背景:精神病涉及思想内容的扭曲,这在一定程度上以异常的方式反映出来,即单词在语义上与语音中的话语联系在一起。我们试图探索这些语言异常是如何通过大脑语义网络中假定的电路级异常来实现的。
方法:使用计算大语言模型,来自变压器(BERT)的双向编码器表示,我们量化了180个样本中给定单词序列(困惑)的上下文期望度,这些样本是从首发精神分裂症(FES)患者和年龄匹配的对照对3张图片的描述中获得的,父母的社会地位,和性,用7T超高场功能磁共振成像(fMRI)扫描。随后,困惑被用来参数化一个频谱动态因果模型(DCM)的有效连通性内(内在)和(外在)4个关键区域之间的语义网络在休息,即颞叶,额下回(IFG),颞中后回(MTG),还有角回.
结果:我们包括60名参与者,包括30名FES患者和30名对照。我们在FES组中观察到更高的困惑,这表明通过先前的上下文,患者之间的言语是不可预测的。贝叶斯模型比较的结果表明,包括该组的DCM通过困惑相互作用最好地解释了神经活动的基本模式。我们观察到IFG内自我抑制有效连接的增加,以及pMTG内的自我抑制音调降低,在FES组。IFG中自我抑制音调的增加与IFG和后部MTG之间的区域间激发密切相关且呈正相关,而后部MTG的自我抑制与这种区域间激发呈负相关。
结论:我们的设计在有选择地激活语义网络的任务期间没有解决语义网络中的连接问题,这可以证实这项静息状态fMRI研究的发现。此外,我们没有进行复制研究,理想情况下使用不同语言的语音。
结论:作为对精神病中特殊言语的解释,这些结果指示了整个语义网络中调节信息流的兴奋-抑制性平衡的转变,仅限于以前与含义的执行控制特别相关的两个区域。基于我们将大型语言模型与因果连通性估计相结合的方法,我们认为语义控制的丧失是导致精神病混乱的潜在神经认知机制。
BACKGROUND: Psychosis involves a distortion of thought content, which is partly reflected in anomalous ways in which words are semantically connected into utterances in
speech. We sought to explore how these linguistic anomalies are realized through putative circuit-level abnormalities in the brain\'s semantic network.
METHODS: Using a computational large-language model, Bidirectional Encoder Representations from Transformers (BERT), we quantified the contextual expectedness of a given word sequence (perplexity) across 180 samples obtained from descriptions of 3 pictures by patients with first-episode schizophrenia (FES) and controls matched for age, parental social status, and sex, scanned with 7 T ultra-high field functional magnetic resonance imaging (fMRI). Subsequently, perplexity was used to parametrize a spectral dynamic causal model (DCM) of the effective connectivity within (intrinsic) and between (extrinsic) 4 key regions of the semantic network at rest, namely the anterior temporal lobe, the inferior frontal gyrus (IFG), the posterior middle temporal gyrus (MTG), and the angular gyrus.
RESULTS: We included 60 participants, including 30 patients with FES and 30 controls. We observed higher perplexity in the FES group, indicating that
speech was less predictable by the preceding context among patients. Results of Bayesian model comparisons showed that a DCM including the group by perplexity interaction best explained the underlying patterns of neural activity. We observed an increase of self-inhibitory effective connectivity within the IFG, as well as reduced self-inhibitory tone within the pMTG, in the FES group. An increase in self-inhibitory tone in the IFG correlated strongly and positively with inter-regional excitation between the IFG and posterior MTG, while self-inhibition of the posterior MTG was negatively correlated with this interregional excitation.
CONCLUSIONS: Our design did not address connectivity in the semantic network during tasks that selectively activated the semantic network, which could corroborate findings from this resting-state fMRI study. Furthermore, we do not present a replication study, which would ideally use
speech in a different language.
CONCLUSIONS: As an explanation for peculiar
speech in psychosis, these results index a shift in the excitatory-inhibitory balance regulating information flow across the semantic network, confined to 2 regions that were previously linked specifically to the executive control of meaning. Based on our approach of combining a large language model with causal connectivity estimates, we propose loss in semantic control as a potential neurocognitive mechanism contributing to disorganization in psychosis.