The effects of sex and age on movie-watching functional connectivity and movie clip classification

• Published in: Brain Structure and Function Vol. 230; no. 6; p. 116
• Main Authors: Yang, Chengxiao, Biswal, Bharat B., Wang, Pan
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 09.07.2025; Springer Nature B.V
• Subjects: Adult; Age; Age Factors; Biomedical and Life Sciences; Biomedicine; Brain; Brain - diagnostic imaging; Brain - physiology; Cell Biology; Connectome; Datasets; External stimuli; Female; Females; Functional magnetic resonance imaging; Humans; Influence; Investigations; Magnetic Resonance Imaging; Male; Motion Pictures; Nerve Net - diagnostic imaging; Nerve Net - physiology; Neural networks; Neural Pathways - diagnostic imaging; Neural Pathways - physiology; Neuroimaging; Neurology; Neurosciences; Original; Original Article; Photic Stimulation; Sex; Sex Characteristics; Sex Factors; Sparsity; Support Vector Machine; Young Adult; Functional connectivity; Average cross-session correlation; Movie watching; Support vector machine; Demographic effect
• ISSN: 1863-2661; 1863-2653; 1863-2661; 0340-2061
• DOI: 10.1007/s00429-025-02962-0

Functional connectivity (FC) is a key tool for understanding the complex interactions within the human brain, highlighting connections between various regions. This study delves into the multifaceted influences shaping functional magnetic resonance imaging FC patterns during movie watching, focusing on the effects of sex, age, and movie clip. Leveraging the Human Connectome Project dataset, we systematically examine FC patterns elicited during movie watching. Notably, sex-specific variations in FC are observed, with females exhibiting heightened FC within visual, limbic, and default mode networks, while males display predominant intra-network connectivity within somatomotor and attention networks. Age-related variations further manifest, revealing FC increases with age in early adulthood (21–35 years old) within some specific networks. Moreover, our investigation unveils the profound influence of movie clips on FC patterns, with significant interactions observed between clips, sex, and age. Feature selection using the Average Cross-Session Correlation method highlights FC as distinct fingerprints of clips, and the Support Vector Machine classifier shows high accuracy (Accuracy > 0.9) when using these features. Our findings underscore the importance of considering individual demographic factors and external stimuli in understanding neural connectivity dynamics during movie-watching, with implications for both basic neuroscience research and clinical neuroimaging applications.