bioRxivNeurosciencePreprint
Directionally tuned signals in mouse visual and subicular cortex during passive rotation
Marin Dauguet, Flavia AluisiiD, Mark WexleriD, Ivan CoheniD, Jean LaurensiD, Michael GraupneriD, Desdemona FrickeriD
Abstract
Head-direction (HD) cells integrate visual and vestibular inputs and provide an internal compass which is essential for navigation, but how the directional activity in the subicular complex (SUB) and in the visual cortex (VIS) depends on the visual scene has not been compared directly. Here, we recorded simultaneously from the two regions with Neuropixels probes, while rotating head-fixed mice across all azimuthal directions, in controlled visual conditions, and in darkness. We found many directionally tuned units in both SUB and VIS. The preferred directions of SUB units were distributed uniformly and followed the rotation of a single prominent visual cue. The preferred directions of VIS units on the other hand were concentrated towards the visual cue. Heading was decoded with good accuracy from population activity from either region in cue rich visual conditions. In the presence of a single cue, decoding performance was higher in VIS. In darkness, the directional tuning was apparently lost at the single cell level, in both VIS and SUB. Importantly, even in darkness, the tuning-ordered structure of pairwise correlations was largely maintained in SUB, but not in VIS. This dissociation suggests that the SUB coherence reflects an internally organized attractor that can maintain its structure without vision or active movement, whereas VIS coherence largely reflects the external sensory structure. A wave-like distortion in decoded heading with respect to a visual cue suggests that a single salient landmark can shape the HD signal. Taken together, visual and head direction signals allow for an internal compass with continuity in the absence of landmarks, and recalibration as landmarks are reinstated.
- organism: mouse
- assay: electronic health records
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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