**3. Learning of patterns**

As mentioned above, ASD is characterized by delays in language learning, including the learning of new words, their use, the pragmatics of language, or the fluidity of use (see e.g., Lord, Risi, & Pickles, 2004, for a review). These delays, as well as other symptoms of autism, have been attributed to differences in how patterns of information are learned (e.g., L. G. Klinger, Klinger, & Pohlig, 2007). More specifically, individuals with autism might have difficulty learning underlying patterns of events when hypothesis-testing strategies cannot be applied. This kind of learning is commonly studied under the umbrella of implicit learning (see Perruchet, 2008; Shanks, 2005, for reviews), artificial-grammars learning (e.g., Reber, 1967), or pattern detection in category formation (e.g., Ashby & Maddox, 2005; Keri, 2003). Here, we use the term "implicit learning", consistent with the term used in ASD research.

Studies of pattern learning have led to interesting findings in ASD. On the one hand, there are several findings that suggest impaired implicit learning in ASD (e.g., Romero-Munguía, 2008). Consider, for example, findings obtained with the so-called serial reaction time (SRT) task: Participants are asked to press a key to indicate a particular stimulus in a sequence. Learning is reflected in a decrease in reaction time for sequences that contain subtle repeated patterns, compared to random sequences (cf., Nissen & Bullemer, 1987). While typically developing children demonstrated such learning, participants with ASD did not (Mostofsky, Goldberg, Landa, & Denckla, 2000). Further support for compromised implicit learning comes from findings on prototype learning (Klinger & Dawson, 2001). The task was to categorize fictitious animals that differed in features like ear length, leg length, and neck length (cf., Younger, 1993). Children with ASD performed more poorly than control participants match in verbal age (see also Klinger et al., 2007). In fact, performance on implicit learning tasks was highly correlated with ASD symptomatology, including communication skills, social skills, and the occurrence of repetitive behaviors.

However, the difference in implicit-learning abilities between ASD and control participants is not stable across task context, even when tested in the same lab (cf., Klinger & Dawson 2001; Klinger et al., 2001). Consider the SRT task again: when the inter-stimulus interval was reduced to 120ms (Barnes, Howard, Howard, Gilotty, Kenworthy, Gaillard 2008) or omitted altogether (Travers, Klinger, Mussey, & Klinger 2010), there was no difference between ASD and control participants. Both groups of children could learn to anticipate the rule-based sequence, compared to a random sequence (see also Muller, Cauich, Rubio, Mizuno, & Couchesne, 2004). Similarly, there was evidence for sequence learning when the rule was greatly simplified and the training extended to multiple sessions (Gordon & Stark, 2007). Furthermore, children with ASD demonstrate repetition priming effects comparable to those of controls (i.e., they could identify studies items better than non-studied items; Renner, Klinger, & Renner, 2000). And they were found to have intact semantic priming for simple common words (Toichi & Kamio, 2002) – further evidence for implicit-learning abilities in ASD. Overall, these findings have undermined a claim that ASD is characterized by a general difficulty with implicit learning, in turn undermining an effort to explain social deficits, motor abnormalities, and language deficits associated with the disorder.

There are many ways in which context effects on implicit learning could be explained. For example, one could address the differences in findings by looking for differences in the groups of participants, whether in age, symtomatology, or co-morbidity. It is possible that the findings fail to univocally address the question of implicit-learning competence in ASD because participants differ across different tasks. Or one could look for differences in other internal processes that could explain the pattern of performance. Tasks might differ in the degree to which they tap a participant's working memory. Or they differ in the extent to which they require the integration of gross-motor movements. Or they differ in whether they afford or undermine the use of explicit (i.e., hypothesis-testing) strategies. Indeed, ASD performance is comparable to that of typically developing children when the prototype learning task required a rule-based approach (Klinger & Dawson, 2001). And an exceedingly short inter-stimulus interval might have forced the minds of participants with ASD to abandon their bias to use a hypothesis-testing strategy and therefore make room for an implicit-learning process. There are multiple problems with this kind of reasoning, a major one being that it fails to address the entire list of context effects – beyond a comparison of a few studies.
