Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the OpenEphys acquisition system, making it widely available for use in experiments.

PurposePeople with central field loss (CFL) lose information in the scotomatous region. Remapping is a method to modify images to present the missing information outside the scotoma. This study tested the hypothesis that remapping improves reading performance for subjects with simulated CFL.MethodsCircular central scotomas, with diameters ranging from 4° to 16°, were simulated in normally sighted subjects using an eye tracker on either a head-mounted display (HMD) (experiments 1, 2) or a traditional monitor (experiment 3). In the three experiments, reading speed was measured for groups of 7, 11, and 13 subjects with and without remapping of text.ResultsRemapping increased reading speed in all three experiments. On the traditional monitor, it increased reading speed by 34% (8°), 38% (12°), and 35% (16°). In the two HMD experiments, remapping increased reading speed only for the largest scotoma size, possibly due to latency of updating of the simulated scotoma.ConclusionsRemapping significantly increased reading speed in simulated CFL subjects. Additional testing should examine the efficacy of remapping for reading and other visual tasks for patients with advanced CFL.

Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the OpenEphys acquisition system, making it widely available for use in experiments.

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