2016
DOI: 10.3389/fnins.2016.00183
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Representation of Instantaneous and Short-Term Loudness in the Human Cortex

Abstract: Acoustic signals pass through numerous transforms in the auditory system before perceptual attributes such as loudness and pitch are derived. However, relatively little is known as to exactly when these transformations happen, and where, cortically or sub-cortically, they occur. In an effort to examine this, we investigated the latencies and locations of cortical entrainment to two transforms predicted by a model of loudness perception for time-varying sounds: the transforms were instantaneous loudness and sho… Show more

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Cited by 20 publications
(25 citation statements)
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“…In a previous study (Thwaites et al., 2016), we investigated whether the time-varying instantaneous loudness or short-term loudness predicted by the loudness model of Glasberg and Moore (2002) is ‘tracked’ by cortical current, a phenomenon known as cortical entrainment. The extent of cortical entrainment was estimated from electro- and magneto-encephalographic (EMEG) measures of cortical current, recorded while normal-hearing participants listened to continuous speech.…”
Section: Introductionmentioning
confidence: 85%
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“…In a previous study (Thwaites et al., 2016), we investigated whether the time-varying instantaneous loudness or short-term loudness predicted by the loudness model of Glasberg and Moore (2002) is ‘tracked’ by cortical current, a phenomenon known as cortical entrainment. The extent of cortical entrainment was estimated from electro- and magneto-encephalographic (EMEG) measures of cortical current, recorded while normal-hearing participants listened to continuous speech.…”
Section: Introductionmentioning
confidence: 85%
“…It is the loudness derived from auditory filters with CFs spanning a 1-Cam range. To obtain the overall instantaneous loudness, the specific instantaneous loudness is summed for filters with CFs between 1.75 and 39.0 Cams (corresponding to 47.5 Hz and 15,108 Hz, respectively), as described by Glasberg and Moore (2002) and Thwaites et al. (2016).…”
Section: Defining Candidate Modelsmentioning
confidence: 99%
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“…Several approaches to extraction of the broad-band temporal envelope from a speech signal have been proposed (Biesmans et al 2016, Thwaites et al 2016. In case of the oddball task, the envelope was extracted by a direct calculation of the absolute values of the Hilbert-transform.…”
Section: Extraction Of Onset Envelopesmentioning
confidence: 99%