Quantifying Changes in Brain Function Following Injury via Network Measures.

Area of Science:

• Neuroscience
• Systems Neuroscience
• Computational Neuroscience

Background:

• Widefield optical imaging allows for large-scale, longitudinal monitoring of cerebral cortex activity in awake, behaving animals.
• Understanding how brain networks reorganize after injury is crucial for developing effective treatments.
• Previous studies have explored network alterations, but a comprehensive measure of information flow changes post-injury is needed.

Purpose of the Study:

• To investigate alterations in the brain's functional network structure following injury using widefield optical imaging.
• To quantify changes in information flow within cortical networks after inducing an injury.
• To assess the potential of network analysis for tracking injury-induced changes and recovery.

Main Methods:

• Cortical activity was recorded in transgenic mice expressing GCaMP6s using widefield optical imaging during pre- and post-injury sessions.
• The "communicability" metric was employed to quantitatively assess information flow within the functional brain networks.
• Spectral clustering was applied to communicability networks to differentiate between pre- and post-injury states.

Main Results:

• Significant alterations in functional network structure were observed after injury compared to control subjects.
• Specific network links contributing to altered connectivity post-injury were spatially localized.
• Spectral clustering effectively distinguished between pre- and post-injury network states.

Conclusions:

• The study demonstrates that brain injury significantly alters large-scale cortical network structure and information flow.
• Communicability analysis combined with spectral clustering provides an effective method for tracking injury-related network changes.
• This approach holds promise for monitoring brain network dynamics during recovery and informing therapeutic strategies.