Efficient Hardware Architecture for Correlation-Based Spike Detection and Unsupervised Clustering

This chapter presents a novel hardware architecture for correlation-based spike detection and unsupervised clustering. The architecture is able to utilize the information extracted from the results of spike clustering for efficient spike detection. The architecture supports the fast computation for the normalized correlation and OSORT operations. The normalized correlation is used for template matching for accurate spike detection. The OSORT algorithm is adopted for unsupervised classification of the detected spikes. The mean of spikes of each cluster produced by the OSORT algorithm is used as the templates for subsequent detection. The architecture adopts postnormalization technique for reducing the area costs. Modified OSORT operations are also proposed for facilitating unsupervised clustering by hardware. The proposed architecture is implemented by field programmable gate array (FPGA) for performance evaluation. In addition to attaining high detection and classification accuracy for spike sorting, experimental results reveal that the proposed architecture is an efficient design providing low area cost and high throughput for real-time offline spike sorting applications

Mechanisms of Feedback in the Visual System

Feedback is an ubiquitous feature of neural systems though there is little consensus on the roles of mechanisms involved with feedback. We set up an in vivo preparation to study and characterize an accessible and isolated feedback loop within the visual system of the leopard frog, Rana pipiens. We recorded extracellularly within the nucleus isthmi, a nucleus providing direct topographic feedback to the optic tectum, a nucleus that receives the vast majority of retinal output. The optic tectum and nucleus isthmi of the amphibian are homologous structures to the superior colliculus and parabigeminal nucleus in mammals, respectively. We formulated a novel threshold for detecting neuronal spikes within a low signal-to-noise environment, as exists in the nucleus isthmi due to its high density of small neuronal cell bodies. Combining this threshold with a recently developed spike sorting procedure enabled us to extract simultaneous recordings from up to 7 neurons at a time from a single extracellular electrode. We then stimulated the frog using computer driven dynamic spatiotemporal visual stimuli to characterize the responses of the nucleus isthmi neurons. We found that the responses display surprisingly long time courses to simple visual stimuli. Furthermore, we found that when stimulated with complex contextual stimuli the response of the nucleus isthmi is quite counter-intuitive. When a stimulus is presented outside of the classical receptive field along with a stimulus within the receptive field, the response is actually higher than the response to just a stimulus within the classical receptive field. Finally, we compared the responses of all of the simultaneously recorded neurons and, together with data from in vitro experiments within the nucleus isthmi, conclude that the nucleus isthmi of the frog is composed of just one electrophysiological population of cells

Méthodes et systèmes pour la détection adaptative et temps réel d'activité dans les signaux biologiques

L intéraction entre la biologie et l électronique est une discpline en pleine essort. De nom-breux systèmes électroniques tentent de s interconnecter avec des tissus ou des cellules vivantesa n de décoder l information biologique. Le Potentiel d action (PA) est au coeur de codagebiologique et par conséquent il est nécéssaire de pouvoir les repérer sur tout type de signal bio-logique. Par conséquent, nous étudions dans ce manuscrit la possibilité de concevoir un circuitélectronique couplé à un système de microélectrodes capable d e ectuer une acquisition, unedétection des PAs et un enregistrement des signaux biologiques. Que ce soit en milieu bruitéou non, nous considérons le taux de détection de PA et la contrainte de temps réel commedes notions primordiales et la consommation en silicium comme un prix à payer. Initialementdéveloppés pour l étude de signaux neuronaux et pancréatiques, ces systèmes conviennent par-faitement pour d autres type de cellules.Interaction between biology and electronic is in expansion. Many electronic systems aretrying to interconnect with tissues or living cells to decode biological information. The ActionPotential (AP) is the heart of biological coding and therefore it is necessary to be able to locateit from any type of biological signal. Therefore, we study in this manuscript the possibility ofdesigning an electronic circuit coupled to microelectrodes capable of acquisition, detection ofPAs and recording of biological signals. Whether or not in a noisy environment, we consider thedetection rate of PA and the real time-computing constraint as an hard speci cationand andsilicon area as a price to pay. Initially developed for the study of neural signals and pancreatic,these systems are ideal for other types of cells.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

Untersuchung von Verarbeitungsalgorithmen zur automatischen Auswertung neuronaler Signale aus Multielektroden-Arrays

Mit Hilfe von Multielektroden-Arrays (MEAs) können viele Zellen gleichzeitig kontaktiert und deren elektrische Aktivität abgeleitet werden. Für die weitere Analyse müssen die abgeleiteten Signale in ihre Einzelbestandteile zerlegt werden. Dieser Vorgang wird als Spike Sorting bezeichnet. In der vorliegenden Arbeit werden Ansätze für ein vollständig automatisiertes Spike Sorting vorgestellt und untersucht. Dabei werden Verfahren aufgezeigt, die mit Hilfe von adaptiven Verfahren die abgeleiteten Zellsignale optimal filtern und automatisch in deren Einzelkomponenten zerlegen

Integration eines Neuro-Sensors in ein Messsystem sowie Untersuchungen zur Unit-Separation

An der Universität Rostock wurde im Rahmen einer Dissertation ein neuartiger CMOS (Complementary Metal Oxide Semiconductor) Sensorchip zur extrazellulären Analyse elektrisch aktiver biologischer Zellen eingesetzt. Dieser Chip besitzt außer einem MEA (Multielektrodenarray) noch weitere FET (Field Effect Transistor)-basierte Sensoren zur Erfassung unterschiedlicher Zellparameter. Neben der Inbetriebnahme dieses Sensors wurden externe Hardware zur Messwerterfassung und Algorithmen zur Signalaufbereitung entworfen und realisiert. Das Ziel war die Schaffung eines Cell Monitor Systems (CMS) zur teilautomatisierten Nutzung des Silizium-basierten Sensorchips.At the University of Rostock a new hybrid CMOS (Complementary Metal Oxide Semiconductor) sensor chip has been applied to analyse biological electrogenic cells. This chip consists of a MEA (Multi Electrode Array) and several types of FET (Field Effect Transistor) based sensors to monitor substance dependent cell reactions in-vitro. The system consists of the actual sensor chip including a cell culture area, an external hardware platform for data acquisition and digital signal processing algorithms for signal conditioning. Finally a Cell Monitor System (CMS) for the semi-automatic data acquisition was realised to increase the efficiency of the sensor chip usage

Methods for analyzing the influence of molecular dynamics on neuronal activity

Magdeburg, Univ., Fak. für Informatik, Diss., 2015von Stefan Sokol