Brain Informatics Technology

3Future Directions and Challenges in Brain Informatics

Kriti Sankhla

Department of Computer Science and Engineering, Poornima University, Jaipur, India

Abstract

Brain informatics is the headline among the rest of the things that brain science is reaching by fusing neuroscience, data science, and synthetic intelligence. Coming on the way, it opens opportunities as well as challenges that may be influencing the course of its future. This chapter expounds on the coming directions and trials in brain informatics, alongside global overview of the improvements and barriers that will characterize the coming stages of adding new methods and tools to support the research and applications.

The chapter introduces the integration of multi-modal brain data, which is a highly critical part of Brain Informatics. One of the traditional but inaccurate methods is relying on a single data source like a functional MRI (fMRI) or electroencephalogram (EEG). However, the category from which advantages of such data are to be drawn should be capable of integrating all types of data, from imaging and electrophysiological signals to genetic data and behavioral data, to create a more comprehensive picture of brain functioning and disorders. The chapter deliberates on the breakthroughs in data fusion and the machine-learning methods aiming to increase the precision and scope of brain data analysis.

Another core point in computational neuroscience is expanding its boundaries. The ability of advanced computing ...