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Abstract:
Electroencephalography (EEG) is a non-invasive neuroimaging tool which can be used to measure brain activity with excellent temporal resolution. By solving the so-called ‘inverse problem’, one can not only study the time-course of activation during a particular task, but also identify the location of the underlying neural sources in the brain. Usually, these methods are applied to averaged data obtained from EEG recordings during which volunteers perform a given, usually brief (0.1-5s) task over many dozens repetitions. This averaging across many brief trials results in clearer responses, as artifactual or randomly occurring events (noise, eye blinks, eye wanderings, etc) will be reduced. Here, we take a radically new approach, and ask whether one can obtain reliable source localization associated to a particular stimulus feature (such as visual contrast) when using complex natural stimuli presented over long periods of time. We made EEG recordings (64 channels) in 7 subjects who passively watched 2 minute long segments from different commercially available movies (the segments were repeated 20 times). We then developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc. Source localization of this artifact-free data was calculated at each time point of the movie using low resolution electromagnetic tomography (LORETA). We then calculated the correlation coefficient between variations in the EEG source strength in over 6000 voxels within the brain with variations in movie contrast. As expected, we found that visual contrast in the movie mapped specifically to voxels within area V1, thus showing that a feature that varies continuously in its strength can be reliably mapped onto the cortical region involved in its processing. These findings open a new approach to mapping brain function with a high temporal resolution and allow the localization of a multitude of brain areas based on a single experiment using uncontrolled, natural stimuli.
