Functional near infrared spectroscopy in novice and expert surgeons--a manifold embedding approach.
Monitoring expertise development in surgery is likely to benefit from evaluations of cortical brain function. Brain behaviour is dynamic and nonlinear. The aim of this paper is to evaluate the application of a nonlinear dimensionality reduction technique to enhance visualisation of multidimensional functional Near Infrared Spectroscopy (fNIRS) data. Manifold embedding is applied to prefrontal haemodynamic signals obtained during a surgical knot tying task from a group of 62 healthy subjects with varying surgical expertise. The proposed method makes no assumption about the functionality of the data set and is shown to be capable of recovering the intrinsic low dimensional structure of in vivo brain data. After manifold embedding, Earth Mover's Distance (EMD) is used to quantify different patterns of cortical behaviour associated with surgical expertise and analyse the degree of inter-hemispheric channel pair symmetry.
Royal Society/Wolfson Medical Image Computing Laboratory, Department of Biosurgery and Surgical Technology, Imperial College London, United Kingdom. d.leff@imperial.ac.uk
Daniel Richard
DR
Leff
Felipe
F
Orihuela-Espina
Louis
L
Atallah
Ara
A
Darzi
Guang-Zhong
GZ
Yang
D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D002540:Cerebral Cortex / Q000502:physiology*; D013502:General Surgery; D006801:Humans; D008297:Male; D009048:Motor Skills / Q000502:physiology*; D011361:Professional Competence; D013055:Spectrophotometry, Infrared / Q000379:methods*; D013647:Task Performance and Analysis