This competing renewal investigates the role of number knowledge in word meaning. In the prior funding period, we discovered that non-aphasic patients with corticobasal degeneration (CBD) have difficulty with number knowledge, and that this interferes with their comprehension of number-based quantifiers like "at least half" and "most." MRI and pathology studies associated this with parietal disease. Converging evidence related quantifier comprehension to parietal activation during fMRI studies of healthy controls. We propose to show that the quantity component of number knowledge is responsible for a specific aspect of number-based quantifier meaning, and studies of CBD and fMRI work in healthy adults will relate this to the intraparietal sulcus. This collaborates with another, pragmatic component of quantifier meaning, and studies of non-aphasic patients with frontal disease due to frontotemporal lobar degeneration (FTLD) and fMRI studies of healthy controls will relate this aspect of quantifier comprehension to prefrontal cortex. Quantifiers can be ambiguous, and a neuroeconomic approach to decision-making will be applied to the interpretation of quantifiers with ambiguous meaning. We will show that evaluating the probability of a specific interpretation is mediated by prefrontal cortex, that appreciating the value of unambiguous communication is related to orbital frontal cortex, and that the integration of these decision-making components is supported by inferior parietal cortex.
In this competing renewal, we propose to show that the quantity component of number knowledge contributes to the representation of number-based quantifiers like at least half and most. Studies of patients with corticobasal degeneration and fMRI activation studies of healthy controls will relate this to inferior parietal cortex. This collaborates with another, pragmatic component of quantifiers, and studies of patients with frontotemporal lobar degeneration and fMRI studies of healthy adults will relate this to prefrontal cortex. Quantifiers can be ambiguous, and we will adopt a neuroeconomic approach to decision-making to help understand quantifier interpretation. This process will be mediated by a large-scale neural network including several frontal and parietal regions. The proposed work will provide important insights into the cognitive neuroscience of language and number while improving diagnostic accuracy in an elusive neurodegenerative condition.
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