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Published in Chapter:
Visualizing Neuroscience Through AI: A Systematic Review
Roohi Sille (University of Petroleum and Energy Studies, India),
Akshita Kapoor (University of Petroleum and Energy Studies, India), Tanupriya Choudhury (University of Petroleum and Energy Studies, India),
Hussain Falih Mahdi (University of Diyala, Iraq), and
Madhu Khurana (University of Gloucestershire, UK)
Copyright: © 2023
|Pages: 13
DOI: 10.4018/978-1-6684-6980-4.ch002
Abstract
The field of neuroscience explains how the neural networks in the brain work together to perform a variety of tasks, including pattern recognition, relative memory, object recognition, and more. The mental activity that makes different jobs possible is difficult to understand. Understanding the various patterns present in natural neural networks requires a combination of artificial intelligence and neuroscience, which requires less computation. As a result, it is possible to understand a large number of brain reactions in relation to the activity that each person is engaged in. Human brain neurons need to be trained by experience in order to perform activities like moving the hands, arms, and legs while also considering how to respond to each activity. In the past 10 years, artificial intelligence (AI), with its potential to uncover patterns in vast, complex data sets, has made amazing strides, in part by emulating how the brain does particular computations. This chapter reviews the replication of neuroscience via AI in a real-time scenario.