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Machine Learning Approaches and Neuroimaging in Cognitive Functions of the Human Brain: A Review

  • Siamak AramEmail author
  • Denis Kornev
  • Roozbeh Sadeghian
  • Saeed Esmaili Sardari
  • Sagar Kora Venu
  • Hadis Dashtestani
  • Amir Gandjbakhche
Conference paper
  • 332 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1201)

Abstract

Brain science is that sphere of knowledge on the frontline of modern reality wherefrom the accuracy of diagnoses and speed of decision making depends on human mental health. Machine Learning and Deep Learning are the contemporary methodologies and algorithms that can combine a huge amount of complex data in the coherent structure and help scientists solve brain disorders. This paper reviews different Machine Learning algorithms that investigate data patterns and trends, collected from the human brain using several neuroimaging techniques.

Keywords

Functional near-infrared spectroscopy Deep Learning Cognitive functions Machine Learning Neuroimaging 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Siamak Aram
    • 1
    Email author
  • Denis Kornev
    • 1
  • Roozbeh Sadeghian
    • 1
  • Saeed Esmaili Sardari
    • 1
  • Sagar Kora Venu
    • 1
  • Hadis Dashtestani
    • 2
  • Amir Gandjbakhche
    • 2
  1. 1.Harrisburg University of Science and TechnologyHarrisburgUSA
  2. 2.Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesdaUSA

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