The present study examined the neural substrate of two classes of quantifiers: Numerical quantifiers like "at least three" which require magnitude processing, and logical quantifiers like "some" which can be satisfied using a simple form of perceptual logic. We assessed these distinct classes of quantifiers with converging observations from two sources: functional imaging data from healthy adults, and behavioral and structural data from patients with corticobasal degeneration, who have acalculia. Our findings are consistent with the claim that numerical quantifier comprehension depends on a parietal-dorsolateral prefrontal network, but logical quantifier comprehension depends instead on a rostral medial prefrontal-posterior cingulate network. These observations emphasize the important contribution of abstract number knowledge to the meaning of numerical quantifiers in semantic memory and the potential role of a logic-based evaluation in the service of non-numerical quantifiers.
Both language and genes evolve by transmission over generations with opportunity for differential replication of forms. The understanding that gene frequencies change at random by genetic drift, even in the absence of natural selection, was a seminal advance in evolutionary biology. Stochastic drift must also occur in language as a result of randomness in how linguistic forms are copied between speakers. Here we quantify the strength of selection relative to stochastic drift in language evolution. We use time series derived from large corpora of annotated texts dating from the 12th to 21st centuries to analyse three well-known grammatical changes in English: the regularization of past-tense verbs, the introduction of the periphrastic 'do', and variation in verbal negation. We reject stochastic drift in favour of selection in some cases but not in others. In particular, we infer selection towards the irregular forms of some past-tense verbs, which is likely driven by changing frequencies of rhyming patterns over time. We show that stochastic drift is stronger for rare words, which may explain why rare forms are more prone to replacement than common ones. This work provides a method for testing selective theories of language change against a null model and reveals an underappreciated role for stochasticity in language evolution.
Quantifiers are very common in everyday speech, but we know little about their cognitive basis or neural representation. The present study examined comprehension of three classes of quantifiers that depend on different cognitive components in patients with focal neurodegenerative diseases. Patients evaluated the truth-value of a sentence containing a quantifier relative to a picture illustrating a small number of familiar objects, and performance was related to MRI grey matter atrophy using voxel-based morphometry. We found that patients with corticobasal syndrome (CBS) and posterior cortical atrophy (PCA) are significantly impaired in their comprehension of Cardinal Quantifiers (e.g. “At least three birds are on the branch”), due in part to their deficit in quantity knowledge. MRI analyses related this deficit to temporal-parietal atrophy found in CBS/PCA. We also found that patients with behavioral variant frontotemporal dementia (bvFTD) are significantly impaired in their comprehension of Logical Quantifiers (e.g. “Some the birds are on the branch”), associated with a simple form of perceptual logic, and this correlated with their deficit on executive measures. This deficit was related to disease in rostral prefrontal cortex in bvFTD. These patients were also impaired in their comprehension of Majority Quantifiers (e.g. “At least half of the birds are on the branch”), and this too was correlated with their deficit on executive measures. This was related to disease in the basal ganglia interrupting a frontal-striatal loop critical for executive functioning. These findings suggest that a large-scale frontal-parietal neural network plays a crucial role in quantifier comprehension, and that comprehension of specific classes of quantifiers may be selectively impaired in patients with focal neurodegenerative conditions in these areas.
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