This reassured us that the reported difference in synchronization between the groups was not driven by responses to the auditory stimuli but rather was driven by fluctuations in spontaneous activity. Our results suggest that reduced neural synchronization is a notable characteristic of autism, evident at very early stages of autism development. Compared with language-delayed and control toddlers, toddlers with autism exhibited significantly weaker Selleck Adriamycin interhemispheric synchronization in IFG and/or

STG, two areas commonly associated with language processing (Figure 2 and Figure 3). Furthermore, in the autism group, IFG synchronization strength was correlated with behavioral scores, scaling positively with language abilities and negatively with autism severity (Figure 4). Whether poor interhemispheric synchronization in putative language areas plays a causal role in generating autistic behavioral symptoms cannot be determined by this study. Nevertheless, the fact that poor synchronization was found in the language system of toddlers with autism, and not in toddlers with language delay (both groups exhibited similarly low expressive language scores; Figure S6), suggests that reduced synchronization may reflect the existence of a specific pathophysiological mechanism that is unique to autism. It is remarkable that quantifying the synchronization of spontaneous cortical activity

during natural sleep holds such valuable information about the developmental

state of a toddler. The majority Tariquidar concentration of the toddlers with autism in our sample (72%) could be identified with high accuracy (84%) by the strength of interhemispheric correlation in putative language areas (Figure 3 and Figure S2). These results the were obtained when selecting a correlation threshold of 0.38. Raising the threshold would increase the number of identified toddlers with autism (higher sensitivity) at the expense of reduced accuracy (lower specificity). Regardless of the precise threshold chosen, these results suggest that quantifying spontaneous cortical activity during sleep may aid in the early diagnosis of autism and enable earlier intervention (Pierce et al., 2009 and Zwaigenbaum et al., 2009). There are many clear advantages to this technique. Scanning during natural sleep does not require subject compliance, eliminating the possibility that group differences in brain activity arise from task differences or behavioral strategies. In fact, in toddlers it is practically the only way of avoiding incessant movement artifacts and random uncontrolled behaviors. Even more importantly, scanning during sleep permits the inclusion of individuals with severe autistic traits who are usually excluded from autism imaging studies. Note that this study is one of a handful of fMRI studies that include individuals with severe autism, a critical requirement for an early diagnostic tool and for thorough evaluation of hypotheses regarding autism neurophysiology.