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Reproducible, Generalizable Brain Models of Affective Processes

Part of the Nebraska Symposium on Motivation book series (NSM,volume 66)

Abstract

Recent years have seen dramatic advancement in the measurement of biology at a systems level. In humans, neuroimaging can be used to probe the brain bases of affect and emotion in increasingly sophisticated ways, but the complexity of these measures presents new challenges in maintaining scientific transparency and reproducibility. We describe several new models of the brain bases of affective processes, including models that predict the intensity of pain, negative affect, autonomic responses, and prosocial emotions including empathic care and distress. These models reduce complex, brain-wide neuroimaging data to measures that can be readily replicated and generalized across laboratories, and they can yield correlates of affective behavior that are substantially stronger than those based on single regions from standard brain maps. They can also be used as mechanistic targets for interventions, allowing comparisons across diverse treatments. Most importantly, they can teach us about the brain representations that underlie various forms of affect, in part by providing information about the necessary and sufficient brain bases for predicting affective states and behaviors. The results across the series of studies discussed here indicate that different forms of affect have reliably different brain representations. For example, somatic pain, romantic rejection, vicarious pain, and empathic care all have differentiable brain substrates. The latter processes are particularly important for empathy and prosocial behavior, and the chapter includes an extended example of how multivariate brain measures can inform us about how we might recognize others’ suffering and take action to help.

Keywords

  • Brain models
  • Affective processes
  • Scientific transparency
  • Scientific reproducibility
  • Prosocial emotions
  • Somatic pain
  • Empathic care
  • Prosocial behavior

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Acknowledgments

We are grateful for support from the National Institutes of Health, including grants R01DA035484 (Tor Wager), R01MH076136 (Tor Wager), R01MH116026 (Luke Chang), T32DA017637 (Philip Kragel), and U01 500470-78051 (Lisa Feldman Barrett). MATLAB code for analyses used in papers and figures is available at: https://github.com/canlab.

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Kragel, P., Wager, T.D. (2019). Reproducible, Generalizable Brain Models of Affective Processes. In: Neta, M., Haas, I. (eds) Emotion in the Mind and Body. Nebraska Symposium on Motivation, vol 66. Springer, Cham. https://doi.org/10.1007/978-3-030-27473-3_8

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