Neural Noise

Human hippocampal theta–gamma coupling and sequential planning during navigation

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  • Human theta–gamma coupling coordinates sequential planning during navigation; neural mechanisms underlie executing sequences of actions to reach a destination (PNAS).1
  • Electrophysiological and relevant for computational neuroscience and potential decoding targets.1
  • The study used noninvasive magnetoencephalography (MEG) with an abstract image-based navigation task; participants planned routes through novel sequences of locations to reach a goal, allowing separation of planning and execution phases.1
  • Hippocampal theta power decreased with proximity to the current goal — but only during accurate navigation — suggesting theta reflects active spatial computation rather than mere locomotion.1
  • Theta–gamma phase–amplitude coupling (PAC) increased with goal proximity, consistent with the theoretical model that sequences of upcoming locations are encoded as gamma bursts at successive theta phases within each cycle.1
  • A double dissociation was observed between gamma subtypes: entorhinal high gamma dominated while traversing novel paths, while hippocampal low gamma dominated during previously experienced paths — replicating findings from rodent studies and extending them to the human non-invasive domain.1
  • This validates the “theta compression hypothesis” first proposed for short-term memory in rodents (O’Keefe & Recce, 1993): the same phase–amplitude coding mechanism used for sequential memory consolidation appears to be recruited for prospective planning in humans.2
  • Authors are from University College London (Human Electrophysiology Lab, Wellcome Centre for Human Neuroimaging); lead author Zimo Huang; co-authors James Bisby, Neil Burgess, and Daniel Bush; funded by a Wellcome Principal Research Fellowship (NB) and UKRI Frontier Research Grant (DB).1
  • Published in PNAS Vol. 123, No. 9 (March 3, 2026; online Feb 27, 2026); MEG data and analysis code deposited at the UCL Research Data Repository.1
  • The findings support using theta–gamma PAC as a neural decoding target for prospective planning states in closed-loop BCI applications and provide a mechanistic account of why hippocampal theta is elevated during route planning tasks.2

Footnotes

  1. https://www.pnas.org/doi/abs/10.1073/pnas.2513547123?af=R ↩ ↩2 ↩3 ↩4 ↩5 ↩6 ↩7 ↩8

  2. https://bushlab-ucl.github.io/publications/ ↩ ↩2

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