Phase-locked response to low-frequency tones in single auditory nerve fibers of the squirrel monkey.

Rose, Jerzy E.; Brugge, John F.; Anderson, D. J.; Hind, Joseph E.

doi:10.1152/jn.1967.30.4.769

Cited by 826 publications

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“…In those models, period skipping arises already at the deterministic level (i.e., in the absence of sources of heterogeneity and inhomogeneity) [9], while noise is sometimes considered [10] to reproduce the level of irregularity observed in the experiments. Other striking examples of polymodal cycles * jordi.g.ojalvo@upc.edu embedded in an otherwise oscillatory dynamics were reported long ago in sensory neurons [11] and bacterial motility [12].…”

Section: Introductionmentioning

confidence: 90%

Optimizing periodicity and polymodality in noise-induced genetic oscillators

2011

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Many cellular functions are based on the rhythmic organization of biological processes into self-repeating cascades of events. Some of these periodic processes, such as the cell cycles of several species, exhibit conspicuous irregularities in the form of period skippings, which lead to polymodal distributions of cycle lengths. A recently proposed mechanism that accounts for this quantized behavior is the stabilization of a Hopf-unstable state by molecular noise. Here we investigate the effect of varying noise in a model system, namely an excitable activator-repressor genetic circuit, that displays this noise-induced stabilization effect. Our results show that an optimal noise level enhances the regularity (coherence) of the cycles, in a form of coherence resonance. Similar noise levels also optimize the multimodal nature of the cycle lengths. Together, these results illustrate how molecular noise within a minimal gene regulatory motif confers robust generation of polymodal patterns of periodicity.

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Section: Introductionmentioning

confidence: 90%

Optimizing periodicity and polymodality in noise-induced genetic oscillators

2011

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“…Regardless of BF, at effective stimulus frequencies above -2,000 Hz the sensitivity to IPD drops off demonstrably, which is expected if the mechanism that underlies IPD sensitivity at the cortex is limited primarily by the interactions in the lower brain stem of converging phase-locked afferent input from the two ears. Auditory nerve phase locking, which underlies IPD sensitivity, is exhibited at low-frequencies by high-BF fibers (Johnson 1980;Rose et al 1967). In the inferior colliculus, IPD sensitivity is observed at stimulus frequencies as high as 3,100 Hz, but above 2,500 Hz the number of such cells is reported to decrease markedly (Kuwada and Yin 1983).…”

Section: Sensitivity To Ipdmentioning

confidence: 99%

“…These two acoustical cues, among others, are intimately related to the ability of a listener to localize sound sources in space (see e.g., Blauert 1983). For tonal stimuli of low frequency and in the steady state or near steady state, a neuron's ITD sensitivity is generally believed to derive mainly from interactions between time-locked afferent input arising from the two cochleae (Johnson 1980;Rose et al 1967) and converging on neurons in the medial superior olivary nucleus (Goldberg and Brown 1969;Yin and Chan 1990). Once established, ITD sensitivity is then presumably preserved by neuronal circuits at successively higher levels of the lemniscal pathway including the dorsal nucleus of the lateral lemniscus (Brugge et al 1970), central nucleus of the inferior colliculus (Kuwada et al 1979;Rose et al 1966), ventral division of the medial geniculate body (Aitkin and Webster 1972), and as many as three fields of the auditory cortex (Brugge et al 1969;Orman and Phillips 1984).…”

Section: Introductionmentioning

confidence: 99%

Auditory cortical neurons are sensitive to static and continuously changing interaural phase cues

Reale

Brugge

1990

Journal of Neurophysiology

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SUMMARYAND CONCLUSIONS1. The interaural-phase-difference (IPD) sensitivity of single neurons in the primary auditory (AI) cortex of the anesthetized cat was studied at stimulus frequencies ranging from 120 to 2,500 Hz. Best frequencies of the 43 AI cells sensitive to IPD ranged from 190 to 2,400 Hz.2. A static IPD was produced when a pair of low-frequency tone bursts, differing from one another only in starting phase, were presented dichotically. The resulting IPD-sensitivity curves, which plot the number of discharges evoked by the binaural signal as a function of IPD, were deeply modulated circular functions. IPD functions were analyzed for their mean vector length (r> and mean interaural phase (0). Phase sensitivity was relatively independent of best frequency (BF) but highly dependent on stimulus frequency. Regardless of BF or stimulus frequency within the excitatory response area the majority of cells fired maximally when the ipsilateral tone lagged the contralateral signal and fired least when this interaural-phase relationship was reversed.3. Sensitivity to continuously changing IPD was studied by delivering to the two ears 3-s tones that differed slightly in frequency, resulting in a binaural beat. Approximately 26% of the cells that showed a sensitivity to static changes in IPD also showed a sensitivity to dynamically changing IPD created by this binaural tonal combination. The discharges were highly periodic and tightly synchronized to a particular phase of the binaural beat cycle. High synchrony can be attributed to the fact that cortical neurons typically respond to an excitatory stimulus with but a single spike that is often precisely timed to stimulus onset. A period histogram, binned on the binaural beat frequency (fb), produced an equivalent IPD-sensitivity function for dynamically changing interaural phase. For neurons sensitive to both static and continuously changing interaural phase there was good correspondence between their static (0,) and dynamic (0,) mean interaural phases.4. All cells responding to a dynamically changing stimulus exhibited a linear relationship between mean interaural phase and beat frequency. Most cells responded equally well to binaural beats regardless of the initial direction of phase change. For a fixed duration stimulus, and at relatively low fb, the number of spikes evoked increased with increasing fb, reflecting the increasing number of effective stimulus cycles. At higher,& AI neurons were unable to follow the rate at which the most effective phase repeated itself during the 3 s of stimulation.5. Changing stimulus intensity equally at both ears at BF resulted in relatively little systematic change in the interaural-phase sensitivity when data obtained near threshold and at nonmonotonic levels were excluded from the analysis. In a few cells where the effects of intensity change were studied at a number of excitatory frequencies the results were the same.6. The IPD functions were converted to interaural-time-difference (ITD) functions. Approximately 85% of the cur...

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“…Hind et al [16] and Rose et al [37,38] found that, for a large range of stimulus intensities, histograms of the responses of auditory nerve fibers to continuous pure tones have shapes that closely resemble half-wave rectified sine waves and that histograms of the responses to two-tone complexes also have shapes that are similar to the waveforms of a half-wave rectified combination of the same two frequencies.…”

Section: Introductionmentioning

confidence: 99%

Frequency selectivity of phase-locking of complex sounds in the auditory nerve of the rat

Møller

1983

Hearing Research

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Frequency selectivity of single auditory nerve fibers in the auditory nerve of the rat was studied using pseudorandom noise as the stimulus. The noise was lowpass filtered ternary m-sequences. Period histograms of the discharges of single auditory nerve fibers, locked to the periodicity of the noise, were cross-correlated with one period of the noise to obtain estimates of the impulse response. These cross-correlograms were subsequently Fourier transformed to obtain estimates of the frequency transfer functions. Earlier results obtained using noise that was based on binary sequences as the stimulus showed a systematic dependence on stimulus intensity of the bandwidth and center frequency of the computer transfer functions. The results of the present study confirmed this dependence and showed that a linear model based upon first-order cross-correlations fit the histograms of response. It is concluded that phase-locked activity of single auditory nerve fibers accurately reproduces the half-wave rectified motion of the basilar membrane over a large range of sound intensities.

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Phase-locked response to low-frequency tones in single auditory nerve fibers of the squirrel monkey.

Cited by 826 publications

References 0 publications

Optimizing periodicity and polymodality in noise-induced genetic oscillators

Optimizing periodicity and polymodality in noise-induced genetic oscillators

Auditory cortical neurons are sensitive to static and continuously changing interaural phase cues

Frequency selectivity of phase-locking of complex sounds in the auditory nerve of the rat

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