Timescale-Invariant Pattern Recognition by Feedforward Inhibition and Parallel Signal Processing

Creutzig, Felix; Benda, Jan; Wohlgemuth, Sandra; Stumpner, Andreas; Ronacher, Bernhard and Herz, Andreas V. M. (2010): Timescale-Invariant Pattern Recognition by Feedforward Inhibition and Parallel Signal Processing. In: Neural Computation, Vol. 22, No. 6: pp. 1493-1510

Abstract

The timescale-invariant recognition of temporal stimulus sequences is vital for many species and poses a challenge for their sensory systems. Here we present a simple mechanistic model to address this computational task, based on recent observations in insects that use rhythmic acoustic communication signals for mate finding. In the model framework, feed-forward inhibition leads to burst-like response patterns in one neuron of the circuit. Integrating these responses over a fixed time window by a readout neuron creates a timescale-invariant stimulus representation. Only two additional processing channels, each with a feature detector and a readout neuron, plus one final coincidence detector for all three parallel signal streams, are needed to account for the behavioral data. In contrast to previous solutions to the general time-warp problem, no time delay lines or sophisticated neural architectures are required. Our results suggest a new computational role for feedforward inhibition and underscore the power of parallel signal processing.

• Item Type: Journal article
• Faculties: Biology > Department Biology II > Neurobiology
• Subjects: 500 Science > 570 Life sciences; biology
• ISSN: 0899-7667
• Language: English