Large-scale Multi-electrode Array Research Articles

Spike sorting in the presence of stimulation artifacts: a dynamical control systems approach

Objective. Bi-directional electronic neural interfaces, capable of both electrical recording and stimulation, communicate with the nervous system to permit precise calibration of electrical inputs by capturing the evoked neural responses. However, one significant challenge is that stimulation artifacts often mask the actual neural signals. To address this issue, we introduce a novel approach that employs dynamical control systems to detect and decipher electrically evoked neural activity despite the presence of electrical artifacts. Approach. Our proposed method leverages the unique spatiotemporal patterns of neural activity and electrical artifacts to distinguish and identify individual neural spikes. We designed distinctive dynamical models for both the stimulation artifact and each neuron observed during spontaneous neural activity. We can estimate which neurons were active by analyzing the recorded voltage responses across multiple electrodes post-stimulation. This technique also allows us to exclude signals from electrodes heavily affected by stimulation artifacts, such as the stimulating electrode itself, yet still accurately differentiate between evoked spikes and electrical artifacts. Main results. We applied our method to high-density multi-electrode recordings from the primate retina in an ex vivo setup, using a grid of 512 electrodes. Through repeated electrical stimulations at varying amplitudes, we were able to construct activation curves for each neuron. The curves obtained with our method closely resembled those derived from manual spike sorting. Additionally, the stimulation thresholds we estimated strongly agreed with those determined through manual analysis, demonstrating high reliability ( R2=0.951 for human 1 and R2=0.944 for human 2). Significance. Our method can effectively separate evoked neural spikes from stimulation artifacts by exploiting the distinct spatiotemporal propagation patterns captured by a dense, large-scale multi-electrode array. This technique holds promise for future applications in real-time closed-loop stimulation systems and for managing multi-channel stimulation strategies.

GABAergic Inhibition Controls Receptive Field Size, Sensitivity, and Contrast Preference of Direction Selective Retinal Ganglion Cells Near the Threshold of Vision.

Information about motion is encoded by direction-selective retinal ganglion cells (DSGCs). These cells reliably transmit this information across a broad range of light levels, spanning moonlight to sunlight. Previous work indicates that adaptation to low light levels causes heterogeneous changes to the direction tuning of ON-OFF (oo)DSGCs and suggests that superior-preferring ON-OFF DSGCs (s-DSGCs) are biased toward detecting stimuli rather than precisely signaling direction. Using a large-scale multielectrode array, we measured the absolute sensitivity of ooDSGCs and found that s-DSGCs are 10-fold more sensitive to dim flashes of light than other ooDSGCs. We measured their receptive field (RF) sizes and found that s-DSGCs also have larger receptive fields than other ooDSGCs; however, the size difference does not fully explain the sensitivity difference. Using a conditional knock-out of gap junctions and pharmacological manipulations, we demonstrate that GABA-mediated inhibition contributes to the difference in absolute sensitivity and receptive field size at low light levels, while the connexin36-mediated gap junction coupling plays a minor role. We further show that under scotopic conditions, ooDSGCs exhibit only an ON response, but pharmacologically removing GABA-mediated inhibition unmasks an OFF response. These results reveal that GABAergic inhibition controls and differentially modulates the responses of ooDSGCs under scotopic conditions.

Efficient Coding by Midget and Parasol Ganglion Cells in the Human Retina

In humans, midget and parasol ganglion cells account for most of the input from the eyes to the brain. Yet, how they encode visual information is unknown. Here, we perform large-scale multi-electrode array recordings from retinas of treatment-naive patients who underwent enucleation surgery for choroidal malignant melanomas. We identify robust differences in the function of midget and parasol ganglion cells, consistent asymmetries between their ON and OFF types (that signal light increments and decrements, respectively) and divergence in the function of human versus non-human primate retinas. Our computational analyses reveal that the receptive fields of human midget and parasol ganglion cells divide naturalistic movies into adjacent spatiotemporal frequency domains with equal stimulus power, while the asymmetric response functions of their ON and OFF types simultaneously maximize stimulus coverage and information transmission and minimize metabolic cost. Thus, midget and parasol ganglion cells in the human retina efficiently encode our visual environment.

“Silent” NMDA Synapses Enhance Motion Sensitivity in a Mature Retinal Circuit

Retinal direction-selective ganglion cells (DSGCs) have the remarkable ability to encode motion over a wide range of contrasts, relying on well-coordinated excitation and inhibition (E/I). E/I is orchestrated by a diverse set of glutamatergic bipolar cells that drive DSGCs directly, as well as indirectly through feedforward GABAergic/cholinergic signals mediated by starburst amacrine cells. Determining how direction-selective responses are generated across varied stimulus conditions requires understanding how glutamate, acetylcholine, and GABA signals are precisely coordinated. Here, we use a combination of paired patch-clamp recordings, serial EM, and large-scale multi-electrode array recordings to show that a single high-sensitivity source of glutamate is processed differentially by starbursts via AMPA receptors and DSGCs via NMDA receptors. We further demonstrate how this novel synaptic arrangement enables DSGCs to encode direction robustly near threshold contrasts. Together, these results reveal a space-efficient synaptic circuit model for direction computations, in which "silent" NMDA receptors play critical roles.

Cell type-specific changes in retinal ganglion cell function induced by rod death and cone reorganization in rats.

We have determined the impact of rod death and cone reorganization on the spatiotemporal receptive fields (RFs) and spontaneous activity of distinct retinal ganglion cell (RGC) types. We compared RGC function between healthy and retinitis pigmentosa (RP) model rats (S334ter-3) at a time when nearly all rods were lost but cones remained. This allowed us to determine the impact of rod death on cone-mediated visual signaling, a relevant time point because the diagnosis of RP frequently occurs when patients are nightblind but daytime vision persists. Following rod death, functionally distinct RGC types persisted; this indicates that parallel processing of visual input remained largely intact. However, some properties of cone-mediated responses were altered ubiquitously across RGC types, such as prolonged temporal integration and reduced spatial RF area. Other properties changed in a cell type-specific manner, such as temporal RF shape (dynamics), spontaneous activity, and direction selectivity. These observations identify the extent of functional remodeling in the retina following rod death but before cone loss. They also indicate new potential challenges to restoring normal vision by replacing lost rod photoreceptors.NEW & NOTEWORTHY This study provides novel and therapeutically relevant insights to retinal function following rod death but before cone death. To determine changes in retinal output, we used a large-scale multielectrode array to simultaneously record from hundreds of retinal ganglion cells (RGCs). These recordings of large-scale neural activity revealed that following the death of all rods, functionally distinct RGCs remain. However, the receptive field properties and spontaneous activity of these RGCs are altered in a cell type-specific manner.

Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

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

In vitro cyto-biocompatibility study of thin-film transistors substrates using an organotypic culture method.

Thin-Film-Transistors Liquid-Crystal Display has become a standard in the field of displays. However, the structure of these devices presents interest not only in that field, but also for biomedical applications. One of the key components, called here TFT substrate, is a glass substrate with a dense and large array of thousands of transparent micro-electrodes that can be considered as a large scale multi-electrode array(s). Multi-electrode array(s) are widely used for in vitro electrical investigations on neurons and brain, allowing excitation, registration, and recording of their activity. However, the range of application of conventional multi-electrode array(s) is usually limited to some tens of cells in a homogeneous cell culture, because of a small area, small number and a low density of the micro-electrodes. TFT substrates do not have these limitations and the authors are currently studying the possibility to use TFT substrates as new tools for in vitro electrical investigation on tissues and organoids. In this respect, experiments to determine the cyto-biocompatibility of TFT substrates with tissues were conducted and are presented in this study. The investigation was performed using an organotypic culture method with explants of brain and liver tissues of chick embryos. The results in term of morphology, cell migration, cell density and adhesion were compared with the results from Thermanox®, a conventional plastic for cell culture, and with polydimethylsiloxane, a hydrophobic silicone. The results with TFT substrates showed similar results as for the Thermanox®, despite the TFT hydrophobicity. TFT substrates have a weak cell adhesion and promote cell migration similarly to Thermanox®. It could be concluded that the TFT substrates are cyto-biocompatible with the two studied organs.

Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging

Understanding the function of modulatory interneuron networks is a major challenge, because such networks typically operate over long spatial scales and involve many neurons of different types. Here, we use an indirect electrical imaging method to reveal the function of a spatially extended, recurrent retinal circuit composed of two cell types. This recurrent circuit produces peripheral response suppression of early visual signals in the primate magnocellular visual pathway. We identify a type of polyaxonal amacrine cell physiologically via its distinctive electrical signature, revealed by electrical coupling with ON parasol retinal ganglion cells recorded using a large-scale multi-electrode array. Coupling causes the amacrine cells to fire spikes that propagate radially over long distances, producing GABA-ergic inhibition of other ON parasol cells recorded near the amacrine cell axonal projections. We propose and test a model for the function of this amacrine cell type, in which the extra-classical receptive field of ON parasol cells is formed by reciprocal inhibition from other ON parasol cells in the periphery, via the electrically coupled amacrine cell network.

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons.

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.

Ambient illumination switches contrast preference of specific retinal processing streams.

Contrast, a fundamental feature of visual scenes, is encoded in a distributed manner by ∼ 20 retinal ganglion cell (RGC) types, which stream visual information to the brain. RGC types respond preferentially to positive (ON(pref)) or negative (OFF(pref)) contrast and differ in their sensitivity to preferred contrast and responsiveness to nonpreferred stimuli. Vision operates over an enormous range of mean light levels. The influence of ambient illumination on contrast encoding across RGC types is not well understood. Here, we used large-scale multielectrode array recordings to characterize responses of mouse RGCs under lighting conditions spanning five orders in brightness magnitude. We identify three functional RGC types that switch contrast preference in a luminance-dependent manner (Sw1-, Sw2-, and Sw3-RGCs). As ambient illumination increases, Sw1- and Sw2-RGCs shift from ON(pref) to OFF(pref) and Sw3-RGCs from OFF(pref) to ON(pref). In all cases, transitions in contrast preference are reversible and track light levels. By mapping spatiotemporal receptive fields at different mean light levels, we find that changes in input from ON and OFF pathways in receptive field centers underlie shifts in contrast preference. Sw2-RGCs exhibit direction-selective responses to motion stimuli. Despite changing contrast preference, direction selectivity of Sw2-RGCs and other RGCs as well as orientation-selective responses of RGCs remain stable across light levels.

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.

Functional connectivity in the retina at the resolution of photoreceptors

To understand a neural circuit requires knowing its connectivity. This paper reports measurements of functional connectivity between the input and ouput layers of the retina at single cell resolution and its implications for color vision. Multi-electrode technology was employed to record simultaneously from complete populations of the retinal ganglion cell types (midget, parasol, small bistratified) that transmit high-resolution visual signals to the brain. Fine-grained visual stimulation was used to identify the location, type and strength of the functional input of each cone photoreceptor to each ganglion cell. The populations of ON and OFF midget and parasol cells each sampled the complete population of long and middle wavelength sensitive cones. However, only OFF midget cells frequently received strong input from short wavelength sensitive cones. ON and OFF midget cells exhibited a small non-random tendency to selectively sample from either long or middle wavelength sensitive cones, to a degree not explained by clumping in the cone mosaic. These measurements reveal computations in a neural circuit at the elementary resolution of individual neurons.

Neurons show their true colours

How do we tell red from green? Work on the primate retina shows how neural circuitry combines signals from individual cone photoreceptor cells to provide the basic building blocks for colour vision. See Article p.673 Colour vision arises in the retina, and in primates the first stage of processing consists of overlapping lattices of cone cells and ganglion cells, each of which samples visual space uniformly. Colour perception arises from the comparison of signals from different cone types, but how these inputs are combined by the ganglion cells, which transmit the output of the retina, has been an issue of contention over the years. Using large-scale multi-electrode arrays and fine-grained visual stimulation, Field et al. have now mapped out the location and type of single-cone inputs to entire populations of ganglion cells, resulting in input–output maps at an unprecedented resolution and scale.

Receptive Field Mosaics of Retinal Ganglion Cells Are Established Without Visual Experience

A characteristic feature of adult retina is mosaic organization: a spatial arrangement of cells of each morphological and functional type that produces uniform sampling of visual space. How the mosaics of visual receptive fields emerge in the retina during development is not fully understood. Here we use a large-scale multielectrode array to determine the mosaic organization of retinal ganglion cells (RGCs) in rats around the time of eye opening and in the adult. At the time of eye opening, we were able to reliably distinguish two types of ON RGCs and two types of OFF RGCs in rat retina based on their light response and intrinsic firing properties. Although the light responses of individual cells were not yet mature at this age, each of the identified functional RGC types formed a receptive field mosaic, where the spacing of the receptive field centers and the overlap of the receptive field extents were similar to those observed in the retinas of adult rats. These findings suggest that, although the light response properties of RGCs may need vision to reach full maturity, extensive visual experience is not required for individual RGC types to form a regular sensory map of visual space.

Direction Selectivity in the Retina Is Established Independent of Visual Experience and Cholinergic Retinal Waves

Direction selectivity in the retina requires the asymmetric wiring of inhibitory inputs onto four subtypes of On-Off direction-selective ganglion cells (DSGCs), each preferring motion in one of four cardinal directions. The primary model for the development of direction selectivity is that patterned activity plays an instructive role. Here, we use a unique, large-scale multielectrode array to demonstrate that DSGCs are present at eye opening, in mice that have been reared in darkness and in mice that lack cholinergic retinal waves. These data suggest that direction selectivity in the retina is established largely independent of patterned activity and is therefore likely to emerge as a result of complex molecular interactions.

Modeling large-scale neural network culture interface on very-high density multi-electrode arrays

The use of multi-electrode arrays (MEA) technology is developing in neuroscience fields like neuro-pharmacology [1,2], network plasticity investigation [3-5] or neurological diseases [6] and disorders [7]. Dissociated cultures or slices are now often employed on 60–100 multi-site arrays. Recently, matrixes of several thousands of microelectrodes have been developed in order to gain higher spatial resolution from the cell scale up to large network scale. With the framework of a European Consortium (IDEA Project) we developed a 4096 electrode MEA using the Active Pixel Sensor APS technology as well as a computer model of cortical dissociated cultures grown on this device including the neuron-to-electrode interface. Our goal is to better understand the network mechanisms responsible for recorded activity, and to provide integrated software for Computer Aided Design (CAD) of neural engineering devices. Since it was computationally too heavy to work with thousands of interconnected Hodgkin-Huxley cell models, we chose to implement the Izhikevich model which is known as a good compromise between realistic cellular properties and computation time [8]. Indeed, the classical standard leaky integrate-and-fire cellular model can hardly mimic the rich repertoire of intrinsic cellular properties that can be found in biological substrates. We present here the first recordings of high-density MEAs together with dedicated software which can simulate the complete system composed of the electrode matrix and the biological network grown on top. The first results of these large-scale interconnected networks simulations (size and number of cells similar to those recorded in vitro) are consistent with the first recorded data using our prototype of high-density MEAs: (i) the bursts initiation location varies randomly from one place to another, (ii) their propagation varies with the connectivity and the level of presynaptic firing, (iii) the average bursting frequency with no inhibitory connections is close to 1 Hz and similar activity is obtained with bicucculin treated dissociated culture activity. Finally, (iv) the model burst propagation speed is about 100 mm/s and this value has also been computed on real cultures in our lab. This tool is currently used to optimize the design and to investigate the properties of large-scale MEA devices under development and constitutes an innovative neuro-engineering CAD environment.