Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BACKGROUND

Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed.

METHODS

We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split).

RESULTS

In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset.

LIMITATIONS

The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects.

CONCLUSIONS

This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

Augmenting Frontal Dopamine Tone Enhances Maintenance over Gating Processes in Working Memory

The contents of working memory must be maintained in the face of distraction, but updated when appropriate. To manage these competing demands of stability and flexibility, maintained representations in working memory are complemented by distinct gating mechanisms that selectively transmit information into and out of memory stores. The operations of such dopamine-dependent gating systems in the midbrain and striatum and their complementary dopamine-dependent memory maintenance operations in the cortex may therefore be dissociable. If true, selective increases in cortical dopamine tone should preferentially enhance maintenance over gating mechanisms. To test this hypothesis, tolcapone, a catechol-O-methyltransferase inhibitor that preferentially increases cortical dopamine tone, was administered in a randomized, double-blind, placebo-controlled, within-subject fashion to 49 participants who completed a hierarchical working memory task that varied maintenance and gating demands. Tolcapone improved performance in a condition with higher maintenance requirements and reduced gating demands, reflected in a reduction in the slope of RTs across the distribution. Resting-state fMRI data demonstrated that the degree to which tolcapone improved performance in individual participants correlated with increased connectivity between a region important for stimulus response mappings (left dorsal premotor cortex) and cortical areas implicated in visual working memory, including the intraparietal sulcus and fusiform gyrus. Together, these results provide evidence that augmenting cortical dopamine tone preferentially improves working memory maintenance.

Patients with autism spectrum disorders display reproducible functional connectivity alterations

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

Adaptive behavior in autism: Minimal clinically important differences on the Vineland-II

Autism Spectrum Disorder (ASD) is associated with persistent impairments in adaptive abilities across multiple domains. These social, personal, and communicative impairments become increasingly pronounced with development, and are present regardless of IQ. The Vineland Adaptive Behavior Scales, Second Edition (Vineland-II) is the most commonly used instrument for quantifying these impairments, but minimal clinically important differences (MCIDs) on Vineland-II scores have not been rigorously established in ASD. We pooled data from several consortia/registries (EU-AIMS LEAP study, ABIDE-I, ABIDE-II, INFOR, Simons Simplex Collection and Autism Treatment Network [ATN]) and clinical investigations and trials (Stanford, Yale, Roche) resulting in a data set of over 9,000 individuals with ASD. Two approaches were used to estimate MCIDs: distribution-based methods and anchor-based methods. Distribution-based MCID [d-MCID] estimates included the standard error of the measurement, as well as one-fifth and one-half of the covariate-adjusted standard deviation (both cross-sectionally and longitudinally). Anchor-based MCID [a-MCID] estimates include the slope of linear regression of clinician ratings of severity on the Vineland-II score, the slope of linear regression of clinician ratings of longitudinal improvement category on Vineland-II change, the Vineland-II change score maximally differentiating clinical impressions of minimal versus no improvement, and equipercentile equating. Across strata, the Vineland-II Adaptive Behavior Composite standardized score MCID estimates range from 2.01 to 3.2 for distribution-based methods, and from 2.42 to 3.75 for sample-size-weighted anchor-based methods. Lower Vineland-II standardized score MCID estimates were observed for younger and more cognitively impaired populations. These MCID estimates enable users of Vineland-II to assess both the statistical and clinical significance of any observed change. Autism Res 2018, 11: 270-283. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

The Vineland Adaptive Behavior Scales (2nd edition; Vineland-II) is the most widely used scale for assessing day-to-day "adaptive" skills. Yet, it is unknown how much Vineland-II scores must change for those changes to be regarded as clinically significant. We pooled data from over 9,000 individuals with ASD to show that changes of 2-3.75 points on the Vineland-II Composite score represent the "minimal clinically-important difference." These estimates will help evaluate the benefits of potential new treatments for ASD.

The role of fMRI in drug development

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.

Working memory gating mechanisms explain developmental change in rule-guided behavior

Cognitive control requires choosing contextual information to update into working memory (input gating), maintaining it there (maintenance) stable against distraction, and then choosing which subset of maintained information to use in guiding action (output gating). Recent work has raised the possibility that the development of rule-guided behavior, in the transition from childhood to adolescence, is linked specifically to changes in the gating components of working memory (Amso, Haas, McShane, & Badre, 2014). Given the importance of effective rule-guided behavior for decision making in this developmental transition, we used hierarchical rule tasks to probe the precise developmental dynamics of working memory gating. This mechanistic precision informs ongoing efforts to train cognitive control and working memory operations across typical and atypical development. The results of Experiment 1 verified that the development of rule-guided behavior is uniquely linked to increasing hierarchical complexity but not to increasing maintenance demands across 1st, 2nd, and 3rd order rule tasks. Experiment 2 then investigated whether this developmental trajectory in rule-guided behavior is best explained by change in input gating or output gating. Further, as input versus output gating also tend to correlate with a more proactive versus reactive control strategy in these tasks, we assessed developmental change in the degree to which these two processes were deployed efficiently given the task. Experiment 2 shows that the developmental change observed in Experiment 1 and in Amso et al. (2014) is likely a result of increased efficacy of output gating processes, as well as greater strategic efficiency in that adolescents opt for this costly process less often than children.

The Necessity of Rostrolateral Prefrontal Cortex for Higher-Level Sequential Behavior

Frontal neocortex is thought to support our highest intellectual abilities, including our ability to plan and enact a sequence of tasks toward a desired goal. In everyday life, such task sequences are abstract in that they do not require consistent movement sequences and are often assembled "on the fly." Yet, remarkably little is known about the necessity of frontal sub-regions for such control. Participants repeatedly completed sequences of simple tasks during fMRI scanning. Rostrolateral prefrontal cortex (RLPFC) activation ramped over sequence position and reset at the initiation of each new sequence. To establish the necessity and function of RLPFC in this task, participants performed the sequential task while undergoing transcranial magnetic stimulation (TMS) of the RLPFC versus two prefrontal control regions. Across two independent experiments, only RLPFC stimulation increasingly disrupted task performance as each sequence progressed. These data establish RLPFC as necessary for uncertainty resolution during sequence-level control.

Parallel temporal dynamics in hierarchical cognitive control

Cognitive control allows us to follow abstract rules in order to choose appropriate responses given our desired outcomes. Cognitive control is often conceptualized as a hierarchical decision process, wherein decisions made at higher, more abstract levels of control asymmetrically influence lower-level decisions. These influences could evolve sequentially across multiple levels of a hierarchical decision, consistent with much prior evidence for central bottlenecks and seriality in decision-making processes. However, here, we show that multiple levels of hierarchical cognitive control are processed primarily in parallel. Human participants selected responses to stimuli using a complex, multiply contingent (third order) rule structure. A response deadline procedure allowed assessment of the accuracy and timing of decisions made at each level of the hierarchy. In contrast to a serial decision process, error rates across levels of the decision mostly declined simultaneously and at identical rates, with only a slight tendency to complete the highest level decision first. Simulations with a biologically plausible neural network model demonstrate how such parallel processing could emerge from a previously developed hierarchically nested frontostriatal architecture. Our results support a parallel processing model of cognitive control, in which uncertainty on multiple levels of a decision is reduced simultaneously.

Multiple gates on working memory

The contexts for action may be only transiently visible, accessible, and relevant. The corticobasal ganglia (BG) circuit addresses these demands by allowing the right motor plans to drive action at the right times, via a BG-mediated gate on motor representations. A long-standing hypothesis posits these same circuits are replicated in more rostral brain regions to support gating of cognitive representations. Key evidence now supports the prediction that BG can act as a gate on the input to working memory, as a gate on its output, and as a means of reallocating working memory representations rendered irrelevant by recent events. These discoveries validate key tenets of many computational models, circumscribe motor and cognitive models of recurrent cortical dynamics alone, and identify novel directions for research on the mechanisms of higher-level cognition.

A neural network model of individual differences in task switching abilities

We use a biologically grounded neural network model to investigate the brain mechanisms underlying individual differences specific to the selection and instantiation of representations that exert cognitive control in task switching. Existing computational models of task switching do not focus on individual differences and so cannot explain why task switching abilities are separable from other executive function (EF) abilities (such as response inhibition). We explore hypotheses regarding neural mechanisms underlying the "Shifting-Specific" and "Common EF" components of EF proposed in the Unity/Diversity model (Miyake & Friedman, 2012) and similar components in related theoretical frameworks. We do so by adapting a well-developed neural network model of working memory (Prefrontal cortex, Basal ganglia Working Memory or PBWM; Hazy, Frank, & O'Reilly, 2007) to task switching and the Stroop task, and comparing its behavior on those tasks under a variety of individual difference manipulations. Results are consistent with the hypotheses that variation specific to task switching (i.e., Shifting-Specific) may be related to uncontrolled, automatic persistence of goal representations, whereas variation general to multiple EFs (i.e., Common EF) may be related to the strength of PFC representations and their effect on processing in the remainder of the cognitive system. Moreover, increasing signal to noise ratio in PFC, theoretically tied to levels of tonic dopamine and a genetic polymorphism in the COMT gene, reduced Stroop interference but increased switch costs. This stability-flexibility tradeoff provides an explanation for why these two EF components sometimes show opposing correlations with other variables such as attention problems and self-restraint.

Corticostriatal output gating during selection from working memory

Convergent evidence suggests that corticostriatal interactions act as a gate to select the input to working memory (WM). However, not all information in WM is relevant for behavior simultaneously. For this reason, a second "output gate" might advantageously govern which contents of WM influence behavior. Here, we test whether frontostriatal circuits previously implicated in input gating also support output gating during selection from WM. fMRI of a hierarchical rule task with dissociable input and output gating demands demonstrated greater lateral prefrontal cortex (PFC) recruitment and frontostriatal connectivity during output gating. Moreover, PFC and striatum correlated with distinct behavioral profiles. Whereas PFC recruitment correlated with mean efficiency of selection from WM, striatal recruitment and frontostriatal interactions correlated with its reliability, as though such dynamics stochastically gate WM's output. These results support the output gating hypothesis, suggesting that contextual representations in PFC influence striatum to select which information in WM drives responding.

The practice of going helps children to stop: the importance of context monitoring in inhibitory control

How do we stop ourselves during ongoing action? Recent work implies that stopping per se is easy given sufficient monitoring of contextual cues signaling the need to change action. We test key implications of this idea for improving inhibitory control. Seven- to 9-year-old children practiced stopping an ongoing action or monitoring for cues that signaled the need to go again. Both groups subsequently showed better response inhibition in a Stop-Signal task than active controls, and practice monitoring yielded a dose-response relationship. When monitoring practice was optimized to occur while children engaged in responding, the greatest benefits were observed-even greater than from practicing stopping itself. These findings demonstrate the importance of monitoring processes in developing response inhibition and suggest promising new directions for interventions.

Working memory management and predicted utility

Given the limited capacity of working memory (WM), its resources should be allocated strategically. One strategy is filtering, whereby access to WM is granted preferentially to items with the greatest utility. However, reallocation of WM resources might be required if the utility of maintained information subsequently declines. Here, we present behavioral, computational, and neuroimaging evidence that human participants track changes in the predicted utility of information in WM. First, participants demonstrated behavioral costs when the utility of items already maintained in WM declined and resources should be reallocated. An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items. Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful. Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.

Delaying gratification depends on social trust

Delaying gratification is hard, yet predictive of important life outcomes, such as academic achievement and physical health. Prominent theories focus on the role of self-control, hypersensitivity to immediate rewards, and the cost of time spent waiting. However, delaying gratification may also require trust in people delivering future rewards as promised. To test the role of social trust, participants were presented with character vignettes and faces that varied in trustworthiness, and then choose between hypothetical smaller immediate or larger delayed rewards from those characters. Across two experiments, participants were less willing to wait for delayed rewards from less trustworthy characters, and perceived trustworthiness predicted willingness to delay gratification. These findings provide the first demonstration of a causal role for social trust in willingness to delay gratification, independent of other relevant factors, such as self-control or reward history. Thus, delaying gratification requires choosing not only a later reward, but a reward that is potentially less likely to be delivered, when there is doubt about the person promising it. Implications of this work include the need to revise prominent theories of delay of gratification, and new directions for interventions with populations characterized by impulsivity.

Why won't you do what I want? The informative failures of children and models

Computational models are powerful tools - too powerful, according to some. We argue that the idea that models can "do anything" is wrong, and describe how their failures have been informative. We present new work showing surprising diversity in the effects of feedback on children's task-switching, such that some children perseverate despite this feedback, other children switch as instructed, and yet others play an "opposites" game without truly switching to the newly-instructed task. We present simulations that demonstrate the failure of an otherwise-successful neural network model to capture this failure of children. Simulating this pattern motivates the inclusion of updating mechanisms that make contact with a growing literature on frontostriatal function, despite their absence in extant theories of the development of cognitive flexibility. We argue from this and other examples that computational models are more constrained than is typically acknowledged, and that their resulting failures can be theoretically illuminating.

Developing Cognitive Control: Three Key Transitions

The ability to flexibly break out of routine behaviors develops gradually and is essential for success in life. We discuss three key developmental transitions toward more flexible behavior. First, children develop an increasing ability to overcome habits by engaging cognitive control in response to environmental signals. Second, children shift from recruiting cognitive control reactively, as needed in the moment, to recruiting cognitive control proactively, in preparation for needing it. Third, children shift from relying on environmental signals for engaging cognitive control to becoming more self-directed. All three transitions can be understood in terms of the development of increasingly active and abstract goal representations in prefrontal cortex.

A unified framework for inhibitory control

Inhibiting unwanted thoughts, actions and emotions figures centrally in daily life, and the prefrontal cortex (PFC) is widely viewed as a source of this inhibitory control. We argue that the function of the PFC is best understood in terms of representing and actively maintaining abstract information, such as goals, which produces two types of inhibitory effects on other brain regions. Inhibition of some subcortical regions takes a directed global form, with prefrontal regions providing contextual information relevant to when to inhibit all processing in a region. Inhibition within neocortical (and some subcortical) regions takes an indirect competitive form, with prefrontal regions providing excitation of goal-relevant options. These distinctions are crucial for understanding the mechanisms of inhibition and how they can be impaired or improved.

From an executive network to executive control: a computational model of the n-back task

A paradigmatic test of executive control, the n-back task, is known to recruit a widely distributed parietal, frontal, and striatal "executive network," and is thought to require an equally wide array of executive functions. The mapping of functions onto substrates in such a complex task presents a significant challenge to any theoretical framework for executive control. To address this challenge, we developed a biologically constrained model of the n-back task that emergently develops the ability to appropriately gate, bind, and maintain information in working memory in the course of learning to perform the task. Furthermore, the model is sensitive to proactive interference in ways that match findings from neuroimaging and shows a U-shaped performance curve after manipulation of prefrontal dopaminergic mechanisms similar to that observed in studies of genetic polymorphisms and pharmacological manipulations. Our model represents a formal computational link between anatomical, functional neuroimaging, genetic, behavioral, and theoretical levels of analysis in the study of executive control. In addition, the model specifies one way in which the pFC, BG, parietal, and sensory cortices may learn to cooperate and give rise to executive control.