Visualizing neuroscience through AI: A systematic review

Sille, Roohi, Kapoor, Akshita, Choudhury, Tanupriya, Mahdi, Hussain Falih and Khurana, Madhu ORCID: 0000-0003-3976-1256 (2023) Visualizing neuroscience through AI: A systematic review. In: Exploring future opportunities of brain-inspired artificial intelligence. Advances in Computational Intelligence and Robotics (ACIR) . IGI Global, Hershey, PA, pp. 15-27. ISBN 9781668469804

Preview	Text (Published version) 12954 KHURANA Madhu (2023) Visualizing neuroscience through AI chapter.pdf - Published Version Available under License All Rights Reserved. Download (279kB) | Preview
Preview	Text (Published front material) 12954 KHURANA Madhu (2023) Visualizing neuroscience through AI front material.pdf - Published Version Available under License All Rights Reserved. Download (643kB) | Preview

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.

Item Type:	Book Section
Subjects:	Q Science > QA Mathematics > QA76 Computer software R Medicine > RC Internal medicine > RC321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Rhiannon Goodland
Date Deposited:	13 Sep 2023 08:30
Last Modified:	31 Oct 2023 13:03
URI:	https://eprints.glos.ac.uk/id/eprint/12954

University Staff: Request a correction | Repository Editors: Update this record