Lacomba-Arnau Elena, Martínez-Molina Agustín, Garrido Luis Eduardo, Barrós-Loscertales Alfonso
Departament de Psicologia, Sociologia i Treball Social, Universitat de Lleida, Lleida, Spain.
Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
Biol Psychiatry Glob Open Sci. 2025 May 7;5(5):100526. doi: 10.1016/j.bpsgos.2025.100526. eCollection 2025 Sep.
The reinforcement sensitivity theory (RST) proposes 3 neurobiological systems that underlie individual differences in sensitivity to reward, punishment, and motivational conflicts. From a latent variable perspective, theoretical model structures can be identified based on empirical data. We applied exploratory and confirmatory factor analyses as well as structural equation modeling (SEM) with the aim of evaluating the RST neurobiological systems from biological phenotype indicators based on brain morphological organization.
We analyzed magnetic resonance imaging (MRI) data from 300 healthy adults (128 female, 172 male) using gray matter volumes extracted through the Neuromorphometrics atlas, targeting RST-related brain systems. To assess the underlying structure of RST neurobiological systems, we used principal component analysis, confirmatory factor analysis, exploratory factor analysis, and exploratory SEM, as well as its model hierarchy. All analyses were enhanced by advanced techniques such as parallel analysis and exploratory graph analysis.
The findings reveal a robust 4-factor model: the behavioral activation system, the combined behavioral inhibition and fight-flight-freeze system, and a dual constraint system with dorsal cortical stream and ventral cortical stream. The dorsal cortical stream exhibited significant integrative capacity, impacting the model hierarchy through top-down projections on all the other systems. Exploratory SEM provided the best fit to the MRI data, underscoring its suitability for summarizing neural substrate data.
This study provides insights into the neurobiological foundations of RST, proposing a structural brain topology that is consistent with the theoretical proposal and emerging empirical evidence in human research. The results support the integration of psychological constructs with biological phenotypes.
强化敏感性理论（RST）提出了3种神经生物学系统，这些系统是个体在对奖励、惩罚和动机冲突的敏感性方面存在差异的基础。从潜在变量的角度来看，可以根据实证数据确定理论模型结构。我们应用探索性和验证性因素分析以及结构方程模型（SEM），旨在基于脑形态组织的生物学表型指标评估RST神经生物学系统。
我们分析了300名健康成年人（128名女性，172名男性）的磁共振成像（MRI）数据，使用通过神经形态计量学图谱提取的灰质体积，以RST相关脑系统为目标。为了评估RST神经生物学系统的潜在结构，我们使用了主成分分析、验证性因素分析、探索性因素分析和探索性SEM及其模型层次结构。所有分析都通过并行分析和探索性图形分析等先进技术得到了加强。
研究结果揭示了一个稳健的四因素模型：行为激活系统、行为抑制与战斗-逃跑-冻结组合系统，以及一个具有背侧皮质流和腹侧皮质流的双重约束系统。背侧皮质流表现出显著的整合能力，通过对所有其他系统的自上而下投射影响模型层次结构。探索性SEM对MRI数据的拟合效果最佳，强调了其在总结神经基质数据方面的适用性。
本研究深入探讨了RST的神经生物学基础，提出了一种与理论提议以及人类研究中不断涌现的实证证据相一致的脑结构拓扑。结果支持将心理结构与生物学表型进行整合。
