Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis
Joshua J Strohl1, Joseph Carrión1, Patricio T Huerta2,3,4
1Laboratory of Immune and Neural Networks, Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
Scientific Reports
|November 12, 2024
Summary
Behavioral task-associated PET (beta-PET) measures brain networks. This novel technique identifies threat memory networks and predicts defense responses, even when disrupted by sepsis in mice.
Area of Science:
- Neuroscience
- Medical Imaging
Background:
- Positron emission tomography (PET) with [18F]fluorodeoxyglucose (FDG) measures brain activity.
- Behavioral tasks during PET scans link brain activity to specific functions.
Purpose of the Study:
- Introduce behavioral task-associated PET (beta-PET) for studying threat memory.
- Investigate the neural basis of contextual threat memory and its disruption in sepsis.
Main Methods:
- Developed beta-PET using two scans: one post-familiarization, one post-threat recall.
- Applied beta-PET to a mouse model of long sepsis to analyze threat memory networks.
- Utilized machine learning for data analysis and prediction of behavioral responses.
Main Results:
- Beta-PET identified a distinct network for contextual threat memory.
- Observed uncoupling of this network in the sepsis model.
- Demonstrated beta-PET's ability to predict defense responses and their sepsis-induced breakdown.
Conclusions:
- Beta-PET is a viable method for mapping task-related brain networks, specifically for threat memory.
- Sepsis disrupts contextual threat memory networks, impacting defense behaviors.
- Beta-PET offers a predictive tool for assessing behavioral and neural changes in disease models.
