Comparing data quality from an online and in-person lab sample on dynamic theory of mind tasks.

Nearly half the published research in psychology is conducted with online samples, but the preponderance of these studies rely primarily on self-report measures. The current study validated data quality from an online sample on a novel, dynamic task by comparing performance between an in-lab and online sample on two dynamic measures of theory of mind-the ability to infer others' mental states. Theory of mind is a cognitively complex construct that has been widely studied across multiple domains of psychology. One task was based on the show The Office®, and has been previously validated by the authors with in-lab samples. The second was a novel task based on the show Nathan for You®, which was selected to account for familiarity effects associated with The Office. Both tasks measured various dimensions of theory of mind (inferring beliefs, understanding motivations, detecting deception, identifying faux pas, and understanding emotions). The in-person lab samples (N = 144 and 177, respectively) completed the tasks between-subject, whereas the online sample (N = 347 from Prolific Academic) completed them within-subject, with order counterbalanced. The online sample's performance across both tasks was reliable (Cronbach's α = .66). For The Office, the in-person sample outperformed the online sample on some types of theory of mind, but this was driven by their greater familiarity with the show. Indeed, for the relatively unfamiliar show Nathan for You, performance did not differ between the two samples. Together, these results suggest that crowdsourcing platforms elicit reliable performance on novel, dynamic, complex tasks.

High-amplitude cofluctuations in cortical activity drive functional connectivity.

Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network's modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research.

Edge-centric analysis of time-varying functional brain networks with applications in autism spectrum disorder.

The interaction between brain regions changes over time, which can be characterized using time-varying functional connectivity (tvFC). The common approach to estimate tvFC uses sliding windows and offers limited temporal resolution. An alternative method is to use the recently proposed edge-centric approach, which enables the tracking of moment-to-moment changes in co-fluctuation patterns between pairs of brain regions. Here, we first examined the dynamic features of edge time series and compared them to those in the sliding window tvFC (sw-tvFC). Then, we used edge time series to compare subjects with autism spectrum disorder (ASD) and healthy controls (CN). Our results indicate that relative to sw-tvFC, edge time series captured rapid and bursty network-level fluctuations that synchronize across subjects during movie-watching. The results from the second part of the study suggested that the magnitude of peak amplitude in the collective co-fluctuations of brain regions (estimated as root sum square (RSS) of edge time series) is similar in CN and ASD. However, the trough-to-trough duration in RSS signal is greater in ASD, compared to CN. Furthermore, an edge-wise comparison of high-amplitude co-fluctuations showed that the within-network edges exhibited greater magnitude fluctuations in CN. Our findings suggest that high-amplitude co-fluctuations captured by edge time series provide details about the disruption of functional brain dynamics that could potentially be used in developing new biomarkers of mental disorders.

Video-evoked fMRI BOLD responses are highly consistent across different data acquisition sites.

Naturalistic imaging paradigms, in which participants view complex videos in the scanner, are increasingly used in human cognitive neuroscience. Videos evoke temporally synchronized brain responses that are similar across subjects as well as within subjects, but the reproducibility of these brain responses across different data acquisition sites has not yet been quantified. Here, we characterize the consistency of brain responses across independent samples of participants viewing the same videos in functional magnetic resonance imaging (fMRI) scanners at different sites (Indiana University and Caltech). We compared brain responses collected at these different sites for two carefully matched datasets with identical scanner models, acquisition, and preprocessing details, along with a third unmatched dataset in which these details varied. Our overall conclusion is that for matched and unmatched datasets alike, video-evoked brain responses have high consistency across these different sites, both when compared across groups and across pairs of individuals. As one might expect, differences between sites were larger for unmatched datasets than matched datasets. Residual differences between datasets could in part reflect participant-level variability rather than scanner- or data- related effects. Altogether our results indicate promise for the development and, critically, generalization of video fMRI studies of individual differences in healthy and clinical populations alike.

Temporal fluctuations in the brain's modular architecture during movie-watching.

Brain networks are flexible and reconfigure over time to support ongoing cognitive processes. However, tracking statistically meaningful reconfigurations across time has proven difficult. This has to do largely with issues related to sampling variability, making instantaneous estimation of network organization difficult, along with increased reliance on task-free (cognitively unconstrained) experimental paradigms, limiting the ability to interpret the origin of changes in network structure over time. Here, we address these challenges using time-varying network analysis in conjunction with a naturalistic viewing paradigm. Specifically, we developed a measure of inter-subject network similarity and used this measure as a coincidence filter to identify synchronous fluctuations in network organization across individuals. Applied to movie-watching data, we found that periods of high inter-subject similarity coincided with reductions in network modularity and increased connectivity between cognitive systems. In contrast, low inter-subject similarity was associated with increased system segregation and more rest-like architectures. We then used a data-driven approach to uncover clusters of functional connections that follow similar trajectories over time and are more strongly correlated during movie-watching than at rest. Finally, we show that synchronous fluctuations in network architecture over time can be linked to a subset of features in the movie. Our findings link dynamic fluctuations in network integration and segregation to patterns of inter-subject similarity, and suggest that moment-to-moment fluctuations in functional connectivity reflect shared cognitive processing across individuals.

Accurate prediction of individual subject identity and task, but not autism diagnosis, from functional connectomes.

Despite enthusiasm about the potential for using fMRI-based functional connectomes in the development of biomarkers for autism spectrum disorder (ASD), the literature is full of negative findings-failures to distinguish ASD functional connectomes from those of typically developing controls (TD)-and positive findings that are inconsistent across studies. Here, we report on a new study designed to either better differentiate ASD from TD functional connectomes-or, alternatively, to refine our understanding of the factors underlying the current state of affairs. We scanned individuals with ASD and controls both at rest and while watching videos with social content. Using multiband fMRI across repeat sessions, we improved both data quantity and scanning duration by collecting up to 2 hr of data per individual. This is about 50 times the typical number of temporal samples per individual in ASD fcMRI studies. We obtained functional connectomes that were discriminable, allowing for near-perfect individual identification regardless of diagnosis, and equally reliable in both groups. However, contrary to what one might expect, we did not consistently or robustly observe in the ASD group either reductions in similarity to TD functional connectivity (FC) patterns or shared atypical FC patterns. Accordingly, FC-based predictions of diagnosis group achieved accuracy levels around chance. However, using the same approaches to predict scan type (rest vs. video) achieved near-perfect accuracy. Our findings suggest that neither the limitations of resting state as a "task," data resolution, data quantity, or scan duration can be considered solely responsible for failures to differentiate ASD from TD functional connectomes.

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies.

A rapidly growing number of studies on autism spectrum disorder (ASD) have used resting-state fMRI to identify alterations of functional connectivity, with the hope of identifying clinical biomarkers or underlying neural mechanisms. However, results have been largely inconsistent across studies, and there remains a pressing need to determine the primary factors influencing replicability. Here, we used resting-state fMRI data from the Autism Brain Imaging Data Exchange to investigate two potential factors: denoising strategy and data site (which differ in terms of sample, data acquisition, etc.). We examined the similarity of both group-averaged functional connectomes and group-level differences (ASD vs. control) across 33 denoising pipelines and four independently-acquired datasets. The group-averaged connectomes were highly consistent across pipelines (r = 0.92 ± 0.06) and sites (r = 0.88 ± 0.02). However, the group differences, while still consistent within site across pipelines (r = 0.76 ± 0.12), were highly inconsistent across sites regardless of choice of denoising strategies (r = 0.07 ± 0.04), suggesting lack of replication may be strongly influenced by site and/or cohort differences. Across-site similarity remained low even when considering the data at a large-scale network level or when considering only the most significant edges. We further show through an extensive literature survey that the parameters chosen in the current study (i.e., sample size, age range, preprocessing methods) are quite representative of the published literature. These results highlight the importance of examining replicability in future studies of ASD, and, more generally, call for extra caution when interpreting alterations in functional connectivity across groups of individuals.

Volitional eye movement control and ADHD traits: a twin study.

BACKGROUND: Top-down volitional command of eye movements may serve as a candidate endophenotype of ADHD, an important function underlying goal-directed action in everyday life. In this twin study, we examined the relation between performance on a response inhibition eye-tracking paradigm and parent-rated ADHD traits in a population-based twin sample. We hypothesized that altered eye movement control is associated with the severity of ADHD traits and that this association is attributable to genetic factors. METHODS: A total of 640 twins (320 pairs, 50% monozygotic) aged 9-14 years) from the Child and Adolescent Twin Study in Sweden (CATSS) participated. Twins performed the antisaccade task indexing inhibitory alterations as either direction errors (following exogenous cues rather than instructions) or premature anticipatory eye movements (failure to wait for cues). We calculated the associations of eye movement control and ADHD traits using linear regression mixed-effects models and genetic and environmental influences with multivariate twin models. RESULTS: Premature anticipatory eye movements were positively associated with inattentive traits (ß = .17; 95% CI: 0.04, 0.31), while controlling for hyperactive behaviors and other covariates. Both premature anticipatory eye movements and inattention were heritable (h2  = 0.40, 95% CI: 0.22, 0.56; h2  = 0.55; 95% CI: 0.42, 0.65; respectively), and their genetic correlation was small but statistically significant (r = .19, 95% CI: 0.02, 0.36). However, the genetic correlation did not remain significant after adjusting for covariates (age, sex, hyperactivity traits, IQ). No link was found between direction errors and ADHD traits. CONCLUSIONS: This study indicates that there is a specific, genetically influenced, relation between top-down eye movement control and the inattentive traits typical of ADHD.

Identifying and characterizing systematic temporally-lagged BOLD artifacts.

Residual noise in the BOLD signal remains problematic for fMRI - particularly for techniques such as functional connectivity, where findings can be spuriously influenced by noise sources that can covary with individual differences. Many such potential noise sources - for instance, motion and respiration - can have a temporally lagged effect on the BOLD signal. Thus, here we present a tool for assessing residual lagged structure in the BOLD signal that is associated with nuisance signals, using a construction similar to a peri-event time histogram. Using this method, we find that framewise displacements - both large and very small - were followed by structured, prolonged, and global changes in the BOLD signal that depend on the magnitude of the preceding displacement and extend for tens of seconds. This residual lagged BOLD structure was consistent across datasets, and independently predicted considerable variance in the global cortical signal (as much as 30-40% in some subjects). Mean functional connectivity estimates varied similarly as a function of displacements occurring many seconds in the past, even after strict censoring. Similar patterns of residual lagged BOLD structure were apparent following respiratory fluctuations (which covaried with framewise displacements), implicating respiration as one likely mechanism underlying the displacement-linked structure observed. Global signal regression largely attenuates this artifactual structure. These findings suggest the need for caution in interpreting results of individual difference studies where noise sources might covary with the individual differences of interest, and highlight the need for further development of preprocessing techniques for mitigating such structure in a more nuanced and targeted manner.

Idiosyncratic brain activation patterns are associated with poor social comprehension in autism.

Autism spectrum disorder (ASD) features profound social deficits but neuroimaging studies have failed to find any consistent neural signature. Here we connect these two facts by showing that idiosyncratic patterns of brain activation are associated with social comprehension deficits. Human participants with ASD (N = 17) and controls (N = 20) freely watched a television situation comedy (sitcom) depicting seminaturalistic social interactions ("The Office", NBC Universal) in the scanner. Intersubject correlations in the pattern of evoked brain activation were reduced in the ASD group-but this effect was driven entirely by five ASD subjects whose idiosyncratic responses were also internally unreliable. The idiosyncrasy of these five ASD subjects was not explained by detailed neuropsychological profile, eye movements, or data quality; however, they were specifically impaired in understanding the social motivations of characters in the sitcom. Brain activation patterns in the remaining ASD subjects were indistinguishable from those of control subjects using multiple multivariate approaches. Our findings link neurofunctional abnormalities evoked by seminaturalistic stimuli with a specific impairment in social comprehension, and highlight the need to conceive of ASD as a heterogeneous classification.

Prior expectations about where other people are likely to direct their attention systematically influence gaze perception.

Different locations in the visual environment vary greatly in terms of how likely they are to draw a person's attention. When inferring the most likely target of another person's gaze, it would therefore be a reasonable strategy to incorporate expectations about the relative visual salience of these various locations, weighing this prior knowledge against incoming social signals (e.g., eye cues). This Bayesian approach to modeling gaze perception has informed computer vision techniques, but whether this model accounts well for human performance remains an untested hypothesis. We present subjects with a "gazer" fixating his eyes on various locations on a two-dimensional surface, and project arbitrary photographic images onto that surface. Subjects judge where the gazer is looking in each image. A full Bayesian model, which takes image salience information into account, fits subjects' gaze judgments better than a reduced model that only considers the perceived direction of the gazer's eyes. Varying the amount of time the subject is allowed to view the gazer reveals that center bias tends to dominate gaze judgments early, whereas salient features specific to the projected image influence judgments at longer viewing durations.

Agenesis of the corpus callosum and autism: a comprehensive comparison.

The corpus callosum, with its ∼200 million axons, remains enigmatic in its contribution to cognition and behaviour. Agenesis of the corpus callosum is a congenital condition in which the corpus callosum fails to develop; such individuals exhibit localized deficits in non-literal language comprehension, humour, theory of mind and social reasoning. These findings together with parent reports suggest that behavioural and cognitive impairments in subjects with callosal agenesis may overlap with the profile of autism spectrum disorders, particularly with respect to impairments in social interaction and communication. To provide a comprehensive test of this hypothesis, we directly compared a group of 26 adults with callosal agenesis to a group of 28 adults with a diagnosis of autism spectrum disorder but no neurological abnormality. All participants had full-scale intelligence quotient scores >78 and groups were matched on age, handedness, and gender ratio. Using the Autism Diagnostic Observation Schedule together with current clinical presentation to assess autistic symptomatology, we found that 8/26 (about a third) of agenesis subjects presented with autism. However, more formal diagnosis additionally involving recollective parent-report measures regarding childhood behaviour showed that only 3/22 met complete formal criteria for an autism spectrum disorder (parent reports were unavailable for four subjects). We found no relationship between intelligence quotient and autism symptomatology in callosal agenesis, nor evidence that the presence of any residual corpus callosum differentiated those who exhibited current autism spectrum symptoms from those who did not. Relative to the autism spectrum comparison group, parent ratings of childhood behaviour indicated children with agenesis were less likely to meet diagnostic criteria for autism, even for those who met autism spectrum criteria as adults, and even though there was no group difference in parent report of current behaviours. The findings suggest two broad conclusions. First, they support the hypothesis that congenital disruption of the corpus callosum constitutes a major risk factor for developing autism. Second, they quantify specific features that distinguish autistic behaviour associated with callosal agenesis from autism more generally. Taken together, these two findings also leverage specific questions for future investigation: what are the distal causes (genetic and environmental) determining both callosal agenesis and its autistic features, and what are the proximal mechanisms by which absence of the callosum might generate autistic symptomatology?

Largely typical patterns of resting-state functional connectivity in high-functioning adults with autism.

A leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, yet the majority of studies report effects that are either very weak, inconsistent across studies, or explain results incompletely. Here we apply multiple analytical approaches to resting-state BOLD-fMRI data at the whole-brain level. Neurotypical and high-functioning adults with autism displayed very similar patterns and strengths of resting-state connectivity. We found only limited evidence in autism for abnormal resting-state connectivity at the regional level and no evidence for altered connectivity at the whole-brain level. Regional abnormalities in functional connectivity in autism spectrum disorder were primarily in the frontal and temporal cortices. Within these regions, functional connectivity with other brain regions was almost exclusively lower in the autism group. Further examination showed that even small amounts of head motion during scanning have large effects on functional connectivity measures and must be controlled carefully. Consequently, we suggest caution in the interpretation of apparent positive findings until all possible confounding effects can be ruled out. Additionally, we do not rule out the possibility that abnormal connectivity in autism is evident at the microstructural synaptic level, which may not be reflected sensitively in hemodynamic changes measured with BOLD-fMRI.

Differential electrophysiological response during rest, self-referential, and non-self-referential tasks in human posteromedial cortex.

The electrophysiological basis for higher brain activity during rest and internally directed cognition within the human default mode network (DMN) remains largely unknown. Here we use intracranial recordings in the human posteromedial cortex (PMC), a core node within the DMN, during conditions of cued rest, autobiographical judgments, and arithmetic processing. We found a heterogeneous profile of PMC responses in functional, spatial, and temporal domains. Although the majority of PMC sites showed increased broad gamma band activity (30-180 Hz) during rest, some PMC sites, proximal to the retrosplenial cortex, responded selectively to autobiographical stimuli. However, no site responded to both conditions, even though they were located within the boundaries of the DMN identified with resting-state functional imaging and similarly deactivated during arithmetic processing. These findings, which provide electrophysiological evidence for heterogeneity within the core of the DMN, will have important implications for neuroimaging studies of the DMN.

Smartphone-based gaze estimation for in-home autism research.

Atypical gaze patterns are a promising biomarker of autism spectrum disorder. To measure gaze accurately, however, it typically requires highly controlled studies in the laboratory using specialized equipment that is often expensive, thereby limiting the scalability of these approaches. Here we test whether a recently developed smartphone-based gaze estimation method could overcome such limitations and take advantage of the ubiquity of smartphones. As a proof-of-principle, we measured gaze while a small sample of well-assessed autistic participants and controls watched videos on a smartphone, both in the laboratory (with lab personnel) and in remote home settings (alone). We demonstrate that gaze data can be efficiently collected, in-home and longitudinally by participants themselves, with sufficiently high accuracy (gaze estimation error below 1° visual angle on average) for quantitative, feature-based analysis. Using this approach, we show that autistic individuals have reduced gaze time on human faces and longer gaze time on non-social features in the background, thereby reproducing established findings in autism using just smartphones and no additional hardware. Our approach provides a foundation for scaling future research with larger and more representative participant groups at vastly reduced cost, also enabling better inclusion of underserved communities.

Fluorescent ratiometric indicators based on Cu(II)-induced changes in poly(NIPAM) microparticle volume.

Microparticles consisting of the thermal responsive polymer N-isopropyl acrylamide (polyNIPAM), a metal ion-binding ligand and a fluorophore pair that undergoes fluorescence resonance energy transfer (FRET) have been prepared and characterized. Upon the addition of Cu(II), the microparticles swell or contract depending on whether charge is introduced or neutralized on the polymer backbone. The variation in microparticle morphology is translated into changes in emission of each fluorophore in the FRET pair. By measuring the emission intensity ratio between the FRET pair upon Cu(II) addition, the concentration of metal ion in solution can be quantified. This ratiometric fluorescent indicator is the newest technique in an ongoing effort to use emission spectroscopy to monitor Cu(II) thermodynamic activity in environmental water samples.

Determining Whether Older Adults Use Similar Strategies to Young Adults in Theory of Mind Tasks.

OBJECTIVES: Theory of mind-the ability to infer others' mental states-declines over the life span, potentially due to cognitive decline. However, it is unclear whether deficits emerge because older adults use the same strategies as young adults, albeit less effectively, or use different or no strategies. The current study compared the similarity of older adults' theory of mind errors to young adults' and a random model. METHODS: One hundred twenty older adults (MAge = 74.68 years; 64 female) and 111 young adults (MAge = 19.1; 61 female) completed a novel theory of mind task (clips from an episode of the sitcom The Office®), and a standard measure of cognitive function (Logical Memory II). Monte Carlo resampling estimated the likelihood that older adults' error patterns were more similar to young adults' or a random distribution. RESULTS: Age deficits emerged on the theory of mind task. Poorer performance was associated with less similarity to young adults' response patterns. Overall, older adults' response patterns were ~2.7 million times more likely to match young adults' than a random model. Critically, one fourth of older adults' errors were more similar to the random distribution. Poorer memory ability contributed to this relationship. DISCUSSION: Age deficits in theory of mind performance may be driven by a subset of older adults and be related to disparities in strategy use. A certain amount of cognitive ability may be necessary for older adults to engage similar strategies to young adults' during theory of mind.

Intact bilateral resting-state networks in the absence of the corpus callosum.

Temporal correlations between different brain regions in the resting-state BOLD signal are thought to reflect intrinsic functional brain connectivity (Biswal et al., 1995; Greicius et al., 2003; Fox et al., 2007). The functional networks identified are typically bilaterally distributed across the cerebral hemispheres, show similarity to known white matter connections (Greicius et al., 2009), and are seen even in anesthetized monkeys (Vincent et al., 2007). Yet it remains unclear how they arise. Here we tested two distinct possibilities: (1) functional networks arise largely from structural connectivity constraints, and generally require direct interactions between functionally coupled regions mediated by white-matter tracts; and (2) functional networks emerge flexibly with the development of normal cognition and behavior and can be realized in multiple structural architectures. We conducted resting-state fMRI in eight adult humans with complete agenesis of the corpus callosum (AgCC) and normal intelligence, and compared their data to those from eight healthy matched controls. We performed three main analyses: anatomical region-of-interest-based correlations to test homotopic functional connectivity, independent component analysis (ICA) to reveal functional networks with a data-driven approach, and ICA-based interhemispheric correlation analysis. Both groups showed equivalently strong homotopic BOLD correlation. Surprisingly, almost all of the group-level independent components identified in controls were observed in AgCC and were predominantly bilaterally symmetric. The results argue that a normal complement of resting-state networks and intact functional coupling between the hemispheres can emerge in the absence of the corpus callosum, favoring the second over the first possibility listed above.

Intermolecular approach to metal ion indicators based on polymer phase transitions coupled to fluorescence resonance energy transfer.

An approach to ratiometric fluorescence detection of quenching metal ions was devised by copolymerizing N-isopropylacrylamide with small percentages of bipyridine and amine monomers. The copolymer was divided into two portions. The amine group on one portion was functionalized with AlexaFluor555 (donor fluorophore) and the other with AlexaFluor647 (acceptor fluorophore). The indicator consists of a mixture of these two portions. Aggregation above the lower critical solution temperature (LCST) of this copolymer brings about a large increase in fluorescence resonance energy transfer (FRET). Addition of Cu(II) and other complexing metal ions to the aggregated copolymer introduces charge onto the backbone, causing the copolymer to redissolve with a resulting decrease in FRET. The ratio of acceptor to donor fluorescence varies with Cu(II) concentration. A plot of intensity ratio vs. pCu is sigmoidal with a log K(f) of 6.1 for the Cu(II)-bipyridine complex. The data are consistent with the formation of a 1 : 1 complex. The copolymer responds to higher concentrations of other transition metal ions. The selectivity for Cu(II) is consistent with the literature values for 1 : 1 formation constants for bipyridine with metal ions.