Developing and Validating a Novel, Culture-Fair Assessment of Fluid Intelligence: A Multimodal Approach Combining Neuroimaging and Behavioral Measures in Indonesia

Abstract

Introduction: Fluid intelligence (Gf) is a critical cognitive ability, but its assessment is often biased by cultural and educational factors. Existing Gf tests developed in Western contexts may not be valid in diverse populations like Indonesia. This study aimed to develop and validate a novel, culture-fair Gf assessment tool (the "Indonesian Fluid Intelligence Scale" - IFIS) for Indonesian adults, utilizing a multimodal approach combining behavioral testing with neuroimaging (fMRI and EEG).

Methods: A mixed-methods design was employed. Phase 1 involved the development of the IFIS, drawing on culturally relevant materials and minimizing reliance on language and formal education. Phase 2 involved a cross-sectional study with 300 Indonesian adults (aged 18-45) with varying educational backgrounds and socioeconomic statuses, recruited from urban and rural areas. Participants completed the IFIS, a standardized Gf test (Raven's Progressive Matrices - RPM), and underwent fMRI and EEG recordings during cognitive task performance. Statistical analyses included correlational analyses, confirmatory factor analysis (CFA), and machine learning techniques to explore the relationship between IFIS scores, RPM scores, and neural activity patterns.

Results: The IFIS demonstrated good internal consistency (Cronbach's alpha = 0.85) and test-retest reliability (r = 0.88). CFA supported a single-factor structure for the IFIS. IFIS scores correlated significantly with RPM scores (r = 0.68, p < 0.001), but showed weaker correlations with years of education (r = 0.35, p < 0.001) compared to RPM (r = 0.52, p < 0.001). fMRI revealed that higher IFIS scores were associated with increased activation in the frontoparietal network (FPN), particularly the dorsolateral prefrontal cortex (dlPFC) and posterior parietal cortex (PPC), during task performance. EEG analysis showed increased theta and alpha power in frontal and parietal regions during IFIS task performance, correlating with higher scores. Machine learning models, using combined fMRI and EEG data, could predict IFIS scores with high accuracy (AUC = 0.89).

Conclusion: The IFIS provides a promising, culture-fair assessment of Gf in Indonesian adults. The multimodal approach, combining behavioral and neuroimaging data, provides strong evidence for the construct validity of the IFIS. The findings highlight the importance of considering cultural context in cognitive assessment and demonstrate the potential of neuroimaging to validate cognitive measures.