Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
Section of Psychiatry - Unit of Treatment Resistant Psychosis - Laboratory of Molecular and Translational Psychiatry - Department of Neuroscience, Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy.
Hum Brain Mapp. 2023 May;44(7):2829-2840. doi: 10.1002/hbm.26248. Epub 2023 Feb 28.
While verbal memory is among the most compromised cognitive domains in schizophrenia (SZ), its neural substrates remain elusive. Here, we explored the structural and functional brain network correlates of verbal memory impairment in SZ. We acquired diffusion and resting-state functional MRI data of 49 SZ patients, classified as having preserved (VMP, n = 22) or impaired (VMI, n = 26) verbal memory based on the List Learning task, and 55 healthy controls (HC). Structural and functional connectivity matrices were obtained and analyzed to assess associations with disease status (SZ vs. HC) and verbal memory impairment (VMI vs. VMP) using two complementary data-driven approaches: threshold-free network-based statistics (TFNBS) and hybrid connectivity independent component analysis (connICA). TFNBS showed altered connectivity in SZ patients compared with HC (p < .05, FWER-corrected), with distributed structural changes and functional reorganization centered around sensorimotor areas. Specifically, functional connectivity was reduced within the visual and somatomotor networks and increased between visual areas and associative and subcortical regions. Only a tiny cluster of increased functional connectivity between visual and bilateral parietal attention-related areas correlated with verbal memory dysfunction. Hybrid connICA identified four robust traits, representing fundamental patterns of joint structural-functional connectivity. One of these, mainly capturing the functional connectivity profile of the visual network, was significantly associated with SZ (HC vs. SZ: Cohen's d = .828, p < .0001) and verbal memory impairment (VMP vs. VMI: Cohen's d = -.805, p = .01). We suggest that aberrant connectivity of sensorimotor networks may be a key connectomic signature of SZ and a putative biomarker of SZ-related verbal memory impairment, in consistency with bottom-up models of cognitive disruption.
虽然言语记忆是精神分裂症（SZ）中受影响最严重的认知领域之一，但它的神经基础仍然难以捉摸。在这里，我们探索了言语记忆障碍在 SZ 中的结构和功能脑网络相关性。我们获得了 49 名 SZ 患者的弥散张量成像（DTI）和静息态功能磁共振成像（rs-fMRI）数据，根据列表学习任务将他们分为言语记忆保留（VMP，n=22）和言语记忆受损（VMI，n=26）。获得结构和功能连接矩阵，并使用两种互补的数据驱动方法（无阈值网络基于统计（TFNBS）和混合连接独立成分分析（connICA））分析与疾病状态（SZ 与 HC）和言语记忆障碍（VMI 与 VMP）的关联。TFNBS 显示与 HC 相比，SZ 患者的连接发生了改变（p<.05，FWER 校正），分布于感觉运动区的结构变化和功能重组。具体而言，视觉和躯体运动网络内的功能连接减少，视觉区域与联合和皮质下区域之间的功能连接增加。仅与言语记忆功能障碍相关的视觉区域和双侧顶叶注意力相关区域之间增加的功能连接存在一个微小的聚类。混合 connICA 确定了四个稳健的特征，代表联合结构-功能连接的基本模式。其中一个主要捕获视觉网络的功能连接模式，与 SZ 显著相关（HC 与 SZ：Cohen's d=0.828，p<.0001）和言语记忆障碍（VMP 与 VMI：Cohen's d=0.805，p=0.01）。我们认为，感觉运动网络的连接异常可能是 SZ 的关键连接组学特征，也是 SZ 相关言语记忆障碍的潜在生物标志物，与认知障碍的自下而上模型一致。
