We present a biomimetic system that captures essential functional properties of the glomerular layer of the mammalian olfactory bulb, specifically including its capacity to decorrelate similar odor representations without foreknowledge of the statistical distributions of analyte features. Our system is based on a digital neuromorphic chip consisting of 256 leaky-integrate-and-fire neurons, 1024 × 256 crossbar synapses, and address-event representation communication circuits. The neural circuits configured in the chip reflect established connections among mitral cells, periglomerular cells, external tufted cells, and superficial short-axon cells within the olfactory bulb, and accept input from convergent sets of sensors configured as olfactory sensory neurons. This configuration generates functional transformations comparable to those observed in the glomerular layer of the mammalian olfactory bulb. Our circuits, consuming only 45 pJ of active power per spike with a power supply of 0.85 V, can be used as the first stage of processing in low-power artificial chemical sensing devices inspired by natural olfactory systems.
Keywords: neuromorphic, biomimetic, olfaction, artificial chemical sensing, neurosynaptic core, small-world, digital neuron, AER
Citation: Imam N, Cleland TA, Manohar R, Merolla PA, Arthur JV, Akopyan F and Modha DS (2012) Implementation of olfactory bulb glomerular-layer computations in a digital neurosynaptic core. Front. Neurosci. 6:83. doi: 10.3389/fnins.2012.00083
Received: 29 February 2012; Accepted: 18 May 2012;
Published online: 06 June 2012.
Edited by:Gabriel A. Silva, University of California San Diego, USA
Reviewed by:Vassiliy Tsytsarev, University of Maryland School of Medicine, USA
Copyright: © 2012 Imam, Cleland, Manohar, Merolla, Arthur, Akopyan and Modha. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
*Correspondence: Nabil Imam, Computer Systems Lab, Department of Electrical and Computer Engineering, Cornell University, 314 Rhodes Hall, Hoy Road, Ithaca, NY 14850, USA. e-mail: firstname.lastname@example.org