A Shared, Flexible Neural Map Architecture Reflects Capacity Limits in Both Visual Short-Term Memory and Enumeration

Human cognition is characterized by severe capacity limits: we can accurately track, enumerate, or hold in mind only a small number of items at a time. It remains debated whether capacity limitations across tasks are determined by a common system. Here we measure brain activation of adult subjects performing either a visual short-term memory (vSTM) task consisting of holding in mind precise information about the orientation and position of a variable number of items, or an enumeration task consisting of assessing the number of items in those sets. We show that task-specific capacity limits (three to four items in enumeration and two to three in vSTM) are neurally reflected in the activity of the posterior parietal cortex (PPC): an identical set of voxels in this region, commonly activated during the two tasks, changed its overall response profile reflecting task-specific capacity limitations. These results, replicated in a second experiment, were further supported by multivariate pattern analysis in which we could decode the number of items presented over a larger range during enumeration than during vSTM. Finally, we simulated our results with a computational model of PPC using a saliency map architecture in which the level of mutual inhibition between nodes gives rise to capacity limitations and reflects the task-dependent precision with which objects need to be encoded (high precision for vSTM, lower precision for enumeration). Together, our work supports the existence of a common, flexible system underlying capacity limits across tasks in PPC that may take the form of a saliency map.

[1]  D. V. Essen,et al.  Surface-Based and Probabilistic Atlases of Primate Cerebral Cortex , 2007, Neuron.

[2]  D. Melcher,et al.  The Role of Attentional Priority and Saliency in Determining Capacity Limits in Enumeration and Visual Working Memory , 2011, PloS one.

[3]  Bahador Bahrami,et al.  A Candidate for the Attentional Bottleneck: Set-size Specific Modulation of the Right TPJ during Attentive Enumeration , 2011, Journal of Cognitive Neuroscience.

[4]  Jason B. Mattingley,et al.  Spatial working memory and spatial attention rely on common neural processes in the intraparietal sulcus , 2010, NeuroImage.

[5]  Bertrand Thirion,et al.  Deciphering Cortical Number Coding from Human Brain Activity Patterns , 2009, Current Biology.

[6]  Brian Butterworth,et al.  Are Subitizing and Counting Implemented as Separate or Functionally Overlapping Processes? , 2002, NeuroImage.

[7]  N. Cowan The magical number 4 in short-term memory: A reconsideration of mental storage capacity , 2001, Behavioral and Brain Sciences.

[8]  M. Goldberg,et al.  Neuronal Activity in the Lateral Intraparietal Area and Spatial Attention , 2003, Science.

[9]  P. Cavanagh,et al.  Flexible cognitive resources: competitive content maps for attention and memory , 2013, Trends in Cognitive Sciences.

[10]  S. Dehaene,et al.  Single-trial classification of parallel pre-attentive and serial attentive processes using functional magnetic resonance imaging , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[11]  Gustavo Deco,et al.  Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network , 2012, PloS one.

[12]  Jon Driver,et al.  Integration of Goal- and Stimulus-Related Visual Signals Revealed by Damage to Human Parietal Cortex , 2010, The Journal of Neuroscience.

[13]  D. Melcher,et al.  Subitizing reflects visuo-spatial object individuation capacity , 2011, Cognition.

[14]  E. Brannon,et al.  Monotonic Coding of Numerosity in Macaque Lateral Intraparietal Area , 2007, PLoS biology.

[15]  S. Geisser,et al.  On methods in the analysis of profile data , 1959 .

[16]  J. Gottlieb From Thought to Action: The Parietal Cortex as a Bridge between Perception, Action, and Cognition , 2007, Neuron.

[17]  Ravi S. Menon,et al.  Human fMRI evidence for the neural correlates of preparatory set , 2002, Nature Neuroscience.

[18]  David C. Burr,et al.  Linear mapping of numbers onto space requires attention , 2012, Cognition.

[19]  J. Jay Todd,et al.  Capacity limit of visual short-term memory in human posterior parietal cortex , 2004, Nature.

[20]  Kazuyuki Aihara,et al.  Human posterior parietal cortex maintains color, shape and motion in visual short-term memory , 2008, Brain Research.

[21]  Wim Fias,et al.  Salience maps in parietal cortex: Imaging and computational modeling , 2010, NeuroImage.

[22]  P. Cavanagh,et al.  Visual short-term memory operates more efficiently on boundary features than on surface features , 2008, Perception & psychophysics.

[23]  D. Melcher,et al.  A visual sense of number emerges from the dynamics of a recurrent on-center off-surround neural network , 2014, Brain Research.

[24]  David C. Van Essen,et al.  Application of Information Technology: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex , 2001, J. Am. Medical Informatics Assoc..

[25]  S Dehaene,et al.  Spatially invariant coding of numerical information in functionally defined subregions of human parietal cortex. , 2015, Cerebral cortex.

[26]  D. Melcher,et al.  Temporal buffering and visual capacity: The time course of object formation underlies capacity limits in visual cognition , 2013, Attention, Perception, & Psychophysics.

[27]  Paul J. Laurienti,et al.  An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets , 2003, NeuroImage.

[28]  D. V. van Essen,et al.  A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex. , 2005, NeuroImage.

[29]  M. Goldberg,et al.  Space and attention in parietal cortex. , 1999, Annual review of neuroscience.

[30]  Zhentao Zuo,et al.  Effects of number magnitude and notation at 7T: separating the neural response to small and large, symbolic and nonsymbolic number. , 2014, Cerebral cortex.