Défavorisation sociale et facteurs associés au dépistage du SARS-CoV-2 à l'échelle locale dans une région du Sud de la France entre Juillet 2020 et Janvier 2022

Introduction

Les inégalités sociales sont fortement associées aux inégalités de santé, que ce soit pour les maladies chroniques ou infectieuses. Le SARS-CoV-2 ne fait pas exception, l'étude nationale EpiCov ayant montré dès juin 2020 un risque de COVID-19 croissant avec la défavorisation sociale.

Le dépistage demeure un des piliers du contrôle de cette pandémie, tant à l'échelle individuelle pour l'isolement des cas et de leurs contacts à risque, que populationnelle pour identifier et cibler certaines mesures d'accompagnement. L'accès au dépistage ne saurait être considéré comme uniforme, tant l'accès au soin apparaît déficitaire dans certains territoires (zones urbaines défavorisées, rurales). Par ailleurs, le manque de prise en compte des inégalités sociales dans les mesures de suivi des cas a été souligné.

Notre objectif était de prendre en compte le sous-diagnostic du SARS-CoV-2 lié à la défavorisation sociale afin d'améliorer le ciblage des actions de santé publique à l'échelle régionale.

Matériels et méthodes

Le nombre de tests (RT-PCR et antigéniques) et de cas de COVID-19 positifs enregistrés dans la base SI-DEP ont été agrégées à l'échelle spatiale des IRIS (subdivision géographique d'environ 2000 habitants) et temporelle selon des périodes correspondant aux grandes mesures de contrôle de l'épidémie (pré-, pendant, post-confinement, passe sanitaire…). Les taux de dépistage, d'incidence de COVID-19 et de positivité des tests ont été définis par IRIS et par période.

Nous avons caractérisé le profil socio-démographique de chaque IRIS à partir de données de population et d'accès au soin (source INSEE et DREES), et de l'European Deprivation Index (EDI), indicateur spécifique de défavorisation sociale.

Enfin, nous avons analysé le ratio de taux de dépistage (RTD) selon le profil socio-démographique après ajustement sur l'accès au soin, au moyen d'un modèle additif généralisé hiérarchique prenant en compte l'autocorrélation spatiale entre les IRIS voisins.

Résultats

Nous avons distingué 10 périodes entre Juillet 2020 et Janvier 2022, et identifié six profils d'IRIS : un profil rural, un rural/péri-urbain, et quatre profils urbains correspondant respectivement à des IRIS aisés, denses de centre-ville, défavorisées, et denses très défavorisées.

Le taux de dépistage des IRIS urbains très défavorisés était systématiquement inférieur au taux de dépistage des IRIS urbains/péri-urbains aisés (RTD entre 0.85 (IC95 %=0.80-0.91) et 0.64 (0.59-0.69)). Les pics d'incidence de COVID-19 ont été atteints plus tardivement dans les IRIS très défavorisées que dans les IRIS aisés lors de périodes de confinement (novembre 2020) ou de périodes de vaccination massive (juillet 2021).

Conclusion

Cette étude a permis d'identifier une liste limitée d'IRIS caractérisés par un sous-dépistage et un retard d'efficacité des mesures sanitaires de freinage de la COVID-19. Ils ont ainsi pu être priorisés dans les interventions mises en place par les acteurs régionaux et locaux de la réponse à la pandémie.

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Massively parallel microwire arrays integrated with CMOS chips for neural recording

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

West Nile virus infections in France, July to November 2018

Key messages

We describe the most important episode of West Nile Virus transmission identified in humans in France. In 2018, West Nile virus lineage 2 was isolated for the first time in France which might change the epidemiological situation in the country.

Autochthonous chikungunya and dengue fever outbreak in Mainland France, 2010-2018

Background

Aedes albopictus, vector of dengue and chikungunya viruses, is implanted in mainland France, exposing to the risk of autochthonous transmission. Since 2006, epidemiological and entomological surveillance activities aim to prevent or limit the occurrence of autochthonous cases. We aimed to describe episodes of transmission and control measures implemented in order to reflect on surveillance activities.

Methods

We reviewed all publications and documents produced on autochthonous transmission episodes in France and surveillance protocols. We reviewed surveillance activities, investigation methods and control measures implemented.

Results

Between 2010 and 2018, eight episodes of autochthonous dengue fever transmission and three of chikungunya were recorded in mainland France. All of them occurred in the South east of France, between July and October, when vector density was the highest. Transmission areas were limited to single domestic houses located in discontinuous urban areas. Only two episodes happened in two distinct areas. Chikungunya episodes led to 31 cases and dengue fever episodes to 23 cases. Most cases were identified by door-to-door investigations set-up in transmission areas. We isolated serotypes 1 and 2 for dengue and East Central South Africa lineage for chikungunya in autochthonous cases. Adulticide vector control measures were effective in controlling transmission.

Seven episodes of transmission were due to failure in identifying primary imported cases. Four episodes occurred because of the absence or the lack of vector controls measures around primary imported cases.

Conclusions

Surveillance activities, and autochthonous cases investigations, were effective in limiting the extent of transmission, but were highly demanding for surveillance actors. Identified causes of transmission highlight the need of regular awareness campaigns targeting physicians and biologists.

Key messages

Effectiveness of the surveillance system of dengue, chikungunya and zika viruses, and autochthonous cases investigations. Needs of awareness and training courses targeting health professionals to the risk represented by these viruses.

Monitoring measles outbreaks using emergency department data in France

Background

Measles’ outbreaks still occur in industrialised countries and reactive monitoring of the disease is needed. In France, measles’ monitoring is based on a mandatory notification (MN).

Methods

In France, for each emergency department (ED) visit, an Electronic ED Abstract (EEDA) is transmitted to the OSCOUR® network included in national Syndromic Surveillance System. EEDA include the diagnosis at discharge using International Classification of Disease (ICD-10). This study aims to evaluate the correlation between the number of measles MN and the number of ED visits related to measles and to calculate the positive predictive value (PPV) of diagnosis at discharge of measles in ED. The study period covered the third wave of the 2008-2011 French outbreak. From 2010 to 2011, we analyzed EEDA transmitted from 32/53 ED of the PACA region and regional measles MN. Using weekly aggregated data, the correlation between the number of measles cases given by both MN and ED sources was assessed (Pearson coefficient). In the 4 ED (2 pediatric) of the teaching hospital of Marseille, electronic medical files coded as measles were reviewed to evaluate the PPV of the diagnosis coded according to the national MN case definition (gold standard).

Results

2,949 MN were transmitted and 1,306/1.3 million visits in ED were coded as measles. The peak of the outbreak was reported the same week by EEDA and MN. The correlation between EEDA and MN was strong (0.91; p < 0.001). Hospitalization rate was 20.7% and 21.0% according to EEDA and MN (p = 0.81). Among 363 medical files coded as measles in the 4 ED, 14 cases (3.9%) did not fulfilled the national case definition (PPV: 96.1 [IC95%: 94.2-98.1]), 86 (23.7%) fulfilled criteria for “clinical case” and 263 (72.5%) for “confirmed case".

Conclusions

Most of the time, ED visits coded as measles fulfilled diagnosis criteria. Our results suggested that EEDA (better reactivity) could be complementary to MN (better completeness) to monitor measles.

Key messages

Most of the time, ED visits coded as measles fulfilled diagnosis criteria: PPV of coded medical diagnosis in ED for measles is high. Reactivity of ED data monitoring could usefully complete mandatory notification for measles surveillance.

Technologies to Study Action Potential Propagation With a Focus on HD-MEAs

Axons convey information in neuronal circuits via reliable conduction of action potentials (APs) from the axon initial segment (AIS) to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of APs. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e., genetically encoded voltage imaging (GEVI), subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays (MEAs), intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.

Medullary Respiratory Circuit Is Reorganized by a Seasonally-Induced Program in Preparation for Hibernation

Deep hibernators go through several cycles of profound drops in body temperature during the winter season, with core temperatures sometimes reaching near freezing. Yet unlike non-hibernating mammals, they can sustain breathing rhythms. The physiological processes that make this possible are still not understood. In this study, we focused on the medullary Ventral Respiratory Column of a facultative hibernator, the Syrian hamster. Using shortened day-lengths, we induced a "winter-adapted" physiological state, which is a prerequisite for hibernation. When recording electrophysiological signals from acute slices in the winter-adapted pre-Bötzinger complex (preBötC), spike trains showed higher spike rates, amplitudes, complexity, as well as higher temperature sensitivity, suggesting an increase in connectivity and/or synaptic strength during the winter season. We further examined action potential waveforms and found that the depolarization integral, as measured by the area under the curve, is selectively enhanced in winter-adapted animals. This suggests that a shift in the ion handling kinetics is also being induced by the winter-adaptation program. RNA sequencing of respiratory pre-motor neurons, followed by gene set enrichment analysis, revealed differential regulation and splicing in structural, synaptic, and ion handling genes. Splice junction analysis suggested that differential exon usage is occurring in a select subset of ion handling subunits (ATP1A3, KCNC3, SCN1B), and synaptic structure genes (SNCB, SNCG, RAB3A). Our findings show that the hamster respiratory center undergoes a seasonally-cued alteration in electrophysiological properties, likely protecting against respiratory failure at low temperatures.

Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies

Advances in microfabrication technology have enabled the production of devices containing arrays of thousands of closely spaced recording electrodes, which afford subcellular resolution of electrical signals in neurons and neuronal networks. Rationalizing the electrode size and configuration in such arrays demands consideration of application-specific requirements and inherent features of the electrodes. Tradeoffs among size, spatial density, sensitivity, noise, attenuation, and other factors are inevitable. Although recording extracellular signals from neurons with planar metal electrodes is fairly well established, the effects of the electrode characteristics on the quality and utility of recorded signals, especially for small, densely packed electrodes, have yet to be fully characterized. Here, we present a combined experimental and computational approach to elucidating how electrode size, and size-dependent parameters, such as impedance, baseline noise, and transmission characteristics, influence recorded neuronal signals. Using arrays containing platinum electrodes of different sizes, we experimentally evaluated the electrode performance in the recording of local field potentials (LFPs) and extracellular action potentials (EAPs) from the following cell preparations: acute brain slices, dissociated cell cultures, and organotypic slice cultures. Moreover, we simulated the potential spatial decay of point-current sources to investigate signal averaging using known signal sources. We demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se, especially for electrodes <10 μm in width or diameter to achieve high-spatial-resolution readout. By minimizing electrode impedance of small electrodes (<10 μm) via surface modification, we could maximize the signal-to-noise ratio to electrically visualize the propagation of axonal EAPs and to isolate single-unit spikes. Due to the large amplitude of LFP signals, recording quality was high and nearly independent of electrode size. These findings should be of value in configuring in vitro and in vivo microelectrode arrays for extracellular recordings with high spatial resolution in various applications.

Abstract P6-18-04: Ribociclib with a non-steroidal aromatase inhibitor and goserelin in premenopausal women with hormone receptor-positive, HER2-negative advanced breast cancer: MONALEESA-7 age subgroup analysis

Background: Younger patients (pts) with breast cancer may experience more aggressive disease and are more likely to die from their cancer vs older pts. In the Phase III MONALEESA-7 study (NCT02278120), the addition of ribociclib (RIB; cyclin-dependent kinase 4/6 inhibitor) to a non-steroidal aromatase inhibitor (NSAI) or tamoxifen (TAM) + goserelin significantly prolonged progression-free survival (PFS) in premenopausal women with hormone receptor-positive (HR+), HER2-negative (HER2–) advanced breast cancer (ABC; hazard ratio 0.553; p&lt;0.0001). RIB treatment benefit was observed irrespective of endocrine partner (NSAI or TAM). Here we report results from a MONALEESA-7 subgroup analysis in pts aged &lt;40 yrs and ≥40 yrs who received RIB or placebo (PBO) in combination with an NSAI + goserelin.

Methods: Pre- or perimenopausal women with HR+, HER2– ABC who had received no prior endocrine therapy and ≤1 line of chemotherapy for ABC were enrolled. Of the 672 pts randomized, 495 (74%) received RIB (600 mg/day, 3-weeks-on/1-week-off) or PBO + an NSAI (letrozole [2.5 mg/day] or anastrozole [1 mg/day]) and goserelin (3.6 mg every 28 days). The primary endpoint was locally assessed PFS; secondary endpoints included overall response rate (ORR), clinical benefit rate (CBR), and safety. A prespecified subgroup analysis was performed in pts aged &lt;40 yrs and ≥40 yrs.

Results: A total of 144 pts were aged &lt;40 yrs (RIB vs PBO arm: 78 vs 66) and 351 were aged ≥40 yrs (170 vs 181). As of August 20, 2017, in the RIB vs PBO arms, treatment was ongoing in 50% vs 23% of pts aged &lt;40 yrs and 54% vs 43% of pts aged ≥40 yrs; disease progression was the most common reason for treatment discontinuation (&lt;40 yrs: 37% vs 68%; ≥40 yrs: 35% vs 44%). Median PFS was prolonged in the RIB vs PBO arms both in pts aged &lt;40 yrs (not reached vs 10.8 months; hazard ratio 0.435; 95% confidence interval [CI] 0.276–0.686) and in pts aged ≥40 yrs (27.5 vs 19.1 months; hazard ratio 0.625; 95% CI 0.449–0.870). In pts with measurable disease, the ORR (RIB vs PBO arm) was 49% vs 32% in pts aged &lt;40 yrs and 51% vs 38% in pts aged ≥40 yrs; CBR was 81% vs 61% and 82% vs 65%, respectively. The most common Grade 3 adverse events (AEs; ≥5% of pts in either arm; RIB vs PBO arm) were neutropenia (&lt;40 yrs: 47% vs 5%; ≥40 yrs: 58% vs 3%), leukopenia (&lt;40 yrs: 18% vs 2%; ≥40 yrs: 14% vs 1%), diarrhea (&lt;40 yrs: 5% vs 0; ≥40 yrs: 1% vs 0), and increased alanine aminotransferase (&lt;40 yrs: 4% vs 2%; ≥40 yrs: 5% vs 1%); neutropenia was the only Grade 4 AE occurring in ≥5% of pts in either arm (&lt;40 yrs: 15% vs 0; ≥40 yrs: 8% vs 1%). New post-baseline QTcF &gt;480 ms (RIB vs PBO arm) occurred in 3% vs 2% of pts aged &lt;40 yrs and 7% vs 1% of pts aged ≥40 yrs.

Conclusions: Consistent treatment benefit was observed with RIB + NSAI vs PBO + NSAI in premenopausal women with HR+, HER2– ABC irrespective of age. RIB + NSAI had a manageable safety profile in pts aged &lt;40 yrs and in those aged ≥40 yrs, with a safety profile similar to that observed in the full study population.

Citation Format: Tripathy D, Campos-Gomez S, Lu Y-S, Franke F, Bardia A, Wheatley-Price P, Cruz FM, Hegg R, Cardoso F, Gaur A, Kong O, Diaz-Padilla I, Miller M, Hurvitz S. Ribociclib with a non-steroidal aromatase inhibitor and goserelin in premenopausal women with hormone receptor-positive, HER2-negative advanced breast cancer: MONALEESA-7 age subgroup analysis [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-18-04.

Automatic spike sorting for high-density microelectrode arrays

High-density microelectrode arrays can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike sorters must be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multielectrodes, however, suffer from the "curse of dimensionality" and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal component analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently with classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data prewhitening before the principal component analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and that were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation was not required. NEW & NOTEWORTHY We present an automatic spike sorting algorithm that combines three strategies to scale classical spike sorting techniques for high-density microelectrode arrays: 1) splitting the recording electrodes into small groups and sorting them independently; 2) clustering a subset of spikes and classifying the rest to limit computation time; and 3) prewhitening the spike waveforms to enable the use of parameter-free clustering. Finally, we combined these strategies into an automatic spike sorter that is competitive with state-of-the-art spike sorters.

How Diverse Retinal Functions Arise from Feedback at the First Visual Synapse

Many brain regions contain local interneurons of distinct types. How does an interneuron type contribute to the input-output transformations of a given brain region? We addressed this question in the mouse retina by chemogenetically perturbing horizontal cells, an interneuron type providing feedback at the first visual synapse, while monitoring the light-driven spiking activity in thousands of ganglion cells, the retinal output neurons. We uncovered six reversible perturbation-induced effects in the response dynamics and response range of ganglion cells. The effects were enhancing or suppressive, occurred in different response epochs, and depended on the ganglion cell type. A computational model of the retinal circuitry reproduced all perturbation-induced effects and led us to assign specific functions to horizontal cells with respect to different ganglion cell types. Our combined experimental and theoretical work reveals how a single interneuron type can differentially shape the dynamical properties of distinct output channels of a brain region.

Tracking individual action potentials throughout mammalian axonal arbors

Axons are neuronal processes specialized for conduction of action potentials (APs). The timing and temporal precision of APs when they reach each of the synapses are fundamentally important for information processing in the brain. Due to small diameters of axons, direct recording of single AP transmission is challenging. Consequently, most knowledge about axonal conductance derives from modeling studies or indirect measurements. We demonstrate a method to noninvasively and directly record individual APs propagating along millimeter-length axonal arbors in cortical cultures with hundreds of microelectrodes at microsecond temporal resolution. We find that cortical axons conduct single APs with high temporal precision (~100 µs arrival time jitter per mm length) and reliability: in more than 8,000,000 recorded APs, we did not observe any conduction or branch-point failures. Upon high-frequency stimulation at 100 Hz, successive became slower, and their arrival time precision decreased by 20% and 12% for the 100th AP, respectively.

Acquisition of Bioelectrical Signals with Small Electrodes

Although the mechanisms of recording bioelectrical signals from different types of electrogenic cells (neurons, cardiac cells etc.) by means of planar metal electrodes have been extensively studied, the recording characteristics and conditions for very small electrode sizes are not yet established. Here, we present a combined experimental and computational approach to elucidate, how the electrode size influences the recorded signals, and how inherent properties of the electrode, such as impedance, noise, and transmission characteristics shape the signal. We demonstrate that good quality recordings can be achieved with electrode diameters of less than 10 µm, provided that impedance reduction measures have been implemented and provided that a set of requirements for signal amplification has been met.

Travel-associated and autochthonous Zika virus infection in mainland France, 1 January to 15 July 2016

During summer 2016, all the conditions for local mosquito-borne transmission of Zika virus (ZIKV) are met in mainland France: a competent vector, Aedes albopictus, a large number of travellers returning from ZIKV-affected areas, and an immunologically naive population. From 1 January to 15 July 2016, 625 persons with evidence of recent ZIKV infection were reported in mainland France. We describe the surveillance system in place and control measures implemented to reduce the risk of infection.

Congenital Nystagmus Gene FRMD7 Is Necessary for Establishing a Neuronal Circuit Asymmetry for Direction Selectivity

Neuronal circuit asymmetries are important components of brain circuits, but the molecular pathways leading to their establishment remain unknown. Here we found that the mutation of FRMD7, a gene that is defective in human congenital nystagmus, leads to the selective loss of the horizontal optokinetic reflex in mice, as it does in humans. This is accompanied by the selective loss of horizontal direction selectivity in retinal ganglion cells and the transition from asymmetric to symmetric inhibitory input to horizontal direction-selective ganglion cells. In wild-type retinas, we found FRMD7 specifically expressed in starburst amacrine cells, the interneuron type that provides asymmetric inhibition to direction-selective retinal ganglion cells. This work identifies FRMD7 as a key regulator in establishing a neuronal circuit asymmetry, and it suggests the involvement of a specific inhibitory neuron type in the pathophysiology of a neurological disease.

Video Abstract

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FRMD7 is required for the horizontal optokinetic reflex in mice as in humans

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Horizontal direction selectivity is lost in the retina of FRMD7 mutant mice

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Asymmetry of inhibitory inputs to horizontal DS cells is lost in FRMD7 mutant mice

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FRMD7 is expressed in ChAT-expressing cells in the retina of mice and primates

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations.

A method for electrophysiological characterization of hamster retinal ganglion cells using a high-density CMOS microelectrode array

Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 μm electrode pitch), we were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience, and latency. These properties were clustered to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density of 2780 cells/mm² at 2 mm (42°) from the optic nerve head. Using five parameters extracted from the responses to visual stimuli, we obtained seven ganglion cell types.

Visual coding with a population of direction-selective neurons

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions.

Spike sorting of synchronous spikes from local neuron ensembles

Synchronous spike discharge of cortical neurons is thought to be a fingerprint of neuronal cooperativity. Because neighboring neurons are more densely connected to one another than neurons that are located further apart, near-synchronous spike discharge can be expected to be prevalent and it might provide an important basis for cortical computations. Using microelectrodes to record local groups of neurons does not allow for the reliable separation of synchronous spikes from different cells, because available spike sorting algorithms cannot correctly resolve the temporally overlapping waveforms. We show that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure. Using tetrodes with a three-dimensional structure, we demonstrate with simulated data and ground truth in vitro data, obtained by dual intracellular recording of two neurons located next to a tetrode, that the spike sorting of synchronous spikes can be as successful as the spike sorting of nonoverlapping spikes and that the spatial information provided by multielectrodes greatly reduces the error rates. We apply the method to tetrode recordings from the prefrontal cortex of behaving primates, and we show that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons.

ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms

BACKGROUND

New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times.

NEW METHOD

We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy.

RESULTS

ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval.

COMPARISON WITH EXISTING METHODS

ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers.

CONCLUSION

ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity.

Highly integrated CMOS microsystems to interface with neurons at subcellular resolution

CMOS high-density transducer arrays enable fundamentally new neuroscientific insights through, e.g., facilitating investigation of axonal signaling characteristics, with the "axonal" side of neuronal activity being largely inaccessible to established methods. They also enable high-throughput monitoring of potentially all action potentials in a larger neuronal network (> 1000 neurons) over extended time to see developmental effects or effects of disturbances. Applications include research in neural diseases and pharmacology.

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

High-Throughput Hardware for Real-Time Spike Overlap Decomposition in Multi-Electrode Neuronal Recording Systems

Spike overlaps occur frequently in dense neuronal network recordings, creating difficulties for spike sorting. Brainmachine interfaces and in vivo studies of neuronal network dynamics often require that an accurate spike sorting be done in real time, with low execution latency (on the order of milliseconds). Moreover, modern neuronal recording systems that feature thousands of electrodes require processing of several tens or hundreds of neurons in parallel. The existing algorithms capable of performing spike overlap decomposition are generally very complex and unsuitable for real-time implementation, especially for an on-chip implementation. Here we present a hardware device capable of processing pair-wise spike overlaps in real time. A previously-published spike sorting algorithm, which is not suitable for processing data of large neuronal networks with low latency, has been optimized for high-throughput, low-latency hardware implementation. The designed hardware architecture has been verified on an FPGA platform. Low spike sorting error rates (0.05) for overlapping spikes have been achieved with a latency of 2.75 ms, rendering the system particularly suitable for use in closed-loop experiments.

Real-time monitoring of immobilized single yeast cells through multifrequency electrical impedance spectroscopy

We present a microfluidic device, which enables single cells to be reliably trapped and cultivated while simultaneously being monitored by means of multifrequency electrical impedance spectroscopy (EIS) in the frequency range of 10 kHz-10 MHz. Polystyrene beads were employed to characterize the EIS performance inside the microfluidic device. The results demonstrate that EIS yields a low coefficient of variation in measuring the diameters of captured beads (~0.13%). Budding yeast, Saccharomyces cerevisiae, was afterwards used as model organism. Single yeast cells were immobilized and measured by means of EIS. The bud growth was monitored through EIS at a temporal resolution of 1 min. The size increment of the bud, which is difficult to determine optically within a short time period, can be clearly detected through EIS signals. The impedance measurements also reflect the changes in position or motion of single yeast cells in the trap. By analyzing the multifrequency EIS data, cell motion could be qualitatively discerned from bud growth. The results demonstrate that single-cell EIS can be used to monitor cell growth, while also detecting potential cell motion in real-time and label-free approach, and that EIS constitutes a sensitive tool for dynamic single-cell analysis.

Parameters for burst detection

Bursts of action potentials within neurons and throughout networks are believed to serve roles in how neurons handle and store information, both in vivo and in vitro. Accurate detection of burst occurrences and durations are therefore crucial for many studies. A number of algorithms have been proposed to do so, but a standard method has not been adopted. This is due, in part, to many algorithms requiring the adjustment of multiple ad-hoc parameters and further post-hoc criteria in order to produce satisfactory results. Here, we broadly catalog existing approaches and present a new approach requiring the selection of only a single parameter: the number of spikes N comprising the smallest burst to consider. A burst was identified if N spikes occurred in less than T ms, where the threshold T was automatically determined from observing a probability distribution of inter-spike-intervals. Performance was compared vs. different classes of detectors on data gathered from in vitro neuronal networks grown over microelectrode arrays. Our approach offered a number of useful features including: a simple implementation, no need for ad-hoc or post-hoc criteria, and precise assignment of burst boundary time points. Unlike existing approaches, detection was not biased toward larger bursts, allowing identification and analysis of a greater range of neuronal and network dynamics.