Evaluation of Connexin Hemichannel Activity In Vivo.

Connexin hemichannels (Cx HCs) are hexameric structures at the cell plasma membrane, whose function as membrane transport proteins allows for the passive flow of small hydrophilic molecules and ions (≤1 kDa) between the cytosol and the extracellular environment. Activation of Cx HCs is highly dependent on pathological conditions. HC activity provokes changes in the microenvironment, inducing the dissemination of signaling molecules in both an autocrine and paracrine manner. Given the elicitation of a variety of signaling pathways, and assortment of Cx species and dispersion throughout the body, Cx HCs have been implicated in a range of processes such as cell proliferation, differentiation, cell death, and tissue modeling and remodeling. While studying the expression and localization of Cx HCs can be done using traditional laboratory techniques, such as immunoblot analysis, measuring the functionality/activity of the HCs requires a more explicit methodology and is essential for determining Cx-mediated physiological changes. The study of Cx HC function/activity has focused mainly on in vitro measurements through electrophysiological characterization or, more commonly, using HC-permeable dye uptake studies. Here, we describe the use of dye uptake to measure Cx HC activity in vivo using mechanically stimulated osteocytic Cx43 HCs with Evans blue dye as our model.

A library of electrophysiological responses in plants - a model of transversal education and open science.

Electrophysiology in plants is understudied, and, moreover, an ideal model for student inclusion at all levels of education. Here, we report on an investigation in open science, whereby scientists worked with high school students, faculty, and undergraduates from Chile, Germany, Serbia, South Korea, and the USA. The students recorded the electrophysiological signals of >15 plant species in response to a flame or tactile stimulus applied to the leaves. We observed that approximately 60% of the plants studied showed an electrophysiological response, with a delay of ~ 3-6 s after stimulus presentation. In preliminary conduction velocity experiments, we verified that observed signals are indeed biological in origin, with information transmission speeds of ~ 2-9 mm/s. Such easily replicable experiments can serve to include more investigators and students in contributing to our understanding of plant electrophysiology.

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array.

Large-scale neuronal networks and their complex distributed microcircuits are essential to generate perception, cognition, and behavior that emerge from patterns of spatiotemporal neuronal activity. These dynamic patterns emerging from functional groups of interconnected neuronal ensembles facilitate precise computations for processing and coding multiscale neural information, thereby driving higher brain functions. To probe the computational principles of neural dynamics underlying this complexity and investigate the multiscale impact of biological processes in health and disease, large-scale simultaneous recordings have become instrumental. Here, a high-density microelectrode array (HD-MEA) is employed to study two modalities of neural dynamics - hippocampal and olfactory bulb circuits from ex-vivo mouse brain slices and neuronal networks from in-vitro cell cultures of human induced pluripotent stem cells (iPSCs). The HD-MEA platform, with 4096 microelectrodes, enables non-invasive, multi-site, label-free recordings of extracellular firing patterns from thousands of neuronal ensembles simultaneously at high spatiotemporal resolution. This approach allows the characterization of several electrophysiological network-wide features, including single/-multi-unit spiking activity patterns and local field potential oscillations. To scrutinize these multidimensional neural data, we have developed several computational tools incorporating machine learning algorithms, automatic event detection and classification, graph theory, and other advanced analyses. By supplementing these computational pipelines with this platform, we provide a methodology for studying the large, multiscale, and multimodal dynamics from cell assemblies to networks. This can potentially advance our understanding of complex brain functions and cognitive processes in health and disease. Commitment to open science and insights into large-scale computational neural dynamics could enhance brain-inspired modeling, neuromorphic computing, and neural learning algorithms. Furthermore, understanding the underlying mechanisms of impaired large-scale neural computations and their interconnected microcircuit dynamics could lead to the identification of specific biomarkers, paving the way for more accurate diagnostic tools and targeted therapies for neurological disorders.

Beyond a Transmission Cable-New Technologies to Reveal the Richness in Axonal Electrophysiology.

The axon is a neuronal structure capable of processing, encoding, and transmitting information. This assessment contrasts with a limiting, but deeply rooted, perspective where the axon functions solely as a transmission cable of somatodendritic activity, sending signals in the form of stereotypical action potentials. This perspective arose, at least partially, because of the technical difficulties in probing axons: their extreme length-to-diameter ratio and intricate growth paths preclude the study of their dynamics through traditional techniques. Recent findings are challenging this view and revealing a much larger repertoire of axonal computations. Axons display complex signaling processes and structure-function relationships, which can be modulated via diverse activity-dependent mechanisms. Additionally, axons can exhibit patterns of activity that are dramatically different from those of their corresponding soma. Not surprisingly, many of these recent discoveries have been driven by novel technology developments, which allow for in vitro axon electrophysiology with unprecedented spatiotemporal resolution and signal-to-noise ratio. In this review, we outline the state-of-the-art in vitro toolset for axonal electrophysiology and summarize the recent discoveries in axon function it has enabled. We also review the increasing repertoire of microtechnologies for controlling axon guidance which, in combination with the available cutting-edge electrophysiology and imaging approaches, have the potential for more controlled and high-throughput in vitro studies. We anticipate that a larger adoption of these new technologies by the neuroscience community will drive a new era of experimental opportunities in the study of axon physiology and consequently, neuronal function.

KCNH6 channel promotes insulin exocytosis via interaction with Munc18-1 independent of electrophysiological processes.

Glucose-stimulated insulin secretion (GSIS) in pancreatic islet ß-cells primarily relies on electrophysiological processes. Previous research highlighted the regulatory role of KCNH6, a member of the Kv channel family, in governing GSIS through its influence on ß-cell electrophysiology. In this study, we unveil a novel facet of KCNH6's function concerning insulin granule exocytosis, independent of its conventional electrical role. Young mice with ß-cell-specific KCNH6 knockout (ßKO) exhibited impaired glucose tolerance and reduced insulin secretion, a phenomenon not explained by electrophysiological processes alone. Consistently, islets from KCNH6-ßKO mice exhibited reduced insulin secretion, conversely, the overexpression of KCNH6 in murine pancreatic islets significantly enhanced insulin release. Moreover, insulin granules lacking KCNH6 demonstrated compromised docking capabilities and a reduced fusion response upon glucose stimulation. Crucially, our investigation unveiled a significant interaction between KCNH6 and the SNARE protein regulator, Munc18-1, a key mediator of insulin granule exocytosis. These findings underscore the critical role of KCNH6 in the regulation of insulin secretion through its interaction with Munc18-1, providing a promising and novel avenue for enhancing our understanding of the Kv channel in diabetes mechanisms.

Cell motility: Bioelectrical control of behavior without neurons.

Single cells are capable of remarkably sophisticated, sometimes animal-like, behaviors. New work demonstrates bioelectric control of motility through the differential regulation of appendage movements in a unicellular organism that walks across surfaces using leg-like bundles of cilia.

Nicotinic Receptors in Human Chromaffin Cells: Characterization, Functional and Physical Interactions between Subtypes and Regulation.

This review summarizes our research on nicotinic acetylcholine receptors in human chromaffin cells. Limited research has been conducted in this field on human tissue, primarily due to the difficulties associated with obtaining human cells. Receptor subtypes were characterized here using molecular biology and electrophysiological patch-clamp techniques. However, the most significant aspect of this study refers to the cross-talk between the two main subtypes identified in these cells, the α7- and α3ß4* subtypes, aiming to avoid their desensitization. The article also reviews other aspects, including the regulation of their expression, function or physical interaction by choline, Ca2+, and tyrosine and serine/threonine phosphatases. Additionally, the influence of sex on their expression is also discussed.

Disease-associated nonsense and frame-shift variants resulting in the truncation of the GluN2A or GluN2B C-terminal domain decrease NMDAR surface expression and reduce potentiating effects of neurosteroids.

N-methyl-D-aspartate receptors (NMDARs) play a critical role in normal brain function, and variants in genes encoding NMDAR subunits have been described in individuals with various neuropsychiatric disorders. We have used whole-cell patch-clamp electrophysiology, fluorescence microscopy and in-silico modeling to explore the functional consequences of disease-associated nonsense and frame-shift variants resulting in the truncation of GluN2A or GluN2B C-terminal domain (CTD). This study characterizes variant NMDARs and shows their reduced surface expression and synaptic localization, altered agonist affinity, increased desensitization, and reduced probability of channel opening. We also show that naturally occurring and synthetic steroids pregnenolone sulfate and epipregnanolone butanoic acid, respectively, enhance NMDAR function in a way that is dependent on the length of the truncated CTD and, further, is steroid-specific, GluN2A/B subunit-specific, and GluN1 splice variant-specific. Adding to the previously described effects of disease-associated NMDAR variants on the receptor biogenesis and function, our results improve the understanding of the molecular consequences of NMDAR CTD truncations and provide an opportunity for the development of new therapeutic neurosteroid-based ligands.

Structural heterogeneity of the ion and lipid channel TMEM16F.

Transmembrane protein 16 F (TMEM16F) is a Ca2+-activated homodimer which functions as an ion channel and a phospholipid scramblase. Despite the availability of several TMEM16F cryogenic electron microscopy (cryo-EM) structures, the mechanism of activation and substrate translocation remains controversial, possibly due to restrictions in the accessible protein conformational space. In this study, we use atomic force microscopy under physiological conditions to reveal a range of structurally and mechanically diverse TMEM16F assemblies, characterized by variable inter-subunit dimerization interfaces and protomer orientations, which have escaped prior cryo-EM studies. Furthermore, we find that Ca2+-induced activation is associated to stepwise changes in the pore region that affect the mechanical properties of transmembrane helices TM3, TM4 and TM6. Our direct observation of membrane remodelling in response to Ca2+ binding along with additional electrophysiological analysis, relate this structural multiplicity of TMEM16F to lipid and ion permeation processes. These results thus demonstrate how conformational heterogeneity of TMEM16F directly contributes to its diverse physiological functions.

DeePhys: A machine learning-assisted platform for electrophysiological phenotyping of human neuronal networks.

Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell-derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.

Awake ripples enhance emotional memory encoding in the human brain.

Enhanced memory for emotional experiences is hypothesized to depend on amygdala-hippocampal interactions during memory consolidation. Here we show using intracranial recordings from the human amygdala and the hippocampus during an emotional memory encoding and discrimination task increased awake ripples after encoding of emotional, compared to neutrally-valenced stimuli. Further, post-encoding ripple-locked stimulus similarity is predictive of later memory discrimination. Ripple-locked stimulus similarity appears earlier in the amygdala than in hippocampus and mutual information analysis confirms amygdala influence on hippocampal activity. Finally, the joint ripple-locked stimulus similarity in the amygdala and hippocampus is predictive of correct memory discrimination. These findings provide electrophysiological evidence that post-encoding ripples enhance memory for emotional events.

Bioelectricity in dental medicine: a narrative review.

BACKGROUND: Bioelectric signals, whether exogenous or endogenous, play crucial roles in the life processes of organisms. Recently, the significance of bioelectricity in the field of dentistry is steadily gaining greater attention. OBJECTIVE: This narrative review aims to comprehensively outline the theory, physiological effects, and practical applications of bioelectricity in dental medicine and to offer insights into its potential future direction. It attempts to provide dental clinicians and researchers with an electrophysiological perspective to enhance their clinical practice or fundamental research endeavors. METHODS: An online computer search for relevant literature was performed in PubMed, Web of Science and Cochrane Library, with the keywords "bioelectricity, endogenous electric signal, electric stimulation, dental medicine." RESULTS: Eventually, 288 documents were included for review. The variance in ion concentration between the interior and exterior of the cell membrane, referred to as transmembrane potential, forms the fundamental basis of bioelectricity. Transmembrane potential has been established as an essential regulator of intercellular communication, mechanotransduction, migration, proliferation, and immune responses. Thus, exogenous electric stimulation can significantly alter cellular action by affecting transmembrane potential. In the field of dental medicine, electric stimulation has proven useful for assessing pulp condition, locating root apices, improving the properties of dental biomaterials, expediting orthodontic tooth movement, facilitating implant osteointegration, addressing maxillofacial malignancies, and managing neuromuscular dysfunction. Furthermore, the reprogramming of bioelectric signals holds promise as a means to guide organism development and intervene in disease processes. Besides, the development of high-throughput electrophysiological tools will be imperative for identifying ion channel targets and precisely modulating bioelectricity in the future. CONCLUSIONS: Bioelectricity has found application in various concepts of dental medicine but large-scale, standardized, randomized controlled clinical trials are still necessary in the future. In addition, the precise, repeatable and predictable measurement and modulation methods of bioelectric signal patterns are essential research direction.

A machine learning approach for real-time cortical state estimation.

Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.

Single threshold adaptive deep brain stimulation in Parkinson's disease depends on parameter selection, movement state and controllability of subthalamic beta activity.

BACKGROUND: Deep brain stimulation (DBS) is an invasive treatment option for patients with Parkinson's disease. Recently, adaptive DBS (aDBS) systems have been developed, which adjust stimulation timing and amplitude in real-time. However, it is unknown how changes in parameters, movement states and the controllability of subthalamic beta activity affect aDBS performance. OBJECTIVE: To characterize how parameter choice, movement state and controllability interactively affect the electrophysiological and behavioral response to single threshold aDBS. METHODS: We recorded subthalamic local field potentials in 12 patients with Parkinson's disease receiving single threshold aDBS in the acute post-operative state. We investigated changes in two aDBS parameters: the onset time and the smoothing of real-time beta power. Electrophysiological patterns and motor performance were assessed while patients were at rest and during a simple motor task. We further studied the impact of controllability on aDBS performance by comparing patients with and without beta power modulation during continuous stimulation. RESULTS: Our findings reveal that changes in the onset time control the extent of beta power suppression achievable with single threshold adaptive stimulation during rest. Behavioral data indicate that only specific parameter combinations yield a beneficial effect of single threshold aDBS. During movement, action induced beta power suppression reduces the responsivity of the closed loop algorithm. We further demonstrate that controllability of beta power is a prerequisite for effective parameter dependent modulation of subthalamic beta activity. CONCLUSION: Our results highlight the interaction between single threshold aDBS parameter selection, movement state and controllability in driving subthalamic beta activity and motor performance. By this means, we identify directions for the further development of closed-loop DBS algorithms.

Translation of an existing implantable cardiac monitoring device for measurement of gastric electrical slow-wave activity.

BACKGROUND: Despite evidence that slow-wave dysrhythmia in the stomach is associated with clinical conditions such as gastroparesis and functional dyspepsia, there is still no widely available device for long-term monitoring of gastric electrical signals. Actionable biomarkers of gastrointestinal health are critically needed, and an implantable slow-wave monitoring device could aid in the establishment of causal relationships between symptoms and gastric electrophysiology. Recent developments in the area of wireless implantable gastric monitors demonstrate potential, but additional work and validation are required before this potential can be realized. METHODS: We hypothesized that translating an existing implantable cardiac monitoring device, the Reveal LINQ™ (Medtronic), would present a more immediate solution. Following ethical approval and laparotomy in anesthetized pigs (n = 7), a Reveal LINQ was placed on the serosal surface of the stomach, immediately adjacent to a validated flexible-printed-circuit (FPC) electrical mapping array. Data were recorded for periods of 7.5 min, and the resultant signal characteristics from the FPC array and Reveal LINQ were compared. KEY RESULTS: The Reveal LINQ device recorded slow waves in 6/7 subjects with a comparable period (p = 0.69), signal-to-noise ratio (p = 0.58), and downstroke width (p = 0.98) to the FPC, but with reduced amplitude (p = 0.024). Qualitatively, the Reveal LINQ slow-wave signal lacked the prolonged repolarization phase present in the FPC signals. CONCLUSIONS & INFERENCES: These findings suggest that existing cardiac monitors may offer an efficient solution for the long-term monitoring of slow waves. Translation toward implantation now awaits.

Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states.

The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multimodal single-cell datasets enables the investigation of cell types and states heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for the exploration of excitability states of neurons based on their Action Potential (AP) waveforms. The NSS method describes the AP waveform based on a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach on two datasets of murine cortical neurons, focusing it on GABAergic neurons. The validation process involves a combination of NSS-based clustering analysis, features exploration, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. Results show that the NSS-based analysis captures neuronal excitability states that possess biological relevance independently of cell subtype. In particular, Neuronal Spike Shapes (NSS) captures, among others, a well-characterized fast-spiking excitability state, supported by both electrophysiological and transcriptomic validation. Gene Ontology Enrichment Analysis reveals voltage-gated potassium (K+) channels as specific markers of the identified NSS partitions. This finding strongly corroborates the biological relevance of NSS partitions as excitability states, as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, being directly implicated in the regulation of neuronal excitability.

From Perugino to Picasso revisited: Electrophysiological responses to faces in paintings from different art styles.

Behavioral research (Ventura, et al., 2023) suggested that pictorial representations of faces varying along a realism-distortion spectrum elicit holistic processing as natural faces. Whether holistic face neural responses are engaged similarly remains, however, underexplored. In the present study, we evaluated the neural correlates of naturalist and artistic face processing, by exploring electrophysiological responses to faces in photographs versus in four major painting styles. The N170 response to faces in photographs was indistinguishable from that elicited by faces in the renaissance art style (depicting the most realistic faces), whilst both categories elicited larger N170 than faces in other art styles (post-impressionism, expressionism, and cubism), with a gradation in brain activity. The present evidence suggest that visual processing may become finer grained the more the realistic nature of the face. Despite behavioral equivalence, the neural mechanisms for holistic processing of natural faces and faces in diverse art styles are not equivalent.

Age- and region-dependent cortical excitability in the zQ175 Huntington disease mouse model.

The neurodegenerative disorder, Huntington disease (HD), manifests as disorders of movement, cognition and mood. Although studies report abnormal corticostriatal synaptic function early in HD mouse models, less is known about cortical-cortical activity across brain regions and disease stages. Recently, we reported enhanced mesoscale spread of cortical responses to sensory stimulation in vivo at early-manifest stages of two HD mouse models. Here, we investigated cortical excitability of zQ175 HD-model mice compared to their wild-type littermates across different cell types, ages and/or cortical regions using ex vivo electrophysiology. Cortical pyramidal neurons (CPNs) in somatosensory cortex of zQ175 mice showed intrinsic hyper-excitability at 3-4 months, but hypo-excitability at early-manifest stage (8-9 months); reduced frequency of spontaneous excitatory postsynaptic currents (sEPSCs) was seen at both ages. In contrast, motor cortex CPNs in early-manifest zQ175 mice showed increased intrinsic excitability and sEPSC frequency. Large-amplitude excitatory discharges recorded from CPNs in early-manifest zQ175 mice showed increased frequency only in somatosensory cortex, suggesting the intrinsic hypo-excitability of these CPNs may be compensatory against cortical network hyper-excitability. Similarly, in early-manifest zQ175 mice, region-dependent differences were seen in fast-spiking interneurons (FSIs): somatosensory but not motor FSIs from early-manifest zQ175 mice had reduced intrinsic excitability. Moreover, CPNs showed decreased frequency of spontaneous inhibitory postsynaptic currents and increased excitatory-inhibitory (E-I) balance of evoked synaptic currents in somatosensory cortex. Aberrant large-amplitude discharges and reduced inhibitory drive may therefore underlie E-I imbalances that result in circuit changes and synaptic dysfunction in early-manifest HD.

Structural Basis of the Bivalency of the TRPV1 Agonist DkTx.

Bivalency is a prevalent natural mechanism to enhance receptor avidity. Various two-domain disulfide-rich peptides exhibiting bivalent action have been identified from animal venoms. A unique characteristic of these peptides is that they induce a pharmacological response different from that provoked by any of the constituent domains. The enhanced potency and avidity of such peptides is therefore a consequence of their domain fusion by a peptide linker. The role of the linker itself, beyond conjugation, remains unclear. Here, we investigate how the linker affects the bivalency of the capsaicin receptor (TRPV1) agonist DkTx. We recombinantly produced isotope labelled DkTx using a protein splicing approach, to solve the high-resolution solution structure of DkTx, revealing residual linker order stabilised by linker-domain interactions leading to biased domain orientations. The significance of this was studied using a combination of mutagenesis, spin relaxation studies and electrophysiology measurements. Our results reveal that disrupting the pre-organisation of the domains of DkTx is accompanied by reductions in potency and onset of avidity. Our findings support a model of pre-configured two-domain binding, in favour of the previously suggested sequential binding model. This highlights the significance of ordered elements in linker design and the natural evolution of these in bivalent toxins.