://creativecommons.
org/licenses/by/4.0/.
© The Author(s) 2021
J.M. Lahnakoski et al.
3
Molecular Psychiatry
... 5 To date, most studies focusing on the neural bases of psychiatric disorders use categorical diagnostic systems, but neurobiological changes are now increasingly recognized as being more strongly related to combinations of different dimensions of psychopathology, than to general clinical labels. 6 The sluggish pace of discovery in psychiatry has been, in part, attributed, to the limited validity and certain arbitrariness of traditional diagnoses. A solution to the shortcomings of traditional taxonomies is emerging as a quantitative nosology -an empirically based organization of psychopathology. ...
... 8 Measuring daily behavior using personal smart devices, often referred to as "digital phenotyping" could also be a way of recognizing natural behavioral patterns, which could potentially assist clinicians in revealing subtle early signs for interpersonal difficulties, before symptoms develop into a fully-fledged psychiatric disorder. 6 Insights combining behavioral and neuroimaging markers of psychopathology may be key for detecting clinically applicable biomarkers for psychiatric disorders that can feedback into clinical practice and enable novel insights into the brain mechanisms underlying individual psychopathology. 6 CURRENT TREATMENT IS NOT ENOUGH Current treatments, which consist mostly of psychopharmacology and psychotherapy, still offer suboptimal responses. ...
... 6 Insights combining behavioral and neuroimaging markers of psychopathology may be key for detecting clinically applicable biomarkers for psychiatric disorders that can feedback into clinical practice and enable novel insights into the brain mechanisms underlying individual psychopathology. 6 CURRENT TREATMENT IS NOT ENOUGH Current treatments, which consist mostly of psychopharmacology and psychotherapy, still offer suboptimal responses. 10 Studies show that people suffering from severe mental health conditions die 10 to 20 years earlier than the general population, with globally mental disorders account for 1 to 6 years lived with disability. ...
View
... 15 It remains unknown whether our understanding from laboratory findings could be generalised to the real-world manifestations of schizophrenia, which is key to developing effective personalised assessments and interventions. 71 Therefore, interpersonal computational psychiatry also calls for more ecologically valid research (eg, ecological momentary assessment of rich phenotypes with portable devices). 71 In this regard, the technology of virtual reality holds a high potential to facilitate research, as used in intervention work. ...
... 71 Therefore, interpersonal computational psychiatry also calls for more ecologically valid research (eg, ecological momentary assessment of rich phenotypes with portable devices). 71 In this regard, the technology of virtual reality holds a high potential to facilitate research, as used in intervention work. 72 Although challenges remain, this framework opens new windows into future research and clinical practice: quantitative measurements of social coordination deficits can benefit from data-driven analyses; and functional connectivity derived from meta-analyses can predict diverse social behaviours, 73 fostering the establishment of direct brain-behaviour relationships and the detection of key brain networks. ...
The interpersonal computational psychiatry of social coordination in schizophrenia
Article
  • Jul 2023
Impairments in social coordination form a core dimension of various psychiatric disorders, including schizophrenia. Advances in interpersonal and computational psychiatry support a major change in studying social coordination in schizophrenia. Although these developments provided novel perspectives to study how interpersonal activities shape coordination and to examine computational mechanisms, direct attempts to integrate the two methodologies have been sparse. Here, we propose an interpersonal computational framework that (1) leverages the active inference framework to model aberrant social coordination processes in schizophrenia and (2) incorporates dynamical system models to dissect intrapersonal and interpersonal synchronisation to inform a statistical model based on active inference. We discuss how this interpersonal computational psychiatry framework can elucidate the aberrant processes leading to psychopathology, with schizophrenia as an example, and highlight how it might aid clinical intervention and practice. Finally, we discuss challenges and opportunities for using the framework in studying social coordination impairments.
View
... For example, simulations could explore the interaction of neuroticism with environmental stressors, testing whether the predicted outcomes align with real-world data. Additionally, data from digital sensing technologies (e.g., actimetry, speech markers) and ecological momentary assessments can be used to augment agent behaviors, ensuring alignment with real-world behavioral patterns and enhancing the realism of the simulations [71][72][73] . ...
Modelling the impact of environmental and social determinants on mental health using generative agents
Article
Full-text available
  • Jan 2025
Mental health is shaped by socio-environmental determinants, yet traditional research approaches struggle to capture their complex interactions. This review explores the potential of generative agents, powered by large language models, to simulate human-like behaviour in virtual environments for mental health research. We outline potential applications including the modelling of adverse life events, urbanicity, climate change, discuss potential challenges and describe how generative agents could transform mental health research.
View
... Three main factors contribute to ecological validity: the nature of the setting, the stimuli applied, and the subject's response (Schmuckler, 2001). For example, in the case of neuropsychological test performance, prediction of real-life functioning has been shown to be generally modest, because standardized and objective measures of real-life functioning itself are often missing (Chaytor & Schmitter-Edgecombe, 2003;Lahnakoski et al., 2021). However, recent developments in methodologies such as ecological momentary assessment (Shiffman et al., 2008), and the increasing use of naturalistic stimuli in neuroimaging research (Sonkusare et al., 2019), constitute promising steps toward enhancing neuroscience-based prediction of real-life function and dysfunction. ...
Methodological considerations: Integrating measures across assessment modalities
Preprint
Full-text available
  • Sep 2024
Large-scale multimodal data have never been more accessible in neuroscience, providing an unprecedented opportunity to study interindividual differences. Integrating these data across assessment modalities, as opposed to treating each modality in isolation, requires careful consideration of both theoretical and practical nature. This chapter provides an overview of key concepts essential for truly integrative clinical neuroscience. Successful translation of basic research into clinical knowledge requires a common reference framework that accounts for dimensional phenotypes organized at multiple levels in a dynamically interacting system. At the same time, clinical care relies on relatively simple categories to enable efficient prevention, diagnosis, and treatment of pathological conditions. An appropriate framework must bridge both, with particular emphasis on aspects that are important for understanding the occurrence and developing treatment of dysfunctional states. Neuroscience methodology is embedded in this hierarchical organization, with different recording and stimulation methods targeting processes at different levels. Challenges remain in the actual integration of data obtained at different biological levels, on different timescales, at different spatial resolutions, and often in different species. In particular, cross-species translation of (clinical) research can only succeed if both the measurement methodology and the process to be measured are well conceived and have clear counterparts in humans and the respective animal models. Finally, we show how “deep multimodal phenotyping” represents an ideal case of neuroscience research crossing multiple levels of organization in single individuals. Emerging tools for complex multivariate data analysis should aim to successfully integrate these data into real-world knowledge.
View
... Synchrony deficits in PSZ can be investigated using paradigms for interpersonal coordination, such as a simple joint fingertapping paradigm (Heggli et al., 2019) as well as more naturalistic situations (Pan and Cheng, 2020;Lahnakoski et al., 2022). However, conventional analytic approaches assess coordination between individuals based solely on reaction time, phase, or synchrony. ...
Interpersonal coordination in schizophrenia: A concise update on paradigms, computations, and neuroimaging findings
Article
Full-text available
  • Feb 2023
Social functioning impairment is a hallmark of mental illness. As one of the most intractable and severe psychiatric disorders, schizophrenia is characterized by deficits on multiple social cognitive domains. In particular, failures of interpersonal coordination (i.e., actions that occur in spatial and temporal concordance with those of other individuals in a social setting) in schizophrenia are closely linked to significant prognostic indicators, such as symptom remission, quality of life, and employment. Despite the increasing interest in the psychological and neural mechanisms of interpersonal coordination in schizophrenia, important gaps in our understanding remain. Notably, the study of the mechanisms underpinning interpersonal coordination is currently undergoing a methodological shift, moving its focus from single-person tasks to second- and multi-person paradigms, and from model-free to model-based analyses. However, applications of these advanced approaches in schizophrenia has been slow. Here, we provide a concise update on the uses of multi-person paradigms to study interpersonal coordination and mathematical models to dissect its computational mechanisms, at both behavioral and neural levels. We then review prior studies on large-scale neuroimaging studies that explore brain correlates of general social functions and further pointed to the implementation of dissecting interpersonal coordination deficits in schizophrenia. Finally, we highlight key challenges as well as exciting opportunities for integrating research in computational psychiatry with second- and multi-person approaches in investigating interpersonal coordination deficits in schizophrenia.
View
Synchrony Across Brains
Article
  • Oct 2024
  • ANNU REV PSYCHOL
Second-person neuroscience focuses on studying the behavioral and neuronal mechanisms of real-time social interactions within single and across interacting brains. In this review article, we describe the developments that have been undertaken to study socially interactive phenomena and have helped to focus on behavioral and neurobiological processes that extend across interaction partners. More specifically, we focus on the role that synchrony across brains plays in enabling and facilitating social interaction and communication and in shaping social coordination and learning, and we consider how reduced synchrony across brains may constitute a core feature of psychopathology.
View
View
View
Noninvasive brain stimulation in autism: review and outlook for personalized interventions in adult patients
Article
Full-text available
  • May 2024
  • CEREB CORTEX
Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.
View
sCD14, a marker of immune-inflammation can help to distinguish between psychotic disorders with and without disordered social interaction
Article
  • Oct 2023
  • MED HYPOTHESES
Social interaction difficulties and loneliness as well as activation of immunological pathways and a status of low-grade immune-inflammation are thought to be associated with psychotic disorders. So far, a single biomarker that indicates disordered social interaction as part of psychotic disorders and immune-inflammation has yet to found but could be clinically useful. If low-grade immune-inflammation is a contributor to psychotic disorders, it raises the question where exactly, when and why it begins to negatively impact the human body? Deviant gut microbiota have been discussed in this context. Here, stress resulting from disordered social interaction may contribute to the disruption of the intestinal barrier. Lipopolysaccharides (LPS) from bacteria can enter the body leading to an activation of monocytes – among others – via the cluster of differentiation 14 (CD14) and further influencing central nervous structures. CD14 can be released by monocytes upon activation as a soluble form (sCD14). We hypothesize that sCD14 could be a useful biomarker to evaluate the consequences of disordered social interaction in psychotic patients including low-grade immune-inflammation via the gut-brain axis. This could be performed using an analysis of gut microbiota, flow cytometry and proteome analysis of blood and cerebrospinal fluid (CSF) and cerebral Magnetic Resonance Imaging (MRI) together with further systematic evaluations of social behavior.
View
Proof-of-Mechanism Study of the PDE10 Inhibitor RG7203 in Patients with Schizophrenia and Negative Symptoms
Article
Full-text available
  • Mar 2021
Background Reduced activation of dopamine D1 receptor signaling may be implicated in reward functioning as a potential driver of negative symptoms in schizophrenia. Phosphodiesterase (PDE) 10A, an enzyme that is highly expressed in the striatum, modulates both dopamine D2- and D1-dependent signaling. Methods We assessed whether augmentation of D1 signaling by the PDE10 inhibitor RG7203 enhances imaging and behavioral markers of reward functions in schizophrenia patients with negative symptoms. In a 3-period, double-blind, cross-over study, we investigated the effects of RG7203 (5 mg and 15 mg doses) and placebo as adjunctive treatment to stable background antipsychotic treatment in chronic schizophrenia patients with moderate levels of negative symptoms. Effects on reward functioning and reward-based effortful behavior were evaluated using the monetary incentive delay (MID) task during functional magnetic resonance imaging and the Effort Cost Benefit and Working Memory Reinforcement Learning tasks. Results Patients (n = 33; 30 male, mean [standard deviation] age 36.6 ± 7.0 years; Positive and Negative Syndrome Scale Negative Symptom Factor Score 23.0 ± 3.5 at screening) were assessed at 3 study centers in the United States; 24 patients completed the study. RG7203 at 5 mg significantly increased reward expectation-related activity in the MID, but in the context of significantly decreased overall activity across all task conditions. Conclusions In contrast to our expectations, RG7203 significantly worsened reward-based effortful behavior and indices of reward learning. The results do not support the utility of RG7203 as adjunctive treatment for negative symptoms in patients with schizophrenia.
View
Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges
Article
Full-text available
  • Nov 2020
Individuals differ in their physiological responsiveness to stressful challenges, and stress potentiates the development of many diseases. Heart rate variability (HRV), a measure of cardiac vagal break, is emerging as a strong index of physiological stress vulnerability. Thus, it is important to develop tools that identify predictive markers of individual differences in HRV responsiveness without exposing subjects to high stress. Here, using machine learning approaches, we show the strong predictive power of high-dimensional locomotor responses during novelty exploration to predict HRV responsiveness during stress exposure. Locomotor responses are collected in two ecologically valid virtual reality scenarios inspired by the animal literature and stress is elicited and measured in a third threatening virtual scenario. Our model’s predictions generalize to other stressful challenges and outperforms other stress prediction instruments, such as anxiety questionnaires. Our study paves the way for the development of behavioral digital phenotyping tools for early detection of stress-vulnerable individuals.
View
Unobtrusive tracking of interpersonal orienting and distance predicts the subjective quality of social interactions
Article
Full-text available
  • Aug 2020
Interpersonal coordination of behaviour is essential for smooth social interactions. Measures of interpersonal behaviour, however, often rely on subjective evaluations, invasive measurement techniques or gross measures of motion. Here, we constructed an unobtrusive motion tracking system that enables detailed analysis of behaviour at the individual and interpersonal levels, which we validated using wearable sensors. We evaluate dyadic measures of joint orienting and distancing, synchrony and gaze behaviours to summarize data collected during natural conversation and joint action tasks. Our results demonstrate that patterns of proxemic behaviours, rather than more widely used measures of interpersonal synchrony, best predicted the subjective quality of the interactions. Increased distance between participants predicted lower enjoyment, while increased joint orienting towards each other during cooperation correlated with increased effort reported by the participants. Importantly, the interpersonal distance was most informative of the quality of interaction when task demands and experimental control were minimal.These results suggest that interpersonal measures of behaviour gathered during minimally constrained social interactions are particularly sensitive for the subjective quality of social interactions and may be useful for interaction-based phenotyping for further studies.
View
A Connectome Wide Functional Signature of Transdiagnostic Risk for Mental Illness
Article
Full-text available
  • Apr 2018
  • BIOL PSYCHIAT
Background High rates of comorbidity, shared risk, and overlapping therapeutic mechanisms have led psychopathology research towards transdiagnostic dimensional investigations of clustered symptoms. One influential framework accounts for these transdiagnostic phenomena through a single general factor, sometimes referred to as the ‘p’ factor, associated with risk for all common forms of mental illness. Methods Here we build on past research identifying unique structural neural correlates of the p factor by conducting a data-driven analysis of connectome wide intrinsic functional connectivity (n = 605). Results We demonstrate that higher p factor scores and associated risk for common mental illness maps onto hyper-connectivity between visual association cortex and both frontoparietal and default mode networks. Conclusions These results provide initial evidence that the transdiagnostic risk for common forms of mental illness is associated with patterns of inefficient connectome wide intrinsic connectivity between visual association cortex and networks supporting executive control and self-referential processes, networks which are often impaired across categorical disorders.
View
New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research
Article
Full-text available
  • May 2016
Background A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Objective Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. Methods We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. Results We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Conclusions Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health.
View
Toward a second-person neuropsychiatry
Article
Full-text available
Psychiatric disorders can affect our ability to successfully and enjoyably interact with others. Conversely, having difficulties in social relations is known to increase the risk of developing a psychiatric disorder. In this article, the assumption that psychiatric disorders can be construed as disorders of social interaction is reviewed from a clinical point of view. Furthermore, it is argued that a psychiatrically motivated focus on the dynamics of social interaction may help to provide new perspectives for the field of social neuroscience. Such progress may be crucial to realize social neuroscience’s translational potential and to advance the transdiagnostic investigation of the neurobiology of psychiatric disorders.
View
Nonverbal synchrony of head- and body-movement in psychotherapy: different signals have different associations with outcome
Article
Full-text available
  • Sep 2014
Objective: The coordination of patient’s and therapist’s bodily movement – nonverbal synchrony – has been empirically shown to be associated with psychotherapy outcome. This finding was based on dynamic movement patterns of the whole body. The present paper is a new analysis of an existing dataset (Ramseyer and Tschacher, 2011), which extends previous findings by differentiating movements pertaining to head and upper-body regions. Method: In a sample of 70 patients (37 female, 33 male) treated at an outpatient psychotherapy clinic, we quantified nonverbal synchrony with an automated objective video-analysis algorithm (motion energy analysis). Head- and body-synchrony was quantified during the initial 15 min of video-recorded therapy sessions. Micro-outcome was assessed with self-report post-session questionnaires provided by patients and their therapists. Macro-outcome was measured with questionnaires that quantified attainment of treatment goals and changes in experiencing and behavior at the end of therapy. Results: The differentiation of head- and body-synchrony showed that these two facets of motor coordination were differentially associated with outcome. Head-synchrony predicted global outcome of therapy, while body-synchrony did not, and body-synchrony predicted session outcome, while head-synchrony did not. Conclusion: The results pose an important amendment to previous findings, which showed that nonverbal synchrony embodied both outcome and interpersonal variables of psychotherapy dyads. The separation of head- and body-synchrony suggested that distinct mechanisms may operate in these two regions: Head-synchrony embodied phenomena with a long temporal extension (overall therapy success), while body-synchrony embodied phenomena of a more immediate nature (session-level success). More explorations with fine-grained analyses of synchronized phenomena in nonverbal behavior may shed additional light on the embodiment of psychotherapy process.
View
Patients with autism spectrum disorders display reproducible functional connectivity alterations
Article
  • Feb 2019
  • Sci Transl Med
Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper-and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.
View
View
Digital Phenotyping: Technology for a New Science of Behavior
Article
  • Oct 2017
Traditionally, psychiatry has offered clinical insights through keen behavioral observation and a deep study of emotion. With the subsequent biological revolution in psychiatry displacing psychoanalysis, some psychiatrists were concerned that the field shifted from “brainless” to “mindless.”¹ Over the past 4 decades, behavioral expertise, once the strength of psychiatry, has diminished in importance as psychiatric research focused on pharmacology, genomics, and neuroscience, and much of psychiatric practice has become a series of brief clinical interactions focused on medication management. In research settings, assigning a diagnosis from the Diagnostic and Statistical Manual of Mental Disorders has become a surrogate for behavioral observation. In practice, few clinicians measure emotion, cognition, or behavior with any standard, validated tools.
View