Reaching measures and feedback effects in auditory peripersonal space

Abstract

We analyse the effects of exploration feedback on reaching measures of perceived auditory peripersonal space (APS) boundary and the auditory distance perception (ADP) of sound sources located within it. We conducted an experiment in which the participants had to estimate if a sound source was (or not) reachable and to estimate its distance (40 to 150 cm in 5-cm steps) by reaching to a small loudspeaker. The stimulus consisted of a train of three bursts of Gaussian broadband noise. Participants were randomly assigned to two groups: Experimental (EG) and Control (CG). There were three phases in the following order: Pretest–Test–Posttest. For all phases, the listeners performed the same task except for the EG-Test phase where the participants reach in order to touch the sound source. We applied models to characterise the participants’ responses and provide evidence that feedback significantly reduces the response bias of both the perceived boundary of the APS and the ADP of sound sources located within reach. In the CG, the repetition of the task did not affect APS and ADP accuracy, but it improved the performance consistency: the reachable uncertainty zone in APS was reduced and there was a tendency to decrease variability in ADP.

Auditory distance perception by blind and sighted participants for both within- and beyond-reach sources.

“…The authors proposed a model in which, after the feedback session, the participants were able to apply an optimal correction without altering the slope (associated with the response range). Interestingly, when we applied the model proposed by Hüg et al (2019) to our average reaching data, we observed that the blind participants' intercept yielded an almost optimal response (unsigned bias is minimized and signed bias is very close to zero), while sighted participants were far from optimality. That is, blind participants had an average response similar to that reported by Hüg et al (2019) for sighted participants after a feedback session.…”

“…Interestingly, when we applied the model proposed by Hüg et al (2019) to our average reaching data, we observed that the blind participants' intercept yielded an almost optimal response (unsigned bias is minimized and signed bias is very close to zero), while sighted participants were far from optimality. That is, blind participants had an average response similar to that reported by Hüg et al (2019) for sighted participants after a feedback session. This result suggests that blind participants could be using the audio-motor feedback obtained from manipulating nearby sources to calibrate ADP and that this calibration is kept over time.…”

“…This change in the response is the type of change that the authors observed after feedback was provided and therefore serves as a model of the overall performance of the response in terms of bias. The performance of the response for a given shift is obtained by recalculating the between-subjects average of the collapsed bias, both signed and unsigned (for a full description of the methodology, please see Hüg et al, 2019). In this way, we obtain a curve of the collapsed bias that is a function of the shift.…”

“…The effect of changes in the intercept on the signed and unsigned total bias can be modeled by applying a shift in the subjects' responses (Hüg et al, 2019). As a consequence, the mean response curve of each group moves up and down, shifting the intercept by the same amount while keeping the slope constant.…”

Rediscovering Richard Held: Activity and Passivity in Perceptual Learning

“…We have performed a study to compare the effect of active and passive exploration on a task where participants, blindfolded and seated, had to reach toward a sound source located in front of them at different distances (similar task as in Hüg et al, 2019). In the active condition, during a training session participants freely explored the arrangement until reaching and touching the sound source.…”