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Real‐time multiple linear regression for fMRI supported by time‐aware acquisition and processing
Author(s) -
Smyser Christopher,
Grabowski Thomas J.,
Frank Randall J.,
Haller John W.,
Bolinger Lizann
Publication year - 2001
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/1522-2594(200102)45:2<289::aid-mrm1038>3.0.co;2-u
Subject(s) - computer science , parametric statistics , artificial intelligence , disk formatting , data mining , data acquisition , pattern recognition (psychology) , machine learning , real time computing , statistics , mathematics , operating system
Real‐time parametric statistical analysis of functional MRI (fMRI) data would potentially enlarge the scope of experimentation and facilitate its application to clinical populations. A system is described that addresses the need for rapid analysis of fMRI data and lays the foundation for dealing with problems that impede the application of fMRI to clinical populations. The system, I/OWA (Input/Output time‐aWare Architecture), combines a general architecture for sampling and time‐stamping relevant information channels in fMRI (image acquisition, stimulation, subject responses, cardiac and respiratory monitors, etc.) and an efficient approach to manipulating these data, featuring incremental subsecond multiple linear regression. The advantages of the system are the simplification of event timing and efficient and unified data formatting. Substantial parametric analysis can be performed and displayed in real‐time. Immediate (replay) and delayed off‐line analysis can also be performed with the same interface. The capabilities of the system are demonstrated in normal subjects using a polar visual angle phase mapping paradigm. The system provides a time‐accounting infrastructure that readily supports standard and innovative approaches to fMRI. Magn Reson Med 45:289–298, 2001. © 2001 Wiley‐Liss, Inc.