Measuring the Frequency-Specific Functional Connectivity Using Wavelet Coherence Analysis in Stroke Rats Based on...

Area of Science:

• Neuroscience
• Biomedical Optics
• Systems Biology

Background:

• Optical intrinsic signal imaging (OISi) is used to assess cortical functional connectivity (FC) in animal models.
• Previous OISi studies measured FC separately in time or frequency domains, limited to frequencies below 0.08 Hz, missing faster hemodynamic oscillations.
• Existing methods cannot simultaneously track the time and frequency dependency of FC, limiting comprehensive analysis of fast cortical events.

Purpose of the Study:

• To evaluate cerebral response changes in stroke rats using wavelet coherence (WC) transform of OISi time series.
• To measure functional connectivity (FC) at higher frequencies (up to 4.5 Hz) and simultaneously monitor its time and frequency dependency.
• To assess the efficacy of OISi-based WC analysis in diagnosing stroke severity and infarct size.

Main Methods:

• Optical intrinsic signal imaging (OISi) was employed to acquire cortical activity data in a rat stroke model.
• Wavelet coherence (WC) transform was applied to the OISi time series to analyze functional connectivity.
• Statistical analyses were performed to compare signal amplitude, responsive area size, correlation, and WC between stroke and healthy hemispheres.

Main Results:

• Wavelet coherence (WC) of the brain significantly diminished in the ischemic motor and somatosensory cortices of stroke rats.
• Signal amplitude, responsive area size, correlation, and WC were significantly lower in the stroke hemisphere compared to the healthy hemisphere.
• The study demonstrated simultaneous monitoring of time and frequency dependency of FC up to 4.5 Hz.

Conclusions:

• OISi-based WC analysis is an efficient method for evaluating functional connectivity changes in the brain after stroke.
• This technique allows for the diagnosis of the relative severity of infarction and the size of the infarcted region.
• The findings highlight the utility of WC transform in OISi for a more comprehensive understanding of cortical dynamics in neurological injury.