More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states.
Just because an area is slightly more active on the right side of the brain in a given task does not mean that the task is a "right brain" task.
Wolf is the right-brain person, dreaming up recipe ideas, while Mary oversees the left-brain tasks, navigating Oregon's complicated regulatory requirements.
We used T2 images for the whole-brain task because this is most heavily relied upon for brain tumour detection.
This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals.
Stimuli for the whole-brain task consisted of 60 T2 brain MRI images from one patient with a right medial temporal lobe intrinsic tumour (see Fig. 1 for example slices).
The first was a whole-brain task, which consisted of 60 consecutively presented slices from one patient; the second was an independent-slice detection task, which consisted of 32 independent slices from five different patients.
A limitation of the whole-brain task was that each slice was presented for a fixed 1500-ms duration which does not reflect clinical practice in which clinicians can scroll freely through the image in any direction at their desired speed.
In the whole-brain task, eye-gaze data was recorded while participants sequentially viewed 60 slices of a patient's brain MRI and in the independent-slice task, both eye-gaze data and performance measures were recorded when participants inspected 32 brain MRIs (16 tumorous; 16 healthy).
The whole-brain task revealed that scanning patterns were more similar for Run 1 than Run 2. One interpretation is that scanning patterns in Run 1 were largely driven by saliency which supports models of visual saliency whereby fast and primitive bottom-up processes bias the observer towards the most salient stimuli in the early stages of exposure (Parkhurst, Law, & Niebur, 2002).
