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Extracting Spatial Information
The location of a rat can be deciphered from hippocampal activity by detecting the firing of individual place-selective neurons. In contrast, the local field potential (LFP), which arises from the coherent voltage fluctuations of large hippocampal cell populations, has been hard to decode. Agarwal et al. (p. 626) worked out how to recover positional information exclusively from multiple-site LFP measurements in the rat hippocampus. The information was as precise as that derived from spiking place cells. The approach might also be applicable more generally for deciphering information from coherent population activity anywhere in the brain.
Abstract
Although neuronal spikes can be readily detected from extracellular recordings, synaptic and subthreshold activity remains undifferentiated within the local field potential (LFP). In the hippocampus, neurons discharge selectively when the rat is at certain locations, while LFPs at single anatomical sites exhibit no such place-tuning. Nonetheless, because the representation of position is sparse and distributed, we hypothesized that spatial information can be recovered from multiple-site LFP recordings. Using high-density sampling of LFP and computational methods, we show that the spatiotemporal structure of the theta rhythm can encode position as robustly as neuronal spiking populations. Because our approach exploits the rhythmicity and sparse structure of neural activity, features found in many brain regions, it is useful as a general tool for discovering distributed LFP codes.
