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BackgroundThe migrainous aura has different clinical phenotypes. While the various clinical differences are well-described, little is known about their neurophysiological underpinnings. To elucidate the latter, we compared white matter fiber bundles and gray matter cortical thickness between healthy controls (HC), patients with pure visual auras (MA) and patients with complex neurological auras (MA+).Methods3T MRI data were collected between attacks from 20 patients with MA and 15 with MA+, and compared with those from 19 HCs. We analyzed white matter fiber bundles using tract-based spatial statistics (TBSS) of diffusion tensor imaging (DTI) and cortical thickness with surface-based morphometry of structural MRI data.ResultsTract-based spatial statistics showed no significant difference in diffusivity maps between the three subject groups. As compared to HCs, both MA and MA+ patients had significant cortical thinning in temporal, frontal, insular, postcentral, primary and associative visual areas. In the MA group, the right high-level visual-information-processing areas, including lingual gyrus, and the Rolandic operculum were thicker than in HCs, while in the MA+ group they were thinner.DiscussionThese findings show that migraine with aura is associated with cortical thinning in multiple cortical areas and that the clinical heterogeneity of the aura is reflected by opposite thickness changes in high-level visual-information-processing, sensorimotor and language areas.

Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals’ ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex, and Occipital Place Area (OPA) using Dynamic Causal Modelling for resting-state functional magnetic resonance data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire. We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

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