Thalamus and claustrum control parallel layer 1 circuits in retrosplenial cortex
Ellen KW Brennan,
Izabela Jedrasiak-Cape,
Sameer Kailasa,
Sharena P Rice,
Shyam Kumar Sudhakar,
Omar J Ahmed
Affiliations
Ellen KW Brennan
Department of Psychology, University of Michigan, Ann Arbor, United States; Neuroscience Graduate Program, University of Michigan, Ann Arbor, United States
Izabela Jedrasiak-Cape
Department of Psychology, University of Michigan, Ann Arbor, United States
Department of Mathematics, University of Michigan, Ann Arbor, United States
Sharena P Rice
Department of Psychology, University of Michigan, Ann Arbor, United States; Neuroscience Graduate Program, University of Michigan, Ann Arbor, United States
Shyam Kumar Sudhakar
Department of Psychology, University of Michigan, Ann Arbor, United States
Department of Psychology, University of Michigan, Ann Arbor, United States; Neuroscience Graduate Program, University of Michigan, Ann Arbor, United States; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, United States; Kresge Hearing Research Institute, University of Michigan, Ann Arbor, United States; Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States
The granular retrosplenial cortex (RSG) is critical for both spatial and non-spatial behaviors, but the underlying neural codes remain poorly understood. Here, we use optogenetic circuit mapping in mice to reveal a double dissociation that allows parallel circuits in superficial RSG to process disparate inputs. The anterior thalamus and dorsal subiculum, sources of spatial information, strongly and selectively recruit small low-rheobase (LR) pyramidal cells in RSG. In contrast, neighboring regular-spiking (RS) cells are preferentially controlled by claustral and anterior cingulate inputs, sources of mostly non-spatial information. Precise sublaminar axonal and dendritic arborization within RSG layer 1, in particular, permits this parallel processing. Observed thalamocortical synaptic dynamics enable computational models of LR neurons to compute the speed of head rotation, despite receiving head direction inputs that do not explicitly encode speed. Thus, parallel input streams identify a distinct principal neuronal subtype ideally positioned to support spatial orientation computations in the RSG.
