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Resolving Precise Temporal Processing Properties of the Auditory System Using Continuous Stimuli

¹Trinity College Institute of Neuroscience, ²School of Engineering, and ³School of Medicine, Trinity College Dublin, Dublin, Ireland; ⁴Program in Cognitive Neuroscience, Departments of Psychology and Biology, City College of the City University of New York, New York; and ⁵The Cognitive Neurophysiology Laboratory, Nathan S. Kline Institute for Psychiatric Research, Program in Cognitive Neuroscience and Schizophrenia, Orangeburg, New York

Submitted 8 August 2008; accepted in final form 5 May 2009

In natural environments complex and continuous auditory stimulation is virtually ubiquitous. The human auditory system has evolved to efficiently process an infinitude of everyday sounds, which range from short, simple bursts of noise to signals with a much higher order of information such as speech. Investigation of temporal processing in this system using the event-related potential (ERP) technique has led to great advances in our knowledge. However, this method is restricted by the need to present simple, discrete, repeated stimuli to obtain a useful response. Alternatively the continuous auditory steady-state response is used, although this method reduces the evoked response to its fundamental frequency component at the expense of useful information on the timing of response transmission through the auditory system. In this report, we describe a method for eliciting a novel ERP, which circumvents these limitations, known as the AESPA (auditory-evoked spread spectrum analysis). This method uses rapid amplitude modulation of audio carrier signals to estimate the impulse response of the auditory system. We show AESPA responses with high signal-to-noise ratios obtained using two types of carrier wave: a 1-kHz tone and broadband noise. To characterize these responses, they are compared with auditory-evoked potentials elicited using standard techniques. A number of similarities and differences between the responses are noted and these are discussed in light of the differing stimulation and analysis methods used. Data are presented that demonstrate the generalizability of the AESPA method and a number of applications are proposed.