Research Progress and Clinical Application of Brain Disorders Based on Fusion Multimodal Imaging and Neurogenomics: Early Diagnosis, Neuromodulation and Machine Learning Vol II

Brain diseases are caused by lesions in the brain that lead to symptoms of corresponding neurological deficits. These diseases can be broadly classified into cerebrovascular diseases, inflammatory diseases, intracranial space-occupying lesions, hydrocephalus, cerebral parasitic diseases, extrapyramidal disorders, epilepsy, and cranial trauma. The study of brain diseases can involve the cross-fertilization of several disciplines, including genomics, molecular medicine, brain imaging, brain networks and machine learning. Advances in the sequencing technology helped us understand genetic alterations accurately, quickly, and cheaply, and gain a more fundamental and mechanistic understanding of brain disorders. In the meantime, multimodal imaging technology, a method of fusing image data from different imaging techniques (CT, MRI, PET, SPECT) to improve the accuracy and reliability of diagnostic imaging, provided a basis for the study of brain cognitive mechanisms and are also applied to assess structural and functional brain abnormalities in patients. Imaging technology and artificial intelligence allowed us to noninvasively visualize the brain structure, understand the brain network and strengthen the cognition of the brain. By exploring their mechanisms, the studies of brain disorders can provide potential novel biomarkers for diagnosis genuinely. They should be carried out from microscale to macroscale, from structure to function, from node to brain network.

Currently, diagnostic and therapeutic approaches to brain disorders are mainly derived from a number of relatively well-established randomised controlled trials and behavioural studies. But the understanding of their underlying mechanisms is not yet systematic or comprehensive, and lacks major breakthroughs. Hence, there is a need to further explore the underlying mechanisms of brain disorders by combining the above-mentioned approaches. Based on different perspectives and multidisciplinary intersections, we need a new understanding of brain diseases.

This Research Topic will focus on the potential mechanisms of brain diseases from the aspects of neurogenomics, signaling pathways, molecular mechanisms, using multimodal imaging genomics, neuromodulation and machine learning approaches, with a goal to provide new perspectives and approaches to study the underlying mechanisms and therapeutic targets of their pathogenesis, and closely integrates basic and clinical research to further enhance our understanding of brain diseases. We welcome contributions to the advances in the understanding of brain diseases and their related disorders in the respects of neurogenomics, multimodal imaging genomics, cell biology, signaling pathways, molecular mechanisms and neuromodulation. Besides traditional animal models and in vitro approaches, studies utilizing statistical and bioinformatics methods covering machine learning and other libraries and toolkits of algorithms based on histologic data are also welcome.

We welcome submissions of research and review articles on themes including but not limited to the following,

 Alteration of brain disorders and related conditions in molecular and cellular level.
 New perspectives on the diagnosis of brain diseases and related disorders.
 Functional neurocognition and diagnosis of brain diseases based on multimodal neurofunctional imaging.
 Multi-omics studies identifying pathogenic mechanisms and potential therapeutic targets for brain diseases and related disorders with mechanistic proofs
 Pathophysiological mechanisms of neurodegeneration in brain diseases and related disorders, with identified novel signaling pathways and molecular mechanisms.
 The etiology and pathogenesis of brain diseases uncovered using brain imaging techniques, to explore the link between structural and functional changes in early brain diseases, on pathophysiologic pathogenesis.
 New hypotheses or insights into the etiology or pathogenesis of brain diseases based on machine learning and other statistical methods, with proof from mechanistic study

Please note: studies consisting solely of bioinformatic investigation of publicly available genomic/transcriptomic/proteomic data do not fall within the scope of the section unless they are expanded and provide significant biological or mechanistic insight into the process being studied and will not be accepted as part of this Research Topic.