Natural ITD statistics predict human auditory spatial perception

Pavão, Rodrigo; Sussman, Elyse; Fischer, Brian J.; Peña, José Luis

doi:10.7554/elife.51927

Cited by 16 publications

(19 citation statements)

References 52 publications

(121 reference statements)

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“…The contribution of yaw and roll to the process of sound localisation based on ITD can be investigated with the so-called ITD angular rate, i.e., dITD/da with a being the source angle along a given rotation axis. ITD angular rate describes the change in ITD caused by the change in the source direction [64]. Figure 3 shows ITD angular rates for the three rotation axes and sources placed over the full sphere.…”

Section: Acoustic Features and Perceptual Cuesmentioning

confidence: 99%

Towards modelling active sound localisation based on Bayesian inference in a static environment

et al. 2021

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Over the decades, Bayesian statistical inference has become a staple technique for modelling human multisensory perception. Many studies have successfully shown how sensory and prior information can be combined to optimally interpret our environment. Because of the multiple sound localisation cues available in the binaural signal, sound localisation models based on Bayesian inference are a promising way of explaining behavioural human data. An interesting aspect is the consideration of dynamic localisation cues obtained through self-motion. Here we provide a review of the recent developments in modelling dynamic sound localisation with a particular focus on Bayesian inference. Further, we describe a theoretical Bayesian framework capable to model dynamic and active listening situations in humans in a static auditory environment. In order to demonstrate its potential in future implementations, we provide results from two examples of simplified versions of that framework.

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Section: Acoustic Features and Perceptual Cuesmentioning

confidence: 99%

Towards modelling active sound localisation based on Bayesian inference in a static environment

et al. 2021

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“…For each condition (combination of frequency and reference ITD), the estimated dITD threshold was the ITD value which maximally separated the subject's correct and incorrect/unsure responses. This is essentially the same protocol as the one described in (Pavão et al 2020), but applied to additional subjects (Experiments 1 and 2). Figure 4 supplement shows dITD thresholds averaged across subjects for each condition from the three datasets/experiments, which differ by the set of conditions presented to the independent pool of subjects.…”

Section: Human Ditd Thresholdsmentioning

confidence: 99%

“…In order to select the method for computing √FI ITD that best predicts human ITD thresholds, we pooled the previously collected data for 24 subjects (12 females and 12 males) by (Pavão et al 2020) with data for 30 subjects (9 females and 21 males) collected specifically for our study in two experimental phases. The protocol was approved by the Ethics Committee of Universidade Federal do ABC.…”

Section: Estimation Of Ditd Thresholdsmentioning

confidence: 99%

“…Our premise is that estimating √FI ITD through methods which mimic auditory mechanisms and reflect properties of natural environments could improve prediction of ITD discriminability. The direct method for estimating √FI ITD described in (Pavão et al 2020) was based on a single HRTF database for which, √FI ITD curves are asymmetric, and ITDs were computed from the acoustic signals independently of their amplitude and delay compensation. These are potential caveats given that human head and ears are symmetrical, there is a sound pressure threshold for exciting the basilar membrane, and whether delay lines exist in humans or not is still under debate.…”

Section: Introductionmentioning

confidence: 99%

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Low noise HRTFs and delay line corrections are detrimental to the prediction of ITD discrimination thresholds from environmental statistics

Camperos

Gonçalves

Marin

et al. 2022

Preprint

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Interaural Time Difference (ITD) is the main cue for azimuthal auditory perception in humans. ITDs at each frequency contribute differently to azimuth discrimination, which can be quantified by their azimuthal Fisher Information. Consistently, human ITD discrimination thresholds are predicted by the azimuthal information. However, this prediction is poor for frequencies below 500 Hz. Such poor prediction could be ascribed to the strategy of quantifying azimuthal information using HRTFs obtained in unnaturalistic anechoic chambers or by using a direct method which does not incorporate the delay lines proposed by the Jeffress-Colburn model. In the present study, we obtained ITD discrimination thresholds from extensive sampling across frequency and ITD, and applied multiple strategies for quantifying azimuthal information. These strategies employed HRTFs obtained in realistic and anechoic chambers, with and without considering delay lines. We found that ITD discriminability thresholds across the complete range of frequencies are better predicted by azimuthal information conveyed by ITD cues when (1) we use naturalistic high-noise HRTFs, and (2) ITD delay compensation is not applied. Our results support that auditory perception is shaped by natural environments, which include high reverberation in low frequencies. Moreover, we also suggest that delay lines are not a crucial feature for determining ITD discrimination thresholds in the human auditory system.

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“…A relationship between frequency tuning and ITD tuning has been reported in the midbrain and brainstem of mammalian models as well, however this was proposed to be related to ITD neural coding and detection properties rather than anticipated ITD reliability (McAlpine et al, 2001;Hancock and Delgutte, 2004;Day and Semple, 2011;Bremen and Joris, 2013). In contrast, recent findings show that human spatial perception is driven by natural ITD statistics across frequencies, including ITD variability induced by concurrent sounds (Pavão et al, 2020), suggesting commonalities between humans and owls in the anticipation of ITD cue reliability based on acoustic properties of the head. Overall, these previous studies indicate that the predictive coding of natural ITD reliability is inherent in the brain of humans and owls, but directly testing development and causality of this statistical property on the frequency tuning of neurons representing auditory space and whether this coding is innately fixed or experience dependent remain open questions.…”

Section: Introductionmentioning

confidence: 96%

Development shaped by cue reliability in the barn owl’s auditory midbrain

Shadron

Peña

2022

Preprint

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Sensory systems display capability to preferentially choose stimuli based on their reliability at conveying accurate information. While previous reports have shown the ability of the brain to reweigh cues based on ongoing or dynamic changes in reliability, how the brain may learn and maintain neural responses to sensory statistics expected to be stable over longer time periods remain significant open questions of potential mechanisms underlying naturalistic biased perception. This study provides evidence that the barn owl's midbrain is shaped by permanent statistics experienced during development. The barn owl's midbrain features a topographic map of auditory space where neurons compute horizontal sound location from the interaural time difference (ITD). Previous work has shown that frequency tuning of these midbrain map neurons is correlated with the pattern of most reliable frequencies for the neurons' preferred ITD. This pattern of ITD reliability is due to the filtering properties of the head, primarily determined by the facial ruff in the barn owl. In this study, we found that the absence of a facial ruff led to a decrease in the reliability of high frequencies originating from frontal space. To test if the owl's frequency tuning of midbrain map neurons is driven by permanent changes in the pattern of ITD reliability, these neurons were recorded from adult owls, who had the facial ruff removed as juveniles, and from juvenile owls, before the facial ruff developed. In both groups, we found that frontally-tuned neurons displayed tunings to frequencies lower than reported in normal adult owls, consistent with the difference in ITD reliability between the normal and ruff removed conditions. Juvenile owls also exhibited more heterogeneous frequency tuning, suggesting developmental processes that refine tuning to match the pattern of ITD reliability. Additional recordings immediately upstream of the midbrain map displayed ITD tuned neural responses for all frequencies across the owl's normal hearing range. Broader analysis of the effects of ruff-removal on the acoustical properties of spatial cues indicated a dominant role of ITD reliability in driving the adaptive changes in frequency tuning. These results support the hypothesis that frequency tuning in the midbrain map is developmentally adapted to permanent statistics of spatial cues, implementing probabilistic coding for sound localization.

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Natural ITD statistics predict human auditory spatial perception

Cited by 16 publications

References 52 publications

Towards modelling active sound localisation based on Bayesian inference in a static environment

Towards modelling active sound localisation based on Bayesian inference in a static environment

Low noise HRTFs and delay line corrections are detrimental to the prediction of ITD discrimination thresholds from environmental statistics

Development shaped by cue reliability in the barn owl’s auditory midbrain

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