Loss of language in early development of autism and specific language impairment

Background:  Several authors have highlighted areas of overlap in symptoms and impairment among children with autism spectrum disorder (ASD) and children with specific language impairment (SLI). By contrast, loss of language and broadly defined regression have been reported as relatively specific to autism. We compare the incidence of language loss and language progression of children with autism and SLI. Methods:  We used two complementary studies: the Special Needs and Autism Project (SNAP) and the Manchester Language Study (MLS) involving children with SLI. This yielded a combined sample of 368 children (305 males and 63 females) assessed in late childhood for autism, history of language loss, epilepsy, language abilities and nonverbal IQ. Results:  language loss occurred in just 1% of children with SLI but in 15% of children classified as having autism or autism spectrum disorder. Loss was more common among children with autism rather than milder ASD and is much less frequently reported when language development is delayed. For children who lost language skills before their first phrases, the phrased speech milestone was postponed but long-term language skills were not significantly lower than children with autism but without loss. For the few who experienced language loss after acquiring phrased speech, subsequent cognitive performance is more uncertain. Conclusions:  Language loss is highly specific to ASD. The underlying developmental abnormality may be more prevalent than raw data might suggest, its possible presence being hidden for children whose language development is delayed.

An agent based approach to distributed task modeling for co-operative task support

This paper describes the design and implementation of an agent based network for the support of collaborative switching tasks within the control room environment of the National Grid Company plc. This work includes aspects from several research disciplines, including operational analysis, human computer interaction, finite state modelling techniques, intelligent agents and computer supported co-operative work. Aspects of these procedures have been used in the analysis of collaborative tasks to produce distributed local models for all involved users. These models have been used as the basis for the production of local finite state automata. These automata have then been embedded within an agent network together with behavioural information extracted from the task and user analysis phase. The resulting support system is capable of task and communication management within the transmission despatch environment.

Perspex machine X: software development

The Perspex Machine arose from the unification of computation with geometry. We now report significant redevelopment of both a partial C compiler that generates perspex programs and of a Graphical User Interface (GUI). The compiler is constructed with standard compiler-generator tools and produces both an explicit parse tree for C and an Abstract Syntax Tree (AST) that is better suited to code generation. The GUI uses a hash table and a simpler software architecture to achieve an order of magnitude speed up in processing and, consequently, an order of magnitude increase in the number of perspexes that can be manipulated in real time (now 6,000). Two perspex-machine simulators are provided, one using trans-floating-point arithmetic and the other using transrational arithmetic. All of the software described here is available on the world wide web. The compiler generates code in the neural model of the perspex. At each branch point it uses a jumper to return control to the main fibre. This has the effect of pruning out an exponentially increasing number of branching fibres, thereby greatly increasing the efficiency of perspex programs as measured by the number of neurons required to implement an algorithm. The jumpers are placed at unit distance from the main fibre and form a geometrical structure analogous to a myelin sheath in a biological neuron. Both the perspex jumper-sheath and the biological myelin-sheath share the computational function of preventing cross-over of signals to neurons that lie close to an axon. This is an example of convergence driven by similar geometrical and computational constraints in perspex and biological neurons.