Autism is a profound disorder of brain development and, despite the rigorous scientific attention paid to it, many fundamental questions remain unanswered. Classically, the study of autism has focused on specific aspects such as the atypicalities in social cognition, theory of mind, joint attention, language, and emotional regulation, and the alterations in those brain regions that underlie these behaviors (Behrmann, et al., 2006
; Dakin & Frith, 2005
; Klin, Jones, Schultz, Volkmar, & Cohen, 2002a
; Luna, et al., 2002
; Peterson, Wellman, & Liu, 2005
). Here, using naturalistic, rich sensory stimulation, and an assumption-free inter-SC and intra-SC analysis, we explore the whole-brain activation profile in high-functioning adults with autism, and demonstrate that the functional response time courses in autism during natural viewing are markedly atypical across many brain regions (). In particular, the expected cortical response profile is masked by idiosyncratic alterations in the response time courses in areas ranging from primary sensory cortices all the way through to high-level association areas ().
Specifically, we document three major findings. First, relative to the well-defined and predictable patterns of activity in typical subjects, the cortical activation patterns in individuals with autism were highly disrupted in multiple cortical areas, including both primary sensory areas and higher-order areas ( and ). This suggests that autism is associated with a broad neuronal dysfunction, affecting multiple, disparate cortical areas. Second, within each individual with autism, retested under identical circumstances, the intra-SC was higher than the inter-SC (). This suggests that at least part of the variability observed in each autistic individual might emerge from a consistent but idiosyncratic activation pattern in response to the sensory input (Rogers, Hepburn, Stackhouse, & Wehner, 2003
). Finally, given that we were able to uncover typical response time courses in each autistic individual ( and Supplementary Figure 2
), the idiosyncratic fluctuations appear to interfere with, but not entirely abolish, the neuronal processing of the movie. Indeed, all of the individuals with autism achieved at least some understanding of the movie's plot, as revealed by the post-scan questionnaire, indicating that the fluctuations observed in each autistic individual did not eliminate their ability to comprehend the external input. At the same time, the breakdown in the inter-SC observed within the individuals with autism () attests to the presence of idiosyncratic signal fluctuations even while the individuals are actively watching the movie.
These idiosyncratic response time courses are not attributable to irregular head movements, or to the irregular eye movement patterns observed in individuals with autism across repeated presentations of the movie, or to group differences in signal amplitude. Finally, the finding that each individual with autism was able to follow the movie's plot, together with the fact that we were able to uncover a typical signal in the autism group and the test-retest replicability, argue against the likelihood that the idiosyncratic response time courses are simply induced by a lack of attention to the movie.
What is the source of the idiosyncratic response time courses observed in each autistic individual? First, the responses might be related to a set of individualized strategies employed by each autism subject in response to the rich sensory input. These strategies can vary from individual to individual, but still be highly reliable within an autistic individual. Thus, it could be that the increase in reliable responses within each autistic individual (increased intra-SC within the autism group; ) uncovers the singularity of the neuronal responses in each autistic individual. These individual profiles may serve as the neural correlate for the extensive heterogeneity in behavioral symptoms (social behavior, communication abilities, and restricted, repetitive or stereotyped patterns of behavior) expressed, not just across the autism spectrum, but even within individuals falling at the same point along the continuum. Note that, in contrast to the substantial inter-individual variability observed in individuals who are diagnosed with autism that is co-morbid with attention deficit disorder (Geurts, et al., 2008
), we see relatively stable, repeatable patterns within, although not between, individuals. Further studies are needed in order to identify the ramifications of these individual profiles and to assess whether it is indeed the case that the behavioral heterogeneity is mediated by the differing individual neural patterns. It is, of course, also crucial to understand how the observed variability across autistic individuals gives rise to the well-known triad of symptoms common in autism.
Another possibility, albeit not mutually exclusive, is that these idiosyncratic responses are related to more generalized physiological and/or structural alternations in the autistic's brain. For example, the idiosyncratic activity in autism may result from disproportionately higher levels of excitation and/or lower levels of inhibition in the individuals (Polleux & Lauder, 2004
; Rubenstein & Merzenich, 2003
), resulting in hyperexcitable cortex. This would be consistent with reports of high levels of noisy spike activity on EEG/MEG (Daoust, Limoges, Bolduc, Mottron, & Godbout, 2004
; Hurley, Lewine, Jones, Orrison, & Taber, 2000
) and increased seizure incidence in autism (Hughes & Melyn, 2005
; Tuchman, 2000
). However, it is important to note that fMRI provides only an indirect measure of the neuronal responses (Logothetis, Pauls, Augath, Trinath, & Oeltermann, 2001
; Mukamel, et al., 2005
), and thus we cannot directly assess this hypothesis with the current data set. Moreover, the idiosyncratic response time courses may be due to an excess of white matter tracts in autism, relative to matched controls (Courchesne, et al., 2001
; Freitag, et al., 2009
; Hendry, et al., 2005
; Herbert, 2005
; Herbert, et al., 2004
). Regardless of the source of the variability across individuals with autism, whether it be physiological or structural, our results indicate that these irregularities are expressed in a lawful manner within each individual under real-life viewing conditions. In other words, the idiosyncratic responses are reliably induced (i.e., time locked) to the external stimuli with each autistic individual, and cannot be attributed to an internally induced erratic and unstable set of responses.
Finally, our findings of idiosyncratic response time courses may be linked with the claim that individuals with autism experience sensory overload (for example, (Crane, Goddard, & Pring, 2009
). These results are also consistent with the recent “intense world syndrome” model of autism (Markram, Rinaldi, & Markram, 2007
), in which the excessive neuronal processing in circumscribed circuits in individuals with autism leads to hyper-reactivity, which interferes with the processing of the incoming information, which, in turn, leads to social and environmental withdrawal. On this account, in response to this excessive neuronal activation, the neural system is thought to “lock down” the individual to a small repertoire of idiosyncratic behaviors, which are repeated with high frequency. In our data, we observed strong idiosyncratic fluctuations (see ) and these may be associated (either as cause or effect) with the hypersensitivity and hyperfunctionality observed in autistic individuals.
In sum, we have exploited a novel inter-correlation approach, which has enabled us to document both typical and atypical aspects of the cortical activation patterns in high functioning adults with autism. Our study exposes the extensive presence of idiosyncratic response time courses in the individuals with autism during the processing of complex, dynamic external stimuli. Any full theoretical account of autism will need to be able to explain both the common aspects of the response as well as the apparent idiosyncratic, repeatable within-subject neural profile. We note that this analytic approach has much potential to elucidate the neural dynamics that are activated in naturalistic conditions in individuals with autism, as reflected by its ability to distinguish clearly between individuals with autism and their typical counterparts. Taken together, these findings may pave the way to future research focusing on identifying and characterizing the underline sources of such idiosyncratic fluctuations, which may also help developing diagnostic tools for autism in at-risk populations.