A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

Jean Laurens, Dora Angelaki

Research output: Contribution to journalArticle

Abstract

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements.

Original languageEnglish (US)
Article numbere28074
JournaleLife
Volume6
DOIs
StatePublished - Oct 18 2017

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Neurons
Motion estimation
Head Movements
Sensory Feedback
Sensory Receptor Cells
Feedback
Brain Stem
Cues
Kalman filters
Head
Modulation

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation. / Laurens, Jean; Angelaki, Dora.

In: eLife, Vol. 6, e28074, 18.10.2017.

Research output: Contribution to journalArticle

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