{"title":"Reply to: “Model mimicry limits conclusions about neural tuning and can mistakenly imply unlikely priors”","authors":"Reuben Rideaux, Paul M. Bays, William J. Harrison","doi":"10.1038/s41467-025-60860-9","DOIUrl":null,"url":null,"abstract":"<p><b><span>replying to</span></b> Michael J. Wolff et al. Nature Communications [DOI of MA to be added at proof] (2025)</p><p>A key goal of visual neuroscience is to understand how the physical properties of the world are represented by the brain. Efficient coding theory<sup>1,2</sup> states that neural resources allocated to coding environmental features should be proportional to the frequency with which those features are found in nature. We recently found<sup>3</sup> a horizontal bias in the neural representation of visual orientation, as measured in humans with electroencephalography (EEG). We then used <i>generative forward modelling</i><sup>4</sup>, a method of comparing empirical neuroimaging recordings with matched simulated data produced by different population codes, to adjudicate between previously proposed and novel population codes of orientation in the visual cortex. Wolff and Rademaker<sup>5</sup> replicated our main findings in their own data as well as in a re-analysis of our data: there is a horizontal bias in EEG measurements of orientation. They argue, however, that generative forward modelling has limited utility because it is susceptible to model mimicry, i.e. many different population codes could be responsible for the same pattern of EEG signals. Further, the authors propose an alternative explanation for the horizontal bias observed in EEG, involving an interaction between stimulus vignetting<sup>6</sup> and a greater spatial representation of the horizontal meridian relative to the vertical meridian<sup>7,8,9</sup>. According to Wolff and Rademaker, this explanation is more plausible because it assumes equal representation of cardinal orientations and, in their view, there is little evidence supporting a horizontal bias in prior literature. Here we respond to these alternative explanations.</p><p>While we recognise that model mimicry presents a challenge in any inverse problem, we argue, contrary to Wolff and Rademaker, that rational constraints based on established neurophysiology can mitigate this risk. We will first clarify and expand on existing evidence that provides theoretical grounds for expecting a horizontal bias in neural representation, then explain why stimulus vignetting is unable to provide an alternative explanation for our results, and why Wolff and Rademaker’s findings for peripheral stimuli fail to challenge them. Finally, we highlight converging evidence for the horizontal bias obtained across multiple neuroimaging methods.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"37 1","pages":""},"PeriodicalIF":14.7000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-60860-9","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
replying to Michael J. Wolff et al. Nature Communications [DOI of MA to be added at proof] (2025)
A key goal of visual neuroscience is to understand how the physical properties of the world are represented by the brain. Efficient coding theory1,2 states that neural resources allocated to coding environmental features should be proportional to the frequency with which those features are found in nature. We recently found3 a horizontal bias in the neural representation of visual orientation, as measured in humans with electroencephalography (EEG). We then used generative forward modelling4, a method of comparing empirical neuroimaging recordings with matched simulated data produced by different population codes, to adjudicate between previously proposed and novel population codes of orientation in the visual cortex. Wolff and Rademaker5 replicated our main findings in their own data as well as in a re-analysis of our data: there is a horizontal bias in EEG measurements of orientation. They argue, however, that generative forward modelling has limited utility because it is susceptible to model mimicry, i.e. many different population codes could be responsible for the same pattern of EEG signals. Further, the authors propose an alternative explanation for the horizontal bias observed in EEG, involving an interaction between stimulus vignetting6 and a greater spatial representation of the horizontal meridian relative to the vertical meridian7,8,9. According to Wolff and Rademaker, this explanation is more plausible because it assumes equal representation of cardinal orientations and, in their view, there is little evidence supporting a horizontal bias in prior literature. Here we respond to these alternative explanations.
While we recognise that model mimicry presents a challenge in any inverse problem, we argue, contrary to Wolff and Rademaker, that rational constraints based on established neurophysiology can mitigate this risk. We will first clarify and expand on existing evidence that provides theoretical grounds for expecting a horizontal bias in neural representation, then explain why stimulus vignetting is unable to provide an alternative explanation for our results, and why Wolff and Rademaker’s findings for peripheral stimuli fail to challenge them. Finally, we highlight converging evidence for the horizontal bias obtained across multiple neuroimaging methods.
回复Michael J. Wolff等人。视觉神经科学的一个关键目标是理解世界的物理特性是如何用大脑来表示的。高效编码理论1,2指出,分配给编码环境特征的神经资源应该与这些特征在自然界中出现的频率成正比。我们最近发现,用脑电图(EEG)测量人类视觉方向的神经表征存在水平偏差。然后,我们使用生成前向模型4,这是一种将经验神经成像记录与不同种群代码产生的匹配模拟数据进行比较的方法,以判定视觉皮层中先前提出的和新的种群方向代码。Wolff和Rademaker5在他们自己的数据以及对我们数据的重新分析中重复了我们的主要发现:脑电图测量方向存在水平偏差。然而,他们认为,生成正演模型的效用有限,因为它容易受到模型模仿的影响,即许多不同的人口代码可能负责相同的脑电图信号模式。此外,作者对脑电图中观察到的水平偏差提出了另一种解释,包括刺激渐晕和相对于垂直子午线的更大的水平子午线空间表征之间的相互作用7,8,9。根据Wolff和Rademaker的说法,这种解释更合理,因为它假设了基本取向的平等代表,而且在他们看来,几乎没有证据支持先前文献中的水平偏差。在这里,我们对这些不同的解释做出回应。虽然我们认识到模型模仿在任何逆向问题中都是一个挑战,但我们认为,与Wolff和Rademaker相反,基于既定神经生理学的理性约束可以减轻这种风险。我们将首先澄清和扩展现有的证据,这些证据为预期神经表征中的水平偏差提供了理论基础,然后解释为什么刺激渐晕不能为我们的结果提供另一种解释,以及为什么Wolff和Rademaker关于外围刺激的发现未能挑战他们。最后,我们强调了通过多种神经成像方法获得的水平偏差的收敛证据。
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.