The study of human brain atlas can be dated back to the early of the 20th century. At the initial stage, researchers made endless efforts to map the brain and anatomically partition it into areas based on cytoarchitectonic information. The recent human Brainnetome Atlas is a novel type of atlas that, unlike the ordinary ones, provides connectivity-based parcellation, with a specific focus on brain connectivity architecture. The unprecedented connectivity-based thought fills the gap in old-fashioned brain mapping.
Only by constantly improving the fineness and accuracy of brain atlas, can we make good use of it to identify biomarkers for mental disorders.
However, the journey of Brainnetome Atlas is far from over. There are still much more to do before we can finally apply it for therapies like transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS). What is more, only by constantly improving the fineness and accuracy of brain atlas, can we make good use of it to identify biomarkers for mental disorders.
In this respect, magnetic resonance imaging (MRI) – the technology that existed before the atlas – has been in a dilemma for a long time. Although having been available for more than three decades and still rapidly developing, MRI has not been adopted for clinical diagnosis criteria for brain disorders, particularly mental disorders. This could be due to limited disease data and poor accuracy of brain atlases.
Harnessing the brain atlas
To put the atlas into use, we propose three important directions for future studies on the human Brainnetome Atlas. The first one is about identifying the biomarkers for early diagnosis, prognosis, and therapeutic efficacy evaluation in different mental disorders based on more sophisticated atlases. The second direction is to confirm the matching of different areas in the atlas to functional circuits of cognition such as emotion and memory and to generate brain functional atlases at different scales. Another direction involves the use of the language- or cognition-related brain atlas in computational modeling in brain-inspired artificial intelligence (AI) studies.
There is tremendous amount of research that can be done on the link between brain atlas and the above-mentioned brain-inspired AI computing, which will be a research hotspot in the future. Although AI is a touted concept nowadays, challenges are everywhere including limited options of techniques for AI computation. Revealing how human brain processes information may largely facilitate the development of AI computation. For instance, it has been found that, when the human brain is processing information, the high-order interactions between neurons are characterized by the second-order interactions. It is important to uncover the false mask of the so-called high order. That will largely simplify AI computation and systemic structure design.
Our next plan is to establish nonhuman primate brain atlases at three different levels. First, we will create a similar macroscopic atlas of macaque monkey brain as that of the human brain by parcellating its brain into different areas based on macrostructural features. Based on the macroscopic atlas, we will apply classical neural tract tracing technique and the new viral tracing methods to further create the connectivity atlas at the level of the neuronal populations (or different types of neurons). This is a major issue of importance to be addressed in the next 5 to 10 years.
As for the fineness, it is far superior to the purely MRI-dependent method. To delineate a microscopic atlas is our ultimate goal, although hardly achievable, as currently there is no better technique available in this field other than the electron microscopy.
The establishment of nonhuman primate brain atlas using invasive tracing techniques, which are inapplicable in human beings, would advance our understanding of the atlas of human brain. In addition, comparing nonhuman primate and human atlases at the macroscale may provide some hints on the similarity and difference between the two species during evolution at the brain functional connectivity level.