Before the onset of motor symptoms, Parkinson’s disease (PD) involves dysfunction of the anterior olfactory nucleus and olfactory bulb, causing olfactory disturbance, commonly resulting in hyposmia in the early stages of PD. Accumulating evidence has shown that blood oxygen level dependent (BOLD) signals in white matter are altered by olfactory disorders and related stimuli, and the signal changes in brain white matter pathways show a certain degree of specificity, which can reflect changes of early olfactory dysfunction in Parkinson’s disease. In this study, we apply the functional covariance connectivity (FCC) method to decode FCC of gray and white matter in olfactory-related brain regions in Parkinson’s disease. Our results show that the dorsolateral prefrontal, anterior entorhinal cortex and fronto-orbital cortices in the gray matter have abnormal connectivity with the posterior corona radiata and superior corona radiata in white matter in patients with Parkinson’s hyposmia. The functional covariance connection strength (FCS) of the right dorsolateral prefrontal cortex and white matter, and the covariance connection strength of the left superior corona radiata and gray matter function have potential diagnostic value. These results demonstrate that alterations in FCC of gray and white matter in olfactory-related brain regions can reflect the change of olfactory function in the early stages of Parkinson’s disease, indicating that it could be a potential neuroimaging marker for early diagnosis.
ObjectivesRehabilitation, aerobic exercise, and many traditional Chinese exercises are known to significantly improve balance in patients with Parkinson’s disease. Baduanjin, a traditional physical and mental exercise, has long been practiced for health care as it regulates organs, the nervous and motor systems.MethodsWe recruited 31 eligible participants. Patients underwent a 3-week Baduanjin program, including 35-min exercise daily. Scores on the Modified Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Non-motor Symptoms Scale (NMSS), and gait and balance tests were compared before and after the Baduanjin program.ResultsMDS-UPDRS-total (t = 4.669, P ≤ 0.001), MDS-UPDRS part-I (t = 5.805, P ≤ 0.001), MDS-UPDRS part-II (t = 5.234, P ≤ 0.001), MDS-UPDRS part-III (t = 3.274, P = 0.003), and NMSS (t = 4.815, P ≤ 0.001) scores significantly decreased after the 3-week intervention. Gait parameters like step (t = 2.289, P = 0.030) and cycle (t = 2.181, P = 0.038) durations also significantly improved, while Balance-check® indicators, including the total score (t = −2.147, P = 0.041) and grade (t = 3.432, P = 0.002) significantly differed before and after exercise.ConclusionBaduanjin exercise shows beneficial effects for non-motor symptoms, balance, gait, and daily activities in patients with Parkinson’s disease. Baduanjin can be included in the patients’ family exercise, which is conducive to their rehabilitation, as well as for obtaining important social and economic benefits.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [ChiCTR-IPR-17011875].
IntroductionApathy is a prevalent mood disturbance that occurs in a wide range of populations, including those with normal cognitive aging, mental disorders, neurodegenerative disorders and traumatic brain injuries. Recently, neuroimaging technologies have been employed to elucidate the neural substrates underlying brain disorders accompanying apathy. However, the consistent neural correlates of apathy across normal aging and brain disorders are still unclear.MethodsThis paper first provides a brief review of the neural mechanism of apathy in healthy elderly individuals, those with mental disorders, neurodegenerative disorders, and traumatic brain injuries. Further, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, the structural and functional neuroimaging meta-analysis using activation likelihood estimation method is performed on the apathy group with brain disorders and the healthy elderly, aiming at exploring the neural correlates of apathy.ResultsThe structural neuroimaging meta-analysis showed that gray matter atrophy is associated with apathy in the bilateral precentral gyrus (BA 13/6), bilateral insula (BA 47), bilateral medial frontal gyrus (BA 11), bilateral inferior frontal gyrus, left caudate (putamen) and right anterior cingulate, while the functional neuroimaging meta-analysis suggested that the functional connectivity in putamen and lateral globus pallidus is correlated with apathy.DiscussionThrough the neuroimaging meta-analysis, this study has identified the potential neural locations of apathy in terms of brain structure and function, which may offer valuable pathophysiological insights for developing more effective therapeutic interventions for affected patients.
Many studies reported that spontaneous fluctuation of the blood oxygen level-dependent signal exists in multiple frequency components and changes over time. By assuming a reliable energy contrast between low- and high-frequency bands for each voxel, we developed a novel spectrum contrast mapping (SCM) method to decode brain activity at the voxel-wise level and further validated it in designed experiments. SCM consists of the following steps: first, the time course of each given voxel is subjected to fast Fourier transformation; the corresponding spectrum is divided into low- and high-frequency bands by given reference frequency points; then, the spectral energy ratio of the low- to high-frequency bands is calculated for each given voxel. Finally, the activity decoding map is formed by the aforementioned energy contrast values of each voxel. Our experimental results demonstrate that the SCM (1) was able to characterize the energy contrast of task-related brain regions; (2) could decode brain activity at rest, as validated by the eyes-closed and eyes-open resting-state experiments; (3) was verified with test-retest validation, indicating excellent reliability with most coefficients > 0.9 across the test sessions; and (4) could locate the aberrant energy contrast regions which might reveal the brain pathology of brain diseases, such as Parkinson’s disease. In summary, we demonstrated that the reliable energy contrast feature was a useful biomarker in characterizing brain states, and the corresponding SCM showed excellent brain activity-decoding performance at the individual and group levels, implying its potentially broad application in neuroscience, neuroimaging, and brain diseases.
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