What we do 

Our lab is mainly interested in pain, fear and decision making. These topics are naturally intertwined, for example in classical conditioning, an example for fear learning, the organsim learns to predict a painful stimulus (e.g. shock). In addition, aversive outcomes such as pain have a tremendous influence on our behavior and especially on our decision making, which is mainly centered around the idea of seeking pleasant and avoiding aversive states e.g. those involving pain.

We try to identify mechanims behind these phenomena using a multi-level approach: analysis of behavior (e.g. eye-tracking), analysis of autonomic responses (e.g. skin conductance, pupil size) computational modeling of the underlying algorithmic and neural processes, multimodal neuroimaging (fMRI and EEG) of these processes, and pharmacological challenges to investigate the causal role of specific neurotransmitter systems.

These studies will not only contribute to our understanding of basic neuroscience mechanisms, but also provide novel ideas and approaches in clinical neuroscience, which could eventually improve prevention, diagnosis, prognosis and disease progression assessment in neuropsychiatric disorders including chronic pain. 

Pain

In the domain of pain we study very basic physiological mechanisms of pain processing and more complex interactions with cognitive systems. 

One example of a basic mechanism is the longstanding and heavily debated question whether certain brain areas play a special role in pain processing. Many previous studies on this topic confounded pain with salience, but we have now suggested a novel approach how to disentangle pain from salience (preprint of Horing et al.; details below). 

In addition, we have a major focus on the cognitive modulation of pain processing. A prime example of this effect is the placebo and nocebo effect in which expectation and experience can shape pain perception. Together with our Physics group, we have developed novel MR protocols to investigate spinal cord and brain responses simultaneously. This method was used to show that placebo analgesia involves modulation at the spinal cord level (Eippert et al., 2009) and more recently that also nocebo nyperalgesia involves a spinal mechanism (Tinnermann et al., 2017). We also employ pharmacological interventions and computational models, to identify the neuronal mechanisms underlying these effects. 

Fear

After initial studies on classical conditioning, we have a focus on generalization in fear learning or put simply why we fear something that we have never encountereed, but what looks similar to a dangerous object. Here we employ Bayesian models to explain how the percpetual distance can explain fear generalization (Onat and Büchel 2015; preview by Katherine Whalley).  We often use very simple paradigms such as classical conditioning, because this enables a link of our research to existing animal work. Methodologically, we are also bridging the gap between human neuroscientific research and animal neurophysiology by using high resolution neuroimaging techniques for instance to investigate emotional processing in different subnuclei of the amygdala.

Decision making

We have a longstanding interest in value based decision making, temporal discounting and hedonic processing. We currently focus on the opioid system and for instance could show that hedonic processing in the ventral striatum depends on endogoenous opioids (Büchel et al., 2018; details below).  An additional interest lies in the predictive value of neuronal markers for the development of addictive behavior. As part of the IMAGEN study together with our partner Brain Knutson at Stanford, we could show that hypoactivation of the ventral striatum and the dlPFC at age 14 can predict problematic drug use at age 16 (Büchel et al., 2017)

Examples of recent projects