Post-stroke depression is a serious complication of stroke that significantly restricts rehabilitation. The use of immersive virtual reality for stroke survivors is promising. Herein, we investigated the effects of a novel immersive virtual reality training system on PSD and explored induced effective connectivity alterations in emotional networks using multivariate Granger causality analysis. Forty-four patients with PSD were equally allocated into an immersive-virtual reality group and a control group. In addition to their usual rehabilitation treatments, the participants in the immersive-virtual reality (...) group participated in an immersive-virtual reality rehabilitation program, while the patients in the control group received 2D virtual reality rehabilitation training. The Hamilton Depression Rating Scale, modified Barthel Index, and resting-state functional magnetic resonance imaging data were collected before and after a 4-week intervention. rsfMRI data were analyzed using multivariate GCA. We found that the immersive virtual reality training was more effective in improving depression in patients with PSD but had no statistically significant improvement in MBI scores compared to the control group. The GCA showed that the following causal connectivities were strengthened after immersive virtual reality training: from the amygdala, insula, middle temporal gyrus, and caudate nucleus to the dorsolateral prefrontal cortex; from the insula to the medial prefrontal cortex; and from the thalamus to the posterior superior temporal sulcus. These causal connectivities were weakened after treatment in the control group. Our results indicated the neurotherapeutic use of immersive virtual reality rehabilitation as an effective non-pharmacological intervention for PSD; the alteration of causal connectivity in emotional networks might constitute the neural mechanisms underlying immersive-virtual reality rehabilitation in PSD. (shrink)

BackgroundThe cognitive level of post-stroke aphasia patients is generally lower than non-aphasia patients, and cognitive impairment affects the outcome of stroke. However, for different types of PSA, what kind of cognitive assessment methods to choose is not completely clear. We investigated the Montreal Cognitive Assessment, the Mini-Mental State Examination, and the Non-language-based Cognitive Assessment to observe the evaluation effect of CI in patients with fluent aphasia and non-fluent aphasia.Methods92 stroke patients were included in this study. Demographic and clinical data of (...) the stroke group were documented. The language and cognition were evaluated by Western Aphasia Battery, MoCA, MMSE, and NLCA. PSA were divided into FA and NFA according to the Chinese aphasia fluency characteristic scale. Pearson’s product–moment correlation coefficient test and multiple linear regression analysis were performed to explore the relationship between the sub-items of WAB and cognitive scores. The classification rate of CI was tested by Pearson’s Chi-square test or Fisher’s exact test.ResultsThe scores of aphasia quotient, MoCA, MMSE, and NLCA in NFA were lower than FA. AQ was positively correlated with MoCA, MMSE, and NLCA scores. Stepwise multiple linear regression analysis suggested that naming explained 70.7% of variance of MoCA and 79.9% of variance of MMSE; comprehension explained 46.7% of variance of NLCA. In the same type of PSA, there was no significant difference in the classification rate. The classification rate of CI in NFA by MoCA and MMSE was higher than that in FA. There was no significant difference in the classification rate of CI between FA and NFA by NLCA.ConclusionMoCA, MMSE, and NLCA can be applied in FA. NLCA is recommended for NFA. (shrink)