Recordings Of Spontaneous Activity Research Articles

Chronic multiscale resolution of mouse brain networks using combined mesoscale cortical imaging and subcortical fiber photometry.

Genetically encoded optical probes to image calcium levels in neurons in vivo are used widely as a real-time measure of neuronal activity in the brain. Mesoscale calcium imaging through a cranial window provides a method of studying the interaction of circuit activity between cortical areas but lacks access to subcortical regions. We have developed an optical and surgical preparation that preserves wide-field imaging of the cortical surface while also permitting access to specific subcortical networks. This was achieved using an optical fiber implanted in the striatum, along with a bilateral widefield cranial window, enabling simultaneous mesoscale cortical imaging and subcortical fiber photometry recording of calcium signals in a transgenic animal expressing GCaMP. Subcortical signals were collected from the dorsal regions of the striatum. We combined this approach with multiple sensory-motor tasks, including specific auditory and visual stimulation, and video monitoring of animal movements and pupillometry during head-fixed behaviors. We found high correlations between cortical and striatal activity in response to sensory stimulation or movement. Furthermore, spontaneous activity recordings revealed that specific motifs of cortical activity are correlated with presynaptic activity recorded in the striatum, enabling us to select for corticostriatal activity motifs. We believe that this method can be utilized to reveal not only global patterns but also cell-specific connectivity that provides insight into corticobasal ganglia circuit organization.

Differences and Similarities in Spontaneous Activity Between Animal Models of Cancer-Induced Pain and Neuropathic Pain.

BackgroundClinical data on cancer-induced pain (CIP) demonstrate widespread changes in sensory function. It is characterized in humans not only by stimulus-invoked pain, but also by spontaneous pain. In our previous studies in an animal model of CIP, we observed changes in intrinsic membrane properties and excitability of dorsal root ganglion (DRG) sensory neurons corresponding to mechanical allodynia and hyperalgesia, of which abnormal activities of Aβ-fiber sensory neurons are consistent in a rat model of peripheral neuropathic pain (NEP).ObjectiveTo investigate whether there are related peripheral neural mechanisms between the CIP and NEP models of spontaneous pain, we compared the electrophysiological properties of DRG sensory neurons at 2–3 weeks after CIP and NEP model induction.MethodsCIP models were induced with metastasis tumour-1 rat breast cancer cells implanted into the distal epiphysis of the femur. NEP models were induced with a polyethylene cuff implanted around the sciatic nerve. Spontaneous pain in animals is measured by spontaneous foot lifting (SFL). After measurement of SFL, the animals were prepared for electrophysiological recordings of spontaneous activity (SA) in DRG neurons in vivo.ResultsOur data showed that SFL and SA occurred in both models. The proportion of SFL and SA of C-fiber sensory neurons in CIP was more significantly increased than in NEP models. There was no difference in duration of SFL and the rate of SA between the two models. The duration of SFL is related to the rate of SA in C-fiber in both models.ConclusionThus, SFL may result from SA activity in C-fiber neurons in CIP and NEP rats. The differences and similarities in spontaneous pain between CIP and NEP rats is related to the proportion and rate of SA in C-fibers, respectively.

Comparative microelectrode array data of the functional development of hPSC-derived and rat neuronal networks

We present a dataset of microelectrode array (MEA) recordings from human pluripotent stem cell (hPSC)-derived and rat embryonic cortical neurons during their in vitro maturation. The data were prepared to assess extracellularly recorded spontaneous activity and to compare the functional development of these neuronal networks. In addition to recordings of spontaneous activity, we provide pharmacological responses of hPSC-derived and rat cortical cultures at their mature stage. Together with the recorded electrode raw data, we share the analysis code to form a comprehensive dataset including spike times, spike waveforms, burst activity and network synchronization metrics calculated with two different connectivity estimators. Moreover, we provide the analysis code that produced the key scientific findings published previously with this dataset. This large dataset enables investigation of the functional aspects of maturing cortical neuronal networks and provides substantial parameters to assess the differences and similarities between hPSC-derived and rat cortical networks in vitro. This publicly available dataset will be beneficial, especially for experimental and computational neuroscientists.

Mouse Models of Osteoarthritis: A Summary of Models and Outcomes Assessment.

Osteoarthritis (OA) is a multidimensional health problem and a common chronic disease. It has a substantial impact on patient quality of life and is a common cause of pain and mobility issues in older adults. The functional limitations, lack of curative treatments, and cost to society all demonstrate the need for translational and clinical research. The use of OA models in mice is important for achieving a better understanding of the disease. Models with clinical relevance are needed to achieve 2 main goals: to assess the impact of the OA disease (pain and function) and to study the efficacy of potential treatments. However, few OA models include practical strategies for functional assessment of the mice. OA signs in mice incorporate complex interrelations between pain and dysfunction. The current review provides a comprehensive compilation of mouse models of OA and animal evaluations that include static and dynamic clinical assessment of the mice, merging evaluation of pain and function by using automatic and noninvasive techniques. These new techniques allow simultaneous recording of spontaneous activity from thousands of home cages and also monitor environment conditions. Technologies such as videography and computational approaches can also be used to improve pain assessment in rodents but these new tools must first be validated experimentally. An example of a new tool is the digital ventilated cage, which is an automated home-cage monitor that records spontaneous activity in the cages.

A Model of Epileptogenesis in Rhinal Cortex-Hippocampus Organotypic Slice Cultures.

Organotypic slice cultures have been widely used to model brain disorders and are considered excellent platforms for evaluating a drug's neuroprotective and therapeutic potential. Organotypic slices are prepared from explanted tissue and represent a complex multicellular ex vivo environment. They preserve the three-dimensional cytoarchitecture and local environment of brain cells, maintain the neuronal connectivity and the neuron-glia reciprocal interaction. Hippocampal organotypic slices are considered suitable to explore the basic mechanisms of epileptogenesis, but clinical research and animal models of epilepsy have suggested that the rhinal cortex, composed of perirhinal and entorhinal cortices, play a relevant role in seizure generation. Here, we describe the preparation of rhinal cortex-hippocampus organotypic slices. Recordings of spontaneous activity from the CA3 area under perfusion with complete growth medium, at physiological temperature and in the absence of pharmacological manipulations, showed that these slices depict evolving epileptic-like events throughout time in culture. Increased cell death, through propidium iodide uptake assay, and gliosis, assessed with fluorescence-coupled immunohistochemistry, was also observed. The experimental approach presented highlights the value of rhinal cortex-hippocampus organotypic slice cultures as a platform to study the dynamics and progression of epileptogenesis and to screen potential therapeutic targets for this brain pathology.

Functional and directed connectivity of the cortico-limbic network in mice in vivo

Higher cognitive processes and emotional regulation depend on densely interconnected telencephalic and limbic areas. Central structures of this cortico-limbic network are ventral hippocampus (vHC), medial prefrontal cortex (PFC), basolateral amygdala (BLA) and nucleus accumbens (NAC). Human and animal studies have revealed both anatomical and functional alterations in specific connections of this network in several psychiatric disorders. However, it is often not clear whether functional alterations within these densely interconnected brain areas are caused by modifications in the direct pathways, or alternatively through indirect interactions. We performed multi-site extracellular recordings of spontaneous activity in three different brain regions to study the functional connectivity in the BLA–NAC–PFC–vHC network of the lightly anesthetized mouse in vivo. We show that BLA, NAC, PFC and vHC are functionally connected in distinct frequency bands and determined the influence of a third brain region on this connectivity. In addition to describing mutual synchronicity, we determined the strength of functional connectivity for each region in the BLA–NAC–PFC–vHC network. We find a region-specificity in the strength of feedforward and feedback connections for each region in its interaction with other areas in the network. Our results provide insights into functional and directed connectivity in the cortico-limbic network of adult wild-type mice, which may be helpful to further elucidate the pathophysiological changes of this network in psychiatric disorders and to develop target-specific therapeutic interventions.

Magnesium-based biodegradable microelectrodes for neural recording.

This article reports fabrication, characterization, degradation and electrical properties of biodegradable magnesium (Mg) microwires coated with two functional polymers, and the first in vivo evidence on the feasibility of Mg-based biodegradable microelectrodes for neural recording. Conductive poly(3,4‑ethylenedioxythiophene) (PEDOT) coating was first electrochemically deposited onto Mg microwire surface, and insulating biodegradable poly(glycerol sebacate) (PGS) was then spray-coated onto PEDOT surface to improve the overall properties of microelectrode. The assembled PGS/PEDOT-coated Mg microelectrodes showed high homogeneity in coating thickness, surface morphology and composition before and after in vivo recording. The charge storage capacity (CSC) of PGS/PEDOT-coated Mg microwire (1.72mC/cm2) was nearly 5 times higher than the standard platinum (Pt) microwire widely used in implantable electrodes. The Mg-based microelectrode demonstrated excellent neural-recording capability and stability during in vivo multi-unit neural recordings in the auditory cortex of a mouse. Specifically, the Mg-based electrode showed clear and stable onset response, and excellent signal-to-noise ratio during spontaneous-activity recordings and three repeats of stimulus-evoked recordings at two different anatomical locations in the auditory cortex. During 10days of immersion in artificial cerebrospinal fluid (aCSF) in vitro, PGS/PEDOT-coated Mg microelectrodes showed slower degradation and less change in impedance than PEDOT-coated Mg electrodes. The biodegradable PGS coating protected the PEDOT coating from delamination, and prolonged the mechanical integrity and electrical properties of Mg-based microelectrode. Mg-based novel microelectrodes should be further studied toward clinical translation because they can potentially eliminate the risks and costs associated with secondary surgeries for removal of failed or no longer needed electrodes.

Neuronal Spatial Arrangement Shapes Effective Connectivity Traits of in vitro Cortical Networks

We studied effective connectivity in rat cortical cultures with various degrees of spatial aggregation, ranging from homogeneous networks to highly aggregated ones. We considered small cultures 3 mm in diameter and that contained about 2;000 neurons. Spatial inhomogeneity favored an increase of metric correlations and connectivity among neighboring neurons. Effective connectivity was determined from spontaneous activity recordings using calcium fluorescence imaging. We used generalized transfer entropy as tool to infer the effective connectivity. We carried out numerical simulations to build networks that mimicked the experimental ones and to test the reliability of the connectivity-inference algorithm. Effective connectivity traits were investigated during the development of the cultures over two weeks, and along the gradual blockade of excitatory connections through CNQX. We observed that the average effective connectivity rapidly increased during culture development. At day in vitro (DIV) 15 the average excitatory in-degree was measured as ≃k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</sup> 50 for homogeneous and semi aggregated networks, and ≃k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</sup> 120 for aggregated ones, and with 20 percent inhibition. Aggregated cultures exhibited assortative traits and a high resilience to chemical damage, while the other cultures were dissassortative or neutral, and less resilient. Our work illustrates the role of metric correlations in spatially embedded networks in shaping connectivity and activity traits in living neuronal networks.

Average proportional consecutive interval difference accurately differentiates spontaneous activity from motor unit potentials.

An objective method is required to detect spontaneous activity (SA) for prevalence studies in needle electromyography (EMG). Because of frequent similarities in the morphology of SA and motor unit potentials (MUP), identification of SA depends on assessment of firing regularity, which has not yet been quantitated through a modern interface. Prospective recordings obtained from patients referred for electrodiagnostic evaluation were analyzed by using decomposition-based quantitative EMG (DQEMG) customized to calculate descriptive statistics. Forty-four MUP recordings (39 participants) and 80 SA recordings (62 participants) were analyzed. One hundred one of 124 recordings successfully interfaced with DQEMG. The remaining recordings were analyzed in Audacity. Average proportional consecutive interval differences differentiated SA from MUPs with 97.5% sensitivity (confidence interval [CI] 91.3%-99.7%) and 100.0% specificity (CI 92%-100%). There was substantial overlap, however, for SD and mean consecutive differences. Average proportional consecutive interval difference accurately differentiates SA from MUPs and may be useful in future prevalence studies of SA.

The neuron-specific interleukin-1 receptor accessory protein alters emergent network state properties in Vitro

Small in vitro neuronal/glial networks exhibit sleep-like states. Sleep regulatory substance interleukin-1β (IL1) signals via its type I receptor and a receptor accessory protein (AcP). AcP has a neuron-specific isoform called AcPb. After sleep deprivation, AcPb, but not AcP, upregulates in brain, and mice lacking AcPb lack sleep rebound. Herein we used action potentials (APs), AP burstiness, synchronization of electrical activity (SYN), and delta wave (0.5–3.75 Hz) power to characterize cortical culture network state. Homologous parameters are used in vivo to characterize sleep. Cortical cells from 1–2-day-old pups from AcP knockout (KO, lacking both AcP and AcPb), AcPb KO (lacking only AcPb), and wild type (WT) mice were cultured separately on multi-electrode arrays. Recordings of spontaneous activity were taken each day during days 4–14 in vitro. In addition, cultures were treated with IL1, or in separate experiments, stimulated electrically to determine evoked response potentials (ERPs). In AcP KO cells, the maturation of network properties accelerated compared to those from cells lacking only AcPb. In contrast, the lack of AcPb delayed spontaneous network emergence of sleep-linked properties. The addition of IL1 enhanced delta wave power in WT cells but not in AcP KO or AcPb KO cells. The ontology of electrically-induced ERPs was delayed in AcP KO cells. We conclude IL1 signaling has a critical role in the emergence of sleep-linked network behavior with AcP playing a dominant role in the slowing of development while AcPb enhances development rates of sleep-linked emergent network properties.

All-Optical Electrophysiology for High-Throughput Functional Characterization of a Human iPSC-Derived Motor Neuron Model of ALS.

SummaryHuman induced pluripotent stem cell (iPSC)-derived neurons are an attractive substrate for modeling disease, yet the heterogeneity of these cultures presents a challenge for functional characterization by manual patch-clamp electrophysiology. Here, we describe an optimized all-optical electrophysiology, “Optopatch,” pipeline for high-throughput functional characterization of human iPSC-derived neuronal cultures. We demonstrate the method in a human iPSC-derived motor neuron (iPSC-MN) model of amyotrophic lateral sclerosis (ALS). In a comparison of iPSC-MNs with an ALS-causing mutation (SOD1 A4V) with their genome-corrected controls, the mutants showed elevated spike rates under weak or no stimulus and greater likelihood of entering depolarization block under strong optogenetic stimulus. We compared these results with numerical simulations of simple conductance-based neuronal models and with literature results in this and other iPSC-based models of ALS. Our data and simulations suggest that deficits in slowly activating potassium channels may underlie the changes in electrophysiology in the SOD1 A4V mutation.

Polyimide-based 3D microelectrode arrays for in vitro testing of human 3D engineered neural tissues

Polyimide-based 3D microelectrode arrays for in vitro testing of human 3D engineered neural tissues

Effect of substrate coating material on spontaneous activity of human-induced pluripotent stem cell-derived neuronal stem cells

Effect of substrate coating material on spontaneous activity of human-induced pluripotent stem cell-derived neuronal stem cells

Uncorrelated Neural Firing in Mouse Visual Cortex during Spontaneous Retinal Waves.

Synchronous firing among the elements of forming circuits is critical for stabilization of synapses. Understanding the nature of these local network interactions during development can inform models of circuit formation. Within cortex, spontaneous activity changes throughout development. Unlike the adult, early spontaneous activity occurs in discontinuous population bursts separated by long silent periods, suggesting a high degree of local synchrony. However, whether the micro-patterning of activity within early bursts is unique to this early age and specifically tuned for early development is poorly understood, particularly within the column. To study this we used single-shank multi-electrode array recordings of spontaneous activity in the visual cortex of non-anesthetized neonatal mice to quantify single-unit firing rates, and applied multiple measures of network interaction and synchrony throughout the period of map formation and immediately after eye-opening. We find that despite co-modulation of firing rates on a slow time scale (hundreds of ms), the number of coactive neurons, as well as pair-wise neural spike-rate correlations, are both lower before eye-opening. In fact, on post-natal days (P)6–9 correlated activity was lower than expected by chance, suggesting active decorrelation of activity during early bursts. Neurons in lateral geniculate nucleus developed in an opposite manner, becoming less correlated after eye-opening. Population coupling, a measure of integration in the local network, revealed a population of neurons with particularly strong local coupling present at P6–11, but also an adult-like diversity of coupling at all ages, suggesting that a neuron’s identity as locally or distally coupled is determined early. The occurrence probabilities of unique neuronal “words” were largely similar at all ages suggesting that retinal waves drive adult-like patterns of co-activation. These findings suggest that the bursts of spontaneous activity during early visual development do not drive hyper-synchronous activity within columns. Rather, retinal waves provide windows of potential activation during which neurons are active but poorly correlated, adult-like patterns of correlation are achieved soon after eye-opening.

A Machine Learning Based Approach to Control Network Activity

A Machine Learning Based Approach to Control Network Activity

Stand-alone MEA device for medium-throughput testing of 3D engineered neural tissue

Stand-alone MEA device for medium-throughput testing of 3D engineered neural tissue

Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays.

Cultured neurons on multi electrode arrays (MEAs) have been widely used to study various aspects of neuronal (network) functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to enable directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the designs' functionality, however, suggested room for further improvement. We designed a two chamber MEA aiming to create a unidirectional connection between the networks in both chambers (“emitting” and “receiving”). To achieve this unidirectionality, all interconnecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber). Visual inspection showed that axons predominantly grew through the channels in the promoted direction. This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (i.e., a one-chamber-only burst) in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber.

Endogenous sequential cortical activity evoked by visual stimuli.

Although the functional properties of individual neurons in primary visual cortex have been studied intensely, little is known about how neuronal groups could encode changing visual stimuli using temporal activity patterns. To explore this, we used in vivo two-photon calcium imaging to record the activity of neuronal populations in primary visual cortex of awake mice in the presence and absence of visual stimulation. Multidimensional analysis of the network activity allowed us to identify neuronal ensembles defined as groups of cells firing in synchrony. These synchronous groups of neurons were themselves activated in sequential temporal patterns, which repeated at much higher proportions than chance and were triggered by specific visual stimuli such as natural visual scenes. Interestingly, sequential patterns were also present in recordings of spontaneous activity without any sensory stimulation and were accompanied by precise firing sequences at the single-cell level. Moreover, intrinsic dynamics could be used to predict the occurrence of future neuronal ensembles. Our data demonstrate that visual stimuli recruit similar sequential patterns to the ones observed spontaneously, consistent with the hypothesis that already existing Hebbian cell assemblies firing in predefined temporal sequences could be the microcircuit substrate that encodes visual percepts changing in time.

Self-organized criticality in cortical assemblies occurs in concurrent scale-free and small-world networks.

The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different ‘connectivity rules’ drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime.

Robust Discovery of Temporal Structure in Multi-neuron Recordings Using Hopfield Networks

Abstract We present here a novel method for the classical task of extracting reoccurring spatiotemporal patterns from spiking activity of large populations of neurons. In contrast to previous studies that mainly focus on synchrony detection or exactly recurring binary patterns, we perform the search in an approximate way that clusters together nearby, noisy network states in the data. Our approach is to use minimum probability flow (MPF) parameter estimation to determinis- tically fit very large Hopfield networks on windowed spike trains obtained from recordings of spontaneous activity of neurons in cat visual cortex. Examining the structure of the network memories over the spiking activity after training, we find that the networks robustly discover long-range temporal correlations. Specifically, the recurrent network dynamics denoise and group together windowed spike patterns, revealing underlying structure such as cell assemblies. We first demonstrate this by computing an analogy to spike triggered averages that we call memory triggered averages (MTAs). MTAs are obtained by averaging raw spike train windows that converge under the network dynamics to the same memory. The MTAs reveal promi- nent repeating patterns in the data that are difficult to detect with standard methods such as PCA. Additionally, when memories are collected over eight disjoint epochs in 280 seconds of windowed spiking activity from 50 neurons, their counts are nearly identical and the networks store significantly more memories than would be possible if trained on random patterns.