Embodied behavioural complexity in a ciliated microorganism

ORAL

Abstract

Most animals coordinate behavior using neural computations. Yet, single-celled organisms also exhibit stimulus-responsive, even cognitive, actions. To understand how a single cell can coordinate and drive complex behaviors without any neural encoding, we study an algal protist -- a motile cell with four extremely long cilia. The organism displays a surprisingly rich locomotor repertoire, emerging from the intricate dynamics of the cilia, which form a tight bundle when swimming.

By combining high-speed quantitative live imaging with spectral mode decomposition and wavelet analysis, we extract the spectrum of possible ciliary beating patterns, and derive a dispersion relation coupling the temporal frequency and spatial wavelength of cilia oscillations. In addition, we reconstruct a low-dimensional manifold embedded in the behavioral space, showing that despite the range and complexity of ciliary beating modes, the underlying behavioral manifold is intrinsically low-dimensional with dynamic and excitable transitions in motility behavior encoded as trajectories in this space.

*This work was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme grant 853560 Evomotion (to KYW) and the NSF-Simons National Institute for Theory and Mathematics in Biology (NITMB) Fellowship supported via grants from the NSF (DMS-2235451) and Simons Foundation (MPS-NITMB-00005320) (to ADH). This research received support through Schmidt Sciences, LLC (Polymath Award to JD) and the MIT MathWorks Professorship Fund (JD).

Presenters

  • Alasdair D Hastewell

    • NSF-Simons National Institute for Theory and Mathematics in Biology, Chicago IL, 60611, USA
    • National Institute for Theory and Mathematics in Biology
    • Massachusetts Institute of Technology

Authors

  • Alasdair D Hastewell

    • NSF-Simons National Institute for Theory and Mathematics in Biology, Chicago IL, 60611, USA
    • National Institute for Theory and Mathematics in Biology
    • Massachusetts Institute of Technology
  • Alexander K Boggon

    • University of Exeter
  • Kirsty Y Wan

    • University of Exeter
  • Jorn Dunkel

    • Massachusetts Institute of Technology