Language in genetic syndromes and cognitive modularity

In recent years, research into the impact of genetic abnormalities on cognitive development, including language, has become recognized for its potential to make valuable contributions to our understanding of the brain–behaviour relationships underlying language acquisition as well as to understanding the cognitive architecture of the human mind. The publication of Fodor’s ( 1983 ) book The Modularity of Mind has had a profound impact on the study of language and the cognitive architecture of the human mind. Its central claim is that many of the processes involved in comprehension are undertaken by special brain systems termed ‘modules’. This domain specificity of language or modularity has become a fundamental feature that differentiates competing theories and accounts of language acquisition (Fodor 1983 , 1985 ; Levy 1994 ; Karmiloff-Smith 1998 ). However, although the fact that the adult brain is modularized is hardly disputed, there are different views of how brain regions become specialized for specific functions. A question of some interest to theorists is whether the human brain is modularized from the outset (nativist view) or whether these distinct brain regions develop as a result of biological maturation and environmental input (neuroconstructivist view). One source of insight into these issues has been the study of developmental disorders, and in particular genetic syndromes, such as Williams syndrome (WS) and Down syndrome (DS). Because of their uneven profiles characterized by dissociations of different cognitive skills, these syndromes can help us address theoretically significant questions. Investigations into the linguistic and cognitive profiles of individuals with these genetic abnormalities have been used as evidence to advance theoretical views about innate modularity and the cognitive architecture of the human mind. The present chapter will be organized as follows. To begin, two different theoretical proposals in the modularity debate will be presented. Then studies of linguistic abilities in WS and in DS will be reviewed. Here, the emphasis will be mainly on WS due to the fact that theoretical debates have focused primarily on WS, there is a larger body of literature on WS, and DS subjects have typically been used for the purposes of comparison. Finally, the modularity debate will be revisited in light of the literature review of both WS and DS. Conclusions will be drawn regarding the contribution of these two genetic syndromes to the issue of cognitive modularity, and in particular innate modularity.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.