Multielectrode Cortical Stimulation Selectively Induces Unidirectional Wave Propagation of Excitatory Neuronal Activity in Biophysical Neural Model.

Cortical stimulation is emerging as an experimental tool in basic research and a promising therapy for a range of neuropsychiatric conditions. As multielectrode arrays enter clinical practice, the possibility of using spatiotemporal patterns of electrical stimulation to induce desired physiological patterns has become theoretically possible, but in practice can only be implemented by trial-and-error because of a lack of predictive models. Experimental evidence increasingly establishes traveling waves as fundamental to cortical information-processing, but we lack an understanding of how to control wave properties despite rapidly improving technologies. This study uses a hybrid biophysical-anatomical and neural-computational model to predict and understand how a simple pattern of cortical surface stimulation could induce directional traveling waves via asymmetric activation of inhibitory interneurons. We found that pyramidal cells and basket cells are highly activated by the anodal electrode and minimally activated by the cathodal electrodes, while Martinotti cells are moderately activated by both electrodes but exhibit a slight preference for cathodal stimulation. Network model simulations found that this asymmetrical activation results in a traveling wave in superficial excitatory cells that propagates unidirectionally away from the electrode array. Our study reveals how asymmetric electrical stimulation can easily facilitate traveling waves by relying on two distinct types of inhibitory interneuron activity to shape and sustain the spatiotemporal dynamics of endogenous local circuit mechanisms.SIGNIFICANCE STATEMENT Electrical brain stimulation is becoming increasingly useful to probe the workings of brain and to treat a variety of neuropsychiatric disorders. However, stimulation is currently performed in a trial-and-error fashion as there are no methods to predict how different electrode arrangements and stimulation paradigms will affect brain functioning. In this study, we demonstrate a hybrid modeling approach, which makes experimentally testable predictions that bridge the gap between the microscale effects of multielectrode stimulation and the resultant circuit dynamics at the mesoscale. Our results show how custom stimulation paradigms can induce predictable, persistent changes in brain activity, which has the potential to restore normal brain function and become a powerful therapy for neurological and psychiatric conditions.

Coherent olfactory bulb gamma oscillations arise from coupling independent columnar oscillators.

Spike timing-based representations of sensory information depend on embedded dynamical frameworks within neuronal networks that establish the rules of local computation and interareal communication. Here, we investigated the dynamical properties of olfactory bulb circuitry in mice of both sexes using microelectrode array recordings from slice and in vivo preparations. Neurochemical activation or optogenetic stimulation of sensory afferents evoked persistent gamma oscillations in the local field potential. These oscillations arose from slower, GABA(A) receptor-independent intracolumnar oscillators coupled by GABA(A)-ergic synapses into a faster, broadly coherent network oscillation. Consistent with the theoretical properties of coupled-oscillator networks, the spatial extent of zero-phase coherence was bounded in slices by the reduced density of lateral interactions. The intact in vivo network, however, exhibited long-range lateral interactions that suffice in simulation to enable zero-phase gamma coherence across the olfactory bulb. The timing of action potentials in a subset of principal neurons was phase-constrained with respect to evoked gamma oscillations. Coupled-oscillator dynamics in olfactory bulb thereby enable a common clock, robust to biological heterogeneities, that is capable of supporting gamma-band spike synchronization and phase coding across the ensemble of activated principal neurons.NEW & NOTEWORTHY Odor stimulation evokes rhythmic gamma oscillations in the field potential of the olfactory bulb, but the dynamical mechanisms governing these oscillations have remained unclear. Establishing these mechanisms is important as they determine the biophysical capacities of the bulbar circuit to, for example, maintain zero-phase coherence across a spatially extended network, or coordinate the timing of action potentials in principal neurons. These properties in turn constrain and suggest hypotheses of sensory coding.

Investigating inherited arrhythmias using hiPSC-derived cardiomyocytes.

Fundamental to the functional behavior of cardiac muscle is that the cardiomyocytes are integrated as a functional syncytium. Disrupted electrical activity in the cardiac tissue can lead to serious complications including cardiac arrhythmias. Therefore, it is important to study electrophysiological properties of the cardiac tissue. With advancements in stem cell research, protocols for the production of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been established, providing great potential in modelling cardiac arrhythmias and drug testing. The hiPSC-CM model can be used in conjunction with electrophysiology-based platforms to examine the electrical activity of the cardiac tissue. Techniques for determining the myocardial electrical activity include multielectrode arrays (MEAs), optical mapping (OM), and patch clamping. These techniques provide critical approaches to investigate cardiac electrical abnormalities that underlie arrhythmias.

Transplanted pluripotent stem cell-derived photoreceptor precursors elicit conventional and unusual light responses in mice with advanced retinal degeneration.

Retinal dystrophies often lead to blindness. Developing therapeutic interventions to restore vision is therefore of paramount importance. Here we demonstrate the ability of pluripotent stem cell-derived cone precursors to engraft and restore light responses in the Pde6brd1 mouse, an end-stage photoreceptor degeneration model. Our data show that up to 1.5% of precursors integrate into the host retina, differentiate into cones, and engraft in close apposition to the host bipolar cells. Half of the transplanted mice exhibited visual behavior and of these 33% showed binocular light sensitivity. The majority of retinal ganglion cells exhibited contrast-sensitive ON, OFF or ON-OFF light responses and even motion sensitivity; however, quite a few exhibited unusual responses (eg, light-induced suppression), presumably reflecting remodeling of the neural retina. Our data indicate that despite relatively low engraftment yield, pluripotent stem cell-derived cone precursors can elicit light responsiveness even at advanced degeneration stages. Further work is needed to improve engraftment yield and counteract retinal remodeling to achieve useful clinical applications.

Classification of antiseizure drugs in cultured neuronal networks using multielectrode arrays and unsupervised learning.

OBJECTIVE: Antiseizure drugs (ASDs) modulate synaptic and ion channel function to prevent abnormal hypersynchronous or excitatory activity arising in neuronal networks, but the relationship between ASDs with respect to their impact on network activity is poorly defined. In this study, we first investigated whether different ASD classes exert differential impact upon network activity, and we then sought to classify ASDs according to their impact on network activity. METHODS: We used multielectrode arrays (MEAs) to record the network activity of cultured cortical neurons after applying ASDs from two classes: sodium channel blockers (SCBs) and γ-aminobutyric acid type A receptor-positive allosteric modulators (GABA PAMs). A two-dimensional representation of changes in network features was then derived, and the ability of this low-dimensional representation to classify ASDs with different molecular targets was assessed. RESULTS: A two-dimensional representation of network features revealed a separation between the SCB and GABA PAM drug classes, and could classify several test compounds known to act through these molecular targets. Interestingly, several ASDs with novel targets, such as cannabidiol and retigabine, had closer similarity to the SCB class with respect to their impact upon network activity. SIGNIFICANCE: These results demonstrate that the molecular target of two common classes of ASDs is reflected through characteristic changes in network activity of cultured neurons. Furthermore, a low-dimensional representation of network features can be used to infer an ASDs molecular target. This approach may allow for drug screening to be performed based on features extracted from MEA recordings.

NanoMEA: A Tool for High-Throughput, Electrophysiological Phenotyping of Patterned Excitable Cells.

Matrix nanotopographical cues are known to regulate the structure and function of somatic cells derived from human pluripotent stem cell (hPSC) sources. High-throughput electrophysiological analysis of excitable cells derived from hPSCs is possible via multielectrode arrays (MEAs) but conventional MEA platforms use flat substrates and do not reproduce physiologically relevant tissue-specific architecture. To address this issue, we developed a high-throughput nanotopographically patterned multielectrode array (nanoMEA) by integrating conductive, ion-permeable, nanotopographic patterns with 48-well MEA plates, and investigated the effect of substrate-mediated cytoskeletal organization on hPSC-derived cardiomyocyte and neuronal function at scale. Using our nanoMEA platform, we found patterned hPSC-derived cardiac monolayers exhibit both enhanced structural organization and greater sensitivity to treatment with calcium blocking or conduction inhibiting compounds when subjected to high-throughput dose-response studies. Similarly, hPSC-derived neurons grown on nanoMEA substrates exhibit faster migration and neurite outgrowth speeds, greater colocalization of pre- and postsynaptic markers, and enhanced cell-cell communication only revealed through examination of data sets derived from multiple technical replicates. The presented data highlight the nanoMEA as a new tool to facilitate high-throughput, electrophysiological analysis of ordered cardiac and neuronal monolayers, which can have important implications for preclinical analysis of excitable cell function.

Combining biophysical modeling and deep learning for multielectrode array neuron localization and classification.

Neural circuits typically consist of many different types of neurons, and one faces a challenge in disentangling their individual contributions in measured neural activity. Classification of cells into inhibitory and excitatory neurons and localization of neurons on the basis of extracellular recordings are frequently employed procedures. Current approaches, however, need a lot of human intervention, which makes them slow, biased, and unreliable. In light of recent advances in deep learning techniques and exploiting the availability of neuron models with quasi-realistic three-dimensional morphology and physiological properties, we present a framework for automatized and objective classification and localization of cells based on the spatiotemporal profiles of the extracellular action potentials recorded by multielectrode arrays. We train convolutional neural networks on simulated signals from a large set of cell models and show that our framework can predict the position of neurons with high accuracy, more precisely than current state-of-the-art methods. Our method is also able to classify whether a neuron is excitatory or inhibitory with very high accuracy, substantially improving on commonly used clustering techniques. Furthermore, our new method seems to have the potential to separate certain subtypes of excitatory and inhibitory neurons. The possibility of automatically localizing and classifying all neurons recorded with large high-density extracellular electrodes contributes to a more accurate and more reliable mapping of neural circuits. NEW & NOTEWORTHY We propose a novel approach to localize and classify neurons from their extracellularly recorded action potentials with a combination of biophysically detailed neuron models and deep learning techniques. Applied to simulated data, this new combination of forward modeling and machine learning yields higher performance compared with state-of-the-art localization and classification methods.

Intracellular and Extracellular Recording of Spontaneous Action Potentials in Mammalian Neurons and Cardiac Cells with 3D Plasmonic Nanoelectrodes.

Three-dimensional vertical micro- and nanostructures can enhance the signal quality of multielectrode arrays and promise to become the prime methodology for the investigation of large networks of electrogenic cells. So far, access to the intracellular environment has been obtained via spontaneous poration, electroporation, or by surface functionalization of the micro/nanostructures; however, these methods still suffer from some limitations due to their intrinsic characteristics that limit their widespread use. Here, we demonstrate the ability to continuously record both extracellular and intracellular-like action potentials at each electrode site in spontaneously active mammalian neurons and HL-1 cardiac-derived cells via the combination of vertical nanoelectrodes with plasmonic optoporation. We demonstrate long-term and stable recordings with a very good signal-to-noise ratio. Additionally, plasmonic optoporation does not perturb the spontaneous electrical activity; it permits continuous recording even during the poration process and can regulate extracellular and intracellular contributions by means of partial cellular poration.

AAV-Syn-BDNF-EGFP Virus Construct Exerts Neuroprotective Action on the Hippocampal Neural Network during Hypoxia In Vitro.

Brain-derived neurotrophic factor (BDNF) is one of the key signaling molecules that supports the viability of neural cells in various brain pathologies, and can be considered a potential therapeutic agent. However, several methodological difficulties, such as overcoming the blood⁻brain barrier and the short half-life period, challenge the potential use of BDNF in clinical practice. Gene therapy could overcome these limitations. Investigating the influence of viral vectors on the neural network level is of particular interest because viral overexpression affects different aspects of cell metabolism and interactions between neurons. The present work aimed to investigate the influence of the adeno-associated virus (AAV)-Syn-BDNF-EGFP virus construct on neural network activity parameters in an acute hypobaric hypoxia model in vitro. MATERIALS AND METHODS: An adeno-associated virus vector carrying the BDNF gene was constructed using the following plasmids: AAV-Syn-EGFP, pDP5, DJvector, and pHelper. The developed virus vector was then tested on primary hippocampal cultures obtained from C57BL/6 mouse embryos (E18). Acute hypobaric hypoxia was induced on day 21 in vitro. Spontaneous bioelectrical and calcium activity of neural networks in primary cultures and viability tests were analysed during normoxia and during the posthypoxic period. RESULTS: BDNF overexpression by AAV-Syn-BDNF-EGFP does not affect cell viability or the main parameters of spontaneous bioelectrical activity in normoxia. Application of the developed virus construct partially eliminates the negative hypoxic consequences by preserving cell viability and maintaining spontaneous bioelectrical activity in the cultures. Moreover, the internal functional structure, including the activation pattern of network bursts, the number of hubs, and the number of connections within network elements, is also partially preserved. BDNF overexpression prevents a decrease in the number of cells exhibiting calcium activity and maintains the frequency of calcium oscillations. CONCLUSION: This study revealed the pronounced antihypoxic and neuroprotective effects of AAV-Syn-BDNF-EGFP virus transduction in an acute normobaric hypoxia model.

Sensitivity of neurons in the middle temporal area of marmoset monkeys to random dot motion.

Neurons in the middle temporal area (MT) of the primate cerebral cortex respond to moving visual stimuli. The sensitivity of MT neurons to motion signals can be characterized by using random-dot stimuli, in which the strength of the motion signal is manipulated by adding different levels of noise (elements that move in random directions). In macaques, this has allowed the calculation of "neurometric" thresholds. We characterized the responses of MT neurons in sufentanil/nitrous oxide-anesthetized marmoset monkeys, a species that has attracted considerable recent interest as an animal model for vision research. We found that MT neurons show a wide range of neurometric thresholds and that the responses of the most sensitive neurons could account for the behavioral performance of macaques and humans. We also investigated factors that contributed to the wide range of observed thresholds. The difference in firing rate between responses to motion in the preferred and null directions was the most effective predictor of neurometric threshold, whereas the direction tuning bandwidth had no correlation with the threshold. We also showed that it is possible to obtain reliable estimates of neurometric thresholds using stimuli that were not highly optimized for each neuron, as is often necessary when recording from large populations of neurons with different receptive field concurrently, as was the case in this study. These results demonstrate that marmoset MT shows an essential physiological similarity to macaque MT and suggest that its neurons are capable of representing motion signals that allow for comparable motion-in-noise judgments.NEW & NOTEWORTHY We report the activity of neurons in marmoset MT in response to random-dot motion stimuli of varying coherence. The information carried by individual MT neurons was comparable to that of the macaque, and the maximum firing rates were a strong predictor of sensitivity. Our study provides key information regarding the neural basis of motion perception in the marmoset, a small primate species that is becoming increasingly popular as an experimental model.

Proarrhythmic risk assessment using conventional and new in vitro assays.

Drug-induced QT prolongation is a major safety issue in the drug discovery process. This study was conducted to assess the electrophysiological responses of four substances using established preclinical assays usually used in regulatory studies (hERG channel or Purkinje fiber action potential) and a new assay (human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs)-field potential). After acute exposure, moxifloxacin and dofetilide concentration-dependently decreased IKr amplitude (IC50 values: 102 µM and 40 nM, respectively) and lengthened action potential (100 µM moxifloxacin: +23% and 10 nM dofetilide: +18%) and field potential (300 µM moxifloxacin: +76% and 10 nM dofetilide: +38%) durations. Dofetilide starting from 30 nM induced arrhythmia in hiPSC-CMs. Overnight application of pentamidine (10 and 100 µM) and arsenic (1 and 10 µM) decreased IKr, whereas they were devoid of effects after acute application. Long-term pentamidine incubation showed a time- and concentration-dependent effect on field potential duration. In conclusion, our data suggest that hiPSC-CMs represent a fully functional cellular electrophysiology model which may significantly improve the predictive validity of in vitro safety studies. Thereafter, lead candidates may be further investigated in patch-clamp assays for mechanistic studies on individual ionic channels or in a multicellular Purkinje fiber preparation for confirmatory studies on cardiac conduction.

Analysis of spontaneous activity of superficial dorsal horn neurons in vitro: neuropathy-induced changes.

The superficial dorsal horn contains large numbers of interneurons which process afferent and descending information to generate the spinal nociceptive message. Here, we set out to evaluate whether adjustments in patterns and/or temporal correlation of spontaneous discharges of these neurons are involved in the generation of central sensitization caused by peripheral nerve damage. Multielectrode arrays were used to record from discrete groups of such neurons in slices from control or nerve damaged mice. Whole-cell recordings of individual neurons were also obtained. A large proportion of neurons recorded extracellularly showed well-defined patterns of spontaneous firing. Clock-like neurons (CL) showed regular discharges at ∼6 Hz and represented 9 % of the sample in control animals. They showed a tonic-firing pattern to direct current injection and depolarized membrane potentials. Irregular fast-burst neurons (IFB) produced short-lasting high-frequency bursts (2-5 spikes at ∼100 Hz) at irregular intervals and represented 25 % of the sample. They showed bursting behavior upon direct current injection. Of the pairs of neurons recorded, 10 % showed correlated firing. Correlated pairs always included an IFB neuron. After nerve damage, the mean spontaneous firing frequency was unchanged, but the proportion of CL increased significantly (18 %) and many of these neurons appeared to acquire a novel low-threshold A-fiber input. Similarly, the percentage of IFB neurons was unaltered, but synchronous firing was increased to 22 % of the pairs studied. These changes may contribute to transform spinal processing of nociceptive inputs following peripheral nerve damage. The specific roles that these neurons may play are discussed.

Network burst activity in hippocampal neuronal cultures: the role of synaptic and intrinsic currents.

The goal of this work was to define the contributions of intrinsic and synaptic mechanisms toward spontaneous network-wide bursting activity, observed in dissociated rat hippocampal cell cultures. This network behavior is typically characterized by short-duration bursts, separated by order of magnitude longer interburst intervals. We hypothesize that while short-timescale synaptic processes modulate spectro-temporal intraburst properties and network-wide burst propagation, much longer timescales of intrinsic membrane properties such as persistent sodium (Nap) currents govern burst onset during interburst intervals. To test this, we used synaptic receptor antagonists picrotoxin, 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX), and 3-(2-carboxypiperazine-4-yl)propyl-1-phosphonate (CPP) to selectively block GABAA, AMPA, and NMDA receptors and riluzole to selectively block Nap channels. We systematically compared intracellular activity (recorded with patch clamp) and network activity (recorded with multielectrode arrays) in eight different synaptic connectivity conditions: GABAA + NMDA + AMPA, NMDA + AMPA, GABAA + AMPA, GABAA + NMDA, AMPA, NMDA, GABAA, and all receptors blocked. Furthermore, we used mixed-effects modeling to quantify the aforementioned independent and interactive synaptic receptor contributions toward spectro-temporal burst properties including intraburst spike rate, burst activity index, burst duration, power in the local field potential, network connectivity, and transmission delays. We found that blocking intrinsic Nap currents completely abolished bursting activity, demonstrating their critical role in burst onset within the network. On the other hand, blocking different combinations of synaptic receptors revealed that spectro-temporal burst properties are uniquely associated with synaptic functionality and that excitatory connectivity is necessary for the presence of network-wide bursting. In addition to confirming the critical contribution of direct excitatory effects, mixed-effects modeling also revealed distinct combined (nonlinear) contributions of excitatory and inhibitory synaptic activity to network bursting properties.

Generalized analog thresholding for spike acquisition at ultralow sampling rates.

Efficient spike acquisition techniques are needed to bridge the divide from creating large multielectrode arrays (MEA) to achieving whole-cortex electrophysiology. In this paper, we introduce generalized analog thresholding (gAT), which achieves millisecond temporal resolution with sampling rates as low as 10 Hz. Consider the torrent of data from a single 1,000-channel MEA, which would generate more than 3 GB/min using standard 30-kHz Nyquist sampling. Recent neural signal processing methods based on compressive sensing still require Nyquist sampling as a first step and use iterative methods to reconstruct spikes. Analog thresholding (AT) remains the best existing alternative, where spike waveforms are passed through an analog comparator and sampled at 1 kHz, with instant spike reconstruction. By generalizing AT, the new method reduces sampling rates another order of magnitude, detects more than one spike per interval, and reconstructs spike width. Unlike compressive sensing, the new method reveals a simple closed-form solution to achieve instant (noniterative) spike reconstruction. The base method is already robust to hardware nonidealities, including realistic quantization error and integration noise. Because it achieves these considerable specifications using hardware-friendly components like integrators and comparators, generalized AT could translate large-scale MEAs into implantable devices for scientific investigation and medical technology.

Ultrasound neuromodulation of cultured hippocampal neurons.

Ultrasound is becoming an emerging and promising method for neuromodulation due to its advantage of noninvasiveness and its high spatial resolution. However, the underlying principles of ultrasound neuromodulation have not yet been elucidated. We have herein developed a new in vitro setup to study the ultrasonic neuromodulation, and examined various parameters of ultrasound to verify the effective conditions to evoke the neural activity. Neurons were stimulated with 0.5 MHz center frequency ultrasound, and the action potentials were recorded from rat hippocampal neural cells cultured on microelectrode arrays. As the intensity of ultrasound increased, the neuronal activity also increased. There was a notable and significant increase in both the spike rate and the number of bursts at 50% duty cycle, 1 kHz pulse repetition frequency, and the acoustic intensities of 7.6 W/cm2 and 3.8 W/cm2 in terms of spatial-peak pulse-average intensity and spatial-peak temporal-average intensity, respectively. In addition, the impact of ultrasonic neuromodulation was assessed in the presence of a gamma-aminobutyric acid A (GABAA) receptor antagonist to exclude the effect of activated inhibitory neurons. Interestingly, it is noteworthy that the predominant neuromodulatory effects of ultrasound disappeared when the GABAA blocker was introduced, suggesting the potential of ultrasonic stimulation specifically targeting inhibitory neurons. The experimental setup proposed herein could serve as a useful tool for the clarification of the mechanisms underlying the electrophysiological effects of ultrasound.

Electroconductive Collagen-Carbon Nanodots Nanocomposite Elicits Neurite Outgrowth, Supports Neurogenic Differentiation and Accelerates Electrophysiological Maturation of Neural Progenitor Spheroids.

Neuronal disorders are characterized by the loss of functional neurons and disrupted neuroanatomical connectivity, severely impacting the quality of life of patients. This study investigates a novel electroconductive nanocomposite consisting of glycine-derived carbon nanodots (GlyCNDs) incorporated into a collagen matrix and validates its beneficial physicochemical and electro-active cueing to relevant cells. To this end, this work employs mouse induced pluripotent stem cell (iPSC)-derived neural progenitor (NP) spheroids. The findings reveal that the nanocomposite markedly augmented neuronal differentiation in NP spheroids and stimulate neuritogenesis. In addition, this work demonstrates that the biomaterial-driven enhancements of the cellular response ultimately contribute to the development of highly integrated and functional neural networks. Lastly, acute dizocilpine (MK-801) treatment provides new evidence for a direct interaction between collagen-bound GlyCNDs and postsynaptic N-methyl-D-aspartate (NMDA) receptors, thereby suggesting a potential mechanism underlying the observed cellular events. In summary, the findings establish a foundation for the development of a new nanocomposite resulting from the integration of carbon nanomaterials within a clinically approved hydrogel, toward an effective biomaterial-based strategy for addressing neuronal disorders by restoring damaged/lost neurons and supporting the reestablishment of neuroanatomical connectivity.

Unsupervised spike sorting for multielectrode arrays based on spike shape features and location methods.

Microelectrode arrays (MEAs) enable simultaneous measurement of spike trains from numerous neurons, owing to advancements in microfabrication technology. These probes are highly valuable for comprehending the intricate dynamics of neuronal networks. Spike sorting is a pivotal step in comprehensively analyzing the activity of neuronal networks from extracellular recordings. However, the accuracy of spike sorting is relatively low due to the dense sampling of spikes in MEAs. Here, we propose an unsupervised pipeline named UMAP-COM method, which utilizes combined features to address this problem. These combined features comprise dominant spike shape features extracted by the uniform manifold approximation and projection (UMAP), as well as spike locations estimated by the center of mass (COM). We validate the UMAP-COM method on publicly available datasets from different kinds of probes, demonstrating that it is more accurate than other spike sorting methods. Furthermore, we conduct separate evaluations of spike shape feature extraction methods and spike localization methods. In this comparison, UMAP emerges as the superior feature extraction method, demonstrating its effectiveness in accurately representing spike shapes. Additionally, we find that the COM method outperforms other spike localization methods, highlighting its ability to enhance the accuracy of spike sorting.

Dynamic electrical stimulation enhances the recruitment of spinal interneurons by corticospinal input.

Highly varying patterns of electrostimulation (Dynamic Stimulation, DS) delivered to the dorsal cord through an epidural array with 18 independent electrodes transiently facilitate corticospinal motor responses, even after spinal injury. To partly unravel how corticospinal input are affected by DS, we introduced a corticospinal platform that allows selective cortical stimulation during the multisite acquisition of cord dorsum potentials (CDPs) and the simultaneous supply of DS. Firstly, the epidural interface was validated by the acquisition of the classical multisite distribution of CDPs and their input-output profile elicited by pulses delivered to peripheral nerves. Apart from increased EMGs, DS selectively increased excitability of the spinal interneurons that first process corticospinal input, without changing the magnitude of commands descending from the motor cortex, suggesting a novel correlation between muscle recruitment and components of cortically-evoked CDPs. Finally, DS increases excitability of post-synaptic spinal interneurons at the stimulation site and their responsiveness to any residual supraspinal control, thus supporting the use of electrical neuromodulation whenever the motor output is jeopardized by a weak volitional input, due to a partial disconnection from supraspinal structures and/or neuronal brain dysfunctions.

Anisotropy and Frequency Dependence of Signal Propagation in the Cerebellar Circuit Revealed by High-Density Multielectrode Array Recordings.

The cerebellum is one of the most connected structures of the central nervous system and receives inputs over an extended frequency range. Nevertheless, the frequency dependence of cerebellar cortical processing remains elusive. In this work, we characterized cerebellar cortex responsiveness to mossy fibers activation at different frequencies and reconstructed the spread of activity in the sagittal and coronal planes of acute mouse cerebellar slices using a high-throughput high-density multielectrode array (HD-MEA). The enhanced spatiotemporal resolution of HD-MEA revealed the frequency dependence and spatial anisotropy of cerebellar activation. Mossy fiber inputs reached the Purkinje cell layer even at the lowest frequencies, but the efficiency of transmission increased at higher frequencies. These properties, which are likely to descend from the topographic organization of local inhibition, intrinsic electroresponsiveness, and short-term synaptic plasticity, are critical elements that have to be taken into consideration to define the computational properties of the cerebellar cortex and its pathological alterations.

Spinal facilitation of descending motor input.

Highly varying patterns of electrostimulation (Dynamic Stimulation, DS) delivered to the dorsal cord through an epidural array with 18 independent electrodes transiently facilitate corticospinal motor responses, even after spinal injury. To partly unravel how corticospinal input are affected by DS, we introduced a corticospinal platform that allows selective cortical stimulation during the multisite acquisition of cord dorsum potentials (CDPs) and the simultaneous supply of DS. Firstly, the epidural interface was validated by the acquisition of the classical multisite distribution of CDPs on the dorsal cord and their input-output profile elicited by pulses delivered to peripheral nerves. Apart from increased EMGs, DS selectively increased excitability of the spinal interneurons that first process corticospinal input, without changing the magnitude of commands descending from the motor cortex, suggesting a novel correlation between muscle recruitment and components of cortically-evoked CDPs. Finally, DS increases excitability of post-synaptic spinal interneurons at the stimulation site and their responsiveness to any residual supraspinal control, thus supporting the use of electrical neuromodulation whenever the motor output is jeopardized by a weak volitional input, due to a partial disconnection from supraspinal structures and/or neuronal brain dysfunctions.