Search

Human and mouse dorsal root ganglia (hDRG and mDRG) neurons are important tools in understanding the molecular and electrophysiological mechanisms that underlie nociception and drive pain behaviors. One of the simplest differences in firing phenotypes is that neurons are single-firing (exhibit only one action potential) or multi-firing (exhibit 2 or more action potentials). To determine if single- and multi-firing hDRG neurons exhibit differences in intrinsic properties, firing phenotypes, and AP waveform properties, and if these properties could be used to predict multi-firing, we measured 22 electrophysiological properties by whole-cell patch-clamp electrophysiology of 94 hDRG neurons from six male and four female donors. We then analyzed the data using several machine learning models to determine if these properties could be used to predict multi-firing. We used 1,000 iterations of Monte Carlo cross-validation to split the data into different train and test sets and tested the logistic regression, k -nearest neighbors, random forest, support vector classifier, and XGBoost machine learning models. All models tested had a >80% accuracy on average, with support vector classifier, and XGBoost performing the best. We found that several properties correlated with multi-firing hDRG neurons and together could be used to predict multi-firing neurons in hDRG including a long decay time, a low rheobase, and long first spike latency. We also found that the hDRG models were able to predict multi-firing with 90% accuracy in mDRG neurons. Understanding these properties could be beneficial in the elucidation of targets on peripheral sensory neurons related to pain., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Zurek et al.)

Background: The study of neurons is fundamental to unraveling the complexities of the nervous system. Primary neuronal cultures from rodents have long been a cornerstone of experimental studies, yet limitations related to their non-human nature and ethical concerns have prompted the development of alternatives. In recent years, the derivation of neurons from human-induced pluripotent stem cells (hiPSCs) has emerged as a powerful option, offering a scalable source of cells for diverse applications. Neural progenitor cells (NPCs) derived from hiPSCs can be efficiently differentiated into functional neurons, providing a platform to study human neural physiology and pathology in vitro. However, challenges persist in achieving consistent and reproducible outcomes across experimental settings., Comparison With Existing Methods: Our aim is to provide a step-by-step methodological protocol, augmenting existing procedures with additional instructions and parameters, to guide researchers in achieving reproducible results., Methods and Results: We outline procedures for the differentiation of hiPSC-derived NPCs into electrically competent neurons, encompassing initial cell density, morphology, maintenance, and differentiation. We also describe the analysis of specific markers for assessing neuronal phenotype, along with electrophysiological analysis to evaluate biophysical properties of neuronal excitability. Additionally, we conduct a comparative analysis of three different chemical methods-KCl, N-methyl-D-aspartate (NMDA), and bicuculline-to induce neuronal depolarization and assess their effects on the induction of both fast and slow post-translational, transcriptional, and post-transcriptional responses., Conclusion: Our protocol provides clear instructions for generating reliable human neuronal cultures with defined electrophysiological properties to investigate neuronal differentiation and model diseases in vitro., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The brain is an intricate system that controls a variety of functions. It consists of a vast number of cells that exhibit diverse characteristics. To understand brain function in health and disease, it is crucial to classify neurons accurately. Recent advancements in machine learning have provided a way to classify neurons based on their electrophysiological activity. This paper presents a deep-learning framework that classifies neurons solely on this basis. The framework uses data from the Allen Cell Types database, which contains a survey of biological features derived from single-cell recordings from mice and humans. The shared information from both sources is used to classify neurons into their broad types with the help of a joint model. An accurate domain-adaptive model, integrating electrophysiological data from both mice and humans, is implemented. Furthermore, data from mouse neurons, which also includes labels of transgenic mouse lines, is further classified into subtypes using an interpretable neural network model. The framework provides state-of-the-art results in terms of accuracy and precision while also providing explanations for the predictions., Competing Interests: Declarations. Competing Interest: The authors declare no competing interests., (© 2024. The Author(s).)

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer potential as an in vitro model for studying drug cardiotoxicity and patient-specific cardiovascular disease. The inherent electrophysiological heterogeneity of these cells limits the depth of insights that can be drawn from well-designed experiments. In this review, we provide our perspective on some sources and the consequences of iPSC-CM heterogeneity. We demonstrate the extent of heterogeneity in the literature and explain how such heterogeneity is exacerbated by patch-clamp experimental artifacts in the manual and automated set-up. Finally, we discuss how this heterogeneity, caused by both intrinsic and extrinsic factors, limits our ability to build digital twins of patient-derived cardiomyocytes., (© 2024 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.)

To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. Although new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe skull-shaped hemispheric implants enabling large-scale electrophysiology datasets (SHIELD). These 3D-printed skull-replacement implants feature customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedure's high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase SHIELD's scientific utility, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful, large-scale electrophysiological experiments for the study of distributed neural computation., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Morphogenetic regulation during embryogenesis and regeneration rely on information transfer and coordination between different regions. Here, we explore theoretically the coupling between bioelectrical and transcriptional oscillations at the individual cell and multicellular levels. The simulations, based on a set of ion channels and intercellular gap junctions, show that bioelectrical and transcriptional waves can electrophysiologically couple distant regions of a model network in phase and antiphase oscillatory states that include synchronization phenomena. In this way, different multicellular regionalizations can be encoded by cell potentials that oscillate between depolarized and polarized states, thus allowing a spatio-temporal coding. Because the electric potential patterns characteristic of development and regeneration are correlated with the spatial distributions of signaling ions and molecules, bioelectricity can act as a template for slow biochemical signals following a hierarchy of experimental times. In particular, bioelectrical gradients that couple cell potentials to transcription rates give to each single cell a rough idea of its location in the multicellular ensemble, thus controlling local differentiation processes that switch on and off crucial parts of the genome., Competing Interests: Declaration of competing interest M.L. is cofounder of the company Morphoceuticals Inc., which operates in the regenerative medicine and hopes to do regeneration by bioelectric technology., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Cardiac electrophysiology and mechanics are strongly interconnected. Their interaction is, among others, mediated by mechano-electric feedback through stretch-activated ion channels (SACs). The electrophysiological changes induced by SACs may contribute to arrhythmogenesis, but the precise SAC-induced electrophysiological changes remain incompletely understood. Here, we provide a systematic characterization of stretch effects through three distinguished SACs on cardiac electrophysiology using computational modelling. We implemented potassium-selective, calcium-selective and non-selective SACs in the Tomek-Rodriguez-O'Hara-Rudy model of human ventricular electrophysiology. The model was calibrated to experimental data from isolated cardiomyocytes undergoing stretch, considering inter-species differences, and disease-related remodelling of SACs. SAC-mediated effects on the action potential (AP) were analysed by varying stretch amplitude, application timing and/or duration. Afterdepolarizations of different amplitudes were observed with transient 10-ms stretch stimuli of 15-18% applied during phase 4, while stretch ≥18% during phase 4 elicited triggered APs. Longer stimuli shifted the threshold of AP trigger during phase 4 to lower amplitudes, while shorter stimuli increased it. Continuous stretch provoked electrophysiological remodelling. Furthermore, stretch shortened duration or changed morphology of a subsequent electrically evoked AP, and, if applied during a vulnerable time window with sufficient amplitude, prevented its occurrence because of stretch-induced modulation of sodium and L-type calcium channel gating. These effects were more pronounced with disease-related SAC remodelling due to increased stretch sensitivity of diseased hearts. We showed that SACs may induce afterdepolarizations and triggered activities, and prevent subsequent AP generation or change its morphology. These effects depend on cardiomyocyte stretch characteristics and disease-related SACs remodelling and may contribute to cardiac arrhythmogenesis. KEY POINTS: The interplay between cardiac electrophysiology and mechanics is mediated by mechano-electric feedback through stretch-activated ion channels (SACs). These channels may be pro-arrhythmic, but their precise effect on electrophysiology remains unclear. Here we present a systematic in silico characterization of stretch effects through three SACs by implementing inter-species differences as well as disease-related remodelling of SACs in a novel computational model of human ventricular cardiomyocyte electrophysiology. Our simulations showed that, at the cellular level, SACs may provoke electrophysiological remodelling, afterdepolarizations, triggered activities, change the morphology or shorten subsequent electrically evoked action potentials. The model further suggests that a vulnerable window exists in which stretch prevents the following electrically triggered beat occurrence. The pro-arrhythmic effects of stretch strongly depend on disease-related SAC remodelling as well as on stretch characteristics, such as amplitude, time of application and duration. Our study helps in understanding the role of stretch in cardiac arrhythmogenesis and revealing the underlying cellular mechanisms., (© 2023 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.)

Recent advances in extracellular electrophysiology now facilitate the recording of spikes from hundreds or thousands of neurons simultaneously. This has necessitated both the development of new computational methods for spike sorting and better methods to determine spike-sorting accuracy. One long-standing method of assessing the false discovery rate (FDR) of spike sorting-the rate at which spikes are assigned to the wrong cluster-has been the rate of interspike interval (ISI) violations. Despite their near ubiquitous usage in spike sorting, our understanding of how exactly ISI violations relate to FDR, as well as best practices for using ISI violations as a quality metric, remains limited. Here, we describe an analytical solution that can be used to predict FDR from the ISI violation rate (ISI v ). We test this model in silico through Monte Carlo simulation and apply it to publicly available spike-sorted electrophysiology datasets. We find that the relationship between ISI v and FDR is highly nonlinear, with additional dependencies on firing frequency, the correlation in activity between neurons, and contaminant neuron count. Predicted median FDRs in public datasets recorded in mice were found to range from 3.1 to 50.0%. We found that stochasticity in the occurrence of ISI violations as well as uncertainty in cluster-specific parameters make it difficult to predict FDR for single clusters with high confidence but that FDR can be estimated accurately across a population of clusters. Our findings will help the growing community of researchers using extracellular electrophysiology assess spike-sorting accuracy in a principled manner., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Vincent and Economo.)

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Chronic gastroduodenal symptoms disproportionately affect females of childbearing age; however, the effect of menstrual cycling on gastric electrophysiology is poorly defined. To establish the effect of the menstrual cycle on gastric electrophysiology, healthy subjects underwent noninvasive Body Surface Gastric Mapping (BSGM; 8x8 array) with the validated symptom logging App (Gastric Alimetry, New Zealand). Participants included were premenopausal females in follicular ( n = 26) and luteal phases ( n = 18) and postmenopausal females ( n = 30) and males ( n = 51) were controls. Principal gastric frequency (PGF), body mass index (BMI) adjusted amplitude, Gastric Alimetry Rhythm Index (GA-RI), Fed:Fasted Amplitude Ratio (ff-AR), meal response curves, and symptom burden were analyzed. Menstrual cycle-related electrophysiological changes were then transferred to an established anatomically accurate computational gastric fluid dynamics model (meal viscosity 0.1 Pas) to predict the impact on gastric mixing and emptying. PGF was significantly higher in the luteal versus follicular phase [mean 3.21 cpm, SD (0.17) vs. 2.94 cpm, SD (0.17), P < 0.001] and versus males [3.01 cpm, SD (0.2), P < 0.001]. In the computational model, this translated to 8.1% higher gastric mixing strength and 5.3% faster gastric emptying for luteal versus follicular phases. Postmenopausal females also exhibited higher PGF than females in the follicular phase [3.10 cpm, SD (0.24) vs. 2.94 cpm, SD (0.17), P = 0.01], and higher BMI-adjusted amplitude [40.7 µV (33.02-52.58) vs. 29.6 µV (26.15-39.65), P < 0.001], GA-RI [0.60 (0.48-0.73) vs. 0.43 (0.30-0.60), P = 0.005], and ff-AR [2.51 (1.79-3.47) vs. 1.48 (1.21-2.17), P = 0.001] than males. There were no differences in symptoms. These results define variations in gastric electrophysiology with regard to human menstrual cycling and menopause. NEW & NOTEWORTHY This study evaluates gastric electrophysiology in relation to the menstrual cycle using a novel noninvasive high-resolution methodology, revealing substantial variations in gastric activity with menstrual cycling and menopause. Gastric slow-wave frequency is significantly higher in the luteal versus follicular menstrual phase. Computational modeling predicts that this difference translates to higher rates of gastric mixing and liquid emptying in the luteal phase, which is consistent with previous experimental data evaluating menstrual cycling effects on gastric emptying.

Background: Silicon-based micro-pillar substrates (MPS), as three-dimensional cell culture platforms with vertically aligned micro-patterned scaffolding structures, are known to facilitate high-quality growth and morphology of dorsal root ganglion (DRG) sensory neurons, promote neurite outgrowth and enhance neurite alignment. However, the electrophysiological aspects of DRG neurons cultured on silicon MPSs have not been thoroughly investigated, which is of greatest importance to ensure that such substrates do not disrupt neuronal homeostasis and function before their widespread adoption in diverse biomedical applications., New Method: We conducted whole-cell patch-clamp recordings to explore the electrophysiological properties of DRG neurons cultured on MPS arrays, utilizing a custom-made upright patch-clamp setup., Results: Our findings revealed that DRG neurons exhibited similar electrophysiological responses on patterned MPS samples when compared to the control planar glass surfaces. Notably, there were no significant differences observed in the action potential parameters or firing patterns of action potentials between neurons grown on either substrate., Comparison With Existing Methods: In the current study we for the first time confirmed that successful electrophysiological recordings can be obtained from the cells grown on MPS., Conclusion: Our results imply that, despite the potential alterations caused by the cumulative trauma of tissue harvest and cell dissociation, essential functional cell properties of DRG neurons appear to be relatively maintained on MPS surfaces. Therefore, vertically aligned silicon MPSs could be considered as a potentially effective three-dimensional system for supporting a controlled cellular environment in culture., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets., Competing Interests: Declaration of interests The authors declare no competing financial interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Scientific research demands reproducibility and transparency, particularly in data-intensive fields like electrophysiology. Electrophysiology data are typically analyzed using scripts that generate output files, including figures. Handling these results poses several challenges due to the complexity and iterative nature of the analysis process. These stem from the difficulty to discern the analysis steps, parameters, and data flow from the results, making knowledge transfer and findability challenging in collaborative settings. Provenance information tracks data lineage and processes applied to it, and provenance capture during the execution of an analysis script can address those challenges. We present Alpaca (Automated Lightweight Provenance Capture), a tool that captures fine-grained provenance information with minimal user intervention when running data analysis pipelines implemented in Python scripts. Alpaca records inputs, outputs, and function parameters and structures information according to the W3C PROV standard. We demonstrate the tool using a realistic use case involving multichannel local field potential recordings of a neurophysiological experiment, highlighting how the tool makes result details known in a standardized manner in order to address the challenges of the analysis process. Ultimately, using Alpaca will help to represent results according to the FAIR principles, which will improve research reproducibility and facilitate sharing the results of data analyses., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Köhler et al.)

Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging., Competing Interests: Declaration of Competing Interest M.L. is a scientfic co-founder of Morphoceuticals Inc., which does research in the field of bioelectrically induced organ regeneration. M.L. is also a scientific co-founder of Astonishing Labs, which does research in the field of aging., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Human induced pluripotent stem cell-derived sensory neurons (hiPSC-SNs) and human dorsal root ganglia neurons (hDRG-N) are popular tools in the field of pain research; however, few groups make use of both approaches. For screening and analgesic validation purposes, important characterizations can be determined of the similarities and differences between hDRG-N and hiPSC-SNs. This study focuses specifically on the electrophysiology properties of hDRG-N in comparison to hiPSC-SNs. We also compared hDRG-N and hiPSC-SNs from both male and female donors to evaluate potential sex differences. We recorded neuronal size, rheobase, resting membrane potential, input resistance, and action potential waveform properties from 83 hiPSCs-SNs (2 donors) and 108 hDRG-N neurons (8 donors). We observed several statistically significant electrophysiological differences between hDRG-N and hiPSC-SNs, such as size, rheobase, input resistance, and several action potential waveform properties. Correlation analysis also revealed many properties that were positively or negatively correlated, some of which were differentially correlated between hDRG-N and hiPSC-SNs. This study shows several differences between hDRG-N and hiPSC-SNs and allows a better understanding of the advantages and disadvantages of both for use in pain research. We hope this study will be a valuable resource for pain researchers considering the use of these human in vitro systems for mechanistic studies and/or drug development projects. PERSPECTIVE: hiPSC-SNs and hDRG-N are popular tools in the field of pain research. This study allows for a better functional understanding of the pros and cons of both tools., (Copyright © 2024 United States Association for the Study of Pain, Inc. Published by Elsevier Inc. All rights reserved.)

In vivo transmembrane-voltage detection reflected the electrophysiological activities of the biological system, which is crucial for the diagnosis of neuronal disease. Traditional implanted electrodes can only monitor limited regions and induce relatively large tissue damage. Despite emerging monitoring methods based on optical imaging have access to signal recording in a larger area, the recording wavelength of less than 1000 nm seriously weakens the detection depth and resolution in vivo . Herein, a Förster resonance energy transfer (FRET)-based nano-indicator, NaYbF 4 :Er@NaYF 4 @Cy7.5@DPPC (Cy7.5-ErNP) with emission in the near-infrared IIb biological window (NIR-IIb, 1500-1700 nm) is developed for transmembrane-voltage detection. Cy7.5 dye is found to be voltage-sensitive and is employed as the energy donor for the energy transfer to the lanthanide nanoparticle, NaYbF 4 :Er@NaYF 4 (ErNP), which works as the acceptor to achieve electrophysiological signal responsive NIR-IIb luminescence. Benefiting from the high penetration and low scattering of NIR-IIb luminescence, the Cy7.5-ErNP enables both the visualization of action potential in vitro and monitoring of Mesial Temporal lobe epilepsy (mTLE) disease in vivo . This work presents a concept for leveraging the lanthanide luminescent nanoprobes to visualize electrophysiological activity in vivo , which facilitates the development of an optical nano-indicator for the diagnosis of neurological disorders.

The medial mammillary bodies (MBs) play an important role in the formation of spatial memories; their dense inputs from hippocampal and brainstem regions makes them well placed to integrate movement-related and spatial information, which is then extended to the anterior thalamic nuclei and beyond to the cortex. While the anatomical connectivity of the medial MBs has been well studied, much less is known about their physiological properties, particularly in freely moving animals. We therefore carried out a comprehensive characterization of medial MB electrophysiology across arousal states by concurrently recording from the medial MB and the CA1 field of the hippocampus in male rats. In agreement with previous studies, we found medial MB neurons to have firing rates modulated by running speed and angular head velocity, as well as theta-entrained firing. We extended the characterization of MB neuron electrophysiology in three key ways: (1) we identified a subset of neurons (25%) that exhibit dominant bursting activity; (2) we showed that ∼30% of theta-entrained neurons exhibit robust theta cycle skipping, a firing characteristic that implicates them in a network for prospective coding of position; and (3) a considerable proportion of medial MB units showed sharp-wave ripple (SWR) responsive firing (∼37%). The functional heterogeneity of MB electrophysiology reinforces their role as an integrative node for mnemonic processing and identifies potential roles for the MBs in memory consolidation through propagation of SWR-responsive activity to the anterior thalamus and prospective coding in the form of theta cycle skipping., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Dillingham et al.)

Performing efficient wound management is essential for infected diabetic wounds due to the complex pathology. Flexible electronics have been recognized as one of the promising solutions for wound management. Herein, a kind of skin-adhesive and self-healing flexible bioelectronic was developed, which could be employed as a diagnostic wound dressing to record diabetic wound healing and monitor electrophysiological signals of the patients. The flexible substrate of diagnostic wound dressings showed excellent tissue adhesive (to various substrates including biological samples), self-healing (fracture strength restores by 96%), and intrinsic antibacterial properties (antibacterial ratio >96% against multidrug-resistant bacteria). The diagnostic wound dressings could record the glucose level (1-30 mM), pH values (4-7), and body temperature (18.8-40.0 °C) around the infected diabetic wounds. Besides, the dressings could help optimize treatment strategies based on electrophysiological signals of patients monitored in real-time. This study contributes to developing flexible bioelectronics for the diagnosis and management of diabetic wounds.

Motivated by the unexplored potential of in vitro neural systems for computing and by the corresponding need of versatile, scalable interfaces for multimodal interaction, an accurate, modular, fully customizable, and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated is presented. This approach entails a reconfigurable platform that works across multiple industry standards and that enables a complete signal chain, from neural substrates sampled through micro-electrode arrays (MEAs) to data acquisition, downstream analysis, and cloud storage. Built-in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations, spatial topologies, and constitutive materials. Through a dedicated analysis and management software suite, the utility and robustness of this system are demonstrated across neural cultures and applications, including embryonic stem cell-derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging, and long-term recording. Overall, this technology, termed "mind in vitro" to underscore the computing inspiration, provides an end-to-end solution that can be widely deployed due to its affordable (>10× cost reduction) and open-source nature, catering to the expanding needs of both conventional and unconventional electrophysiology., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Introduction/aims: In the early stage, hereditary transthyretin (ATTRv) amyloidosis predominantly affects small nerve fibers, resulting in autonomic dysfunction and impaired sensation of pain and temperature. Evaluation of small fiber neuropathy (SFN) is therefore important for early diagnosis and treatment of ATTRv amyloidosis. Herein, we aimed to investigate the accuracy of a quick and non-invasive commercial sudomotor function test (SFT) for the assessment of SFN in ATTRv amyloidosis., Methods: We performed the SFT in 39 Japanese adults with ATTRv amyloidosis, and we analyzed the correlations between electrochemical skin conductance (ESC) values obtained via the SFT and the parameters of other neuropathy assessment methods., Results: ESC in the feet demonstrated significant, moderate correlations with intraepidermal nerve fiber density (IENFD) results (Spearman's rank correlation coefficient [r s ], 0.58; p < .002) and other neuropathy assessment methods including the sensory nerve action potential amplitude in the nerve conduction studies (r s , 0.52; p < .001), the Neuropathy Impairment Score (r s , -0.45; p < .01), the heat-pain detection threshold (r s , -0.62; p < .0001), and the autonomic section of the Kumamoto ATTRv clinical score (r s , -0.53; p < .0001)., Discussion: In this study, we found that ESC values in the feet via the SFT demonstrated significant, moderate correlations with IENFD and other SFN assessment methods in patients with ATTRv amyloidosis, suggesting that the SFT appears to be an appropriate method for assessment of SFN in this disease., (© 2023 Wiley Periodicals LLC.)

For a long time, electrical signaling was neglected at the expense of signaling studies in plants being concentrated with chemical and hydraulic signals. Studies conducted in recent years have revealed that plants are capable of emitting, processing, and transmitting bioelectrical signals to regulate a wide variety of physiological functions. Many important biological and physiological phenomena are accompanied by these cellular electrical manifestations, which supports the hypothesis about the importance of bioelectricity as a fundamental 'model' for response the stresses environmental and for activities regeneration of these organisms. Electrical signals have also been characterized and discriminated against in genetically modified plants under stress mediated by sucking insects and/or by the application of systemic insecticides. Such results can guide future studies that aim to elucidate the factors involved in the processes of resistance to stress and plant defense, thus aiding in the development of successful strategies in integrated pest management. Therefore, this mini review includes the results of studies aimed at electrical signaling in response to biotic stress. We also demonstrated how the generation and propagation of electrical signals takes place and included a description of how these electrical potentials are measured.

Gastric motility is coordinated by bioelectric slow waves (SWs) and dysrhythmic SW activity has been linked with motility disorders. Magnetogastrography (MGG) is the non-invasive measurement of the biomagnetic fields generated by SWs. Dysrhythmia identification using MGG is currently challenging because source models are not well developed and the impact of anatomical variation is not well understood. A novel method for the quantitative spatial co-registration of serosal SW potentials, MGG, and geometric models of anatomical structures was developed and performed on two anesthetized pigs to verify feasibility. Electrode arrays were localized using electromagnetic transmitting coils. Coil localization error for the volume where the stomach is normally located under the sensor array was assessed in a benchtop experiment, and mean error was 4.2±2.3mm and 3.6±3.3° for a coil orientation parallel to the sensor array and 6.2±5.7mm and 4.5±7.0° for a perpendicular coil orientation. Stomach geometries were reconstructed by fitting a generic stomach to up to 19 localization coils, and SW activation maps were mapped onto the reconstructed geometries using the registered positions of 128 electrodes. Normal proximal-to-distal and ectopic SW propagation patterns were recorded from the serosa and compared against the simultaneous MGG measurements. Correlations between the center-of-gravity of normalized MGG and the mean position of SW activity on the serosa were 0.36 and 0.85 for the ectopic and normal propagation patterns along the proximal-distal stomach axis, respectively. This study presents the first feasible method for the spatial co-registration of MGG, serosal SW measurements, and subject-specific anatomy. This is a significant advancement because these data enable the development and validation of novel non-invasive gastric source characterization methods., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: No commercial support was received for any material presented in this publication. L. K. Cheng, T. R. Angeli-Gordon and N. Paskaranandavadivel hold intellectual property and/or patent applications on gastrointestinal electrophysiology. L. K. Cheng, T. R. Angeli-Gordon and N. Paskaranandavadivel are shareholders in FlexiMap Ltd., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Penetrating flexible electrode arrays can simultaneously record thousands of individual neurons in the brains of live animals. However, it has been challenging to spatially map and longitudinally monitor the dynamics of large three-dimensional neural networks. Here we show that optimized ultraflexible electrode arrays distributed across multiple cortical regions in head-fixed mice and in freely moving rats allow for months-long stable electrophysiological recording of several thousand neurons at densities of about 1,000 neural units per cubic millimetre. The chronic recordings enhanced decoding accuracy during optogenetic stimulation and enabled the detection of strongly coupled neuron pairs at the million-pair and millisecond scales, and thus the inference of patterns of directional information flow. Longitudinal and volumetric measurements of neural couplings may facilitate the study of large-scale neural circuits., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Objective. Functional connectivity networks explain the different brain states during the diverse motor, cognitive, and sensory functions. Extracting connectivity network configurations and their temporal evolution is crucial for understanding brain function during diverse behavioral tasks. Approach. In this study, we introduce the use of dynamic mode decomposition (DMD) to extract the dynamics of brain networks. We compared DMD with principal component analysis (PCA) using real magnetoencephalography data during motor and memory tasks. Main results. The framework generates dominant connectivity brain networks and their time dynamics during simple tasks, such as button press and left-hand movement, as well as more complex tasks, such as picture naming and memory tasks. Our findings show that the proposed methodology with both the PCA-based and DMD-based approaches extracts similar dominant connectivity networks and their corresponding temporal dynamics. Significance. We believe that the proposed methodology with both the PCA and the DMD approaches has a very high potential for deciphering the spatiotemporal dynamics of electrophysiological brain network states during tasks., (© 2023 IOP Publishing Ltd.)

The ex vivo cortical slice is an extremely versatile preparation, but its utility ultimately depends on understanding its limitations and functional constraints. A question for experimentalists new to the field of cortical slice electrophysiology might be - what are the different network dynamical states available to a cortical slice as a function of excitatory drive? The purpose of this study is to provide a coherent answer to this question, within the context of extracellularly recorded population field potentials. Cortical slices (400 µm) were prepared from adult male or female C57 mice. Evoked responses were recorded within cortical layer III/IV using extracellularly positioned metal electrodes. In the first part of the study, slice excitatory drive was increased by reducing the concentration of magnesium ions in the artificial cerebrospinal fluid - and the evoked responses categorized during the transition. In the second part, each of the identified functional states were explored in greater detail with tissue perfusion conditions and excitatory drive optimised for the requisite response state. As expected, rodent cortical slices did not generate spontaneous, persistent EEG-like field potential activity. However, distinct response states (spontaneous and evoked) characterized by intermittent population bursts could be differentiated as a function of excitatory drive. Each state reflected different modes of neocortical activation: "monosynaptic" responses were brief, non-propagating activations, reflecting an inhibited cortex with sensory processing blocked; polysynaptic and epileptiform activity propagated intra-cortically, the latter reflecting a hyperactivated, hypersynchronous "seizing" cortex. Polysynaptic activity most closely resembled sensory "up states" associated with intracortical sensory processing. Understanding the functional distinction between the different cortical slice response states is the starting point for designing experiments that maximise the utility of this ex vivo model. The results and descriptions in this study should help slice experimentalists less experienced in the nuances of cortical slice neurophysiology to make informed choices about how to tailor the parameters of the model to suit the specific aims of their research., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Genetic differences in cerebellar sensitivity to alcohol (EtOH) influence EtOH consumption phenotype in animal models and contribute to risk for developing an alcohol use disorder in humans. We previously determined that EtOH enhances cerebellar granule cell (GC) tonic GABA A R currents in low EtOH consuming rodent genotypes, but suppresses it in high EtOH consuming rodent genotypes. Moreover, pharmacologically counteracting EtOH suppression of GC tonic GABA A R currents reduces EtOH consumption in high alcohol consuming C57BL/6J (B6J) mice, suggesting a causative role. In the low EtOH consuming rodent models tested to date, EtOH enhancement of GC tonic GABA A R currents is mediated by inhibition of neuronal nitric oxide synthase (nNOS) which drives increased vesicular GABA release onto GCs and a consequent enhancement of tonic GABA A R currents. Consequently, genetic variation in nNOS expression across rodent genotypes is a key determinant of whether EtOH enhances or suppresses tonic GABA A R currents, and thus EtOH consumption. We used behavioral, electrophysiological, and immunocytochemical techniques to further explore the relationship between EtOH consumption and GC GABA A R current responses in C57BL/6N (B6N) mice. B6N mice consume significantly less EtOH and achieve significantly lower blood EtOH concentrations than B6J mice, an outcome not mediated by differences in taste. In voltage-clamped GCs, EtOH enhanced the GC tonic current in B6N mice but suppressed it in B6J mice. Immunohistochemical and electrophysiological studies revealed significantly higher nNOS expression and function in the GC layer of B6N mice compared to B6Js. Collectively, our data demonstrate that despite being genetically similar, B6N mice consume significantly less EtOH than B6J mice, a behavioral difference paralleled by increased cerebellar nNOS expression and opposite EtOH action on GC tonic GABA A R currents in each genotype., (Published by Elsevier Ltd.)

Understanding brain function requires repeatable measurements of neural activity across multiple scales and multiple brain areas. In mice, large scale cortical neural activity evokes hemodynamic changes readily observable with intrinsic signal imaging (ISI). Pairing ISI with visual stimulation allows identification of primary visual cortex (V1) and higher visual areas (HVAs), typically through cranial windows that thin or remove the skull. These procedures can diminish long-term mechanical and physiological stability required for delicate electrophysiological measurements made weeks to months after imaging (e.g., in subjects undergoing behavioral training). Here, we optimized and directly validated an intact skull ISI system in mice. We first assessed how imaging quality and duration affect reliability of retinotopic maps in V1 and HVAs. We then verified ISI map retinotopy in V1 and HVAs with targeted, multi-site electrophysiology several weeks after imaging. Reliable ISI maps of V1 and multiple HVAs emerged with ~ 60 trials of imaging (65 ± 6 min), and these showed strong correlation to local field potential (LFP) retinotopy in superficial cortical layers (r 2  = 0.74-0.82). This system is thus well-suited for targeted, multi-area electrophysiology weeks to months after imaging. We provide detailed instructions and code for other researchers to implement this system., (© 2022. The Author(s).)

This study aimed to determine whether neural drive is redistributed between muscles during a fatiguing isometric contraction, and if so, whether the initial level of common synaptic input between these muscles constrains this redistribution. We studied two muscle groups: triceps surae (14 participants) and quadriceps (15 participants). Participants performed a series of submaximal isometric contractions and a torque-matched contraction maintained until task failure. We used high-density surface electromyography to identify the behavior of 1,874 motor units from the soleus, gastrocnemius medialis (GM), gastrocnemius lateralis (GL), rectus femoris, vastus lateralis (VL), and vastus medialis (VM). We assessed the level of common drive between muscles in the absence of fatigue using a coherence analysis. We also assessed the redistribution of neural drive between muscles during the fatiguing contraction through the correlation between their cumulative spike trains (index of neural drive). The level of common drive between VL and VM was significantly higher than that observed for the other muscle pairs, including GL-GM. The level of common drive increased during the fatiguing contraction, but the differences between muscle pairs persisted. We also observed a strong positive correlation of neural drive between VL and VM during the fatiguing contraction ( r = 0.82). This was not observed for the other muscle pairs, including GL-GM, which exhibited differential changes in neural drive. These results suggest that less common synaptic input between muscles allows for more flexible coordination strategies during a fatiguing task, i.e., differential changes in neural drive across muscles. The role of this flexibility on performance remains to be elucidated. NEW & NOTEWORTHY Redundancy of the neuromuscular system theoretically allows for a redistribution of the neural drive across muscles (i.e., between-muscle compensation) during a fatiguing contraction. Our results suggest that a high level of common input between muscles (e.g., vastus lateralis and medialis) represents a neural constraint making it less likely to redistribute the neural drive across these muscles. In this way, redistribution was only observed across muscles that share little common synaptic input (e.g., gastrocnemius lateralis and medialis).

Objective. Extracellular electrophysiology has been widely applied to neural circuit dissections. However, long-term multiregional recording in free-moving mice remains a challenge. Low-cost and easy-fabrication of elaborate drivable electrodes is required for their prevalence. Approach. A three-layer nested construct (outside diameter, OD ∼ 1.80 mm, length ∼10 mm, <0.1 g) was recruited as a drivable component, which consisted of an ethylene-vinyl acetate copolymer heat-shrinkable tube, non-closed loop ceramic bushing, and stainless ferrule with a bulge twining silver wire. The supporting and working components were equipped with drivable components to be assembled into a drivable microwire electrode array with a nested structure (drivable MEANS). Two drivable microwire electrode arrays were independently implanted for chronic recording in different brain areas at respective angles. An optic fiber was easily loaded into the drivable MEANS to achieve optogenetic modulation and electrophysiological recording simultaneously. Main results. The drivable MEANS had lightweight (∼0.37 g), small (∼15 mm × 15 mm × 4 mm), and low cost (⩽$64.62). Two drivable MEANS were simultaneously implanted in mice, and high-quality electrophysiological recordings could be applied ⩾5 months after implantation in freely behaving animals. Electrophysiological recordings and analysis of the lateral septum (LS) and lateral hypothalamus in food-seeking behavior demonstrated that our drivable MEANS can be used to dissect the function of neural circuits. An optical fiber-integrated drivable MEANS (∼0.47 g) was used to stimulate and record LS neurons, which suggested that changes in working components can achieve more functions than electrophysiological recordings, such as optical stimulation, drug release, and calcium imaging. Significance. Drivable MEANS is an easily fabricated, lightweight drivable microwire electrode array for multiple-region electrophysiological recording in free-moving mice. Our design is likely to be a valuable platform for both current and prospective users, as well as for developers of multifunctional electrodes for free-moving mice., (Creative Commons Attribution license.)

Cell-type-specific, activity-dependent electrophysiology can allow in-depth analysis of functional connectivity inside complex neural circuits composed of various cell types. To date, optics-based fluorescence recording devices enable monitoring cell-type-specific activities. However, the monitoring is typically limited to a single brain region, and the temporal resolution is significantly low. Herein, a multimodal multi-shank fluorescence neural probe that allows cell-type-specific electrophysiology from multiple deep-brain regions at a high spatiotemporal resolution is presented. A photodiode and an electrode-array pair are monolithically integrated on each tip of a minimal-form-factor silicon device. Both fluorescence and electrical signals are successfully measured simultaneously in GCaMP6f expressing mice, and the cell type from sorted neural spikes is identified. The probe's capability of combined electro-optical recordings for cell-type-specific electrophysiology at multiple brain regions within a neural circuit is demonstrated. The new experimental paradigm to enable the precise investigation of functional connectivity inside and across complex neural circuits composed of various cell types is expected., (© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.)

In the auditory modality, noise trauma has often been used to investigate cortical plasticity as it causes cochlear hearing loss. One limitation of these past studies, however, is that the effects of noise trauma have been mostly documented at the granular layer, which is the main cortical recipient of thalamic inputs. Importantly, the cortex is composed of six different layers each having its own pattern of connectivity and specific role in sensory processing. The present study aims at investigating the effects of acute and chronic noise trauma on the laminar pattern of spontaneous activity (SA) in primary auditory cortex (A1) of the anesthetized guinea pig. We show that spontaneous activity is dramatically altered across cortical layers after acute and chronic noise-induced hearing loss. First, spontaneous activity was globally enhanced across cortical layers, both in terms of firing rate and amplitude of spike-triggered average of local field potentials. Second, current source density on (spontaneous) spike-triggered average of local field potentials indicates that current sinks develop in the supra- and infragranular layers. These latter results suggest that supragranular layers become a major input recipient and the propagation of spontaneous activity over a cortical column is greatly enhanced after acute and chronic noise-induced hearing loss. We discuss the possible mechanisms and functional implications of these changes. NEW & NOTEWORTHY The present study investigates the effects of acute and chronic noise trauma on the laminar pattern of spontaneous activity in the primary auditory cortex. Our study is first to report that noise trauma alters the sequence of cortical column activation during ongoing activity. In particular, we show that the supragranular layer becomes a major input recipient and the synaptic activity in the infragranular layers is enhanced.

Microelectrode recordings (MERs) are often used during deep brain stimulation (DBS) surgeries to confirm the position of electrodes in patients with advanced Parkinson's disease. The present study focused on 32 patients who had undergone DBS surgery for advanced Parkinson's disease. The first objective was to confront the anatomical locations of intraoperative individual MERs as determined electrophysiologically with those determined postoperatively by image reconstructions. The second aim was to search for differences in cell characteristics among the three subthalamic nucleus (STN) subdivisions and between the STN and other identified subcortical structures. Using the DISTAL atlas implemented in the Lead-DBS image reconstruction toolbox, each MER location was determined postoperatively and attributed to specific anatomical structures (sensorimotor, associative or limbic STN; substantia nigra [SN], thalamus, nucleus reticularis polaris, zona incerta [ZI]). The STN dorsal borders determined intraoperatively from electrophysiology were then compared with the STN dorsal borders determined by the reconstructed images. Parameters of spike clusters (firing rates, amplitudes - with minimum amplitude of 60 μV -, spike durations, amplitude spectral density of β-oscillations) were compared between structures (ANOVAs on ranks). Two hundred and thirty one MERs were analyzed (144 in 34 STNs, 7 in 4 thalami, 5 in 4 ZIs, 34 in 10 SNs, 41 others). The average difference in depth of the electrophysiological dorsal STN entry in comparison with the STN entry obtained with Lead-DBS was found to be of 0.1 mm (standard deviation: 0.8 mm). All 12 analyzed MERs recorded above the electrophysiologically-determined STN entry were confirmed to be in the thalamus or zona incerta. All MERs electrophysiologically attributed to the SN were confirmed to belong to this nucleus. However, 6/34 MERs that were electrophysiologically attributed to the ventral STN were postoperatively reattributed to the SN. Furthermore, 44 MERs of 3 trajectories, which were intraoperatively attributed to the STN, were postoperatively reattributed to the pallidum or thalamus. MER parameters seemed to differ across the STN, with higher spike amplitudes (H = 10.64, p < 0.01) and less prevalent β-oscillations (H = 9.81, p < 0.01) in the limbic STN than in the sensorimotor and associative subdivisions. Some cells, especially in the SN, showed longer spikes with lower firing rates, in agreement with described characteristics of dopamine cells. However, these probabilistic electrophysiological signatures might become clinically less relevant with the development of image reconstruction tools, which deserve to be applied intraoperatively., (Copyright © 2022 Faculty of medicine, University Hospitals of Geneva. Published by Elsevier Inc. All rights reserved.)

The regular equilateral triangular periodic firing pattern of grid cells in the entorhinal cortex is considered a regular metric for the spatial world, and the grid-like representation correlates with hexadirectional modulation of theta (4-8 Hz) power in the entorhinal cortex relative to the moving direction. However, researchers have not clearly determined whether grid cells provide only simple spatial measures in human behavior-related navigation strategies or include other factors such as goal rewards to encode information in multiple patterns. By analysing the hexadirectional modulation of EEG signals in the theta band in the entorhinal cortex of patients with epilepsy performing spatial target navigation tasks, we found that this modulation presents a grid pattern that carries target-related reward information. This grid-like representation is influenced by explicit goals and is related to the local characteristics of the environment. This study provides evidence that human grid cell population activity is influenced by reward information at the level of neural oscillations., (© 2021. The Author(s).)

Recent studies have shown that neural activity in a well-defined patch in the posterior superior temporal sulcus (the "gaze-following patch," GFP) of the primate brain is strongly modulated when the other's gaze attracts the observer's attention to locations/objects, the other is looking at. Changes of the mean discharge rate of neurons in the monkey GFP indicate that they are involved in two distinct computations: the allocation of spatial attention guided by the other's gaze vector and the suppression of gaze following if inappropriate in a given situation. Here, we asked if and how the discharge variability of neurons in the GFP is related to the task and if it carries information on behavioral performance. To this end, we calculated the Fano factor as a measure of across-trial discharge variability as a function of time. Our results show that all neurons exhibiting a task-related discharge-rate modulation also exhibit a stimulus onset-dependent drop in the Fano factor. Furthermore, the amplitude of the Fano factor reduction is modulated by task condition and the neuron's selectivity in this regard. We found that these effects are directly related to the monkeys' behavioral performance in that the Fano factor is predictive about upcoming correct or wrong decisions. Our results indicate that neuronal discharge variability as gauged by the Fano factor, hitherto primarily studied in the context of visual perception or motor control, is an informative measure also in studies of the neural underpinnings of complex social behavior. NEW & NOTEWORTHY Quenching of neural variability following stimulus onset is a widely accepted phenomenon. However, the relevance of quenching for the shaping of complex social behaviors remains to be explored. Here, we show that task selective neurons in the GFP exhibit a higher degree of variability quenching than their neighboring unselective neurons. Furthermore, we demonstrate that behavioral errors are not only associated with lower firing rates but also less variability quenching, suggesting that both facilitate optimal performance.

Dynamic causal models (DCMs) of electrophysiological data allow, in principle, for inference on hidden, bulk synaptic function in neural circuits. The directed influences between the neuronal elements of modeled circuits are subject to delays due to the finite transmission speed of axonal connections. Ordinary differential equations are therefore not adequate to capture the ensuing circuit dynamics, and delay differential equations (DDEs) are required instead. Previous work has illustrated that the integration of DDEs in DCMs benefits from sophisticated integration schemes in order to ensure rigorous parameter estimation and correct model identification. However, integration schemes that have been proposed for DCMs either emphasize speed (at the possible expense of accuracy) or robustness (but with computational costs that are problematic in practice). In this technical note, we propose an alternative integration scheme that overcomes these shortcomings and offers high computational efficiency while correctly preserving the nature of delayed effects. This integration scheme is available as open-source code in the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) toolbox and can be easily integrated into existing software (SPM) for the analysis of DCMs for electrophysiological data. While this paper focuses on its application to the convolution-based formalism of DCMs, the new integration scheme can be equally applied to more advanced formulations of DCMs (e.g. conductance based models). Our method provides a new option for electrophysiological DCMs that offers the speed required for scientific projects, but also the accuracy required for rigorous translational applications, e.g. in computational psychiatry., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2021. Published by Elsevier Inc.)

Nervous systems face a torrent of sensory inputs, including proprioceptive feedback. Signal integration depends on spatially and temporally coinciding signals. It is unclear how relative time delays affect multimodal signal integration from spatially distant sense organs. We measured transmission times and latencies along all processing stages of sensorimotor pathways in the stick insect leg muscle control system, using intra- and extracellular recordings. Transmission times of signals from load-sensing tibial and trochanterofemoral campaniform sensilla (tiCS, tr/fCS) to the premotor network were longer than from the movement-sensing femoral chordotonal organ (fCO). We characterized connectivity patterns from tiCS, tr/fCS, and fCO afferents to identified premotor nonspiking interneurons (NSIs) and motor neurons (MNs) by distinguishing short- and long-latency responses to sensory stimuli. Functional NSI connectivity depended on sensory context. The timeline of multisensory integration in the NSI network showed an early phase of movement signal processing and a delayed phase of load signal integration. The temporal delay of load signals relative to movement feedback persisted into MN activity and muscle force development. We demonstrate differential delays in the processing of two distinct sensory modalities generated by the sensorimotor network and affecting motor output. The reported temporal differences in sensory processing and signal integration improve our understanding of sensory network computation and function in motor control. NEW & NOTEWORTHY Networks integrating multisensory input face the challenge of not only spatial but also temporal integration. In the local network controlling insect leg movements, proprioceptive signal delays differ between sensory modalities. Specifically, signal transmission times to and neuronal connectivity within the sensorimotor network lead to delayed information about leg loading relative to movement signals. Temporal delays persist up to the level of the motor output, demonstrating its relevance for motor control.

Barrington's nucleus (Bar), which controls micturition behavior through downstream projections to the spinal cord, contains two types of projection neurons, Bar CRH and Bar ESR1 , that have different functions and target different spinal circuitry. Both types of neurons project to the L 6 -S 1 spinal intermediolateral (IML) nucleus, whereas Bar ESR1 neurons also project to the dorsal commissural nucleus (DCN). To obtain more information about the spinal circuits targeted by Bar, we used patch-clamp recording in spinal slices from adult mice in combination with optogenetic stimulation of Bar terminals. Recording of opto-evoked excitatory postsynaptic currents (oEPSCs) in 1,1'-dilinoleyl-3,3,3',3'-tetramethylindocarbocyanine, 4-chlorobenzenesulfonate (DiI)-labeled lumbosacral preganglionic neurons (LS-PGNs) revealed that both Bar neuronal populations make strong glutamatergic monosynaptic connections with LS-PGNs, whereas Bar ESR1 neurons also elicited smaller-amplitude glutamatergic polysynaptic oEPSCs or polysynaptic opto-evoked inhibitory postsynaptic currents (oIPSCs) in some LS-PGNs. Optical stimulation of Bar CRH and Bar ESR1 terminals also elicited monosynaptic oEPSCs and polysynaptic oIPSCs in sacral DCN neurons, some of which must include interneurons projecting to either the IML or ventral horn. Application of capsaicin increased opto-evoked firing during repetitive stimulation of Bar terminals through the modulation of spontaneous postsynaptic currents in LS-PGNs. In conclusion, our experiments have provided insights into the synaptic mechanisms underlying the integration of inputs from Bar to autonomic circuitry in the lumbosacral spinal cord that may control micturition. NEW & NOTEWORTHY Photostimulation of Bar CRH or Bar ESR1 axons in the adult mouse spinal cord elicits excitatory or inhibitory postsynaptic responses in multiple cell types related to the autonomic nervous system including preganglionic neurons (PGNs) in the lumbosacral intermediolateral nucleus and interneurons in the lumbosacral dorsal commissure nucleus. Integration of excitatory inputs from Bar and from visceral primary afferents in PGNs may be important in the regulation of micturition behavior.

Efficient communication between the glial cells and neurons is a bi-directional process that is essential for conserving normal functioning in the central nervous system (CNS). Neurons dynamically regulate other brain cells in the healthy brain, yet little is known about the first pathways involving oligodendrocytes and neurons. Oligodendrocytes are the myelin-forming cells in the CNS that are needed for the propagation of action potentials along axons and additionally serve to support neurons by neurotrophic factors (NFTs). In demyelinating diseases, like multiple sclerosis (MS), oligodendrocytes are thought to be the victims. Axonal damage begins early and remains silent for years, and neurological disability develops when a threshold of axonal loss is reached, and the compensatory mechanisms are depleted. Three hypotheses have been proposed to explain axonal damage: 1) the damage is caused by an inflammatory process; 2) there is an excessive accumulation of intra-axonal calcium levels; and, 3) demyelinated axons evolve to a degenerative process resulting from the lack of trophic support provided by myelin or myelin-forming cells. Although MS was traditionally considered to be a white matter disease, the demyelination process also occurs in the cerebral cortex. Recent data supports the notion that initial response is triggered by CNS injury. Thus, the understanding of the role of neuron-glial neurophysiology would help provide us with further explanations. We should take in account the suggestion that MS is in part an autoimmune disease that involves genetic and environmental factors, and the pathological response leads to demyelination, axonal loss and inflammatory infiltrates.

Phrenic afferents project to brainstem areas responsible for cardiorespiratory control and the mid-cervical spinal cord containing the phrenic motor nucleus. Our purpose was to quantify the impact of small- and large-diameter phrenic afferent activation on phrenic motor output. Anesthetized and ventilated rats received unilateral phrenic nerve stimulation while contralateral phrenic motor output and blood pressure were recorded. Twelve currents of 40-Hz inspiratory-triggered stimulation were delivered (20 s on, 5 min off) to establish current response curves. Stimulation pulse width was varied to preferentially activate large-diameter phrenic afferents (narrow pulse width) and recruit small-diameter fibers (wide pulse width). Contralateral phrenic amplitude was elevated immediately poststimulation at currents above 35 µA for wide and 70 µA for narrow pulse stimulation when compared with animals not receiving stimulation (time controls). Wide pulse width stimulation also increased phrenic burst frequency at currents ≥35 µA, caused a transient decrease in mean arterial blood pressure at currents ≥50 µA, and resulted in a small change in heart rate at 300 µA. Unilateral dorsal rhizotomy attenuated stimulation-induced cardiorespiratory responses indicating that phrenic afferent activation is required. Additional analyses compared phrenic motor amplitude with output before stimulation and showed that episodic activation of phrenic afferents with narrow pulse stimulation can induce short-term plasticity. We conclude that the activation of phrenic afferents 1 ) enhances contralateral phrenic motor amplitude when large-diameter afferents are activated, and 2 ) when small-diameter fibers are recruited, the amplitude response is associated with changes in burst frequency and cardiovascular parameters. NEW & NOTEWORTHY Acute, inspiratory-triggered stimulation of phrenic afferents increases contralateral phrenic motor amplitude in adult rats. When small-diameter afferents are recruited, the amplitude response is accompanied by an increase in phrenic burst frequency, a transient decrease in mean arterial blood pressure, and a slight increase in heart rate. Repeated episodes of large-diameter phrenic afferent activation may also be capable of inducing short-term plasticity.

The limit of dynamic endurance during repetitive contractions has been referred to as the point of muscle fatigue, which can be measured by mechanical and electrophysiological parameters combined with subjective estimates of load tolerance for revealing the human real-world capacity required to work continuously. In this study, an isotonic muscular endurance (IME) testing protocol under a psychophysiological fatigue criterion was developed for measuring the retentive capacity of the power output of lower limb muscles. Additionally, to guide the development of electrophysiological evaluation methods, linear and non-linear techniques for creating surface electromyography (sEMG) models were compared in terms of their ability to estimate muscle fatigue. Forty healthy college-aged males performed three trials of an isometric peak torque test and one trial of an IME test for the plantar flexors and knee and hip extensors. Meanwhile, sEMG activity was recorded from the medial gastrocnemius, lateral gastrocnemius, vastus medialis, rectus femoris, vastus lateralis, gluteus maximus, and biceps femoris of the right leg muscles. Linear techniques (amplitude-based parameters, spectral parameters, and instantaneous frequency parameters) and non-linear techniques (a multi-layer perception neural network) were used to predict the time-dependent power output during dynamic contractions. Two mechanical manifestations of muscle fatigue were observed in the IME tests, including power output reduction between the beginning and end of the test and time-dependent progressive power loss. Compared with linear mapping (linear regression) alone or a combination of sEMG variables, non-linear mapping of power loss during dynamic contractions showed significantly higher signal-to-noise ratios and correlation coefficients between the actual and estimated power output. Muscular endurance required in real-world activities can be measured by considering the amount of work produced or the activity duration via the recommended IME testing protocol under a psychophysiological termination criterion. Non-linear mapping techniques provide more powerful mapping of power loss compared with linear mapping in the IME testing protocol., (© 2021. The Author(s).)

The review surveys various aspects of the plasticity of nerve fibers, in particular the prolonged increase in their excitability evoked by polarization, focusing on a long-lasting increase in the excitability of myelinated afferent fibers traversing the dorsal columns of the spinal cord. We review the evidence that increased axonal excitability 1 ) follows epidurally applied direct current (DC) as well as relatively short (5 or 10 ms) current pulses and synaptically evoked intrinsic field potentials; 2 ) critically depends on the polarization of branching regions of afferent fibers at the sites where they bifurcate and give off axon collaterals entering the spinal gray matter in conjunction with actions of extrasynaptic GABA A membrane receptors; and 3 ) shares the feature of being activity-independent with the short-lasting effects of polarization of peripheral nerve fibers. A comparison between the polarization evoked sustained increase in the excitability of dorsal column fibers and spinal motoneurons (plateau potentials) indicates the possibility that they are mediated by partly similar membrane channels (including noninactivating type L Cav ++ 1.3 but not Na + channels) and partly different mechanisms. We finally consider under which conditions transspinally applied DC (tsDCS) might reproduce the effects of epidural polarization on dorsal column fibers and the possible advantages of increased excitability of afferent fibers for the rehabilitation of motor and sensory functions after spinal cord injuries. NEW & NOTEWORTHY This review supplements previous reviews of properties of nerve fibers by surveying recent experimental evidence for their long-term plasticity. It also extends recent descriptions of spinal effects of DC by reviewing effects of polarization of afferent nerve fibers within the dorsal columns, the mechanisms most likely underlying the long-lasting increase in their excitability and possible clinical implications.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are becoming instrumental in cardiac research, human-based cell level cardiotoxicity tests, and developing patient-specific care. As one of the principal functional readouts is contractility, we propose a novel electromechanical hiPSC-CM computational model named the hiPSC-CM-CE. This model comprises a reparametrized version of contractile element (CE) by Rice et al., 2008, with a new passive force formulation, integrated into a hiPSC-CM electrophysiology formalism by Paci et al. in 2020. Our simulated results were validated against in vitro data reported for hiPSC-CMs at matching conditions from different labs. Specifically, key action potential (AP) and calcium transient (CaT) biomarkers simulated by the hiPSC-CM-CE model were within the experimental ranges. On the mechanical side, simulated cell shortening, contraction-relaxation kinetic indices (RT 50 and RT 25 ), and the amplitude of tension fell within the experimental intervals. Markedly, as an inter-scale analysis, correct classification of the inotropic effects due to non-cardiomyocytes in hiPSC-CM tissues was predicted on account of the passive force expression introduced to the CE. Finally, the physiological inotropic effects caused by Verapamil and Bay-K 8644 and the aftercontractions due to the early afterdepolarizations (EADs) were simulated and validated against experimental data. In the future, the presented model can be readily expanded to take in pharmacological trials and genetic mutations, such as those involved in hypertrophic cardiomyopathy, and study arrhythmia trigger mechanisms., (© 2021 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.)

The discrimination of complex sounds is a fundamental function of the auditory system. This operation must be robust in the presence of noise and acoustic clutter. Echolocating bats are auditory specialists that discriminate sonar objects in acoustically complex environments. Bats produce brief signals, interrupted by periods of silence, rendering echo snapshots of sonar objects. Sonar object discrimination requires that bats process spatially and temporally overlapping echoes to make split-second decisions. The mechanisms that enable this discrimination are not well understood, particularly in complex environments. We explored the neural underpinnings of sonar object discrimination in the presence of acoustic scattering caused by physical clutter. We performed electrophysiological recordings in the inferior colliculus of awake big brown bats, to broadcasts of prerecorded echoes from physical objects. We acquired single unit responses to echoes and discovered a subpopulation of IC neurons that encode acoustic features that can be used to discriminate between sonar objects. We further investigated the effects of environmental clutter on this population's encoding of acoustic features. We discovered that the effect of background clutter on sonar object discrimination is highly variable and depends on object properties and target-clutter spatiotemporal separation. In many conditions, clutter impaired discrimination of sonar objects. However, in some instances clutter enhanced acoustic features of echo returns, enabling higher levels of discrimination. This finding suggests that environmental clutter may augment acoustic cues used for sonar target discrimination and provides further evidence in a growing body of literature that noise is not universally detrimental to sensory encoding. NEW & NOTEWORTHY Bats are powerful animal models for investigating the encoding of auditory objects under acoustically challenging conditions. Although past work has considered the effect of acoustic clutter on sonar target detection, less is known about target discrimination in clutter. Our work shows that the neural encoding of auditory objects was affected by clutter in a distance-dependent manner. These findings advance the knowledge on auditory object detection and discrimination and noise-dependent stimulus enhancement.

Neurophysiological signals are often noisy, nonsinusoidal, and consist of transient bursts. Extraction and analysis of oscillatory features (such as waveform shape and cross-frequency coupling) in such data sets remains difficult. This limits our understanding of brain dynamics and its functional importance. Here, we develop iterated masking empirical mode decomposition (itEMD), a method designed to decompose noisy and transient single-channel data into relevant oscillatory modes in a flexible, fully data-driven way without the need for manual tuning. Based on empirical mode decomposition (EMD), this technique can extract single-cycle waveform dynamics through phase-aligned instantaneous frequency. We test our method by extensive simulations across different noise, sparsity, and nonsinusoidality conditions. We find itEMD significantly improves the separation of data into distinct nonsinusoidal oscillatory components and robustly reproduces waveform shape across a wide range of relevant parameters. We further validate the technique on multimodal, multispecies electrophysiological data. Our itEMD extracts known rat hippocampal θ waveform asymmetry and identifies subject-specific human occipital α without any prior assumptions about the frequencies contained in the signal. Notably, it does so with significantly less mode mixing compared with existing EMD-based methods. By reducing mode mixing and simplifying interpretation of EMD results, itEMD will enable new analyses into functional roles of neural signals in behavior and disease. NEW & NOTEWORTHY We introduce a novel, data-driven method to identify oscillations in neural recordings. This approach is based on empirical mode decomposition and reduces mixing of components, one of its main problems. The technique is validated and compared with existing methods using simulations and real data. We show our method better extracts oscillations and their properties in highly noisy and nonsinusoidal datasets.

Supraspinal signals play a significant role in compensatory responses to postural perturbations. Although the cortex is not necessary for basic postural tasks in intact animals, its role in responding to unexpected postural perturbations after spinal cord injury (SCI) has not been studied. To better understand how SCI impacts cortical encoding of postural perturbations, the activity of single neurons in the hindlimb sensorimotor cortex (HLSMC) was recorded in the rat during unexpected tilts before and after a complete midthoracic spinal transection. In a subset of animals, limb ground reaction forces were also collected. HLSMC activity was strongly modulated in response to different tilt profiles. As the velocity of the tilt increased, more information was conveyed by the HLSMC neurons about the perturbation due to increases in both the number of recruited neurons and the magnitude of their responses. SCI led to attenuated and delayed hindlimb ground reaction forces. However, HLSMC neurons remained responsive to tilts after injury but with increased latencies and decreased tuning to slower tilts. Information conveyed by cortical neurons about the tilts was therefore reduced after SCI, requiring more cells to convey the same amount of information as before the transection. Given that reorganization of the hindlimb sensorimotor cortex in response to therapy after complete midthoracic SCI is necessary for behavioral recovery, this sustained encoding of information after SCI could be a substrate for the reorganization that uses sensory information from above the lesion to control trunk muscles that permit weight-supported stepping and postural control. NEW & NOTEWORTHY The role of cortical circuits in the encoding of posture and balance is of interest for developing therapies for spinal cord injury. This work demonstrated that unexpected postural perturbations are encoded in the hindlimb sensorimotor cortex even in the absence of hindlimb sensory feedback. In fact, the hindlimb sensorimotor cortex continues to encode for postural perturbations after complete spinal transection.

A hallmark of electrophysiological brain activity is its 1/f-like spectrum - power decreases with increasing frequency. The steepness of this 'roll-off' is approximated by the spectral exponent, which in invasively recorded neural populations reflects the balance of excitatory to inhibitory neural activity (E:I balance). Here, we first establish that the spectral exponent of non-invasive electroencephalography (EEG) recordings is highly sensitive to general (i.e., anaesthesia-driven) changes in E:I balance. Building on the EEG spectral exponent as a viable marker of E:I, we then demonstrate its sensitivity to the focus of selective attention in an EEG experiment during which participants detected targets in simultaneous audio-visual noise. In addition to these endogenous changes in E:I balance, EEG spectral exponents over auditory and visual sensory cortices also tracked auditory and visual stimulus spectral exponents, respectively. Individuals' degree of this selective stimulus-brain coupling in spectral exponents predicted behavioural performance. Our results highlight the rich information contained in 1/f-like neural activity, providing a window into diverse neural processes previously thought to be inaccessible in non-invasive human recordings., Competing Interests: LW, TD, LF, SS, DG, BV No competing interests declared, JO Reviewing Editor for eLife, (© 2021, Waschke et al.)

Synchronization and bursting activity are intrinsic electrophysiological properties of in vivo and in vitro neural networks. During early development, cortical cultures exhibit a wide repertoire of synchronous bursting dynamics whose characterization may help to understand the parameters governing the transition from immature to mature networks. Here we used machine learning techniques to characterize and predict the developing spontaneous activity in mouse cortical neurons on microelectrode arrays (MEAs) during the first three weeks in vitro. Network activity at three stages of early development was defined by 18 electrophysiological features of spikes, bursts, synchrony, and connectivity. The variability of neuronal network activity during early development was investigated by applying k-means and self-organizing map (SOM) clustering analysis to features of bursts and synchrony. These electrophysiological features were predicted at the third week in vitro with high accuracy from those at earlier times using three machine learning models: Multivariate Adaptive Regression Splines, Support Vector Machines, and Random Forest. Our results indicate that initial patterns of electrical activity during the first week in vitro may already predetermine the final development of the neuronal network activity. The methodological approach used here may be applied to explore the biological mechanisms underlying the complex dynamics of spontaneous activity in developing neuronal cultures., (© 2021. The Author(s).)

Long QT syndrome (LQTS), Brugada syndrome (BrS), and catecholaminergic polymorphic ventricular tachycardia (CPVT) are genetic diseases of the heart caused by mutations in specific cardiac ion channels and are characterized by paroxysmal arrhythmias, which can deteriorate into ventricular fibrillation. In LQTS3 and BrS different mutations in the SCN5A gene lead to a gain-or a loss-of-function of the voltage-gated sodium channel Nav1.5, respectively. Although sharing the same gene mutation, these syndromes are characterized by different clinical manifestations and functional perturbations and in some cases even present an overlapping clinical phenotype. Several studies have shown that Na + current abnormalities in LQTS3 and BrS can also cause Ca 2+ -signaling aberrancies in cardiomyocytes (CMs). Abnormal Ca 2+ homeostasis is also the main feature of CPVT which is mostly caused by heterozygous mutations in the RyR2 gene. Large numbers of disease-causing mutations were identified in RyR2 and SCN5A but it is not clear how different variants in the SCN5A gene produce different clinical syndromes and if in CPVT Ca 2+ abnormalities and drug sensitivities vary depending on the mutation site in the RyR2. These questions can now be addressed by using patient-specific in vitro models of these diseases based on induced pluripotent stem cells (iPSCs). In this review, we summarize different insights gained from these models with a focus on electrophysiological perturbations caused by different ion channel mutations and discuss how will this knowledge help develop better stratification and more efficient personalized therapies for these patients., (Copyright © 2021 Elsevier Inc. All rights reserved.)