The ERICA Toolbox for Event Related Independent Component Analysis
This toolbox performs Event-related independent component analysis [1], which:
• Is useful for event-related fMRI when the neuronal and/or haemodynamic response to events (the “fMRI response”) is not known a priori
• Assumes only that the peri-event fMRI time-course is similar for each event
• Requires fMRI time-series input data along with event timing
• Otherwise makes no assumptions about neuronal or hemodynamic response
• Step 1: At each voxel, estimate the fMRI response associated with the events of interest
• Step 2: Perform a spatial ICA on the resultant 4D spatio-temporal response map
• Results in a series of spatial maps and associated peri-event time-series
• Can detect neuronal responses even if they precede the events (e.g. anticipatory effects)
• Can detect subnetworks with different peri-event time-courses [2]
[1] DOI: 10.1016/j.neuroimage.2012.12.025
[2] DOI: 10.1111/epi.12163
• Is useful for event-related fMRI when the neuronal and/or haemodynamic response to events (the “fMRI response”) is not known a priori
• Assumes only that the peri-event fMRI time-course is similar for each event
• Requires fMRI time-series input data along with event timing
• Otherwise makes no assumptions about neuronal or hemodynamic response
• Step 1: At each voxel, estimate the fMRI response associated with the events of interest
• Step 2: Perform a spatial ICA on the resultant 4D spatio-temporal response map
• Results in a series of spatial maps and associated peri-event time-series
• Can detect neuronal responses even if they precede the events (e.g. anticipatory effects)
• Can detect subnetworks with different peri-event time-courses [2]
[1] DOI: 10.1016/j.neuroimage.2012.12.025
[2] DOI: 10.1111/epi.12163
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erica: ERICA version 2.0beta01 release
ERICA_v2.0beta01.zip posted by David Abbott on Jun 12, 2019