
Contents
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Introduction: Number in The Human and Animal Brain Introduction: Number in The Human and Animal Brain
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Model: Number-Sensitive and Number-Selective Coding Model: Number-Sensitive and Number-Selective Coding
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Data: Number-Sensitive and Number-Selective Coding Data: Number-Sensitive and Number-Selective Coding
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Single-Unit Evidence in The Monkey Single-Unit Evidence in The Monkey
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Behavioral Evidence in Humans Behavioral Evidence in Humans
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Neuroimaging Evidence in Humans Neuroimaging Evidence in Humans
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Networks for Number Representation Networks for Number Representation
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Stages of Non-Symbolic Number Processing Stages of Non-Symbolic Number Processing
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Pathways for Symbolic and Non-Symbolic Number Pathways for Symbolic and Non-Symbolic Number
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Beyond Small-Number Representation: Working Memory, Task Demands, and Multi-Digit Numbers Beyond Small-Number Representation: Working Memory, Task Demands, and Multi-Digit Numbers
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The Object Location Map as A Visual Short-Term Memory System The Object Location Map as A Visual Short-Term Memory System
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Symbolic Number and Working Memory Symbolic Number and Working Memory
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Adding Task Demands Adding Task Demands
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Multi-Digit Numbers Multi-Digit Numbers
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Concluding Remarks Concluding Remarks
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References References
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31 Basic Number Representation and Beyond: neuroimaging and computational modeling
Get accessChantal Roggeman, Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
Wim Fias, Department of Experimental Psychology, Ghent University, Belgium and Ghent Institute for Functional and Metabolic Imaging
Tom Verguts, Department of Experimental Psychology, Ghent University, Belgium and Ghent Institute for Functional and Metabolic Imaging
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Published:06 January 2015
Cite
Abstract
We discuss recent computational network models of elementary number processing. One key issue to emerge from this work is a crucial distinction between symbolic and non-symbolic number representation, and the related distinction between number-selective and number-sensitive coding. Empirical predictions from the models were tested, and are here summarized. Another issue is the relation with task-based decision making mechanisms. In both lab and real-life settings, representations are seldomly accessed in a task-neutral manner, rather subjects are usually presented with a task. A related theme is the functional association between number representations and working memory. In these issues also, both modeling and neuroimaging work is summarized. To conclude, we propose that the combined modeling-neuroimaging approach should be extended to tackle more complex questions about number processing (e.g. fractions, development, dyscalculia).
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