Functional ultrasound imaging of the human spinal cord.

Utilizing the first in-human functional ultrasound imaging (fUSI) of the spinal cord, we demonstrate the integration of spinal functional responses to electrical stimulation. We record and characterize the hemodynamic responses of the spinal cord to a neuromodulatory intervention commonly used for treating pain and increasingly used for the restoration of sensorimotor and autonomic function. We found that the hemodynamic response to stimulation reflects a spatiotemporal modulation of the spinal cord circuitry not previously recognized. Our analytical capability offers a mechanism to assess blood flow changes with a new level of spatial and temporal precision in vivo and demonstrates that fUSI can decode the functional state of spinal networks in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. This work is a critical step toward developing a vital technique to study spinal cord function and effects of clinical neuromodulation.

A network analysis of developing brain cultures.

We recorded electrical activity from four developing embryonic brain cultures (4-40 days in vitro) using multielectrode arrays (MEAs) with 60 embedded electrodes. Data were filtered for local field potentials (LFPs) and downsampled to 1 ms to yield a matrix of time series consisting of 60 electrode × 60 000 time samples per electrode per day per MEA. Each electrode time series was rendered stationary and nonautocorrelated by applying an ARIMA (25, 1, 1) model and taking the residuals (i.e. innovations). Two kinds of analyses were then performed. First, a pairwise crosscorrelation (CC) analysis (±25 1 ms lags) revealed systematic changes in CC with lag, day in vitro (DIV), and inter-electrode distance. Specifically, (i) positive CCs were 1.76× more prevalent and 1.44× stronger (absolute value) than negative ones, and (ii) the strength of CC increased with DIV and decreased with lag and inter-electrode distance. Second, a network equilibrium analysis was based on the instantaneous (1 ms resolution) logratio of the number of electrodes that were above or below their mean, called simultaneous departure from equilibrium, SDE. This measure possesses a major computational advantage over the pairwise crosscorrelation approach because it is very simple and fast to calculate, an important factor for the analysis of large networks. The results obtained with SDE covaried highly with CC over DIV, which further validates the usefulness of this measure as a computationally effective tool for large scale network analysis.