Publications

Mechanical forces are increasingly recognized as major regulators of several physiological processes at both the molecular and cellular level; therefore, a deep understanding of the sensing of these forces and their conversion into electrical signals are essential for studying the mechanosensitive properties of soft biological tissues. To contribute to this field, we present a dual-purpose device able to mechanically stimulate retinal tissue and to record the spiking activity of retinal ganglion cells (RGCs). This new instrument relies on combining ferrule-top micro-indentation, which provides local measurements of viscoelasticity, with high-density multi-electrode array (HD-MEAs) to simultaneously record the spontaneous activity of the retina. In this paper, we introduce this instrument, describe its technical characteristics, and present a proof-of-concept experiment that shows how RGC spiking activity of explanted mice retinas respond to mechanical micro-stimulations of their photoreceptor layer. The data suggest that, under specific conditions of indentation, the retina perceive the mechanical stimulation as modulation of the visual input, besides the longer time-scale of activation, and the increase in spiking activity is not only localized under the indentation probe, but it propagates across the retinal tissue.

Accurate estimation of interactions in neuronal circuits is critical in understanding neural information processing and the neuronal dynamics of emergent networks. Transfer entropy(TE) is a model-free information theoretic measure of flow of information between two random processes. TE has recently gained much popularity due to its effectiveness in estimating effective connectivity among neurons from simulated networks. However, experimental recordings inherently lack the ground truth information of neural connectivity - making it difficult to identify true connections from spurious connections. To tackle this problem, we present a superimposition method where the estimated connectivity is superimposed onto the spatial firing density plot. The firing density plot, on itself, does not provide connectivity information but we assume that frequently firing channels are more likely to have more active interactions. A neuron's firing depends on the presynaptic inputs, and highly interconnected neurons tend to have more presynaptic inputs resulting in more frequent firing. The firing density plot is organised in a spatial layout, which corresponds substantially to the structural layout. We demonstrated that the connectivity estimated closely corresponds to the firing density plot when superimposed onto the firing density plot. To strengthen the arguement, we analyse the firing count and the connectivity inferred for each randomly sampled channel and found a positively correlated relationship.

A major goal in the stem cell field is to generate tissues that can be utilized as a universal tool for in vitro models of development and disease, drug development, or as a resource for patients suffering from disease or injury. Great efforts are being made to differentiate human pluripotent stem cells in vitro toward retinal tissue, which is akin to native human retina in its cytoarchitecture and function, yet the numerous existing retinal induction protocols remain variable in their efficiency and do not routinely produce morphologically or functionally mature photoreceptors. Herein, we determine the impact that the method of embryoid body (EB) formation and maintenance as well as cell line background has on retinal organoid differentiation from human embryonic stem cells and human induced pluripotent stem cells. Our data indicate that cell line-specific differences dominate the variables that underline the differentiation efficiency in the early stages of differentiation. In contrast, the EB generation method and maintenance conditions determine the later differentiation and maturation of retinal organoids. Of the latter, the mechanical method of EB generation under static conditions, accompanied by media supplementation with Y27632 for the first 48 hours of differentiation, results in the most consistent formation of laminated retinal neuroepithelium containing mature and electrophysiologically responsive photoreceptors. Collectively, our data provide substantive evidence for stage-specific differences in the ability to give rise to laminated retinae, which is determined by cell line-specific differences in the early stages of differentiation and EB generation/organoid maintenance methods at later stages.

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Tissue specific extracellular matrices (ECM) provide structural support and enable access to molecular signals and metabolites, which are essential for directing stem cell renewal and differentiation. To mimic this phenomenon in vitro, tissue decellularisation approaches have been developed, resulting in the generation of natural ECM scaffolds that have comparable physical and biochemical properties of the natural tissues and are currently gaining traction in tissue engineering and regenerative therapies due to the ease of standardised production, and constant availability. In this manuscript we report the successful generation of decellularised ECM-derived peptides from neural retina (decel NR) and retinal pigment epithelium (decel RPE), and their impact on differentiation of human pluripotent stem cells (hPSCs) to retinal organoids. We show that culture media supplementation with decel RPE and RPE-conditioned media (CM RPE) significantly increases the generation of rod photoreceptors, whilst addition of decel NR and decel RPE significantly enhances ribbon synapse marker expression and the light responsiveness of retinal organoids. Photoreceptor maturation, formation of correct synapses between retinal cells and recording of robust light responses from hPSC-derived retinal organoids remain unresolved challenges for the field of regenerative medicine. Enhanced rod photoreceptor differentiation, synaptogenesis and light response in response to addition of decellularised matrices from RPE and neural retina as shown herein provide a novel and substantial advance in generation of retinal organoids for drug screening, tissue engineering and regenerative medicine.

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Retinal ganglion cells, the sole output neurons of the retina, exhibit surprising diversity. A recent study reported over 30 distinct types in the mouse retina, indicating that the processing of visual information is highly parallelised in the brain. The advent of high density multi-electrode arrays now enables recording from many hundreds to thousands of neurons from a single retina. Here we describe a method for the automatic classification of large-scale retinal recordings using a simple stimulus paradigm and a spike train distance measure as a clustering metric. We evaluate our approach using synthetic spike trains, and demonstrate that major known cell types are identified in high-density recording sessions from the mouse retina with around 1,000 retinal ganglion cells. A comparison across different retinas reveals substantial variability between preparations, suggesting pooling data across retinas should be approached with caution. As a parameter-free method, our approach is broadly applicable for cellular physiological classification in all sensory modalities.

Fast ripples (FRs; activity of >250 Hz) have been considered as a biomarker of epileptic activity in the hippocampus and entorhinal cortex; it is thought that they signal the focus of seizure generation. Similar high-frequency network activity has been produced in vitro by changing extracellular medium composition, by using pro-epileptic substances, or by electrical stimulation. Here we study the propagation of these events between different subregions of the male rat hippocampus in a recently introduced experimental model of FRs in entorhinal cortex–hippocampal slices in vitro. By using a matrix of 4096 microelectrodes, the sites of initiation, propagation pathways, and spatiotemporal characteristics of activity patterns could be studied with unprecedented high resolution. To this end, we developed an analytic tool based on bidimensional current source density estimation, which delimits sinks and sources with a high precision and evaluates their trajectories using the concept of center of mass. With this methodology, we found that FRs can arise almost simultaneously at noncontiguous sites in the CA3-to-CA1 direction, underlying the spatial heterogeneity of epileptogenic foci, while continuous somatodendritic waves of activity develop. An unexpected, yet important propagation route is the propagation of activity from CA3 into the hilus and dentate gyrus. This pathway may cause reverberating activation of both regions, supporting sustained pathological network events and altered information processing in hippocampal networks.

Mutations in pre-mRNA processing factors (PRPFs) cause autosomal-dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed genes cause non-syndromic retinal disease. Here, we generate transcriptome profiles from RP11 (PRPF31-mutated) patient-derived retinal organoids and retinal pigment epithelium (RPE), as well as Prpf31^+/− mouse tissues, which revealed that disrupted alternative splicing occurred for specific splicing programmes. Mis-splicing of genes encoding pre-mRNA splicing proteins was limited to patient-specific retinal cells and Prpf31^+/− mouse retinae and RPE. Mis-splicing of genes implicated in ciliogenesis and cellular adhesion was associated with severe RPE defects that include disrupted apical – basal polarity, reduced trans-epithelial resistance and phagocytic capacity, and decreased cilia length and incidence. Disrupted cilia morphology also occurred in patient-derived photoreceptors, associated with progressive degeneration and cellular stress. In situ gene editing of a pathogenic mutation rescued protein expression and key cellular phenotypes in RPE and photoreceptors, providing proof of concept for future therapeutic strategies.

Functional-effective connectivity and network topology are nowadays key issues for studying brain physiological functions and pathologies. Inferring neuronal connectivity from electrophysiological recordings presents open challenges and unsolved problems. In this work, we present a cross-correlation based method for reliably estimating not only excitatory but also inhibitory links, by analyzing multi-unit spike activity from large-scale neuronal networks. The method is validated by means of realistic simulations of large-scale neuronal populations. New results related to functional connectivity estimation and network topology identification obtained by experimental electrophysiological recordings from high-density and large-scale (i.e., 4096 electrodes) microtransducer arrays coupled to in vitro neural populations are presented. Specifically, we show that: (i) functional inhibitory connections are accurately identified in in vitro cortical networks, providing that a reasonable firing rate and recording length are achieved; (ii) small-world topology, with scale-free and rich-club features are reliably obtained, on condition that a minimum number of active recording sites are available. The method and procedure can be directly extended and applied to in vivo multi-units brain activity recordings.

The ability to monitor electrogenic cells accurately plays a pivotal role in neuroscience, cardiology and cell biology. Despite pioneering research and long-lasting efforts, the existing methods for intracellular recording of action potentials on the large network scale suffer limitations that prevent their widespread use. Here, we introduce the concept of a meta-electrode, a planar porous electrode that mimics the optical and biological behaviour of three-dimensional plasmonic antennas but also preserves the ability to work as an electrode. Its synergistic combination with plasmonic optoacoustic poration allows commercial complementary metal–oxide semiconductor multi-electrode arrays to record intracellular action potentials in large cellular networks. We apply this approach to measure signals from human-induced pluripotent stem cell-derived cardiac cells, rodent primary cardiomyocytes and immortalized cell types and demonstrate the possibility of non-invasively testing a variety of relevant drugs. Due to its robustness and easiness of use, we expect the method will be rapidly adopted by the scientific community and by pharmaceutical companies.

Microelectrode array (MEA) systems with up to several thousands of recording electrodes and electrical or optical stimulation capabilities are commercially available or described in the literature. By exploiting their submillisecond and micrometric temporal and spatial resolutions to record bioelectrical signals, such emerging MEA systems are increasingly used in neuroscience to study the complex dynamics of neuronal networks and brain circuits. However, they typically lack the capability of implementing real-time feedback between the detection of neuronal spiking events and stimulation, thus restricting large-scale neural interfacing to open-loop conditions. In order to exploit the potential of such large-scale recording systems and stimulation, we designed and validated a fully reconfigurable FPGA-based processing system for closed-loop multichannel control. By adopting a Xilinx Zynq-all-programmable system on chip that integrates reconfigurable logic and a dual-core ARM-based processor on the same device, the proposed platform permits low-latency preprocessing (filtering and detection) of spikes acquired simultaneously from several thousands of electrode sites. To demonstrate the proposed platform, we tested its performances through ex vivo experiments on the mice retina using a state-of-the-art planar high-density MEA that samples 4096 electrodes at 18 kHz and record light-evoked spikes from several thousands of retinal ganglion cells simultaneously. Results demonstrate that the platform is able to provide a total latency from whole-array data acquisition to stimulus generation below 2 ms. This opens the opportunity to design closed-loop experiments on neural systems and biomedical applications using emerging generations of planar or implantable large-scale MEA systems.

The availability of in vitro models of the human retina in which to perform pharmacological and toxicological studies is an urgent and unmet need. An essential step for developing in vitro models of human retina is the ability to generate laminated, physiologically functional, and light-responsive retinal organoids from renewable and patient specific sources. We investigated five different human-induced pluripotent stem cell (iPSC) lines and showed a significant variability in their efficiency to generate retinal organoids. Despite this variability, by month 5 of differentiation, all iPSC-derived retinal organoids were able to generate light responses, albeit immature, comparable to the earliest light responses recorded from the neonatal mouse retina, close to the period of eye opening. All iPSC-derived retinal organoids exhibited at this time a well-formed outer nuclear like layer containing photoreceptors with inner segments, connecting cilium, and outer like segments. The differentiation process was highly dependent on seeding cell density and nutrient availability determined by factorial experimental design. We adopted the differentiation protocol to a multiwell plate format, which enhanced generation of retinal organoids with retinal-pigmented epithelium (RPE) and improved ganglion cell development and the response to physiological stimuli. We tested the response of iPSC-derived retinal organoids to Moxifloxacin and showed that similarly to in vivo adult mouse retina, the primary affected cell types were photoreceptors. Together our data indicate that light responsive retinal organoids derived from carefully selected and differentiation efficient iPSC lines can be generated at the scale needed for pharmacology and drug screening purposes.

Spike train synchrony estimation of neuronal cultures provides valuable insights into firing patterns of neurons in terms of degree of similarity or dissimilarity. These estimations have proven to be a useful tool in neuroscience since synchrony in neuronal networks is thought to be related to cognitive processes, sensory awareness, learning and neurological disorders. Many mathematical measures have been developed to quantify the degree of synchrony. These synchrony metrics are generally used for smaller sets of spike trains and not been explored for larger High Density Multi Electrode Arrays (HD-MEA) datasets with thousands of channels. Here, bivariate and multivariate ISI-distance and SPIKE-distance metrics are utilized on both synthetic and experimental HD-MEA datasets to quantify spike train synchrony. It is demonstrated that, despite the significant size of the datasets, the approaches are effective in identifying and quantifying interesting bursting or change in spike train behaviours which are not always obvious from the raster plot.

Mutations in PRoline-Rich Transmembrane protein 2 (PRRT2) underlie a group of paroxysmal disorders including epilepsy, kinesigenic dyskinesia and migraine. Most of the mutations lead to impaired PRRT2 expression and/or function, emphasizing the pathogenic role of the PRRT2 deficiency. In this work, we investigated the phenotype of primary hippocampal neurons obtained from mouse embryos in which the PRRT2 gene was constitutively inactivated. Although PRRT2 is expressed by both excitatory and inhibitory neurons, its deletion decreases the number of excitatory synapses without significantly affecting the number of inhibitory synapses or the nerve terminal ultrastructure. Analysis of synaptic function in primary PRRT2 knockout excitatory neurons by live imaging and electrophysiology showed slowdown of the kinetics of exocytosis, weakened spontaneous and evoked synaptic transmission and markedly increased facilitation. Inhibitory neurons showed strengthening of basal synaptic transmission, accompanied by faster depression. At the network level these complex synaptic effects resulted in a state of heightened spontaneous and evoked activity that was associated with increased excitability of excitatory neurons in both PRRT2 knockout primary cultures and acute hippocampal slices. The data indicate the existence of network instability/hyperexcitability as the possible basis of the paroxysmal phenotypes associated with PRRT2 mutations.

Neuronal responses to external stimuli vary from trial to trial partly because they depend on continuous spontaneous variations of the state of neural circuits, reflected in variations of ongoing activity prior to stimulus presentation. Understanding how post-stimulus responses relate to the pre-stimulus spontaneous activity is thus important to understand how state dependence affects information processing and neural coding, and how state variations can be discounted to better decode single-trial neural responses. Here we exploited high-resolution CMOS electrode arrays to record simultaneously from thousands of electrodes in in-vitro cultures stimulated at specific sites. We used information-theoretic analyses to study how ongoing activity affects the information that neuronal responses carry about the location of the stimuli. We found that responses exhibited state dependence on the time between the last spontaneous burst and the stimulus presentation and that the dependence could be described with a linear model. Importantly, we found that a small number of selected neurons carry most of the stimulus information and contribute to the state-dependent information gain. This suggests that a major value of large-scale recording is that it individuates the small subset of neurons that carry most information and that benefit the most from knowledge of its state dependence.

In the mammalian retina, horizontal cells receive glutamatergic inputs from many rod and cone photoreceptors and return feedback signals to them, thereby changing photoreceptor glutamate release in a light-dependent manner. Horizontal cells also provide feedforward signals to bipolar cells. It is unclear, however, how horizontal cell signals also affect the temporal, spatial, and contrast tuning in retinal output neurons, the ganglion cells. To study this, we generated a genetically modified mouse line in which we eliminated the light dependency of feedback by deleting glutamate receptors from mouse horizontal cells. This genetic modification allowed us to investigate the impact of horizontal cells on ganglion cell signaling independent of the actual mode of feedback in the outer retina and without pharmacological manipulation of signal transmission. In control and genetically modified mice (both sexes), we recorded the light responses of transient OFF-α retinal ganglion cells in the intact retina. Excitatory postsynaptic currents (EPSCs) were reduced and the cells were tuned to lower temporal frequencies and higher contrasts, presumably because photoreceptor output was attenuated. Moreover, receptive fields of recorded cells showed a significantly altered surround structure. Our data thus suggest that horizontal cells are responsible for adjusting the dynamic range of retinal ganglion cells and, together with amacrine cells, contribute to the center/surround organization of ganglion cell receptive fields in the mouse.

Substrate-integrated multielectrode arrays (MEAs) enable multisite, long-term, and label-free sensing and actuation of neuronal electrical signals in reduced cell culture models for network electrophysiology. Conventional, thin-film fabricated passive MEAs typically provide a few tens of electrode sites. New generations of active CMOS-based high-resolution arrays provide the capabilities of simultaneous recordings from thousands of neurons over fields of view of several square millimeters, yet allowing extracellular electrical imaging to be achieved down to the subcellular scale. In turn, such advancement in chip-based electrical readouts can significantly complement recently developed biotechnological and bimolecular techniques for neurobiology applications. Here, we describe (1) a simple method to fabricate passive MEAs and (2) protocols for preparing and growing primary rat hippocampal neuronal cultures and human iPS-derived neurons on MEAs. The aim is to provide reliable protocols for initiating the reader to this technology and for stimulating their further development and experimental use in neurobiology.

Individuals with 22q11.2 microdeletion syndrome (22q11.2 DS) show cognitive and behavioral dysfunctions, developmental delays in childhood and risk of developing schizophrenia and autism. Despite extensive previous studies in adult animal models, a possible embryonic root of this syndrome has not been determined. Here, in neurons from a 22q11.2 DS mouse model (Lgdel^+/−), we found embryonic-premature alterations in the neuronal chloride cotransporters indicated by dysregulated NKCC1 and KCC2 protein expression levels. We demonstrate with large-scale spiking activity recordings a concurrent deregulation of the spontaneous network activity and homeostatic network plasticity. Additionally, Lgdel^+/− networks at early development show abnormal neuritogenesis and void of synchronized spontaneous activity. Furthermore, parallel experiments on Dgcr8^+/− mouse cultures reveal a significant, yet not exclusive contribution of the dgcr8 gene to our phenotypes of Lgdel^+/− networks. Finally, we show that application of bumetanide, an inhibitor of NKCC1, significantly decreases the hyper-excitable action of GABA_A receptor signaling and restores network homeostatic plasticity in Lgdel^+/− networks. Overall, by exploiting an on-a-chip 22q11.2 DS model, our results suggest a delayed GABA-switch in Lgdel^+/− neurons, which may contribute to a delayed embryonic development. Prospectively, acting on the GABA-polarity switch offers a potential target for 22q11.2 DS therapeutic intervention.

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SpiCoDyn, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SpiCoDyn processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SpiCoDyn is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

Nanoparticles (NPs) are increasingly used in biomedical applications, but the factors that influence their interactions with living cells need to be elucidated. Here, we reveal the role of NP surface charge in determining their neuronal interactions and electrical responses. We discovered that negatively charged NPs administered at low concentration (10 nM) interact with the neuronal membrane and at the synaptic cleft, whereas positively and neutrally charged NPs never localize on neurons. This effect is shape and material independent. The presence of negatively charged NPs on neuronal cell membranes influences the excitability of neurons by causing an increase in the amplitude and frequency of spontaneous postsynaptic currents at the single cell level and an increase of both the spiking activity and synchronous firing at neural network level. The negatively charged NPs exclusively bind to excitable neuronal cells, and never to nonexcitable glial cells. This specific interaction was also confirmed by manipulating the electrophysiological activity of neuronal cells. Indeed, the interaction of negatively charged NPs with neurons is either promoted or hindered by pharmacological suppression or enhancement of the neuronal activity with tetrodotoxin or bicuculline, respectively. We further support our main experimental conclusions by using numerical simulations. This study demonstrates that negatively charged NPs modulate the excitability of neurons, revealing the potential use of NPs for controlling neuron activity.

Neurotoxicity and the accumulation of extracellular amyloid-beta_1–42 (Aβ) peptides are associated with the development of Alzheimer’s disease (AD) and correlate with neuronal activity and network dysfunctions, ultimately leading to cellular death. However, research on neurodegenerative diseases is hampered by the paucity of reliable readouts and experimental models to study such functional decline from an early onset and to test rescue strategies within networks at cellular resolution. To overcome this important obstacle, we demonstrate a simple yet powerful in vitro AD model based on a rat hippocampal cell culture system that exploits large-scale neuronal recordings from 4096-electrodes on CMOS-chips for electrophysiological quantifications. This model allows us to monitor network activity changes at the cellular level and to uniquely uncover the early activity-dependent deterioration induced by Aβ-neurotoxicity. We also demonstrate the potential of this in vitro model to test a plausible hypothesis underlying the Aβ-neurotoxicity and to assay potential therapeutic approaches. Specifically, by quantifying N-methyl D-aspartate (NMDA) concentration-dependent effects in comparison with low-concentration allogenic-Aβ, we confirm the role of extrasynaptic-NMDA receptors activation that may contribute to Aβ-neurotoxicity. Finally, we assess the potential rescue of neural stem cells (NSCs) and of two pharmacotherapies, memantine and saffron, for reversing Aβ-neurotoxicity and rescuing network-wide firing.

Polyethylene glycol (PEG) has been shown to restore axonal continuity after peripheral nerve transection in animal models. We hypothesized that PEG can also restore axonal continuity in the central nervous system. In this current experiment, coronal sectioning of the brains of Sprague-Dawley rats was performed after animal sacrifice. 3Brain high-resolution microelectrode arrays (MEA) were used to measure mean firing rate (MFR) and peak amplitude across the corpus callosum of the ex-vivo brain slices. The corpus callosum was subsequently transected and repeated measurements were performed. The cut ends of the corpus callosum were still apposite at this time. A PEG solution was applied to the injury site and repeated measurements were performed. MEA measurements showed that PEG was capable of restoring electrophysiology signaling after transection of central nerves. Before injury, the average MFRs at the ipsilateral, midline, and contralateral corpus callosum were 0.76, 0.66, and 0.65 spikes/second, respectively, and the average peak amplitudes were 69.79, 58.68, and 49.60 μV, respectively. After injury, the average MFRs were 0.71, 0.14, and 0.25 spikes/second, respectively and peak amplitudes were 52.11, 8.98, and 16.09 μV, respectively. After application of PEG, there were spikes in MFR and peak amplitude at the injury site and contralaterally. The average MFRs were 0.75, 0.55, and 0.47 spikes/second at the ipsilateral, midline, and contralateral corpus callosum, respectively and peak amplitudes were 59.44, 45.33, 40.02 μV, respectively. There were statistically differences in the average MFRs and peak amplitudes between the midline and non-midline corpus callosum groups (P< 0.01, P< 0.05). These findings suggest that PEG restores axonal conduction between severed central nerves, potentially representing axonal fusion.

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Highlights

• An automated spike sorting method for dense, large-scale recordings is presented
• Efficient data representation enables sorting of thousands of channels
• Automated unit selection through model-based quality control
• Conventional spike sorting frequently fails under non-optimal signal conditions

Summary

We present a method for automated spike sorting for recordings with high-density, large-scale multielectrode arrays. Exploiting the dense sampling of single neurons by multiple electrodes, an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features is exploited for fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. Performance is demonstrated using recordings with a 4,096-channel array and validated using anatomical imaging, optogenetic stimulation, and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our approach demonstrates that it is feasible to reliably isolate the activity of up to thousands of neurons and that dense, multi-channel probes substantially aid reliable spike sorting.

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