ABSTRACT
Objective To explore the feature of functional connectivity of default mode network (DMN) and salience network (SN) in unmedicated schizophrenia patients during a resting state by functional magnetic resonance imaging (fM-RI). Methods The SPM8 and DPARSFA softwares combined with independent component analysis (ICA) were used to in-vestigate functional connectivity (FC) of the DMN and SN in 27 unmedicated patients with schizophrenia and 27 age-and gender-matched healthy controls. Results Concerning the DMN, patients with schizophrenia showed decreased FC in right inferior frontal gyrus , right precuneus(unadjusted P<0.05)and increased FC in right middle cingulate gyrus, left middle frontal gyrus(unadjusted P<0.05). With regard to the SN, patients showed reduced connectivity in left inferior frontal gyrus, right inferior frontal gyrus, left anterior cingulate, left postcentral gyrus(unadjusted P<0.05)and increased connectivity in left superior temporal gyrus(unadjusted P<0.05). Correlation analyses showed that the increased FC of left superior temporal gyrus significantly correlated with PANSS-positive symptoms(r=0.568,P=0.002)and decreased FC of right precuneus significantly negatively correlated with delusion symptom(r=-0.458,P=0.016). Conclusion This study provides evidence for resting state functional abnormalities of DMN and SN in unmedicated schizophrenia patients. These aberrant function connectivities in some brain regions of the two networks could be a source of abnormal introspectively-oriented mental actives.
ABSTRACT
Objective To detect the recruitment pattern of motor unit in human flexor digitorum superficialis (FDS) at different force levels produced by the index finger. Methods Eight subjects were recruited to produce a certain force level with the index finger to match the ordered force level (20%, 40%, 60% maximum voluntary contraction). During the force tracking task, the multi-channel surface electromyography (sEMG) signals were recorded on FDS using 8×1 (row×column) electrode-array. The motor unit action potential (MUAP) information was extracted by Fast Independent Component Analysis (FastICA), and then the correlation between MUAP pattern and force level was analyzed. Results Four different types of MUAP were extracted successfully by FastICA from original sEMG signals and the total number of MUAP showed an increasing trend with the force level increasing. At different force levels, the proportion of different types of MUAP was different, showing different trends with change of the force level. ConclusionsAt different levels of the finger force, the recruitment pattern of motor unit in FDS will be changed so as to produce the force accordingly.
ABSTRACT
Objective To explore fMRI data with independent component analysis (ICA) in order to investigate effects of transcutaneous electrical acupoint stimulation (TEAS) on brain function. Methods The experiment was performed on a whole-body 1.5 T GE Signa Excite MRI scanner with which the brain oxygenation level dependent (BOLD)/EPI images were acquired from a female traumatic brain injury patient. A block designed protocol was used. Both durations of rest and TEAS were 30 seconds. The data processing was performed with GIFT, Statistical Parametric Mapping 5 (SPM5) and MRIcro. Results from ICA and SPM were compared. Results Extended Infomax algorithm provided by GIFT found thirteen independent components (ICs), each of which contained a spatial map and a corresponding time course. The spatial maps associated with task-related ICs resembled the activation maps from SPM5 but were not totally identical. In addition, the time courses of these ICs differed from the shape of canonical HRF model used by SPM. Conclusion ICA is a good choice to investigate data and obtain prior knowledge before using model-based methods such as SPM.