Connectome-based prediction of functional impairment in experimental stroke models

Area of Science:

• Neuroscience
• Systems Neuroscience
• Computational Neuroscience

Background:

• Investigating cerebrovascular disease mechanisms requires understanding functional impairment in experimental stroke and hemorrhage models.
• The relationship between functional deficits and changes in neuronal population connectivity in rat brains remains unclear.

Purpose of the Study:

• To analyze how functional impairments in rat models of stroke and hemorrhage relate to brain connectivity changes.
• To develop a framework for predicting remote functional deficits based on brain network alterations.

Main Methods:

• Utilized middle cerebral artery occlusion and intracerebral hemorrhage models in rats.
• Assessed motor and spatial memory function, and hippocampal activation using Fos immunohistochemistry.
• Analyzed connectivity changes using network architecture metrics and dynamic brain modeling with the neuroVIISAS rat connectome.

Main Results:

• Functional impairment correlated with the extent and location of brain injury.
• Lesioned areas exhibited stronger coactivation with motor and spatial learning regions.
• Dynamic modeling predicted hippocampal hypoactivation and spatial memory deficits across all stroke types.

Conclusions:

• Brain injury location and extent significantly influence functional outcomes.
• Altered network dynamics predict remote functional impairments, particularly in the hippocampus.
• The study offers a framework for identifying and predicting stroke-induced remote functional deficits.