Periodic Reporting for period 4 - STRESNET (Stress Resilience and Network-Feedback Training)
Período documentado: 2021-03-01 hasta 2022-08-31
Decreasing the burden of stress-related mental problems and diseases is seen by many as one of the greatest health care challenges of the 21st century. Figures show that (each year) 60.4 million people (14% of the EU population) suffer from anxiety disorders, while major depression affects 29.8 million people (6.9%). Critically, stress-related symptoms tend to become chronic diseases, highlighting the need for early interventions to prevent their development. Efforts toward prevention are, however, hampered by a lack of understanding of the factors that determine resilience to stressors. The STRESNET project has made a major contribution to filling this gap by first detailing the effects of stress on brain function, with a focus on global shifts in brain function at the level of large-scale brain networks. Second, it identified the specific networks that are associated with resilience to real-life stressors, using mobile applications for self-report mood questionnaires and wearable biosensors. Third, the project has developed a novel biofeedback intervention based on real-time functional MRI to specifically target these brain networks, and showed that healthy volunteers can be trained to self-regulate brain activity at the level of balance between these brain networks. Together, these efforts provide a scientific foundation for future efforts toward mental health prevention in individuals at risk for development of stress-related diseases.
The STRESNET project has first developed the methodology for investigating neural responses to standardized laboratory stressors. Then, we implemented a platform that allowed us to investigate subjective (self report) and objective (physiological activity) measures of stress responsiveness in real life. Third, we developed the methodology that allowed us to investigate the potential effects of biofeedback based on neural activity in large-scale brain networks affected by stress.
Using these technologies, we found strong support for the core hypothesis that guided the project, namely that the acute stress response induces a shift in balance between large-scale brain networks. We showed how this shift is altered in individuals vulnerable for development of stress-related mental disorders, and how it predicts emotional responsiveness to stressors in real life. Finally, we showed that control over this stress-induced shift can be trained using biofeedback based on neural activity. Our results were disseminated at scientific conferences, seminars, summers schools, and in prominent international scientific journals. Our work has furthermore attracted substantial media attention (inter)nationally. The project team has furthermore actively reached out to the general public by organizing and participating in various public symposia, for instance on burnout and stress resilience.
Using these technologies, we found strong support for the core hypothesis that guided the project, namely that the acute stress response induces a shift in balance between large-scale brain networks. We showed how this shift is altered in individuals vulnerable for development of stress-related mental disorders, and how it predicts emotional responsiveness to stressors in real life. Finally, we showed that control over this stress-induced shift can be trained using biofeedback based on neural activity. Our results were disseminated at scientific conferences, seminars, summers schools, and in prominent international scientific journals. Our work has furthermore attracted substantial media attention (inter)nationally. The project team has furthermore actively reached out to the general public by organizing and participating in various public symposia, for instance on burnout and stress resilience.
The STRESNET project aimed to move beyond the state of the art in three critical directions: 1) From brain regions to brain circuits: Stress-related mental disorders should be studied as maladaptations at the circuit level rather than individual brain regions. 2) From treatment to prevention: Early intervention in stress-related disorders is critical to break the vicious cycle of remission and relapse. Technological developments such as wearable biosensors and mobile applications developed in the STRESNET project are creating the opportunity for real-life health monitoring and early intervention. 3) From vulnerability to resilience: Because resilience does not equal the absence of vulnerability, understanding factors that uniquely determine stress resilience is critical to develop new ways to promote mental health. The STRESNET project has made substantial contributions in moving the field of research into stress and stress-related disorders in these novel directions, and has thereby created the opportunity to develop and test early interventions to prevent development, relapse, and chronification of stress-related disorders.