You are here:
Dopaminergic mechanisms of reinforcement learning and working memory deficits in schizophrenia patients
Dysfunction of dopaminergic neurotransmission with a hyperdopaminergic state in the basal ganglia is a corner stone in current pathophysiological theories of schizophrenia. Molecular brain imaging studies in schizophrenia patients have confirmed increased striatal dopamine synthesis capacity. Alterations in the mesolimbic dopaminergic system can alter reinforcement learning functions such as prediction error signalling. Altered prediction error signalling and value representation have been proposed to contribute to central aspects of the disorder including aberrant salience attribution as well as motivational impairments. Alterations in the mesocortical dopaminergic system have been related to cognitive deficits such as working memory impairments caused by dysfunctions in fronto-parietal networks. For the therapy of schizophrenia antipsychotic medication is of great importance. Antidopaminergic antipsychotic medication is known to reduce psychotic symptoms and acts mainly via blocking of dopamine D2 receptors. However, little is known about how antipsychotic treatment effects presynaptic dopamine synthesis capacity and how treatment changes in presynaptic dopamine synthesis relate to changes in reinforcement learning, salience attribution and working memory function in schizophrenia patients. Therefore, we will investigate unmedicated schizophrenia patients before and after antipsychotic treatment in a longitudinal, multimodal study combining functional magnetic resonance imaging (fMRI) with positron emission tomography (PET) using the radioligand [18F]fluorodopa (FDOPA) to measure dopamine synthesis capacity. Detailed computational modeling will be used to describe alterations of reinforcement learning and working memory on the behavioral and neuronal level. We will compare pre- to post-treatment measures and test associations between the (hypothetical) change in dopamine synthesis capacity and changes in salience attribution, reward-dependent learning and working memory function in schizophrenia patients. This will enhance our understanding of the mechanisms of antipsychotic treatment on the dopaminergic dysfunction and core aberrant cognitive processes in schizophrenia patients.
Neural and behavioral markers for the motivational negative symptoms of schizophrenia – a longitudinal approach
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.
Neuronal value representation and pharmacological modulation of extinction learning in AUD (Juniorgroup of the DFG Forschergruppe FOR1617 – SCHL1969-2/1)
Addiction has been conceptualized as a disorder of learning with dysfunctions of neuronal structures underlying the attribution of value to environmental stimuli. Three key factors in the development and maintenance of alcohol use disorder (AUD) are at the core of this proposal: (i) the "hijacked" reward system with altered neuronal value representation of alcohol related and non-alcohol related reinforcers, (ii) the shift from goal-directed to habitual behavioural control, and (iii) the lack of behavioural adaptation in the absence of reward or in the presence of aversive consequences. These factors have been investigated in animal models using paradigms of habitization and extinction learning and in functional neuroimaging studies in healthy individuals. However, in humans suffering from AUD, the underlying neurobiological correlates are poorly understood. Therefore, the aim of this project is to develop and test behavioural and neuroimaging paradigms that will allow us to investigate 1) mechanisms of value representation of drug-related and non-drug related reinforcers, 2) the shift from goal-directed to habitual behavioural control and 3) modulation of learned alcohol-related behaviour during extinction. Specifically, alcohol-related rewarding stimuli will be contrasted with food-related and monetary rewards in instrumental learning, habitization, and extinction learning and complemented by pharmacological challenge studies using D-cycloserine, a potent enhancer of extinction learning. This project has a close cooperation with the Max-Planck Fellow Group 'Cognitive and affective control of behavioural adaptation'.
More information about the DFG Forschergruppe 'Learning & habitization as predictors of the development & maintenance of alcoholism' (FOR 1617):
The research group collaborates with multiple research facilities in Berlin and maintains several national and international scientific cooperations, e.g.
- Max-Planck Fellow Group 'Cognitive and affective control of behavioural adaptation' at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig
- Wellcome Trust Centre for Neuroimaging and Medical School, UCL, London (Ray Dolan)
- Section of Systems Neuroscience, Department of Psychiatry and Psychotherapy, Faculty of Medicine Carl Gustav Carus, Technical University Dresden (Michael Smolka, Hans-Ulrich Wittchen)
- Department of Nuclear Medicine and Research Center for Advanced Science and Technology, Tokyo University, Japan (Yoshitaka Kumakura)
- Department of Nuclear Medicine, Ludwig Maximilian University, Munich (Paul Cumming)
- Department of Psychology, Stanford University, CA, USA (Brian Knutson)