Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience.

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Bipolar disorder is characterized by internally affective fluctuations. The abnormality of inherently mental state can be assessed using resting-state fMRI data without producing task-induced biases. In this study, we hypothesized that the resting-state connectivity related to the frontal, striatal, and thalamic regions, which were associated with mood regulations and cognitive functions, can be altered for bipolar disorder. We used the Pearson's correlation coefficients to estimate functional connectivity followed by the hierarchical modular analysis to categorize the resting-state functional regions of interest (ROIs). The selected functional connectivities associated with the striatal-thalamic circuit and default mode network (DMN) were compared between bipolar patients and healthy controls. Significantly decreased connectivity in the striatal-thalamic circuit and between the striatal regions and the middle and posterior cingulate cortex was observed in the bipolar patients. We also observed that the bipolar patients exhibited significantly increased connectivity between the thalamic regions and the parahippocampus. No significant changes of connectivity related to the frontal regions in the DMN were observed. The changed resting-state connectivity related to the striatal-thalamic circuit might be an inherent basis for the altered emotional and cognitive processing in the bipolar patients.

Sporadic Creutzfeldt-Jakob disease (sCJD) is the most common human prion disease. EEG is the method of choice to support the diagnosis of a human prion disease. Periodic sharp wave complexes (PSWCs) on the EEG usually indicate a progressive stage of CJD. However, PSWCs only become obvious at around 8 to 12 weeks after the onset of clinical symptoms, and in a few cases, even later. Independent component analysis (ICA) is a new technique to separate statistically independent components from a mixture of data. This study recruited seven patients who fit the criteria of CJD between 2002 and 2005 and 10 patients with Alzheimer's disease (AD) as control subjects. Using an ICA algorithm, we were able to split typical PSWCs into several independent temporal components in conjunction with spatial maps. The PSWCs were not observed in the initial EEG studies of patients with either AD or CJD. However, the ICA algorithm was able to extract periodic discharges and epileptiform discharges from raw EEG of patients with CJD at as early as 3 to 5 weeks after disease onset. Such discharges otherwise could hardly be discerned by visual inspection. In conclusion, ICA may increase the sensitivity of EEG and facilitate the early diagnosis of CJD.

Multiple system atrophy of the cerebellar type is a sporadic neurodegenerative disorder of the central nervous system. We hypothesized that the white matter degeneration of the cerebellum and pons in this disease may cause a breakdown of cerebellar structural networks and further reduce the network efficiency of cerebellar-connected cerebral regions. Diffusion tensor tractography was used to construct the structural networks of 19 cerebellar-type multiple system atrophy patients, who were compared with 19 age- and sex-matched controls. Graph theory was used to assess the small-world properties and topological organization of structure networks in both the control and patient groups. Our results showed that the cerebellar-type multiple system atrophy patients exhibited altered small-world architecture with significantly increased characteristic shortest path lengths and decreased clustering coefficients. We also found that white matter degeneration in the cerebellum was characterized by reductions in network strength (number and integrity of fiber connections) of the cerebellar regions, which further induced extensively decreased network efficiency for numerous cerebral regions. Finally, we found that the reductions in nodal efficiency of the cerebellar lobules and bilateral sensorimotor, prefrontal, and basal ganglia regions negatively correlated with the severity of ataxia for the cerebellar-type multiple system atrophy patients. This study demonstrates for the first time that the brains of cerebellar-type multiple system atrophy patients exhibit disrupted topological organization of white matter structural networks. Thus, this study provides structural evidence of the relationship between abnormalities of white matter integrity and network efficiency that occurs in cerebellar-type multiple system atrophy.