Distribution of Interaural Time Difference in the Barn Owl's Inferior Colliculus in the Low- and High-Frequency Ranges

Abstract

Interaural time differences are an important cue for azimuthal sound localization. It is still unclear whether the same neuronal mechanisms underlie the representation in the brain of interaural time difference in different vertebrates and whether these mechanisms are driven by common constraints, such as optimal coding. Current sound localization models may be discriminated by studying the spectral distribution of response peaks in tuning curves that measure the sensitivity to interaural time difference. The sound localization system of the barn owl has been studied intensively, but data that would allow discrimination between currently discussed models are missing from this animal. We have therefore obtained extracellular recordings from the time-sensitive subnuclei of the barn owl's inferior colliculus. Response peaks were broadly scattered over the physiological range of interaural time differences. A change in the representation of the interaural phase differences with frequency was not observed. In some neurons, response peaks fell outside the physiological range of interaural time differences. For a considerable number of neurons, the peak closest to zero interaural time difference was not the behaviorally relevant peak. The data are in best accordance with models suggesting that a place code underlies the representation of interaural time difference. The data from the high-frequency range, but not from the low-frequency range, are consistent with predictions of optimal coding. We speculate that the deviation of the representation of interaural time difference from optimal-coding models in the low-frequency range is attributable to the diminished importance of low frequencies for catching prey in this species.

Direction Selectivity Mediated by Adaptation in the Owl's Inferior Colliculus

“…There is mounting evidence that DS for FM sweeps can be explained by asymmetric excitation and inhibition across the tonotopic axis (Casseday et al, 1994;Zhang et al, 2003;Ye et al, 2010;Kuo and Wu, 2012). These mechanisms are consistent with findings in vision where asymmetric circuit structure confers DS in the retina (Briggman et al, 2011;Wei et al, 2011;Vaney et al, 2012).…”

“…Adult barn owls of both sexes (3 males, 1 female) were implanted with stainless steel head plates and a reference post, as described previously (Steinberg and Peña, 2011;Wang et al, 2012). A dental acrylic well was built around the craniotomy above external nucleus of the IC (ICx) for repeated sessions in each animal.…”

Neural Development of Binaural Tuning through Hebbian Learning Predicts Frequency-Dependent Best Delays

“…In birds, physiological observations are in general accordance with the Jeffress model (Jeffress, 1948): in each frequency band, binaural neurons have heterogeneous BDs, resulting from differences in axonal delays of their inputs, and the ITD of the sound source is signaled by the BD of the maximally activated neuron (Carr and Konishi, 1990). One notable disagreement is that, instead of covering the full physiological range of ITDs (Ϯ250 s in the barn owl) (von Campenhausen and Wagner, 2006), BDs rarely exceed half the characteristic period of the neuron (Wagner et al, 2007;Köppl and Carr, 2008;Carr et al, 2009), an approximate constraint called the "-limit." Figure 1A shows the BD and CF of 625 cells in the core of central nucleus of the inferior colliculus (ICCc) of the barn owl (data provided by H. Wagner (Rheinisch-Westfälische Technische Hochschule, Aachen, Germany) and previously shown in Wagner et al, 2007): high-frequency cells tend to have smaller BDs than lowfrequency cells, and 85% of all BDs fall within the -limit (i.e., BD Ͻ 1/(2CF), solid curves).…”

“…If synaptic weights evolve according to some Hebbian mechanism, i.e., synapses are strengthened when input and output are coactive, then these input correlations should translate into correlated synaptic modifications. Since we are interested in the development of delay selectivity at a submillisecond timescale, the basis of such a Hebbian mechanism must be the timing of presynaptic and (Wagner et al, 2007): 85% of all BDs are within the -limit (solid curves). B, Top, The sound is bandpass filtered by the basilar membrane around a characteristic frequency (vertical units are arbitrary).…”

“…One notable disagreement is that, instead of covering the full physiological range of ITDs (Ϯ250 s in the barn owl) (von Campenhausen and Wagner, 2006), BDs rarely exceed half the characteristic period of the neuron (Wagner et al, 2007;Köppl and Carr, 2008;Carr et al, 2009), an approximate constraint called the "-limit." Figure 1A shows the BD and CF of 625 cells in the core of central nucleus of the inferior colliculus (ICCc) of the barn owl (data provided by H. Wagner (Rheinisch-Westfälische Technische Hochschule, Aachen, Germany) and previously shown in Wagner et al, 2007): high-frequency cells tend to have smaller BDs than lowfrequency cells, and 85% of all BDs fall within the -limit (i.e., BD Ͻ 1/(2CF), solid curves). From a functional point of view, this is not a strong constraint because BDs with the same phase relative to the CF are mostly redundant.…”