Creating probabilistic maps of the face network in the adolescent brain: a multicentre functional MRI study

Large-scale magnetic resonance (MR) studies of the human brain offer unique opportunities for identifying genetic and environmental factors shaping the human brain. Here, we describe a dataset collected in the context of a multi-centre study of the adolescent brain, namely the IMAGEN Study. We focus on one of the functional paradigms included in the project to probe the brain network underlying processing of ambiguous and angry faces. Using functional MR (fMRI) data collected in 1,110 adolescents, we constructed probabilistic maps of the neural network engaged consistently while viewing the ambiguous or angry faces; 21 brain regions responding to faces with high probability were identified. We were also able to address several methodological issues, including the minimal sample size yielding a stable location of a test region, namely the fusiform face area (FFA), as well as the effect of acquisition site (eight sites) and scanner (four manufacturers) on the location and magnitude of the fMRI response to faces in the FFA. Finally, we provided a comparison between male and female adolescents in terms of the effect sizes of sex differences in brain response to the ambiguous and angry faces in the 21 regions of interest. Overall, we found a stronger neural response to the ambiguous faces in several cortical regions, including the fusiform face area, in female (vs. male) adolescents, and a slightly stronger response to the angry faces in the amygdala of male (vs. female) adolescents.     

Altered functional connectivity during face processing in children born with very low birth weight

Structural brain alterations have been reported in key emotional face processing regions following preterm birth; however, few studies have investigated the functional networks underlying these processes in children born with very low birth weight (VLBW). Using magnetoencephalography (MEG), we examined the functional networks related to the implicit processing of happy and angry faces in 5-year-old VLBW (n = 28) and full-term (FT; n = 24) children. We found that VLBW children showed atypical recruitment of emotional face processing networks in theta (4–7 Hz) compared to FT children. VLBW children showed reduced theta connectivity during processing of angry faces only. This hypo-connected theta-band network was anchored in the left orbitofrontal and parietal regions, involved in the higher level processing of faces and emotion regulation. At the behavioural level, despite VLBW children performing within the normal range, FT children had significantly higher affect recognition scores. Our MEG results suggest a selective impairment in processing angry faces, which would negatively impact social functioning in VLBW children. In FT children, greater recruitment of this theta-band network was positively associated with improved affect recognition scores. Thus, our findings suggest an important role of theta oscillations in early face processing, deficits which may contribute to broader socio-emotional impairments in VLBW children.     

Interrelating differences in structural and functional connectivity in the older adult's brain

In the normal aging process, the functional connectome restructures and shows a shift from more segregated to more integrated brain networks, which manifests itself in highly different cognitive performances in older adults. Underpinnings of this reorganization are not fully understood, but may be related to age‐related differences in structural connectivity, the underlying scaffold for information exchange between regions. The structure–function relationship might be a promising factor to understand the neurobiological sources of interindividual cognitive variability, but remain unclear in older adults. Here, we used diffusion weighted and resting‐state functional magnetic resonance imaging as well as cognitive performance data of 573 older subjects from the 1000BRAINS cohort (55–85 years, 287 males) and performed a partial least square regression on 400 regional functional and structural connectivity (FC and SC, respectively) estimates comprising seven resting‐state networks. Our aim was to identify FC and SC patterns that are, together with cognitive performance, characteristic of the older adults aging process. Results revealed three different aging profiles prevalent in older adults. FC was found to behave differently depending on the severity of age‐related SC deteriorations. A functionally highly interconnected system is associated with a structural connectome that shows only minor age‐related decreases. Because this connectivity profile was associated with the most severe age‐related cognitive decline, a more interconnected FC system in older adults points to a process of dedifferentiation. Thus, functional network integration appears to increase primarily when SC begins to decline, but this does not appear to mitigate the decline in cognitive performance.     

Maturational trajectories of local and long‐range functional connectivity in autism during face processing

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14–21) with ASD and age‐ and IQ‐matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long‐range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7–13). We found that both local and long‐range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long‐range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long‐range functional connectivity measures.     

Social contact and other-race face processing in the human brain

The present study investigated the influence social factorsupon the neural processing of faces of other races using event-relatedpotentials. A multi-tiered approach was used to identify face-specificstages of processing, to test for effects of race-of-face uponprocessing at these stages and to evaluate the impact of socialcontact and individuating experience upon these effects. Theresults showed that race-of-face has significant effects uponface processing, starting from early perceptual stages of structuralencoding, and that social factors may play an important rolein mediating these effects.     

Disruption of structural and functional networks in long‐standing multiple sclerosis

Both gray matter atrophy and disruption of functional networks are important predictors for physical disability and cognitive impairment in multiple sclerosis (MS), yet their relationship is poorly understood. Graph theory provides a modality invariant framework to analyze patterns of gray matter morphology and functional coactivation. We investigated, how gray matter and functional networks were affected within the same MS sample and examined their interrelationship. Magnetic resonance imaging and magnetoencephalography (MEG) were performed in 102 MS patients and 42 healthy controls. Gray matter networks were computed at the group‐level based on cortical thickness correlations between 78 regions across subjects. MEG functional networks were computed at the subject level based on the phase‐lag index between time‐series of regions in source‐space. In MS patients, we found a more regular network organization for structural covariance networks and for functional networks in the theta band, whereas we found a more random network organization for functional networks in the alpha2 band. Correlation analysis revealed a positive association between covariation in thickness and functional connectivity in especially the theta band in MS patients, and these results could not be explained by simple regional gray matter thickness measurements. This study is a first multimodal graph analysis in a sample of MS patients, and our results suggest that a disruption of gray matter network topology is important to understand alterations in functional connectivity in MS as regional gray matter fails to take into account the inherent connectivity structure of the brain. Hum Brain Mapp 35:5946–5961, 2014. © 2014 Wiley Periodicals, Inc.     

Defining the face processing network: optimization of the functional localizer in fMRI

Functional localizers that contrast brain signal when viewing faces versus objects are commonly used in functional magnetic resonance imaging studies of face processing. However, current protocols do not reliably show all regions of the core system for face processing in all subjects when conservative statistical thresholds are used, which is problematic in the study of single subjects. Furthermore, arbitrary variations in the applied thresholds are associated with inconsistent estimates of the size of face-selective regions-of-interest (ROIs). We hypothesized that the use of more natural dynamic facial images in localizers might increase the likelihood of identifying face-selective ROIs in individual subjects, and we also investigated the use of a method to derive the statistically optimal ROI cluster size independent of thresholds. We found that dynamic facial stimuli were more effective than static stimuli, identifying 98% (versus 72% for static) of ROIs in the core face processing system and 69% (versus 39% for static) of ROIs in the extended face processing system. We then determined for each core face processing ROI, the cluster size associated with maximum statistical face-selectivity, which on average was approximately 50 mm(3) for the fusiform face area, the occipital face area, and the posterior superior temporal sulcus. We suggest that the combination of (a) more robust face-related activity induced by a dynamic face localizer and (b) a cluster-size determination based on maximum face-selectivity increases both the sensitivity and the specificity of the characterization of face-related ROIs in individual subjects.     

Age‐specific associations between oestradiol,cortico‐amygdalar structural covariance,and verbal and spatial skills

Oestradiol is known to play an important role in the developing human brain, although little is known about the entire network of potential regions that might be affected and how these effects may vary from childhood to early adulthood, which in turn can explain sexually differentiated behaviours. In the present study, we examined the relationships between oestradiol, cortico‐amygdalar structural covariance, and cognitive or behavioural measures typically showing sex differences (verbal/spatial skills, anxious‐depressed symptomatology) in 152 children and adolescents (aged 6‐22 years). Cortico‐amygdalar structural covariance shifted from positive to negative across the age range. Oestradiol was found to diminish the impact of age on cortico‐amygdalar covariance for the pre‐supplementary motor area/frontal eye field and retrosplenial cortex (across the age range), as well as for the posterior cingulate cortex (in older children). Moreover, the influence of oestradiol on age‐related cortico‐amygdalar networks was associated with higher word identification and spatial working memory (across the age range), as well as higher reading comprehension (in older children), although it did not impact anxious‐depressed symptoms. There were no significant sex effects on any of the above relationships. These findings confirm the importance of developmental timing on oestradiol‐related effects and hint at the non‐sexually dimorphic role of oestradiol‐related cortico‐amygdalar structural networks in aspects of cognition distinct from emotional processes.     

Cross‐population myelination covariance of human cerebral cortex

Cross‐population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small‐worldness. Furthermore, we found that the correlation between myelination covariance and resting‐state functional connectivity (RSFC) was uniform within each resting‐state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance–RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730–4743, 2017. © 2017 Wiley Periodicals, Inc.     

Generalizable predictive modeling of semantic processing ability from functional brain connectivity

Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating conceptual and meaningful information. Neuroimaging studies of SP typically collapse data from many subjects, but its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural network organizations contribute to the individual differences in SP behaviors. We aim to identify the neural signatures underlying SP variabilities by analyzing functional connectivity (FC) patterns based on a large‐sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two‐stage predictive modeling approach to build an internally cross‐validated model and to test the model''s generalizability with unseen data from different HCP samples and other out‐of‐sample datasets. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five SP‐related behavioral tests. This cross‐validated model can be used to predict unseen HCP data. The model generalizability was enhanced in the language task compared with other tasks used during scanning and was better for females than males. The model constructed from the HCP dataset can be partially generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out‐of‐sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education for healthy individuals and intervention for SP and language deficits patients.     

Structural optimality and neurogenetic expression mediate functional dynamics in the human brain

The human brain exhibits a rich functional repertoire in terms of complex functional connectivity patterns during rest and tasks. However, how this is developed upon a fixed structural anatomy remains poorly understood. Here we investigated the hypothesis that resting state functional connectivity and the manner in which it changes during tasks related to a set of underlying structural connections that promote optimal communication in the brain. We used a game‐theoretic model to identify such optimal connections in the structural connectome of 50 healthy individuals and subsequently used the optimal structural connections to predict resting‐state functional connectivity with high accuracy. In contrast, we found that nonoptimal connections accurately predicted functional connectivity during a working memory task. We further found that this balance between optimal and nonoptimal connections between brain regions was associated with a specific gene expression linked to neurotransmission. This multimodal evidence shows for the first time that structure–function relationships in the human brain are related to how brain networks navigate information along different white matter connections as well as the brain's underlying genetic profile.     

Large‐scale brain network abnormalities in Huntington's disease revealed by structural covariance

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel‐based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre‐specified motor, working memory, cognitive flexibility, and social‐affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre‐HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre‐HD were observed, but increased positive correlations were evident for mHD, relative to pre‐HD and HC. These findings could be explained by a HD‐related neuronal loss heterogeneously affecting the examined network at the pre‐HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow‐up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs. Hum Brain Mapp 37:67–80, 2016. © 2015 Wiley Periodicals, Inc.     

Mapping adolescent reward anticipation,receipt, and prediction error during the monetary incentive delay task

The functional neuroanatomy and connectivity of reward processing in adults are well documented, with relatively less research on adolescents, a notable gap given this developmental period's association with altered reward sensitivity. Here, a large sample (n = 1,510) of adolescents performed the monetary incentive delay (MID) task during functional magnetic resonance imaging. Probabilistic maps identified brain regions that were reliably responsive to reward anticipation and receipt, and to prediction errors derived from a computational model. Psychophysiological interactions analyses were used to examine functional connections throughout reward processing. Bilateral ventral striatum, pallidum, insula, thalamus, hippocampus, cingulate cortex, midbrain, motor area, and occipital areas were reliably activated during reward anticipation. Bilateral ventromedial prefrontal cortex and bilateral thalamus exhibited positive and negative activation, respectively, during reward receipt. Bilateral ventral striatum was reliably active following prediction errors. Previously, individual differences in the personality trait of sensation seeking were shown to be related to individual differences in sensitivity to reward outcome. Here, we found that sensation seeking scores were negatively correlated with right inferior frontal gyrus activity following reward prediction errors estimated using a computational model. Psychophysiological interactions demonstrated widespread cortical and subcortical connectivity during reward processing, including connectivity between reward‐related regions with motor areas and the salience network. Males had more activation in left putamen, right precuneus, and middle temporal gyrus during reward anticipation. In summary, we found that, in adolescents, different reward processing stages during the MID task were robustly associated with distinctive patterns of activation and of connectivity.     

Reward anticipation in the adolescent and aging brain

Processing of reward is the basis of adaptive behavior of the human being. Neural correlates of reward processing seem to be influenced by developmental changes from adolescence to late adulthood. The aim of this study is to uncover these neural correlates during a slot machine gambling task across the lifespan. Therefore, we used functional magnetic resonance imaging to investigate 102 volunteers in three different age groups: 34 adolescents, 34 younger adults, and 34 older adults. We focused on the core reward areas ventral striatum (VS) and ventromedial prefrontal cortex (VMPFC), the valence processing associated areas, anterior cingulate cortex (ACC) and insula, as well as information integration associated areas, dorsolateral prefrontal cortex (DLPFC), and inferior parietal lobule (IPL). Results showed that VS and VMPFC were characterized by a hyperactivation in adolescents compared with younger adults. Furthermore, the ACC and insula were characterized by a U‐shape pattern (hypoactivation in younger adults compared with adolescents and older adults), whereas the DLPFC and IPL were characterized by a J‐shaped form (hyperactivation in older adults compared with younger groups). Furthermore, a functional connectivity analysis revealed an elevated negative functional coupling between the inhibition‐related area rIFG and VS in younger adults compared with adolescents. Results indicate that lifespan‐related changes during reward anticipation are characterized by different trajectories in different reward network modules and support the hypothesis of an imbalance in maturation of striatal and prefrontal cortex in adolescents. Furthermore, these results suggest compensatory age‐specific effects in fronto‐parietal regions. Hum Brain Mapp 35:5153–5165, 2014. © 2014 Wiley Periodicals, Inc .     

Evaluating the organizational structure and specificity of network topology within the face processing system

There is increasing appreciation that network‐level interactions among regions produce components of face processing previously ascribed to individual regions. Our goals were to use an exhaustive data‐driven approach to derive and quantify the topology of directed functional connections within a priori defined nodes of the face processing network and evaluate whether the topology is category‐specific. Young adults were scanned with fMRI as they viewed movies of faces, objects, and scenes. We employed GIMME to model effective connectivity among core and extended face processing regions, which allowed us to evaluate all possible directional connections, under each viewing condition (face, object, place). During face processing, we observed directional connections from the right posterior superior temporal sulcus to both the right occipital face area and right fusiform face area (FFA), which does not reflect the topology reported in prior studies. We observed connectivity between core and extended regions during face processing, but this limited to a feed‐forward connection from the FFA to the amygdala. Finally, the topology of connections was unique to face processing. These findings suggest that the pattern of directed functional connections within the face processing network, particularly in the right core regions, may not be as hierarchical and feed‐forward as described previously. Our findings support the notion that topologies of network connections are specialized, emergent, and dynamically responsive to task demands.     

Validation of the NIMH‐ChEFS adolescent face stimulus set in an adolescent,parent, and health professional sample

Attention to faces is a fundamental psychological process in humans, with atypical attention to faces noted across several clinical disorders. Although many clinical disorders onset in adolescence, there is a lack of well‐validated stimulus sets containing adolescent faces available for experimental use. Further, the images comprising most available sets are not controlled for high‐ and low‐level visual properties. Here, we present a cross‐site validation of the National Institute of Mental Health Child Emotional Faces Picture Set (NIMH‐ChEFS), comprised of 257 photographs of adolescent faces displaying angry, fearful, happy, sad, and neutral expressions. All of the direct facial images from the NIMH‐ChEFS set were adjusted in terms of location of facial features and standardized for luminance, size, and smoothness. Although overall agreement between raters in this study and the original development‐site raters was high (89.52%), this differed by group such that agreement was lower for adolescents relative to mental health professionals in the current study. These results suggest that future research using this face set or others of adolescent/child faces should base comparisons on similarly‐aged validation data. Copyright © 2015 John Wiley & Sons, Ltd.     

Resting‐state functional connectivity of the human hippocampus in periadolescent children: Associations with age and memory performance

The hippocampus is necessary for declarative (relational) memory, and the ability to form hippocampal‐dependent memories develops through late adolescence. This developmental trajectory of hippocampal‐dependent memory could reflect maturation of intrinsic functional brain networks, but resting‐state functional connectivity (rs‐FC) of the human hippocampus is not well‐characterized for periadolescent children. Measuring hippocampal rs‐FC in periadolescence would thus fill a gap, and testing covariance of hippocampal rs‐FC with age and memory could inform theories of cognitive development. Here, we studied hippocampal rs‐FC in a cross‐sectional sample of healthy children (N = 96; 59 F; age 9–15 years) using a seed‐based approach, and linked these data with NIH Toolbox measures, the Picture‐Sequence Memory Test (PSMT) and the List Sorting Working Memory Test (LSWMT). The PSMT was expected to rely more on hippocampal‐dependent memory than the LSWMT. We observed hippocampal rs‐FC with an extensive brain network including temporal, parietal, and frontal regions. This pattern was consistent with prior work measuring hippocampal rs‐FC in younger and older samples. We also observed novel, regionally specific variation in hippocampal rs‐FC with age and hippocampal‐dependent memory but not working memory. Evidence consistent with these findings was observed in a second, validation dataset of similar‐age healthy children drawn from the Philadelphia Neurodevelopment Cohort. Further, a cross‐dataset analysis suggested generalizable properties of hippocampal rs‐FC and covariance with age and memory. Our findings connect prior work by describing hippocampal rs‐FC and covariance with age and memory in typically developing periadolescent children, and our observations suggest a developmental trajectory for brain networks that support hippocampal‐dependent memory.     

Predictors of coupling between structural and functional cortical networks in normal aging

Understanding how the mammalian neocortex creates cognition largely depends on knowledge about large‐scale cortical organization. Accumulated evidence has illuminated cortical substrates of cognition across the lifespan, but how topological properties of cortical networks support structure‐function relationships in normal aging remains an open question. Here we investigate the role of connections (i.e., short/long and direct/indirect) and node properties (i.e., centrality and modularity) in predicting functional‐structural connectivity coupling in healthy elderly subjects. Connectivity networks were derived from correlations of cortical thickness and cortical glucose consumption in resting state. Local‐direct connections (i.e., nodes separated by less than 30 mm) and node modularity (i.e., a set of nodes highly interconnected within a topological community and sparsely interconnected with nodes from other modules) in the functional network were identified as the main determinants of coupling between cortical networks, suggesting that the structural network in aging is mainly constrained by functional topological properties involved in the segregation of information, likely due to aging‐related deficits in functional integration. This hypothesis is supported by an enhanced connectivity between cortical regions of different resting‐state networks involved in sensorimotor and memory functions in detrimental to associations between fronto‐parietal regions supporting executive processes. Taken collectively, these findings open new avenues to identify aging‐related failures in the anatomo‐functional organization of the neocortical mantle, and might contribute to early detection of prevalent neurodegenerative conditions occurring in the late life. Hum Brain Mapp 35:2724–2740, 2014. © 2013 Wiley Periodicals, Inc .