Role of Artificial Intelligence in Neuroimaging for Cognitive Research

Title

Role of Artificial Intelligence in Neuroimaging for Cognitive Research

Creator

Malviya M.; Joseph A.; Chandra J.; Pooja V.

Description

Artificial intelligence (AI)-based solutions are used in most of our daily activities. AI has been adapted and it has found various applications. Cognitive research is one area where AI has been applied to understand the hidden patterns in the data. Neuroimaging techniques investigate the neural basis of cognitive processes like perception, attention, memory, language, reasoning, decision-making, and problem-solving. The irregularities in the cognitive process lead to cognitive disabilities and diseases. Neuroimaging techniques, including magnetic resonance imaging (MRI), functional MRI (fMRI), electroencephalography (EEG), and positron emission tomography (PET), along with other data-gathering techniques, are studied to identify cognitive disorders. The imaging techniques generate large amounts of complex data. AI methods, including machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision, are applied and used to analyse and interpret the data generated by various imagining techniques. Numerous techniques have been designed, developed, and proposed to handle the neuroimaging data for cognitive research with the help of AI techniques. AI techniques include ML algorithms like decision trees, random forest, support vector machine (SVM), principal component analysis (PCA), and DL algorithms, including convolution neural networks (CNNs), long short-term memory (LSTM), and generative adversarial networks (GANs). Recent advancements in the field of neuroimages use AI techniques to preprocess, process, and analyse the data generated by various neuroimaging modalities. This chapter provides an in-depth analysis and summary of various AI techniques for processing neuroimages for cognitive disorders. 2024 selection and editorial matter, Anitha S. Pillai and Bindu Menon; individual chapters, the contributors.

Source

Machine Learning and Deep Learning in Neuroimaging Data Analysis, pp. 91-108.

Date

2024-01-01

Publisher

CRC Press

Coverage

Malviya M., Christ University, Bangalore, India; Joseph A., Christ University, Pune, India; Chandra J., Christ University, Bangalore, India; Pooja V., Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-100381554-9; 978-103219068-6

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1201/9781003264767-6

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195914752&doi=10.1201%2f9781003264767-6&partnerID=40&md5=68237c2fcc2487fe35b19a5c00ee1aee