Elucidating how microscale molecular architecture shapes macroscale brain network organization requires integrative frameworks that link transcriptional profiles, structural connectivity, and functional dynamics across scales. However, existing evidence largely relies on cross-modal data acquired from different individuals, limiting causal and mechanistic inference. To overcome this, we performed concurrent awake optogenetic functional MRI (opto-fMRI) and spatial transcriptomics (opto-ST) within the same mice, enabling coupled analysis of neural activity and gene expression in fronto-thalamic and hippo-thalamic networks. Optogenetic stimulation of the medial prefrontal cortex (mPFC) or subiculum (SUB) evoked distinct thalamic BOLD response patterns. Multivariate spatial modeling revealed that energy metabolism and core biochemical processes underlie these GLM-derived activation patterns—a finding further supported by data-driven PCA, which identified enrichments in similar biological processes. These results suggest that conventional linear models predominantly capture linear gene–process relationships, highlighting the need for nonlinear computational approaches in fMRI analysis. Overall, our multi-omics framework reveals that genes regulating metabolic pathways underlie region-specific neurovascular coupling, thereby bridging local transcriptomics and large-scale functional imaging signatures. Bridging molecular to brain network organization is hindered by cross-individual data. Here, the authors show paired fMRI and spatial transcriptomics in awake mice via decoding that metabolic gene programs predict thalamic BOLD activation.
Zhang et al. (Sat,) studied this question.