Combining MRI and VEP imaging to isolate the temporal response of visual cortical areas

The human brain has well over 30 cortical areas devoted to visual processing. Classical neuro-anatomical as well as fMRI studies have demonstrated that early visual areas have a retinotopic organization whereby adjacent locations in visual space are represented in adjacent areas of cortex within a visual area. At the 2006 Electronic Imaging meeting we presented a method using sprite graphics to obtain high resolution retinotopic visual evoked potential responses using multi-focal m-sequence technology (mfVEP). We have used this method to record mfVEPs from up to 192 non overlapping checkerboard stimulus patches scaled such that each patch activates about 12 mm2 of cortex in area V1 and even less in V2. This dense coverage enables us to incorporate cortical folding constraints, given by anatomical MRI and fMRI results from the same subject, to isolate the V1 and V2 temporal responses. Moreover, the method offers a simple means of validating the accuracy of the extracted V1 and V2 time functions by comparing the results between left and right hemispheres that have unique folding patterns and are processed independently. Previous VEP studies have been contradictory as to which area responds first to visual stimuli. This new method accurately separates the signals from the two areas and demonstrates that both respond with essentially the same latency. A new method is introduced which describes better ways to isolate cortical areas using an empirically determined forward model. The method includes a novel steady state mfVEP and complex SVD techniques. In addition, this evolving technology is put to use examining how stimulus attributes differentially impact the response in different cortical areas, in particular how fast nonlinear contrast processing occurs. This question is examined using both state triggered kernel estimation (STKE) and m-sequence "conditioned kernels". The analysis indicates different contrast gain control processes in areas V1 and V2. Finally we show that our m-sequence multi-focal stimuli have advantages for integrating EEG and MEG for improved dipole localization.