The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at , so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

The human left inferior parietal lobule (LIPL) plays a pivotal role in many cognitive functions and is an important node in the default mode network (DMN). Although many previous studies have proposed different parcellation schemes for the LIPL, the detailed functional organization of the LIPL and the exact correspondence between the DMN and LIPL subregions remain unclear. Mounting evidence indicates that spontaneous fluctuations in the brain are strongly associated with cognitive performance at the behavioral level. However, whether a consistent functional topographic organization of the LIPL during rest and under task can be revealed remains unknown. Here, they used resting-state functional connectivity (RSFC) and task-related coactivation patterns separately to parcellate the LIPL and identified seven subregions. Four subregions were located in the supramarginal gyrus (SMG) and three subregions were located in the angular gyrus (AG). The subregion-specific networks and functional characterization revealed that the four anterior subregions were found to be primarily involved in sensorimotor processing, movement imagination and inhibitory control, audition perception and speech processing, and social cognition, whereas the three posterior subregions were mainly involved in episodic memory, semantic processing, and spatial cognition. The results revealed a detailed functional organization of the LIPL and suggested that the LIPL is a functionally heterogeneous area. In addition, the present study demonstrated that the functional architecture of the LIPL during rest corresponds with that found in task processing. Hum Brain Mapp 38:1659-1675, 2017. © 2017 Wiley Periodicals, Inc.

The results of this multi-center study suggest that an abnormally thin left MTG could be involved in the pathogenesis of AVHs in schizophrenia.

In the dual-route language model, the dorsal pathway is known for sound-to-motor mapping, but the role of the ventral stream is controversial. With the goal of enhancing our understanding of language models, this study investigated the diffusion characteristics of candidate tracts in aphasic patients. We evaluated 14 subacute aphasic patients post-stroke and 11 healthy controls with language assessment and diffusion magnetic resonance imaging. Voxel-based lesion-symptom mapping found multiple linguistic associations for the ventral stream, while automated fiber quantification (AFQ) showed, via reduced fractional anisotropy (FA) and axial diffusivity with increased radial diffusivity (all corrected p < 0.05), that the integrity of both the left dorsal and ventral streams was compromised. The average diffusion metrics of each fascicle provided by AFQ also confirmed that voxels with significant FA-language correlations were located in the ventral tracts, including the left inferior fronto-occipital fascicle (IFOF) (comprehension: r = 0.839, p = 0.001; repetition: r = 0.845, p = 0.001; naming: r = 0.813, p = 0.002; aphasia quotient: r = 0.847, p = 0.001) and uncinate fascicle (naming: r = 0.948, p = 0.001). Furthermore, point-wise AFQ revealed that the segment of the left IFOF with the strongest correlations was its narrow stem. The temporal segment of the left inferior longitudinal fascicle was also found to correlate significantly with comprehension (r = 0.663, p = 0.03) and repetition (r = 0.742, p = 0.009). This preliminary study suggests that white matter integrity analysis of the ventral stream may have the potential to reveal aphasic severity and guide individualized rehabilitation. The left IFOF, specifically its narrow stem segment, associates with multiple aspects of language, indicating an important role in semantic processing and multimodal linguistic functions.

2 / 37 HIGHLIGHTS  DiffusionKit has a full pipeline for (pre-)processing and visualization of diffusion MRI data.  DiffusionKit has cross-platform support and a small installation size without 3rd party dependency.  DiffusionKit has both a GUI interface and command-line functions that enable easy operation and batch processing. Comparison with Existing Methods: DiffusionKit provides a full-function pipeline for dMRI data analysis, including data processing, modeling and visualization. Additionally, it provides both a graphical user interface (GUI) and command-line functions, which are helpful for batch processing. The standalone installation package has a small size and cross-platform support. AbstractConclusions: DiffusionKit provides a complete pipeline with cutting-edge methods for dMRI data analysis, including both a GUI interface and command-line functions. The rich functions for both data analysis and visualization will facilitate and benefit dMRI research.

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Feeding ecology of three small fish species, Hypseleotris swinhonis, Ctenogobius giurinus and Pseudorasbora parva was studied seasonally in the Biandantang Lake, a small, shallow lake in central China. Gut length, adjusted for total body length, was significantly higher in spring than in other seasons for all the three species. Seasonal changes in gut length were not associated with changes in food quality. Weight of fore-gut contents, adjusted for body weight, was significantly higher in winter and spring than in summer and autumn in H. swinhonis and C. giurinus, and significantly higher in autumn than in spring and summer for P. parva. Percentage of empty fore-guts was highest in summer and lowest in spring for H. swinhonis and C. giurinus, and highest in winter and lowest in autumn for P. parva. Diet of the three small fishes showed apparent seasonal changes, and these changes reflected partly the seasonal fluctuations of food resources in environment. Diet breadth was high in winter and low in autumn for H. swinhonis, high in winter and low in spring and summer for C. giurinus, and high in autumn and low in spring for P. parva. Diet overlaps between pairs of species were biologically significant in most cases, except between H. swinhonis and P. parva in summer and autumn and between C. giurinus and P. parva in autumn. 2000 The Fisheries Society of the British Isles

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.