Elisabetta Chicca

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Exploring Neural Computation Using Neuromorphic VLSI Technology

The brain can solve complex perceptual tasks in real time, using low power and unreliable elementary units. Replicating the principle found in biological neural systems is useful for understanding biological processes and these principles also inspire the design of novel systems for practical applications. Neuromorphic engineering uses Very Large Scale Integrated (VLSI) electronic circuits to construct biologically-inspired neural processing systems. My research focus on developing such systems to explore the computational capabilities of large networks of recurrently connected spiking neurons. The importance of this project is that it permits exploration of asynchronous, event-based computation, which is a novel form of processing not yet explored in modern computers.

Publications

2011

2010

  • Indiveri, G and Stefanini, F and Chicca, E Spike-based learning with a generalized integrate and fire silicon neuron, International Symposium on Circuits and Systems, ISCAS 2010 1951-1954, 2010
  • Neftci, Emre and Chicca, Elisabetta and Cook, Matthew and Douglas, Rodney State-Dependent Sensory Processing in Networks of VLSI Spiking Neurons, Iscas proceedings 2010, 2010

2009

  • Indiveri, G. and Chicca, E. and Douglas, R. Artificial cognitive systems: From VLSI networks of spiking neurons to neuromorphic cognition, Cognitive Computation, 1:(2) 119-127, 2009

2008

  • Tapson, J. and Diaz, J. and Sander, D. and Gurari, N. and Chicca, E. and Pouliquen, P. and Etienne-Cummings, R. The Feeling of Color: A Haptic Feedback Device for the Visually Disabled, IEEE Biomedical Circuits and Systems Conference (BioCAS08), 2008

2007

  • Chicca, E. and Indiveri, G. and Douglas, R. J. Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons, Advances in Neural Information Processing Systems 19 257-264, 2007
  • Chicca, E. and Whatley, A. M. and Lichtsteiner, P. and Dante, V. and Delbruck, T. and Del Giudice, P. and Douglas, R. J. and Indiveri, G. A multi-chip pulse-based neuromorphic infrastructure and its application to a model of orientation selectivity, IEEE Transactions on Circuits and Systems I, Regular Papers, 54:(5) 981-993, 2007

2006

  • Chicca, E. and Lichtsteiner, P. and Delbruck, T. and Indiveri, G. and Douglas, R. J. Modeling Orientation Selectivity Using a Neuromorphic Multi-Chip System, Proceedings of IEEE International Symposium on Circuits and Systems 1235-1239, 2006
  • Indiveri, G. and Chicca, E. and Douglas, R. A VLSI array of low-power spiking neurons and bistable synapses with spikeĀ–timing dependent plasticity, IEEE Transactions on Neural Networks, 17:(1) 211-221, 2006

2004

  • Ben Dayan Rubin, D. D. and Chicca, E. and Indiveri, G. Characterizing the firing proprieties of an adaptive analog VLSI neuron, Lecture Notes in Computer Science, 3141: 189-200, 2004
  • Chicca, E. and Indiveri, G. and Douglas, R. J. An event based VLSI network of integrate-and-fire neurons, Proceedings of IEEE International Symposium on Circuits and Systems V-357-V-360, 2004
  • Indiveri, G. and Chicca, E. and Douglas, R. A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses, Proceedings of 12th European Symposium on Artificial Neural Networks (ESANN04) 405-410, 2004

2003

2001

  • Chicca, E. and Fusi, S. Stochastic synaptic plasticity in deterministic aVLSI networks of spiking neurons, Proceedings of the World Congress on Neuroinformatics 468-77, 2001
  • Delbruck, T and Liu, S-C. and Chicca, E and Ricci, GM and Bovet, S A Retina/V1 simple cell chip for physiology experiment design or classroom demonstration, IEEE CCD and AIS meeting, June 7-9, 2001, Lake Tahoe, California , 2001
© 2012 Institut für Neuroinformatik