Large-scale multielectrode recording and stimulation of neural activity

Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

Ultrasonic testing of the rails

Badania wykonywane w trakcie produkcji i eksploatacji mają dać odpowiedź o prawidłowości wykonania wyrobów jakimi są szyny kolejowe. Wykonywane są m.in. badania wizualne i ultradźwiękowe. Badania wizualne stanowią podstawowe badania nieniszczące w diagnostyce szyn kolejowych. W katalogu szyn dokonano klasyfikacji wad takich uszkodzeń jak np. pęknięcia. Odnaleźć tam można informacje dotyczące lokalizacji, położenia czy przyczyn powstawania wad w szynach. Jednym z pierwszych zastosowań badań ultradźwiękowych jest wykrywanie wad w szynach. Celem badania jest wykrycie wad występujących w objętości materiału oraz oceny ich wielkości. Badanie szyn zamocowanych na torze powoduje wprowadzanie fal ultradźwiękowych z powierzchni główki przez warstwę cieczy sprzęgającej z powierzchnią badania. Niemożliwy jest dostęp z powierzchni stopki i nie można wykryć rozwijających się pęknięć eksploatacyjnych w stopce. Zastosowanie przy wykonywaniu badań ultradźwiękowych znajdują miedzy innymi technika echa, technika tandem czy nowoczesna technika ultradźwiękowa Phased-Array.Tests carried out during production and exploitation are to give an answer about the correctness of made products such as rails. Visual and ultrasonic examination are performed. Visual examinations are basic non-destructive examinations in rails diagnostics. In the rails catalog, defects of such damage like cracks were classified. You can find there information about the location, position or causes of defects in the rails. Detection of defects in rails is one of the first applications of ultrasonic testing. The aim of the study is to detect defects occurring in the volume of the material and evaluation of their size. Examination of rails mounted on the track causes the introduction of ultrasonic waves from the surface of the head through the coupling liquid layer with the surface of the test. Access from the surface of footer is impossible and no detectable cracks in the footer can be detected. Application in performing in the field of ultrasonic testing include echo technique, tandem technique or modern ultrasonic technique Phased-Array

Properties and application of a multichannel integrated circuit for low-artifact, patterned electrical stimulation of neural tissue

Modern multielectrode array (MEA) systems can record the neuronal activity from thousands of electrodes, but their ability to provide spatio-temporal patterns of electrical stimulation is very limited. Furthermore, the stimulus-related artifacts significantly limit the ability to record the neuronal responses to the stimulation. To address these issues, we designed a multichannel integrated circuit for a patterned MEA-based electrical stimulation and evaluated its performance in experiments with isolated mouse and rat retina. The Stimchip includes 64 independent stimulation channels. Each channel comprises an internal digital-to-analogue converter that can be configured as a current or voltage source. The shape of the stimulation waveform is defined independently for each channel by the real-time data stream. In addition, each channel is equipped with circuitry for reduction of the stimulus artifact. Main results. Using a high-density MEA stimulation/recording system, we effectively stimulated individual retinal ganglion cells (RGCs) and recorded the neuronal responses with minimal distortion, even on the stimulating electrodes. We independently stimulated a population of RGCs in rat retina, and using a complex spatio-temporal pattern of electrical stimulation pulses, we replicated visually evoked spiking activity of a subset of these cells with high fidelity. Significance. Compared with current state-of-the-art MEA systems, the Stimchip is able to stimulate neuronal cells with much more complex sequences of electrical pulses and with significantly reduced artifacts. This opens up new possibilities for studies of neuronal responses to electrical stimulation, both in the context of neuroscience research and in the development of neuroprosthetic devices

Multiplex networks of cortical and hippocampal neurons revealed at different timescales

10.1371/journal.pone.0115764PLoS ONE912e11576

Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible

Large-scale, high-resolution multielectrode-array recording depicts functional network differences of cortical and hippocampal cultures

10.1371/journal.pone.0105324PLoS ONE98e10532

High-Degree Neurons Feed Cortical Computations

10.1371/journal.pcbi.1004858PLoS Computational Biology125e100485

Optimization of electrical stimulation for a high-fidelity artificial retina

Retinal prostheses aim to restore visual perception in patients blinded by photoreceptor degeneration, by stimulating surviving retinal ganglion cells (RGCs), causing them to send artificial visual signals to the brain. Present-day devices produce limited vision, in part due to indiscriminate and simultaneous activation of many RGCs of different types that normally signal asynchronously. To improve artificial vision, we propose a closed-loop, cellular-resolution device that automatically identifies the types and properties of nearby RGCs, calibrates its stimulation to produce a dictionary of achievable RGC activity patterns, and then uses this dictionary to optimize stimulation patterns based on the incoming visual image. To test this concept, we use a high-density multi-electrode array as a lab prototype, and deliver a rapid sequence of electrical stimuli from the dictionary, progressively assembling a visual image within the visual integration time of the brain. Greedily minimizing the error between the visual stimulus and a linear reconstruction (as a surrogate for perception) yields a real-time algorithm with an efficiency of 96% relative to optimum. This framework also provides insights for developing efficient hardware. For example, using only the most effective 50% of electrodes minimally affects performance, suggesting that an adaptive device configured using measured properties of the patient's retina may permit efficiency with accuracy