Sunday, November 24, 2024
11/24/2024
ABSTRACT Electrocorticography (ECoG) uses many sensors to measure mesoscale electrical potentials directly from the surface of cerebral cortex, termed cortical surface electrical potentials (CSEPs). Though ECoG has long been used clinically, newly improved fabrication procedures have enabled devices with sufficiently small electrodes to record very high-frequency, spatially localized signals. These high-frequency CSEPs may be primarily generated within a single cortical column, and thus are an ideal signal to link investigation of brain function from local micro-circuit processing to broadly distributed computations. No other current recording technology provides these signals in both humans and animal models. ECoG is thus a critical methodological bridge between basic neuroscience findings and our understanding of the human brain in health and disease. However, adoption of ECoG for basic neuroscience, and realizing its full potentials in humans, is impeded by a lack of understanding of the precise biophysical processes that generate CSEPs. We have collaborated in the design of novel ECoG devices with small electrodes. With these devices, we discovered that CSEPs include multiple distinct high-frequency (>100Hz) components, which are spatially localized to the diameter of a cortical column. Here, we propose to use direct electrophysiological monitoring and optogenetic perturbations in rats and mice, combined with biophysically detailed simulations to reveal the origins of these distinct frequency components of ECoG signals. We hypothesize that distinct CSEP components represent distinct cell types and laminar sources within a cortical column, and thus report different types of information in the local cortical network associated with these sources This research will provide understanding of the cellular and biophysical origins of cortical surface electrical potentials. By enhancing the spatial localization of sources associated with distinct CSEP components, we will increase the precision with which ECoG can be used to monitor neuronal processing. This will advance the use of ECoG in basic neuroscience for ‘columnar scale’ neurophysiology monitoring of distributed cortical processing at high temporal resolution.
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