"What is in a word? No versus Yes differentially engage the lateral orbitofrontal cortex": Correction.

Reports an error in "What is in a word? No versus Yes differentially engage the lateral orbitofrontal cortex" by Nelly Alia-Klein, Rita Z. Goldstein, Dardo Tomasi, Lei Zhang, Stephanie Fagin-Jones, Frank Telang, Gene-Jack Wang, Joanna S. Fowler and Nora D. Volkow (Emotion, 2007[Aug], Vol 7[3], 649-659). The supplemental materials link should appear as follows: http://dx.doi.org/10.1037/1528-3542.7.3.649.supp. (The following abstract of the original article appeared in record 2007-11660-018.) The words "No" and "Yes" are involved in conditioning to prohibit or encourage behavior, respectively. The authors, therefore, hypothesized that these words would be attributed to endogenous valence, activating neuronal circuits involved with valence and emotional control. Functional MRI (fMRI) at 4 Tesla was used to record regional brain activity while participants were exposed to emphatic vocalizations of the words. Results showed that No and Yes were associated with opposite brain-behavior responses; while No was negatively valenced, produced slower response times, and evoked a negative signal in the right lateral orbitofrontal cortex (OFC), Yes was positively valenced, produced faster response times, and evoked a positive signal in a contiguous region of the OFC. Attribution of negative valence to No and trait anger control were associated with increased responsivity of the OFC to No. Inasmuch as sensitivity to the prohibitive command No develops during childhood through interaction with primary caregivers as the first social objects, our findings may implicate the lateral OFC in the neurobiology of emotion regulation and subsequent social development. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Neural correlates of sexual arousal in homosexual and heterosexual men.

Men exhibit much higher levels of genital and subjective arousal to sexual stimuli containing their preferred sex than they do to stimuli containing only the nonpreferred sex. This study used event-related functional magnetic resonance imaging to investigate how this category-specific pattern would be reflected in the brains of homosexual (n = 11) and heterosexual (n = 11) men. Comparisons of activation to preferred sexual stimuli, nonpreferred sexual stimuli, and sports stimuli revealed large networks correlated with sexual arousal, spanning multiple cortical and subcortical areas. Both homosexual and heterosexual men exhibited category-specific arousal in brain activity. Within the amygdala, greater preference-related activity was observed in homosexual men, but it is unclear whether this is a cause or a consequence of their sexuality. In a subsequent analysis of regions hypothesized to support arousal, both participant groups demonstrated widespread increases in evoked activity for preferred stimuli. Aggregate data from these regions produced significant differences between stimulus types in 16 out of 22 participants. Significant activational differences matched reported sexual orientation in 15 of these 16 participants, representing an advance in psychophysiological measures of arousal. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

想象热刺激和实际热刺激脑功能成像研究

本实验用功能性核磁共振成像技术（fMRI）对人想象热刺激和实际接受热刺激进行了研究。这是继想象冷刺激和实际接受冷刺激实验之后的另一个关于想象刺激与实际接受刺激的实验、实验结果发现想象热刺激与实际热刺激激活脑区既有相同之处也有不同之处。想象热刺激激活了初级体感区（SI）、左侧额上回、左侧额中回、运动区和扣带回。实际热刺激激活了初级体感区（SI）区、右侧额上回、右侧额中回、运动区。区别在于额叶和扣带回,这个结论与想象冷刺激和实际冷刺激实验的结论几乎相同,只是两种情况下在额叶的具体差别不同。     

基于功能磁共振成像的人脑效应连接网络识别方法综述

人脑效应连接网络刻画了脑区间神经活动的因果效应. 对不同人群的脑效应连接网络进行研究不仅能为神经精神疾病病理机制的理解提供新视角, 而且能为疾病的早期诊断和治疗评价提供新的脑网络影像学标记, 具有十分重要的理论意义和应用价值. 利用计算方法从功能磁共振成像(Functional magnetic resonance imaging, fMRI)数据中识别脑效应连接网络是目前人脑连接组学中一项重要的研究课题. 本文首先概括了从fMRI数据中进行脑效应连接网络识别的主要流程, 说明了其中的主要步骤和方法; 然后, 给出了一种脑效应连接网络识别方法的分类体系, 并对其中一些代表性的识别算法进行了阐述; 最后, 通过对该领域挑战性问题的分析, 预测了脑效应连接网络识别未来的研究方向, 以期对相关研究提供一定的参考.     

基于智能计算的脑机制研究

解析脑认知原理和脑疾病的发病机制已是当下脑科学研究的热点。智能计算在脑影像领域的应用可为认知心理学研究、脑疾病的识别和干预以及类脑智能理论研究等提供借鉴和参考。本文介绍利用智能影像计算方法在识别脑认知网络成分、构建脑有向连接模型、预测认知行为变化、构建心理过程神经表征等方面的工作,并对未来相关研究进行展望。     

fMRI数据的有监督特征提取方法综述

近年来,机器学习技术广泛用于从功能磁共振成像（functional magnetic resonance imaging,fMRI）数据中解码视觉信息、精神状态、情绪和其它感兴趣的大脑感知和认知功能。然而,由于fMRI数据样本维数高,样本量少,一般需要利用特征提取方法去除多余的预测变量和实验噪声等信息,避免机器学习模型出现过拟合问题,提高模型的预测准确率和泛化能力。介绍和讨论了常用fMRI数据有监督特征提取方法的一般原理和研究现状,并着重分析其性能和可能改进方向,最后对特征提取方法在fMRI中的研究方向进行了展望。     

基于多维模式分析对说谎的脑网络特征识别

为了研究说谎时的脑网络特征,采集了32个被试在说真话和说谎条件下的功能磁共振数据,预处理后利用AAL模板构建不同条件下的功能连接网络,再利用基于机器学习的多维模式分类器对说谎和说真话进行分类。该分类器取得了良好的分类正确率82.03%(说谎84.38%,说真话79.69%),并提取了辨别说谎和说真话的有效的功能连接模式。结果表明了使用大尺度的功能连接对说谎和说真话进行分类的良好性能,并且从脑网络角度揭示了说谎的特征。     

ICA算法在fMRI中的应用

独立分量分析（ICA）是信号处理领域新近发展起来的一种很有应用前景的方法,而脑功能磁共振（fMRI）信号的有效分离与识别是一个正在研究和实验之中的技术领域。近年来,ICA已被成功地应用于fMRI数据的处理,成为分析IMRI数据的一种很有效的方法。本文介绍了ICA在分析fMRI数据方面的应用,以及多种ICA算法在fMRI信号盲源分离中 的应用,分析了三种算法的问题,给出了本人对此研究的展望。     

fMRI动态功能网络构建及其在脑部疾病识别中的应用

如何从复杂的fMRI数据中提取 丰富的大脑信息是提高脑部疾病识别精度的关键。传统的静息态功能磁共振成像分析中,功能连接网络被认为是稳定不变的。提出一种基于成组独立成分分析的构建动态功能连接网络的方法,并通过该网络来获取功能网络本身的动态特性。首先,利用成组独立成分分析法提取fMRI数据的空间独立成分作为网络节点,并通过滑动时间窗的方法获取窗口时间序列,构建动态功能连接网络。以动态功能网络作为特征,对精神分裂症患者和正常被试数据进行分类识别。实验结果表明,该方法能够获取fMRI数据的时间维度信息,提高识别效果,在一定程度上能为临床诊断提供客观参照。     

汉字读音判断时非文盲右脑活动特征的fMRI研究

利用功能性磁共振成像（fMRI）技术探讨汉字语音判断时非文盲的大脑活动特征。实验使用汉字语音和纯音比较了中国人文盲和非文盲语音加工过程脑机制的差异。结果表明文盲与非文盲汉字语音加工脑机制不同,且非文盲的脑活动强,尤其是右脑。