Philip X. Joris

Coincidence Detection in the Auditory System: 50 Years after Jeffress

The result of Jeffress’ model is a representation of ITD as a spatial activity profile in an array of tuned cells. Unfortunately, this part of the model has been the most elusive to document. Best ITDs in the MSO are strongly biased toward the contralateral hemifield and fall mostly within the range of ITDs naturally encountered by a cat (0–400 μs) (Yin and Chan 1990xYin, T.C.T. and Chan, J.C.K. J. Neurophysiol. 1990; 64: 465–488PubMedSee all ReferencesYin and Chan 1990). Moreover, there is a significant correlation between the best ITDs and the rostrocaudal location of recording sites pooled from different experiments. The most rostrally located cells prefer small ITDs, while cells located caudally prefer large positive ITDs as generated by sounds in the contralateral hemifield (Figure 1CFigure 1C). However, the relationship is quite scattered and needs to be reexamined by methods that do not necessitate pooling across animals. Importantly, it is in agreement with the anatomical findings on contralateral delay lines extending rostral to caudal, which predict best ITDs to be small rostrally and large caudally. This observation departs from the original scheme of Jeffress, in which ITDs corresponding to both ipsi- and contralaterally located sources are encoded on both sides of the brain, but it is consonant with the contralateralization generally found in other sensory and motor systems.In conclusion, the current view on binaural time processing contains the essential features proposed by Jeffress. Just as Hubel and Wiesel’s model of orientation selectivity has provided a bull’s eye for vision research, the simple model introduced by Jeffress has served as a focal point in audition and has sparked many computational and experimental studies, illustrating the heuristic value of such qualitative models in neuroscience. To end, we mention one particularly interesting study that bridges the gap between human psychophysics and experimental studies in animals. Multiple sclerosis patients with focal lesions in the pons showed abnormal discrimination of ITDs, as well as abnormalities in their brainstem evoked responses, but could still discriminate interaural intensity differences (Levine et al. 1993xLevine, R.A., Gardner, J.C., Stufflebeam, S.M., Fullerton, B.C., Carlisle, E.W., Furst, M., Rosen, B.R., and Kiang, N.Y.S. Hear. Res. 1993; 68: 59–72Crossref | PubMed | Scopus (28)See all ReferencesLevine et al. 1993). These findings were interpretable in the framework of Jeffress’ model by assuming that demyelination caused a desynchronization or decorrelation of the spike patterns fed to the binaural processor. Such decorrelation impairs discrimination of ITDs but not of intensity differences, which are usually thought to require a comparison of average spike counts and to be unaffected by disruption of fine time structure. While this study does not bear directly on the details of the Jeffress model, it provides a compelling argument for the importance of spike timing in human auditory functioning.§To whom correspondence should be addressed (e-mail: yin@physiology.wisc.edu).

A matter of time: internal delays in binaural processing.

As an animal navigates its surroundings, the sounds reaching its two ears change in waveform similarity (interaural correlation) and in time of arrival (interaural time difference, ITD). Humans are exquisitely sensitive to these binaural cues, and it is generally agreed that this sensitivity involves coincidence detectors and internal delays that compensate for external acoustic delays (ITDs). Recent data show an unexpected relationship between the tuning of a neuron to frequency and to ITD, leading to several proposals for sources of internal delay and the neural coding of interaural temporal cues. We review the alternatives, and argue that an understanding of binaural mechanisms requires consideration of sensitivity not only to ITDs, but also to interaural correlation.

Binaural and cochlear disparities

Binaural auditory neurons exhibit “best delays” (BDs): They are maximally activated at certain acoustic delays between sounds at the two ears and thereby signal spatial sound location. BDs arise from delays internal to the auditory system, but their source is controversial. According to the classic Jeffress model, they reflect pure time delays generated by differences in axonal length between the inputs from the two ears to binaural neurons. However, a relationship has been reported between BDs and the frequency to which binaural neurons are most sensitive (the characteristic frequency), and this relationship is not predicted by the Jeffress model. An alternative hypothesis proposes that binaural neurons derive their input from slightly different places along the two cochleas, which induces BDs by virtue of the slowness of the cochlear traveling wave. To test this hypothesis, we performed a coincidence analysis on spiketrains of pairs of auditory nerve fibers originating from different cochlear locations. In effect, this analysis mimics the processing of phase-locked inputs from each ear by binaural neurons. We find that auditory nerve fibers that innervate different cochlear sites show a maximum number of coincidences when they are delayed relative to each other, and that the optimum delays decrease with characteristic frequency as in binaural neurons. These findings suggest that cochlear disparities make an important contribution to the internal delays observed in binaural neurons.

Frequency selectivity in Old-World monkeys corroborates sharp cochlear tuning in humans

Frequency selectivity in the inner ear is fundamental to hearing and is traditionally thought to be similar across mammals. Although direct measurements are not possible in humans, estimates of frequency tuning based on noninvasive recordings of sound evoked from the cochlea (otoacoustic emissions) have suggested substantially sharper tuning in humans but remain controversial. We report measurements of frequency tuning in macaque monkeys, Old-World primates phylogenetically closer to humans than the laboratory animals often taken as models of human hearing (e.g., cats, guinea pigs, chinchillas). We find that measurements of tuning obtained directly from individual auditory-nerve fibers and indirectly using otoacoustic emissions both indicate that at characteristic frequencies above about 500 Hz, peripheral frequency selectivity in macaques is significantly sharper than in these common laboratory animals, matching that inferred for humans above 4–5 kHz. Compared with the macaque, the human otoacoustic estimates thus appear neither prohibitively sharp nor exceptional. Our results validate the use of otoacoustic emissions for noninvasive measurement of cochlear tuning and corroborate the finding of sharp tuning in humans. The results have important implications for understanding the mechanical and neural coding of sound in the human cochlea, and thus for developing strategies to compensate for the degradation of tuning in the hearing-impaired.

Correlation Index: A new metric to quantify temporal coding

The standard procedure to study temporal encoding of sound waveforms in the auditory system has been Fourier analysis of responses to periodic stimuli. We introduce a new metric--correlation index (CI)--which is based on a simple counting of spike coincidences. It can be used for responses to aperiodic stimuli and does not require knowledge of the stimulus. Moreover, the basic procedure of comparing spiketimes in spiketrains is more physiological than currently used methods for temporal analysis. The CI is the peak value of the normalized shuffled autocorrelogram (SAC), which provides a quantitative summary of temporal structure in the neural response to arbitrary stimuli. We illustrate the CI and SACs by comparing temporal coding in the auditory nerve and output fibers of the cochlear nucleus.

Acoustic Stria: Anatomy of Physiologically Characterized Cells and Their Axonal Projection Patterns

The mammalian cochlear nucleus (CN) has been a model structure to study the relationship between physiological and morphological cell classes. Several issues remain, in particular with regard to the projection patterns and physiology of neurons that exit the CN dorsally via the dorsal (DAS), intermediate (IAS), and commissural stria. We studied these neurons physiologically and anatomically using the intra‐axonal labeling method. Multipolar cells with onset chopper (OC) responses innervated the ipsilateral ventral and dorsal CN before exiting the CN via the commissural stria. Upon reaching the midline they turned caudally to innervate the opposite CN. No collaterals were seen innervating any olivary complex nuclei. Octopus cells typically showed onset responses with little or no sustained activity. The main axon used the IAS and followed one of two routes occasionally giving off olivary complex collaterals on their way to the contralateral ventral nucleus of the lateral lemniscus (VNLL). Here they can have elaborate terminal arbors that surround VNLL cells. Fusiform and giant cells have overlapping but not identical physiology. Fusiform but not giant cells typically show pauser or buildup responses. Axons of both cells exit via the DAS and take the same course to reach the contralateral IC without giving off any collaterals en route. J. Comp. Neurol. 482:349–371, 2005.

Responses of Cochlear Nucleus Cells and Projections of their Axons

The advent of intracellular recording using horseradish peroxidase-filled glass electrodes offered a new and exciting approach to the in vivo cochlear nucleus (CN) preparation. Sharp glass microelectrodes, filled with a standard salt solution containing positively charged HRP molecules, made it feasible to record and characterize supra- and subthreshold intracellular responses of individual neurons to auditory stimuli, inject and subsequently recover the same HRP-labeled cell and ask the following basic questions; 1) Do morphologically defined cell types in the cochlear nucleus respond in a certain way to simple auditory stimuli at both the sub- and suprathreshold level? 2) Are the synaptic inputs of different cell types different, in terms of location, type and concentration, and are they arranged in ways that might help to explain the cell type’s unique responsiveness? 3) What is the projection pattern of individual axons originating from a given cell type, what are the shapes of vesicles within the terminals of these axons and can we make educated guesses about their influence on other cell populations based on this information?

How Secure Is In Vivo Synaptic Transmission at the Calyx of Held

The medial nucleus of the trapezoid body (MNTB) receives excitatory input from giant presynaptic terminals, the calyces of Held. The MNTB functions as a sign inverter giving inhibitory input to the lateral and medial superior olive, where its input is important in the generation of binaural sensitivity to cues for sound localization. Extracellular recordings from MNTB neurons show complex spikes consisting of a prepotential, thought to reflect synaptic activation, followed by a postsynaptic action potential. This makes the synapse ideal to study synaptic transmission in vivo because presynaptic and postsynaptic activity can be monitored with a single electrode. Recent in vivo and in vitro studies have observed isolated prepotentials in the MNTB suggesting that, under certain stimulus conditions, synaptic transmission fails. We investigated synaptic transmission at the calyx of Held in the MNTB of the adult cat and concluded that synaptic transmission was completely secure in terms of rate of transmitted spikes. However, synaptic transmission was found to be less secure in terms of timing. With increasing spike rate, the synaptic delay showed an increase of up to 100 μs, as well as a decrease in amplitude of the action potential. This variability in delay is of a surprisingly high magnitude given the hypothesized role of these binaural circuits in sound localization and given the fact that this is one of the largest synapses in the mammalian brain.

Enhanced Temporal Response Properties of Anteroventral Cochlear Nucleus Neurons to Broadband Noise

Compared with auditory nerve (AN) fibers, trapezoid body (TB) fibers of the cat show enhanced synchronization to low-frequency tones. This phenomenon probably contributes to the high temporal resolution of binaural processing. We examined whether enhanced synchronization also occurs to sustained broadband noise. We recorded responses to a reference Gaussian noise and its polarity-inverted version in the TB of barbiturate-anesthetized cats. From these we constructed shuffled autocorrelograms (SACs) and quantified spike timing by measuring the amplitude and width of their central peak. Many TB fibers with low characteristic frequency (CF) showed SACs with higher and narrower central peaks than ever observed in the AN, indicating better consistency and precision of temporal coding. Larger peaks were also observed in TB fibers with high CF, but this was mostly caused by higher average firing rates, resulting in a larger number of coincident spikes across stimulus repetitions. The results document monaural preprocessing of the temporal information delivered to binaural nuclei in the olivary complex, which likely contributes to the high sensitivity to interaural time differences.

Panoramic Measurements of the Apex of the Cochlea

Our understanding of cochlear mechanics is impeded by the lack of truly panoramic data. Sensitive mechanical measurements cover only a narrow cochlear region, mostly in the base. The global spatiotemporal pattern of vibrations along the cochlea cannot be inferred from such local measurements but is often extrapolated beyond the measurement spot under the assumption of scaling invariance. Auditory nerve responses give an alternative window on the entire cochlea, but traditional techniques do not allow recovery of the effective vibration pattern. We developed a new analysis technique to measure cochlear amplitude and phase transfer of fibers with characteristic frequencies <5 kHz. Data from six cats yielded panoramic phase profiles along the apex of the cochlea for an ∼5 octave range of stimulus frequencies. All profiles accumulated systematic phase lags from base to apex. Phase accumulation was not gradual but showed a two-segment character: a steep segment (slow propagation) around the characteristic position of the stimulus, and a shallow segment (fast propagation) basal to it. The transition between the segments occurred in a narrow region and was smooth. Wavelength near characteristic position decreased from ∼3.5 to ∼1 mm for frequencies from 200 to 4000 Hz, corresponding to phase velocities of ∼0.5 to ∼5 m/s. The accumulated phase lag between the eardrum and characteristic position varied from ∼1 cycle at 200 Hz to ∼2.5 cycle at 4 kHz, invalidating scaling invariance. The generic character of our analysis technique and its success in solving the difficult problem of reconstructing the effective sensory input from neural recordings suggest its wider application as a powerful alternative to customary system analysis techniques.