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Across-channel timing differences as a potential code for the frequency of pure tones.

Carlyon RP, Long CJ, Micheyl C - J. Assoc. Res. Otolaryngol. (2011)

Bottom Line: When a pure tone or low-numbered harmonic is presented to a listener, the resulting travelling wave in the cochlea slows down at the portion of the basilar membrane (BM) tuned to the input frequency due to the filtering properties of the BM.It has been suggested that the auditory system exploits these across-channel timing differences to encode the pitch of both pure tones and resolved harmonics in complex tones.We conclude that although the use of across-channel timing cues provides an a priori attractive and plausible means of encoding pitch, many of the most obvious metrics for using that cue produce pitch estimates that are strongly influenced by the overall level and therefore are unlikely to provide a straightforward means for encoding the pitch of pure tones.

View Article: PubMed Central - PubMed

Affiliation: MRC Cognition & Brain Sciences Unit, 15 Chaucer Rd., Cambridge, CB2 7EF, UK. bob.carlyon@mrc-cbu.cam.ac.uk

ABSTRACT
When a pure tone or low-numbered harmonic is presented to a listener, the resulting travelling wave in the cochlea slows down at the portion of the basilar membrane (BM) tuned to the input frequency due to the filtering properties of the BM. This slowing is reflected in the phase of the response of neurons across the auditory nerve (AN) array. It has been suggested that the auditory system exploits these across-channel timing differences to encode the pitch of both pure tones and resolved harmonics in complex tones. Here, we report a quantitative analysis of previously published data on the response of guinea pig AN fibres, of a range of characteristic frequencies, to pure tones of different frequencies and levels. We conclude that although the use of across-channel timing cues provides an a priori attractive and plausible means of encoding pitch, many of the most obvious metrics for using that cue produce pitch estimates that are strongly influenced by the overall level and therefore are unlikely to provide a straightforward means for encoding the pitch of pure tones.

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The “knee point” as a function of level and input frequency. The curves shown are derived from the best-fitting model described in the text for input frequencies spaced 3 semitones apart, starting at 250 Hz, and with levels of 50, 70 and 90 dB SPL.
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Fig7: The “knee point” as a function of level and input frequency. The curves shown are derived from the best-fitting model described in the text for input frequencies spaced 3 semitones apart, starting at 250 Hz, and with levels of 50, 70 and 90 dB SPL.

Mentions: A second possible code for frequency that makes use of the PT involves estimating fs from the location of the transition between the steep and shallow portions of the functions shown in Figure 1 and in the top panels of Figure 4. This could be implemented by an array of “third-order” neurons that subtract the outputs of adjacent “second-order” neurons (Figure 3C–E). This “third-order” array would show a maximum when the second derivative of the phase-vs.-CF function is maximal. To estimate this “knee point”, we refitted the data shown in Figure 4 with “broken-stick” functions consisting of two straight lines, one of which was constrained to have a zero slope. Examples of this fit for two frequencies and levels are shown in Figure 6. When applied to the same range of fs as shown in Figure 4, this “broken-stick” model yields almost exactly the same RMS error of fit (all frequency and level conditions combined) as the “arc-tangent” model described above: 0.2791 cycles for the broken-stick fit model vs. 0.2796 for the arc-tangent fit. The knee point varies monotonically with fs, but, as Figure 7 shows, is not independent of level. For example, the knee point for a 250-Hz, 90-dB tone occurs at a place in the AN array having a higher CF than that for a 500-Hz, 50-dB tone. The effect of level, averaged across fs, was 0.8 octaves, more than half the 1.33-octave effect of fs.FIG. 6


Across-channel timing differences as a potential code for the frequency of pure tones.

Carlyon RP, Long CJ, Micheyl C - J. Assoc. Res. Otolaryngol. (2011)

The “knee point” as a function of level and input frequency. The curves shown are derived from the best-fitting model described in the text for input frequencies spaced 3 semitones apart, starting at 250 Hz, and with levels of 50, 70 and 90 dB SPL.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3298616&req=5

Fig7: The “knee point” as a function of level and input frequency. The curves shown are derived from the best-fitting model described in the text for input frequencies spaced 3 semitones apart, starting at 250 Hz, and with levels of 50, 70 and 90 dB SPL.
Mentions: A second possible code for frequency that makes use of the PT involves estimating fs from the location of the transition between the steep and shallow portions of the functions shown in Figure 1 and in the top panels of Figure 4. This could be implemented by an array of “third-order” neurons that subtract the outputs of adjacent “second-order” neurons (Figure 3C–E). This “third-order” array would show a maximum when the second derivative of the phase-vs.-CF function is maximal. To estimate this “knee point”, we refitted the data shown in Figure 4 with “broken-stick” functions consisting of two straight lines, one of which was constrained to have a zero slope. Examples of this fit for two frequencies and levels are shown in Figure 6. When applied to the same range of fs as shown in Figure 4, this “broken-stick” model yields almost exactly the same RMS error of fit (all frequency and level conditions combined) as the “arc-tangent” model described above: 0.2791 cycles for the broken-stick fit model vs. 0.2796 for the arc-tangent fit. The knee point varies monotonically with fs, but, as Figure 7 shows, is not independent of level. For example, the knee point for a 250-Hz, 90-dB tone occurs at a place in the AN array having a higher CF than that for a 500-Hz, 50-dB tone. The effect of level, averaged across fs, was 0.8 octaves, more than half the 1.33-octave effect of fs.FIG. 6

Bottom Line: When a pure tone or low-numbered harmonic is presented to a listener, the resulting travelling wave in the cochlea slows down at the portion of the basilar membrane (BM) tuned to the input frequency due to the filtering properties of the BM.It has been suggested that the auditory system exploits these across-channel timing differences to encode the pitch of both pure tones and resolved harmonics in complex tones.We conclude that although the use of across-channel timing cues provides an a priori attractive and plausible means of encoding pitch, many of the most obvious metrics for using that cue produce pitch estimates that are strongly influenced by the overall level and therefore are unlikely to provide a straightforward means for encoding the pitch of pure tones.

View Article: PubMed Central - PubMed

Affiliation: MRC Cognition & Brain Sciences Unit, 15 Chaucer Rd., Cambridge, CB2 7EF, UK. bob.carlyon@mrc-cbu.cam.ac.uk

ABSTRACT
When a pure tone or low-numbered harmonic is presented to a listener, the resulting travelling wave in the cochlea slows down at the portion of the basilar membrane (BM) tuned to the input frequency due to the filtering properties of the BM. This slowing is reflected in the phase of the response of neurons across the auditory nerve (AN) array. It has been suggested that the auditory system exploits these across-channel timing differences to encode the pitch of both pure tones and resolved harmonics in complex tones. Here, we report a quantitative analysis of previously published data on the response of guinea pig AN fibres, of a range of characteristic frequencies, to pure tones of different frequencies and levels. We conclude that although the use of across-channel timing cues provides an a priori attractive and plausible means of encoding pitch, many of the most obvious metrics for using that cue produce pitch estimates that are strongly influenced by the overall level and therefore are unlikely to provide a straightforward means for encoding the pitch of pure tones.

Show MeSH