Automated cortical projection of head-surface locations for transcranial functional brain mapping

• Published in: NeuroImage (Orlando, Fla.) Vol. 26; no. 1; pp. 18 - 28
• Main Authors: Okamoto, Masako, Dan, Ippeita
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.05.2005; Elsevier Limited
• Subjects: Adult; Algorithms; Automation; Brain Mapping - methods; Cerebral Cortex - physiology; Electromagnetic Fields; Female; Heart attacks; Human brain mapping; Humans; Image Interpretation, Computer-Assisted; International 10-20 system; Magnetic Resonance Imaging; Male; Medical imaging; Methods; Middle Aged; Models, Statistical; Near-infrared spectroscopy; Neural Pathways - anatomy & histology; Neural Pathways - physiology; NMR; Nuclear magnetic resonance; Optical topography; Positron-Emission Tomography; Probabilistic anatomical platform; Reproducibility of Results; Spatial registration; Spectroscopy, Near-Infrared; Transcranial magnetic stimulation; Transcranial magnetic stimulation; Human brain mapping; International 10-20 system; Spatial registration; Optical topography; Probabilistic anatomical platform; Near-infrared spectroscopy
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2005.01.018

Recent advancements in two noninvasive transcranial neuroimaging techniques, near-infrared spectroscopy (NIRS) and transcranial magnetic stimulation (TMS), signify the increasing importance of establishing structural compatibility between transcranial methods and conventional tomographic methods, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). The transcranial data obtained from the head surface should be projected onto the cortical surface to present the transcranial brain-mapping data on the same platform as tomographic methods. Thus, we developed two transcranial projection algorithms that project given head-surface points onto the cortical surface in structural images, and computer programs based on them. The convex-hull algorithm features geometric handling of the cortical surface, while the balloon-inflation algorithm is faster, and better reflects the local cortical structure. The automatic cortical projection methods proved to be as effective as the manual projection method described in our previous study. These methods achieved perfect correspondence between any given point on the head surface or a related nearby point in space, and its cortical projection point. Moreover, we developed a neighbor-reference method that enables transcranial cortical projection of a given head-surface point in reference to three neighboring points and one additional standard point, even when no structural image of the subject is available. We also calculated an error factor associated with these probabilistic estimations. The current study presents a close topological link between transcranial and tomographic brain-mapping modalities, which could contribute to inter-modal data standardization.