Roy D. Patterson

The Processing of Temporal Pitch and Melody Information in Auditory Cortex

An fMRI experiment was performed to identify the main stages of melody processing in the auditory pathway. Spectrally matched sounds that produce no pitch, fixed pitch, or melody were all found to activate Heschls gyrus (HG) and planum temporale (PT). Within this region, sounds with pitch produced more activation than those without pitch only in the lateral half of HG. When the pitch was varied to produce a melody, there was activation in regions beyond HG and PT, specifically in the superior temporal gyrus (STG) and planum polare (PP). The results support the view that there is hierarchy of pitch processing in which the center of activity moves anterolaterally away from primary auditory cortex as the processing of melodic sounds proceeds.

Auditory filter shapes derived with noise stimuli

A wide‐band noise having a deep notch with sharp edges was used to mask a tone. The notch was centered on the tone, and threshold was measured as the width of the notch was increased from 0.0 to 0.8 times the tone frequency (0.5, 1.0, or 2.0 kHz). The spectrum level of the noise was 40 dB SPL. If it is assumed that the auditory filter is reasonably symmetric at these intensities, then the shape of the filter centered on the tone can be estimated from the first derivative of the curve relating tone threshold to the width of the notch in the noise. The 3‐dB bandwidths of the filters obtained were about 0.13 of their center frequency. In the region of the passband, the Gaussian curve provides a good approximation to the shape of the derived filters. The equivalent rectangular bandwidths of the Gaussian approximations are about 0.20 of their center frequency, which is comparable to the critical‐band estimates of R. Zwicker, G. Flottorp, and S. S. Stevens [’’Critical bandwidth in loudness summation,’’ J. Acoust. Soc. Am. 29, 548–557 (1957)]. The Gaussian approximation cannot be used outside the passband, because the tails of the derived filters do not fall as fast as the Gaussian curve. Subject Classification: [43]65.58, [43]65.35; [43]80.50.

Time‐domain modeling of peripheral auditory processing: A modular architecture and a software platform

A software package with a modular architecture has been developed to support perceptual modeling of the fine-grain spectro-temporal information observed in the auditory nerve. The package contains both functional and physiological modules to simulate auditory spectral analysis, neural encoding, and temporal integration, including new forms of periodicity-sensitive temporal integration that generate stabilized auditory images. Combinations of the modules enable the user to approximate a wide variety of existing, time-domain, auditory models. Sequences of auditory images can be replayed to produce cartoons of auditory perceptions that illustrate the dynamic response of the auditory system to everyday sounds.

The deterioration of hearing with age: Frequency selectivity, the critical ratio, the audiogram, and speech threshold

The frequency selectivity of the auditory system was measured by masking a sinusoidal signal (0.5, 2.0, or 4.0 kHz) or a filtered-speech signal with a wideband noise having a notch, or stopband, centered on the signal. As the notch was widened performance improved for both types of signal but the rate of improvement decreased as the age of the 16 listeners increased from 23 to 75 years, indicating a loss in frequency selectivity with age. Auditory filter shapes derived from the tone-in-noise data show (a) that the passband of the filter broadens progressively with age, and (b) that the dynamic range of the filter ages like the audiogram. That is, the range changes little with age before 55, but beyond this point there is an accelerating rate of loss. The speech experiment shows comparable but smaller effects. The filter-width measurements show that the critical ratio is a poor estimator of frequency selectivity because it confounds the tuning of the system with the efficiency of the signal-detection and speech-processing mechanisms that follow the filter. An alternative, one-point measure of frequency selectivity, which is both sensitive and reliable, is developed via the filter-shape model of masking.

Complex Sounds and Auditory Images

In recent years, there has been a growing interest in the perception of complex sounds, and a growing interest in models that attempt to explain our perception of these sounds in terms of peripheral processes involving the interaction of neighbouring frequency bands and/or more central processes involving the combination of information across distant frequency bands. In this paper we review the perception of four types of complex sound, two traditional (pulse trains and vowels), and two novel (Profile Analysis, PA, and Comodulation Masking Release, CMR). The review is conducted with the aid of a general purpose model of peripheral auditory processing that produces ‘auditory images’ of the sounds. The model includes the interactions associated with adaptation and suppression as observed in the auditory nerve, and it includes the phase alignment and temporal integration which take place before the formation of our initial images of the sounds, but it does not include any of the processes that combine information across widely separated frequency bands. The auditory images assist the discussion of complex sounds by indicating which effects might be explained peripherally and which effects definitely require central processing.

Off‐frequency listening and auditory‐filter asymmetry

The phenomenon of off-frequency listening, and the asymmetry of the auditory filter, were investigated by performing a masking experiment in which a 2.0-kHz tonal signal (0.4 sec in duration) was masked by a pair of noise bands, one below and the other above the tone. The noise bands were 0.8-hKz wide. The edges of the bands were very sharp, the spectrum level in the band was 40 dB SPL, and the masker was on continuously throughout the experiment. Tone threshold was measured as a function of the distances from the tone to the nearer edge of each noise band. It was assumed that conditions in which one noise band was near the tone and the other remote from the tone would encourage the observer to listen off frequency, that is, to center his auditory filter, not at the tone frequency, but at the frequency that optimizes the signal-to-noise ratio at the output of the filter. The threshold data were analysed with a power spectrum model of masking in which it was assumed that the general form of the filter shape was a rounded exponential (a pair of back-to-back, negative exponentials with the peak smoothed and the tails raised). The specific filter shape obtained by applying this model to the threshold data has a broad passband (a 200-Hz, 3-dB bandwidth), steep skirts (slopes of 100 dB/octave) and shallower tails (slopes of 30-50 dB/octave) that take over 30-35 dB down from the peak of sensitivity. The filter is asymmetric, with the lower branch slightly broader than the upper. The filter is shifted off frequency by more than half its bandwidth in some cases, and the shift can improve the signal-to-noise ratio by up to 5.0 dB.

A TIME-DOMAIN, LEVEL-DEPENDENT AUDITORY FILTER : THE GAMMACHIRP

A frequency-modulation term has been added to the gammatone auditory filter to produce a filter with an asymmetric amplitude spectrum. When the degree of asymmetry in this “gammachirp” auditory filter is associated with stimulus level, the gammachirp is found to provide an excellent fit to 12 sets of notched-noise masking data from three different studies. The gammachirp has a well-defined impulse response, unlike the conventional roex auditory filter, and so it is an excellent candidate for an asymmetric, level-dependent auditory filterbank in time-domain models of auditory processing.

Encoding of the temporal regularity of sound in the human brainstem

We measured the neural activity associated with the temporal structure of sound in the human auditory pathway from cochlear nucleus to cortex. The temporal structure includes regularities at the millisecond level and pitch sequences at the hundreds-of-milliseconds level. Functional magnetic resonance imaging (fMRI) of the whole brain with cardiac triggering allowed simultaneous observation of activity in the brainstem, thalamus and cerebrum. This work shows that the process of recoding temporal patterns into a more stable form begins as early as the cochlear nucleus and continues up to auditory cortex.

The processing and perception of size information in speech sounds.

There is information in speech sounds about the length of the vocal tract; specifically, as a child grows, the resonators in the vocal tract grow and the formant frequencies of the vowels decrease. It has been hypothesized that the auditory system applies a scale transform to all sounds to segregate size information from resonator shape information, and thereby enhance both size perception and speech recognition [Irino and Patterson, Speech Commun. 36, 181-203 (2002)]. This paper describes size discrimination experiments and vowel recognition experiments designed to provide evidence for an auditory scaling mechanism. Vowels were scaled to represent people with vocal tracts much longer and shorter than normal, and with pitches much higher and lower than normal. The results of the discrimination experiments show that listeners can make fine judgments about the relative size of speakers, and they can do so for vowels scaled well beyond the normal range. Similarly, the recognition experiments show good performance for vowels in the normal range, and for vowels scaled well beyond the normal range of experience. Together, the experiments support the hypothesis that the auditory system automatically normalizes for the size information in communication sounds.

A time domain description for the pitch strength of iterated rippled noise

Two versions of a cascaded add, attenuate, and delay circuit were used to generate iterated rippled noise (IRN) stimuli. IRN stimuli produce a repetition pitch whose strength relative to the noise can be varied by changing the type of circuit, the attenuation, or the number of iterations in the circuit. Listeners were asked to discriminate between various pairs of IRN stimuli which differed in the type of network used to generate the sounds or the number of iterations (n = 1, 2, 3, 4, 7, and 9). Performance was determined for IRN stimuli generated with delays of 2, 4, and 8 ms and for four bandpass filter conditions (0-2000, 250-2000, 500-2000, and 750-2000 Hz). Some IRN stimuli were extremely difficult to discriminate despite relatively large spectral differences, while other IRN stimuli produced readily discriminable changes in perception, despite small spectral differences. these contrasting results are inconsistent with simple spectral explanations for the perception of IRN stimuli. An explanation based on the first peak of the autocorrelation function of IRN stimuli is consistent with the results. Simulations of the processing performed by the peripheral auditory system (i.e., interval histograms and correlograms) produce results which are consistent with the involvement of these temporal processes in the perception of IRN stimuli.