Neural and behavioral markers for motivational negative symptoms of schizophrenia: a longitudinal approach

• Applicant: Professor Dr. Florian Schlagenhauf
• Subject Area: Biological Psychiatry
• Term: from 2017 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 323528193

The motivational negative symptoms of schizophrenia include avolition, asociality and anhedonia. These symptoms strongly contribute to impairments in social and occupational functioning as well as quality of life. At the same time there is a lack of evidence-based biological and psychosocial treatment approaches. Recent research employing behavioral experiments and functional neuroimaging has linked negative symptoms mainly to dysfunctions of the reward system. Despite these advances, treatment development is still hindered by a lack of biomarkers that can reliably link clinical symptoms to pathophysiological mechanisms. This project will define a set of neural and behavioral markers that can serve as biomarkers for treatment development for motivational negative symptoms. For this purpose we will establish (1) that these markers are robustly associated with negative symptoms, (2) that this association is longitudinally stable and (3) that this association is stable across centers. Furthermore, we will assess the longitudinal predictive power of each neurobehavioral marker for motivational negative symptoms. Finally, we will explore whether a combination of markers can improve cross-sectional and longitudinal prediction and be useful for defining mechanistically informed patient subgroups.In a longitudinal study at two centers (Berlin and Zurich) we will recruit 132 patients with 66 patients with schizophrenia and 30 controls. These participants will have a full assessment of psychopathology, behavioral measures and functional magnetic resonance imaging at intake and at 3 months. In addition, a follow-up psychopathological assessment will be performed in patients 9 months after intake. Behavioral markers will be derived from tasks assessing reinforcement learning, effort-based decision making, goal-directed behavioral control and option generation. Functional magnetic resonance imaging markers will be obtained with tasks assessing reward anticipation, reinforcement learning and working memory. Analytic approaches will include state-of-the-art computational modeling of behavioral and imaging data using a reinforcement learning framework and dynamic causal modelling as well as unsupervised classification approaches.Establishing a stable set of neural and behavioral markers will improve our understanding of motivational negative symptoms by bridging clinical phenomena and pathophysiological mechanisms. These markers can contribute to treatment development by identifying potential targets for biological and psychosocial interventions and they can be used as endpoints in clinical trials to better define the mechanisms of treatment interventions. Overall, we believe that this project is of high importance, because it will allow transforming the promising results of recent behavioral and neuroimaging research into a set of markers that will considerably improve the foundation for treatment research on the negative symptoms of schizophrenia.

• DFG Programme: Research Grants
• International Connection: Switzerland
• Co-Investigator: Privatdozent Dr. Stefan Kaiser