A competitive neural model of small number detection
Neural Networks
Modelling the statistical processing of visual information
Neurocomputing
A theoretical framework for multiple neural network systems
Neurocomputing
Compressed scaling of abstract numerosity representations in adult humans and monkeys
Journal of Cognitive Neuroscience
Order and magnitude share a common representation in parietal cortex
Journal of Cognitive Neuroscience
Journal of Cognitive Neuroscience
Rule extraction from a multilayer feedforward trained network via interval arithmetic inversion
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Connectionist modeling of linguistic quantifiers
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Spatial attention determines the nature of nonverbal number representation
Journal of Cognitive Neuroscience
Algebraic structure of verbal narratives with dual meanings
Mathematical and Computer Modelling: An International Journal
Multiple object individuation and exact enumeration
Journal of Cognitive Neuroscience
The parietal cortex in sensemaking: the dissociation of multiple types of spatial information
Computational Intelligence and Neuroscience - Special issue on Neurocognitive Models of Sense Making
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Despite their lack of language, human infants and several animal species possess some elementary abilities for numerical processing. These include the ability to recognize that a given numerosity is being presented visually or auditorily, and, at a later stage of development, the ability to compare two nume-rosities and to decide which is larger. We propose a model for the development of these abilities in a formal neuronal network. Initially, the model is equipped only with unordered numerosity detectors. It can therefore detect the numerosity of an input set and can be conditioned to react accordingly. In a later stage, the addition of a short-term memory network is shown to be sufficient for number comparison abilities to develop. Our computer simulations account for several phenomena in the numerical domain, including the distance effect and Fechner's law for numbers. They also demonstrate that infants' numerosity detection abilities may be explained without assuming that infants can count. The neurobiological bases of the critical components of the model are discussed.