Extracellular Electrophysiology Research Articles

Pharmacological characterization of prostaglandin E2 EP2 and EP4 receptors in male rat locus coeruleus neurons ex vivo

The inflammatory mediator prostaglandin E2 (PGE2) binds to Gs-coupled EP2 and EP4 receptors. These receptors are located in the locus coeruleus (LC), the principal noradrenergic nucleus in the brain, but their functional role remains unknown. In this study, the PGE2 EP2 and EP4 receptors in LC cells from male rat brain slices were pharmacologically characterized by single-unit extracellular electrophysiology. The EP2 receptor agonists butaprost (0.01–10 μM) and treprostinil (0.03–10 µM) and the EP4 receptor agonists rivenprost (0.01 nM–1 µM) and TCS2510 (0.20 nM–2 µM) increased the firing rate of LC neurons in a concentration-dependent manner. The EP2 receptor antagonist PF-04418948 (10 nM) hindered the excitatory effect of butaprost and treprostinil while the EP4 receptor antagonist L-161,982 (30 and 300 nM) blocked the excitatory effect caused by rivenprost and TCS2510. The effects of butaprost and rivenprost were prevented by extracellular sodium replacement but were not modified by the protein kinase A (PKA) activator 8-Br-cAMP (1 mM) or the inhibitor H-89 (10 μM). However, the Gβγ subunit blocker gallein (20 μM) hindered the stimulatory effect of butaprost while the Gαs subunit inhibitor NF449 (10 µM) prevented that of rivenprost. Finally, rivenprost-induced stimulation (30 nM) was not occluded by butaprost (1 µM).In conclusion, activation of EP2 and EP4 receptors excites LC noradrenergic neurons through sodium-dependent currents via different G protein subunits in male rat brain slices. EP2 and EP4 in the LC may constitute pharmacological targets for the treatment of pain, fever, drug addiction, anxiety and neuroinflammatory diseases.

Rapid Hippocampal Synaptic Potentiation Induced by Ketamine Metabolite ( 2R , 6R )-Hydroxynorketamine Persistently Primes Synaptic Plasticity.

The pharmacologically active ( R , S )-ketamine (ketamine) metabolite ( 2R , 6R )-hydroxynorketamine (HNK) maintains ketamine's preclinical antidepressant profile without adverse effects. While hypotheses have been proposed to explain how ketamine and its metabolites initiate their antidepressant-relevant effects, it remains unclear how sustained therapeutic actions arise following drug elimination. To distinguish the physiological mechanisms involved in the rapid from sustained actions of HNK, we utilized extracellular electrophysiology combined with pharmacology to develop an in vitro hippocampal slice incubation model that exhibited pharmacological fidelity to the 1) rapid synaptic potentiation induced by HNK at the Schaffer collateral-CA1 (SC-CA1) synapse during bath-application to slices collected from mice, and 2) maintenance of metaplastic (priming) activity that lowered the threshold for N- methyl-D-aspartate receptor (NMDAR) activation-dependent long-term potentiation (LTP) hours after in vivo dosing. We then used this model to reveal novel druggable mechanisms engaged in HNK's temporally-sensitive antidepressant synaptic actions, finding that the induction of synaptic potentiation by HNK did not require NMDAR activity, but NMDAR activity was necessary to maintain synaptic priming. HNK required protein kinase A (PKA) activity to rapidly potentiate SC-CA1 neurotransmission to facilitate synaptic priming that persistently promoted LTP formation. HNK's rapid actions were blocked by inhibitors of adenylyl cyclase 1 (AC1), but not an AC5 inhibitor. We conclude that HNK rapidly potentiates SC-CA1 synaptic efficacy, which then stimulates priming mechanisms that persistently favor antidepressant-relevant plasticity. Targeting such priming mechanisms may be an effective antidepressant strategy, and using approaches such as our incubation model may aid in revealing novel pharmacological targets.

Micro-electrode array recording of extracellular electrical potentials of liquid static surface fermented Hericium erinaceus

Hericium erinaceus is a basidiomycetes fungus with previously uncharacterised extracellular electrophysiology. Here, we present results of recordings of the electrical potentials of fungal biofilms of this species using microelectrode arrays (MEAs). In particular, we focused on modelling the temporal and spatial progression of the low frequency (≤ 1 Hz) potentials. Culture media control studies showed that the electrical potential activity results from the growth and subsequent spiking behaviours of the mycelium extracellular matrices. An antifungal assay using nystatin suspension, 10,000 unit/mL in DPBS, provided evidence for the biological origin of electrical potentials due to targeting of the selective permeability of the cell membrane and subsequent cessation of electrical activity. Conversely, injection of L-glutamic acid increased the combined multi-channel mean firing rate from 0.04 Hz to 0.1 Hz. Analysis of bursting and spatial propagation of the extracellular signals are also presented.

Assessing Cross-Contamination in Spike-Sorted Electrophysiology Data.

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 (ISIv). 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 ISIv 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.

Multi-day neuron tracking in high-density electrophysiology recordings using earth mover’s distance

Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. Advances in high-density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here, we propose a neuron tracking method that can identify the same cells independent of firing statistics, that are used by most existing methods. Our method is based on between-day non-rigid alignment of spike-sorted clusters. We verified the same cell identity in mice using measured visual receptive fields. This method succeeds on datasets separated from 1 to 47 days, with an 84% average recovery rate.

Multi-day neuron tracking in high-density electrophysiology recordings using earth mover's distance.

Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. Advances in high-density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here, we propose a neuron tracking method that can identify the same cells independent of firing statistics, that are used by most existing methods. Our method is based on between-day non-rigid alignment of spike-sorted clusters. We verified the same cell identity in mice using measured visual receptive fields. This method succeeds on datasets separated from 1 to 47 days, with an 84% average recovery rate.

Variations in touch representation in the hummingbird and zebra finch forebrain

Somatosensation is essential for animals to perceive the external world through touch, allowing them to detect physical contact, temperature, pain, and body position. Studies on rodent vibrissae have highlighted the organization and processing in mammalian somatosensory pathways.1,2 Comparative research across vertebrates is vital for understanding evolutionary influences and ecological specialization on somatosensory systems. Birds, with their diverse morphologies, sensory abilities, and behaviors, serve as ideal models for investigating the evolution of somatosensation. Prior studies have uncovered tactile-responsive areas within the avian telencephalon, particularly in pigeons,3,4,5,6 parrots,7 and finches,8 but variations in somatosensory maps and responses across avian species are not fully understood. This study aims to explore somatotopic organization and neural coding in the telencephalon of Anna's hummingbirds (Calypte anna) and zebra finches (Taeniopygia guttata) by using invivo extracellular electrophysiology to record activity in response to controlled tactile stimuli on various body regions. These findings reveal unique representations of body regions across distinct forebrain somatosensory nuclei, indicating significant differences in the extent of areas dedicated to certain body surfaces, which may correlate with their behavioral importance.

Elevated fear states facilitate ventral hippocampal engagement of basolateral amygdala neuronal activity.

Fear memory formation and retention rely on the activation of distributed neural circuits. The basolateral amygdala (BLA) and ventral hippocampus (VH) in particular are two regions that support contextual fear memory processes and share reciprocal connections. The VH → BLA pathway is critical for increases in fear after initial learning, in both fear renewal following extinction learning and during fear generalization. This raises the possibility that functional changes in VH projections to the BLA support increases in learned fear. In line with this, fear can also be increased with alterations to the original content of the memory via reconsolidation, as in fear elevation procedures. However, very little is known about the functional changes in the VH → BLA pathway supporting reconsolidation-related increases in fear. In this study, we used in vivo extracellular electrophysiology to examine the functional neuronal changes within the BLA and in the VH → BLA pathway as a result of fear elevation and standard fear retrieval procedures. Elevated fear expression was accompanied by higher BLA spontaneous firing compared to a standard fear retrieval condition. Across a range of stimulation frequencies, we also found that VH stimulation evoked higher BLA firing following fear elevation compared to standard retrieval. These results suggest that fear elevation is associated with an increased capacity of the VH to drive neuronal activity in the BLA, highlighting a potential circuit involved in strengthening existing fear memories.

Extracellular electrophysiology on clonal human β-cell spheroids.

Pancreatic islets are important in nutrient homeostasis and improved cellular models of clonal origin may very useful especially in view of relatively scarce primary material. Close 3D contact and coupling between β-cells are a hallmark of physiological function improving signal/noise ratios. Extracellular electrophysiology using micro-electrode arrays (MEA) is technically far more accessible than single cell patch clamp, enables dynamic monitoring of electrical activity in 3D organoids and recorded multicellular slow potentials (SP) provide unbiased insight in cell-cell coupling. We have therefore asked whether 3D spheroids enhance clonal β-cell function such as electrical activity and hormone secretion using human EndoC-βH1, EndoC-βH5 and rodent INS-1 832/13 cells. Spheroids were formed either by hanging drop or proprietary devices. Extracellular electrophysiology was conducted using multi-electrode arrays with appropriate signal extraction and hormone secretion measured by ELISA. EndoC-βH1 spheroids exhibited increased signals in terms of SP frequency and especially amplitude as compared to monolayers and even single cell action potentials (AP) were quantifiable. Enhanced electrical signature in spheroids was accompanied by an increase in the glucose stimulated insulin secretion index. EndoC-βH5 monolayers and spheroids gave electrophysiological profiles similar to EndoC-βH1, except for a higher electrical activity at 3 mM glucose, and exhibited moreover a biphasic profile. Again, physiological concentrations of GLP-1 increased AP frequency. Spheroids also exhibited a higher secretion index. INS-1 cells did not form stable spheroids, but overexpression of connexin 36, required for cell-cell coupling, increased glucose responsiveness, dampened basal activity and consequently augmented the stimulation index. In conclusion, spheroid formation enhances physiological function of the human clonal β-cell lines and these models may provide surrogates for primary islets in extracellular electrophysiology.

A 3D In Vitro Cortical Tissue Model Based on Dense Collagen to Study the Effects of Gamma Radiation on Neuronal Function.

Studies on gamma radiation-induced injury have long been focused on hematopoietic, gastrointestinal, and cardiovascular systems, yet little is known about the effects of gamma radiation on the function of human cortical tissue. The challenge in studying radiation-induced cortical injury is, in part, due to a lack of human tissue models and physiologically relevant readouts. Here, a physiologically relevant 3Dcollagen-based cortical tissue model (CTM) is developed for studying the functional response of human iPSC-derived neurons and astrocytes to a sub-lethal radiation exposure (5Gy). Cytotoxicity, DNA damage, morphology, and extracellular electrophysiology are quantified. It is reported that 5Gy exposure significantly increases cytotoxicity, DNA damage, and astrocyte reactivity while significantly decreasing neurite length and neuronal network activity. Additionally, it is found that clinically deployed radioprotectant amifostine ameliorates the DNA damage, cytotoxicity, and astrocyte reactivity. The CTM provides a critical experimental platform to understand cell-level mechanisms by which gamma radiation (GR) affects human cortical tissue and to screen prospective radioprotectant compounds.

Adaptive frequency-domain filtering for neural signal preprocessing

Electrical interference from various sources is a common issue for experimental extracellular electrophysiology recordings collected using multi-electrode array neural recording systems. This interference deteriorates the signal-to-noise ratio (SNR) of the raw electrophysiology signals and hampers the accuracy of data post-processing using techniques such as spike-sorting. Traditional signal processing methods to digitally remove electrical interference during post-processing include bandpass filtering to limit the signal to the relevant spectral range of the biological data, e.g., the spikes band (300 Hz - 7 kHz), targeted notch filtering to remove power line interference from standard alternating current mains electricity and common reference removal to minimize noise common to all electrodes. These methods require a priori knowledge of the frequency of the interfering signal source to address the unique electromagnetic interference environment of each experimental setup. We discuss an adaptive method for automatically removing narrow-band electrical interference through a spectral peak detection and removal (SPDR) step that can be applied during post-processing of the recorded data, based on the intuition that tall, narrowband signals localized in the signal spectrum correspond to interference, rather than the activity of neurons. A spectral peak prominence (SPP) threshold is used to detect these peaks in the frequency domain, which will then be removed via notch filtering. We applied this method to simulated waveforms and also experimental electrophysiology data collected from cerebral organoids to demonstrate its effectiveness for removing unwanted interference without significantly distorting the neural signals. We discuss that proper selection of the SPP threshold is required to avoid over-filtering, which can result in distortion of the electrophysiology data. We also compare the firing-rate activity in the filtered electrophysiology with fluorescence calcium imaging, a secondary cellular activity marker, to quantify signal distortion and provide bounds on SNR-based optimization of the SPP threshold. The adaptive filtering technique demonstrated in this paper is a powerful method that can automatically detect and remove interband interference in recorded neural signals, potentially enabling data collection in more naturalistic settings where external interference signals are difficult to eliminate.

Adaptive octree meshes for simulation of extracellular electrophysiology

Objective. The interaction between neural tissues and artificial electrodes is crucial for understanding and advancing neuroscientific research and therapeutic applications. However, accurately modeling this space around the neurons rapidly increases the computational complexity of neural simulations. Approach. This study demonstrates a dynamically adaptive simulation method that greatly accelerates computation by adjusting spatial resolution of the simulation as needed. Use of an octree structure for the mesh, in combination with the admittance method for discretizing conductivity, provides both accurate approximation and ease of modification on-the-fly. Main results. In tests of both local field potential estimation and multi-electrode stimulation, dynamically adapted meshes achieve accuracy comparable to high-resolution static meshes in an order of magnitude less time. Significance. The proposed simulation pipeline improves model scalability, allowing greater detail with fewer computational resources. The implementation is available as an open-source Python module, providing flexibility and ease of reuse for the broader research community.

3D Functional Neuronal Networks in Free-Standing Bioprinted Hydrogel Constructs.

The composition, elasticity, and organization of the extracellular matrix within the central nervous system contribute to the architecture and function of the brain. From an in vitro modeling perspective, soft biomaterials are needed to mimic the 3D neural microenvironments. While many studies have investigated 3D culture and neural network formation in bulk hydrogel systems, these approaches have limited ability to position cells to mimic sophisticated brain architectures. In this study, cortical neurons and astrocytes acutely isolated from the brains of rats are bioprinted in a hydrogel to form 3D neuronal constructs. Successful bioprinting of cellular and acellular strands in a multi-bioink approach allows the subsequent formation of gray- and white-matter tracts reminiscent of cortical structures. Immunohistochemistry shows the formation of dense, 3D axon networks. Calcium signaling and extracellular electrophysiology in these 3D neuronal networks confirm spontaneous activity in addition to evoked activities under pharmacological and electrical stimulation. The system and bioprinting approaches are capable of fabricating soft, free-standing neuronal structures of different bioink and cell types with high resolution and throughput, which provide a promising platform for understanding fundamental questions of neural networks, engineering neuromorphic circuits, and for in vitro drug screening.

The impact of social defeat on basomedial amygdala neuronal activity in adult male rats

Social stressors negatively impact social function, and this is mediated by the amygdala across species. Social defeat stress is an ethologically relevant social stressor in adult male rats that increases social avoidance, anhedonia, and anxiety-like behaviors. While amygdala manipulations can mitigate the negative effects of social stressors, the impact of social defeat on the basomedial subregion of the amygdala is relatively unclear. Understanding the role of the basomedial amygdala may be especially important, as prior work has demonstrated that it drives physiological responses to stress, including heart-rate related responses to social novelty. In the present study, we quantified the impact of social defeat on social behavior and basomedial amygdala neuronal responses using anesthetized in vivo extracellular electrophysiology in adult male Sprague Dawley rats. Socially defeated rats displayed increased social avoidance behavior towards novel Sprague Dawley conspecifics and reduced time initiating social interactions relative to controls. This effect was most pronounced in rats that displayed defensive, boxing behavior during social defeat sessions. We next found that socially defeated rats showed lower overall basomedial amygdala firing and altered the distribution of neuronal responses relative to the control condition. We separated neurons into low and high Hz firing groups, and neuronal firing was reduced in both low and high Hz groups but in a slightly different manner. This work demonstrates that basomedial amygdala activity is sensitive to social stress, displaying a distinct pattern of social stress-driven activity relative to other amygdala subregions.

Transcriptomic cell type structures in vivo neuronal activity across multiple timescales

Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30min). We show that transcriptomic cell-class information is embedded in the timing of single neuron activity in the intact brain of behaving animals (calcium imaging and extracellular electrophysiology) as well as in a bio-realistic model of the visual cortex. Further, a subset of excitatory cell types are distinguishable but can be classified with higher accuracy when considering cortical layer and projection class. Finally, we show that computational fingerprints of cell types may be universalizable across structured stimuli and naturalistic movies. Our results indicate that transcriptomic class and type may be imprinted in the timing of single neuron activity across diverse stimuli.

Electrophysiology as a Tool to Decipher the Network Mechanism of Visceral Pain in Functional Gastrointestinal Disorders.

Abdominal pain, including visceral pain, is prevalent in functional gastrointestinal (GI) disorders (FGIDs), affecting the overall quality of a patient's life. Neural circuits in the brain encode, store, and transfer pain information across brain regions. Ascending pain signals actively shape brain dynamics; in turn, the descending system responds to the pain through neuronal inhibition. Pain processing mechanisms in patients are currently mainly studied with neuroimaging techniques; however, these techniques have a relatively poor temporal resolution. A high temporal resolution method is warranted to decode the dynamics of the pain processing mechanisms. Here, we reviewed crucial brain regions that exhibited pain-modulatory effects in an ascending and descending manner. Moreover, we discussed a uniquely well-suited method, namely extracellular electrophysiology, that captures natural language from the brain with high spatiotemporal resolution. This approach allows parallel recording of large populations of neurons in interconnected brain areas and permits the monitoring of neuronal firing patterns and comparative characterization of the brain oscillations. In addition, we discussed the contribution of these oscillations to pain states. In summary, using innovative, state-of-the-art methods, the large-scale recordings of multiple neurons will guide us to better understanding of pain mechanisms in FGIDs.

GRINtrode: a neural implant for simultaneous two-photon imaging and extracellular electrophysiology in freely moving animals.

In vivo imaging and electrophysiology are powerful tools to explore neuronal function that each offer unique complementary information with advantages and limitations. Capturing both data types from the same neural population in the freely moving animal would allow researchers to take advantage of the capabilities of both modalities and further understand how they relate to each other. Here, we present a head-mounted neural implant suitable for in vivo two-photon imaging of neuronal activity with simultaneous extracellular electrical recording in head-fixed or fiber-coupled freely moving animals. A gradient refractive index (GRIN) lens-based head-mounted neural implant with extracellular electrical recording provided by tetrodes on the periphery of the GRIN lens was chronically implanted. The design of the neural implant allows for recording from head-fixed animals, as well as freely moving animals by coupling the imaging system to a coherent imaging fiber bundle. We demonstrate simultaneous two-photon imaging of GCaMP and extracellular electrophysiology of neural activity in awake head-fixed and freely moving mice. Using the collected information, we perform correlation analysis to reveal positive correlation between optical and local field potential recordings. Simultaneously recording neural activity using both optical and electrical methods provides complementary information from each modality. Designs that can provide such bi-modal recording in freely moving animals allow for the investigation of neural activity underlying a broader range of behavioral paradigms.

Determination of tomato fruit life stages from long-term extracellular electrophysiology recordings

ISHS XXXI International Horticultural Congress (IHC2022): International Symposium on Integrative Approaches to Product Quality in Fruits and Vegetables Determination of tomato fruit life stages from long-term extracellular electrophysiology recordings

Diversity in spatial frequency, temporal frequency, and speed tuning across mouse visual cortical areas and layers.

The mouse visual system consists of several visual cortical areas thought to be specialized for different visual features and/or tasks. Previous studies have revealed differences between primary visual cortex (V1) and other higher visual areas, namely, anterolateral (AL) and posteromedial (PM), and their tuning preferences for spatial and temporal frequency. However, these differences have primarily been characterized using methods that are biased toward superficial layers of cortex, such as two-photon calcium imaging. Fewer studies have investigated cell types in deeper layers of these areas and their tuning preferences. Because superficial versus deep-layer neurons and different types of deep-layer neurons are known to have different feedforward and feedback inputs and outputs, comparing the tuning preferences of these groups is important for understanding cortical visual information processing. In this study, we used extracellular electrophysiology and two-photon calcium imaging targeted toward two different layer 5 cell classes to characterize their tuning properties in V1, AL, and PM. We find that deep-layer neurons, similar to superficial layer neurons, are also specialized for different spatial and temporal frequencies, with the strongest differences between AL and V1, and AL and PM, but not V1 and PM. However, we note that the deep-layer neuron populations preferred a larger range of SFs and TFs compared to previous studies. We also find that extratelencephalically projecting layer 5 neurons are more direction selective than intratelencephalically projecting layer 5 neurons.

Fiber photometry in striatum reflects primarily nonsomatic changes in calcium.

Fiber photometry enables recording of population neuronal calcium dynamics in awake mice. While the popularity of fiber photometry has grown in recent years, it remains unclear whether photometry reflects changes in action potential firing (that is, 'spiking') or other changes in neuronal calcium. In microscope-based calcium imaging, optical and analytical approaches can help differentiate somatic from neuropil calcium. However, these approaches cannot be readily applied to fiber photometry. As such, it remains unclear whether the fiber photometry signal reflects changes in somatic calcium, changes in nonsomatic calcium or a combination of the two. Here, using simultaneous in vivo extracellular electrophysiology and fiber photometry, along with in vivo endoscopic one-photon and two-photon calcium imaging, we determined that the striatal fiber photometry does not reflect spiking-related changes in calcium and instead primarily reflects nonsomatic changes in calcium.