Sokunbi Moses O, Soula Oumayma, Ochieng Bertha, Staff Roger T
Faculty of Health and Life Sciences, De Montfort University, Leicester LE1 9BH, UK.
Faculty of Medicine of Sfax, University of Sfax, Sfax 3029, Tunisia.
Brain Sci. 2025 Jul 26;15(8):796. doi: 10.3390/brainsci15080796.
Autism spectrum disorder (ASD) is characterised by atypical behavioural and cognitive diversity, yet the neural underpinnings linking brain activity and individual presentations remain poorly understood. In this study, we investigated the relationship between resting-state functional magnetic resonance imaging (fMRI) signal complexity and intelligence (full-scale intelligence quotient (FIQ); verbal intelligence quotient (VIQ); and performance intelligence quotient (PIQ)) in male adults with ASD ( = 14) and matched neurotypical controls ( = 15). We used three complexity-based metrics: Hurst exponent (H), fuzzy approximate entropy (fApEn), and fuzzy sample entropy (fSampEn) to characterise resting-state fMRI signal dynamics, and correlated these measures with standardised intelligence scores. Using a whole-brain measure, ASD participants showed significant negative correlations between PIQ and both fApEn and fSampEn, suggesting that increased neural irregularity may relate to reduced cognitive-perceptual performance in autistic individuals. No significant associations between entropy (fApEn and fSampEn) and PIQ were found in the control group. Group differences in brain-behaviour associations were confirmed through formal interaction testing using Fisher's -to- transformation, which showed significantly stronger correlations in the ASD group. Complementary regression analyses with interaction terms further demonstrated that the entropy (fApEn and fSampEn) and PIQ relationship was significantly moderated by group, reinforcing evidence for autism-specific neural mechanisms underlying cognitive function. These findings provide insight into how cognitive functions in autism may not only reflect deficits but also an alternative neural strategy, suggesting that distinct temporal patterns may be associated with intelligence in ASD. These preliminary findings could inform clinical practice and influence health and social care policies, particularly in autism diagnosis and personalised support planning.
自闭症谱系障碍（ASD）的特征是行为和认知的非典型多样性，但将大脑活动与个体表现联系起来的神经基础仍知之甚少。在本研究中，我们调查了患有ASD的成年男性（n = 14）和匹配的神经典型对照组（n = 15）静息态功能磁共振成像（fMRI）信号复杂性与智力（全量表智商（FIQ）；言语智商（VIQ）；和操作智商（PIQ））之间的关系。我们使用了三种基于复杂性的指标：赫斯特指数（H）、模糊近似熵（fApEn）和模糊样本熵（fSampEn）来表征静息态fMRI信号动态，并将这些测量值与标准化智力分数相关联。使用全脑测量方法，ASD参与者的PIQ与fApEn和fSampEn均呈显著负相关，这表明神经不规则性增加可能与自闭症个体的认知感知能力下降有关。在对照组中未发现熵（fApEn和fSampEn）与PIQ之间存在显著关联。通过使用费舍尔z变换的形式交互测试证实了脑-行为关联的组间差异，结果显示ASD组的相关性显著更强。带有交互项的补充回归分析进一步表明，熵（fApEn和fSampEn）与PIQ之间的关系受到组的显著调节，这进一步证明了认知功能背后存在自闭症特异性神经机制。这些发现为自闭症的认知功能如何不仅反映缺陷，还反映一种替代神经策略提供了见解，表明不同的时间模式可能与ASD中的智力相关。这些初步发现可为临床实践提供参考，并影响健康和社会护理政策，特别是在自闭症诊断和个性化支持计划方面。
