|
|
|
Data
|
Online learning model of olfactory bulb external plexiform layer network (Imam & Cleland 2020)
|
Thomas Cleland
|
|
|
|
|
This model illustrates the rapid online learning of odor representations, and their recognition despite high levels of interference (other competing odorants), in a model of the olfactory bulb external plexiform layer (EPL) network. The computational principles embedded in this model are based on the those developed in the biophysical models of Li and Cleland (2013, 2017).
This is a standard Python version of a model written for Intel's Loihi neuromorphic hardware platform (The Loihi code is available at https://github.com/intel-nrc-ecosystem/models/tree/master/official/epl).
|
-
Olfactory bulb main mitral GLU cell Show
Other
-
Olfactory bulb main interneuron granule MC GABA cell Show
Other
|
|
|
|
|
|
|
-
Neuron or other electrically excitable cell Show
Other
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
tac29@cornell.edu
|
|
|
|
|
|
|
|
|
|
|
Neuromorphic network
|
Online learning
|
|
|
Imam, Nabil
Clelalnd, Thomas
|
|
|
Imam N, Cleland TA (2020) Rapid learning and robust recall in a neuromorphic olfactory circuit. Nature Machine Intelligence (in press).
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
