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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Regional topography of auditory and visual attention: An fMRI-based meta-analysis
Juha Salmi1, Beatrice Aquilino2, Beyza Poçan3
1Unit of Psychology, Faculty of Education and Psychology, University of Oulu, P.O. Box 8000, Oulu FI-90014, Finland; Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 11000, Espoo FI-00076 AALTO, Finland; Department of Psychology, Faculty of Medicine, University of Helsinki, P.O. Box 21, Helsinki FI-00014, Finland.
None:
More than three decades of functional magnetic resonance imaging (fMRI) has gathered extensive evidence of auditory and visual attention effects in the human brain. However, a meta-analysis covering both modalities is lacking. The present activation likelihood estimation (ALE) based meta-analysis reports overlap and segregation of auditory vs. visual attention effects, further dividing those to effects of orienting vs. maintenance of attention, top-down controlled vs. bottom-up triggered attention, and attention to spatial vs. linguistic stimuli. Forty-three eligible auditory and 96 visual studies reporting a total of 1884 activation foci were found with PubMed and Scopus search. ALE meta-analysis revealed multimodal attention-related convergence zones with specific regional specialization in the dorsal and ventral parietal and frontal cortices and supplementary motor area / anterior cingulate cortex. Overall, visual attention was biased towards the dorsal attention network and auditory attention towards the ventral attention network. Midline posterior parietal cortex was associated with spatial attention in both modalities and language-related attention effects in the left inferior frontal and inferior temporal cortices were observed in the audition. In conclusion, the present study showcases the regional topography of attention effects in the brain, identifying brain areas dependent or independent of sensory modality, subprocess of attention, and type of stimulus. The proposed evidence-based multimodal model of attention can be used for interpreting future brain imaging findings as well as clinical observations.

