| Issue |
EPJ Web Conf.
Volume 341, 2025
2nd International Conference on Advent Trends in Computational Intelligence and Communication Technologies (ICATCICT 2025)
|
|
|---|---|---|
| Article Number | 01016 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/epjconf/202534101016 | |
| Published online | 20 November 2025 | |
https://doi.org/10.1051/epjconf/202534101016
A Study on Brain Computing Interface
1 Phd Scholar, School of Computing Science and Engineering VIT Bhopal.
2 Senior Assistant Professor, School of Computing Science and Engineering VIT Bhopal.
3 Senior Associate Professor, School of Computing Science and Engineering, VIT Bhopal.
4 Programmer, IPS Academy, Institute of Engineering and Science, Indore.
5 Assistant Professor, IPS Academy, Institute of Engineering and Science, Indore.
Published online: 20 November 2025
Brain computing, or neuromorphic computing, is a revolutionary field inspired by the human brain's parallel processing and energy efficiency. Unlike traditional computers that separate memory and processing, brain-inspired systems integrate these functions, enabling faster, more efficient data handling.The core of this technology is the use of artificial neural networks (ANNs) and specialized neuromorphic hardware. ANNs mimic the brain's structure, while hardware like spiking neural networks (SNNs) and memristors physically replicate the brain's synaptic behavior. These systems excel at tasks like pattern recognition and machine learning, where adaptability is key. However, the field faces significant challenges. Developing scalable hardware that matches the brain's complexity and creating effective software to train these systems are major hurdles. Additionally, we need a deeper understanding of the brain's own computational principles to unlock the full potential of this technology.Despite these challenges, brain computing is poised to transform various sectors, including artificial intelligence, robotics, and healthcare, by creating a new generation of cognitive systems that can learn and reason in a more human-like way.
Key words: Brain Computing / EEG / Neuromorphic Computing / spiking neural networks / Electrocorticography
© The Authors, published by EDP Sciences, 2025
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