Learning a temporal code

Abstract. The paper proposes a concrete information encoding for networks of spiking neurons. A temporal code is presented in which neurons respond to simultaneous spike releases of a particular group of neurons. The paper puts a spike-based learning rule in the context of that coding and shows how a network adapts to events experienced while observing an environment. Furthermore, correlations between events distant in time can be learnt. To demonstrate this, a net is simulated, the neurons of which become selective to moving bar stimuli after repeated presentations of samples

Learning a temporal code Ph. Ha iger

Abstract. The paper proposes a concrete information encoding for networks of spiking neurons. A temporal code is presented in which neurons respond to simultaneous spike releases of a particular group of neurons. The paper puts a spike-based learning rule in the context of that coding and shows how a network adapts to events experienced while observing an environment. Furthermore, correlations between events distant in time can be learnt. To demonstrate this, a net is simulated, the neurons of which become selective tomoving bar stimuli after repeated presentations of samples. 1

Learning a temporal code Ph. Ha iger

Abstract. The paper proposes a concrete information encoding for networks of spiking neurons. A temporal code is presented in which neurons respond to simultaneous spike releases of a particular group of neurons. The paper puts a spike-based learning rule in the context of that coding and shows how a network adapts to events experienced while observing an environment. Furthermore, correlations between events distant in time can be learnt. To demonstrate this, a net is simulated, the neurons of which become selective tomoving bar stimuli after repeated presentations of samples. 1