Pathologically reduced neural flexibility recovers during psychotherapy of OCD patients

Precision non-invasive brain stimulation: anin silicopipeline for personalized control of brain dynamics

Objective.Non-invasive brain stimulation (NIBS) offers therapeutic benefits for various brain disorders. Personalization may enhance these benefits by optimizing stimulation parameters for individual subjects.Approach.We present a computational pipeline for simulating and assessing the effects of NIBS using personalized, large-scale brain network activity models. Using structural MRI and diffusion-weighted imaging data, the pipeline leverages a convolutional neural network-based segmentation algorithm to generate subject-specific head models with up to 40 tissue types and personalized dielectric properties. We integrate electromagnetic simulations of NIBS exposure with whole-brain network models to predict NIBS-dependent perturbations in brain dynamics, simulate the resulting EEG traces, and quantify metrics of brain dynamics.Main results.The pipeline is implemented on o2S2PARC, an open, cloud-based infrastructure designed for collaborative and reproducible computational life science. Furthermore, a dedicated planning tool provides guidance for optimizing electrode placements for transcranial temporal interference stimulation. In two proof-of-concept applications, we demonstrate that: (i) transcranial alternating current stimulation produces expected shifts in the EEG spectral response, and (ii) simulated baseline network activity exhibits physiologically plausible fluctuations in inter-hemispheric synchronization.Significance.This pipeline facilitates a shift from exposure-based to response-driven optimization of NIBS, supporting new stimulation paradigms that steer brain dynamics towards desired activity patterns in a controlled manner.

A multi-modality and multi-dyad approach to measuring flexibility in psychotherapy

INTRODUCTION

Flexibility, the ability of an individual to adapt to environmental changes in ways that facilitate goal attainment, has been proposed as a potential mechanism underlying psychopathology and psychotherapy. In psychotherapy, most findings are based on self-report measures that have important limitations. We propose a multimodal, multi-dyad approach based on a nonlinear dynamical systems framework to capture the complexity of this concept.

METHOD

A new research paradigm was designed to explore the validity of the proposed conceptual model. The paradigm includes a psychotherapy-like social interaction, during which body movement and facial expressiveness data were collected. We analyzed the data using Hankel Alternative View of Koopmann analysis to reconstruct attractors of the observed behaviors and compare them.

RESULTS

The patterns of behavior in the two cases differ, and differences in the reconstructed attractors correspond with differences in self-report measures and behavior in the interactions.

CONCLUSIONS

The case studies show that information provided by a single modality is not enough to provide the full picture, and multiple modalities are needed. These observations can serve as an initial support for our claims that a multi-modal and multi-dyad approach to flexibility can address some of the issues of measurement in the field.

Fears Worth Testing Out: A Systematic Review of the Neural Mechanisms of Treatment Outcome for Anxiety-Related Disorders

With the advent of human neuroimaging, researchers were drawn to the idea that by better understanding the human brain, more effective mental health interventions could be developed. It has been more than 20 years since the first functional magnetic resonance imaging (fMRI) studies were conducted to examine changes in brain activation with anxiety-related treatments and more than 60 studies have since been published in this vein. For the current review, we conduct a systematic review of this literature, focusing on adult studies using task-based fMRI to measure brain activation changes with pharmacologic or psychotherapy interventions for phobia, social anxiety disorder, panic disorder, generalized anxiety disorder, posttraumatic stress disorder, and obsessive-compulsive disorder. Neuroscientific theories of anxiety-related disorders and their treatment have focused on prefrontal-insula-amygdala networks. Treatment-related decreases in amygdala and/or anterior insula activation were identified as the most consistent finding across disorders, with the most consistent results reported for specific phobia. Directionality of change and specific regions implicated in the prefrontal cortex were inconsistent across studies. The potential importance for probing other networks and processes as mechanisms of anxiety treatment was recognized, such as striatal regions underlying inhibitory learning or reward responsivity. Future treatment-fMRI research related to anxiety disorders would benefit from larger sample sizes, use of more nuanced computational approaches, and increased focus on replication. There is continued promise that fMRI research will enhance our understanding of how treatments work and inform the evolution of more effective or personalized mental health treatment.

Pattern transitions in diary data of MDD patients: a mixed-methods multiple case study of psychotherapy dynamics

Aim

Mixed-methods approaches promise a deep understanding of psychotherapeutic processes. This study uses qualitative and quantitative data from daily diary entries and daily self-assessments during inpatient treatment. The aim of the study is to get an insight into the similarities and differences between both types of data and how they represent self-organized pattern transitions in psychotherapy. While a complete correlation of results is not expected, we anticipate observing amplifying and subsidiary patterns from both perspectives.

Materials and methods

Daily, five MDD patients wrote diaries and completed self-assessments using the Therapy Process Questionnaire, a questionnaire for monitoring the change dynamics of psychotherapy. The data were collected using the Synergetic Navigation System, an online tool for real-time monitoring. Diary entries of the patients described their experiences in everyday life. The qualitative text analysis was conducted using Mixed Grounded Theory, which provided categories representing the patients' ongoing experiences of transformation and stagnation. The time series data was analyzed using the dynamic complexity algorithm and the pattern transition detection algorithm. Results from qualitative and quantitative analyses were combined and compared. Following the process of data triangulation, the leading perspective came from the theory of self-organization. In addition to presenting the overall results for all five patients, we delve into two specific case examples in greater detail.

Results

Specific and highly diversified diary entries of 5 patients were classified into the categories of perceived pattern stability, noticing improvement, broadening the perspective, critical instability, and experiencing moments of Kairos. Patients reported problems not only related to their disorder (e.g., lack of energy and hopelessness) but also to phases and steps of change, which could be related to the theory of self-organization (e.g., problem attractors, critical fluctuations, pattern transitions, and Kairos). Qualitative and quantitative analysis provide important supplementary results without being redundant or identical.

Conclusion

Data triangulation allows for a comprehensive and multi-perspective understanding of therapeutic change dynamics. The different topics expressed in the diary entries especially help to follow micro-psychological processes, which are far from being a simple reaction to interventions. The way patients experience themselves being in stability or instability and stagnation or transformation is surprisingly close to the general features of self-organizing processes in complex systems.

Plasticity in mental health: A network theory

Plasticity is the ability to modify brain and behavior, ultimately promoting an amplification of the impact of the context on the individual's mental health. Thus, plasticity is not beneficial per se but its value depends on contextual factors, such as the quality of the living environment. High plasticity is beneficial in a favorable environment, but can be detrimental in adverse conditions, while the opposite applies to low plasticity. Resilience and vulnerability are not univocally associated to high or low plasticity. Consequently, individuals should undergo different preventive and therapeutic strategies according to their plasticity levels and living conditions. Here, an operationalization of plasticity relying on network theory is proposed: the strength of the connection among the network elements defining the individual, such as its symptoms, is a measure of plasticity. This theoretical framework represents a promising tool to investigate research questions related to changes in neural structure and activity and in behavior, and to improve therapeutic strategies for psychiatric disorders, such as major depression.

About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject's Cellular Immune Activity: A Biopsychosocial Analysis

In a previous integrative single-case study, we collected biological, psychological and social time-series data on a 25-year-old healthy woman over the course of 126 12-h intervals (63 days) and used urinary neopterin as an indicator of cellular immune activity [Schubert et al. 2012 (1)]. The present re-evaluation introduced Dynamic Complexity (DC) as an additional non-linear and non-stationary measure to further investigate the subject's biopsychosocial dynamics during the study. The new time series dealing with urinary neopterin complexity revealed a cyclic, circaseptan (about-weekly) repeating pattern (6.59 days). The only weekly reoccurring events over the course of the study that were associated with this immunological pattern were the in-depth interviews with the subject (mean distance between interviews: 6.5 days). Superposed epoch analysis (SEA) revealed a U-shaped relation between neopterin complexity and interviews, with a decrease in neopterin complexity before and during interviews and an increase after interviews. Furthermore, the complexity scores for irritation, anxiousness/depressiveness and mental activity were positively correlated with neopterin complexity. The results suggest that the interviews, which had been found to be related to the subject's need for educational and/or social accomplishment, were marked by stress (decrease in psycho-immunological flexibility and adaptability), which was then relieved after the interviews (increase in psycho-immunological flexibility and adaptability). It appears that the subject's cellular immune activity, as indicated by neopterin complexity, functionally mirrored the emotional meaning she ascribed to the in-depth interviews. This re-evaluation is in line with the view that biopsychosocial research requires multimodal analysis of single cases based on qualitative (e.g., in-depth interviews) and quantitative (e.g., time series analysis) data under conditions of "life as it is lived".