The question of how such atypicalities can result

The question of how such atypicalities can result in an uneven cognitive profile in which some skills can be near (or even better than) typical, while others show deficits has always posed a significant challenge to accounts of developmental disorders that postulate general factors, such as widespread synapse dysfunction, as being causal. It is commonly assumed that such widespread purchase apexbio dilution differences will necessarily have domain-general cognitive consequences and be accompanied by global delayed development. I believe this assumption to be incorrect, as it fails to take account of constructive and adaptive developmental processes (Karmiloff-Smith, 2009; Johnson, 2011). As discussed earlier, we have previously argued that the behaviors associated with autism can be interpreted as a natural adaptive developmental response to limited or sub-optimal neural processing early in postnatal life (see also Johnson et al., 2015 for details). In summary;
Adaptation through changes in network structure (Question 2) Vértes and Bullmore (2014) characterize human brain development in terms of the increasing organization of structural and functional connectivity networks; a progression from near random networks to efficient “small world” networks (small world networks involve semi-independent “modules” containing many short-range connections being connected at a longer range to critical “hub” regions). Large-scale structural connections develop rapidly and achieve near-adult levels of network complexity within the first few years. During these first years there is scope for these developmental changes in structural connectivity to reflect aspects of the interaction between the brain and its environment. While functional connectivity also increases in complexity and organization during early years, the specificity of the mapping between structural and functional connectivity networks (i.e., the extent to which functional connectivity patterns are constrained by structural connectivity networks) appears to increase with age during development and up to adolescence (Hagmann et al., 2010). This observation is consistent with other reports of increasing constraints on structure-function relations with increasing age (Gordon et al., 2011) and closely related predictions from the Interactive Specialization framework (Johnson, 2011). In terms of sensitive periods for human brain development, therefore, there are potentially two types of whole-brain network adjustment that could underpin ontogenetic adaptation. First, the construction of the structural connectivity network over the first two years may be open to influence by a variety of factors, including the previous ontogenetic history of brain functioning (Benders et al., 2015). Second, the less specialized network present in the infant brain allows for a broader mapping between the computations that underlie adaptive behaviors and their implementation across structural neural networks. In other words, during the first two years there may be several different options for how the computations necessary to support our species-typical behaviors can be implemented in terms of underlying structural connectivity. These options for implementing functional networks become narrowed to the most efficient configurations in the course of typical development (Vértes and Bullmore, 2014), along with their associated changes in underlying structural networks. However, initially other options are possible that may be evident in later life as different “styles” of neural processing. For example, a more featural and detail-oriented style of processing may reflect an alternate structure-function connectivity mapping for some key networks. Importantly, these adaptive changes may be difficult to reverse in later life even if there are changes in the external environment or internal neural processing. An emerging literature is concerned with changes in network connectivity following acquired lesions in adults. Although the capacity for compensatory network responses in adults is likely to be reduced compared to the first 2 years of life, there are likely to be similarities in these changes. In general, following traumatic brain injury functional networks show a reduction in their “small world” architecture (Sharp et al., 2014) to a less differentiated state. More specific changes include a strengthening of connectivity to/from frontal regions, increases in the strength of the default mode network, and an apparent disconnection of network hubs (Fagerholm et al., 2015; Sharp et al., 2011).