Raul Pratik, McNally Kate, Ward Lawrence M, van Boxtel Jeroen J A
Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, ACT, Australia.
Department of Psychology, University of British Columbia, Vancouver, BC, Canada.
Front Neurosci. 2023 Apr 14;17:1110714. doi: 10.3389/fnins.2023.1110714. eCollection 2023.
While noise is generally believed to impair performance, the detection of weak stimuli can sometimes be enhanced by introducing optimum noise levels. This phenomenon is termed 'Stochastic Resonance' (SR). Past evidence suggests that autistic individuals exhibit higher neural noise than neurotypical individuals. It has been proposed that the enhanced performance in Autism Spectrum Disorder (ASD) on some tasks could be due to SR. Here we present a computational model, lab-based, and online visual identification experiments to find corroborating evidence for this hypothesis in individuals without a formal ASD diagnosis. Our modeling predicts that artificially increasing noise results in SR for individuals with low internal noise (e.g., neurotypical), however not for those with higher internal noise (e.g., autistic, or neurotypical individuals with higher autistic traits). It also predicts that at low stimulus noise, individuals with higher internal noise outperform those with lower internal noise. We tested these predictions using visual identification tasks among participants from the general population with autistic traits measured by the Autism-Spectrum Quotient (AQ). While all participants showed SR in the lab-based experiment, this did not support our model strongly. In the online experiment, significant SR was not found, however participants with higher AQ scores outperformed those with lower AQ scores at low stimulus noise levels, which is consistent with our modeling. In conclusion, our study is the first to investigate the link between SR and superior performance by those with ASD-related traits, and reports limited evidence to support the high neural noise/SR hypothesis.
虽然一般认为噪声会损害表现，但有时通过引入最佳噪声水平可以增强对微弱刺激的检测。这种现象被称为“随机共振”（SR）。过去的证据表明，自闭症个体比神经典型个体表现出更高的神经噪声。有人提出，自闭症谱系障碍（ASD）患者在某些任务上表现增强可能是由于随机共振。在此，我们提出一个基于实验室的计算模型和在线视觉识别实验，以在没有正式ASD诊断的个体中寻找支持这一假设的确凿证据。我们的模型预测，人为增加噪声会使内部噪声低的个体（如神经典型个体）产生随机共振，而内部噪声高的个体（如自闭症个体或具有较高自闭症特征的神经典型个体）则不会。它还预测，在低刺激噪声下，内部噪声高的个体比内部噪声低的个体表现更好。我们使用视觉识别任务对来自普通人群且通过自闭症谱系商数（AQ）测量有自闭症特征的参与者进行了测试。虽然在基于实验室的实验中所有参与者都表现出随机共振，但这并没有有力地支持我们的模型。在在线实验中，未发现显著的随机共振，然而在低刺激噪声水平下，AQ分数较高的参与者比AQ分数较低的参与者表现更好，这与我们的模型一致。总之，我们的研究首次调查了具有ASD相关特征的个体中随机共振与卓越表现之间的联系，并报告了有限的证据来支持高神经噪声/随机共振假设。
