Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Neuromorphic Cognition

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_113-1



The hallmark of cognitive behavior is the ability of an agent to select an economically advantageous action based on immediate external stimuli as well as on their longer-term context. Neuromorphic cognition refers to the cognitive abilities of systems or agents implemented in neuromorphic electronic VLSI technology whose processing architecture is similar to the distributed, asynchronous one of biological brains. Neuromorphic agents are typically real-time behaving systems composed of multiple asynchronous event-based VLSI chips that integrate networks of silicon neurons and dynamic synapses together and that are interfaced to event-based neuromorphic sensors and robotic actuators. In order to express cognitive performance, these agents require a hardware infrastructure that supports local learning and decision making, for distributed communication and for the...


Synaptic Weight CMOS VLSI Computational Layer Silicon Neuron Neuromorphic System 
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This work was supported by the EU ERC Grant “neuroP” (257219). Part of this work, including the one on soft WTA networks, was done in collaboration with Elisabetta Chicca. We acknowledge also the CapoCaccia and Telluride workshops on neuromorphic engineering (The CapoCaccia Cognitive Neuromorphic Engineering Workshop (http://capocaccia.ethz.ch/) and the Telluride neuromorphic cognition engineering workshop (http://www.ine-web.org)) for fruitful discussions on neuromorphic cognition.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Institute of NeuroinformaticsUniversity of Zurich and ETH ZurichZurichSwitzerland