Department of Psychology, Washington University, St. Louis, Missouri 63130, USA.
Biol Psychiatry. 2011 Jul 1;70(1):43-50. doi: 10.1016/j.biopsych.2011.02.010. Epub 2011 Apr 15.
A fundamental challenge for understanding neuropsychiatric disease is identifying sources of individual differences in psychopathology, especially when there is substantial heterogeneity of symptom expression, such as is found in schizophrenia (SCZ). We hypothesized that such heterogeneity might arise in part from consistently widespread yet variably patterned alterations in the connectivity of focal brain regions.
We used resting state functional connectivity magnetic resonance imaging to identify variable global dysconnectivity in 23 patients with DSM-IV SCZ relative to 22 age-, gender-, and parental socioeconomic status-matched control subjects with a novel global brain connectivity method that is robust to high variability across individuals. We examined cognitive functioning with a modified Sternberg task and subtests from the Wechsler Adult Intelligence Scale-Third Edition. We measured symptom severity with the Scale for Assessment of Positive and Negative Symptoms.
We identified a dorsolateral prefrontal cortex (PFC) region with global and highly variable dysconnectivity involving within-PFC underconnectivity and non-PFC overconnectivity in patients. Variability in this "under/over" pattern of dysconnectivity strongly predicted the severity of cognitive deficits (matrix reasoning IQ, verbal IQ, and working memory performance) as well as individual differences in every cardinal symptom domain of SCZ (poverty, reality distortion, and disorganization).
These results suggest that global dysconnectivity underlies dorsolateral PFC involvement in the neuropathology of SCZ. Furthermore, these results demonstrate the possibility that specific patterns of dysconnectivity with a given network hub region might explain individual differences in symptom presentation in SCZ. Critically, such findings might extend to other neuropathologies with diverse presentation.
理解神经精神疾病的一个基本挑战是确定精神病理学个体差异的来源,尤其是在存在大量症状表现异质性的情况下,例如在精神分裂症(SCZ)中。我们假设,这种异质性可能部分源于局灶性脑区连接的一致性广泛但模式可变的改变。
我们使用静息状态功能磁共振成像来识别 23 名 DSM-IV SCZ 患者相对于 22 名年龄、性别和父母社会经济地位匹配的对照者的可变全局去连接,使用一种新颖的全局脑连接方法,该方法对个体之间的高度变异性具有鲁棒性。我们使用改良的 Sternberg 任务和 Wechsler 成人智力量表第三版的子测试来检查认知功能。我们使用阳性和阴性症状评定量表来测量症状严重程度。
我们确定了一个背外侧前额叶皮层(PFC)区域,该区域存在全局和高度可变的去连接,涉及 PFC 内的连接不足和非 PFC 的连接过度。这种“不足/过度”去连接模式的变异性强烈预测了认知缺陷的严重程度(矩阵推理智商、言语智商和工作记忆表现)以及 SCZ 每个主要症状领域的个体差异(贫困、现实扭曲和紊乱)。
这些结果表明,全局去连接是 SCZ 背外侧 PFC 神经病理学的基础。此外,这些结果表明,具有给定网络枢纽区域的特定去连接模式可能解释了 SCZ 症状表现的个体差异。至关重要的是,这些发现可能扩展到具有不同表现的其他神经病理学。