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Cereb Cortex. 2018 May 1;28(5):1771-1782. doi: 10.1093/cercor/bhx087.

Bayesian Mapping Reveals That Attention Boosts Neural Responses to Predicted and Unpredicted Stimuli.

Garrido MI1,2,3,4, Rowe EG1,2, Halász V1,2,3, Mattingley JB1,3,5.

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Queensland Brain Institute, The University of Queensland, 4072 Brisbane, Australia.
Centre for Advanced Imaging, The University of Queensland,  4072 Brisbane, Australia.
ARC Centre of Excellence for Integrative Brain Function, The University of Queensland, 4072 Brisbane, Australia.
School of Mathematics and Physics, The University of Queensland, 4072 Brisbane, Australia.
School of Psychology, The University of Queensland, 4072 Brisbane, Australia.


Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.


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