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Music and natural image processing share a common feature-integration rule

Research output: Contribution in Book/Report/ProceedingsPaper

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Publication date07/2009
Host publicationCogSci 2009
PublisherCognitive Science Society
Pages2481-2486
Number of pages6
<mark>Original language</mark>English
EventProceedings of the 31st Annual Conference of the Cognitive Science Society - , United Kingdom

Conference

ConferenceProceedings of the 31st Annual Conference of the Cognitive Science Society
CountryUnited Kingdom
Period20/09/13 → …

Conference

ConferenceProceedings of the 31st Annual Conference of the Cognitive Science Society
CountryUnited Kingdom
Period20/09/13 → …

Abstract

The world is rich in sensory information, and the challenge for any neural sensory system is to piece together the diverse messages from large arrays of feature detectors. In vision and auditory research, there has been speculation about the rules governing combination of signals from different neural channels: e.g. linear (city-block) addition, Euclidian (energy) summation, or a maximum rule. These are all special cases of a more general Minkowski summation rule (Cue1^m+Cue2^m)^(1/m), where m=1, 2 and infinity respectively. Recently, we reported that Minkowski summation with exponent m=2.84 accurately models combination of visual cues in photographs [To et al. (2008). Proc Roy Soc B, 275, 2299]. Here, we ask whether this rule is equally applicable to cue combinations across different auditory dimensions: such as intensity, pitch, timbre and content. We found that in suprathreshold discrimination tasks using musical sequences, a Minkowski summation with exponent close to 3 (m=2.95) outperformed city-block, Euclidian or maximum combination rules in describing cue integration across feature dimensions. That the same exponent is found in this music experiment and our previous vision experiments, suggests the possibility of a universal “Minkowski summation Law” in sensory feature integration. We postulate that this particular Minkowski exponent relates to the degree of correlation in activity between different sensory neurons when stimulated by natural stimuli, and could reflect an overall economical and efficient encoding mechanism underlying perceptual integration of features in the natural world.