The neural substrates of cognitive control deficits in autism spectrum disorders
Introduction
Autism spectrum disorders (ASDs), including autism, high functioning autism, Asperger's Disorder, and PDDNOS, are neurodevelopmental disorders with a prevalence of 1 in 150 (CDC MMWR, 2007). Impairments in executive functions are among the most consistently reported deficits in individuals with ASDs (see Ozonoff et al., 2006, Verté et al., 2006). Executive function deficits in autism generally are assumed to be the result of abnormal prefrontal cortex (PFC) function. However, there have been few published functional magnetic resonance imaging (fMRI) studies of executive functions in individuals with ASDs, and only one has been conducted in adolescents (see Silk, Rinehart, Bradshaw, Tonge, Egan, O’Boyle, et al., 2006). Thus, little is known about the specific brain regions and neural circuits associated with executive deficits in adolescents with ASDs.
Cognitive control is a parsimonious and mechanistic term evolving in the field of cognitive neuroscience to refer to what previously have been thought of as executive functions. Cognitive control refers to the ability to flexibly allocate mental resources to guide thoughts and actions in light of internal goals. It involves processing of task-relevant over competing information. Cognitive control must be engaged to represent task-relevant information, to overcome habitual responses, to ignore irrelevant stimuli, to transform mental representations, and to act in novel or rapidly changing conditions (Braver et al., 2002, Bunge et al., 2002). Impairments in cognitive control cause perseveration on over-learned behaviors. When assessed using behavioral measures requiring maintenance of task-relevant information and inhibition of a prepotent response tendency, cognitive control appears to be impaired in adolescents with ASDs (Solomon et al., 2008).
Cognitive control-based approaches are premised on clearly articulated links to neural systems. For example, the neural basis of cognitive control has been specified in the Miller and Cohen (2001) “guided activation hypothesis,” which suggests that (1) the PFC is specialized for the representation and maintenance of task-relevant information or “context,” (2) that context information is maintained in the PFC as a pattern of neural activity; and (3) that context representations mediate cognitive control through interactions that provide top-down biasing that modulates the flow of information in other brain systems that more directly support task performance (Braver et al., 2002, Fuster, 2002, Thompson-Schill et al., 2005).
Cognitive control has been associated with a reliable network of brain regions including the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex (ACC), and the parietal cortex (Curtis et al., 2004, Yarkoni et al., 2005). DLPFC is recruited when information must be maintained over a delay (Curtis & D’Esposito, 2003), when it is necessary to overcome prepotent response tendencies (D’Esposito & Postle, 2002); and when it is necessary to maintain appropriate context for action (MacDonald, Cohen, Stenger, & Carter, 2000). Better performers on cognitive control tasks activate the PFC more reliably and robustly than poorer performers (MacDonald et al., 2000, Rypma et al., 2002). Hypoactivation of the PFC during cognitive control tasks is also found in individuals with disorders including schizophrenia (Perlstein et al., 2003, Snitz et al., 2005).
The ACC is thought to function as part of a “control loop.” In this loop, dorsal ACC signals the occurrence of conflicts in information processing and thereby triggers compensatory adjustments in cognitive control, which serve to reduce conflict in subsequent task performance (Botvinick et al., 2004, Carter et al., 1998, Egner and Hirsch, 2005). Magnitude of error-related activity in the ACC has been shown to predict changes in response times and the magnitude of activity in DLPFC on trials immediately following error commission (Kerns, 2006).
The parietal cortex is activated when it is necessary to switch attentional focus (Corbetta, Kincade, Ollinger, McAvoy, & Shulman, 2000) or task sets (Braver et al., 2003, Dreher et al., 2002, Ravizza and Carter, 2008, Yeung et al., 2006). Some also have argued that the parietal cortex acts as a repository of learned stimulus–response associations that are accessed through top-down biasing by the PFC (Bunge et al., 2003, Wendelken et al., 2008).
The majority of fMRI studies of executive functions including response inhibition, working memory, mental rotation, spatial attention shifting, and response monitoring in individuals with ASDs have shown an overall reduction in brain activation in regions associated with these functions (see Schmitz et al., 2006, Takarae et al., 2007 for exceptions). There have been several fMRI studies of response inhibition in ASDs. Kana, Keller, Minshew, and Just (2007) used two versions of a go-no-go task in 12 adults with autism and 12 matched control subjects and found that participants with autism showed less brain activation in areas generally associated with inhibition including the ACC. In a more demanding version of the task that included a working memory load, individuals with autism displayed greater activation in premotor areas. In a cognitive control task involving overcoming a prepotent response tendency and set shifting, Shafritz, Dichter, Baranek, and Belger (2008) found that, participants exhibited control, but not set shifting impairments, and that individuals with ASDs exhibited less neural activity in the PFC, ACC, and parietal cortex relative to control subjects. In a working memory study using a single letter n-back paradigm, Koshino et al. (2005) found that individuals with autism activated posterior regions (inferior temporal and occipital cortices) more than typically developing subjects, and showed a different pattern of temporal connectivity between prefrontal and parietal regions. fMRI studies of spatial attention in adults with ASDs have found that these individuals exhibit less task-related activation in the DLPFC and parietal cortex than control participants during an occulomotor spatial working memory task (Luna et al., 2002), a bilateral visual spatial attention task (Belmonte & Yurgelun-Todd, 2003), and an attention orienting task (Haist, Adamo, Westerfield, Courchesne, & Townsend, 2005). Silk et al. (2006), also showed that adolescents with high functioning autism showed less activation than matched typically developing control subjects in lateral and medial premotor cortex, DLPFC, ACC, and caudate nucleus during a mental rotation task. In a study of response monitoring and the ACC using a saccadic paradigm, Thakkar et al. (2008) found that adults with autism made more antisaccade errors and showed reduced discrimination between error and correct responses in rostral ACC primarily due to abnormally increased ACC activation on correct trials.
A common theoretical framework that has been used to interpret neuroimaging findings in autism research is the underconnectivity hypothesis (Just, Cherkassky, Keller, & Minshew, 2004), which posits that the major neurobiologic abnormalities involved in autism involve alterations in white matter development, functional underconnectivity in large scale neural networks, and functional over-connectivity in small scale networks (Just et al., 2004, Minshew and Williams, 2007). There have now been several studies documenting “underconnectivity” in executive functions in autism in fronto-parietal regions during tasks of planning (Just, Cherkassky, Keller, Kana, & Minshew, 2007), response inhibition (Kana et al., 2007), and in the ACC (Thakkar et al., 2008).
An examination of relationships between control deficits and clinically relevant behavioral symptoms can help to validate a cognitive control-based model, and to improve understanding of the pathophysiology of ASDs, and their co-morbidities. For example, impairments in cognitive control in ASDs may be related to the existence in this population of Attention Deficit Hyperactivity Disorder (ADHD) symptoms (Casey et al., 2007, Nigg and Casey, 2005). While current diagnostic nosologies do not allow ADHD and autistic disorders to be diagnosed simultaneously, multiple studies have shown high rates of co-morbid attention deficit disorder (ADD) in individuals with ASDs (e.g. Verté et al., 2006). Brieber et al. (2007) observed that children with ADHD and children with autism displayed comparable ADHD symptoms, gray matter reductions in the left medial temporal lobe, and higher gray matter volumes in left inferior parietal cortex. Parietal atypicalities in both groups were interpreted as related to attention deficits. Functional imaging studies of ADHD have found hypoactivation of the anterior cingulate cortex (Durston et al., 2003) and fronto-parietal abnormalities (Booth et al., 2005, Dickstein et al., 2006, Durston et al., 2003). Thus, similar patterns of cingulate and fronto-parietal activity may be observed in individuals with ASDs.
In the current study, we used event-related fMRI, to investigate the neural correlates of cognitive control in a large sample of adolescents aged 12–18 with ASDs and typical development, and to examine the relationships between indices of neural activity and behavioral measures of inattention. The Preparing to Overcome Prepotency (POP) Task, which assesses the effects of advance preparation on overcoming stimulus–response incompatibility has been examined in typically developing young adults, schizophrenia patients, and older adults. Studies have found increased activation in DLPFC (BA 9), anterior frontal (BA 10), parietal cortex (BA 7 and BA 40) and ACC (BA 32) regions during the cue phase of the task. In the probe phase, where subjects execute a motor response, medial frontal (BA 6 and BA 32), and left parietal lobule (BA 7 and BA 40) activation has been observed (Barber and Carter, 2005, Rosano et al., 2005, Snitz et al., 2005). Based on these results as well as those from fMRI studies in autism showing a general pattern of hypoactivation in frontal and parietal regions, our first hypothesis was that individuals with ASDs would show significantly less neural activation in prefrontal, parietal, and anterior cingulate cortices relative to control subjects during the cue phase of the task. Second, given the suggestion that autism is a disorder of reduced connectivity and that impairments in cognitive control could be due to reduced connectivity between frontal, parietal, and ACC regions (Kana et al., 2007), we hypothesized the autism group would show reduced connectivity and integration between these brain regions. Finally, based on the ADHD literature, we hypothesized that activation in fronto-parietal and ACC regions would be related to task performance and ADHD symptoms.
This study helps fill the gap in the pediatric neuroimaging literature on executive functions in ASDs. It employs a large stimulant and antipsychotic-free sample with a gender ratio consistent with the patient population; uses two forms of functional connectivity analysis – including the time series correlation method that has been used in autism research, and the beta series method, which is a natural extension of this method – to establish convergent validity of findings; and examines brain–behavior relationships by investigating relationships between activation and connectivity patterns using measures of attention deficit disorder symptoms.
Section snippets
Participants
Thirty-two subjects with ASDs and 32 subjects with typical development were enrolled in the study. However, 10 subjects with ASDs and 9 subjects with typical development were excluded due to excess motion in the scanner. This left 22 subjects with ASDs (mean age = 15.2 years, standard deviation [SD] = 1.7) and 23 subjects with typical development (mean age = 16.0, SD = 2.0) who are described in this manuscript. Based on the male to female gender ratio of approximately 4:1 in the population of
Behavioral performance
To examine differences in trimmed mean reaction times for red versus green cues, a 2 × 2 analysis of variance (ANOVA) was performed where trial type (red versus green) was the within subjects factor, and group (ASD versus typical) was the between subjects factor. For mean reaction times on red versus green trials, there was a main effect of trial type (F(1, 43) = 24.4, p < .001, ), however the main effect of group and the interaction of trial type and group were not significant. Analysis of
Discussion
The first hypothesis of this study was largely confirmed. In the cue phase of the task, a between group comparison for the red minus green contrast indicated that adolescents with ASDs showed less frontal (BA 10), parietal (BA 7 and BA 40), and occipital (BA 18) activation than typically developing participants. The red minus green trial contrast was further explored by examining activation following green and red cues separately. Individuals with ASDs and typical development showed a similar
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