Makin Alexis D J, Wright Damien, Rampone Giulia, Palumbo Letizia, Guest Martin, Sheehan Rhiannon, Cleaver Helen, Bertamini Marco
Department of Psychological Sciences, University of Liverpool, Eleanor Rathbone Building, Liverpool, L69 7ZA, UK
Department of Psychological Sciences, University of Liverpool, Eleanor Rathbone Building, Liverpool, L69 7ZA, UK.
Cereb Cortex. 2016 Dec;26(12):4416-4434. doi: 10.1093/cercor/bhw255. Epub 2016 Oct 4.
A traditional line of work starting with the Gestalt school has shown that patterns vary in strength and salience; a difference in "Perceptual goodness." The Holographic weight of evidence model quantifies goodness of visual regularities. The key formula states that W = E/N, where E is number of holographic identities in a pattern and N is number of elements. We tested whether W predicts the amplitude of the neural response to regularity in an extrastriate symmetry-sensitive network. We recorded an Event Related Potential (ERP) generated by symmetry called the Sustained Posterior Negativity (SPN). First, we reanalyzed the published work and found that W explained most variance in SPN amplitude. Then in four new studies, we confirmed specific predictions of the holographic model regarding 1) the differential effects of numerosity on reflection and repetition, 2) the similarity between reflection and Glass patterns, 3) multiple symmetries, and 4) symmetry and anti-symmetry. In all cases, the holographic approach predicted SPN amplitude remarkably well; particularly in an early window around 300-400 ms post stimulus onset. Although the holographic model was not conceived as a model of neural processing, it captures many details of the brain response to symmetry.
从格式塔学派开始的传统研究路线表明,模式在强度和显著性方面存在差异;这是一种“感知优度”的差异。全息证据权重模型对视觉规律的优度进行了量化。关键公式为W = E/N,其中E是模式中全息识别的数量,N是元素的数量。我们测试了W是否能预测在一个纹外对称敏感网络中对规律的神经反应的幅度。我们记录了由对称性产生的一种事件相关电位(ERP),称为持续后负波(SPN)。首先,我们重新分析了已发表的研究,发现W解释了SPN幅度中的大部分方差。然后在四项新的研究中,我们证实了全息模型关于以下方面的具体预测:1)数字对反射和重复的不同影响;2)反射与格拉斯图案之间的相似性;3)多重对称性;4)对称性与反对称性。在所有情况下,全息方法都能很好地预测SPN幅度;特别是在刺激开始后约300 - 400毫秒的早期窗口。虽然全息模型并非被构想为一种神经处理模型,但它捕捉到了大脑对对称性反应的许多细节。