The human brain functional parcellation based on fMRI data

Abstract

The human brain is one of the most sophisticated and intelligent functional organization systems found by the human at present, and its complexity lies in: (i) Tens of thousands of neurons are interconnected by synapses to form the complex human brain structure, which is the material and physiological basis of the brain normal work. (ii) These neurons connected to each other exhibit complex and diverse brain activities by their interactions, such as visual information processing, logical reasoning and language expression and so on. More importantly after a long period of evolution, the human brain is highly intelligent, which makes that the human not only can adapt to the environment, but also can transform the world. This diversity and intelligence of the human brain function arouse great interest from researchers and have also been the most important contents in the study of the brain science. Last more than 20 years, nuclear magnetic imaging technologies have got rapid development on nuclear magnetic imaging technologies, such as electroencephalography, magneto encephalography and functional magnetic resonance imaging (fMRI), which greatly promote the development of the human brain function research. Especially, fMRI has the advantages of no invasiveness, high resolution and the simplicity and repeatability of the operation, and has brought a new development opportunity for the research of the human brain function. Recently, based on fMRI data, some computational methods have been used to divide the human brain functionally where the functional parcellation methods of the human brain divide full brain regions or local brain regions into disjoint subregions according to the functional consistency measurements, thus depicts the segmentation of the human brain function and plays a fundamental role in the study of the brain function. Studies have shown that the functional consistency of the subregions obtained by the human functional parcellation is higher than that of brain regions acquired in the human structural atlases. Namely, the human brain functional parcellation is more suitable for the functional analysis of the human brain. Further, the more real brain functional networks and the more interpretability results could be obtained by applying divided functional subregions, which can provide a new approach for the research and exploration of the human brain disease mechanisms. In this review, the principle of fMRI, the acquisition process and characteristics of fMRI data are first introduced, which can help researchers understand in depth fMRI data and associated calculation methods. On this basis, the general flow of the human brain functional parcellation is elaborated, where the human brain functional parcellation is a key step. And then, the paper gives a classification system of the human brain functional parcellation methods and discusses the major human brain functional parcellation algorithms and their characteristics in detail, which enables researchers to have a more systematic and in-depth understanding on the research field. To make an objective comparison, the similarity measures and evaluations commonly used in the human brain functional parcellation algorithms are listed and their characteristics are also outlined to guide the further study of the human brain functions. Next, the paper summarizes the application of the human brain functional parcellation at the aspects of the human brain functional network construction, a neurological disease research and the state forecast of subjects. Finally, the challenging problems and future research directions are deeply analyzed from the perspective of both scientific and technical issues. This work is hopefully beneficial to the researchers engaged in the human brain function research.