Pre_Stim_Results

Animate/inanimate face recognition task was administered using the Presentation program (Neurobehavioral Systems). Face stimuli were obtained from Looser &amp; Wheatley (2010) who morphed twenty inanimate faces with well-matched photographs of human faces using FantaMorph software (Version 3; Abrosoft Co., Beijing, China). The resulting image sets were the product of linear interpolation between the two (human/mannequin) original images. This kept the increments of physical change consistent across the morphing continuum, which consisted of 5 ‘human’ faces (1-5, containing 60-100% human aspects) and 5 ‘mannequin’ faces (7-11, containing 60-100% mannequin aspects) and a sixth, middle face that was considered a 50% human-50% mannequin version.This task consisted of the presentation of 9 blocks of faces presented on a different 15” laptop screen, placed at about eye level approximately 66 cm in front of participants. Each face stimulus block contained a sequence of 11 human-like faces morphed as previously described. This provided a total of 99 faces. When instructed to begin, participants saw a randomly selected face in the middle of the screen, (W: 10-12 cm; H: 11-15 cm) followed by a question as to whether the face was inanimate (1) or animate (2). Each trial lasted 3000ms (1000 ms face stimuli duration and 2000 ms response screen duration). Participants were instructed to relax and minimize movements since EEG was being recorded simultaneously.<br>Presentation of faces was immediately followed by a question as to whether the face was inanimate (1) or animate (2). Reaction times (RTs) were collected for those responses. Outlier analysis of the data was performed in which RTs more than two standard deviations above or below the mean were removed. Participant responses were also analyzed by using polynomial regression fitting to compute the functions representing subjects’ responses. This was done by collecting and analyzing response data from individual subjects across the 9 face blocks (Cheetham &amp; Jancke, 2013), each of which was shown to participants before and after stimulation. Each of the 9 face blocks contained 11 different morph images with a unique morph identifier, also known as a face continua. Response data for each face continua were aggregated and averaged, generating 9 functions displaying the response data prior to stimulation and 9 functions following stimulation. In pooling the 18 different polynomial curves, four cumulative functions were generated -- one for pre-STIM, post-STIM, pre-SHAM, and post-SHAM, thus allowing larger inferences on how participants responded to each morph image prior to and following the onset of stimulation to be drawn. Once the four cumulative functions were generated, the point of subjective equality (PSE) was calculated. This is the point at which a face was equally likely to be deemed animate or inanimate (following Looser &amp; Wheatley, 2010). It was done by finding the polynomial function associated with the fitted curve and finding the x-coordinate corresponding to the point at which the function reached the 50% recognition point. <br><br>

本研究采用Presentation软件（Neurobehavioral Systems公司开发）实施有生命/无生命面孔识别任务。面孔刺激材料取自Looser与Wheatley（2010）的研究，他们使用FantaMorph软件（版本3；北京Abrosoft公司）将20张无生命面孔与匹配度极高的人类面孔照片进行形态融合。最终的图像集由两类原始图像（人类/人体模型）经线性插值生成，此举确保了形态连续体上的物理变化增量保持一致。该形态连续体包含5张“人类”面孔（编号1-5，人类特征占比60%-100%）、5张“人体模型”面孔（编号7-11，模型特征占比60%-100%），以及1张处于中间的50%人类-50%模型特征的混合面孔。

本任务共包含9组面孔刺激块，通过一台15英寸笔记本电脑呈现，屏幕置于被试眼前约66cm处，高度与被试视线齐平。每组面孔刺激块包含11张按前述方式生成的类人面孔，总计99张刺激面孔。当被试接收到开始指令后，屏幕中央会先呈现一张随机选取的面孔（宽10-12cm，高11-15cm），随后显示问题：该面孔为无生命（按键1）还是有生命（按键2）？每个试次总时长为3000ms，其中面孔刺激呈现时长1000ms，作答界面呈现时长2000ms。由于同步采集脑电图（EEG）数据，要求被试保持放松并尽量减少肢体动作。

面孔呈现后立即显示前述作答问题，系统记录被试的反应时（RT）。对反应时数据进行异常值剔除分析：删除超出均值±2个标准差的反应时数据。同时采用多项式回归拟合方法，构建拟合被试作答反应的函数曲线。该分析基于单名被试在9组面孔刺激块上的作答数据完成（Cheetham与Jancke，2013），每组刺激块均在刺激干预前后分别呈现给被试。9组面孔刺激块各包含11张具有唯一形态标识的融合图像，即所谓的面孔形态连续体。对每张面孔形态连续体的作答数据进行汇总与平均，最终生成9组刺激前的反应函数与9组刺激后的反应函数。

将18条不同的多项式曲线合并后，可生成4条累积函数曲线：分别对应刺激前、刺激后、假刺激前以及假刺激后，由此可更全面地推断被试在刺激干预前后对各类融合面孔的反应模式。生成4条累积函数曲线后，计算主观相等点（Point of Subjective Equality, PSE），该点指面孔被判定为有生命与无生命的概率相等的阈值（参照Looser与Wheatley，2010）。具体计算方式为：先确定拟合曲线对应的多项式函数，再求解该函数达到50%识别率时对应的横坐标值。