No abstract

Cell assemblies code information in both the temporal and spatial domain. One tractable example of temporal coding is the phenomenon of phase precession. In medial entorhinal cortex, theta-phase precession is observed in spatially specific grid cells, with grid spike-times shifting to earlier phases of the extracellular theta rhythm as the animal passes through the grid field. Although the exact mechanisms underlying spatial-temporal coding remain unknown, computational work points to single-cell oscillatory activity as a biophysical mechanism capable of producing phase precession. Support for this idea comes from observed correlations between single-cell resonance and entorhinal neurons characterized by phase precession. Here, we take advantage of the absence of single-cell theta-frequency resonance in hyperpolarization-activated cyclic nucleotide-gated (HCN) 1 knockout (KO) mice to examine the relationship between intrinsic rhythmicity and phase precession. We find phase precession is highly comparable between forebrain-restricted HCN1 KO and wild-type mice. Grid fields in HCN1 KO mice display more experience-dependent asymmetry however, consistent with reports of enhanced long-term potentiation in the absence of HCN1 and raising the possibility that the loss of HCN1 improves temporal coding via the rate-phase transformation. Combined, our results clarify the role of HCN1 channels in temporal coding and constrain the number of possible mechanisms generating phase precession. © 2013 Wiley Periodicals, Inc.

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Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject’s spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject’s sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.