A fundamental challenge for bioelectronics is to deliver power to miniature devices inside the body. Wires are common failure points and limit device placement. Wireless power by electromagnetic or ultrasound waves must overcome absorption by the body and impedance mismatches between air, bone, and tissue. Magnetic fields, on the other hand, suffer little absorption by the body or differences in impedance at interfaces between air, bone, and tissue. These advantages have led to magnetically-powered stimulators based on induction or magnetothermal effects. However, fundamental limitations in these power transfer technologies have prevented miniature magneticallypowered stimulators from applications in many therapies and disease models because they do not operate in clinical "high-frequency" ranges above 20 Hz. Here we show that magnetoelectric materials -applied for the first time in bioelectronics devices -enable miniature magnetically-powered neural stimulators that operate at clinically relevant high-frequencies. As an example, we show that ME neural stimulators can effectively treat the symptoms of a Parkinson's disease model in a freely behaving rodent. We also show that ME-powered devices can be miniaturized to sizes smaller than a grain of rice while maintaining effective stimulation voltages. These results suggest that ME materials are an excellent candidate for wireless power delivery that will enable miniature neural stimulators in both clinical and research applications. Wireless neural stimulators have the potential to provide less invasive, longer lasting interfaces to brain regions and peripheral nerves compared to batterypowered devices or wired stimulators. Indeed, wires are a common failure point for bioelectronic devices. Percutaneous wires present a pathway for infection 1 and implanted wires can also limit the ability of the stimulators to move with the tissue, leading to a foreign body response or loss of contact with the target tissue 2,3 . Additionally, chronic stress and strain on wires, particularly for devices in the periphery, can lead to failure in the wire itself or its connection to the stimulator 4 . In small animals like rats and mice, wires used to power neural stimulators can interfere with natural behavior, particularly when studying social interaction between multiple animals 5 .
A fundamental challenge for bioelectronics is to deliver power to miniature devices inside the body. Wires are common failure points and limit device placement. On the other hand, wireless power by electromagnetic or ultrasound waves must overcome absorption by the body and impedance mismatches between air, bone, and tissue. In contrast, magnetic fields suffer little absorption by the body or differences in impedance at interfaces between air, bone, and tissue. These advantages have led to magneticallypowered stimulators based on induction or magnetothermal effects. However, fundamental limitations in these power transfer technologies have prevented miniature magnetically-powered stimulators from applications in many therapies and disease models because they do not operate in clinical "highfrequency" ranges above 50 Hz. Here we show that magnetoelectric materials -applied in bioelectronic devices -enable miniature magnetically-powered neural stimulators that can operate up to clinically-relevant high-frequencies.As an example, we show that ME neural stimulators can effectively treat the symptoms of a hemi-Parkinson's disease model in freely behaving rodents. We further demonstrate that ME-powered devices can be miniaturized to mmsized devices, fully implanted, and wirelessly powered in freely behaving rodents. These results suggest that ME materials are an excellent candidate for wireless power delivery that will enable miniature bioelectronics for both clinical and research applications.
Transient neural activity pervades hippocampal electrophysiological activity. During more quiescent states, brief ≈100 ms periods comprising large ≈150-250 Hz oscillations known as sharp-wave ripples (SWR) which co-occur with ensemble bursts of spiking activity, are regularly found in local field potentials recorded from area CA1. SWRs and their concomitant neural activity are thought to be important for memory consolidation, recall, and memory-guided decision making. Temporallyselective manipulations of hippocampal neural activity upon online hippocampal SWR detection have been used as causal evidence of the importance of SWR for mnemonic process as evinced by behavioral and/or physiological changes. However, though this approach is becoming more wide spread, the performance trade-offs involved in building a SWR detection and disruption system have not been explored, limiting the design and interpretation of SWR detection experiments. We present an open source, plug-and-play, online ripple detection system with a detailed performance characterization. Our system has been constructed to interface with an open source software platform, Trodes, and two hardware acquisition platforms, Open Ephys and SpikeGadgets. We show that our in vivo results -approximately 80% detection latencies falling in between ≈20-66 ms with ≈2 ms closed-loop latencies while maintaining <10 false detections per minute -are dependent upon both algorithmic trade-offs and acquisition hardware. We discuss strategies to improve detection accuracy and potential limitations of online ripple disruptions. By characterizing this system in detail, we present a template for analyzing other closed-loop neural detection and perturbation systems. Thus, we anticipate our modular, open source, realtime system will facilitate a wide range of carefully-designed causal closed-loop neuroscience experiments.
No abstract
Transient neural activity pervades hippocampal electrophysiological activity. During more quiescent states, brief ≈100 ms periods comprising large ≈150-250 Hz oscillations known as sharp-wave ripples (SWR) which co-occur with ensemble bursts of spiking activity, are regularly found in local field potentials recorded from area CA1. SWRs and their concomitant neural activity are thought to be important for memory consolidation, recall, and memory-guided decision making. Temporallyselective manipulations of hippocampal neural activity upon online hippocampal SWR detection have been used as causal evidence of the importance of SWR for mnemonic process as evinced by behavioral and/or physiological changes. However, though this approach is becoming more wide spread, the performance trade-offs involved in building a SWR detection and disruption system have not been explored, limiting the design and interpretation of SWR detection experiments. We present an open source, plug-and-play, online ripple detection system with a detailed performance characterization. Our system has been constructed to interface with an open source software platform, Trodes, and two hardware acquisition platforms, Open Ephys and SpikeGadgets. We show that our in vivo results -approximately 80% detection latencies falling in between ≈20-66 ms with ≈2 ms closed-loop latencies while maintaining <10 false detections per minute -are dependent upon both algorithmic trade-offs and acquisition hardware. We discuss strategies to improve detection accuracy and potential limitations of online ripple disruptions. By characterizing this system in detail, we present a template for analyzing other closed-loop neural detection and perturbation systems. Thus, we anticipate our modular, open source, realtime system will facilitate a wide range of carefully-designed causal closed-loop neuroscience experiments.
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