Implementation of olfactory bulb glomerular-layer computations in a digital neurosynaptic core.
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.
Computer Systems Lab, Department of Electrical and Computer Engineering, Cornell University Ithaca, NY, USA.
Nabil
N
Imam
Thomas A
TA
Cleland
Rajit
R
Manohar
Paul A
PA
Merolla
John V
JV
Arthur
Filipp
F
Akopyan
Dharmendra S
DS
Modha