title: Robust feedforward processing in synfire chains.
abstract: The rapidity of time-constrained visual identification suggests a feedforward process in which neural activity is propagated through a number of cortical stages. The process is modeled by using a synfire chain, leading to a neural-network model which involves propagating activation waves through a sequence of layers. Theory and analysis of the model's behavior, especially in the presence of noise, predict enhancement of wave propagation for a range of noise intensities. Simulation studies confirm this prediction. The results are discussed in terms of (spatio-temporal) stochastic resonance. It is concluded that feedforward processes such as time-constrained visual identification may benefit from moderate levels of noise.
authors.affiliation: Department of Computer Science, University Maastricht, The Netherlands.
authors.forename: E O
authors.initials: EO
authors.lastname: Postma
authors.forename: H J
authors.initials: HJ
authors.lastname: van den Herik
authors.forename: P T
authors.initials: PT
authors.lastname: Hudson
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D003491:Cybernetics; D016571:Neural Networks, Computer; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*