Neural circuit disruptions of eye gaze processing in autism spectrum disorder and schizophrenia: An activation likelihood estimation meta-analysis.

BACKGROUND: Impairment in social cognition, particularly eye gaze processing, is a shared feature common to autism spectrum disorder (ASD) and schizophrenia. However, it is unclear if a convergent neural mechanism also underlies gaze dysfunction in these conditions. The present study examined whether this shared eye gaze phenotype is reflected in a profile of convergent neurobiological dysfunction in ASD and schizophrenia. METHODS: Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates across the whole brain to identify spatial convergence. Functional coactivation with regions emerging as significant was assessed using meta-analytic connectivity modeling. Functional decoding was also conducted. RESULTS: Fifty-six experiments (n = 30 with schizophrenia and n = 26 with ASD) from 36 articles met inclusion criteria, which comprised 354 participants with ASD, 275 with schizophrenia and 613 healthy controls (1242 participants in total). In ASD, aberrant activation was found in the left amygdala relative to unaffected controls during gaze processing. In schizophrenia, aberrant activation was found in the right inferior frontal gyrus and supplementary motor area. Across ASD and schizophrenia, aberrant activation was found in the right inferior frontal gyrus and right fusiform gyrus during gaze processing. Functional decoding mapped the left amygdala to domains related to emotion processing and cognition, the right inferior frontal gyrus to cognition and perception, and the right fusiform gyrus to visual perception, spatial cognition, and emotion perception. These regions also showed meta-analytic connectivity to frontoparietal and frontotemporal circuitry. CONCLUSION: Alterations in frontoparietal and frontotemporal circuitry emerged as neural markers of gaze impairments in ASD and schizophrenia. These findings have implications for advancing transdiagnostic biomarkers to inform targeted treatments for ASD and schizophrenia.

Amygdala-prefrontal connectivity in children with maladaptive aggression is modulated by social impairment.

Aggressive behavior is common across childhood-onset psychiatric disorders and is associated with impairments in social cognition and communication. The present study examined whether amygdala connectivity and reactivity during face emotion processing in children with maladaptive aggression are moderated by social impairment. This cross-sectional study included a well-characterized transdiagnostic sample of 101 children of age 8-16 years old with clinically significant levels of aggressive behavior and 32 typically developing children without aggressive behavior. Children completed a face emotion perception task of fearful and calm faces during functional magnetic resonance imaging. Aggressive behavior and social functioning were measured by standardized parent ratings. Relative to controls, children with aggressive behavior showed reduced connectivity between the amygdala and the dorsolateral prefrontal cortex (PFC) during implicit emotion processing. In children with aggressive behavior, the association between reduced amygdala-ventrolateral PFC connectivity and greater severity of aggression was moderated by greater social impairment. Amygdala reactivity to fearful faces was also associated with severity of aggressive behavior for children without social deficits but not for children with social deficits. Social impairments entail difficulties in interpreting social cues and enacting socially appropriate responses to frustration or provocation, which increase the propensity for an aggressive response via diminished connectivity between the amygdala and the ventral PFC.

Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling.

Disruptions in frontoparietal networks supporting emotion regulation have been long implicated in maladaptive childhood aggression. However, the association of connectivity between large-scale functional networks with aggressive behavior has not been tested. The present study examined whether the functional organization of the connectome predicts severity of aggression in children. This cross-sectional study included a transdiagnostic sample of 100 children with aggressive behavior (27 females) and 29 healthy controls without aggression or psychiatric disorders (13 females). Severity of aggression was indexed by the total score on the parent-rated Reactive-Proactive Aggression Questionnaire. During fMRI, participants completed a face emotion perception task of fearful and calm faces. Connectome-based predictive modeling with internal cross-validation was conducted to identify brain networks that predicted aggression severity. The replication and generalizability of the aggression predictive model was then tested in an independent sample of children from the Adolescent Brain Cognitive Development (ABCD) study. Connectivity predictive of aggression was identified within and between networks implicated in cognitive control (medial-frontal, frontoparietal), social functioning (default mode, salience), and emotion processing (subcortical, sensorimotor) (r = 0.31, RMSE = 9.05, p = 0.005). Out-of-sample replication (p < 0.002) and generalization (p = 0.007) of findings predicting aggression from the functional connectome was demonstrated in an independent sample of children from the ABCD study (n = 1791; n = 1701). Individual differences in large-scale functional networks contribute to variability in maladaptive aggression in children with psychiatric disorders. Linking these individual differences in the connectome to variation in behavioral phenotypes will advance identification of neural biomarkers of maladaptive childhood aggression to inform targeted treatments.

Sex differences in medial prefrontal and parietal cortex structure in children with disruptive behavior.

Sex differences in brain structure in children with disruptive behavior disorders (DBD) remain poorly understood. This study examined sex differences in gray matter volume in children with DBD in a priori regions-of-interest implicated in the pathophysiology of disruptive behavior. We then conducted a whole-brain analysis of cortical thickness to examine sex differences in regions not included in our hypothesis. Exploratory analyses investigated unique associations between structure, and dimensional measures of severity of disruptive behavior and callous-unemotional traits. This cross-sectional study included 88 children with DBD (30 females) aged 8-16 years and 50 healthy controls (20 females). Structural MRI data were analyzed using surface-based morphometry to test for interactions between sex and group. Multiple-regression analyses tested for sex-specific associations between structure, callous-unemotional traits, and disruptive behavior severity. Boys with DBD showed reduced gray matter volume in the left ventromedial prefrontal cortex (vmPFC) and reduced cortical thickness in the supramarginal gyrus, but not girls compared to respective controls. Dimensional analyses revealed associations between sex, callous-unemotional traits, and disruptive behavior for amygdala and vmPFC volume, and ventrolateral prefrontal cortex cortical thickness. Sex-specific differences in prefrontal structures involved in emotion regulation may support identification of neural biomarkers of disruptive behavior to inform target-based treatments.

Genetic predictors of hippocampal subfield volume in PTSD cases and trauma-exposed controls.

Behavioural, structural, and functional neuroimaging have implicated the hippocampus as a critical brain region in posttraumatic stress disorder (PTSD) pathogenesis. Recent work in a normative, primarily European, sample identified 15 unique genetic loci contributing to structural variability in six hippocampal subfield volumes. We explored the relevance of these loci in two samples (Mental Illness Research Education and Clinical Centre [MIRECC] and Grady; n = 290) of trauma-exposed individuals enriched for PTSD and of diverse ancestry. Four of the previous loci demonstrated nominal evidence of replication in the MIRECC dataset, primarily within non-Hispanic whites (NHW). One locus replicated in the Grady cohort, which was composed exclusively of non-Hispanic blacks (NHB). Our data supported genetic interactions with diagnosis of lifetime PTSD and genetic interactions with childhood trauma in the MIRECC sample, but not the Grady sample. Given the racial, diagnostic, and trauma-exposure differences with the original genome-wide association study (GWAS) report, we conducted a full GWAS in the MIRECC and Grady datasets. Interactions between genetic variants and lifetime PTSD or childhood trauma were interrogated for single nucleotide polymorphisms (SNPs) with evidence of main effects. Genetic associations surpassed false discovery rate (FDR)-correction within hippocampal subfields in fimbria, subiculum, cornu ammonis-1 (CA1), and hippocampal amygdala transition area (HATA). One association was replicated in the Grady cohort (rs12880795 in TUNAR with left (L)-HATA volume). The most significant association in the MIRECC dataset was between rs6906714 in LINC02571 and right (R)-fimbria volume (p = 5.99×10-8, q = 0.0056). Interestingly, the effect of rs6906714 on R-fimbria volume increased with exposure to childhood trauma (gene*environment [G*E] interaction p = 0.022). These preliminary results argue for G*E interactions between genetic loci with PTSD and childhood trauma on hippocampal phenotypes. Our results underscore the need for larger neuroimaging-genetic studies in PTSD, trauma, and ancestrally diverse populations.

Las neuroimagenologia, conductual, estructural y funcional ha implicado que el hipocampo se constituye como una región cerebral critica en la patogénesis del trastorno de estrés postraumático (TEPT). Un trabajo reciente, realizado en una muestra normativa, principalmente europea, identifico 15 loci genéticos únicos que contribuyen a la variabilidad estructural de seis volúmenes de subcampos hipocampales. Exploramos la relevancia de estos loci en dos muestras enriquecidas para TEPT (del Centro de Educación y Clínica Investigación sobre Enfermedades Mentales, MIRECC por sus siglas en inglés y Grady; n=290) de individuos expuestos a trauma y de ascendencia diversa. Cuatro de los loci previos demostraron evidencia nominal de replicación en la base de datos MIRECC, principalmente en personas de raza blanca no hispánicos (NHW). Se replicó un locus en la cohorte Grady, que estaba compuesta exclusivamente por personas de raza negra no hispánicos (NHB). Nuestros datos respaldaron las interacciones genéticas con el diagnostico de TEPT a lo largo de la vida e interacciones genéticas con trauma infantil en la muestra MIRECC, pero no en la de Grady. Debido a las diferencias raciales, diagnósticas y de exposición a trauma con el reporte original del estudio de asociación del genoma completo (GWAS por sus siglas en ingles), realizamos un GWAS completo con la base de datos MIRECC y Grady. Se exploraron polimorfismos de nucleótido único (SNPs por sus siglas en ingles) en las interacciones de variantes genéticas del TEPT a lo largo de la vida y del trauma infantil, con evidencia de un efecto genético principal. Las asociaciones genéticas sobrepasaron a la corrección de tasa de falso descubrimiento (FDR) dentro de los subcampos hipocampales de la fimbria, subículo, asta de Amon-1 (CA1), y el área de transición hipocampo-amigdaliana (HATA). Una asociación se replicó en la cohorte de Grady (rs 12880795 en TUNAR con volumen izquierdo del HATA). La asociación más significativa en la base de datos de MIRECC estuvo entre rs6906714 en LINC02571 y el volumen de la fimbria derecha (p=5.99×10-8, q=0.0056). Interesantemente, el efecto rs6906714 sobre el volumen de la fimbria derecha se incrementaba con la exposición al trauma infantil (interacción gen* ambiente [G*A] p=0.022). Estos resultados preliminares orientarían a la presencia de interacciones G*A de loci genéticos con el TEPT y trauma infantil en fenotipos del hipocampo. Nuestro resultados destacan la necesidad de estudios más grandes que vinculen neuroimagenes y genética en poblaciones con TEPT, trauma, y genealogía diversa.

Analyzing the stability of gene expression using a simple reaction-diffusion model in an early Drosophila embryo.

In all complex organisms, the precise levels and timing of gene expression controls vital biological processes. In higher eukaryotes, including the fruit fly Drosophila melanogaster, the complex molecular control of transcription (the synthesis of RNA from DNA) and translation (the synthesis of proteins from RNA) events driving this gene expression are not fully understood. In particular, for Drosophila melanogaster, there is a plethora of experimental data, including quantitative measurements of both RNA and protein concentrations, but the precise mechanisms that control the dynamics of gene expression during early development and the processes which lead to steady-state levels of certain proteins remain elusive. This study analyzes a current mathematical modeling approach in an attempt to better understand the long-term behavior of gene regulation. The model is a modified reaction-diffusion equation which has been previously employed in predicting gene expression levels and studying the relative contributions of transcription and translation events to protein abundance [10,11,24]. Here, we use Matrix Algebra and Analysis techniques to study the stability of the gene expression system and analyze equilibria, using very general assumptions regarding the parameter values incorporated into the model. We prove that, given realistic biological parameter values, the system will result in a unique, stable equilibrium solution. Additionally, we give an example of this long-term behavior using the model alongside actual experimental data obtained from Drosophila embryos.

Perceptual and Semantic Phases of Face Identification Processing: A Multivariate Electroencephalography Study.

Rapid identification of a familiar face requires an image-invariant representation of person identity. A varying sample of familiar faces is necessary to disentangle image-level from person-level processing. We investigated the time course of face identity processing using a multivariate electroencephalography analysis. Participants saw ambient exemplars of celebrity faces that differed in pose, lighting, hairstyle, and so forth. A name prime preceded a face on half of the trials to preactivate person-specific information, whereas a neutral prime was used on the remaining half. This manipulation helped dissociate perceptual- and semantic-based identification. Two time intervals within the post-face onset electroencephalography epoch were sensitive to person identity. The early perceptual phase spanned 110-228 msec and was not modulated by the name prime. The late semantic phase spanned 252-1000 msec and was sensitive to person knowledge activated by the name prime. Within this late phase, the identity response occurred earlier in time (300-600 msec) for the name prime with a scalp topography similar to the FN400 ERP. This may reflect a matching of the person primed in memory with the face on the screen. Following a neutral prime, the identity response occurred later in time (500-800 msec) with a scalp topography similar to the P600f ERP. This may reflect activation of semantic knowledge associated with the identity. Our results suggest that processing of identity begins early (110 msec), with some tolerance to image-level variations, and then progresses in stages sensitive to perceptual and then to semantic features.

Reduced Amygdala-Prefrontal Functional Connectivity in Children With Autism Spectrum Disorder and Co-occurring Disruptive Behavior.

BACKGROUND: Disruptive behaviors are prevalent in children with autism spectrum disorder (ASD) and often cause substantial impairments. However, the underlying neural mechanisms of disruptive behaviors remain poorly understood in ASD. In children without ASD, disruptive behavior is associated with amygdala hyperactivity and reduced connectivity with the ventrolateral prefrontal cortex (vlPFC). This study examined amygdala reactivity and connectivity in children with ASD with and without co-occurring disruptive behavior disorders. We also investigated differential contributions of externalizing behaviors and callous-unemotional traits to variance in amygdala connectivity and reactivity. METHODS: This cross-sectional study involved behavioral assessments and neuroimaging in three groups of children 8 to 16 years of age: 18 children had ASD and disruptive behavior, 20 children had ASD without disruptive behavior, and 19 children were typically developing control participants matched for age, gender, and IQ. During functional magnetic resonance imaging, participants completed an emotion perception task of fearful versus calm faces. Task-specific changes in amygdala reactivity and connectivity were examined using whole-brain, psychophysiological interaction, and multiple regression analyses. RESULTS: Children with ASD and disruptive behavior showed reduced amygdala-vlPFC connectivity compared with children with ASD without disruptive behavior. Externalizing behaviors and callous-unemotional traits were associated with amygdala reactivity to fearful faces in children with ASD after controlling for suppressor effects. CONCLUSIONS: Reduced amygdala-vlPFC connectivity during fear processing may differentiate children with ASD and disruptive behavior from children with ASD without disruptive behavior. The presence of callous-unemotional traits may have implications for identifying differential patterns of amygdala activity associated with increased risk of aggression in ASD. These findings suggest a neural mechanism of emotion dysregulation associated with disruptive behavior in children with ASD.

Category representations in the brain are both discretely localized and widely distributed.

Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Initial functional MRI studies supported the localizationist perspective that category information is represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately. However, localized representations are revealed by using analytical methods that separate unique from shared information among brain regions. The distributed nature of shared information and the localized nature of unique information suggest that brain connectivity may encourage spreading of information but category-specific computations are carried out in distinct domain-specific regions. NEW & NOTEWORTHY Whether visual category information is localized in unique domain-specific brain regions or distributed in many domain-general brain regions is hotly contested. We resolve this debate by using multivariate analyses to parse functional MRI signals from different brain regions into unique and shared variance. Our findings support elements of both models and show information is initially localized and then shared among other regions leading to distributed representations being observed.

Sensitivity to Faces with Typical and Atypical Part Configurations within Regions of the Face-processing Network: An fMRI Study.

Perception of faces has been shown to engage a domain-specific set of brain regions, including the occipital face area (OFA) and the fusiform face area (FFA). It is commonly held that the OFA is responsible for the detection of faces in the environment, whereas the FFA is responsible for processing the identity of the face. However, an alternative model posits that the FFA is responsible for face detection and subsequently recruits the OFA to analyze the face parts in the service of identification. An essential prediction of the former model is that the OFA is not sensitive to the arrangement of internal face parts. In the current fMRI study, we test the sensitivity of the OFA and FFA to the configuration of face parts. Participants were shown faces in which the internal parts were presented in a typical configuration (two eyes above a nose above a mouth) or in an atypical configuration (the locations of individual parts were shuffled within the face outline). Perception of the atypical faces evoked a significantly larger response than typical faces in the OFA and in a wide swath of the surrounding posterior occipitotemporal cortices. Surprisingly, typical faces did not evoke a significantly larger response than atypical faces anywhere in the brain, including the FFA (although some subthreshold differences were observed). We propose that face processing in the FFA results in inhibitory sculpting of activation in the OFA, which accounts for this region's weaker response to typical than to atypical configurations.

Genome-wide association study of subcortical brain volume in PTSD cases and trauma-exposed controls.

Depending on the traumatic event, a significant fraction of trauma survivors subsequently develop PTSD. The additional variability in PTSD risk is expected to arise from genetic susceptibility. Unfortunately, several genome-wide association studies (GWAS) have failed to identify a consistent genetic marker for PTSD. The heritability of intermediate phenotypes such as regional brain volumes is often 80% or higher. We conducted a GWAS of subcortical brain volumes in a sample of recent military veteran trauma survivors (n = 157), grouped into PTSD (n = 66) and non-PTSD controls (n = 91). Covariates included PTSD diagnosis, sex, intracranial volume, ancestry, childhood trauma, SNP×PTSD diagnosis, and SNP×childhood trauma. We identified several genetic markers in high linkage disequilibrium (LD) with rs9373240 (p = 2.0 × 10-7, FDR q = 0.0375) that were associated with caudate volume. We also observed a significant interaction between rs9373240 and childhood trauma (p-values = 0.0007-0.002), whereby increased trauma exposure produced a stronger association between SNPs and increased caudate volume. We identified several SNPs in high LD with rs34043524, which is downstream of the TRAM1L1 gene that were associated with right lateral ventricular volume (p = 1.73 × 10-7; FDR q = 0.032) and were also associated with lifetime alcohol abuse or dependence (p = 2.49 × 10-7; FDR q = 0.0375). Finally, we identified several SNPs in high LD with rs13140180 (p = 2.58 × 10-7; FDR q = .0016), an intergenic region on chromosome 4, and several SNPs in the TMPRSS15 associated with right nucleus accumbens volume (p = 2.58 × 10-7; FDR q = 0.017). Both TRAM1L1 and TMPRSS15 have been previously implicated in neuronal function. Key results survived genome-wide multiple-testing correction in our sample. Leveraging neuroimaging phenotypes may offer a shortcut, relative to clinical phenotypes, in mapping the genetic architecture and neurobiological pathways of PTSD.

Holistic versus feature-based binding in the medial temporal lobe.

A central question for cognitive neuroscience is how feature-combinations that give rise to episodic/source memories are encoded in the brain. Although there is much evidence that the hippocampus (HIP) is involved in feature binding, and some evidence that other brain regions are as well, there is relatively little evidence about the nature of the resulting representations in different brain regions. We used multivoxel pattern analysis (MVPA) to investigate how feature combinations might be represented, contrasting two possibilities, feature-based versus holistic. Participants viewed stimuli that were composed of three source features - a person (face or body), a scene (indoor or outdoor), and an object (bike or luggage) - which were combined to make eight unique stimulus identities. We reasoned that regions that can classify the eight identities (a multiclass classification) but not the individual features (a binary classification) likely have a holistic representation of each identity. In contrast, regions that can classify the eight identities and can classify each feature are likely to contain feature-based representations of these identities. To further probe the extent of feature-based or holistic classification in each region, we developed and validated a novel approach that directly compares binary and multiclass classification. We found clear evidence for holistic representation in the parahippocampal cortex (PHC), consistent with theories that posit that pattern-separation-like binding mechanisms are not unique to the HIP. Further clarifying the mechanisms of feature binding should benefit from systematic comparisons of multi-feature representations and whether they vary with task, type of stimulus, and/or experience.

Reevaluating the Efficacy and Predictability of Antidepressant Treatments: A Symptom Clustering Approach.

IMPORTANCE: Depressive severity is typically measured according to total scores on questionnaires that include a diverse range of symptoms despite convincing evidence that depression is not a unitary construct. When evaluated according to aggregate measurements, treatment efficacy is generally modest and differences in efficacy between antidepressant therapies are small. OBJECTIVES: To determine the efficacy of antidepressant treatments on empirically defined groups of symptoms and examine the replicability of these groups. DESIGN, SETTING, AND PARTICIPANTS: Patient-reported data on patients with depression from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial (n = 4039) were used to identify clusters of symptoms in a depressive symptom checklist. The findings were then replicated using the Combining Medications to Enhance Depression Outcomes (CO-MED) trial (n = 640). Mixed-effects regression analysis was then performed to determine whether observed symptom clusters have differential response trajectories using intent-to-treat data from both trials (n = 4706) along with 7 additional placebo and active-comparator phase 3 trials of duloxetine (n = 2515). Finally, outcomes for each cluster were estimated separately using machine-learning approaches. The study was conducted from October 28, 2014, to May 19, 2016. MAIN OUTCOMES AND MEASURES: Twelve items from the self-reported Quick Inventory of Depressive Symptomatology (QIDS-SR) scale and 14 items from the clinician-rated Hamilton Depression (HAM-D) rating scale. Higher scores on the measures indicate greater severity of the symptoms. RESULTS: Of the 4706 patients included in the first analysis, 1722 (36.6%) were male; mean (SD) age was 41.2 (13.3) years. Of the 2515 patients included in the second analysis, 855 (34.0%) were male; mean age was 42.65 (12.17) years. Three symptom clusters in the QIDS-SR scale were identified at baseline in STAR*D. This 3-cluster solution was replicated in CO-MED and was similar for the HAM-D scale. Antidepressants in general (8 of 9 treatments) were more effective for core emotional symptoms than for sleep or atypical symptoms. Differences in efficacy between drugs were often greater than the difference in efficacy between treatments and placebo. For example, high-dose duloxetine outperformed escitalopram in treating core emotional symptoms (effect size, 2.3 HAM-D points during 8 weeks, 95% CI, 1.6 to 3.1; P < .001), but escitalopram was not significantly different from placebo (effect size, 0.03 HAM-D points; 95% CI, -0.7 to 0.8; P = .94). CONCLUSIONS AND RELEVANCE: Two common checklists used to measure depressive severity can produce statistically reliable clusters of symptoms. These clusters differ in their responsiveness to treatment both within and across different antidepressant medications. Selecting the best drug for a given cluster may have a bigger benefit than that gained by use of an active compound vs a placebo.

The Effects of Face Inversion and Face Race on the P100 ERP.

Research about the neural basis of face recognition has investigated the timing and anatomical substrates of different stages of face processing. Scalp-recorded ERP studies of face processing have focused on the N170, an ERP with a peak latency of ∼170 msec that has long been associated with the initial structural encoding of faces. However, several studies have reported earlier ERP differences related to faces, suggesting that face-specific processes might occur before N170. Here, we examined the influence of face inversion and face race on the timing of face-sensitive scalp-recorded ERPs by examining neural responses to upright and inverted line-drawn and luminance-matched white and black faces in a sample of white participants. We found that the P100 ERP evoked by inverted faces was significantly larger than that evoked by upright faces. Although this inversion effect was statistically significant at 100 msec, the inverted-upright ERP difference peaked at 138 msec, suggesting that it might represent an activity in neural sources that overlap with P100. Inverse modeling of the inversion effect difference waveform suggested possible neural sources in pericalcarine extrastriate visual cortex and lateral occipito-temporal cortex. We also found that the inversion effect difference wave was larger for white faces. These results are consistent with behavioral evidence that individuals process the faces of their own races more configurally than faces of other races. Taken together, the inversion and race effects observed in the current study suggest that configuration influences face processing by at least 100 msec.

Electrophysiological correlates of face-evoked person knowledge.

Face recognition includes identifying a face as perceptually familiar and recollecting biographical information, or person-knowledge, associated with the face. The majority of studies examining the neural basis of face recognition have confounded these stages by comparing brain responses evoked by novel and perceptually familiar famous faces. Here, we recorded EEG in two tasks in which subjects viewed two sets of faces that were equally perceptually familiar, but which had differing levels of associated person-knowledge. Our results dissociated the effects of person-knowledge from perceptual familiarity. Faces with associated biographical information elicited a larger ∼600ms centroparietal positivity in both a passive viewing task in which subjects viewed faces without explicitly responding, and an active question-answering task in which subjects indicated whether or not they knew particular facts about the faces. In the question task only, person-knowledge was associated with a negative ERP difference over right posterior scalp over the 170-450ms interval which appeared again at long latency (>900ms).

Reactivation during encoding supports the later discrimination of similar episodic memories.

Episodic memory is characterized by remembering events as unique combinations of features. Even when some features of events overlap, we are later often able to discriminate among them. Here we ask whether hippocampally mediated reactivation of an earlier event when a similar one occurs supports subsequent memory that two similar but not identical events occurred (mnemonic discrimination). In two experiments, participants viewed objects (Experiment 1) or scenes (Experiment 2) during functional MRI (fMRI). After scanning, participants had to remember whether repeated items had been identical or similar. In Experiment 2, representational similarity between the 1st and 2nd presentation predicted participants' ability to remember that the presentations were different, suggesting that the first item was reactivated while viewing the second. A similar but weaker result was found in Experiment 1 that did not survive correction for multiple comparisons. Furthermore, both experiments yielded evidence that the hippocampus was involved in reactivation; hippocampal pattern similarity (and, in Experiment 2, hippocampal activity during the 2nd presentation) correlated with pattern similarity in several regions of visual cortex. These results provide the first fMRI evidence that hippocampally mediated reactivation contributes to the later memory that two similar, but different events occurred. © 2016 Wiley Periodicals, Inc.

Task influences pattern discriminability for faces and bodies in ventral occipitotemporal cortex.

Our prior research showed that faces and bodies activate overlapping regions of the ventral occipitotemporal cortex (VOTC). However, faces and bodies were nonetheless discriminable in these same overlapping regions when their spatial patterns of activity were classified using multivoxel pattern analysis (MVPA). Here we investigated whether these spatial patterns and their time courses were influenced by different categorization tasks. Participants viewed pictures of faces or headless bodies depicting a happy or fearful emotion. In one task, they categorized the picture as a face or a body regardless of emotion. In the other task, they categorized the emotion regardless of whether it was depicted by a face or body. Using a classifier trained on independent data, we found higher face-body classification accuracy for the emotion categorization task. The classifier was applied to each post-stimulus time-point to characterize the temporal course of classification. Accuracy initially rose equivalently above chance for both tasks, but then increased over a longer duration when participants categorized emotions. Thus, the temporal course of pattern differences between faces and bodies in VOTC was modulated by the behavioral goal of the observer, suggesting the top-down modulatory effect of task context on the category-selectivity activity in the VOTC.

Functional Heterogeneity and Convergence in the Right Temporoparietal Junction.

The right temporoparietal junction (rTPJ) is engaged by tasks that manipulate biological motion processing, Theory of Mind attributions, and attention reorienting. The proximity of activations elicited by these tasks raises the question of whether these tasks share common cognitive component processes that are subserved by common neural substrates. Here, we used high-resolution whole-brain functional magnetic resonance imaging in a within-subjects design to determine whether these tasks activate common regions of the rTPJ. Each participant was presented with the 3 tasks in the same imaging session. In a whole-brain analysis, we found that only the right and left TPJs were activated by all 3 tasks. Multivoxel pattern analysis revealed that the regions of overlap could still discriminate the 3 tasks. Notably, we found significant cross-task classification in the right TPJ, which suggests a shared neural process between the 3 tasks. Taken together, these results support prior studies that have indicated functional heterogeneity within the rTPJ but also suggest a convergence of function within a region of overlap. These results also call for further investigation into the nature of the function subserved in this overlap region.

The Function Biomedical Informatics Research Network Data Repository.

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

Neural regions discriminating contextual information as conveyed through the learned preferences of others.

The human brain consists of a network of regions that are engaged when one observes the movements of others. Observing unexpected movements, as defined by the context, often elicits greater activity, particularly in the right posterior superior temporal sulcus (pSTS). This implies that observers use contextual information to form expectations about an agent's goal and subsequent movements. The current study sought to identify regions that support the formation of these context-dependent expectations, with the pSTS being one candidate, given the consistent contextual modulation of its activity. We presented participants with fictitious individuals who had emotion-dependent food preferences, and instructed participants to indicate which food they expected each individual to choose based on the individual's current emotional state. Each individual's preference and emotional state therefore created a context that informed the observer's expectation of the individual's choice. Multi-voxel pattern analysis (MVPA) was used to assess if these different contexts could be discriminated in the pSTS and elsewhere in the brain. No evidence for context discrimination was found in the pSTS. Context discrimination was found instead a network of other brain regions including the anterior medial prefrontal cortex (amPFC), bilateral parietal cortex, left middle temporal gyrus (L MTG) and left anterior temporal lobe (L ATL), which have been previously associated with context processing, and semantic and memory retrieval. All together, these regions possibly support the formation of context-dependent expectations of an agent's goal.