Tricks for optimizing the information flow through your visual brain

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Our eyes capture way more information than our brains can possibly process. To reduce this information stream, the visual brain performs two tricks: it can either summarize the information, or it can single out a small piece of it. But how these two brain tricks “collaborate” was not known yet. In the Journal of Cognitive Science, Alessandro Grillini and co-authors show how the brain does this at the level of groups of neurons: attending in different ways changes the way the output of neurons in the primary visual cortex is combined, thereby varying the “built-in magnifying glass” through which you see. Combining signals of only a few neurons results in singling out information (but also costs more energy to process the information), whereas combining the signals of many neurons results in more summarizing (costing less energy for the brain to process, but also resulting in more crowding). Want to know more about this little known neural processing stage? Find the paper here.

This is what the brain tricks look like after making a mathematical model of them……


Two prominent strategies that the human visual system uses to reduce incoming information are spatial integration and selective attention. Whereas spatial integration summarizes and combines information over the visual field, selective attention can single it out for scrutiny. The way in which these well-known mechanisms-with rather opposing effects-interact remains largely unknown. To address this, we had observers perform a gaze-contingent search task that nudged them to deploy either spatial or feature-based attention to maximize performance. We found that, depending on the type of attention employed, visual spatial integration strength changed either in a strong and localized or a more modest and global manner compared with a baseline condition. Population code modeling revealed that a single mechanism can account for both observations: Attention acts beyond the neuronal encoding stage to tune the spatial integration weights of neural populations. Our study shows how attention and integration interact to optimize the information flow through the brain.