Imbalance of neural oscillations in cognitive related brain regions after ischemic stroke and its relationship with cognitive dysfunction

The Shanhai Medical Neurolog system is used for signal acquisition, with a sampling rate set to 30000 Hz and a duration of 3 minutes per acquisition. Before applying electrical stimulation, first collect a 3-minute baseline signal. During the stimulation process, due to current interference, LFP signals are often contaminated by high amplitude artifacts, making it difficult to effectively extract the true neural activity. To ensure the physiological authenticity and reliability of signal analysis, this study adopts a delayed signal analysis strategy, which means waiting for 3-5 seconds after the end of stimulation, waiting for the high amplitude artifacts caused by electrical stimulation to disappear, and then collecting LFP signals for 3 minutes for subsequent analysis. In addition, this study also set up a group of healthy rats receiving the same pattern of electrical stimulation to evaluate the basal effects of the stimulation regimen in non stroke brains. The collection time points for electrophysiological data include: the 6th day after electrode implantation in a healthy state, the 1st day after MCAO stroke modeling, and the 1st, 7th, and 14th days before and after stimulation intervention. Electrophysiological data analysis: The raw LFP recorded data is saved in a binary format file and analyzed accordingly in MATLAB, as well as converted to a. mat file. Then, the LFP data is bandpass filtered and clustered into typical frequency bands, （theta，4-10 Hz; beta，10-30 Hz; slow gamma，30-55 Hz; fast gamma，55-100 Hz）。 The attenuation in the stopband is set to 80 dB, and the allowed ripple amount in the passband is 1 dB. The frequency difference between the beginning of the first stopband and the beginning of the first passband, as well as the frequency difference between the beginning of the second passband and the beginning of the second stopband, are both 0.5 Hz. For all collected LFP signals, further power spectral density (PSD) analysis, time-frequency plot drawing, and power statistical analysis of each frequency band are carried out. Functional connectivity analysis of brain regions: In order to determine functional connectivity, neural coupling between two brain regions was analyzed for cross-correlation in MATLAB. The instantaneous amplitudes of LFP recorded by mPFC and HPC were considered as two discrete time series x (n) and y (n), respectively. Calculate Coeff using the xcorr function in MATLAB