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Peter Tse, Prescott Alexander, Alex Schlegel; THE NEURAL BASES OF MENTAL OPERATIONS IN VISUAL WORKING MEMORY. Journal of Vision 2016;16(12):941. https://doi.org/10.1167/16.12.941.
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© ARVO (1962-2015); The Authors (2016-present)
Background: In Baddeley's (1986) model of working memory, the brain manipulates mental representations via a central executive system that directs activity in subsystems like the visuospatial sketchpad. Many neuroimaging studies implicate a network including dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC) as the neural correlate of this model (e.g. Schlegel, et al., 2013). Current understanding suggests that DLPFC acts as Baddeley's central executive, directing transformations of mental representations in other regions rather than storing representations directly. For instance, Crowe and colleagues (2013) showed that neurons in monkey prefrontal cortex transmit executive control signals to parietal neurons. Question: In our fMRI studies, we asked whether DLPFC, PPC and other areas direct the manipulation of mental imagery or if they are also involved in representing mental images themselves. Method: We developed a hierarchy of abstract shapes and an orthogonal hierarchy of mental operations that could be performed on those shapes. In each of a series of trials, human participants performed a particular mental operation on a particular shape. Results: Using multivariate pattern classification methods on neural activity in DLPFC, we could decode both the shape that participants imagined and the mental operation that they performed. Representational similarity analyses showed that the informational structures of both DLPFC and PPC correlated significantly with both the shape and the operation hierarchies, although DLPFC correlated more with the operation hierarchy and PPC correlated more with the shape hierarchy. Conclusion: Our results suggest that information about both mentally imaged shapes and mental operations over those operands is distributed throughout specialized nodes of the frontoparietal network rather than localized to particular regions.
Meeting abstract presented at VSS 2016
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