A low-cost, multiplexedμECoG system for high-density recordings in freely moving rodents

Abstract

Objective Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely-behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely-moving rats. Approach Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely-moving awake animals. Main results We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ~10 seconds by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials. Significance This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.

A low-cost, scalable, current-sensing digital headstage for high channel countμECoG

“…Similarly, the reconstructed voltage signal improved ESNR beyond the measured current signal ( t = 13.5, p < 0.001, paired Student’s t-test), while the reconstructed current ESNR deteriorated relative to the measured voltage ( t = −15.1, p < 0.001, paired Student’s t-test). The ESNR values of both signals were consistent with results from previous acute experiments [14]. Example best-frequency responses of sites scoring at 20th and 80th percentiles of ESNR are shown in Figure 7(a).…”

“…Once the impedance correction was applied to reconstruct a voltage signal, decoding accuracy and error were indistinguishable from the original voltage decoding ( χ 1 = 1.42, p = 0.23, LRT of logistical regressions, χ 1 = 2.34, p = 0.13, LRT of Poisson regressions, 8(b)). It should be noted that the decoding metrics of each signal met or exceeded the average accuracy of 52% and error of 0.53 octaves expected for a subdural ketamine preparation in rat auditory cortex [14]. …”

“…As ν → 0, the covariance function corresponds to spatially white noise ( C ( h ) ∝ δ ( h )) and as ν → ∞ , the covariance is Gaussian. A value of ν = 0.5 corresponds to an exponential covariance function [14, 42]. …”

“…The evoked signal-to-noise ratio (ESNR) was previously defined [14] by normalizing the square of the average best frequency MD score by the average squared self-distance of the baseline samples.…”

“…The method is described in detail in [14]. In brief, we formed feature vectors from concatenating the length- M post-tone timeseries of P responsive sites for each of N = 390 trials (13 frequencies × 30 repetitions).…”