Analytical Parameter Estimation of the SIR Epidemic Model. Applications to the COVID-19 Pandemic.

The SIR (Susceptible-Infected-Removed) model is a simple mathematical model of epidemic outbreaks, yet for decades it evaded the efforts of the mathematical community to derive an explicit solution. The present paper reports novel analytical results and numerical algorithms suitable for parametric estimation of the SIR model. Notably, a series solution of the incidence variable of the model is derived. It is proven that the explicit solution of the model requires the introduction of a new transcendental special function, which is a solution of a non-elementary integral equation. The paper introduces iterative algorithms approximating the incidence variable, which allows for estimation of the model parameters from the numbers of observed cases. The approach is applied to the case study of the ongoing coronavirus disease 2019 (COVID-19) pandemic in five European countries: Belgium, Bulgaria, Germany, Italy and the Netherlands. Incidence and case fatality data obtained from the European Centre for Disease Prevention and Control (ECDC) are analysed and the model parameters are estimated and compared.

Analytical and Numerical Treatments of Conservative Diffusions and the Burgers Equation.

The present work is concerned with the study of a generalized Langevin equation and its link to the physical theories of statistical mechanics and scale relativity. It is demonstrated that the form of the coefficients of the Langevin equation depends critically on the assumption of continuity of the reconstructed trajectory. This in turn demands for the fluctuations of the diffusion term to be discontinuous in time. This paper further investigates the connection between the scale-relativistic and stochastic mechanics approaches, respectively, with the study of the Burgers equation, which in this case appears as a stochastic geodesic equation for the drift. By further demanding time reversibility of the drift, the Langevin equation can also describe equivalent quantum-mechanical systems in a path-wise manner. The resulting statistical description obeys the Fokker-Planck equation of the probability density of the differential system, which can be readily estimated from simulations of the random paths. Based on the Fokker-Planck formalism, a new derivation of the transient probability densities is presented. Finally, stochastic simulations are compared to the theoretical results.

A model of space-fractional-order diffusion in the glial scar.

Implantation of neuroprosthetic electrodes induces a stereotypical state of neuroinflammation, which is thought to be detrimental for the neurons surrounding the electrode. Mechanisms of this type of neuroinflammation are still poorly understood. Recent experimental and theoretical results point to a possible role of the diffusing species in this process. The paper considers a model of anomalous diffusion occurring in the glial scar around a chronic implant in two simple geometries - a separable rectilinear electrode and a cylindrical electrode, which are solvable exactly. We describe a hypothetical extended source of diffusing species and study its concentration profile in steady-state conditions. Diffusion transport is assumed to obey a fractional-order Fick law, derivable from physically realistic assumptions using a fractional calculus approach. Presented fractional-order distribution morphs into integer-order diffusion in the case of integral fractional exponents. The model demonstrates that accumulation of diffusing species can occur and the scar properties (i.e. tortuosity, fractional order, scar thickness) and boundary conditions can influence such accumulation. The observed shape of the concentration profile corresponds qualitatively with GFAP profiles reported in the literature. The main difference with respect to the previous studies is the explicit incorporation of the apparatus of fractional calculus without assumption of an ad hoc tortuosity parameter. The approach can be adapted to other studies of diffusion in biological tissues, for example of biomolecules or small drug molecules.

Migraine preventive drugs differentially affect cortical spreading depression in rat.

Cortical spreading depression (CSD) is the most likely cause of the migraine aura. Drugs with distinct pharmacological properties are effective in the preventive treatment of migraine. To test the hypothesis that their common denominator might be suppression of CSD we studied in rats the effect of three drugs used in migraine prevention: lamotrigine which is selectively effective on the aura but not on the headache, valproate and riboflavin which have a non-selective effect. Rats received for 4 weeks daily intraperitoneal injections of one of the three drugs. For valproate and riboflavin we used saline as control, for lamotrigine its vehicle dimethyl sulfoxide. After treatment, cortical spreading depressions were elicited for 2h by occipital KCl application. We measured CSD frequency, its propagation between a posterior (parieto-occipital) and an anterior (frontal) electrode, and number of Fos-immunoreactive nuclei in frontal cortex. Lamotrigine suppressed CSDs by 37% and 60% at posterior and anterior electrodes. Valproate had no effect on posterior CSDs, but reduced anterior ones by 32% and slowed propagation velocity. Riboflavin had no significant effect at neither recording site. Frontal Fos expression was decreased after lamotrigine and valproate, but not after riboflavin. Serum levels of administered drugs were within the range of those usually effective in patients. Our study shows that preventive anti-migraine drugs have differential effects on CSD. Lamotrigine has a marked suppressive effect which correlates with its rather selective action on the migraine aura. Valproate and riboflavin have no effect on the triggering of CSD, although they are effective in migraine without aura. Taken together, these results are compatible with a causal role of CSD in migraine with aura, but not in migraine without aura.

The Active Segmentation Platform for Microscopic Image Classification and Segmentation.

Image segmentation still represents an active area of research since no universal solution can be identified. Traditional image segmentation algorithms are problem-specific and limited in scope. On the other hand, machine learning offers an alternative paradigm where predefined features are combined into different classifiers, providing pixel-level classification and segmentation. However, machine learning only can not address the question as to which features are appropriate for a certain classification problem. The article presents an automated image segmentation and classification platform, called Active Segmentation, which is based on ImageJ. The platform integrates expert domain knowledge, providing partial ground truth, with geometrical feature extraction based on multi-scale signal processing combined with machine learning. The approach in image segmentation is exemplified on the ISBI 2012 image segmentation challenge data set. As a second application we demonstrate whole image classification functionality based on the same principles. The approach is exemplified using the HeLa and HEp-2 data sets. Obtained results indicate that feature space enrichment properly balanced with feature selection functionality can achieve performance comparable to deep learning approaches. In summary, differential geometry can substantially improve the outcome of machine learning since it can enrich the underlying feature space with new geometrical invariant objects.

Preliminary Minimum Reporting Requirements for In-Vivo Neural Interface Research: I. Implantable Neural Interfaces.

The pace of research and development in neuroscience, neurotechnology, and neurorehabilitation is rapidly accelerating, with the number of publications doubling every 4.2 years. Maintaining this progress requires technological standards and scientific reporting guidelines to provide frameworks for communication and interoperability. The present lack of such neurotechnology standards limits the transparency, repro-ducibility, and meta-analysis of this growing body of literature, posing an ongoing barrier to research, clinical, and commercial objectives. Continued neurotechnological innovation requires the development of some minimal standards to promote integration between this broad spectrum of technologies and therapies. To preserve design freedom and accelerate the translation of research into safe and effective technologies with maximal user benefit, such standards must be collaboratively co-developed by the full range of neuroscience and neurotechnology stakeholders. This paper summarizes the preliminary recommendations of IEEE P2794 Standards Working Group, developing a Reporting Standard for in-vivo Neural Interface Research (RSNIR).

Workshop Report: Governance of Emerging Nanotechnology Risks in the Semiconductor Industry.

Assessment of risk in the field of nanotechnology requires an integrated multidisciplinary approach due to the complex and cross-disciplinary framework for materials and activities at the nanoscale. The present paper summarizes the workshop "Governance of emerging nano-risk in the semiconductor industry" held on April 26, 2018 in Brussels, Belgium. The event targeted representatives of stakeholder communities involved in the risk assessment and governance of the engineered nanomaterials. Nanoelectronics was selected as an impactful use case for risk assessment approaches and comparison to bottom-up nanofabrication. The workshop outlined key data gaps impeding successful assessment of risks associated with nanoparticle use in the industry, using the semiconductor industry as an example. The workshop outlined mitigation strategies informing future regulatory decisions and identified some directions for future efforts.

Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions.

The eukaryotic cell nucleus is a central organelle whose architecture determines genome function at multiple levels. Deciphering nuclear organizing principles influencing cellular responses and identity is a timely challenge. Despite many similarities between plant and animal nuclei, plant nuclei present intriguing specificities. Complementary to molecular and biochemical approaches, 3D microscopy is indispensable for resolving nuclear architecture. However, novel solutions are required for capturing cell-specific, sub-nuclear and dynamic processes. We provide a pointer for utilising high-to-super-resolution microscopy and image processing to probe plant nuclear architecture in 3D at the best possible spatial and temporal resolution and at quantitative and cell-specific levels. High-end imaging and image-processing solutions allow the community now to transcend conventional practices and benefit from continuously improving approaches. These promise to deliver a comprehensive, 3D view of plant nuclear architecture and to capture spatial dynamics of the nuclear compartment in relation to cellular states and responses. Abbreviations: 3D and 4D: Three and Four dimensional; AI: Artificial Intelligence; ant: antipodal nuclei (ant); CLSM: Confocal Laser Scanning Microscopy; CTs: Chromosome Territories; DL: Deep Learning; DLIm: Dynamic Live Imaging; ecn: egg nucleus; FACS: Fluorescence-Activated Cell Sorting; FISH: Fluorescent In Situ Hybridization; FP: Fluorescent Proteins (GFP, RFP, CFP, YFP, mCherry); FRAP: Fluorescence Recovery After Photobleaching; GPU: Graphics Processing Unit; KEEs: KNOT Engaged Elements; INTACT: Isolation of Nuclei TAgged in specific Cell Types; LADs: Lamin-Associated Domains; ML: Machine Learning; NA: Numerical Aperture; NADs: Nucleolar Associated Domains; PALM: Photo-Activated Localization Microscopy; Pixel: Picture element; pn: polar nuclei; PSF: Point Spread Function; RHF: Relative Heterochromatin Fraction; SIM: Structured Illumination Microscopy; SLIm: Static Live Imaging; SMC: Spore Mother Cell; SNR: Signal to Noise Ratio; SRM: Super-Resolution Microscopy; STED: STimulated Emission Depletion; STORM: STochastic Optical Reconstruction Microscopy; syn: synergid nuclei; TADs: Topologically Associating Domains; Voxel: Volumetric pixel.

Automated characterization of nerve fibers labeled fluorescently: determination of size, class and spatial distribution.

Morphological classification of nerve fibers could help interpret the assessment of neural regeneration and the understanding of selectivity of nerve stimulation. Specific populations of myelinated nerve fibers can be investigated by retrograde tracing from a muscle followed by microscopic measurements of the labeled fibers at different anatomical levels. Gastrocnemius muscles of adult rats were injected with the retrograde tracer Fluoro-Gold. After a survival period of 3 days, cross-sections of spinal cords, ventral roots, sciatic, and tibial nerves were collected and imaged on a fluorescence microscope. Nerve fibers were classified using a variation-based criterion acting on the distribution of their equivalent diameters. The same criterion was used to classify the labeled axons using the size of the fluorescent marker. Measurements of the axons were paired to those of the entire fibers (axons+myelin sheaths) in order to establish the correspondence between so-established axonal and fiber classifications. It was found that nerve fibers in L6 ventral roots could be classified into four populations comprising two classes of Aalpha (denoted Aalpha1 and Aalpha2), Agamma, and an additional class of Agammaalpha fibers. Cut-off borders between Agamma and Agammaalpha fiber classes were estimated to be 5.00+/-0.09 microm (SEM); between Agammaalpha and Aalpha1 fiber classes to be 6.86+/-0.11 microm (SEM); and between Aalpha1 and Aalpha2 fiber classes to be 8.66+/-0.16 microm (SEM). Topographical maps of the nerve fibers that innervate the gastrocnemius muscles were constructed per fiber class for the spinal root L6. The major advantage of the presented approach consists of the combined indirect classification of nerve fiber types and the construction of topographical maps of so-identified fiber classes.

Accurate label-free 3-part leukocyte recognition with single cell lens-free imaging flow cytometry.

Three-part white blood cell differentials which are key to routine blood workups are typically performed in centralized laboratories on conventional hematology analyzers operated by highly trained staff. With the trend of developing miniaturized blood analysis tool for point-of-need in order to accelerate turnaround times and move routine blood testing away from centralized facilities on the rise, our group has developed a highly miniaturized holographic imaging system for generating lens-free images of white blood cells in suspension. Analysis and classification of its output data, constitutes the final crucial step ensuring appropriate accuracy of the system. In this work, we implement reference holographic images of single white blood cells in suspension, in order to establish an accurate ground truth to increase classification accuracy. We also automate the entire workflow for analyzing the output and demonstrate clear improvement in the accuracy of the 3-part classification. High-dimensional optical and morphological features are extracted from reconstructed digital holograms of single cells using the ground-truth images and advanced machine learning algorithms are investigated and implemented to obtain 99% classification accuracy. Representative features of the three white blood cell subtypes are selected and give comparable results, with a focus on rapid cell recognition and decreased computational cost.

Morphometric analysis of the fiber populations of the rat sciatic nerve, its spinal roots, and its major branches.

Correspondence between the nerve composition and the functional characteristics of its fiber populations is not always evident. To investigate such correspondence and to give a systematic picture of the morphology of the rat hind limb nerves, extensive morphometric study was performed on the sciatic nerve, its founding dorsal and ventral spinal roots, and its major branches. Nerve histology was examined in semithin sections via microscopic image analysis. Variation in the density of myelinated fibers, fiber interspace, and nerve cross-sectional area was studied in individual roots and nerves. In the dorsal roots, fiber numbers and cross-sectional areas were directly linearly proportional to the spinal root level number. Constituent fiber populations were identified using multicomponent lognormal models, and an optimal model for every nerve or root was selected by using an information theoretic approach. For the dorsal and ventral roots and the sciatic and peroneal nerves, optimal fiber population models consisted of three components, whereas, for the tibial and sural nerves, two components were optimal. Functional identities of the revealed fiber populations were established by using calculations of corresponding conduction velocities according to Arbuthnott et al. (J. Physiol. [1980] 308:125-157) and anatomical considerations. It is anticipated that morphological parameters established in this study would advance the development of neural prostheses in humans. The proximodistal correspondences among the fiber populations of different nerves were established by parametric statistical comparisons. The proposed approach provides a conceptual framework for understanding the comparative anatomy of the peripheral nerves and spinal roots and can be further applied in other species.

Spatial clustering analysis in neuroanatomy: applications of different approaches to motor nerve fiber distribution.

Spatial organization of the nerve fibers in the peripheral nerves may be important for the studies of axonal regeneration, the degenerative nerve diseases and the construction of interfaces with peripheral nerves, such as nerve prostheses. Functional topography of motor axons related to the gastrocnemius muscle was revealed in the ventral spinal roots by retrograde tracing. Gastrocnemius muscles of adult rats were injected with the tracer Fluoro-Gold. After 3 days of survival the animals were sacrificed and their ventral roots were harvested, sectioned, and imaged on a fluorescence microscope. Maps of the traced fibers were automatically analyzed using a novel approach, local spatial clustering statistics, that tested for occurrences of clusters of motor fibers and visualized them. Thresholds indicating the presence of clustering at various scales of observation were computed based on series of Monte Carlo simulations of random spatial point patterns. Clusters were visualized by kernel interpolation. The approach was tested on simulated data and subsequently applied to the motor fiber maps in the ventral roots. Results revealed clustering of the motor fibers innervating the gastrocnemius muscle at the level of the L6 ventral spinal root. The analysis was validated using Voronoi tessellation and nearest neighbor analysis.

And Then There Was Light: Perspectives of Optogenetics for Deep Brain Stimulation and Neuromodulation.

Deep Brain Stimulation (DBS) has evolved into a well-accepted add-on treatment for patients with severe Parkinsons disease as well as for other chronic neurological conditions. The focal action of electrical stimulation can yield better responses and it exposes the patient to fewer side effects compared to pharmaceuticals distributed throughout the body toward the brain. On the other hand, the current practice of DBS is hampered by the relatively coarse level of neuromodulation achieved. Optogenetics, in contrast, offers the perspective of much more selective actions on the various physiological structures, provided that the stimulated cells are rendered sensitive to the action of light. Optogenetics has experienced tremendous progress since its first in vivo applications about 10 years ago. Recent advancements of viral vector technology for gene transfer substantially reduce vector-associated cytotoxicity and immune responses. This brings about the possibility to transfer this technology into the clinic as a possible alternative to DBS and neuromodulation. New paths could be opened toward a rich panel of clinical applications. Some technical issues still limit the long term use in humans but realistic perspectives quickly emerge. Despite a rapid accumulation of observations about patho-physiological mechanisms, it is still mostly serendipity and empiric adjustments that dictate clinical practice while more efficient logically designed interventions remain rather exceptional. Interestingly, it is also very much the neuro technology developed around optogenetics that offers the most promising tools to fill in the existing knowledge gaps about brain function in health and disease. The present review examines Parkinson's disease and refractory epilepsy as use cases for possible optogenetic stimulation therapies.

Action potential-based MEA platform for in vitro screening of drug-induced cardiotoxicity using human iPSCs and rat neonatal myocytes.

Drug-induced cardiotoxicity poses a negative impact on public health and drug development. Cardiac safety pharmacology issues urged for the preclinical assessment of drug-induced ventricular arrhythmia leading to the design of several in vitro electrophysiological screening assays. In general, patch clamp systems allow for intracellular recordings, while multi-electrode array (MEA) technology detect extracellular activity. Here, we demonstrate a complementary metal oxide semiconductor (CMOS)-based MEA system as a reliable platform for non-invasive, long-term intracellular recording of cardiac action potentials at high resolution. Quinidine (8 concentrations from 10-7 to 2.10-5M) and verapamil (7 concentrations from 10-11 to 10-5M) were tested for dose-dependent responses in a network of cardiomyocytes. Electrophysiological parameters, such as the action potential duration (APD), rates of depolarization and repolarization and beating frequency were assessed. In hiPSC, quinidine prolonged APD with EC50 of 2.2·10-6M. Further analysis indicated a multifactorial action potential prolongation by quinidine: (1) decreasing fast repolarization with IC50 of 1.1·10-6M; (2) reducing maximum upstroke velocity with IC50 of 2.6·10-6M; and (3) suppressing spontaneous activity with EC50 of 3.8·10-6M. In rat neonatal cardiomyocytes, verapamil blocked spontaneous activity with EC50 of 5.3·10-8M and prolonged the APD with EC50 of 2.5·10-8M. Verapamil reduced rates of fast depolarization and repolarization with IC50s of 1.8 and 2.2·10-7M, respectively. In conclusion, the proposed action potential-based MEA platform offers high quality and stable long-term recordings with high information content allowing to characterize multi-ion channel blocking drugs. We anticipate application of the system as a screening platform to efficiently and cost-effectively test drugs for cardiac safety.

Automatic morphometry of synaptic boutons of cultured cells using granulometric analysis of digital images.

Numbers, linear density, and surface area of synaptic boutons can be important parameters in studies on synaptic plasticity in cultured neurons. We present a method for automatic identification and morphometry of boutons based on filtering of digital images using granulometric analysis. Cultures of cortical neurons (DIV8 and DIV21) were fixed and marked with fluorescently labeled antibodies for synapsin I (a marker for synaptic boutons) and MAP-2 (a marker for dendrites). Images were acquired on a confocal microscope and automatically processed. Granulometry, a morphological operator sensitive to the geometry and size of objects, was used to construct a filter passing fuzzy fluorescent grains of a certain size. Next, the filter was overlaid with the original image (masking) and the positive pixels were identified by an integral intensity threshold (thresholding). Disjoint grains, representing individual boutons, were reconstructed from the connected pixels above the threshold, numbered and their area was measured. In total, 1498 boutons with a mean diameter of 1.63 +/- 0.49 microm (S.D.) were measured. Comparisons with manual counts showed that the proposed method was capable of identifying boutons in a systematic manner at the light microscopic level and was a viable alternative to manual bouton counting.

Mechanical and Biological Interactions of Implants with the Brain and Their Impact on Implant Design.

Neural prostheses have already a long history and yet the cochlear implant remains the only success story about a longterm sensory function restoration. On the other hand, neural implants for deep brain stimulation are gaining acceptance for variety of disorders including Parkinsons disease and obsessive-compulsive disorder. It is anticipated that the progress in the field has been hampered by a combination of technological and biological factors, such as the limited understanding of the longterm behavior of implants, unreliability of devices, biocompatibility of the implants among others. While the field's understanding of the cell biology of interactions at the biotic-abiotic interface has improved, relatively little attention has been paid on the mechanical factors (stress, strain), and hence on the geometry that can modulate it. This focused review summarizes the recent progress in the understanding of the mechanisms of mechanical interaction between the implants and the brain. The review gives an overview of the factors by which the implants interact acutely and chronically with the tissue: blood-brain barrier (BBB) breach, vascular damage, micromotions, diffusion etc. We propose some design constraints to be considered in future studies. Aspects of the chronic cell-implant interaction will be discussed in view of the chronic local inflammation and the ways of modulating it.

Three-part differential of unlabeled leukocytes with a compact lens-free imaging flow cytometer.

A compelling clinical need exists for inexpensive, portable haematology analyzers that can be utilized at the point-of-care in emergency settings or in resource-limited settings. Development of a label-free, microfluidic blood analysis platform is the first step towards such a miniaturized, cost-effective system. Here we assemble a compact lens-free in-line holographic microscope and employ it to image blood cells flowing in a microfluidic chip, using a high-speed camera and stroboscopic illumination. Numerical reconstruction of the captured holograms allows classification of unlabeled leukocytes into three main subtypes: lymphocytes, monocytes and granulocytes. A scale-space recognition analysis to evaluate cellular size and internal complexity is also developed and used to build a 3-part leukocyte differential. The lens-free image-based classification is compared to the 3-part white blood cell differential generated by using a conventional analyzer on the same blood sample and is found to be in good agreement with it.

Neuronal activity in the bed nucleus of the stria terminalis in a rat model for obsessive-compulsive disorder.

In search of a new potential target for deep brain stimulation in patients with obsessive-compulsive disorder (OCD), we evaluated the single-cell activity of neurons in the bed nucleus of the stria terminalis (BST) in urethane-anesthetized rats in an animal model for OCD, the schedule-induced polydipsia (SIP) model, and compared this to the BST activity in control rats and to a third group of rats which were introduced in the model but did not develop the SIP, and thus were considered resistant. We compared the firing rate and firing pattern of BST neurons between these groups, between hemispheres and made a correlation of the firing rate and firing pattern to the position in the BST. The variability of BST neurons in SIP rats was lower and the randomness higher than BST neurons in control rats or resistant rats. The firing rate of BST neurons in SIP rats was significantly higher and the burst index lower than BST neurons in resistant rats but not in control rats. Also, neurons from the right hemisphere in the SIP group had a higher burst index than neurons from the left hemisphere. However, this is opposite in the resistant and control group. Third, we found a higher bursting index with increasing (more ventral) depth of recording. These findings suggest that schedule-induced polydipsia, which models compulsive behavior in humans, induces a change in firing behavior of BST neurons.

Substrate topography determines neuronal polarization and growth in vitro.

The establishment of neuronal connectivity depends on the correct initial polarization of the young neurons. In vivo, developing neurons sense a multitude of inputs and a great number of molecules are described that affect their outgrowth. In vitro, many studies have shown the possibility to influence neuronal morphology and growth by biophysical, i.e. topographic, signaling. In this work we have taken this approach one step further and investigated the impact of substrate topography in the very early differentiation stages of developing neurons, i.e. when the cell is still at the round stage and when the first neurite is forming. For this purpose we fabricated micron sized pillar structures with highly reproducible feature sizes, and analyzed neurons on the interface of flat and topographic surfaces. We found that topographic signaling was able to attract the polarization markers of mouse embryonic neurons -N-cadherin, Golgi-centrosome complex and the first bud were oriented towards topographic stimuli. Consecutively, the axon was also preferentially extending along the pillars. These events seemed to occur regardless of pillar dimensions in the range we examined. However, we found differences in neurite length that depended on pillar dimensions. This study is one of the first to describe in detail the very early response of hippocampal neurons to topographic stimuli.

A multichannel integrated circuit for electrical recording of neural activity, with independent channel programmability.

Since a few decades, micro-fabricated neural probes are being used, together with microelectronic interfaces, to get more insight in the activity of neuronal networks. The need for higher temporal and spatial recording resolutions imposes new challenges on the design of integrated neural interfaces with respect to power consumption, data handling and versatility. In this paper, we present an integrated acquisition system for in vitro and in vivo recording of neural activity. The ASIC consists of 16 low-noise, fully-differential input channels with independent programmability of its amplification (from 100 to 6000 V/V) and filtering (1-6000 Hz range) capabilities. Each channel is AC-coupled and implements a fourth-order band-pass filter in order to steeply attenuate out-of-band noise and DC input offsets. The system achieves an input-referred noise density of 37 nV/√Hz, a NEF of 5.1, a CMRR > 60 dB, a THD < 1% and a sampling rate of 30 kS/s per channel, while consuming a maximum of 70 µA per channel from a single 3.3 V. The ASIC was implemented in a 0.35 µm CMOS technology and has a total area of 5.6 × 4.5 mm². The recording system was successfully validated in in vitro and in vivo experiments, achieving simultaneous multichannel recordings of cell activity with satisfactory signal-to-noise ratios.