000200449 001__ 200449
000200449 005__ 20181203023541.0
000200449 0247_ $$2doi$$a10.1016/j.bica.2013.05.010
000200449 022__ $$a2212-683X
000200449 037__ $$aARTICLE
000200449 245__ $$aSelf-organisation of motion features with a temporal asynchronous dynamic vision sensor
000200449 260__ $$c2013
000200449 269__ $$a2013
000200449 336__ $$aJournal Articles
000200449 520__ $$aNeural circuits closer to the periphery tend to be organised in a topological way, i.e. stimuli which are spatially close tend to be mapped onto neighbouring processing neurons. The goal of this study is to show how motion features (optic-flow), which have an inherent spatio-temporal profile, can be self-organised using correlations of precise spike intervals. The proposed framework is applied to the spiking output of an asynchronous dynamic vision sensor (DVS), which mimics the workings of the mammalian retina. Our results show that our framework is able to form a topologic organisation of optic-flow features similar to that observed in the human middle temporal lobe.
000200449 6531_ $$aSelf-organisation
000200449 6531_ $$aMotion perception
000200449 6531_ $$aDynamic vision sensor
000200449 6531_ $$aKohonen-network
000200449 700__ $$aKoeth, F.
000200449 700__ $$aMarques, H. G.
000200449 700__ $$aDelbruck, T.
000200449 773__ $$j6$$tBiologically Inspired Cognitive Architectures$$q8-11
000200449 909C0 $$0252409$$pNCCR-ROBOTICS$$xU12367
000200449 909CO $$particle$$ooai:infoscience.tind.io:200449
000200449 917Z8 $$x221818
000200449 937__ $$aEPFL-ARTICLE-200449
000200449 973__ $$rREVIEWED$$sPUBLISHED$$aOTHER
000200449 980__ $$aARTICLE