Duifhuis pitch: neuromagnetic representation and auditory modeling

2014 ◽  
Vol 112 (10) ◽  
pp. 2616-2627 ◽  
Author(s):  
Martin Andermann ◽  
Roy D. Patterson ◽  
Michael Geldhauser ◽  
Norman Sieroka ◽  
André Rupp
Keyword(s):  
Auditory Cortex ◽  
High Harmonic ◽  
Auditory Periphery ◽  
Harmonic Complex ◽  
Auditory Modeling ◽  
Sine Tone ◽  
Large Peak ◽  
Onset Response ◽  
First Time ◽  
Sustained Field

When a high harmonic is removed from a cosine-phase harmonic complex, we hear a sine tone pop out of the perception; the sine tone has the pitch of the high harmonic, while the tone complex has the pitch of its fundamental frequency, f0. This phenomenon is commonly referred to as Duifhuis Pitch (DP). This paper describes, for the first time, the cortical representation of DP observed with magnetoencephalography. In experiment 1, conditions that produce the perception of a DP were observed to elicit a classic onset response in auditory cortex (P1m, N1m, P2m), and an increment in the sustained field (SF) established in response to the tone complex. Experiment 2 examined the effect of the phase spectrum of the complex tone on the DP activity: Schroeder-phase negative waves elicited a transient DP complex with a similar shape to that observed with cosine-phase waves but with much longer latencies. Following the transient DP activity, the responses of the negative and positive Schroeder-phase waves converged, and the increment in the SF slowly died away. In the absence of DP, the two Schroeder-phase conditions with low peak factors both produced larger SFs than cosine-phase waves with large peak factors. A model of the auditory periphery that includes coupling between adjacent frequency channels is used to explain the early neuromagnetic activity observed in auditory cortex.

Neural Responses in Primary Auditory Cortex Mimic Psychophysical, Across-Frequency-Channel, Gap-Detection Thresholds

2000 ◽  
Vol 84 (3) ◽  
pp. 1453-1463 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Gap Detection ◽  
Frequency Content ◽  
Neural Responses ◽  
Frequency Channel ◽  
Interval Representations ◽  
Onset Response

Responses of single- and multi-units in primary auditory cortex were recorded for gap-in-noise stimuli for different durations of the leading noise burst. Both firing rate and inter-spike interval representations were evaluated. The minimum detectable gap decreased in exponential fashion with the duration of the leading burst to reach an asymptote for durations of 100 ms. Despite the fact that leading and trailing noise bursts had the same frequency content, the dependence on leading burst duration was correlated with psychophysical estimates of across frequency channel (different frequency content of leading and trailing burst) gap thresholds in humans. The duration of the leading burst plus that of the gap was represented in the all-order inter-spike interval histograms for cortical neurons. The recovery functions for cortical neurons could be modeled on basis of fast synaptic depression and after-hyperpolarization produced by the onset response to the leading noise burst. This suggests that the minimum gap representation in the firing pattern of neurons in primary auditory cortex, and minimum gap detection in behavioral tasks is largely determined by properties intrinsic to those, or potentially subcortical, cells.

Consonance and Dissonance of Musical Chords: Neural Correlates in Auditory Cortex of Monkeys and Humans

2001 ◽  
Vol 86 (6) ◽  
pp. 2761-2788 ◽  
Author(s):  
Yonatan I. Fishman ◽  
Igor O. Volkov ◽  
M. Daniel Noh ◽  
P. Charles Garell ◽  
Hans Bakken ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Current Source ◽  
Intractable Epilepsy ◽  
Auditory Evoked Potential ◽  
Harmonic Complex ◽  
Heschl’S Gyrus ◽  
Complex Tones ◽  
Heschl's Gyrus ◽  
Musical Chords ◽  
Consonance And Dissonance

Some musical chords sound pleasant, or consonant, while others sound unpleasant, or dissonant. Helmholtz's psychoacoustic theory of consonance and dissonance attributes the perception of dissonance to the sensation of “beats” and “roughness” caused by interactions in the auditory periphery between adjacent partials of complex tones comprising a musical chord. Conversely, consonance is characterized by the relative absence of beats and roughness. Physiological studies in monkeys suggest that roughness may be represented in primary auditory cortex (A1) by oscillatory neuronal ensemble responses phase-locked to the amplitude-modulated temporal envelope of complex sounds. However, it remains unknown whether phase-locked responses also underlie the representation of dissonance in auditory cortex. In the present study, responses evoked by musical chords with varying degrees of consonance and dissonance were recorded in A1 of awake macaques and evaluated using auditory-evoked potential (AEP), multiunit activity (MUA), and current-source density (CSD) techniques. In parallel studies, intracranial AEPs evoked by the same musical chords were recorded directly from the auditory cortex of two human subjects undergoing surgical evaluation for medically intractable epilepsy. Chords were composed of two simultaneous harmonic complex tones. The magnitude of oscillatory phase-locked activity in A1 of the monkey correlates with the perceived dissonance of the musical chords. Responses evoked by dissonant chords, such as minor and major seconds, display oscillations phase-locked to the predicted difference frequencies, whereas responses evoked by consonant chords, such as octaves and perfect fifths, display little or no phase-locked activity. AEPs recorded in Heschl's gyrus display strikingly similar oscillatory patterns to those observed in monkey A1, with dissonant chords eliciting greater phase-locked activity than consonant chords. In contrast to recordings in Heschl's gyrus, AEPs recorded in the planum temporale do not display significant phase-locked activity, suggesting functional differentiation of auditory cortical regions in humans. These findings support the relevance of synchronous phase-locked neural ensemble activity in A1 for the physiological representation of sensory dissonance in humans and highlight the merits of complementary monkey/human studies in the investigation of neural substrates underlying auditory perception.

scholarly journals Synaptic Recruitment Enhances Gap Termination Responses in Auditory Cortex

2020 ◽  
Vol 30 (8) ◽  
pp. 4465-4480 ◽  
Author(s):  
Bshara Awwad ◽  
Maciej M Jankowski ◽  
Israel Nelken
Keyword(s):  
Auditory Cortex ◽  
Temporal Resolution ◽  
Perceptual Task ◽  
Gap Detection ◽  
Intracellular Recordings ◽  
Short Term ◽  
Mere Existence ◽  
Onset Response ◽  
Synaptic Mechanisms

Abstract The ability to detect short gaps in noise is an important tool for assessing the temporal resolution in the auditory cortex. However, the mere existence of responses to temporal gaps bounded by two short broadband markers is surprising, because of the expected short-term suppression that is prevalent in auditory cortex. Here, we used in-vivo intracellular recordings in anesthetized rats to dissect the synaptic mechanisms that underlie gap-related responses. When a gap is bounded by two short markers, a gap termination response was evoked by the onset of the second marker with minimal contribution from the offset of the first marker. Importantly, we show that the gap termination response was driven by a different (potentially partially overlapping) synaptic population than that underlying the onset response to the first marker. This recruitment of additional synaptic resources is a novel mechanism contributing to the important perceptual task of gap detection.

scholarly journals Spectral response patterns of auditory cortex neurons to harmonic complex tones in alert monkey (Macaca mulatta)

1990 ◽  
Vol 64 (1) ◽  
pp. 282-298 ◽  
Author(s):  
D. W. Schwarz ◽  
R. W. Tomlinson
Keyword(s):  
Receptive Field ◽  
Auditory Cortex ◽  
Pure Tone ◽  
Response Pattern ◽  
Response Patterns ◽  
Neuronal Responses ◽  
Harmonic Complex ◽  
Tuning Curves ◽  
Complex Tones ◽  
Pure Tones

1. The auditory cortex in the superior temporal region of the alert rhesus monkey was explored for neuronal responses to pure and harmonic complex tones and noise. The monkeys had been previously trained to recognize the similarity between harmonic complex tones with and without fundamentals. Because this suggested that they could preceive the pitch of the lacking fundamental similarly to humans, we searched for neuronal responses relevant to this perception. 2. Combination-sensitive neurons that might explain pitch perception were not found in the surveyed cortical regions. Such neurons would exhibit similar responses to stimuli with similar periodicities but differing spectral compositions. The fact that no neuron with responses to a fundamental frequency responded also to a corresponding harmonic complex missing the fundamental indicates that cochlear distortion products at the fundamental may not have been responsible for missing fundamental-pitch perception in these monkeys. 3. Neuronal responses can be expressed as relatively simple filter functions. Neurons with excitatory response areas (tuning curves) displayed various inhibitory sidebands at lower and/or higher frequencies. Thus responses varied along a continuum of combined excitatory and inhibitory filter functions. 4. Five elementary response classes along this continuum are presented to illustrate the range of response patterns. 5. “Filter (F) neurons” had little or no inhibitory sidebands and responded well when any component of a complex tone entered its pure-tone receptive field. Bandwidths increased with intensity. Filter functions of these neurons were thus similar to cochlear nerve-fiber tuning curves. 6. ”High-resolution filter (HRF) neurons” displayed narrow tuning curves with narrowband widths that displayed little growth with intensity. Such cells were able to resolve up to the lowest seven components of harmonic complex tones as distinct responses. They also responded well to wideband stimuli. 7. “Fundamental (F0) neurons” displayed similar tuning bandwidths for pure tones and corresponding fundamentals of harmonic complexes. This response pattern was due to lower harmonic complexes. This response pattern was due to lower inhibitory sidebands. Thus these cells cannot respond to missing fundamentals of harmonic complexes. Only physically present components in the pure-tone receptive field would excite such neurons. 8. Cells with no or very weak responses to pure tones or other narrowband stimuli responded well to harmonic complexes or wideband noise.(ABSTRACT TRUNCATED AT 400 WORDS)

Neural Correlates of Gap Detection in Three Auditory Cortical Fields in the Cat

1999 ◽  
Vol 81 (5) ◽  
pp. 2570-2581 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Lower Boundary ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Neural Correlates ◽  
Lower Envelope ◽  
Gap Detection ◽  
Modal Values ◽  
Onset Response ◽  
Gap Values

Neural correlates of gap detection in three auditory cortical fields in the cat. Mimimum detectable gaps in noise in humans are independent of the position of the gap, whereas in cat primary auditory cortex (AI) they are position dependent. The position dependence in other cortical areas is not known and may resolve this contrast. This study presents minimum detectable gap-in-noise values for which single-unit (SU), multiunit (MU) recordings and local field potentials (LFPs) show an onset response to the noise after the gap. The gap, which varied in duration between 5 and 70 ms, was preceded by a noise burst of either 5 ms (early gap) or 500 ms (late gap) duration. In 10 cats, simultaneous recordings were made with one electrode each in AI, anterior auditory field (AAF), and secondary auditory cortex (AII). In nine additional cats, two electrodes were inserted in AI and one in AAF. Minimum detectable gaps based on SU, MU, or LFP data in each cortical area were the same. In addition, very similar minimum early-gap values were found in all three areas (means, 36.1–41.7 ms). The minimum late-gap values were also similar in AI and AII (means, 11.1 and 11.7 ms), whereas AAF showed significantly larger minimum late-gap durations (mean 21.5 ms). For intensities >35 dB SPL, distributions of minimum early-gap durations in AAF and AII had modal values at ∼45 ms. In AI, the distribution was more uniform. Distributions for minimum late-gap duration were skewed toward low values (mode at 5 ms), but high values (≤60 ms) were found infrequently as well. A small fraction of units showed a response after the gap only for early-gap durations <20 ms. In AI and AII, the mean minimum early- and late-gap durations decreased significantly with increase in the neuron’s characteristic frequency (CF), whereas the lower boundary for the minimum early gap was CF independent. The findings suggest that human within-perceptual-channel gap detection, showing no dependence of the minimum detectable gap on the duration of the leading noise burst, likely is based on the lower envelope of the distribution of neural minimum gap values of units in AI and AAF. In contrast, across-perceptual-channel gap detection, which shows a decreasing minimum detectable gap with increasing duration of the leading noise burst, likely is based on the comparison ofon responses from populations of neurons that converge on units in AII.

Perception of Iterated Rippled Noise Periodicity in Cochlear Implant Users

2017 ◽  
Vol 22 (2) ◽  
pp. 104-115 ◽  
Author(s):  
Luise Wagner ◽  
Stefan K. Plontke ◽  
Torsten Rahne
Keyword(s):  
Objective Measure ◽  
Difference Limen ◽  
Normal Hearing ◽  
Pitch Perception ◽  
Harmonic Complex ◽  
Pitch Matching ◽  
Complex Tones ◽  
The Difference ◽  
Single Sided Deafness ◽  
Onset Response

Pitch perception is more challenging for individuals with cochlear implants (CIs) than normal-hearing subjects because the signal processing by CIs is restricted. Processing and perceiving the periodicity of signals may contribute to pitch perception. Whether individuals with CIs can discern pitch within an iterated rippled noise (IRN) signal is still unclear. In a prospective controlled psychoacoustic study with 34 CI users and 15 normal-hearing control subjects, the difference limen between IRN signals with different numbers of iterations was measured. In 7 CI users and 15 normal-hearing control listeners with single-sided deafness, pitch matching between IRN and harmonic complex tones was measured. The pitch onset response (POR) following signal changes from white noise to IRN was measured electrophysiologically. The CI users could discriminate different numbers of iteration in IRN signals, but worse than normal-hearing listeners. A POR was measured for both normal-hearing subjects and CI users increasing with the pitch salience of the IRN. This indicates that the POR could serve as an objective measure to monitor progress during audioverbal therapy after CI surgery.

Roughness of Two Simultaneous Harmonic Complex Tones On Just-Tempered and Equal-Tempered Scales

2017 ◽  
Vol 35 (2) ◽  
pp. 127-143
Author(s):  
Václav Vencovský ◽  
František Rund
Keyword(s):  
Fundamental Frequency ◽  
Basilar Membrane ◽  
Auditory Periphery ◽  
Harmonic Complex ◽  
Phase Fluctuations ◽  
Fundamental Frequencies ◽  
Spectral Components ◽  
Complex Tones ◽  
Si Model ◽  
Possible Cause

This study is focused on the perceived roughness of two simultaneous harmonic complex tones with ratios between their fundamental frequencies set to create intervals on just-tempered (JT) and equal-tempered (ET) scales. According to roughness theories, ET intervals should produce more roughness. However, previous studies have shown the opposite for intervals in which the lower fundamental frequency of the complex was equal to 261.6 Hz. The aim of this study is to verify and explain these results by using intervals composed of complexes whose spectral components were generated with either a sine starting phase or with a random starting phase. Results of the current study showed the same phenomenon as previous studies. To examine whether the explanation of the phenomenon lies in the function of the peripheral ear, three roughness models based upon this function were used: the Daniel and Weber (1997) model, the synchronization index (SI) model, and the model based on a hydrodynamic cochlear model. For most of the corresponding JT and ET intervals, only the Daniel and Weber (1997) model predicted less roughness in the ET intervals. In addition to this, the intervals were analyzed by a model simulating the auditory periphery. The results showed that a possible cause for the roughness differences may be in the frequencies of fluctuations of the signal in the peripheral ear. For JT intervals the fluctuations in the adjacent places on the simulated basilar membrane had either the same frequency or integer multiples of that frequency and were synchronized. Since a previous study showed that synchronized fluctuations in adjacent auditory filters lead to higher roughness than out of phase fluctuations (Terhardt, 1974), this may cause more roughness across JT and ET intervals.

Neural Changes in Cat Auditory Cortex After a Transient Pure-Tone Trauma

2003 ◽  
Vol 90 (4) ◽  
pp. 2387-2401 ◽  
Author(s):  
Arnaud. J. Noreña ◽  
Masahiko Tomita ◽  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Pure Tone ◽  
Tuning Curve ◽  
Primary Auditory Cortex ◽  
Auditory Brain Stem Response ◽  
Auditory Brain Stem ◽  
Before And After ◽  
Central Inhibition ◽  
Onset Response ◽  
Brain Stem Response

Here we present the changes in cortical activity occurring within a few hours after a 1-h exposure to a 120-dB SPL pure tone (5 or 6 kHz). The changes in primary auditory cortex of 16 ketamine-anesthetized cats were assessed by recording, with two 8-microelectrode arrays, from the same multiunit clusters before and after the trauma. The exposure resulted in a peripheral threshold increase that stabilized after a few hours to on average 40 dB in the frequency range of 6–32 kHz, as measured by the auditory brain stem response. The trauma induced a shift in characteristic frequency toward lower frequencies, an emergence of new responses, a broadening of the tuning curve, and an increase in the maximum of driven discharges. In addition, the onset response after the trauma was of shorter duration than before the trauma. The results suggest the involvement of both a decrease and an increase in inhibition. They are discussed in terms of changes in central inhibition and its implications for tonotopic map plasticity.

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