Are symbolic and nonsymbolic numbers coded differently in the brain? Neuronal data indicate that overlap in numerical tuning curves is a hallmark of the approximate, analogue nature of nonsymbolic number representation. Consequently, patterns of fMRI activity should be more correlated when the representational overlap between two numbers is relatively high. In bilateral intraparietal sulci (IPS), for nonsymbolic numbers, the pattern of voxelwise correlations between pairs of numbers mirrored the amount of overlap in their tuning curves under the assumption of approximate, analogue coding. In contrast, symbolic numbers showed a flat field of modest correlations more consistent with discrete, categorical representation (no systematic overlap between numbers). Directly correlating activity patterns for a given number across formats (e.g., the numeral "6" with six dots) showed no evidence of shared symbolic and nonsymbolic number-specific representations. Overall (univariate) activity in bilateral IPS was well fit by the log of the number being processed for both nonsymbolic and symbolic numbers. IPS activity is thus sensitive to numerosity regardless of format; however, the nature in which symbolic and nonsymbolic numbers are encoded is fundamentally different.
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http://dx.doi.org/10.1002/hbm.22641 | DOI Listing |
J Exp Child Psychol
January 2025
Division of Social Science, The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, China. Electronic address:
Early computational capacity sets the foundation for mathematical learning. Preschool children have been shown to perform both non-symbolic addition and subtraction problems. However, it is still unknown how different operations affect the representational precision of the non-symbolic arithmetic solutions.
View Article and Find Full Text PDFOpen Mind (Camb)
January 2025
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA.
Children can manipulate non-symbolic representations of both small quantities of objects (about four or fewer, represented by the parallel individuation system) and large quantities of objects (represented by the analog magnitude system, or AMS). Previous work has shown that children can perform a variety of non-symbolic operations over AMS representations (like summing and solving for an unknown addend), but are not able to perform further operations on the derived solutions of such non-symbolic operations. However, while the computational capacity of AMS has been studied extensively in early childhood, less is known about the computational capacity of the parallel individuation system.
View Article and Find Full Text PDFBehav Brain Sci
January 2025
Centre for Logic and Philosophy of Science, Ghent University, Ghent,
Stibbard-Hawkes challenges the link between symbolic material evidence and behavioural modernity. Extending this to non-human species, we find that personal adornment, decoration, figurative art, and musical instruments may not uniquely distinguish human cognition. These common criteria may ineffectively distinguish symbolic from non-symbolic cognition or symbolic cognition is not uniquely human.
View Article and Find Full Text PDFEur J Neurosci
January 2025
National Institute of Education, Nanyang Technological University, Singapore.
Approximately 15%-20% of school-aged children suffer from mathematics learning difficulties (MLD). Most children with developmental dyscalculia (DD) or MLD also have comorbid cognitive deficits. Recent literature suggests that research should focus on uncovering the neural underpinnings of MLD across more inclusive samples, rather than limiting studies to pure cases of DD or MLD with highly stringent inclusion criteria.
View Article and Find Full Text PDFFront Psychiatry
December 2024
Departamento de Personalidad, Evaluación y Tratamiento Psicológicos, Universidad de Salamanca, Salamanca, Spain.
Introduction: It is crucial to provide a quality educational response to the needs of autistic children across various mathematical domains. However, there is no consensus on which of the early skills have the greatest predictive effect in the short and long term within these domains. Therefore, this research aimed to a) compare early numerical skills and mathematics domains, and 2) analyze the predictive value of early numerical skills into mathematics domains.
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