Jason S. Nomi

Developmental changes in large-scale network connectivity in autism

Background Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD. Methods The current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups. Results We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11–18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or between-network differences in functional network connectivity compared with neurotypical age-matched individuals. Conclusions Characterizing within- and between-network functional connectivity in age-stratified cohorts of individuals with ASD and TD individuals demonstrates that functional connectivity atypicalities in the disorder are not uniform across the lifespan. These results demonstrate how explicitly characterizing participant age and adopting a developmental perspective can lead to a more nuanced understanding of atypicalities of functional brain connectivity in autism.

Dynamic functional network connectivity reveals unique and overlapping profiles of insula subdivisions

The human insular cortex consists of functionally diverse subdivisions that engage during tasks ranging from interoception to cognitive control. The multiplicity of functions subserved by insular subdivisions calls for a nuanced investigation of their functional connectivity profiles. Four insula subdivisions (dorsal anterior, dAI; ventral, VI; posterior, PI; middle, MI) derived using a data‐driven approach were subjected to static‐ and dynamic functional network connectivity (s‐FNC and d‐FNC) analyses. Static‐FNC analyses replicated previous work demonstrating a cognition‐emotion‐interoception division of the insula, where the dAI is functionally connected to frontal areas, the VI to limbic areas, and the PI and MI to sensorimotor areas. Dynamic‐FNC analyses consisted of k‐means clustering of sliding windows to identify variable insula connectivity states. The d‐FNC analysis revealed that the most frequently occurring dynamic state mirrored the cognition‐emotion‐interoception division observed from the s‐FNC analysis, with less frequently occurring states showing overlapping and unique subdivision connectivity profiles. In two of the states, all subdivisions exhibited largely overlapping profiles, consisting of subcortical, sensory, motor, and frontal connections. Two other states showed the dAI exhibited a unique connectivity profile compared with other insula subdivisions. Additionally, the dAI exhibited the most variable functional connections across the s‐FNC and d‐FNC analyses, and was the only subdivision to exhibit dynamic functional connections with regions of the default mode network. These results highlight how a d‐FNC approach can capture functional dynamics masked by s‐FNC approaches, and reveal dynamic functional connections enabling the functional flexibility of the insula across time. Hum Brain Mapp 37:1770–1787, 2016.

Can Déjà Vu Result from Similarity to a Prior Experience? Support for the Similarity Hypothesis of Déjà Vu

The strange feeling of having been somewhere or done something before—even though there is evidence to the contrary—is called déjà vu. Although déjà vu is beginning to receive attention among scientists (Brown, 2003, 2004), few studies have empirically investigated the phenomenon. We investigated the hypothesis that déjà vu is related to feelings of familiarity and that it can result from similarity between a novel scene and that of a scene experienced in one’s past. We used a variation of the recognition-without-recall method of studying familiarity (Cleary, 2004) to examine instances in which participants failed to recall a studied scene in response to a configurally similar novel test scene. In such instances, resemblance to a previously viewed scene increased both feelings of familiarity and of déjà vu. Furthermore, in the absence of recall, resemblance of a novel scene to a previously viewed scene increased the probability of a reported déjà vu state for the novel scene, and feelings of familiarity with a novel scene were directly related to feelings of being in a déjà vu state.

On the neural networks of empathy: A principal component analysis of an fMRI study

BackgroundHuman emotional expressions serve an important communicatory role allowing the rapid transmission of valence information among individuals. We aimed at exploring the neural networks mediating the recognition of and empathy with human facial expressions of emotion.MethodsA principal component analysis was applied to event-related functional magnetic imaging (fMRI) data of 14 right-handed healthy volunteers (29 +/- 6 years). During scanning, subjects viewed happy, sad and neutral face expressions in the following conditions: emotion recognition, empathizing with emotion, and a control condition of simple object detection. Functionally relevant principal components (PCs) were identified by planned comparisons at an alpha level of p < 0.001.ResultsFour PCs revealed significant differences in variance patterns of the conditions, thereby revealing distinct neural networks: mediating facial identification (PC 1), identification of an expressed emotion (PC 2), attention to an expressed emotion (PC 12), and sense of an emotional state (PC 27).ConclusionOur findings further the notion that the appraisal of human facial expressions involves multiple neural circuits that process highly differentiated cognitive aspects of emotion.

Face processing in autism spectrum disorders: From brain regions to brain networks.

Autism spectrum disorder (ASD) is characterized by reduced attention to social stimuli including the human face. This hypo-responsiveness to stimuli that are engaging to typically developing individuals may result from dysfunctioning motivation, reward, and attention systems in the brain. Here we review an emerging neuroimaging literature that emphasizes a shift from focusing on hypo-activation of isolated brain regions such as the fusiform gyrus, amygdala, and superior temporal sulcus in ASD to a more holistic approach to understanding face perception as a process supported by distributed cortical and subcortical brain networks. We summarize evidence for atypical activation patterns within brain networks that may contribute to social deficits characteristic of the disorder. We conclude by pointing to gaps in the literature and future directions that will continue to shed light on aspects of face processing in autism that are still under-examined. In particular, we highlight the need for more developmental studies and studies examining ecologically valid and naturalistic social stimuli.

Familiarity from the configuration of objects in 3-dimensional space and its relation to déjà vu: a virtual reality investigation.

Déjà vu is the striking sense that the present situation feels familiar, alongside the realization that it has to be new. According to the Gestalt familiarity hypothesis, déjà vu results when the configuration of elements within a scene maps onto a configuration previously seen, but the previous scene fails to come to mind. We examined this using virtual reality (VR) technology. When a new immersive VR scene resembled a previously-viewed scene in its configuration but people failed to recall the previously-viewed scene, familiarity ratings and reports of déjà vu were indeed higher than for completely novel scenes. People also exhibited the contrasting sense of newness and of familiarity that is characteristic of déjà vu. Familiarity ratings and déjà vu reports among scenes recognized as new increased with increasing feature-match of a scene to one stored in memory, suggesting that feature-matching can produce familiarity and déjà vu when recall fails.

Odor recognition without identification

Odors are notoriously difficult to identify, yet an odor can often lead to a sense of recognition, despite an inability to identify it. In the present study, we examined this phenomenon using the recognition-withoutidentification paradigm. Participants studied either odor names alone or odor names that were accompanied by scratch-and-sniff stickers containing their corresponding scents. At test, the participants were presented with blank scratch-and-sniff stickers, half of which corresponded to items that were studied and half of which did not. The participants attempted to identify each test odor, as well as to rate the likelihood that it corresponded to a studied item. In addition, the participants indicated whether they were in a tip-of-the-tongue (TOT) state for a given odor’s name. Odor recognition without identification was found, but only when the participants had actually smelled the test odor at study; it was not found when the participants only studied odor names and were then tested with odors, suggesting that this effect is an episode-specific, perceptually driven phenomenon. Despite this difference, an overall TOT-attribution effect, whereby recognition ratings were higher during TOT states than during non-TOT states, was shown across conditions.

Correspondence between evoked and intrinsic functional brain network configurations

Much of the literature exploring differences between intrinsic and task‐evoked brain architectures has examined changes in functional connectivity patterns between specific brain regions. While informative, this approach overlooks important overall functional changes in hub organization and network topology that may provide insights about differences in integration between intrinsic and task‐evoked states. Examination of changes in overall network organization, such as a change in the concentration of hub nodes or a quantitative change in network organization, is important for understanding the underlying processes that differ between intrinsic and task‐evoked brain architectures. The present study used graph‐theoretical techniques applied to publicly available neuroimaging data collected from a large sample of individuals (N = 202), and a within‐subject design where resting‐state and several task scans were collected from each participant as part of the Human Connectome Project. We demonstrate that differences between intrinsic and task‐evoked brain networks are characterized by a task‐general shift in high‐connectivity hubs from primarily sensorimotor/auditory processing areas during the intrinsic state to executive control/salience network areas during task performance. In addition, we demonstrate that differences between intrinsic and task‐evoked architectures are associated with changes in overall network organization, such as increases in network clustering, global efficiency and integration between modules. These findings offer a new perspective on the principles guiding functional brain organization by identifying unique and divergent properties of overall network organization between the resting‐state and task performance. Hum Brain Mapp 38:1992–2007, 2017.

Chronnectomic patterns and neural flexibility underlie executive function

ABSTRACT Despite extensive research into executive function (EF), the precise relationship between brain dynamics and flexible cognition remains unknown. Using a large, publicly available dataset (189 participants), we find that functional connections measured throughout 56 min of resting state fMRI data comprise five distinct connectivity states. Elevated EF performance as measured outside of the scanner was associated with greater episodes of more frequently occurring connectivity states, and fewer episodes of less frequently occurring connectivity states. Frequently occurring states displayed metastable properties, where cognitive flexibility may be facilitated by attenuated correlations and greater functional connection variability. Less frequently occurring states displayed properties consistent with low arousal and low vigilance. These findings suggest that elevated EF performance may be associated with the propensity to occupy more frequently occurring brain configurations that enable cognitive flexibility, while avoiding less frequently occurring brain configurations related to low arousal/vigilance states. The current findings offer a novel framework for identifying neural processes related to individual differences in executive function.

When word identification fails: ERP correlates of recognition without identification and of word identification failure

Recognition without identification (RWI) refers to peoples ability to discriminate studied from unstudied items when the items themselves fail to be identified, as when people fail to identify words from fragments. We sought to identify the ERP correlates of word fragment RWI in an effort to better understand its underlying mechanisms; in so doing, we also examined the ERP correlates of word identification failure vs. success. We found the ERP correlate of the RWI effect to be the N300; greater negativity was shown for unidentified fragments of studied words than for unidentified fragments of unstudied words between 300-325 ms post test fragment onset. We further separated the ERPs according to whether subjects showed the behavioral RWI effect or not; the N300 effect emerged only among those subjects who showed the behavioral effect, suggesting that the N300 is related to the behavioral effect itself. With regard to the ERP correlates of word identification failure vs. success, we found very early indicators of later word identification success vs. failure (starting at 125 ms) that were independent of priming. These early effects may be preconscious markers of downstream word identification success vs. failure. We also found a later persistent negativity associated with successfully identified words that we propose to be associated with executive function and possibly the successful suppression of irrelevant words that might initially come to mind when attempting to complete a unique word fragment; word fragment identification failure may sometimes be due to a failure to suppress irrelevant or incorrect words.