The Brain Can Plan Actions Toward Things the Eye Doesnâ€™t See

Main Category: Psychology / Psychiatry
Article Date: 24 Jun 2013 â€“ 0:00 PDT

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People can plan strategic movements to several different targets at the same time, even when they see far fewer targets than are actually present, according to a new study published in Psychological Science, a journal of the Association for Psychological Science.

A team of researchers at the Brain and Mind Institute at the University of Western Ontario took advantage of a pictorial illusion â€“ known as the â€œconnectedness illusionâ€ â€“ that causes people to underestimate the number of targets they see.

When people act on these targets, however, they can rapidly plan accurate and strategic reaches that reflect the actual number of targets.

Using sophisticated statistical techniques to analyze participantsâ€™ responses to multiple potential targets, the researchers found that participantsâ€™ reaches to the targets were unaffected by the presence of the connecting lines.

Thus, the â€œconnectedness illusionâ€ seemed to influence the number of targets they perceived but did not impact their ability to plan actions related to the targets.

These findings indicate that the processes in the brain that plan visually guided actions are distinct from those that allow us to perceive the world.

â€œThe design of the experiments allowed us to separate these two processes, even though they normally unfold at the same time,â€ explained lead researcher Jennifer Milne, a PhD student at the University of Western Ontario.

â€œItâ€™s as though we have a semi-autonomous robot in our brain that plans and executes actions on our behalf with only the broadest of instructions from us!â€

According to Mel Goodale, professor at the University of Western Ontario and senior author on the paper, these findings â€œnot only reveal just how sophisticated the visuomotor systems in the brain are, but could also have important implications for the design and implementation of robotic systems and efficient human-machine interfaces.â€

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This work was supported by operating grants from the Natural Sciences and Engineering Research Council of Canada to J. C. Culham (Grant No. 249877 RGPIN) and M. A. Goodale (Grant No. 6313 2007 RGPIN).

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