Man Bites Dog: The Representation of Structured Meaning in Left-Mid Superior Temporal Cortex

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Man Bites Dog: The Representation of Structured Meaning in Left-Mid Superior Temporal Cortex

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Title: Man Bites Dog: The Representation of Structured Meaning in Left-Mid Superior Temporal Cortex
Author: Frankland, Steven Michael
Citation: Frankland, Steven Michael. 2015. Man Bites Dog: The Representation of Structured Meaning in Left-Mid Superior Temporal Cortex. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
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Abstract: Human brains flexibly combine the meanings of individual words to compose structured thoughts. For example, by combining the meanings of ‘bite’, ‘dog’, and ‘man’, we can think either of a dog biting a man, or the newsworthy case of a man biting a dog (Pinker, 1997). Here, in three functional Magnetic Resonance Imaging (fMRI) experiments, we identify a region of left-mid Superior Temporal Cortex (lmSTC) that represents the current values of abstract semantic variables (“Who did it?” and “To whom was it done?”) in anatomically distinct sub-regions. Experiment 1 first identifies a broad region of lmSTC whose activity patterns (a) facilitate decoding of who did what to whom and (b) predict affective amygdala responses that depend on this information (e.g. “the baby kicked the grandfather” vs. “the grandfather kicked the baby”). Experiment 2 then identifies distinct, but neighboring, sub-regions of lmSTC whose activity patterns carry information about the identity of the current agent (“Who did it?”) and the current patient (“To whom was it done?”). These neighboring sub-regions lie along the upper bank of the superior temporal sulcus and the lateral bank of the superior temporal gyrus, respectively. At a high-level, these regions may function like topographically defined data registers, encoding the fluctuating values of abstract semantic variables. Experiment 3 replicates the agent/patient topography of Experiment 2, and further suggests that these variables do not represent the grammatical relations of the sentence, but the semantic relations of the participants in the event described. The code by which lmSTC encodes the values of these variables remains unclear, however. We find no positive evidence that it is either phonological or semantic, leaving open the possibility that lmSTC prioritizes distinctiveness and efficiency by using a compressed code. This functional architecture, which in key respects resembles that of a classical computer, may play a critical role in enabling humans to flexibly generate complex thoughts.
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Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:17467506
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