Abstract
Spatial navigation is an essential aspect of daily life that exhibits significant individual differences. The decline in spatial navigation is considered a critical early behavioral manifestation of various brain disorders, particularly Alzheimer's disease (AD). However, the biological and environmental origins of such differences remain poorly defined. In this study, we conducted a multi-scale review of the latest research on spatial navigation to explore the formation mechanisms of individual differences.
We summarized the multi-level individual differences in spatial navigation from a measurement perspective, including personal long-term experience or learning in real environments, virtual reality technology, and online games and big data. We then reviewed and discussed the formation mechanisms from both genetic and environmental factors. In terms of genetic factors, we found that the heritability of spatial ability was approximately 60%. Several candidate genes, including Bcl-2, S100B, and APOE and a few other genes, were proposed to affect spatial navigation behaviors. The mechanism of action studies gradually shifted from the biological perspective to the brain mechanism perspective. The hippocampus, retrosplenial cortex (RSC), and parahippocampal place area (PPA) were identified as important brain regions where genetic factors act on spatial navigation. However, the complete neurogenetic pathway model has not been established yet.
Regarding environmental exposure, cultural background, living environment, early life experience, navigation software use, and lifestyle were found to shape individuals' spatial navigation ability. However, the environmental associations were relatively superficial. Related studies mostly focused on the structure and function of the hippocampus, and further investigation of its mechanism of action, particularly the brain mechanism, is still lacking.
To overcome these limitations, we propose a gene/environment-brain-behavior model to map the links between genetic and environmental factors and individual differences in spatial navigation. Future research could be developed in three directions. Firstly, genome-wide association studies (GWAS) can be used to comprehensively reveal the key genetic variations influencing spatial navigation ability. Bioinformatics methods, such as polygenic score or polygenic risk score, genetic correlation, and enrichment analysis, can explore the key pathways of related genetic factors. Secondly, gene-environment interaction studies can reveal the complex pathways among genetics, environment, cognition, and behavior, and big data can help make it possible. Finally, brain imaging genetics research can correlate genetics, brain imaging, cognition, and behavior. Through international multicenter collaborations and cohort databases, spatial navigation-related imaging metrics can be correlated with multimodal genetic information to comprehensively reveal key genes and genetic mechanisms affecting brain networks of spatial navigation.
In conclusion, integrative analysis of multi-omics and clinical data would be promising for future studies concerning the complex pathways of spatial navigation. Results will help us understand the development patterns of spatial navigation and further explore the potential clinical applications relevant to brain diseases.
