Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity-based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work.

For decades, it has been largely unknown to what extent multiple functional networks spatially overlap/interact with each other and jointly realize the total cortical function. Here, by developing novel sparse representation of whole-brain fMRI signals and by using the recently publicly released large-scale Human Connectome Project high-quality fMRI data, we show that a number of reproducible and robust functional networks, including both task-evoked and resting state networks, are simultaneously distributed in distant neuroanatomic areas and substantially spatially overlapping with each other, thus forming an initial collection of holistic atlases of functional networks and interactions (HAFNIs). More interestingly, the HAFNIs revealed two distinct patterns of highly overlapped regions and highly specialized regions and exhibited that these two patterns of areas are reciprocally localized, revealing a novel organizational principle of cortical function.

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Convoluted cortical folding and neuronal wiring are 2 prominent attributes of the mammalian brain. However, the macroscale intrinsic relationship between these 2 general cross-species attributes, as well as the underlying principles that sculpt the architecture of the cerebral cortex, remains unclear. Here, we show that the axonal fibers connected to gyri are significantly denser than those connected to sulci. In human, chimpanzee, and macaque brains, a dominant fraction of axonal fibers were found to be connected to the gyri. This finding has been replicated in a range of mammalian brains via diffusion tensor imaging and high-angular resolution diffusion imaging. These results may have shed some lights on fundamental mechanisms for development and organization of the cerebral cortex, suggesting that axonal pushing is a mechanism of cortical folding.

Functional connectomes have been recently shown to be powerful in characterizing brain conditions. However, many previous studies assumed temporal stationarity of functional connectomes, while their temporal dynamics are rarely explored. Here, based on the structural connectomes constructed from diffusion tensor imaging (DTI) data, functional connectomes are derived from resting-state fMRI (R-fMRI) data and are then temporally divided into quasi-stable segments via a sliding time window approach. After integrating and pooling over a large number of those temporally quasi-stable functional connectome segments from 44 post-traumatic stress disorder (PTSD) patients and 51 healthy controls, common functional connectome (CFC) patterns are derived via effective dictionary learning and sparse coding algorithms. It is found that there are 16 CFC patterns that are reproducible across healthy controls, and interestingly, two additional CFC patterns with altered connectivity patterns (termed signature functional connectome (SFC) here) exist dominantly in PTSD subjects. These two SFC patterns alone can successfully differentiate 80% of PTSD subjects from healthy controls with only 2% false positive. Furthermore, the temporal transition dynamics of CFC patterns in PTSD subjects are substantially different from those in healthy controls. These results have been replicated in separate testing datasets, suggesting that dynamic functional connectomics signatures can effectively characterize and differentiate PTSD patients.