Christian Mayr

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Particulate organic matter (POM) and dissolved organic carbon (DOC) release by six dominant hermatypic coral genera (Acropora, Fungia, Goniastrea, Millepora, Pocillopora and Stylophora) were measured under undisturbed conditions by laboratory incubations during four seasonal expeditions to the Northern Red Sea. In addition, the influence of environmental(More)
The computational function of neural networks is thought to depend primarily on the learning/plasticity function carried out at the synapse. Neuromorphic circuit realizations have taken this into account by implementing a variety of synaptical processing functions, with most recent synapse circuits replicating some form of Spike Time Dependent Plasticity(More)
In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from(More)
Classically, action-potential-based learning paradigms such as the Bienenstock-Cooper-Munroe (BCM) rule for pulse rates or spike timing-dependent plasticity for pulse pairings have been experimentally demonstrated to evoke long-lasting synaptic weight changes (i.e., plasticity). However, several recent experiments have shown that plasticity also depends on(More)
In this paper, we present a system architecture currently under development that will allow very large (>10 neurons, >10 synapses) reconfigurable networks to be built, in the form of interlinked dies on a single wafer. Reconfigurable routing and complex adaptation/plasticity across several timescales in neurons and synapses allow for the implementation of(More)
Memristive devices present a new device technology allowing for the realization of compact non-volatile memories. Some of them are already in the process of industrialization. Additionally, they exhibit complex multilevel and plastic behaviors, which make them good candidates for the implementation of artificial synapses in neuromorphic engineering.(More)
The information processing of neural networks depends heavily on the learning/plasticity function carried out at the individual synapses. Traditionally, neuromorphic ICs have integrated forms of Spike-Time-Dependent-Plasticity (STDP), a subset of the rich repertoire of biological plasticity. However, STDP is challenged by rate-dependent learning as well as(More)
Conventional treatment of hematologic malignancies mainly consists of chemotherapeutic agents or a combination of both, chemotherapy and monoclonal antibodies. Despite recent advances, chemotherapeutic treatments often remain unsatisfying due to severe side effects and incomplete long-term remission. Therefore the evaluation of novel therapeutic options is(More)
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(More)