Visual and Vestibular Selectivity for Self-Motion in Macaque Posterior Parietal Area 7a

Eric Avila, Kaushik J. Lakshminarasimhan, Gregory C. Deangelis, Dora E. Angelaki

Research output: Contribution to journalArticlepeer-review

Abstract

We examined the responses of neurons in posterior parietal area 7a to passive rotational and translational self-motion stimuli, while systematically varying the speed of visually simulated (optic flow cues) or actual (vestibular cues) self-motion. Contrary to a general belief that responses in area 7a are predominantly visual, we found evidence for a vestibular dominance in self-motion processing. Only a small fraction of neurons showed multisensory convergence of visual/vestibular and linear/angular self-motion cues. These findings suggest possibly independent neuronal population codes for visual versus vestibular and linear versus angular self-motion. Neural responses scaled with self-motion magnitude (i.e., speed) but temporal dynamics were diverse across the population. Analyses of laminar recordings showed a strong distance-dependent decrease for correlations in stimulus-induced (signal correlation) and stimulus-independent (noise correlation) components of spike-count variability, supporting the notion that neurons are spatially clustered with respect to their sensory representation of motion. Single-unit and multiunit response patterns were also correlated, but no other systematic dependencies on cortical layers or columns were observed. These findings describe a likely independent multimodal neural code for linear and angular self-motion in a posterior parietal area of the macaque brain that is connected to the hippocampal formation.

Original languageEnglish (US)
Pages (from-to)3932-3947
Number of pages16
JournalCerebral Cortex
Volume29
Issue number9
DOIs
StatePublished - Sep 1 2019

Keywords

  • angular rotation
  • electrophysiology
  • forward translation
  • multisensory representation
  • speed tuning

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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