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Oscillatory dynamics in cortex seem to organize into traveling waves that serve a variety of functions. Recent studies show that propofol, a widely used anesthetic, dramatically alters cortical oscillations by increasing slow-delta oscillatory power and coherence. It is not known how this affects traveling waves. We compared traveling waves across the cortex of non-human primates before, during, and after propofol-induced loss of consciousness (LOC). After LOC, traveling waves in the slow-delta (∼1 Hz) range increased, grew more organized, and traveled in different directions relative to the awake state. Higher frequency (8–30 Hz) traveling waves, by contrast, decreased, lost structure, and switched to directions where the slow-delta waves were less frequent. The results suggest that LOC may be due, in part, to increases in the strength and direction of slow-delta traveling waves that, in turn, alter and disrupt traveling waves in the higher frequencies associated with cognition.

Continuous monitoring of electroencephalogram (EEG) recordings in humans under general anesthesia (GA) has demonstrated that changes in EEG dynamics induced by an anesthetic drug are reliably associated with the altered arousal states caused by the drug. This observation suggests that an intelligent, closed-loop anesthesia delivery (CLAD) system operating in real-time could track EEG dynamics and control the infusion rate of a programmable pump to precisely maintain unconsciousness. The United States FDA acknowledges the potential benefits of such automatic physiological closed-loop control devices for patient care. Bringing these devices into clinical practice requires establishing their feasibility in suitable animal models. Therefore, given the close neurophysiological proximity between human and non-human primates (NHPs), we address this problem by developing and validating a propofol CLAD system in rhesus macaques. Our CLAD system has three key components: (1) a data acquisition system that records cortical local field potentials (LFPs) from an NHP in real-time; (2) a computer executing our CLAD algorithm that takes in the LFP signals as input and outputs infusion rates; and (3) a computer-controlled infusion pump that administers intravenous propofol. Our CLAD system controls an empirically-determined LFP marker of unconsciousness (MOU) at a user-prescribed target value by updating every 20 seconds the propofol infusion rate based on real-time processing of the LFP signal. The MOU is the instantaneous power in the 20 to 30 Hz band of the LFP spectrogram. Every cycle (duration ≈ 20 sec), our CLAD algorithm updates the MOU estimate and uses a robust optimal control strategy to adjust the propofol infusion rate based on the instantaneous error. This error is computed as the difference between the current and the user-prescribed target MOU values. Using neural recordings from multiple NHP anesthesia sessions, we first established that our chosen MOU signal was strongly correlated with propofol-induced decreased spiking activity which itself has been shown earlier to be associated with the level of unconsciousness in NHPs. Then we designed robust optimal control strategies that used subject-specific pharmacokinetic-pharmacodynamic models describing the MOU dynamics due to propofol infusion rate changes. Finally, we achieved safe and efficient closed-loop control of level of unconsciousness in 9 CLAD experiments involving 2 NHPs and 2 different 125 min long target MOU profiles with three target MOU changes within a given experiment. Our CLAD system performs stably, accurately and robustly across a total of 1125 min of closed-loop control. The CLAD performance measures, represented as median (25th percentile, 75th percentile), are 3.13 % (2.62%, 3.53%) for inaccuracy, 0.54 %(-0.31%, 0.89%) for bias, -0.02%/min (-0.06%/min, 0.00%/min) for divergence, and 3% (2.49%, 3.59%) for wobble. These performance measures were comparable or superior to previously reported CLAD performance measures from clinical studies (conducted outside USA) as well as rodent-based studies. The key innovations here are: (1) a pre-clinical NHP model for CLAD development and testing, (2) a neuroscience-informed LFP-based MOU for CLAD, (3) parsimonious, pharmacology-informed models to describe MOU dynamics under propofol infusion in rhesus macaques, (4) a novel numerical testing framework for propofol CLAD that incorporates a principled optimal robust control strategy for titrating propofol, and finally (5) experimental findings demonstrating the feasibility of stable, accurate and robust CLAD in the NHP model. Our NHP-based CLAD framework provides a principled pre-clinical research platform that can form the foundation for future clinical studies.

SUMMARYVisual working memory (WM) storage is largely independent between the left and right visual hemifields/cerebral hemispheres, yet somehow WM feels seamless. We studied how WM is integrated across hemifields by recording neural activity bilaterally from lateral prefrontal cortex. An instructed saccade during the WM delay shifted the remembered location from one hemifield to the other. Before the shift, spike rates and oscillatory power showed clear signatures of memory laterality. After the shift, the lateralization inverted, consistent with transfer of the memory trace from one hemisphere to the other. Transferred traces initially used different neural ensembles from feedforward-induced ones but they converged at the end of the delay. Around the time of transfer, synchrony between the two prefrontal hemispheres peaked in theta and beta frequencies, with a directionality consistent with memory trace transfer. This illustrates how dynamics between the two cortical hemispheres can stitch together WM traces across visual hemifields.

The specific circuit mechanisms through which anesthetics induce unconsciousness have not been completely characterized. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with the anesthetic propofol. Unconsciousness was marked by slow frequency (~1 Hz) oscillations in local field potentials, entrainment of local spiking to Up states alternating with Down states of little spiking, and decreased coherence in frequencies above 4 Hz. Thalamic stimulation “awakened” anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

We know that general anesthesia produces unconsciousness but not quite how. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with propofol. Unconsciousness was marked by slow frequency (∼1 Hz) oscillations in local field potentials, entraining local spiking to Up states alternating with Down states of little spiking, and decreased higher frequency (>4 Hz) coherence. The thalamus contributed to cortical rhythms. Its stimulation “awakened” anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness thus resulted from slow frequency hypersynchrony and loss of high-frequency dynamics, partly mediated by the thalamus, that disrupts cortical communication/integration.

Visual working memory (WM) storage is largely independent between the left and right visual hemifields/cerebral hemispheres, yet somehow WM feels seamless. We studied how WM is integrated across hemifields by recording neural activity bilaterally from lateral prefrontal cortex. An instructed saccade during the WM delay shifted the remembered location from one hemifield to the other. Before the shift, spike rates and oscillatory power showed clear signatures of memory laterality. After the shift, the lateralization inverted, consistent with transfer of the memory trace from one hemisphere to the other. Transferred traces initially used different neural ensembles from feedforward-induced ones, but they converged at the end of the delay. Around the time of transfer, synchrony between the two prefrontal hemispheres peaked in theta and beta frequencies, with a directionality consistent with memory trace transfer. This illustrates how dynamics between the two cortical hemispheres can stitch together WM traces across visual hemifields.Brincat et al. use bilateral recording to show working memories transferring between the right and left prefrontal cortex. Transferred memories engage different ensembles than feedforward-induced memory traces. Trace transfer is accompanied by directed interhemispheric theta/beta synchrony., NIMH (Grant R37MH087027), ONR (Grant MURI N00014-16-1-2832), NIGMS (Grant T32GM007753)