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Is neuroimaging measuring information in the brain?

Overview of attention for article published in Psychonomic Bulletin & Review, February 2016
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Title
Is neuroimaging measuring information in the brain?
Published in
Psychonomic Bulletin & Review, February 2016
DOI 10.3758/s13423-016-1002-0
Pubmed ID
Authors

Lee de-Wit, David Alexander, Vebjørn Ekroll, Johan Wagemans

Abstract

Psychology moved beyond the stimulus response mapping of behaviorism by adopting an information processing framework. This shift from behavioral to cognitive science was partly inspired by work demonstrating that the concept of information could be defined and quantified (Shannon, 1948). This transition developed further from cognitive science into cognitive neuroscience, in an attempt to measure information in the brain. In the cognitive neurosciences, however, the term information is often used without a clear definition. This paper will argue that, if the formulation proposed by Shannon is applied to modern neuroimaging, then numerous results would be interpreted differently. More specifically, we argue that much modern cognitive neuroscience implicitly focuses on the question of how we can interpret the activations we record in the brain (experimenter-as-receiver), rather than on the core question of how the rest of the brain can interpret those activations (cortex-as-receiver). A clearer focus on whether activations recorded via neuroimaging can actually act as information in the brain would not only change how findings are interpreted but should also change the direction of empirical research in cognitive neuroscience.

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Mendeley readers

The data shown below were compiled from readership statistics for 350 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 1%
United Kingdom 3 <1%
United States 3 <1%
Netherlands 1 <1%
Canada 1 <1%
Austria 1 <1%
Russia 1 <1%
Slovenia 1 <1%
Unknown 335 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 100 29%
Researcher 73 21%
Student > Master 40 11%
Student > Bachelor 29 8%
Professor 14 4%
Other 46 13%
Unknown 48 14%
Readers by discipline Count As %
Psychology 124 35%
Neuroscience 72 21%
Agricultural and Biological Sciences 27 8%
Engineering 15 4%
Medicine and Dentistry 12 3%
Other 30 9%
Unknown 70 20%