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2020 Volume 36 Issue 12
Detection of Neuronal Activity in the Hippocampus of Sleep Deprived Rats Using Microelectrode Arrays
2020, 36(12): 190703
doi: 10.3866/PKU.WHXB201907033
Abstract:
Sleep deprivation (SD) is the partial or complete loss of sleep and has long been used as a tool in sleep research to interfere with normal sleep cycles in rodents and humans. The progressively-accumulating sleep pressure induced by sleep deprivation can lead to a variety of physiological changes and even death. Compared to traditional detection methods, in vivo detection of neuronal activity using micro-electromechanical system (MEMS) technology following sleep deprivation can help fully elucidate the effects of sleep deprivation at the cellular level. Herein, a computer-controlled rotary roller was used to completely deprive rats of sleep for 14 days and 16-channel microelectrode arrays (MEAs) were fabricated and implanted into the rat hippocampus to measure neural spikes and local field potentials (LFPs) in real-time. The hippocampus is involved in learning and memory and has been the focus of intensive research aimed at understanding the function of sleep. This study was performed to measure the changes in neuronal activity in the rat hippocampus induced by sleep deprivation as well as their overall impact on the brain. After sleep deprivation, both the pyramidal- and inter-neurons showed a higher amplitude and more intense firing patterns. The fast-firing pattern of the neurons after sleep deprivation indicated elevated excitability in the prolonged awake state. In addition, the LFP of the sleep deprived rats fluctuated more frequently. The power of the LFPs in the low-frequency band (0–50 Hz) was calculated, showing increased power of the delta, theta, alpha, and beta bands after sleep deprivation, especially for the delta band (0.1–4 Hz). Generally, LFPs are generated by all types of neural activity in the neural circuit, and the changes in the low frequency band power suggested decreased arousal and increased sleep pressure induced by sleep deprivation, which could further impair brain function. This study was mainly aimed at measuring electrophysiological changes induced by sleep deprivation in the rat brain. Typically, neuronal activity changes were accompanied by the alternation of specific neurotransmitters in the brain. In the future, it will be essential to focus on measuring the concurrent change of electrophysiological and neurochemical signals to better examine the impact of sleep deprivation on brain function. ![]()
Sleep deprivation (SD) is the partial or complete loss of sleep and has long been used as a tool in sleep research to interfere with normal sleep cycles in rodents and humans. The progressively-accumulating sleep pressure induced by sleep deprivation can lead to a variety of physiological changes and even death. Compared to traditional detection methods, in vivo detection of neuronal activity using micro-electromechanical system (MEMS) technology following sleep deprivation can help fully elucidate the effects of sleep deprivation at the cellular level. Herein, a computer-controlled rotary roller was used to completely deprive rats of sleep for 14 days and 16-channel microelectrode arrays (MEAs) were fabricated and implanted into the rat hippocampus to measure neural spikes and local field potentials (LFPs) in real-time. The hippocampus is involved in learning and memory and has been the focus of intensive research aimed at understanding the function of sleep. This study was performed to measure the changes in neuronal activity in the rat hippocampus induced by sleep deprivation as well as their overall impact on the brain. After sleep deprivation, both the pyramidal- and inter-neurons showed a higher amplitude and more intense firing patterns. The fast-firing pattern of the neurons after sleep deprivation indicated elevated excitability in the prolonged awake state. In addition, the LFP of the sleep deprived rats fluctuated more frequently. The power of the LFPs in the low-frequency band (0–50 Hz) was calculated, showing increased power of the delta, theta, alpha, and beta bands after sleep deprivation, especially for the delta band (0.1–4 Hz). Generally, LFPs are generated by all types of neural activity in the neural circuit, and the changes in the low frequency band power suggested decreased arousal and increased sleep pressure induced by sleep deprivation, which could further impair brain function. This study was mainly aimed at measuring electrophysiological changes induced by sleep deprivation in the rat brain. Typically, neuronal activity changes were accompanied by the alternation of specific neurotransmitters in the brain. In the future, it will be essential to focus on measuring the concurrent change of electrophysiological and neurochemical signals to better examine the impact of sleep deprivation on brain function.
2020, 36(12): 200503
doi: 10.3866/PKU.WHXB202005033
Abstract:
Silicon-based neural probes are practical tools for recording neural cell firing. A single silicon-based needle with a width of only 70 μm, prepared using the standard complementary metal-oxide-semiconductor (CMOS) process technology, can contain thousands of electrode-recording sites. Optogenetics has made control over neuronal activity more precise. By recording the electrical activity of neurons stimulated by light, more information about brain activity can be recorded and analyzed. When yellow light or blue light is used to stimulate neurons, the photon energy is greater than the forbidden bandwidth of the silicon substrate, and the valence-band electrons are excited to the conduction band, generating electron-hole pairs. The photoinduced carrier in the silicon substrate severely disrupts the probe's signal-to-noise ratio. Decreasing the disturbance caused by light is a pragmatic way to execute recording and stimulating simultaneously. The traditional noise reduction method involves using heavily doped silicon as the substrate, reducing the carrier life by increasing the impurity concentration, and then reducing the noise of the silicon electrode under illumination. However, the heavily doped silicon substrate has more lattice defects than its lightly doped counterparts, which makes the silicon electrode fragile, and this method is not compatible with the standard CMOS process technology. On analyzing the photoinduced noise mechanism of manufacturing electrodes on lightly doped silicon substrates, we found that the inhomogeneous distribution of carriers generated by light excitation polarizes lightly doped silicon substrates. The potential caused by photoinduced polarization will affect the electrodes fabricated on it. Metalizing and grounding the lightly doped silicon substrate will effectively decrease the polarization potential. On using this method, the noise amplitude caused by the illumination can drop to 0.87% of the original value. To ensure an appropriate firing rate of neurons, the photo-stimulation frequency was chosen to be 20 Hz. Under the illumination of 1 mW·mm-2, the background noise of the electrode could be controlled below 45 μV, which meets the needs for general optogenetics applications. Modification of the lightly doped silicon substrate will meet the requirements of the neural electrode for optogenetics applications. Unlike the traditional method of reducing light-induced noise by heavily doping the entire substrate, the noise reduction method of lightly doped silicon substrate is compatible with the standard CMOS process technology. It provides a noise cancellation method for the preparation of silicon-based neural microelectrodes with dense recording sites and high channel count using standard CMOS processes. ![]()
Silicon-based neural probes are practical tools for recording neural cell firing. A single silicon-based needle with a width of only 70 μm, prepared using the standard complementary metal-oxide-semiconductor (CMOS) process technology, can contain thousands of electrode-recording sites. Optogenetics has made control over neuronal activity more precise. By recording the electrical activity of neurons stimulated by light, more information about brain activity can be recorded and analyzed. When yellow light or blue light is used to stimulate neurons, the photon energy is greater than the forbidden bandwidth of the silicon substrate, and the valence-band electrons are excited to the conduction band, generating electron-hole pairs. The photoinduced carrier in the silicon substrate severely disrupts the probe's signal-to-noise ratio. Decreasing the disturbance caused by light is a pragmatic way to execute recording and stimulating simultaneously. The traditional noise reduction method involves using heavily doped silicon as the substrate, reducing the carrier life by increasing the impurity concentration, and then reducing the noise of the silicon electrode under illumination. However, the heavily doped silicon substrate has more lattice defects than its lightly doped counterparts, which makes the silicon electrode fragile, and this method is not compatible with the standard CMOS process technology. On analyzing the photoinduced noise mechanism of manufacturing electrodes on lightly doped silicon substrates, we found that the inhomogeneous distribution of carriers generated by light excitation polarizes lightly doped silicon substrates. The potential caused by photoinduced polarization will affect the electrodes fabricated on it. Metalizing and grounding the lightly doped silicon substrate will effectively decrease the polarization potential. On using this method, the noise amplitude caused by the illumination can drop to 0.87% of the original value. To ensure an appropriate firing rate of neurons, the photo-stimulation frequency was chosen to be 20 Hz. Under the illumination of 1 mW·mm-2, the background noise of the electrode could be controlled below 45 μV, which meets the needs for general optogenetics applications. Modification of the lightly doped silicon substrate will meet the requirements of the neural electrode for optogenetics applications. Unlike the traditional method of reducing light-induced noise by heavily doping the entire substrate, the noise reduction method of lightly doped silicon substrate is compatible with the standard CMOS process technology. It provides a noise cancellation method for the preparation of silicon-based neural microelectrodes with dense recording sites and high channel count using standard CMOS processes.
2020, 36(12): 190903
doi: 10.3866/PKU.WHXB201909035
Abstract:
Neural electrodes have been extensively utilized for the investigation of neural functions and the understanding of neuronal circuits because of their high spatial and temporal resolution. However, long-term effective electrophysiological recordings in free-behaving animals still constitute a challenging task, which hinders longitudinal studies on complex brain-processing mechanisms at a functional level. Herein, we demonstrate the feasibility and advantages of using a self-spreadable octopus-like electrode (octrode) array for long-term recordings. The octrode array was fabricated by enwrapping a bundle of eight formvar-coated nickel-chromium microwires with a layer of polyethylene glycol in a custom-made mold. After the electrodeposition of platinum nanoparticles, the microwires at the electrode tip were gathered together and then re-enwrapped with a thin layer of gelatin to maintain their structure and mechanical strength for implantation. Shortly after implantation (within 20 min), the biocompatible gelatin encapsulation swelled and dissolved, causing the self-spreading of the recording channels of the octrode array in the brain. The electrochemical characteristics of the electrode/neural tissue interface were investigated by electrochemical impedance spectroscopy (EIS). Four weeks after implantation, the average impedance of the octrodes (1.26 MΩ at 1 kHz) was significantly lower than that of the conventional tetrodes (1.50 MΩ at 1 kHz, p < 0.05, t-test). Additionally, the octrodes exhibited a better pseudo-capacitive characteristic and a considerably faster ion transfer rate at the electrode interface than the tetrodes. Spontaneous action potentials and local field potentials (LFPs) were also recorded in vivo to investigate the electrophysiological performance of the octrodes. The peak-to-peak spike amplitudes recorded for the octrodes were remarkably larger than those recorded for the tetrodes. The signal quality remained at approximately the same level for the four-week period, while the peak-to-peak spike amplitudes recorded for the tetrodes decreased abruptly. Moreover, the voltage amplitudes recorded by the octrodes at 1–200 Hz were notably larger than those by the tetrodes, suggesting a higher sensitivity in the recording of electrophysiological events. Furthermore, we performed immunochemical analyses on the brain tissues at post-implantation to evaluate the histocompatibility of the electrodes. Tissue responses of the octrodes were alleviated considerably, evidenced by the reduced astroglial intensity and increased neuron density around the implant site as compared to the tetrodes, which may be due to the relatively small size of each decentralized recording channel after self-spreading in vivo. Generally, the fabricated octrodes exhibited a lower electrochemical impedance value at the octrode/neural tissue interface and an increased signal quality during the long-term electrophysiological recording in freely moving mice as compared to the conventional tetrodes. All of these are desirable characteristics in neural circuit dissections in vivo. ![]()
Neural electrodes have been extensively utilized for the investigation of neural functions and the understanding of neuronal circuits because of their high spatial and temporal resolution. However, long-term effective electrophysiological recordings in free-behaving animals still constitute a challenging task, which hinders longitudinal studies on complex brain-processing mechanisms at a functional level. Herein, we demonstrate the feasibility and advantages of using a self-spreadable octopus-like electrode (octrode) array for long-term recordings. The octrode array was fabricated by enwrapping a bundle of eight formvar-coated nickel-chromium microwires with a layer of polyethylene glycol in a custom-made mold. After the electrodeposition of platinum nanoparticles, the microwires at the electrode tip were gathered together and then re-enwrapped with a thin layer of gelatin to maintain their structure and mechanical strength for implantation. Shortly after implantation (within 20 min), the biocompatible gelatin encapsulation swelled and dissolved, causing the self-spreading of the recording channels of the octrode array in the brain. The electrochemical characteristics of the electrode/neural tissue interface were investigated by electrochemical impedance spectroscopy (EIS). Four weeks after implantation, the average impedance of the octrodes (1.26 MΩ at 1 kHz) was significantly lower than that of the conventional tetrodes (1.50 MΩ at 1 kHz, p < 0.05, t-test). Additionally, the octrodes exhibited a better pseudo-capacitive characteristic and a considerably faster ion transfer rate at the electrode interface than the tetrodes. Spontaneous action potentials and local field potentials (LFPs) were also recorded in vivo to investigate the electrophysiological performance of the octrodes. The peak-to-peak spike amplitudes recorded for the octrodes were remarkably larger than those recorded for the tetrodes. The signal quality remained at approximately the same level for the four-week period, while the peak-to-peak spike amplitudes recorded for the tetrodes decreased abruptly. Moreover, the voltage amplitudes recorded by the octrodes at 1–200 Hz were notably larger than those by the tetrodes, suggesting a higher sensitivity in the recording of electrophysiological events. Furthermore, we performed immunochemical analyses on the brain tissues at post-implantation to evaluate the histocompatibility of the electrodes. Tissue responses of the octrodes were alleviated considerably, evidenced by the reduced astroglial intensity and increased neuron density around the implant site as compared to the tetrodes, which may be due to the relatively small size of each decentralized recording channel after self-spreading in vivo. Generally, the fabricated octrodes exhibited a lower electrochemical impedance value at the octrode/neural tissue interface and an increased signal quality during the long-term electrophysiological recording in freely moving mice as compared to the conventional tetrodes. All of these are desirable characteristics in neural circuit dissections in vivo.
2020, 36(12): 191205
doi: 10.3866/PKU.WHXB201912054
Abstract:
Optogenetics transforms specific types of neurons through genetic engineering to achieve the cell membrane expression of photosensitive channel protein. When a specific wavelength of light irradiates the photosensitive channel protein, the cell is either excited or inhibited. Optogenetics provides a precise and fast method to control the activity of individual neurons for neuroscience research, which has gained increasing attention as a means of neural regulation. To realize the photogenetic regulation of neurons, light should be introduced into the brain safely and efficiently. Thus, specialized photoelectric devices are needed. Optrode plays a significant role in the application of optogenetics tools, which is the technical basis for the application of optogenetics. Optrode is a kind of implantable neural interface device. It can introduce light into the brain to regulate neural activity and record the changes of neural electrical signals under the control of lights. As the research of optogenetic technology continues, More and more optrodes are being developed and applied in the study of neuroscience and diseases, such as neural circuit, cognition and memory, epilepsy, and sensory function damage. The combination of optrode with optogenetic technologies provides various developmental modes in terms of material selection, device structure, light supply method, and integrated ways. The difficulty in fabricating optrodes lies in performing light stimulation and electrical signal recording without causing the immune rejection of the test animal and affecting its normal physiological activities simultaneously. In this study, based on structural characteristics and manufacturing process, optrodes are classified into two categories: waveguide-based and micro-light emitting diode-based. Subsequently, based on manufacturing process and light supply method, waveguide-based optrodes are further divided into optical fiber-optrode, optical waveguide-optrode based on MENS technology, and LD/LED waveguide-optrode. Similarly, micro-light emitting diode-based optrodes are divided into hard μLED optrode and soft μLED optrode. The advantages and disadvantages of different types of optrodes, as well as the evolution direction, are reviewed and summarized. Additionally, problems with existing optrodes, such as signal quality, biocompatibility, and device reliability, are discussed. Further, the ideal form of the device is presented as possessing the following characteristics: μLED and recording electrode integrated on flexible substrate, small size, high spatial resolution, high biocompatibility, wireless energy supply, wireless data transmission, etc. As optrode technologies are continuously updated, in the application of optogenetic technologies, research on brain neural circuit and functional structure will be better studied, and various nerve diseases will be gradually tamed. ![]()
Optogenetics transforms specific types of neurons through genetic engineering to achieve the cell membrane expression of photosensitive channel protein. When a specific wavelength of light irradiates the photosensitive channel protein, the cell is either excited or inhibited. Optogenetics provides a precise and fast method to control the activity of individual neurons for neuroscience research, which has gained increasing attention as a means of neural regulation. To realize the photogenetic regulation of neurons, light should be introduced into the brain safely and efficiently. Thus, specialized photoelectric devices are needed. Optrode plays a significant role in the application of optogenetics tools, which is the technical basis for the application of optogenetics. Optrode is a kind of implantable neural interface device. It can introduce light into the brain to regulate neural activity and record the changes of neural electrical signals under the control of lights. As the research of optogenetic technology continues, More and more optrodes are being developed and applied in the study of neuroscience and diseases, such as neural circuit, cognition and memory, epilepsy, and sensory function damage. The combination of optrode with optogenetic technologies provides various developmental modes in terms of material selection, device structure, light supply method, and integrated ways. The difficulty in fabricating optrodes lies in performing light stimulation and electrical signal recording without causing the immune rejection of the test animal and affecting its normal physiological activities simultaneously. In this study, based on structural characteristics and manufacturing process, optrodes are classified into two categories: waveguide-based and micro-light emitting diode-based. Subsequently, based on manufacturing process and light supply method, waveguide-based optrodes are further divided into optical fiber-optrode, optical waveguide-optrode based on MENS technology, and LD/LED waveguide-optrode. Similarly, micro-light emitting diode-based optrodes are divided into hard μLED optrode and soft μLED optrode. The advantages and disadvantages of different types of optrodes, as well as the evolution direction, are reviewed and summarized. Additionally, problems with existing optrodes, such as signal quality, biocompatibility, and device reliability, are discussed. Further, the ideal form of the device is presented as possessing the following characteristics: μLED and recording electrode integrated on flexible substrate, small size, high spatial resolution, high biocompatibility, wireless energy supply, wireless data transmission, etc. As optrode technologies are continuously updated, in the application of optogenetic technologies, research on brain neural circuit and functional structure will be better studied, and various nerve diseases will be gradually tamed.
2020, 36(12): 200301
doi: 10.3866/PKU.WHXB202003014
Abstract:
A human brain is composed of a large number of interconnected neurons forming a neural network. To study the functional mechanism of the neural network, it is necessary to record the activity of individual neurons over a large area simultaneously. Brain-computer interface (BCI) refers to the connection established between the human/animal brain and computers/other electronic devices, which enables direct interaction between the brain and external devices. It plays an important role in understanding, protecting, and simulating the brain, especially in helping patients with neurological disorders to restore their impaired motor and sensory functions. Neural electrodes are electrophysiological devices that form the core of BCI, which convert neuronal electrical signals (carried by ions) into general electrical signals (carried by electrons). They can record or interfere with the state of neural activity. The Utah Electrode Array (UEA) designed by the University of Utah is a mainstream neural electrode fabricated by bulk micromachining. Its unique three-dimensional needle-like structure enables each electrode to obtain high spatiotemporal resolution and good insulation between each other. After implantation, the tip of each electrode affects only a small group of neurons around it even allowing to record the action potential of a single neuron. The availability of a large number of electrodes, high quality of signals, and long service life has made UEA the first choice for collecting neuronal signals. Moreover, UEA is the only implantable neural electrode that can record signals in the human cerebral cortex. This article mainly serves as an introduction to the construction, manufacturing process, and functioning of UEA, with a focus on the research progress in fabricating high-density electrode arrays, wireless neural interfaces, and optrode arrays using silicon, glass, and metal as that material of construction. We also discuss the surface modification techniques that can be used to reduce the electrode impedance, minimize the rejection by brain tissue, and improve the corrosion resistance of the electrode. In addition, we summarize the clinical applications where patients can control external devices and get sensory feedback by implanting UEA. Furthermore, we discuss the challenges faced by existing electrodes such as the difficulty in increasing electrode density, poor response of integrated wireless neural interface, and the problems of biocompatibility. To achieve stability and durability of the electrode, advancements in both material science and manufacturing technology are required. We hope that this review can broaden the scope of ideas for the development of UEA. The realization of a fully implantable neural microsystem can contribute to an improved understanding of the functional mechanisms of the neural network and treatment of neurological diseases. ![]()
A human brain is composed of a large number of interconnected neurons forming a neural network. To study the functional mechanism of the neural network, it is necessary to record the activity of individual neurons over a large area simultaneously. Brain-computer interface (BCI) refers to the connection established between the human/animal brain and computers/other electronic devices, which enables direct interaction between the brain and external devices. It plays an important role in understanding, protecting, and simulating the brain, especially in helping patients with neurological disorders to restore their impaired motor and sensory functions. Neural electrodes are electrophysiological devices that form the core of BCI, which convert neuronal electrical signals (carried by ions) into general electrical signals (carried by electrons). They can record or interfere with the state of neural activity. The Utah Electrode Array (UEA) designed by the University of Utah is a mainstream neural electrode fabricated by bulk micromachining. Its unique three-dimensional needle-like structure enables each electrode to obtain high spatiotemporal resolution and good insulation between each other. After implantation, the tip of each electrode affects only a small group of neurons around it even allowing to record the action potential of a single neuron. The availability of a large number of electrodes, high quality of signals, and long service life has made UEA the first choice for collecting neuronal signals. Moreover, UEA is the only implantable neural electrode that can record signals in the human cerebral cortex. This article mainly serves as an introduction to the construction, manufacturing process, and functioning of UEA, with a focus on the research progress in fabricating high-density electrode arrays, wireless neural interfaces, and optrode arrays using silicon, glass, and metal as that material of construction. We also discuss the surface modification techniques that can be used to reduce the electrode impedance, minimize the rejection by brain tissue, and improve the corrosion resistance of the electrode. In addition, we summarize the clinical applications where patients can control external devices and get sensory feedback by implanting UEA. Furthermore, we discuss the challenges faced by existing electrodes such as the difficulty in increasing electrode density, poor response of integrated wireless neural interface, and the problems of biocompatibility. To achieve stability and durability of the electrode, advancements in both material science and manufacturing technology are required. We hope that this review can broaden the scope of ideas for the development of UEA. The realization of a fully implantable neural microsystem can contribute to an improved understanding of the functional mechanisms of the neural network and treatment of neurological diseases.
2020, 36(12): 200304
doi: 10.3866/PKU.WHXB202003042
Abstract:
Optogenetics is a neuromodulation technology that combines light control technology with genetic technology, thus allowing the selective activation and inhibition of the electrical activity in specific types of neurons with millisecond time resolution. Over the past several years, optogenetics has become a powerful tool for understanding the organization and functions of neural circuits, and it holds great promise to treat neurological disorders. To date, the excitation wavelengths of commonly employed opsins in optogenetics are located in the visible spectrum. This poses a serious limitation for neural activity regulation because the intense absorption and scattering of visible light by tissues lead to the loss of excitation light energy and also cause tissue heating. To regulate the activity of neurons in deep brain regions, it is necessary to implant optical fibers or optoelectronic devices into target brain areas, which however can induce severe tissue damage. Non- or minimally-invasive remote control technologies that can manipulate neural activity have been highly desirable in neuroscience research. Upconversion nanoparticles (UCNPs) can emit light with a short wavelength and high frequency upon excitation by light with a long wavelength and low frequency. Therefore, UCNPs can convert low-frequency near-infrared (NIR) light into high-frequency visible light for the activation of light-sensitive proteins, thus indirectly realizing the NIR optogenetic system. Because NIR light has a large tissue penetration depth, UCNP-mediated optogenetics has attracted significant interest for deep-tissue neuromodulation. However, in UCNP-mediated in vivo optogenetic experiments, as the up-conversion efficiency of UCNPs is low, it is generally necessary to apply high-power NIR light to obtain up-converted fluorescence with energy high enough to activate a photosensitive protein. High-power NIR light can cause thermal damage to tissues, which seriously restricts the applications of UCNPs in optogenetic technology. Therefore, the exploration of strategies to increase the up-conversion efficiency, fluorescence intensity, and biocompatibility of UCNPs is of great significance to their wide applications in optogenetic systems. This review summarizes recent developments and challenges in UCNP-mediated optogenetics for deep-brain neuromodulation. We firstly discuss the correspondence between the parameters of UCNPs and employed opsins in optogenetic experiments, which mainly include excitation wavelengths, emission wavelengths, and luminescent lifetimes. Thereafter, we introduce the methods to enhance the conversion efficiency of UCNPs, including optimizing the structure of UCNPs and modifying the organic dyes in UCNPs. In addition, we also discuss the future opportunities in combining UCNP-mediated optogenetics with flexible microelectrode technology for the long-term detection and regulation of neural activity in the case of minimal injury. ![]()
Optogenetics is a neuromodulation technology that combines light control technology with genetic technology, thus allowing the selective activation and inhibition of the electrical activity in specific types of neurons with millisecond time resolution. Over the past several years, optogenetics has become a powerful tool for understanding the organization and functions of neural circuits, and it holds great promise to treat neurological disorders. To date, the excitation wavelengths of commonly employed opsins in optogenetics are located in the visible spectrum. This poses a serious limitation for neural activity regulation because the intense absorption and scattering of visible light by tissues lead to the loss of excitation light energy and also cause tissue heating. To regulate the activity of neurons in deep brain regions, it is necessary to implant optical fibers or optoelectronic devices into target brain areas, which however can induce severe tissue damage. Non- or minimally-invasive remote control technologies that can manipulate neural activity have been highly desirable in neuroscience research. Upconversion nanoparticles (UCNPs) can emit light with a short wavelength and high frequency upon excitation by light with a long wavelength and low frequency. Therefore, UCNPs can convert low-frequency near-infrared (NIR) light into high-frequency visible light for the activation of light-sensitive proteins, thus indirectly realizing the NIR optogenetic system. Because NIR light has a large tissue penetration depth, UCNP-mediated optogenetics has attracted significant interest for deep-tissue neuromodulation. However, in UCNP-mediated in vivo optogenetic experiments, as the up-conversion efficiency of UCNPs is low, it is generally necessary to apply high-power NIR light to obtain up-converted fluorescence with energy high enough to activate a photosensitive protein. High-power NIR light can cause thermal damage to tissues, which seriously restricts the applications of UCNPs in optogenetic technology. Therefore, the exploration of strategies to increase the up-conversion efficiency, fluorescence intensity, and biocompatibility of UCNPs is of great significance to their wide applications in optogenetic systems. This review summarizes recent developments and challenges in UCNP-mediated optogenetics for deep-brain neuromodulation. We firstly discuss the correspondence between the parameters of UCNPs and employed opsins in optogenetic experiments, which mainly include excitation wavelengths, emission wavelengths, and luminescent lifetimes. Thereafter, we introduce the methods to enhance the conversion efficiency of UCNPs, including optimizing the structure of UCNPs and modifying the organic dyes in UCNPs. In addition, we also discuss the future opportunities in combining UCNP-mediated optogenetics with flexible microelectrode technology for the long-term detection and regulation of neural activity in the case of minimal injury.
2020, 36(12): 200305
doi: 10.3866/PKU.WHXB202003050
Abstract:
Neural interfaces have contributed significantly to our understanding of brain functions as well as the development of neural prosthetics. An ideal neural interface should create a seamless and reliable link between the nervous system and external electronics for long periods of time. Implantable electronics that are capable of recording and stimulating neuronal activities have been widely applied for the study of neural circuits or the treatment of neurodegenerative diseases. However, the relatively large cross-sectional footprints of conventional electronics can cause acute tissue damage during implantation. In addition, the mechanical mismatch between conventional rigid electronics and soft brain tissue has been shown to induce chronic tissue inflammatory responses, leading to signal degradation during long-term studies. Thus, it is essential to develop new strategies to overcome these existing challenges and construct more stable neural interfaces. Owing to their unique physical and chemical properties, one-dimensional (1D) and two-dimensional (2D) nanomaterials constitute promising candidates for next-generation neural interfaces. In particular, novel electronics based on 1D and 2D nanomaterials, including carbon nanotubes (CNTs), silicon nanowires (SiNWs), and graphene (GR), have been demonstrated for neural interfaces with improved performance. This review discusses recent developments in neural interfaces enabled by 1D and 2D nanomaterials and their electronics. The ability of CNTs to promote neuronal growth and electrical activity has been proven, demonstrating the feasibility of using CNTs as conducting layers or as modifying layers for electronics. Owing to their good mechanical, electrical and biological properties, CNTs-based electronics have been demonstrated for neural recording and stimulation, neurotransmitter detection, and controlled drug release. Different from CNTs-based electronics, SiNWs-based field effect transistors (FETs) and microelectrode arrays have been successfully demonstrated for intracellular recording of action potentials through penetration into neural cells. Significantly, SiNWs FETs can detect neural activity at the level of individual axons and dendrites with a high signal-to-noise ratio. Their ability to record multiplexed intracellular signals renders SiNWs-based electronics superior to traditional intracellular recording techniques such as patch-clamp recording. Besides, SiNWs have been explored for optically controlled nongenetic neuromodulation due to their tunable electrical and optical properties. As the star of the 2D nanomaterials family, GR has been applied as biomimetic substrates for neural regeneration. Transparent GR-based electronics combining electrophysiological measurements, optogenetics, two-photon microscopy with multicellular calcium imaging have been applied for the construction of multimodal neural interfaces. Finally, we provide an overview of the challenges and future perspectives of nanomaterial-based neural interfaces. ![]()
Neural interfaces have contributed significantly to our understanding of brain functions as well as the development of neural prosthetics. An ideal neural interface should create a seamless and reliable link between the nervous system and external electronics for long periods of time. Implantable electronics that are capable of recording and stimulating neuronal activities have been widely applied for the study of neural circuits or the treatment of neurodegenerative diseases. However, the relatively large cross-sectional footprints of conventional electronics can cause acute tissue damage during implantation. In addition, the mechanical mismatch between conventional rigid electronics and soft brain tissue has been shown to induce chronic tissue inflammatory responses, leading to signal degradation during long-term studies. Thus, it is essential to develop new strategies to overcome these existing challenges and construct more stable neural interfaces. Owing to their unique physical and chemical properties, one-dimensional (1D) and two-dimensional (2D) nanomaterials constitute promising candidates for next-generation neural interfaces. In particular, novel electronics based on 1D and 2D nanomaterials, including carbon nanotubes (CNTs), silicon nanowires (SiNWs), and graphene (GR), have been demonstrated for neural interfaces with improved performance. This review discusses recent developments in neural interfaces enabled by 1D and 2D nanomaterials and their electronics. The ability of CNTs to promote neuronal growth and electrical activity has been proven, demonstrating the feasibility of using CNTs as conducting layers or as modifying layers for electronics. Owing to their good mechanical, electrical and biological properties, CNTs-based electronics have been demonstrated for neural recording and stimulation, neurotransmitter detection, and controlled drug release. Different from CNTs-based electronics, SiNWs-based field effect transistors (FETs) and microelectrode arrays have been successfully demonstrated for intracellular recording of action potentials through penetration into neural cells. Significantly, SiNWs FETs can detect neural activity at the level of individual axons and dendrites with a high signal-to-noise ratio. Their ability to record multiplexed intracellular signals renders SiNWs-based electronics superior to traditional intracellular recording techniques such as patch-clamp recording. Besides, SiNWs have been explored for optically controlled nongenetic neuromodulation due to their tunable electrical and optical properties. As the star of the 2D nanomaterials family, GR has been applied as biomimetic substrates for neural regeneration. Transparent GR-based electronics combining electrophysiological measurements, optogenetics, two-photon microscopy with multicellular calcium imaging have been applied for the construction of multimodal neural interfaces. Finally, we provide an overview of the challenges and future perspectives of nanomaterial-based neural interfaces.
2020, 36(12): 200700
doi: 10.3866/PKU.WHXB202007004
Abstract:
The human brain comprises over 100 billion neurons that communicate with each other via electrical activities called action potentials. Sensory perception, cognition, and behavior all emerge from these activities. Neuroengineering is a developing interdisciplinary field that employs knowledge from neurobiology, electrical and electronic engineering, materials science and engineering, computer science, and many others. Neuroengineering aims to develop tools for understanding the mechanism of brain function at the circuit level, and to further the development of neuromodulation strategy and neuroprosthetics for motor, sensory, and mental rehabilitation from disabilities and illnesses. For high spatial and temporal resolution interfacing with neurons in the brain, implantable multielectrode arrays (MEAs) are a key member of the family of neuroengineering devices, which are designed and fabricated for in vivo electrophysiology, deep brain stimulation, and brain-computer interfaces (BCIs). On the one hand, action potential recording from MEAs can indicate the subject's mental state and movement intentions, thus enabling the BCI technology to control external motor restoration devices such as robotic arms. On the other hand, neural stimulation electrodes can modulate abnormal neural activity and treat disorders like Parkinson's disease, epilepsy, and depression. The physical and chemical properties of the electrodes, nanofabrication of arrays, and electrode–tissue interface materials are all important research subjects in translational neuroscience studies, and the utilization of nanomaterials and nanodevices continuously improves neural electrode technologies. At present, neural interface technology is confronting numerous challenges and opportunities, especially for in vivo neural circuit analysis, neuroelectronic medicine, and functional neuromodulation. The development of neural interface devices eagerly demands super-high-density, mesoscopic recording, minimal invasion, biosignal stability, and wireless interfacing. Achievement of these next-generation neural interface technology capabilities requires collaboration between neuroscientists, neurosurgeons, material scientists, microelectronic engineers, and many others. ![]()
The human brain comprises over 100 billion neurons that communicate with each other via electrical activities called action potentials. Sensory perception, cognition, and behavior all emerge from these activities. Neuroengineering is a developing interdisciplinary field that employs knowledge from neurobiology, electrical and electronic engineering, materials science and engineering, computer science, and many others. Neuroengineering aims to develop tools for understanding the mechanism of brain function at the circuit level, and to further the development of neuromodulation strategy and neuroprosthetics for motor, sensory, and mental rehabilitation from disabilities and illnesses. For high spatial and temporal resolution interfacing with neurons in the brain, implantable multielectrode arrays (MEAs) are a key member of the family of neuroengineering devices, which are designed and fabricated for in vivo electrophysiology, deep brain stimulation, and brain-computer interfaces (BCIs). On the one hand, action potential recording from MEAs can indicate the subject's mental state and movement intentions, thus enabling the BCI technology to control external motor restoration devices such as robotic arms. On the other hand, neural stimulation electrodes can modulate abnormal neural activity and treat disorders like Parkinson's disease, epilepsy, and depression. The physical and chemical properties of the electrodes, nanofabrication of arrays, and electrode–tissue interface materials are all important research subjects in translational neuroscience studies, and the utilization of nanomaterials and nanodevices continuously improves neural electrode technologies. At present, neural interface technology is confronting numerous challenges and opportunities, especially for in vivo neural circuit analysis, neuroelectronic medicine, and functional neuromodulation. The development of neural interface devices eagerly demands super-high-density, mesoscopic recording, minimal invasion, biosignal stability, and wireless interfacing. Achievement of these next-generation neural interface technology capabilities requires collaboration between neuroscientists, neurosurgeons, material scientists, microelectronic engineers, and many others.
2020, 36(12): 200706
doi: 10.3866/PKU.WHXB202007066
Abstract:
As a powerful tool for monitoring and modulating neural activities, implantable neural electrodes constitute the basis for a wide range of applications, including fundamental studies of brain circuits and functions, treatment of various neurological diseases, and realization of brain-machine interfaces. However, conventional neural electrodes have the issue of mechanical mismatch with soft neural tissues, which can result in tissue inflammation and gliosis, thus causing degradation of function over chronic implantation. Furthermore, implantable neural electrodes, especially depth electrodes, can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. With excellent electrical, mechanical, and chemical properties, carbon-based nanomaterials, including graphene and carbon nanotubes (CNTs), have been used as materials of implantable neural electrodes in recent years. Electrodes made from graphene and CNT fibers exhibit low electrochemical impedance, benefiting from the porous microstructure of the fibers. This enables a much smaller size of neural electrode. Together with the low Young's modulus of the fibers, this small size results in very soft electrodes. Soft neural electrodes made from graphene and CNT fibers show a much-reduced inflammatory response and enable stable chronic in vivo action potential recording for 4-5 months. Combining different modalities of neural interfacing, including electrophysiological measurement, optical imaging/stimulation, and magnetic resonance imaging (MRI), could leverage the spatial and temporal resolution advantages of different techniques, thus providing new insights into how neural circuits process information. Transparent neural electrode arrays made from graphene or CNTs enable simultaneous calcium imaging through the transparent electrodes, from which concurrent electrical recording is taken, thus providing complementary cellular information in addition to high-temporal-resolution electrical recording. Transparent neural electrodes from carbon-based nanomaterials can record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Graphene and CNT-based materials were used to fabricate MRI-compatible neural electrodes with negligible artifacts under high field MRI. Simultaneous deep brain stimulation (DBS) and functional magnetic resonance imaging (fMRI) with graphene fiber electrodes in the subthalamic nucleus (STN) in Parkinsonian rats revealed robust blood oxygenation level dependent responses along the basal ganglia-thalamocortical network in a frequency-dependent manner, with responses from some regions not previously detectable. This review introduces the recent development and application of neural electrode technologies based on graphene and CNTs. We also discuss biological safety issues and challenges faced by neural electrodes made from carbon nanomaterials. The use of carbon-based nanomaterials for the fabrication of various soft and multi-modality compatible neural electrodes will provide a powerful platform for both fundamental and translational neuroscience research. ![]()
As a powerful tool for monitoring and modulating neural activities, implantable neural electrodes constitute the basis for a wide range of applications, including fundamental studies of brain circuits and functions, treatment of various neurological diseases, and realization of brain-machine interfaces. However, conventional neural electrodes have the issue of mechanical mismatch with soft neural tissues, which can result in tissue inflammation and gliosis, thus causing degradation of function over chronic implantation. Furthermore, implantable neural electrodes, especially depth electrodes, can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. With excellent electrical, mechanical, and chemical properties, carbon-based nanomaterials, including graphene and carbon nanotubes (CNTs), have been used as materials of implantable neural electrodes in recent years. Electrodes made from graphene and CNT fibers exhibit low electrochemical impedance, benefiting from the porous microstructure of the fibers. This enables a much smaller size of neural electrode. Together with the low Young's modulus of the fibers, this small size results in very soft electrodes. Soft neural electrodes made from graphene and CNT fibers show a much-reduced inflammatory response and enable stable chronic in vivo action potential recording for 4-5 months. Combining different modalities of neural interfacing, including electrophysiological measurement, optical imaging/stimulation, and magnetic resonance imaging (MRI), could leverage the spatial and temporal resolution advantages of different techniques, thus providing new insights into how neural circuits process information. Transparent neural electrode arrays made from graphene or CNTs enable simultaneous calcium imaging through the transparent electrodes, from which concurrent electrical recording is taken, thus providing complementary cellular information in addition to high-temporal-resolution electrical recording. Transparent neural electrodes from carbon-based nanomaterials can record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Graphene and CNT-based materials were used to fabricate MRI-compatible neural electrodes with negligible artifacts under high field MRI. Simultaneous deep brain stimulation (DBS) and functional magnetic resonance imaging (fMRI) with graphene fiber electrodes in the subthalamic nucleus (STN) in Parkinsonian rats revealed robust blood oxygenation level dependent responses along the basal ganglia-thalamocortical network in a frequency-dependent manner, with responses from some regions not previously detectable. This review introduces the recent development and application of neural electrode technologies based on graphene and CNTs. We also discuss biological safety issues and challenges faced by neural electrodes made from carbon nanomaterials. The use of carbon-based nanomaterials for the fabrication of various soft and multi-modality compatible neural electrodes will provide a powerful platform for both fundamental and translational neuroscience research.
2020, 36(12): 200503
doi: 10.3866/PKU.WHXB202005038
Abstract:
Nervous system injury can disrupt communications between neurons, leading to loss of basic nerve functions and even paralysis. The clinical prognosis of nervous system injury is usually poor. This adversely affects the physical and mental health of patients and their families, and causes serious economic losses to the society. Due to slow and incomplete healing, the regenerative capacity of the nervous system is limited. Despite development of various biomedical treatment options such as, stem cell transplantation, neurotrophic factors and scaffold application, it is still very difficult to achieve adequate therapeutic effects that can benefit clinical practice. It is worth noting that nervous system components are closely related to electric fields (EFs), and a fundamental property of neurons is plasticity in response to endogenous and exogenous electrical stimulations. Electrical stimulation has been applied by researchers to induce nerve repair. This review summarizes the progress in research on EFs on neurons and applications of EFs in the treatment of peripheral nerve system and central nerve system injuries, focusing on the methods and effects of electrical stimulation. Research using direct, alternating, and pulsed EFs, with various parameters, has all demonstrated its positive effects on nerve healing and motor function recovery. Research on nanogenerators (NGs), a novel electrical stimulation technology that can convert mechanical energy into electrical energy, has achieved great progress in recent years. In biomedicine, NGs can collect the mechanical energy of human motion and convert it into electrical stimulations without requiring an external power supply, which can lead to significant innovations in electrical stimulation therapy. This review also discusses the recent applications of NGs in the treatment of nervous system diseases. NGs can be used to fabricate miniature, ultra-thin, flexible, and biodegradable healthcare devices according to different application scenarios such as in vivo or in vitro. NGs have enabled specific applications in deep brain stimulation, peripheral nerve stimulation, muscle stimulation, and sensory substitution to restore nervous system function. In order to apply electrical stimulation therapy in the clinical setting and improve the quality of life of patients with neurological injuries, further research into stimulation devices and their settings and parameters is highly desirable. ![]()
Nervous system injury can disrupt communications between neurons, leading to loss of basic nerve functions and even paralysis. The clinical prognosis of nervous system injury is usually poor. This adversely affects the physical and mental health of patients and their families, and causes serious economic losses to the society. Due to slow and incomplete healing, the regenerative capacity of the nervous system is limited. Despite development of various biomedical treatment options such as, stem cell transplantation, neurotrophic factors and scaffold application, it is still very difficult to achieve adequate therapeutic effects that can benefit clinical practice. It is worth noting that nervous system components are closely related to electric fields (EFs), and a fundamental property of neurons is plasticity in response to endogenous and exogenous electrical stimulations. Electrical stimulation has been applied by researchers to induce nerve repair. This review summarizes the progress in research on EFs on neurons and applications of EFs in the treatment of peripheral nerve system and central nerve system injuries, focusing on the methods and effects of electrical stimulation. Research using direct, alternating, and pulsed EFs, with various parameters, has all demonstrated its positive effects on nerve healing and motor function recovery. Research on nanogenerators (NGs), a novel electrical stimulation technology that can convert mechanical energy into electrical energy, has achieved great progress in recent years. In biomedicine, NGs can collect the mechanical energy of human motion and convert it into electrical stimulations without requiring an external power supply, which can lead to significant innovations in electrical stimulation therapy. This review also discusses the recent applications of NGs in the treatment of nervous system diseases. NGs can be used to fabricate miniature, ultra-thin, flexible, and biodegradable healthcare devices according to different application scenarios such as in vivo or in vitro. NGs have enabled specific applications in deep brain stimulation, peripheral nerve stimulation, muscle stimulation, and sensory substitution to restore nervous system function. In order to apply electrical stimulation therapy in the clinical setting and improve the quality of life of patients with neurological injuries, further research into stimulation devices and their settings and parameters is highly desirable.
2020, 36(12): 200907
doi: 10.3866/PKU.WHXB202009078
Abstract:
2020, 36(12): 200908
doi: 10.3866/PKU.WHXB202009081
Abstract:
