Nanotools for neuroscience and brain activity mapping

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

Ultrasensitive Monolithic Dopamine Microsensors Employing Vertically Aligned Carbon Nanofibers

Brain-on-Chip devices, which facilitate on-chip cultures of neurons to simulate brain functions, are receiving tremendous attention from both fundamental and clinical research. Consequently, microsensors are being developed to accomplish real-time monitoring of neurotransmitters, which are the benchmarks for neuron network operation. Among these, electrochemical sensors have emerged as promising candidates for detecting a critical neurotransmitter, dopamine. However, current state-of-the-art electrochemical dopamine sensors are suffering from issues like limited sensitivity and cumbersome fabrication. Here, a novel route in monolithically microfabricating vertically aligned carbon nanofiber electrochemical dopamine microsensors is reported with an anti-blistering slow cooling process. Thanks to the microfabrication process, microsensors is created with complete insulation and large surface areas. The champion device shows extremely high sensitivity of 4.52× 104 µAµM-1·cm-2, which is two-orders-of-magnitude higher than current devices, and a highly competitive limit of detection of 0.243 nM. These remarkable figures-of-merit will open new windows for applications such as electrochemical recording from a single neuron.

Micronano Synergetic Three-Dimensional Bioelectronics: A Revolutionary Breakthrough Platform for Cardiac Electrophysiology

Cardiovascular diseases (CVDs) are the leading cause of mortality and therefore pose a significant threat to human health. Cardiac electrophysiology plays a crucial role in the investigation and treatment of CVDs, including arrhythmia. The long-term and accurate detection of electrophysiological activity in cardiomyocytes is essential for advancing cardiology and pharmacology. Regarding the electrophysiological study of cardiac cells, many micronano bioelectric devices and systems have been developed. Such bioelectronic devices possess unique geometric structures of electrodes that enhance quality of electrophysiological signal recording. Though planar multielectrode/multitransistors are widely used for simultaneous multichannel measurement of cell electrophysiological signals, their use for extracellular electrophysiological recording exhibits low signal strength and quality. However, the integration of three-dimensional (3D) multielectrode/multitransistor arrays that use advanced penetration strategies can achieve high-quality intracellular signal recording. This review provides an overview of the manufacturing, geometric structure, and penetration paradigms of 3D micronano devices, as well as their applications for precise drug screening and biomimetic disease modeling. Furthermore, this review also summarizes the current challenges and outlines future directions for the preparation and application of micronano bioelectronic devices, with an aim to promote the development of intracellular electrophysiological platforms and thereby meet the demands of emerging clinical applications.

Development of wafer-scale multifunctional nanophotonic neural probes for brain activity mapping

Optical techniques, such as optogenetic stimulation and functional fluorescence imaging, have been revolutionary for neuroscience by enabling neural circuit analysis with cell-type specificity. To probe deep brain regions, implantable light sources are crucial. Silicon photonics, commonly used for data communications, shows great promise in creating implantable devices with complex optical systems in a compact form factor compatible with high volume manufacturing practices. This article reviews recent developments of wafer-scale multifunctional nanophotonic neural probes. The probes can be realized on 200 or 300 mm wafers in commercial foundries and integrate light emitters for photostimulation, microelectrodes for electrophysiological recording, and microfluidic channels for chemical delivery and sampling. By integrating active optical devices to the probes, denser emitter arrays, enhanced on-chip biosensing, and increased ease of use may be realized. Silicon photonics technology makes possible highly versatile implantable neural probes that can transform neuroscience experiments.

Engineering Ca2+-Dependent DNA Polymerase Activity

Advancements in synthetic biology have provided new opportunities in biosensing, with applications ranging from genetic programming to diagnostics. Next generation biosensors aim to expand the number of accessible environments for measurements, increase the number of measurable phenomena, and improve the quality of the measurement. To this end, an emerging area in the field has been the integration of DNA as an information storage medium within biosensor outputs, leveraging nucleic acids to record the biosensor state over time. However, slow signal transduction steps, due to the time scales of transcription and translation, bottleneck many sensing-DNA recording approaches. DNA polymerases (DNAPs) have been proposed as a solution to the signal transduction problem by operating as both the sensor and responder, but there is presently a lack of DNAPs with functional sensitivity to many desirable target ligands. Here, we engineer components of the Pol δ replicative polymerase complex of Saccharomyces cerevisiae to sense and respond to Ca2+, a metal cofactor relevant to numerous biological phenomena. Through domain insertion and binding site grafting to Pol δ subunits, we demonstrate functional allosteric sensitivity to Ca2+. Together, this work provides an important foundation for future efforts in the development of DNAP-based biosensors.

Optical Approaches for Investigating Neuromodulation and G Protein-Coupled Receptor Signaling

Despite the fact that roughly 40% of all US Food and Drug Administration (FDA)-approved pharmacological therapeutics target G protein-coupled receptors (GPCRs), there remains a gap in our understanding of the physiologic and functional role of these receptors at the systems level. Although heterologous expression systems and in vitro assays have revealed a tremendous amount about GPCR signaling cascades, how these cascades interact across cell types, tissues, and organ systems remains obscure. Classic behavioral pharmacology experiments lack both the temporal and spatial resolution to resolve these long-standing issues. Over the past half century, there has been a concerted effort toward the development of optical tools for understanding GPCR signaling. From initial ligand uncaging approaches to more recent development of optogenetic techniques, these strategies have allowed researchers to probe longstanding questions in GPCR pharmacology both in vivo and in vitro. These tools have been employed across biologic systems and have allowed for interrogation of everything from specific intramolecular events to pharmacology at the systems level in a spatiotemporally specific manner. In this review, we present a historical perspective on the motivation behind and development of a variety of optical toolkits that have been generated to probe GPCR signaling. Here we highlight how these tools have been used in vivo to uncover the functional role of distinct populations of GPCRs and their signaling cascades at a systems level. SIGNIFICANCE STATEMENT: G protein-coupled receptors (GPCRs) remain one of the most targeted classes of proteins for pharmaceutical intervention, yet we still have a limited understanding of how their unique signaling cascades effect physiology and behavior at the systems level. In this review, we discuss a vast array of optical techniques that have been devised to probe GPCR signaling both in vitro and in vivo.

Advocating for neurodata privacy and neurotechnology regulation

The ability to record and alter brain activity by using implantable and nonimplantable neural devices, while poised to have significant scientific and clinical benefits, also raises complex ethical concerns. In this Perspective, we raise awareness of the ability of artificial intelligence algorithms and data-aggregation tools to decode and analyze data containing highly sensitive information, jeopardizing personal neuroprivacy. Voids in existing regulatory frameworks, in fact, allow unrestricted decoding and commerce of neurodata. We advocate for the implementation of proposed ethical and human rights guidelines, alongside technical options such as data encryption, differential privacy and federated learning to ensure the protection of neurodata privacy. We further encourage regulatory bodies to consider taking a position of responsibility by categorizing all brain-derived data as sensitive health data and apply existing medical regulations to all data gathered via pre-registered neural devices. Lastly, we propose that a technocratic oath may instill a deontology for neurotechnology practitioners akin to what the Hippocratic oath represents in medicine. A conscientious societal position that thoroughly rejects the misuse of neurodata would provide the moral compass for the future development of the neurotechnology field.

Protruding cantilever microelectrode array to monitor the inner electrical activity of cerebral organoids

Stem cell-derived cerebral organoids are artificially grown miniature organ-like structures mimicking embryonic brain architecture. They are composed of multiple neural cell types with 3D cell layer organization exhibiting local field potential. Measuring the extracellular electrical activity by means of conventional planar microelectrode arrays is particularly challenging due to the 3D architecture of organoids. In order to monitor the intra-organoid electrical activity of thick spheroid-shaped samples, we developed long protruding microelectrode arrays able to penetrate the inner regions of cerebral organoids to measure the local potential of neurons within the organoids. A new microfabrication process has been developed which, thanks to the relaxation of internal stresses of a stack of materials deposited over a sacrificial layer, allows one to build a protruding cantilever microelectrode array placed at the apex of beams which rise vertically, over two hundred microns. These slender beams inserted deeply into the organoids give access to the recording of local field potential from neurons buried inside the organoid. This novel device shall provide valuable tools to study neural functions in greater detail.

Diversity of dynamic voltage patterns in neuronal dendrites revealed by nanopipette electrophysiology

Dendrites and dendritic spines are the essential cellular compartments in neuronal communication, conveying information through transient voltage signals. Our understanding of these compartmentalized voltage dynamics in fine, distal neuronal dendrites remains poor due to the difficulties inherent to accessing and stably recording from such small, nanoscale cellular compartments for a sustained time. To overcome these challenges, we use nanopipettes that permit long and stable recordings directly from fine neuronal dendrites. We reveal a diversity of voltage dynamics present locally in dendrites, such as spontaneous voltage transients, bursting events and oscillating periods of silence and firing activity, all of which we characterized using segmentation analysis. Remarkably, we find that neuronal dendrites can display spontaneous hyperpolarisation events, and sustain transient hyperpolarised states. The voltage patterns were activity-dependent, with a stronger dependency on synaptic activity than on action potentials. Long-time recordings of fine dendritic protrusions show complex voltage dynamics that may represent a previously unexplored contribution to dendritic computations.

The next generation of hybrid microfluidic/integrated circuit chips: recent and upcoming advances in high-speed, high-throughput, and multifunctional lab-on-IC systems

Since the field's inception, pioneers in microfluidics have made significant progress towards realizing complete lab-on-chip systems capable of sophisticated sample analysis and processing. One avenue towards this goal has been to join forces with the related field of microelectronics, using integrated circuits (ICs) to perform on-chip actuation and sensing. While early demonstrations focused on using microfluidic-IC hybrid chips to miniaturize benchtop instruments, steady advancements in the field have enabled a new generation of devices that expand past miniaturization into high-performance applications that would not be possible without IC hybrid integration. In this review, we identify recent examples of labs-on-chip that use high-resolution, high-speed, and multifunctional electronic and photonic chips to expand the capabilities of conventional sample analysis. We focus on three particularly active areas: a) high-throughput integrated flow cytometers; b) large-scale microelectrode arrays for stimulation and multimodal sensing of cells over a wide field of view; c) high-speed biosensors for studying molecules with high temporal resolution. We also discuss recent advancements in IC technology, including on-chip data processing techniques and lens-free optics based on integrated photonics, that are poised to further advance microfluidic-IC hybrid chips.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Dual-parameter cell biosensor for real-time monitoring of effects of propionic acid on neurons

Currently, only a few small devices are capable of continuously recording the physiological states of neurons in real time. Micro-electrode arrays (MEAs) are widely used as electrophysiological technology to detect the excitability of neurons non-invasively. However, the development of miniaturized and multi-parameter MEAs capable of real-time recording remains challenging. In this study, an on-chip micro-electrode and platinum resistor array (MEPRA) biosensor was designed and fabricated to monitor both the electrical and temperature signals of cells synchronously in real time. Such on-chip sensor maintains high sensitivity and stability. The MEPRA biosensor was further used to investigate the effects of propionic acid (PA) on primary neurons. The results demonstrate that PA affects the temperature and firing frequency of primary cortical neurons in concentration-dependent manners. The changes of temperature and firing frequency work in tandem with neuronal physiological status, including neuron viability, intracellular calcium concentration, neural plasticity, and mitochondrial function. This highly biocompatible, stable, and sensitive MEPRA biosensor may provide high-precision reference information for investigating the physiological responses of neuron cells under various conditions.

Construction and analysis of functional brain network based on emotional electroencephalogram

Networks play an important role in studying structure or functional connection of various brain areas, and explaining mechanism of emotion. However, there is a lack of comprehensive analysis among different construction methods nowadays. Therefore, this paper studies the impact of different emotions on connection of functional brain networks (FBNs) based on electroencephalogram (EEG). Firstly, we defined electrode node as brain area of vicinity of electrode to construct 32-node small-scale FBN. Pearson correlation coefficient (PCC) was used to construct correlation-based FBNs. Phase locking value (PLV) and phase synchronization index (PSI) were utilized to construct synchrony-based FBNs. Next, global properties and effects of emotion of different networks were compared. The difference of synchrony-based FBN concentrates in alpha band, and the number of differences is less than that of correlation-based FBN. Node properties of different small-scale FBNs have significant differences, offering a new basis for feature extraction of recognition regions in emotional FBNs. Later, we made partition of electrode nodes and 10 new brain areas were defined as regional nodes to construct 10-node large-scale FBN. Results show the impact of emotion on network clusters on the right forehead, and high valence enhances information processing efficiency of FBN by promoting connections in brain areas.

Flexible and Implantable Polyimide Aptamer-Field-Effect Transistor Biosensors

Monitoring neurochemical signaling across time scales is critical to understanding how brains encode and store information. Flexible (vs stiff) devices have been shown to improve in vivo monitoring, particularly over longer times, by reducing tissue damage and immunological responses. Here, we report our initial steps toward developing flexible and implantable neuroprobes with aptamer-field-effect transistor (FET) biosensors for neurotransmitter monitoring. A high-throughput process was developed to fabricate thin, flexible polyimide probes using microelectromechanical-system (MEMS) technologies, where 150 flexible probes were fabricated on each 4 in. Si wafer. Probes were 150 μm wide and 7 μm thick with two FETs per tip. The bending stiffness was 1.2 × 10^-11 N·m². Semiconductor thin films (3 nm In₂O₃) were functionalized with DNA aptamers for target recognition, which produces aptamer conformational rearrangements detected via changes in FET conductance. Flexible aptamer-FET neuroprobes detected serotonin at femtomolar concentrations in high-ionic strength artificial cerebrospinal fluid. A straightforward implantation process was developed, where microfabricated Si carrier devices assisted with implantation such that flexible neuroprobes detected physiological relevant serotonin in a tissue-hydrogel brain mimic.

Nano- and Microsensors for In Vivo Real-Time Electrochemical Analysis: Present and Future Perspectives

Electrochemical nano- and microsensors have been a useful tool for measuring different analytes because of their small size, sensitivity, and favorable electrochemical properties. Using such sensors, it is possible to study physiological mechanisms at the cellular, tissue, and organ levels and determine the state of health and diseases. In this review, we highlight recent advances in the application of electrochemical sensors for measuring neurotransmitters, oxygen, ascorbate, drugs, pH values, and other analytes in vivo. The evolution of electrochemical sensors is discussed, with a particular focus on the development of significant fabrication schemes. Finally, we highlight the extensive applications of electrochemical sensors in medicine and biological science.

Epitaxial Self-Assembly of Interfaces of 2D Metal-Organic Frameworks for Electroanalytical Detection of Neurotransmitters

This paper identifies the electrochemical properties of individual facets of anisotropic layered conductive metal-organic frameworks (MOFs) based on M3(2,3,6,7,10,11-hexahydroxytriphenylene)2 (M3(HHTP)2) (M = Co, Ni). The electroanalytical advantages of each facet are then applied toward the electrochemical detection of neurochemicals. By employing epitaxially controlled deposition of M3(HHTP)2 MOFs on electrodes, the contribution of the basal plane ({001} facets) and edge sites ({100} facets) of these MOFs can be individually determined using electrochemical characterization techniques. Despite having a lower observed heterogeneous electron transfer rate constant, the {001} facets of the M3(HHTP)2 systems prove more selective and sensitive for the detection of dopamine than the {100} facets of the same MOF, with the limit of detection (LOD) of 9.9 ± 2 nM in phosphate-buffered saline and 214 ± 48 nM in a simulated cerebrospinal fluid. Langmuir isotherm studies accompanied by all-atom MD simulations suggested that the observed improvement in performance and selectivity is related to the adsorption characteristics of analytes on the basal plane versus edge sites of the MOF interfaces. This work establishes that the distinct crystallographic facets of 2D MOFs can be used to control the fundamental interactions between analyte and electrode, leading to tunable electrochemical properties by controlling their preferential orientation through self-assembly.

New Era of Electroceuticals: Clinically Driven Smart Implantable Electronic Devices Moving towards Precision Therapy

In the name of electroceuticals, bioelectronic devices have transformed and become essential for dealing with all physiological responses. This significant advancement is attributable to its interdisciplinary nature from engineering and sciences and also the progress in micro and nanotechnologies. Undoubtedly, in the future, bioelectronics would lead in such a way that diagnosing and treating patients' diseases is more efficient. In this context, we have reviewed the current advancement of implantable medical electronics (electroceuticals) with their immense potential advantages. Specifically, the article discusses pacemakers, neural stimulation, artificial retinae, and vagus nerve stimulation, their micro/nanoscale features, and material aspects as value addition. Over the past years, most researchers have only focused on the electroceuticals metamorphically transforming from a concept to a device stage to positively impact the therapeutic outcomes. Herein, the article discusses the smart implants' development challenges and opportunities, electromagnetic field effects, and their potential consequences, which will be useful for developing a reliable and qualified smart electroceutical implant for targeted clinical use. Finally, this review article highlights the importance of wirelessly supplying the necessary power and wirelessly triggering functional electronic circuits with ultra-low power consumption and multi-functional advantages such as monitoring and treating the disease in real-time.

Dense Packed Drivable Optrode Array for Precise Optical Stimulation and Neural Recording in Multiple-Brain Regions

The input-output function of neural networks is complicated due to the huge number of neurons and synapses, and some high-density implantable electrophysiology recording tools with a plane structure have been developed for neural circuit studies in recent years. However, traditional plane probes are limited by the record-only function and inability to monitor multiple-brain regions simultaneously, and the complete cognition of neural networks still has a long way away. Herein, we develop a three-dimensional (3D) high-density drivable optrode array for multiple-brain recording and precise optical stimulation simultaneously. The optrode array contains four-layer probes with 1024 microelectrodes and two thinned optical fibers assembled into a 3D-printed drivable module. The recording performance of microelectrodes is optimized by electrochemical modification, and precise implantation depth control of drivable optrodes is verified in agar. Moreover, in vivo experiments indicate neural activities from CA1 and dentate gyrus regions are monitored, and a tracking of the neuron firing for 2 weeks is achieved. The suppression of neuron firing by blue light has been realized through high-density optrodes during optogenetics experiments. With the feature of large-scale recording, optoelectronic integration, and 3D assembly, the high-density drivable optrode array possesses an important value in the research of brain diseases and neural networks.

Implantable aptamer-field-effect transistor neuroprobes for in vivo neurotransmitter monitoring

While tools for monitoring in vivo electrophysiology have been extensively developed, neurochemical recording technologies remain limited. Nevertheless, chemical communication via neurotransmitters plays central roles in brain information processing. We developed implantable aptamer–field-effect transistor (FET) neuroprobes for monitoring neurotransmitters. Neuroprobes were fabricated using high-throughput microelectromechanical system (MEMS) technologies, where 150 probes with shanks of either 150- or 50-μm widths and thicknesses were fabricated on 4-inch Si wafers. Nanoscale FETs with ultrathin (~3 to 4 nm) In₂O₃ semiconductor films were prepared using sol-gel processing. The In₂O₃ surfaces were coupled with synthetic oligonucleotide receptors (aptamers) to recognize and to detect the neurotransmitter serotonin. Aptamer-FET neuroprobes enabled femtomolar serotonin detection limits in brain tissue with minimal biofouling. Stimulated serotonin release was detected in vivo. This study opens opportunities for integrated neural activity recordings at high spatiotemporal resolution by combining these aptamer-FET sensors with other types of Si-based implantable probes to advance our understanding of brain function.

FARCI: Fast and Robust Connectome Inference

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using in silico datasets from the Neural Connectomics Challenge (NCC) and those generated using the state-of-the-art simulator of Neural Anatomy and Optimal Microscopy (NAOMi) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison with the best performing connectome inference algorithm in the NCC, Generalized Transfer Entropy (GTE), and Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP), FARCI produces more accurate networks over different network sizes, while providing significantly better computational speed and scaling.

Framework for automated sorting of neural spikes from Neuralynx-acquired tetrode recordings in freely-moving mice

BACKGROUND

Extracellular recording represents a crucial electrophysiological technique in neuroscience for studying the activity of single neurons and neuronal populations. The electrodes capture voltage traces that, with the help of analytical tools, reveal action potentials ('spikes') as well as local field potentials. The process of spike sorting is used for the extraction of action potentials generated by individual neurons. Until recently, spike sorting was performed with manual techniques, which are laborious and unreliable due to inherent operator bias. As neuroscientists add multiple electrodes to their probes, the high-density devices can record hundreds to thousands of neurons simultaneously, making the manual spike sorting process increasingly difficult. The advent of automated spike sorting software has offered a compelling solution to this issue and, in this study, we present a simple-to-execute framework for running an automated spike sorter.

METHODS

Tetrode recordings of freely-moving mice are obtained from the CA1 region of the hippocampus as they navigate a linear track. Tetrode recordings are also acquired from the prelimbic cortex, a region of the medial prefrontal cortex, while the mice are tested in a T maze. All animals are implanted with custom-designed, 3D-printed microdrives that carry 16 electrodes, which are bundled in a 4-tetrode geometry.

RESULTS

We provide an overview of a framework for analyzing single-unit data in which we have concatenated the acquisition system (Cheetah, Neuralynx) with analytical software (MATLAB) and an automated spike sorting pipeline (MountainSort). We give precise instructions on how to implement the different steps of the framework, as well as explanations of our design logic. We validate this framework by comparing manually-sorted spikes against automatically-sorted spikes, using neural recordings of the hippocampus and prelimbic cortex in freely-moving mice.

CONCLUSIONS

We have efficiently integrated the MountainSort spike sorter with Neuralynx-acquired neural recordings. Our framework is easy to implement and provides a high-throughput solution. We predict that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find our framework quite valuable as they expand their analytical footprint.

Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression

Many voltammetry methods have been developed to monitor brain extracellular dopamine levels. Fewer approaches have been successful in detecting serotonin in vivo. No voltammetric techniques are currently available to monitor both neurotransmitters simultaneously across timescales, even though they play integrated roles in modulating behavior. We provide proof-of-concept for rapid pulse voltammetry coupled with partial least squares regression (RPV-PLSR), an approach adapted from multi-electrode systems (i.e., electronic tongues) used to identify multiple components in complex environments. We exploited small differences in analyte redox profiles to select pulse steps for RPV waveforms. Using an intentionally designed pulse strategy combined with custom instrumentation and analysis software, we monitored basal and stimulated levels of dopamine and serotonin. In addition to faradaic currents, capacitive currents were important factors in analyte identification arguing against background subtraction. Compared to fast-scan cyclic voltammetry-principal components regression (FSCV-PCR), RPV-PLSR better differentiated and quantified basal and stimulated dopamine and serotonin associated with striatal recording electrode position, optical stimulation frequency, and serotonin reuptake inhibition. The RPV-PLSR approach can be generalized to other electrochemically active neurotransmitters and provides a feedback pipeline for future optimization of multi-analyte, fit-for-purpose waveforms and machine learning approaches to data analysis.

Time for NanoNeuro

The study of electronic properties of materials at the nanoscale has unveiled physical laws and generated materials such as nanoparticles, quantum dots, nanodiamonds, nanoelectrodes, and nanoprobes. Independently, large-scale public and private neuroscience programs have been launched to develop methods to measure and manipulate neural circuits in living animals and humans. Here, we review an upcoming field, NanoNeuro, defined as the intersection of nanoscience and neuroscience, that aims to develop nanoscale methods to record and stimulate neuronal activity. Because of their unique physical properties, nanomaterials have intrinsic advantages as biosensors and actuators, and they may be applicable to humans without the need for genetic modifications. Thus, nanoscience could make major methodological contributions to the future of neuroscience and, more generally, to biomedical sciences.

Integrating single-cell transcriptomics and microcircuit computer modeling

Biophysically realistic computer modeling of neuronal microcircuitry has served as a testing ground for hypotheses related to the structure and function of different brain microcircuits. Recent advances in single-cell transcriptomics provide snapshots of a neuron's molecular state and have demonstrated that cell-specific genetic markers engineer the electrophysiological properties of a neuron. Integrating these molecular details with biophysical modeling can allow unprecedented mechanistic insights. In this opinion review, we consider systems biology-based strategies involving statistical deconvolution and gene ontology to integrate the two approaches. We foresee that this integration will infer the nonlinear interactions between the transcriptomically detailed neurons in different brain states. For an initial assessment of these integrative strategies, we recommend testing them on a penetrant phenotype such as epilepsy or a basic organism model such as Caenorhabditis elegans.

Anti-fouling peptide functionalization of ultraflexible neural probes for long-term neural activity recordings in the brain

Implantable neural probes constitute an essential tool for neuronal activity recordings in basic neuroscience and also hold great promise for the development of neuroprosthesis to restore lost motor or sensory functions of the body. However, conventional neural probes are susceptible to biofouling because of their physicochemical mismatch with neural tissues, resulting in signal degradation in chronic studies. Here, we describe an ultraflexible neural probe (uFNP) with anti-fouling zwitterionic peptide modification for long-term stable neural activity recordings. The anti-fouling zwitterionic peptide consists of two parts: negatively charged glutamic acid (E) and positively charged lysine (K) formed EKEKEK (EK) head to create a hydration layer that resists protein adsorption on the microelectrodes, and a fragment of laminin formed IKVAV tail to increase the adhesion of the microelectrodes to neuronal cells. We demonstrate that EK-IKVAV modified uFNPs can allow for stable neuronal activity recordings over 16 weeks. Immunohistological studies confirm that EK-IKVAV functionalized uFNPs could induce greatly reduced neuronal cell loss. Collectively, these results suggest that the anti-fouling zwitterionic peptide functionalization of uFNPs provide a promising route to construct biocompatible and stable neural interfaces.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

Autonomous Computing Materials

Conventional materials are reaching their limits in computation, sensing, and data storage capabilities, ushered in by the end of Moore's law, myriad sensing applications, and the continuing exponential rise in worldwide data storage demand. Conventional materials are also limited by the controlled environments in which they must operate, their high energy consumption, and their limited capacity to perform simultaneous, integrated sensing, computation, and data storage and retrieval. In contrast, the human brain is capable of multimodal sensing, complex computation, and both short- and long-term data storage simultaneously, with near instantaneous rate of recall, seamless integration, and minimal energy consumption. Motivated by the brain and the need for revolutionary new computing materials, we recently proposed the data-driven materials discovery framework, autonomous computing materials. This framework aims to mimic the brain's capabilities for integrated sensing, computation, and data storage by programming excitonic, phononic, photonic, and dynamic structural nanoscale materials, without attempting to mimic the unknown implementational details of the brain. If realized, such materials would offer transformative opportunities for distributed, multimodal sensing, computation, and data storage in an integrated manner in biological and other nonconventional environments, including interfacing with biological sensors and computers such as the brain itself.

Aptamer Conformational Change Enables Serotonin Biosensing with Nanopipettes

We report artificial nanopores in the form of quartz nanopipettes with ca. 10 nm orifices functionalized with molecular recognition elements termed aptamers that reversibly recognize serotonin with high specificity and selectivity. Nanoscale confinement of ion fluxes, analyte-specific aptamer conformational changes, and related surface charge variations enable serotonin sensing. We demonstrate detection of physiologically relevant serotonin amounts in complex environments such as neurobasal media, in which neurons are cultured in vitro. In addition to sensing in physiologically relevant matrices with high sensitivity (picomolar detection limits), we interrogate the detection mechanism via complementary techniques such as quartz crystal microbalance with dissipation monitoring and electrochemical impedance spectroscopy. Moreover, we provide a novel theoretical model for structure-switching aptamer-modified nanopipette systems that supports experimental findings. Validation of specific and selective small-molecule detection, in parallel with mechanistic investigations, demonstrates the potential of conformationally changing aptamer-modified nanopipettes as rapid, label-free, and translatable nanotools for diverse biological systems.

Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

Flexible Multiplexed In2O3 Nanoribbon Aptamer-Field-Effect Transistors for Biosensing

Flexible sensors are essential for advancing implantable and wearable bioelectronics toward monitoring chemical signals within and on the body. Developing biosensors for monitoring multiple neurotransmitters in real time represents a key in vivo application that will increase understanding of information encoded in brain neurochemical fluxes. Here, arrays of devices having multiple In₂O₃ nanoribbon field-effect transistors (FETs) were fabricated on 1.4-μm-thick polyethylene terephthalate (PET) substrates using shadow mask patterning techniques. Thin PET-FET devices withstood crumpling and bending such that stable transistor performance with high mobility was maintained over >100 bending cycles. Real-time detection of the small-molecule neurotransmitters serotonin and dopamine was achieved by immobilizing recently identified high-affinity nucleic-acid aptamers on individual In₂O₃ nanoribbon devices. Limits of detection were 10 fM for serotonin and dopamine with detection ranges spanning eight orders of magnitude. Simultaneous sensing of temperature, pH, serotonin, and dopamine enabled integration of physiological and neurochemical data from individual bioelectronic devices.

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We fabricated flexible In₂O₃ nanoribbon transistors using cleanroom-free processes

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Flexible In₂O₃ transistors withstood crumpling and bending with stable performance

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Flexible aptamer biosensors detect neurotransmitters in real time

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Multiplexed sensors monitor temperature, pH, serotonin, and dopamine simultaneously

Low-cost calcium fluorometry for long-term nanoparticle studies in living cells

Calcium fluorometry is critical to determine cell homeostasis or to reveal communication patterns in neuronal networks. Recently, characterizing calcium signalling in neurons related to interactions with nanomaterials has become of interest due to its therapeutic potential. However, imaging of neuronal cell activity under stable physiological conditions can be either very expensive or limited in its long-term capability. Here, we present a low-cost, portable imaging system for long-term, fast-scale calcium fluorometry in neurons. Using the imaging system, we revealed temperature-dependent changes in long-term calcium signalling in kidney cells and primary cortical neurons. Furthermore, we introduce fast-scale monitoring of synchronous calcium activity in neuronal cultures in response to nanomaterials. Through graph network analysis, we found that calcium dynamics in neurons are temperature-dependent when exposed to chitosan-coated nanoparticles. These results give new insights into nanomaterial-interaction in living cultures and tissues based on calcium fluorometry and graph network analysis.

Employing Conductive Metal-Organic Frameworks for Voltammetric Detection of Neurochemicals

This paper describes the first implementation of an array of two-dimensional (2D) layered conductive metal-organic frameworks (MOFs) as drop-casted film electrodes that facilitate voltammetric detection of redox active neurochemicals in a multianalyte solution. The device configuration comprises a glassy carbon electrode modified with a film of conductive MOF (M₃HXTP₂; M = Ni, Cu; and X = NH, 2,3,6,7,10,11-hexaiminotriphenylene (HITP) or O, 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP)). The utility of 2D MOFs in voltammetric sensing is measured by the detection of ascorbic acid (AA), dopamine (DA), uric acid (UA), and serotonin (5-HT) in 0.1 M PBS (pH = 7.4). In particular, Ni₃HHTP₂ MOFs demonstrated nanomolar detection limits of 63 ± 11 nM for DA and 40 ± 17 nM for 5-HT through a wide concentration range (40 nM-200 μM). The applicability in biologically relevant detection was further demonstrated in simulated urine using Ni₃HHTP₂ MOFs for the detection of 5-HT with a nanomolar detection limit of 63 ± 11 nM for 5-HT through a wide concentration range (63 nM-200 μM) in the presence of a constant background of DA. The implementation of conductive MOFs in voltammetric detection holds promise for further development of highly modular, sensitive, selective, and stable electroanalytical devices.

Precision Calcium Imaging of Dense Neural Populations via a Cell-Body-Targeted Calcium Indicator

Methods for one-photon fluorescent imaging of calcium dynamics can capture the activity of hundreds of neurons across large fields of view at a low equipment complexity and cost. In contrast to two-photon methods, however, one-photon methods suffer from higher levels of crosstalk from neuropil, resulting in a decreased signal-to-noise ratio and artifactual correlations of neural activity. We address this problem by engineering cell-body-targeted variants of the fluorescent calcium indicators GCaMP6f and GCaMP7f. We screened fusions of GCaMP to natural, as well as artificial, peptides and identified fusions that localized GCaMP to within 50 μm of the cell body of neurons in mice and larval zebrafish. One-photon imaging of soma-targeted GCaMP in dense neural circuits reported fewer artifactual spikes from neuropil, an increased signal-to-noise ratio, and decreased artifactual correlation across neurons. Thus, soma-targeting of fluorescent calcium indicators facilitates usage of simple, powerful, one-photon methods for imaging neural calcium dynamics.

Coupling magnetic and plasmonic anisotropy in hybrid nanorods for mechanochromic responses

Mechanochromic response is of great importance in designing bionic robot systems and colorimetric devices. Unfortunately, compared to mimicking motions of natural creatures, fabricating mechanochromic systems with programmable colorimetric responses remains challenging. Herein, we report the development of unconventional mechanochromic films based on hybrid nanorods integrated with magnetic and plasmonic anisotropy. Magnetic-plasmonic hybrid nanorods have been synthesized through a unique space-confined seed-mediated process, which represents an open platform for preparing next-generation complex nanostructures. By coupling magnetic and plasmonic anisotropy, the plasmonic excitation of the hybrid nanorods could be collectively regulated using magnetic fields. It facilitates convenient incorporation of the hybrid nanorods into polymer films with a well-controlled orientation and enables sensitive colorimetric changes in response to linear and angular motions. The combination of unique synthesis and convenient magnetic alignment provides an advanced approach for designing programmable mechanochromic devices with the desired precision, flexibility, and scalability.

Near-Infrared Voltage Nanosensors Enable Real-Time Imaging of Neuronal Activities in Mice and Zebrafish

Optical voltage sensors with the ability to monitor neuronal activities are invaluable tools for studying information processing of the brain. However, the current genetically encoded voltage indicators usually require high-power visible light for excitation and are limited to genetically addressable model animals. Here, we report a near-infrared (NIR)-excited nongenetic voltage nanosensor that achieves stable recording of neuronal membrane potential in intact animals. The nanosensor is composed of a Förster resonance energy transfer (FRET) pair, the outer membrane-anchored upconversion nanoparticle (UCNP), and the membrane-embedded dipicrylamine (DPA). The negative charge of DPA allows membrane potential fluctuation to affect the distance between the DPA and UCNP, therefore changing the FRET efficiency. Consequently, the emission intensity of the nanosensor can report the membrane potential. Using the nanosensor, we monitor not only electrically evoked changes in the membrane potential of cultured cells but also sensory responses of neurons in intact zebrafish and brain state-modulated subthreshold activities of cortical neurons in intact mice.

Multicolor Polymeric Nanoparticle Neuronal Tracers

Deciphering the targets of axonal projections plays a pivotal role in interpreting neuronal function and pathology. Neuronal tracers are indispensable tools for uncovering the functions and interactions between different subregions of the brain. However, the selection of commercially available neuronal tracers is limited, currently comprising small molecule dyes, viruses, and a handful of synthetic nanoparticles. Here, we describe a series of polymer-based nanoparticles capable of retrograde transport along neurons in vivo in mice. These polymeric nanoparticle neuronal tracers (NNTs) are prepared with a palette of fluorescent labels. The morphologies, charges, and optical properties of NNTs are characterized by analytical methods including fluorescence microscopy, electron microscopy, and dynamic light scattering. Cytotoxicity and cellular uptake were investigated to analyze cellular interactions in vitro. Regardless of the type of fluorophore used in labeling, each tracer was of similar morphology, size, and charge and was competent for retrograde transport in vivo. The platform provides a convenient, scalable synthetic approach for nonviral tracers labeled with a range of fluorophores for in vivo neuronal projection mapping.

64-Channel Carbon Fiber Electrode Arrays for Chronic Electrophysiology

A chief goal in neuroscience is to understand how neuronal activity relates to behavior, perception, and cognition. However, monitoring neuronal activity over long periods of time is technically challenging, and limited, in part, by the invasive nature of recording tools. While electrodes allow for recording in freely-behaving animals, they tend to be bulky and stiff, causing damage to the tissue they are implanted in. One solution to this invasiveness problem may be probes that are small enough to fly under the immune system's radar. Carbon fiber (CF) electrodes are thinner and more flexible than typical metal or silicon electrodes, but the arrays described in previous reports had low channel counts and required time-consuming manual assembly. Here we report the design of an expanded-channel-count carbon fiber electrode array (CFEA) as well as a method for fast preparation of the recording sites using acid etching and electroplating with PEDOT-TFB, and demonstrate the ability of the 64-channel CFEA to record from rat visual cortex. We include designs for interfacing the system with micro-drives or flex-PCB cables for recording from multiple brain regions, as well as a facilitated method for coating CFs with the insulator Parylene-C. High-channel-count CFEAs may thus be an alternative to traditional microwire-based electrodes and a practical tool for exploring the neural code.

High-Aspect-Ratio Nanostructured Surfaces as Biological Metamaterials

Materials patterned with high-aspect-ratio nanostructures have features on similar length scales to cellular components. These surfaces are an extreme topography on the cellular level and have become useful tools for perturbing and sensing the cellular environment. Motivation comes from the ability of high-aspect-ratio nanostructures to deliver cargoes into cells and tissues, access the intracellular environment, and control cell behavior. These structures directly perturb cells' ability to sense and respond to external forces, influencing cell fate, and enabling new mechanistic studies. Through careful design of their nanoscale structure, these systems act as biological metamaterials, eliciting unusual biological responses. While predominantly used to interface eukaryotic cells, there is growing interest in nonanimal and prokaryotic cell interfacing. Both experimental and theoretical studies have attempted to develop a mechanistic understanding for the observed behaviors, predominantly focusing on the cell-nanostructure interface. This review considers how high-aspect-ratio nanostructured surfaces are used to both stimulate and sense biological systems.

Memristive synapses connect brain and silicon spiking neurons

Brain function relies on circuits of spiking neurons with synapses playing the key role of merging transmission with memory storage and processing. Electronics has made important advances to emulate neurons and synapses and brain-computer interfacing concepts that interlink brain and brain-inspired devices are beginning to materialise. We report on memristive links between brain and silicon spiking neurons that emulate transmission and plasticity properties of real synapses. A memristor paired with a metal-thin film titanium oxide microelectrode connects a silicon neuron to a neuron of the rat hippocampus. Memristive plasticity accounts for modulation of connection strength, while transmission is mediated by weighted stimuli through the thin film oxide leading to responses that resemble excitatory postsynaptic potentials. The reverse brain-to-silicon link is established through a microelectrode-memristor pair. On these bases, we demonstrate a three-neuron brain-silicon network where memristive synapses undergo long-term potentiation or depression driven by neuronal firing rates.

Conducting Polymer-Based Composite Materials for Therapeutic Implantations: From Advanced Drug Delivery System to Minimally Invasive Electronics

Conducting polymer-based composites have recently becoming popular in both academic research and industrial practices due to their high conductivity, ease of process, and tunable electrical properties. The multifunctional conducting polymer-based composites demonstrated great application potential for in vivo therapeutics and implantable electronics, including drug delivery, neural interfacing, and minimally invasive electronics. In this review article, the state-of-the-art conducting polymer-based composites in the mentioned biological fields are discussed and summarized. The recent progress on the synthesis, structure, properties, and application of the conducting polymer-based composites is presented, aimed at revealing the structure-property relationship and the corresponding functional applications of the conducting polymer-based composites. Furthermore, key issues and challenges regarding the implantation performance of these composites are highlighted in this paper.

Nanosheet wrapping-assisted coverslip-free imaging for looking deeper into a tissue at high resolution

In order to achieve deep tissue imaging, a number of optical clearing agents have been developed. However, in a conventional microscopy setup, an objective lens can only be moved until it is in contact with a coverslip, which restricts the maximum focusing depth into a cleared tissue specimen. Until now, it is still a fact that the working distance of a high magnification objective lens with a high numerical aperture is always about 100 μm. In this study, a polymer thin film (also called as nanosheet) composed of fluoropolymer with a thickness of 130 nm, less than one-thousandth that of a 170 μm thick coverslip, is employed to replace the coverslip. Owing to its excellent characteristics, such as high optical transparency, mechanical robustness, chemical resistance, and water retention ability, nanosheet is uniquely capable of providing a coverslip-free imaging. By wrapping the tissue specimen with a nanosheet, an extra distance of 170 μm for the movement of objective lens is obtained. Results show an equivalently high resolution imaging can be obtained if a homogenous refractive index between immersion liquid and mounting media is adjusted. This method will facilitate a variety of imaging tasks with off-the-shelf high magnification objectives.

NeuroChaT: A toolbox to analyse the dynamics of neuronal encoding in freely-behaving rodents in vivo

There is a dearth of freely-available, standardised open source analysis tools available for the analysis of neuronal signals recorded in vivo in the freely-behaving animal. In response, we have developed a freely-available, open-source toolbox, NeuroChaT ( Neuron Characterisation Toolbox), specifically addressing this lacuna. Although we have particularly emphasised single unit analyses for spatial coding, NeuroChaT also characterises rhythmic properties of units and their dynamics associated with local field potential signals. NeuroChaT was developed using Python and facilitates a complete pipeline from automation of analysis to producing and managing publication-quality figures. Additionally, we have adopted a platform-independent format (Hierarchical Data Format version 5) for storing recorded and analysed data. By providing an easy-to-use software package, we aim to simplify the adoption of standardised analyses for behavioural neurophysiology and facilitate open data sharing and collaboration between laboratories.

Contemporary strategies for dissecting the neuronal basis of neurodevelopmental disorders

Great efforts in clinical and basic research have shown progress in understanding the neurobiological mechanisms of neurodevelopmental disorders, such as autism, schizophrenia, and attention-deficit hyperactive disorders. Literature on this field have suggested that these disorders are affected by the complex interaction of genetic, biological, psychosocial and environmental risk factors. However, this complexity of interplaying risk factors during neurodevelopment has prevented a complete understanding of the causes of those neuropsychiatric symptoms. Recently, with advances in modern high-resolution neuroscience methods, the neural circuitry analysis approach has provided new solutions for understanding the causal relationship between dysfunction of a neural circuit and behavioral alteration in neurodevelopmental disorders. In this review we will discuss recent progress in developing novel optogenetic and chemogenetic strategies to investigate neurodevelopmental disorders.

Nano-scale transistors for interfacing with brain: design criteria, progress and prospect

According to the World Health Organization, one quarter of the world's population suffers from various neurological disorders ranging from depression to Alzheimer's disease. Thus, understanding the operation mechanism of the brain enables us to help those who are suffering from these diseases. In addition, recent clinical medicine employs electronic brain implants, despite the fact of being invasive, to treat disorders ranging from severe coronary conditions to traumatic injuries. As a result, the deaf could hear, the blind could see, and the paralyzed could control robotic arms and legs. Due to the requirement of high data management capability with a power consumption as low as possible, designing nanoscale transistors as essential I/O electronics is a complex task. Herein, we review the essential design criteria for such nanoscale transistors, progress and prospect for implantable brain-machine-interface electronics. This article also discusses their technological challenges for practical implementation.

Fluorescent Biosensors for Neurotransmission and Neuromodulation: Engineering and Applications

Understanding how neuronal activity patterns in the brain correlate with complex behavior is one of the primary goals of modern neuroscience. Chemical transmission is the major way of communication between neurons, however, traditional methods of detection of neurotransmitter and neuromodulator transients in mammalian brain lack spatiotemporal precision. Modern fluorescent biosensors for neurotransmitters and neuromodulators allow monitoring chemical transmission in vivo with millisecond precision and single cell resolution. Changes in the fluorescent biosensor brightness occur upon neurotransmitter binding and can be detected using fiber photometry, stationary microscopy and miniaturized head-mounted microscopes. Biosensors can be expressed in the animal brain using adeno-associated viral vectors, and their cell-specific expression can be achieved with Cre-recombinase expressing animals. Although initially fluorescent biosensors for chemical transmission were represented by glutamate biosensors, nowadays biosensors for GABA, acetylcholine, glycine, norepinephrine, and dopamine are available as well. In this review, we overview functioning principles of existing intensiometric and ratiometric biosensors and provide brief insight into the variety of neurotransmitter-binding proteins from bacteria, plants, and eukaryotes including G-protein coupled receptors, which may serve as neurotransmitter-binding scaffolds. We next describe a workflow for development of neurotransmitter and neuromodulator biosensors. We then discuss advanced setups for functional imaging of neurotransmitter transients in the brain of awake freely moving animals. We conclude by providing application examples of biosensors for the studies of complex behavior with the single-neuron precision.

Nanostructure Endows Neurotherapeutic Potential in Optogenetics: Current Development and Future Prospects

Optogenetics have evolved as a promising tool to control the processes at a cellular level via photons. Specially, it confers a specific control over cellular function through real-time cytomodulation even in freely moving animals. Neuronal stimulation is prerequisite for deep tissue light penetration or insertion of optrode for light illumination to the neurons that have been proven to be compromised due to poor light penetration and invasiveness of the procedure, respectively. In this review, the application of nanotechnology is being elaborated by the use of metal nanoparticles (AuNPs), upconversion nanocrystals (UCNPs), and quantum dots (CdSe) for targeting particular organs or tissues, and their potential to emit a specific light on excitation to overcome the limitations associated with earlier methods has been elucidated. The optothermal and magnetothermal properties, photoluminescence, and higher photostability of nanomaterials are explored in context of therapeutic applicability of optogenetics. The nanostructure characteristics and specific ion channel targeting have shown promising therapeutic potential against neurodegenerative disorders (Alzheimer's, Parkinson's, Huntington's), epilepsy, and blindness. This review compiles mechanical and optical characteristics of nanomaterials that endow superior optogenetic therapeutic potentials to cure immedicable infirmities.