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Open Access Highly Accessed Research article

Non-linear laws of echoic memory and auditory change detection in humans

Koji Inui1*, Tomokazu Urakawa1, Koya Yamashiro1, Naofumi Otsuru1, Makoto Nishihara2, Yasuyuki Takeshima1, Sumru Keceli1 and Ryusuke Kakigi1

Author affiliations

1 Department of Integrative Physiology, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585, Japan

2 Multidisciplinary Pain Center, Aichi Medical University, Aichi 480-1195, Japan

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Citation and License

BMC Neuroscience 2010, 11:80  doi:10.1186/1471-2202-11-80

Published: 3 July 2010

Abstract

Background

The detection of any abrupt change in the environment is important to survival. Since memory of preceding sensory conditions is necessary for detecting changes, such a change-detection system relates closely to the memory system. Here we used an auditory change-related N1 subcomponent (change-N1) of event-related brain potentials to investigate cortical mechanisms underlying change detection and echoic memory.

Results

Change-N1 was elicited by a simple paradigm with two tones, a standard followed by a deviant, while subjects watched a silent movie. The amplitude of change-N1 elicited by a fixed sound pressure deviance (70 dB vs. 75 dB) was negatively correlated with the logarithm of the interval between the standard sound and deviant sound (1, 10, 100, or 1000 ms), while positively correlated with the logarithm of the duration of the standard sound (25, 100, 500, or 1000 ms). The amplitude of change-N1 elicited by a deviance in sound pressure, sound frequency, and sound location was correlated with the logarithm of the magnitude of physical differences between the standard and deviant sounds.

Conclusions

The present findings suggest that temporal representation of echoic memory is non-linear and Weber-Fechner law holds for the automatic cortical response to sound changes within a suprathreshold range. Since the present results show that the behavior of echoic memory can be understood through change-N1, change-N1 would be a useful tool to investigate memory systems.