Elliot Murphy | Deriving hierarchical phrase structure from the computational properties of travelling oscillations and variational free energy

Guest Lecture

  • Date: Dec 6, 2018
  • Time: 02:00 PM - 03:00 PM (Local Time Germany)
  • Speaker: Elliot Murphy
  • University College London, United Kingdom
  • Location: MPI for Human Cognitive and Brain Sciences
  • Room: Charlotte Buehler Room (C402)
Over the past decade a range of linking hypotheses have been drawn up to ground the recursive syntactic component within the brain. In the realms of cognitive and systems neuroscience, the search for the neural code across a number of domains has seen a marked transition from the analysis of individual spike timings to larger patterns of synchronization. This presentation will argue that the language sciences should embrace these systems-level developments, with recent findings concerning the scope of possible oscillatory synchronization in the human brain (which has independently been shown to exhibit species-specific richness in terms of possible cross-frequency couplings) revealing the existence of traveling/migrating oscillations, adding further impetus to reject the typical stasis found in cartographic neurolinguistics models. After exploring empirically-motivated revisions to the neural code for hierarchical phrase structure, it is discussed how this code could provide a new perspective on language disorders, fluid intelligence and language acquisition. Lastly, it will be suggested that the existence of syntactic structures in natural language constitutes a unique form of epistemic foraging, minimising surprise and variational free energy. Epistemic foraging concerns how brains use accumulated beliefs about the hidden states of the world to prescribe active sampling of new information in order to efficiently reduce uncertainty. This framework can neurobiologically ground recent developments in syntactic theory according to which phrase structure building involves algorithms subject to minimal search procedures, exhibiting general rules of computational efficiency.

Poster
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