The brain’s functional network architecture reveals human motives

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Science  04 Mar 2016:
Vol. 351, Issue 6277, pp. 1074-1078
DOI: 10.1126/science.aac7992

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  • RE: About misinterpretations and mischaracterizations Response to Alex Gamma’s comment
    • Grit Hein, Author /Psychologist/Neuroscientist, University of Zurich
    • Other Contributors:
      • Ernst Fehr, Author/Professor of Economics, University of Zurich

    We are grateful to Alex Gamma for his comments on our paper because it gives us the opportunity to address potential misinterpretations and mischaracterizations of our work.

    To begin with, consider the following experiment. Subjects in the fMRI scanner see a series of pictures of houses and faces and the researcher asks the question whether brain activity in the visual cortex predicts what subjects are actually seeing in each trial – a face or a house. Suppose the researcher uses some sort of machine learning tool (say, a support vector machine) that is trained on the basis of visual cortex activity of n-1 subjects during the watching of houses and faces and the “machine” successfully predicts what the n-th subjects sees in, say, 77% of the cases. To make this prediction, the researcher uses only the brain activation patterns in the visual cortex and nobody has ever before been able to predict what subjects see based on their brain activation patterns. Therefore, the researcher claims that it is possible to predict relatively accurately what individual subjects see in a given trial “merely on the basis of brain activation patterns in the visual cortex”.

    Is there anything wrong with the researcher’s interpretation of the predictive results? Obviously not, because in order to predict what subjects see the researcher only used the brain activation patterns in visual cortex. However, then a critic comes along and asks “what is the point of this predictive circus...

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    Competing Interests: None declared.
  • Hein et al: Innovation and “neuro-posturing"

    Two aspects stand out in the work of Hein et al (2016). One is the innovative analysis of brain imaging data to generate clues about the causal substrate of altruistic behavior. It constitutes the strength of the study and contributes to theory formation in psychological science. The other is a mischaracterization of the explanatory purview of the study, which feeds into current misconceptions about the power of neuroscience to elucidate the mind. I will focus on the latter aspect.

    In describing the rationale of their study, the authors cite the presumed fact that "asking people does not provide relevant information about motives”. Hence their stated aim to explore the possibility of identifying and predicting people's motives “merely on the basis of their functional neural network architecture”. This set-up creates the expectation that the authors are able to make inferences about subjects’ motives without using any information other than their neural activity (the title of the article bolsters that impression).

    This expectation is unjustified, however. The presence of the relevant motives in a subject—empathy-based and reciprocity-based altruism—is assumed as the result of a corresponding motive induction procedure, either watching a confederate receive painful stimuli or seeing a confederate spend money in order to save the subject from receiving painful stimuli. The success of this procedure is assessed by checking participants’ emotional rating...

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    Competing Interests: None declared.

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