Simultaneous measurement of cholinergic tone and neuronal network dynamics in vivo in the rat brain using a novel choline oxidase based electrochemical biosensor

Amperometric bio-sensing of lactate and oxygen concurrently with local field potentials during status epilepticus

Epilepsy is a prevalent neurological disorder with a complex pathogenesis and unpredictable nature, presenting limited treatment options in >30 % of affected individuals. Neurometabolic abnormalities have been observed in epilepsy patients, suggesting a disruption in the coupling between neural activity and energy metabolism in the brain. In this study, we employed amperometric biosensors based on a modified carbon fiber microelectrode platform to directly and continuously measure lactate and oxygen dynamics in the brain extracellular space. These biosensors demonstrated high sensitivity, selectivity, and rapid response time, enabling in vivo measurements with high temporal and spatial resolution. In vivo recordings in the cortex of anaesthetized rats revealed rapid and multiphasic fluctuations in extracellular lactate and oxygen levels following neuronal stimulation with high potassium. Furthermore, real-time measurement of lactate and oxygen concentration dynamics concurrently with network electrical activity during status epilepticus induced by 4-aminopyridine (4-AP) demonstrated phasic changes in lactate levels that correlated with bursts of electrical activity, while tonic levels of lactate remained stable during seizures. This study highlights the complex interplay between lactate dynamics, electrical activity, and oxygen utilization in epileptic seizures.

Challenges and strategies faced in the electrochemical biosensing analysis of neurochemicals in vivo: A review

Our brain is an intricate neuromodulatory network, and various neurochemicals, including neurotransmitters, neuromodulators, gases, ions, and energy metabolites, play important roles in regulating normal brain function. Abnormal release or imbalance of these substances will lead to various diseases such as Parkinson's and Alzheimer's diseases, therefore, in situ and real-time analysis of neurochemical interactions in pathophysiological conditions is beneficial to facilitate our understanding of brain function. Implantable electrochemical biosensors are capable of monitoring neurochemical signals in real time in extracellular fluid of specific brain regions because they can provide excellent temporal and spatial resolution. However, in vivo electrochemical biosensing analysis mainly faces the following challenges: First, foreign body reactions induced by microelectrode implantation, non-specific adsorption of proteins and redox products, and aggregation of glial cells, which will cause irreversible degradation of performance such as stability and sensitivity of the microsensor and eventually lead to signal loss; Second, various neurochemicals coexist in the complex brain environment, and electroactive substances with similar formal potentials interfere with each other. Therefore, it is a great challenge to design recognition molecules and tailor functional surfaces to develop in vivo electrochemical biosensors with high selectivity. Here, we take the above challenges as a starting point and detail the basic design principles for improving in vivo stability, selectivity and sensitivity of microsensors through some specific functionalized surface strategies as case studies. At the same time, we summarize surface modification strategies for in vivo electrochemical biosensing analysis of some important neurochemicals for researchers' reference. In addition, we also focus on the electrochemical detection of low basal concentrations of neurochemicals in vivo via amperometric waveform techniques, as well as the stability and biocompatibility of reference electrodes during long-term sensing, and provide an outlook on the future direction of in vivo electrochemical neurosensing.

Carbon-Based Electrochemical Sensors for In Vivo and In Vitro Neurotransmitter Detection

As essential neurological chemical messengers, neurotransmitters play an integral role in the maintenance of normal mammalian physiology. Aberrant neurotransmitter activity is associated with a range of neurological conditions including Parkinson's disease, Alzheimer's disease, and Huntington's disease. Many studies to date have tested different approaches to detecting neurotransmitters, yet the detection of these materials within the brain, due to the complex environment of the brain and the rapid metabolism of neurotransmitters, remains challenging and an area of active research. There is a clear need for the development of novel neurotransmitter sensing technologies capable of rapidly and sensitively monitoring specific analytes within the brain without adversely impacting the local microenvironment in which they are implanted. Owing to their excellent sensitivity, portability, ease-of-use, amenability to microprocessing, and low cost, electrochemical sensors methods have been widely studied in the context of neurotransmitter monitoring. The present review, thus, surveys current progress in this research field, discussing developed electrochemical neurotransmitter sensors capable of detecting dopamine (DA), serotonin (5-HT), acetylcholine (Ach), glutamate (Glu), nitric oxide (NO), adenosine (ADO), and so on. Of these technologies, those based on carbon nanostructures-modified electrodes including carbon nanotubes (CNTs), graphene (GR), gaphdiyne (GDY), carbon nanofibers (CNFs), and derivatives thereof hold particular promise owing to their excellent biocompatibility and electrocatalytic performance. The continued development of these and related technologies is, thus, likely to lead to major advances in the clinical diagnosis of neurological diseases and the detection of novel biomarkers thereof.

Addressing the Selectivity of Enzyme Biosensors: Solutions and Perspectives

Enzymatic biosensors enjoy commercial success and are the subject of continued research efforts to widen their range of practical application. For these biosensors to reach their full potential, their selectivity challenges need to be addressed by comprehensive, solid approaches. This review discusses the status of enzymatic biosensors in achieving accurate and selective measurements via direct biocatalytic and inhibition-based detection, with a focus on electrochemical enzyme biosensors. Examples of practical solutions for tackling the activity and selectivity problems and preventing interferences from co-existing electroactive compounds in the samples are provided such as the use of permselective membranes, sentinel sensors and coupled multi-enzyme systems. The effect of activators, inhibitors or enzymatic substrates are also addressed by coupled enzymatic reactions and multi-sensor arrays combined with data interpretation via chemometrics. In addition to these more traditional approaches, the review discusses some ingenious recent approaches, detailing also on possible solutions involving the use of nanomaterials to ensuring the biosensors' selectivity. Overall, the examples presented illustrate the various tools available when developing enzyme biosensors for new applications and stress the necessity to more comprehensively investigate their selectivity and validate the biosensors versus standard analytical methods.

Phasic oxygen dynamics confounds fast choline-sensitive biosensor signals in the brain of behaving rodents

Cholinergic fast time-scale modulation of cortical physiology is critical for cognition, but direct local measurement of neuromodulators in vivo is challenging. Choline oxidase (ChOx)-based electrochemical biosensors have been used to capture fast cholinergic signals in behaving animals. However, these transients might be biased by local field potential and O₂-evoked enzymatic responses. Using a novel Tetrode-based Amperometric ChOx (TACO) sensor, we performed highly sensitive and selective simultaneous measurement of ChOx activity (COA) and O₂. In vitro and in vivo experiments, supported by mathematical modeling, revealed that non-steady-state enzyme responses to O₂ give rise to phasic COA dynamics. This mechanism accounts for most of COA transients in the hippocampus, including those following locomotion bouts and sharp-wave/ripples. Our results suggest that it is unfeasible to probe phasic cholinergic signals under most behavioral paradigms with current ChOx biosensors. This confound is generalizable to any oxidase-based biosensor, entailing rigorous controls and new biosensor designs.

Electrochemical Evaluation of a Multi-Site Clinical Depth Recording Electrode for Monitoring Cerebral Tissue Oxygen

The intracranial measurement of local cerebral tissue oxygen levels—PbtO₂—has become a useful tool for the critical care unit to investigate severe trauma and ischemia injury in patients. Our preliminary work in animal models supports the hypothesis that multi-site depth electrode recording of PbtO₂ may give surgeons and critical care providers needed information about brain viability and the capacity for better recovery. Here, we present a surface morphology characterization and an electrochemical evaluation of the analytical properties toward oxygen detection of an FDA-approved, commercially available, clinical grade depth recording electrode comprising 12 Pt recording contacts. We found that the surface of the recording sites is composed of a thin film of smooth Pt and that the electrochemical behavior evaluated by cyclic voltammetry in acidic and neutral electrolyte is typical of polycrystalline Pt surface. The smoothness of the Pt surface was further corroborated by determination of the electrochemical active surface, confirming a roughness factor of 0.9. At an optimal working potential of −0.6 V vs. Ag/AgCl, the sensor displayed suitable values of sensitivity and limit of detection for in vivo PbtO₂ measurements. Based on the reported catalytical properties of Pt toward the electroreduction reaction of O₂, we propose that these probes could be repurposed for multisite monitoring of PbtO₂ in vivo in the human brain.

Multimaterial and multifunctional neural interfaces: from surface-type and implantable electrodes to fiber-based devices

Development of neural interfaces from surface electrodes to fibers with various type, functionality, and materials.

Real-time in vivo detection techniques for neurotransmitters: a review

Functional synapses in the central nervous system depend on a chemical signal exchange process that involves neurotransmitter delivery between neurons and receptor cells in the neuro system.

Frontiers in Electrochemical Sensors for Neurotransmitter Detection: Towards Measuring Neurotransmitters as Chemical Diagnostics for Brain Disorders

It is extremely challenging to chemically diagnose disorders of the brain. There is hence great interest in designing and optimizing tools for direct detection of chemical biomarkers implicated in neurological disorders to improve diagnosis and treatment. Tools that are capable of monitoring brain chemicals, neurotransmitters in particular, need to be biocompatible, perform with high spatiotemporal resolution, and ensure high selectivity and sensitivity. Recent advances in electrochemical methods are addressing these criteria; the resulting devices demonstrate great promise for in vivo neurotransmitter detection. None of these devices are currently used for diagnostic purposes, however these cutting-edge technologies are promising more sensitive, selective, faster, and less invasive measurements. Via this review we highlight significant technical advances and in vivo studies, performed in the last 5 years, that we believe will facilitate the development of diagnostic tools for brain disorders.

Coordinated Acetylcholine Release in Prefrontal Cortex and Hippocampus Is Associated with Arousal and Reward on Distinct Timescales

Cholinergic neurotransmission throughout the neocortex and hippocampus regulates arousal, learning, and attention. However, owing to the poorly characterized timing and location of acetylcholine release, its detailed behavioral functions remain unclear. Using electrochemical biosensors chronically implanted in mice, we made continuous measurements of the spatiotemporal dynamics of acetylcholine release across multiple behavioral states. We found that tonic levels of acetylcholine release were coordinated between the prefrontal cortex and hippocampus and maximal during training on a rewarded working memory task. Tonic release also increased during REM sleep but was contingent on subsequent wakefulness. In contrast, coordinated phasic acetylcholine release occurred only during the memory task and was strongly localized to reward delivery areas without being contingent on trial outcome. These results show that coordinated acetylcholine release between the prefrontal cortex and hippocampus is associated with reward and arousal on distinct timescales, providing dual mechanisms to support learned behavior acquisition during cognitive task performance.

Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations

Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions.

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments.

NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions.

Dynamic-SERS Optophysiology: A Nanosensor for Monitoring Cell Secretion Events

We monitored metabolite secretion near living cells using a plasmonic nanosensor. The nanosensor created from borosilicate nanopipettes analogous to the patch clamp was decorated with Au nanoparticles and served as a surface-enhanced Raman scattering (SERS) substrate with addressable location. With this nanosensor, we acquired SERS locally near Madin-Darby canine kidney (MDCKII) epithelial cells, and we detected multiple metabolites, such as pyruvate, lactate, ATP, and urea simultaneously. These plasmonic nanosensors were capable of monitoring metabolites in the extracellular medium with enough sensitivity to detect an increase in metabolite concentration following the lyses of MDCKII cells with a nonionic surfactant. The plasmonic nanosensors also allowed a relative quantification of a chemical gradient for a metabolite near cells, as demonstrated with a decrease in relative lactate to pyruvate concentration further away from the MDCKII cells. This SERS optophysiology technique for the sensitive and nondestructive monitoring of extracellular metabolites near living cells is broadly applicable to different cellular and tissue models and should therefore provide a powerful tool for cellular studies.

Network burst dynamics under heterogeneous cholinergic modulation of neural firing properties and heterogeneous synaptic connectivity

The characteristics of neural network activity depend on intrinsic neural properties and synaptic connectivity in the network. In brain networks, both of these properties are critically affected by the type and levels of neuromodulators present. The expression of many of the most powerful neuromodulators, including acetylcholine (ACh), varies tonically and phasically with behavioural state, leading to dynamic, heterogeneous changes in intrinsic neural properties and synaptic connectivity properties. Namely, ACh significantly alters neural firing properties as measured by the phase response curve in a manner that has been shown to alter the propensity for network synchronization. The aim of this simulation study was to build an understanding of how heterogeneity in cholinergic modulation of neural firing properties and heterogeneity in synaptic connectivity affect the initiation and maintenance of synchronous network bursting in excitatory networks. We show that cells that display different levels of ACh modulation have differential roles in generating network activity: weakly modulated cells are necessary for burst initiation and provide synchronizing drive to the rest of the network, whereas strongly modulated cells provide the overall activity level necessary to sustain burst firing. By applying several quantitative measures of network activity, we further show that the existence of network bursting and its characteristics, such as burst duration and intraburst synchrony, are dependent on the fraction of cell types providing the synaptic connections in the network. These results suggest mechanisms underlying ACh modulation of brain oscillations and the modulation of seizure activity during sleep states.