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.

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):

Link 1

Link 2

Pavlovian learning mechanisms are involved in the development and maintenance of addictive disorders like alcohol use disorder. Environmental cues repeatedly paired with drugs of abuse acquire motivational value, thus becoming conditioned cues able to elicit craving and trigger relapse even after long phases of abstinence. One way to counteract these maladaptive associations is extinction learning. Because extinction constitutes a new, inhibitory learning process rather than unlearning, several Pavlovian relapse phenomena can cause the conditioned response to recover (i.e. simple passage of time, a change in context, or an unexpected encounter with the reinforcer). Our research project aims to gain a better understanding of the neural circuits involved in appetitive Pavlovian conditioning, extinction, and related relapse phenomena, as this might contribute to more effective treatment strategies in the future.
In a series of experiments with healthy participants we investigate different aspects of Pavlovian learning using conditioning paradigms with monetary and primary reinforcers combined with a multi-modal approach to evaluate conditioned responses (including psycho-phyphysiological measures like skin conductance responses, startle reflexes, or heart rate, as well as eye-tracking and fMRI). Specific research questions are:

(i) Which implicit, psycho-physiological measures are suitable to evaluate appetitive Pavlovian learning processes?

(ii) Can we model appetitive Pavlovian relapse effects on a psycho-physiological level in the laboratory? What are the neural circuits mediating Pavlovian relapse?

(iii) Can we predict Pavlovian relapse effects based on individual differences in psycho-physiological or neural profiles during conditioning and/or extinction?

(iv) Can we pharmacologically augment extinction learning using the partial N-Methyl-D-Aspartat (NMDA) receptor agonist d-cycloserine (DCS)?

Our work is focused on alterations in neurocognitive processes using non-invasive stimulation techniques such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS). We are investigating the experimental modulation of brain activation and its impact on behavioral and neurobiological outcome measures like local activity (fMRI) and effective connectivity (dynamic causal modeling, DCM). Our investigations are centered around cognitive processes underlying human behavior like reward learning and working memory.
Non-invasive stimulation techniques are a putative therapeutic tool for several kinds of symptoms. The understanding of the effect of non-invasive stimulation techniques and its neurobiological underpinnings will help to refine the application for neuropsychiatric patients.