Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis

Positron emission tomography (PET) is a highly sensitive tool for studying physiology and metabolism through positron-emitting radionuclides that label molecular targets in the body with unparalleled specificity, without disturbing their biological function. Here, we introduce a small-animal technique called behavioral task-associated PET (beta-PET) consisting of two scans: the first after a mouse is familiarized with a conditioning chamber, and the second upon recall of contextual threat. Associative threat conditioning occurs between the scans. Beta-PET focuses on brain regions encoding threat memory (e.g., amygdala, prefrontal cortex) and contextual aspects (e.g., hippocampus, subiculum, entorhinal cortex). Our results show that beta-PET identifies a biologically defined functional network encoding contextual threat memory and its uncoupling in a mouse model of long sepsis. Moreover, machine learning algorithms (linear logistic regression) and ordinal trends analysis demonstrate that beta-PET robustly predicts the behavioral defense response and its breakdown during long sepsis.