Title :
Combining tomographic single subject, single trial activity into time-dependent grand-summaries of activated areas and functional connectivity
Author :
Ioannides, Andreas A.
Author_Institution :
Lab. for Human Brain Dynamics, Brain Sci. Inst., Saitama, Japan
Abstract :
Standard statistical analysis and mutual information are employed to summarize the millisecond-by-millisecond single subject, single trial tomographic estimates of brain activity extracted from biomagnetic signals. The first approach (MFT-SPM) characterizes the spatial profile of significant activations at a particular latency in peristimulus time. The second grand-summary provide a time- and lag-dependent inventory of pair-wise interactions between brain areas. The analysis of median nerve stimulation data is used as an example to demonstrate the advantages and limitations of the grand summaries. Expected but also somewhat surprising, and hence easy to overlook, patterns emerge in the left and right hemisphere activations of each subject. These patterns dominate the grand-average summaries across subjects, leading to established results but also new insights. Finally, the amazing spatiotemporal accuracy achievable in MFT tomographic estimates of activity provides a warning that much and potentially valuable information is lost in the average and grand-average summaries.
Keywords :
biomedical MRI; information theory; magnetoencephalography; probability; statistical analysis; tomography; MFT-SPM; biomagnetic signals; brain activity; brain areas; functional connectivity; lag-dependent inventory; magnetic field tomography; median nerve stimulation data; mutual information; pair-wise interactions; peristimulus time; spatial profile; spatiotemporal accuracy; standard statistical analysis; time-dependent grand-summaries; time-dependent inventory; tomographic single subject single trial; Brain; Current density; Electroencephalography; Image reconstruction; Magnetic field measurement; Magnetic heads; Magnetic sensors; Scalp; Sensor systems; Tomography;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1202204