Since the origins of Neuroscience, the development of new techniques for cell visualization, such as the Golgi method, has contributed to revealing the beauty of the central nervous system. Recently, an explosion of new imaging methods to reveal brain structure and function from cellular to organ system levels has emerged. However, recent advances in imaging techniques have not been paralleled by the necessary development of robust analytical tools, restricting the outcome of Neuroscience research. Nevertheless, the development of new techniques in the field of artificial intelligence (machine learning) has opened new possibilities for the automatization of the acquisition and analysis of images, classification of data, and interpretation of results. The adequate combination of both new high-quality imaging technologies, and new classification and advanced data analysis tools will favor rapid growth of current knowledge.
Finally, this knowledge will serve to generate new models of brain organization and function. Hence, neuroscience imaging emerges nowadays as a multidisciplinary field with more potential than ever to unravel the secrets of the brain. Thus, this is a perfect moment to review the evolution of this field, renew old methods, and implement new techniques that allow us to capture the essence of the mind.
The aim of this Research Topic is to discuss the advantages and pitfalls of old and new imaging methods, and associated analytical tools, that are used to explore the structure and function of the brain from the molecular/cellular level, to the whole brain connectome level, in both pre-clinical and clinical settings.
All manuscripts must contain a critical analysis of addressed imaging methodology or analysis tools, highlighting key contributions and achievements in Neuroscience and indicate the author’s perspective for future developments.
Original Research, review papers, methods, perspective, conceptual analysis, brief research report, general commentary, opinion, and technology and Code manuscripts focused on the following topics are welcome:
• Renewed and innovative imaging-related molecular and cellular imaging techniques in neuroscience (fluorescence microscopy, live-imaging, super-resolution, light sheet imaging, and others);
• Genetic engineering for brain imaging, including new methods for connectomics;
• Pre-clinical and clinical brain imaging; including non-human and human brain structural and functional analysis;
• Image analysis tools (stereology, Sholl analysis, segmentation, deconvolution, machine-learning based acquisition or analysis, etc.).
Since the origins of Neuroscience, the development of new techniques for cell visualization, such as the Golgi method, has contributed to revealing the beauty of the central nervous system. Recently, an explosion of new imaging methods to reveal brain structure and function from cellular to organ system levels has emerged. However, recent advances in imaging techniques have not been paralleled by the necessary development of robust analytical tools, restricting the outcome of Neuroscience research. Nevertheless, the development of new techniques in the field of artificial intelligence (machine learning) has opened new possibilities for the automatization of the acquisition and analysis of images, classification of data, and interpretation of results. The adequate combination of both new high-quality imaging technologies, and new classification and advanced data analysis tools will favor rapid growth of current knowledge.
Finally, this knowledge will serve to generate new models of brain organization and function. Hence, neuroscience imaging emerges nowadays as a multidisciplinary field with more potential than ever to unravel the secrets of the brain. Thus, this is a perfect moment to review the evolution of this field, renew old methods, and implement new techniques that allow us to capture the essence of the mind.
The aim of this Research Topic is to discuss the advantages and pitfalls of old and new imaging methods, and associated analytical tools, that are used to explore the structure and function of the brain from the molecular/cellular level, to the whole brain connectome level, in both pre-clinical and clinical settings.
All manuscripts must contain a critical analysis of addressed imaging methodology or analysis tools, highlighting key contributions and achievements in Neuroscience and indicate the author’s perspective for future developments.
Original Research, review papers, methods, perspective, conceptual analysis, brief research report, general commentary, opinion, and technology and Code manuscripts focused on the following topics are welcome:
• Renewed and innovative imaging-related molecular and cellular imaging techniques in neuroscience (fluorescence microscopy, live-imaging, super-resolution, light sheet imaging, and others);
• Genetic engineering for brain imaging, including new methods for connectomics;
• Pre-clinical and clinical brain imaging; including non-human and human brain structural and functional analysis;
• Image analysis tools (stereology, Sholl analysis, segmentation, deconvolution, machine-learning based acquisition or analysis, etc.).
