September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
The effects of content-dependent competition on working memory capacity limits
Author Affiliations
  • Jason Scimeca
    Helen Wills Neuroscience Intitute, University of California, Berkeley
  • Jacob Miller
    Helen Wills Neuroscience Intitute, University of California, Berkeley
  • Mark D'Esposito
    Helen Wills Neuroscience Intitute, University of California, Berkeley
Journal of Vision August 2017, Vol.17, 109. doi:
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      Jason Scimeca, Jacob Miller, Mark D'Esposito; The effects of content-dependent competition on working memory capacity limits. Journal of Vision 2017;17(10):109. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

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Both visual attention and working memory (WM) are marked by severe capacity limits. The biased-competition model (Desimone & Duncan, 1995) proposes that capacity limits in visual attention arise because simultaneously perceived stimuli compete for neural representation in sensory cortex. Sensory recruitment models of WM (D'Esposito, 2007; Postle, 2006) argue that information in WM is maintained in sensory cortex. The competitive map framework links these models by proposing that capacity limits in attention and WM arise from competition in content-dependent cortical maps (Franconeri et al., 2013). A recent study demonstrated that this map framework can explain visual processing limits for simultaneously presented items drawn from either the same or different categories (e.g. two faces/two scenes or four faces; Cohen et al., 2014). Here we examine whether the map framework can explain capacity limits in WM. To prevent competition at perception, four items were sequentially presented and then maintained in WM for 10 seconds. Across several categories (faces/bodies/scenes), WM capacity is higher when items are drawn from separate categories versus a single category. This is consistent with lower across-category versus within-category competition, supporting the role of content-dependent competition in WM capacity limits independent of perceptual competition. Furthermore, we used fMRI and a forward modeling approach (Brouwer & Heeger, 2011) to assess the nature of competition that occurs within WM. Using multivoxel patterns in sensory cortex recorded on low-load (load-2) same-category trials, we trained a model to project fMRI activity into a representational space consisting of content-dependent channels (e.g. a face channel and a scene channel). We then invert the model to reconstruct channel amplitudes based on data from load-4 same-category and mixed-category trials. The amplitude of the relevant channel predicts behavioral accuracy across trials, and these amplitudes are higher on mixed-category versus same-category trials, consistent with reduced cortical competition across content-dependent channels.

Meeting abstract presented at VSS 2017


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