Institute of Anatomy I, Jena University Hospital, School of Medicine, Friedrich Schiller University, Jena, Germany.
Biol Psychol. 2011 Dec;88(2-3):204-14. doi: 10.1016/j.biopsycho.2011.08.003. Epub 2011 Aug 19.
We investigated the influence of Fourier power spectrum (1/f(p)) characteristics on face learning while recording ERPs that are associated with the representation of faces. Two image sets with an altered 1/f(p) characteristics were created. The first set consisted of stimuli with a STEEP SLOPE (1/f(3.5)) and therefore enhanced low spatial frequencies (LSF) and attenuated high spatial frequencies (HSF). The second set consisted of stimuli with a SHALLOW SLOPE (1/f(2)), similar to complex natural scenes and artwork, resulting in enhanced HSF and attenuated LSF. Faces with a SHALLOW SLOPE elicited larger N170 and N250 amplitudes and larger old/new effects for central positivity in comparison to unmodified faces. The opposite effect was observed for faces with a STEEP SLOPE that led to slower reaction times. This result suggests that diminishing the ratio of fine detail (HSF) to coarse structures (LSF) impairs face learning, whereas increasing it facilitates neurocognitive correlates of face learning.
我们研究了傅里叶功率谱（1/f(p)）特征对面部学习的影响，同时记录了与面部表示相关的 ERP。创建了两个具有改变的 1/f(p)特征的图像集。第一组刺激具有陡峭斜率（1/f(3.5)），因此增强了低空间频率（LSF）并衰减了高空间频率（HSF）。第二组刺激具有平缓斜率（1/f(2)），类似于复杂的自然场景和艺术作品，导致增强了 HSF 并衰减了 LSF。与未经修改的面孔相比，具有平缓斜率的面孔会引起更大的 N170 和 N250 幅度以及中央正性的更大旧/新效应。对于具有陡峭斜率的面孔，观察到相反的效果，导致反应时间变慢。这一结果表明，减少精细细节（HSF）与粗糙结构（LSF）的比例会损害面孔学习，而增加它则有助于面孔学习的神经认知相关性。
