Abstract
BACKGROUND: Apathy is a prevalent psychiatric condition after stroke, affecting approximately 30% of stroke survivors. It is associated with slower recovery and an increased risk of depression. Understanding the pathophysiological mechanisms of post stroke apathy (PSA) is crucial for developing targeted rehabilitation strategies. METHODS: In this study, we recruited a total of 18 PSA patients, 18 post-stroke non-apathy (NPSA) patients, and 18 healthy controls (HCs). Apathy was measured using the Apathy Evaluation Scale (AES). Resting-state functional magnetic resonance imaging (rs-fMRI) was utilized to investigate spontaneous brain activity. We estimated the amplitude of low-frequency fluctuation (ALFF) across three different frequency bands (typical band: 0.01-0.08 Hz; slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz) and the fractional amplitude of low-frequency fluctuation (fALFF). RESULTS: Band-specific ALFF differences among the three groups were analyzed. Significant differences were found in the typical band within the left lingual gyrus, right fusiform gyrus, right superior temporal gyrus (STG), and left insula. In the slow-4 band, significant differences were observed in the left middle frontal gyrus (MFG) and right STG. In the slow-5 band, significant differences were identified in the left calcarine cortex and right insula. For fALFF values, significant differences were found in the left lingual gyrus and right thalamus. Moreover, positive correlations were observed between AES scores and the ALFF values in the right STG (r = 0.490, p = 0.002) in the typical band, left MFG (r = 0.478, p = 0.003) and right STG (r = 0.451, p = 0.006) in the slow-4 band, and fALFF values of the right thalamus (r = 0.614, p < 0.001). CONCLUSION: This study is the first to investigate the neural correlates of PSA using voxel-level analysis and different ALFF banding methods. Our findings indicate that PSA involves cortical and subcortical areas, including the left MFG, right STG, and right thalamus. These results may help elucidate the neural mechanisms underlying PSA and could serve as potential neuroimaging indicators for early diagnosis and intervention.