Search

Abstract: Analysis of resting-state functional magnetic resonance imaging (fMRI) data is based on detecting low-frequency signal fluctuations in functionally connected brain areas. These synchronous fluctuations in resting-state networks have been observed in several studies with healthy subjects. In this study, we explored if independent component analysis (ICA) can be used to localize the sensorimotor area from resting-state fMRI data in patients with brain tumors. Finger-tapping activation task and resting-state blood-oxygenation-level-dependent fMRI data were acquired from 8 patients with brain tumors and 10 healthy volunteers. Sensorimotor task independent components (ICtask) were used to verify resting-state independent components (ICrest) individually. In addition, sensorimotor ICrests were compared between the groups and no significant differences were detected in volume, spatial correlation or temporal correlation. These results show that it is possible to localize a sensorimotor area from resting-state data using ICA in patients with brain tumors. This offers a complementary method for assessing the sensorimotor area in subjects with brain tumors who have difficulties in performing motor paradigms. [Copyright &y& Elsevier]

Abstract: Parkinson''s disease (PD) is a common neurological disorder. Recently, bilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become an option in the treatment of severe PD. We measured the health-related quality of life (HRQoL) of 27 parkinsonian patients, who underwent a bilateral STN-operation. The instruments used for the evaluation of the HRQoL were the Parkinson''s Disease Questionnaire (PDQ-39) and the Finnish version of the Nottingham Health Profile (NHP). We found that the quality of life significantly improved when measured with both HRQoL scales. Clinical improvement and improvement in HRQoL were positively correlated. [Copyright &y& Elsevier]