No abstract

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net.

An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.