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Breakthrough in quest for mindreading

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February 11, 2007

Breakthrough in quest for mindreading

Breakthrough in quest for mindreading

February 12, 2007 It appears that the ever more omnipotent computer is set to add another remarkable by unravelling the secrets of mindreading. Every day we plan numerous actions, such as to return a book to a friend or to make an appointment. How and where the brain stores these intentions has been revealed by John-Dylan Haynes from the Max Planck Institute for Human Cognitive and Brain Sciences, in cooperation with researchers from London and Tokyo. For the first time they were able to "read" participants’ intentions out of their brain activity. This was made possible by a new combination of functional magnetic resonance imaging and sophisticated computer algorithms. By imaging patterns of activity in the brain's prefrontal cortex as subjects concentrated on their choice of two future actions, researchers have been able to distinguish cortical activity patterns that correspond to the subjects' different plans.

Past research had indicated that activity in the area of the prefrontal cortex increases when humans engage in goal-related neural processing, but it has been unclear whether patterns of activity might encode an individual's current intention. The observed goal-related activity might also (or, alternatively) represent other processes, such as preparing for a motor response, accessing memories of past related responses, or bearing in mind the choice of responses available.

To address the question of whether intention might be reflected in prefrontal cortical activity, the researchers in the new work used functional magnetic resonance imaging (fMRI) to assess brain activity while subjects concentrated on their choice of intended mental action, but prior to execution of the action. Specifically, subjects were free to choose between adding or subtracting two numbers and were asked to hold in mind their intention until numbers were presented on a screen, along with a choice of outcomes (one of which was correct for the addition choice, one correct for the subtraction choice). Subjects then selected the correct answer according to their planned task, revealing their intended action.

The researchers found that during the delay between the subjects' choice of task and execution of the task, it was possible to decode from activities in two regions of the prefrontal cortex which of the two actions (addition or subtraction) individuals had chosen to pursue. Different patterns of activity were seen during actual execution of the task, showing that regionally distinct neural substrates were involved in task preparation and execution. Decoding of intentions was most robust when activity patterns in the medial prefrontal cortex were taken into account, consistent with the idea that this region of the brain participating in the reflection of an individual on his or her own mental state.

The researchers include John-Dylan Haynes of Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, Bernstein Center for Computational Neuroscience and Charité – Universitätsmedizin in Berlin, Germany, University College London in London, UK; Katsuyuki Sakai of Graduate School of Medicine, University of Tokyo in Tokyo, Japan; Geraint Rees, Sam Gilbert, and Chris Frith of University College London in London, UK; Richard E. Passingham of University College London in London, UK and University of Oxford in Oxford, UK.

This work was supported by the Max Planck Society, the Wellcome Trust, and the Mind-Science Foundation.

The findings, reported by a collaborative group led by John-Dylan Haynes of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, appear in Current Biology online on February 8th.

Haynes et al.: "Reading Hidden Intentions in the Human Brain" Publishing in Current Biology 17, February 20, 2007.

About the Author
Mike Hanlon After Editing or Managing over 50 print publications primarily in the role of a Magazine Doctor, Mike embraced the internet full-time in 1995 and became a "start-up all-rounder" – quite a few start-ups later, he founded Gizmag in 2002. Now he can write again.   All articles by Mike Hanlon
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