On the Relation between Bursts and Dynamic Synapse Properties: a Modulation-Based Ansatz

When entering a synapse, presynaptic pulse trains are filtered according to the recent pulse history at the synapse and also with respect to their own pulse time course. Various behavioral models have tried to reproduce these complex filtering properties. In particular, the quantal model of neurotransmitter release has been shown to be highly selective for particular presynaptic pulse patterns. However, since the original, pulse-iterative quantal model does not lend itself to mathematical analysis, investigations have only been carried out via simulations. In contrast, we derive a comprehensive explicit expression for the quantal model. We show the correlation between the parameters of this explicit expression and the preferred spike train pattern of the synapse. In particular, our analysis of the transmission of modulated pulse trains across a dynamic synapse links the original parameters of the quantal model to the transmission efficacy of two major spiking regimes, that is, bursting and constant-rate ones

VLSI Implementation of a 2.8 Gevent/s Packet-Based AER Interface with Routing and Event Sorting Functionality

State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike-based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behavior of neuromorphic benchmarks. The specialized, dedicated address-event-representation communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA) delivers a factor 25–50 more event transmission rate than other current neuromorphic communication infrastructures

Segmentation of Blood Vessels in Subtraction Angiographic Images

Abstract Digital radiology leads to a growing amount of medical images which impose severe demands on networking and storage resources. These requirements can be met using content-orientated image compression which reduces the amount of data while preserving the diagnostic information. This paper presents a new method for automated vessel segmentation which can be used for both, decision support systems and content-orientated image compression of angiograms.

Modellierung eines wafer-scale Systems für pulsgekoppelte neuronale Netze

Beim Aufbau von konfigurierbaren wafer-scale Systemen für pulsgekoppelte neuronale Netze werden hohe Anforderungen an die Kommunikation zwischen einzelnen Komponenten gestellt. Zur Unterstützung des Hardwareentwurfs, aber auch um die parallele Entwicklung der Software zu ermöglichen, können Simulationsmodelle verwendet werden. Der Aufbau der Architektur und die Implementierung als SystemC-Modell werden beschrieben. Aus der Simulation sind Rückschlüsse auf die Architektur möglich, es ergeben sich aber auch Anforderungen an die zu entwickelnde Softwareumgebung

Abbildung komplexer, pulsierender, neuronaler Netzwerke auf spezielle Neuronale VLSI Hardware

Im Rahmen des FACETS-Projektes ist die optimierte Abbildung neuronaler Netzwerke durch spezielle Algorithmen auf dafür konzipierte Hardware notwendig, um die Simulation plastischer und pulsierender Modelle zu ermöglichen. Die Erstellung der biologischen und Hardware- Modelle sowie die Konzeptionierung und Analyse der Algorithmen werden in dieser Arbeit vorgestellt