Department of Biophysics, Radboud University, Donders Institute for Brain, Cognition and Behaviour, 6525 AJ Nijmegen, The Netherlands.
eNeuro. 2019 Apr 5;6(2). doi: 10.1523/ENEURO.0111-18.2019. eCollection 2019 Mar-Apr.
The auditory system relies on binaural differences and spectral pinna cues to localize sounds in azimuth and elevation. However, the acoustic input can be unreliable, due to uncertainty about the environment, and neural noise. A possible strategy to reduce sound-location uncertainty is to integrate the sensory observations with sensorimotor information from previous experience, to infer where sounds are more likely to occur. We investigated whether and how human sound localization performance is affected by the spatial distribution of target sounds, and changes thereof. We tested three different open-loop paradigms, in which we varied the spatial range of sounds in different ways. For the narrowest ranges, target-response gains were highly idiosyncratic and deviated from an optimal gain predicted by error-minimization; in the horizontal plane the deviation typically consisted of a response overshoot. Moreover, participants adjusted their behavior by rapidly adapting their gain to the target range, both in elevation and in azimuth, yielding behavior closer to optimal for larger target ranges. Notably, gain changes occurred without any exogenous feedback about performance. We discuss how the findings can be explained by a sub-optimal model in which the motor-control system reduces its response error across trials to within an acceptable range, rather than strictly minimizing the error.
听觉系统依赖于双耳差异和耳廓频谱线索来定位水平和垂直方向的声音。然而，由于对环境的不确定性和神经噪声，声信号输入可能不可靠。减少声音定位不确定性的一种可能策略是将感官观察与来自先前经验的感觉运动信息相结合，以推断声音更有可能出现的位置。我们研究了人类声音定位性能是否以及如何受到目标声音的空间分布及其变化的影响。我们测试了三种不同的开环范式，以不同的方式改变声音的空间范围。对于最窄的范围，目标响应增益具有高度的个体差异，并且偏离了根据误差最小化预测的最佳增益；在水平面上，这种偏差通常表现为响应过冲。此外，参与者通过快速将增益调整到目标范围来调整其行为，无论是在仰角还是方位角，从而使较大目标范围的行为更接近最佳。值得注意的是，增益变化发生在没有任何关于性能的外生反馈的情况下。我们讨论了如何通过一个次优模型来解释这些发现，在该模型中，运动控制系统在整个试验中减少其响应误差到可接受的范围内，而不是严格地最小化误差。
