Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression.
Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression.
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DOI：
10.1111/j.1399-5618.2012.01019.x
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发表时间：
2012-06
影响因子：
5.4
通讯作者：
Phillips ML
中科院分区：
文献类型：
--
作者：
Mourão-Miranda J;Almeida JR;Hassel S;de Oliveira L;Versace A;Marquand AF;Sato JR;Brammer M;Phillips ML
最近，模式识别方法被用来对感觉或认知过程引起的大脑活动模式进行分类。在临床上，这些方法主要用于基于结构磁共振成像(MRI)数据对个体分组进行分类。只有少数研究将类似的方法应用于功能磁共振成像(FMRI)数据。我们使用了一个新的分析框架来检验单相和双相抑郁个体在区分快乐和中性面孔的神经活动模式上的差异程度。我们使用了18名患有双相I型障碍(BD)和18名患有复发性单相抑郁(UD)的抑郁患者的数据，他们的抑郁严重程度、年龄和病程相匹配，以及18名年龄和性别比例匹配的健康对照受试者(HC)。使用一般线性模型和高斯过程分类器对fMRI数据进行分析。在两组患者中，区分快乐面孔和中性面孔神经活动模式的准确率总体上都低于HC。HC患者出现强烈和轻微笑脸的预测概率高于BD患者，HC患者出现轻度笑脸的预测概率高于UD患者(均P<；0.001)。有趣的是，UD患者出现强烈笑脸的预测概率显著高于BD患者(p=0.03)。这些结果表明，BD患者的全脑神经活动模式与中性面孔相比，显著低于HC或UD患者。这些发现表明，模式识别方法可以用来识别患者群体中的异常脑活动模式，并具有良好的临床实用价值，可以帮助区分不同精神疾病的患者。
Recently, pattern recognition approaches have been used to classify patterns of brain activity elicited by sensory or cognitive processes. In the clinical context, these approaches have been mainly applied to classify groups of individuals based on structural magnetic resonance imaging (MRI) data. Only a few studies have applied similar methods to functional MRI (fMRI) data. We used a novel analytic framework to examine the extent to which unipolar and bipolar depressed individuals differed on discrimination between patterns of neural activity for happy and neutral faces. We used data from 18 currently depressed individuals with bipolar I disorder (BD) and 18 currently depressed individuals with recurrent unipolar depression (UD), matched on depression severity, age, and illness duration, and 18 age- and gender ratio-matched healthy comparison subjects (HC). fMRI data were analyzed using a general linear model and Gaussian process classifiers. The accuracy for discriminating between patterns of neural activity for happy versus neutral faces overall was lower in both patient groups relative to HC. The predictive probabilities for intense and mild happy faces were higher in HC than in BD, and for mild happy faces were higher in HC than UD (all p < 0.001). Interestingly, the predictive probability for intense happy faces was significantly higher in UD than BD (p = 0.03). These results indicate that patterns of whole-brain neural activity to intense happy faces were significantly less distinct from those for neutral faces in BD than in either HC or UD. These findings indicate that pattern recognition approaches can be used to identify abnormal brain activity patterns in patient populations and have promising clinical utility as techniques that can help to discriminate between patients with different psychiatric illnesses.
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影响因子：
--
作者：
Koutsouleris, Nikolaos;Meisenzahl, Eva M.;Davatzikos, Christos;Bottlender, Ronald;Frodl, Thomas;Scheuerecker, Johanna;Schmitt, Gisela;Zetzsche, Thomas;Decker, Petra;Reiser, Maximilian;Moeller, Hans-Juergen;Gaser, Christian
通讯作者：
Gaser, Christian
影响因子：
10.6
作者：
Fu, Cynthia H. Y.;Mourao-Miranda, Janaina;Brammer, Michael J.
通讯作者：
Brammer, Michael J.
影响因子：
10.6
作者：
Cardoso de Almeida, Jorge Renner;Versace, Amelia;Mechelli, Andrea;Hassel, Stefanie;Quevedo, Karina;Kupfer, David Jerome;Phillips, Mary Louise
通讯作者：
Phillips, Mary Louise
影响因子：
14.5
作者：
Kloeppel, Stefan;Stonnington, Cynthia M.;Chu, Carlton;Draganski, Bogdan;Scahill, Rachael I.;Rohrer, Jonathan D.;Fox, Nick C.;Jack, Clifford R., Jr.;Ashburner, John;Frackowiak, Richard S. J.
通讯作者：
Frackowiak, Richard S. J.
影响因子：
5.7
作者：
Fan, Yong;Batmanghelich, Nematollah;Davatzikos, Christos
通讯作者：
Davatzikos, Christos