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DOI: 10.1177/1754073911421398 2012 4: 22Emotion Review

Henrik WalterAuthor reply: Empathy and the Brain: How We Can Make Progress

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Emotion ReviewVol. 4, No. 1 (January 2012) 22 23

The Author(s) 2012ISSN 1754-0739DOI: 10.1177/1754073911421398er.sagepub.com

Abstract

Neuroscientific research on empathy has made much progress recently. How far can we get and how should we do it? Two different routes have been suggested by Dziobek and Jacobs in their commentaries. The first is becoming ecologically more valid by using real-life settings as stimuli. The second is becoming more quantitative by specifying a neurocognitive model, allowing more precise quantitative predictions. Although neither approaches are mutually exclusive, I suggest that these two routes are in a certain tension to each other. I suggest an additional third, more indirect way, namely studying modulating factors of empathy like emotion regulation which have until now been largely neglected in empathy research.

Keywordsaffective neuroscience, emotion regulation, empathy, theory of mind

There is now a quite well-elaborated, more or less agreed-upon concept of empathy used in social cognitive neuroscience (Walter, 2012). In their commentaries to my article, Diziobek (2012) and Jacobs (2012) have suggested two ways to make further progress. The idea suggested by Dziobek is to investi-gate ecologically more valid empathy-relevant situations. Indeed, many empathy studies have used very static stimuli such as photos, pictures, simple verbal stories, or cartoons, which are less rich compared to empathy-relevant situations from real life, such as conversations and complex social inter-action. Dziobek herself has contributed significantly to this approach by developing ecologically valid instruments like the Movie for the Assessment of Social Cognition (MASC). However, ecological validity in complex matters comes with a cost. If we observe effects between conditions or groups, it is often difficult to attribute them to a specific process involved in the function in question as there are so many factors combined in these complex stimuli. Furthermore, we might end up find-ing a neural correlate of complex stimulus material that is related to very general functions involved in processing com-plex scenes. In contrast to the ecological approach, considerable

progress in cognitive neuroscience has always been made by boiling down a specific question about a complex function to a very simple, highly controllable and straightforwardly inter-pretable experimental design. This approach also recommends itself with respect to the limited nature of our dependent varia-bles in brain imaging.

Another approach of science in general and in cognitive neuroscience in particular has been suggested by Jacobs (2012). He argues that it would be desirable to move on from descrip-tive models to more quantitative models that make exact predictions about the change in certain model parameters under different settings. This is certainly true. Computational neu-roscience even goes a step further by allowing the use of off-line (simulation) experiments which then might inform further experimental work in humans to test predictions generated from simulations. However, this approach is particularly useful for more basic neurocognitive functions that are easily described with a limited set of clearly measurable dependent variables. As a matter of fact, empathy is neither simple, nor, as an affective state, easy to measure. Indeed, the problemthat we have no good or reliable indicator for affective experi-ence as suchmakes it so difficult for affective neuroscience to translate to quantifiable models without becoming too cognitive. In fact, the idea of using more ecological stimulus material and the idea of having a quantitative, precise prediction-generating model do not go very well together, at least in the first place.

Nevertheless, the proof of the pudding is in the eating and time will tell which of these approaches will advance our scien-tific understanding of empathy in the years to come. For the time being it is already very helpful that at least a common con-cept of empathy has emerged and that there are established paradigms and instruments for quantifying empathy. Starting from this common ground I want to suggest a third way to study the neural correlates of empathy more indirectly: by manipulat-ing other cognitiveaffective processes and contextual factors involved in empathy (see de Vignemont & Singer, 2006). For example, conceptually it is clear that in order to not end up in

Empathy and the Brain: How We Can Make Progress

Henrik WalterDepartment of Psychiatry and Psychotherapy, Charit Universittsmedizin Berlin, Germany

Corresponding author: Henrik Walter, Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Charit Universittsmedizin Berlin, Campus Mitte, Charitplatz 1, D-10117 Berlin, Germany. Email: henrik.walter@charite.de

421398 EMR4110.1177/1754073911421398WalterEmotion Review

Author Reply

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Walter Reply to Commentaries 23

experiencing just personal distress but rather to be able to empathize, subjects have to have a good capacity to regulate their (isomorphic) emotions elicited in empathy contexts. Emotion regulation has become a booming field of research which allows to nicely quantify regulated and regulating struc-tures of the brain (e.g., Erk et al., 2010; Walter et al., 2009). By studying the modulation (emotion regulation) of the isomorphic affective states and their neural correlates in controlled ways we will better understand the nature of empathy (see Decety, 2011). Because emotion regulation has already yielded a wealth of quantitative data, this might be a way to get less descriptive and more quantitative on the way towards a neurocognitive or, better, neuroaffective model of empathy. Because individual differ-ences and genetic dispositions are an important issue for empathy, knowledge from imaging genetics about emotion regulation (e.g., Schardt et al., 2010) can perhaps also better be integrated in such a future model.

Note that I suggest neither that these three ways to pro-gress are mutually exclusive, nor that they are the only ways. There are many other approaches out there, for example, investigating brain lesions, brain stimulation, children or patient groups. Progress will be made on different routes being used by people who are experts in their respective fields. Actually, I predict that in some years we will have a new wealth of data which will call for a more comprehensive model of empathy

that hopefully will also be able to integrate some of the insights that the social sciences and humanities have gained.

ReferencesDecety, J. (2011). Dissecting the neural mechanisms mediating empathy.

Emotion Review, 3, 92108.de Vignemont, F., & Singer, T. (2006). The empathic brain: How, when and

why? Trends in Cognitive Sciences, 10, 435441.Dziobek, I. (2012). Towards a more ecologically valid assessment of

empathy. Emotion Review, 4, 1819.Erk, S., Mikschl, A., Stier, S., Ciaramidaro, A., Gapp, V., Weber, B., &

Walter, H. (2010). Acute and sustained effects of cognitive emotion regulation in major depression. The Journal of Neuroscience, 30, 15726 15734.

Jacobs, A. (2012). Comment on Walters Social cognitive neuroscience of empathy: Concepts, circuits, and genes. Emotion Review, 4, 2021.

Schardt, D. M., Erk, S., Nsser, C., Nthen, M. M., Cichon, S., Rietschel, M., Walter, H. (2010). Volition diminishes genetically mediated amygdala hyperreactivity. NeuroImage, 53, 943951.

Walter, H. (2012). Social cognitive neuroscience of empathy: Concepts, circuits, and genes. Emotion Review, 4, 917.

Walter, H., Kalckreuth, A., Schardt, D., Stephan, A., Goschke, T., & Erk, S. (2009). The temporal dynamics of voluntary emotion regulation: Immediate and delayed neural aftereffects. PLoS ONE, 4, e6726. doi: 10.1371/journal.pone.0006726

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