Coordinated cortical thickness alterations across six neurodevelopmental and psychiatric disorders.

Neuropsychiatric disorders are increasingly conceptualized as overlapping spectra sharing multi-level neurobiological alterations. However, whether transdiagnostic cortical alterations covary in a biologically meaningful way is currently unknown. Here, we studied co-alteration networks across six neurodevelopmental and psychiatric disorders, reflecting pathological structural covariance. In 12,024 patients and 18,969 controls from the ENIGMA consortium, we observed that co-alteration patterns followed normative connectome organization and were anchored to prefrontal and temporal disease epicenters. Manifold learning revealed frontal-to-temporal and sensory/limbic-to-occipitoparietal transdiagnostic gradients, differentiating shared illness effects on cortical thickness along these axes. The principal gradient aligned with a normative cortical thickness covariance gradient and established a transcriptomic link to cortico-cerebello-thalamic circuits. Moreover, transdiagnostic gradients segregated functional networks involved in basic sensory, attentional/perceptual, and domain-general cognitive processes, and distinguished between regional cytoarchitectonic profiles. Together, our findings indicate that shared illness effects occur in a synchronized fashion and along multiple levels of hierarchical cortical organization.

Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation?

Age estimation based on DNA methylation (DNAm) can be applied to children, adolescents and adults, but many CG dinucleotides (CpGs) exhibit different kinetics of age-associated DNAm across these age ranges. Furthermore, it is still unclear how growth disorders impact epigenetic age predictions, and this may be particularly relevant for a forensic application. In this study, we analyzed buccal mucosa samples from 95 healthy children and 104 children with different growth disorders. DNAm was analysed by pyrosequencing for 22 CpGs in the genes PDE4C, ELOVL2, RPA2, EDARADD and DDO. The relationship between DNAm and age in healthy children was tested by Spearman's rank correlation. Differences in DNAm between the groups "healthy children" and the (sub-)groups of children with growth disorders were tested by ANCOVA. Models for age estimation were trained (1) based on the data from 11 CpGs with a close correlation between DNAm and age (R ≥ 0.75) and (2) on five CpGs that also did not present significant differences in DNAm between healthy and diseased children. Statistical analysis revealed significant differences between the healthy group and the group with growth disorders (11 CpGs), the subgroup with a short stature (12 CpGs) and the non-short stature subgroup (three CpGs). The results are in line with the assumption of an epigenetic regulation of height-influencing genes. Age predictors trained on 11 CpGs with high correlations between DNAm and age revealed higher mean absolute errors (MAEs) in the group of growth disorders (mean MAE 2.21 years versus MAE 1.79 in the healthy group) as well as in the short stature (sub-)groups; furthermore, there was a clear tendency for overestimation of ages in all growth disorder groups (mean age deviations: total growth disorder group 1.85 years, short stature group 1.99 years). Age estimates on samples from children with growth disorders were more precise when using a model containing only the five CpGs that did not present significant differences in DNAm between healthy and diseased children (mean age deviations: total growth disorder group 1.45 years, short stature group 1.66 years). The results suggest that CpGs in genes involved in processes relevant for growth and development should be avoided in age prediction models for children since they may be sensitive for alterations in the DNAm pattern in cases of growth disorders.

Evidence for differences in DNA methylation between Germans and Japanese.

As a contribution to the discussion about the possible effects of ethnicity/ancestry on age estimation based on DNA methylation (DNAm) patterns, we directly compared age-associated DNAm in German and Japanese donors in one laboratory under identical conditions. DNAm was analyzed by pyrosequencing for 22 CpG sites (CpGs) in the genes PDE4C, RPA2, ELOVL2, DDO, and EDARADD in buccal mucosa samples from German and Japanese donors (N = 368 and N = 89, respectively).Twenty of these CpGs revealed a very high correlation with age and were subsequently tested for differences between German and Japanese donors aged between 10 and 65 years (N = 287 and N = 83, respectively). ANCOVA was performed by testing the Japanese samples against age- and sex-matched German subsamples (N = 83 each; extracted 500 times from the German total sample). The median p values suggest a strong evidence for significant differences (p < 0.05) at least for two CpGs (EDARADD, CpG 2, and PDE4C, CpG 2) and no differences for 11 CpGs (p > 0.3).Age prediction models based on DNAm data from all 20 CpGs from German training data did not reveal relevant differences between the Japanese test samples and German subsamples. Obviously, the high number of included "robust CpGs" prevented relevant effects of differences in DNAm at two CpGs.Nevertheless, the presented data demonstrates the need for further research regarding the impact of confounding factors on DNAm in the context of ethnicity/ancestry to ensure a high quality of age estimation. One approach may be the search for "robust" CpG markers-which requires the targeted investigation of different populations, at best by collaborative research with coordinated research strategies.

A machine learning approach for the factorization of psychometric data with application to the Delis Kaplan Executive Function System.

While a replicability crisis has shaken psychological sciences, the replicability of multivariate approaches for psychometric data factorization has received little attention. In particular, Exploratory Factor Analysis (EFA) is frequently promoted as the gold standard in psychological sciences. However, the application of EFA to executive functioning, a core concept in psychology and cognitive neuroscience, has led to divergent conceptual models. This heterogeneity severely limits the generalizability and replicability of findings. To tackle this issue, in this study, we propose to capitalize on a machine learning approach, OPNMF (Orthonormal Projective Non-Negative Factorization), and leverage internal cross-validation to promote generalizability to an independent dataset. We examined its application on the scores of 334 adults at the Delis-Kaplan Executive Function System (D-KEFS), while comparing to standard EFA and Principal Component Analysis (PCA). We further evaluated the replicability of the derived factorization across specific gender and age subsamples. Overall, OPNMF and PCA both converge towards a two-factor model as the best data-fit model. The derived factorization suggests a division between low-level and high-level executive functioning measures, a model further supported in subsamples. In contrast, EFA, highlighted a five-factor model which reflects the segregation of the D-KEFS battery into its main tasks while still clustering higher-level tasks together. However, this model was poorly supported in the subsamples. Thus, the parsimonious two-factors model revealed by OPNMF encompasses the more complex factorization yielded by EFA while enjoying higher generalizability. Hence, OPNMF provides a conceptually meaningful, technically robust, and generalizable factorization for psychometric tools.

Endocrine stress response in pregnancy and 12 weeks postpartum - Exploring risk factors for postpartum depression.

Pregnancy and the postpartum period are characterized by physiological alterations in cortisol and cortisone levels. In the present study, we sought to explore the risk factors for postpartum depression (PPD) and self-remitting postpartum adjustment disorder (AD) and whether cortisol/cortisone metabolism might have any bearing on them. Hair samples from 196 participants (mean age = 31.44, SD = 4.71) were collected at two time points (1-6 days after childbirth and 12 weeks postpartum) to determine the cumulative hair cortisol (HCC) and hair cortisone (HCNC) exposure in the third trimester and during the 12 weeks postpartum. Compared to the non-depressed group (ND, n = 141), more women in the AD (n = 28) and PPD (n = 27) groups had a personal or family history of depression and more stressful life events. Compared to ND and PPD, more women in the AD group had birth-related complications with their children being more often transferred to a pediatric ward. The factors associated with PPD were found to include being unmarried and having a lower household income, less support at home, more subjectively perceived stress after childbirth and lower maternal sensitivity. The natural decrease in HCC concentration from the third trimester to 12 weeks postpartum was significant only in the ND and AD groups, but not in PPD. In summary, prolonged subjectively perceived postpartum stress associated with living situations may contribute to the development of PPD while birth- and child-related complications are likely to trigger brief episodes of AD. Only in ND and AD, the pregnancy-related physiological changes in glucocorticoid levels return to the pre-pregnancy baseline after 12 weeks. Our observations point to the difference between the ND and PPD groups in glucocorticoid metabolism-related postpartum adjustment, which may be a factor in the development of PPD.

Age estimation based on different molecular clocks in several tissues and a multivariate approach: an explorative study.

Several molecular modifications accumulate in the human organism with increasing age. Some of these "molecular clocks" in DNA and in proteins open up promising approaches for the development of methods for forensic age estimation. A natural limitation of these methods arises from the fact that the chronological age is determined only indirectly by analyzing defined molecular changes that occur during aging. These changes are not linked exclusively to the expired life span but may be influenced significantly by intrinsic and extrinsic factors in the complex process of individual aging. We tested the hypothesis that a combined use of different molecular clocks in different tissues results in more precise age estimates because this approach addresses the complex aging processes in a more comprehensive way. Two molecular clocks (accumulation of D-aspartic acid (D-Asp), accumulation of pentosidine (PEN)) in two different tissues (annulus fibrosus of intervertebral discs and elastic cartilage of the epiglottis) were analyzed in 95 cases, and uni- and multivariate models for age estimation were generated. The more parameters were included in the models for age estimation, the smaller the mean absolute errors (MAE) became. While the MAEs were 7.5-11.0 years in univariate models, a multivariate model based on the two protein clocks in the two tissues resulted in a MAE of 4.0 years. These results support our hypothesis. The tested approach of a combined analysis of different molecular clocks analyzed in different tissues opens up new possibilities in postmortem age estimation. In a next step, we will add the epigenetic clock (DNA methylation) to our protein clocks (PEN, D-Asp) and expand our set of tissues.

Urethral length and bladder neck behavior: can dynamic magnetic resonance imaging give the same results as introital ultrasound?

PURPOSE: To compare dynamic magnetic resonance imaging (dMRI) and introital ultrasound results with regard to urethral length measurements and the evaluation of bladder neck changes. METHODS: Retrospective analyses of urethral length measurements and detection of bladder neck changes (rotated/vertical bladder neck descent, urethral funneling) were conducted in women-scheduled for surgical treatment with alloplastic material-who had undergone introital ultrasound and dMRI presurgery and 3 months postsurgery. Measurement differences between both imaging modalities were evaluated by assessing the confidence interval for the difference in means between the datasets using bootstrap analysis. RESULTS: Based on data from 40 patients (320 image series), the urethra could be clearly measured on every pre- and postsurgical dMRI dataset but not on preoperative ultrasound images in nine women during Valsalva maneuver due to a large cystocele. The estimation of the mean difference distribution based on 500,000 bootstrap resamples indicated that the urethral length was measured shorter by dMRI pre- and postsurgery at rest and postsurgery during Valsalva maneuver (median 1.6-3.1 mm) but longer by dMRI (median 0.2 mm) during Valsalva maneuver presurgery. Rotated/vertical bladder neck descent and urethral funneling diagnoses showed concordance of 67-74% in the direct comparison of patients; the estimation of the concordance indicated poorer outcomes with 50-72%. CONCLUSIONS: Metric information on urethral length from dMRI is comparable to that from introital ultrasound. dMRI is more advantageous in cases with an extended organ prolapse. At present, dMRI does not give the same diagnosis on bladder neck changes as introital ultrasound does.

Network connectivity of motor control in the ageing brain.

Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for 'core' motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.

Definition and characterization of an extended multiple-demand network.

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.

Resting-state functional connectivity of emotion regulation networks in euthymic and non-euthymic bipolar disorder patients.

BACKGROUND: Previous functional magnetic resonance imaging studies in bipolar disorder (BD) have evidenced changes in functional connectivity (FC) in brain areas associated with emotion processing, but how these changes vary with mood state and specific clinical symptoms is not fully understood. METHODS: We investigated resting-state FC between a priori regions of interest (ROIs) from the default-mode network and key structures for emotion processing and regulation in 27 BD patients and 27 matched healthy controls. We further compared connectivity patterns in subgroups of 15 euthymic and 12 non-euthymic patients and tested for correlations of the connectivity strength with measures of mood, anxiety, and rumination tendency. No correction for multiple comparisons was applied given the small population sample and pre-defined target ROIs. RESULTS: Overall, regardless of mood state, BD patients exhibited increased FC of the left amygdala with left sgACC and PCC, relative to controls. In addition, non-euthymic BD patients showed distinctive decrease in FC between right amygdala and sgACC, whereas euthymic patients showed lower FC between PCC and sgACC. Euthymic patients also displayed increased FC between sgACC and right VLPFC. The sgACC-PCC and sgACC-left amygdala connections were modulated by rumination tendency in non-euthymic patients, whereas the sgACC-VLPFC connection was modulated by both the current mood and tendency to ruminate. CONCLUSION: Our results suggest that sgACC-amygdala coupling is critically affected during mood episodes, and that FC of sgACC play a pivotal role in mood normalization through its interactions with the VLPFC and PCC. However, these preliminary findings require replication with larger samples of patients.

Shaping Early Reorganization of Neural Networks Promotes Motor Function after Stroke.

Neural plasticity is a major factor driving cortical reorganization after stroke. We here tested whether repetitively enhancing motor cortex plasticity by means of intermittent theta-burst stimulation (iTBS) prior to physiotherapy might promote recovery of function early after stroke. Functional magnetic resonance imaging (fMRI) was used to elucidate underlying neural mechanisms. Twenty-six hospitalized, first-ever stroke patients (time since stroke: 1-16 days) with hand motor deficits were enrolled in a sham-controlled design and pseudo-randomized into 2 groups. iTBS was administered prior to physiotherapy on 5 consecutive days either over ipsilesional primary motor cortex (M1-stimulation group) or parieto-occipital vertex (control-stimulation group). Hand motor function, cortical excitability, and resting-state fMRI were assessed 1 day prior to the first stimulation and 1 day after the last stimulation. Recovery of grip strength was significantly stronger in the M1-stimulation compared to the control-stimulation group. Higher levels of motor network connectivity were associated with better motor outcome. Consistently, control-stimulated patients featured a decrease in intra- and interhemispheric connectivity of the motor network, which was absent in the M1-stimulation group. Hence, adding iTBS to prime physiotherapy in recovering stroke patients seems to interfere with motor network degradation, possibly reflecting alleviation of post-stroke diaschisis.

Transdiagnostic commonalities and differences in resting state functional connectivity of the default mode network in schizophrenia and major depression.

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.

Neural correlates of reactive aggression in children with attention-deficit/hyperactivity disorder and comorbid disruptive behaviour disorders.

OBJECTIVE: Attention deficit hyperactivity disorder (ADHD) is often linked with impulsive and aggressive behaviour, indexed by high comorbidity rates between ADHD and disruptive behaviour disorders (DBD). The present study aimed to investigate underlying neural activity of reactive aggression in children with ADHD and comorbid DBD using functional neuroimaging techniques (fMRI). METHOD: Eighteen boys with ADHD (age 9-14 years, 10 subjects with comorbid DBD) and 18 healthy controls were administered a modified fMRI-based version of the 'Point Subtraction Aggression Game' to elicit reactive aggressive behaviour. Trials consisted of an 'aggression phase' (punishment for a fictitious opponent) and an 'outcome phase' (presentation of the trial outcome). RESULTS: During the aggression phase, higher aggressive responses of control children were accompanied by higher activation of the ventral anterior cingulate cortex and the temporoparietal junction. Patients displayed inverted results. During the outcome phase, comparison between groups and conditions showed differential activation in the dorsal striatum and bilateral insular when subjects gained points. Losing points was accompanied by differential activation of regions belonging to the insula and the middle temporal sulcus. CONCLUSION: Data support the hypothesis that deficient inhibitory control mechanisms are related to increased impulsive aggressive behaviour in young people with ADHD and comorbid DBD.

PaMiNI-Derived Co-Activation Patterns Indicate Differential Hierarchical Levels for Two Ventral Visual Areas of the Fusiform Gyrus.

PURPOSE: To investigate the distribution of co-activation patterns of the recently identified ventral visual areas FG1 and FG2 of the posterior fusiform gyrus using the novel meta-analytic approach PaMiNI (Pattern Mining in NeuroImaging). MATERIALS AND METHODS: All neuroimaging experiments reporting activation foci within FG1 or FG2 were retrieved from the BrainMap database. The stereotaxic activation foci in standard reference space were analyzed with PaMiNI. Here, Gaussian mixture modeling was applied to the stereotaxic coordinates of all foci to identify the underlying brain regions of each dataset. Then, association analysis was performed to reveal frequent co-activations across the modeled brain regions. RESULTS: Co-activation patterns of FG1 were mainly found within the visual system, i.e. in early visual areas, and were symmetrically distributed across both hemispheres. FG2 features several extra-visual co-activations, mainly to inferior frontal, premotor and parietal regions. Furthermore, the co-activations of FG2 showed clear lateralization to the left FG2. CONCLUSION: FG1 shows characteristics of an intermediate visual area between the early ventral visual cortex and the category-specific higher-order areas. Co-activation patterns of FG2 indicate that FG2 is a higher-order visual area that probably corresponds to the posterior fusiform face area and partly the visual word-form area. Key points. Co-activation patterns of areas FG1 and FG2 were analyzed with PaMiNI. FG1 features mainly symmetric co-activations to areas of the visual system. FG2 shows several extra-visual co-activations, which are left-lateralized. FG1 corresponds to a hierarchically intermediate, FG2 to a higher-order visual area. The PaMiNI approach is extended to seed-specific mapping of co-activation patterns.

Co-activation based parcellation of the human frontal pole.

Historically, the human frontal pole (FP) has been considered as a single architectonic area. Brodmann's area 10 is located in the frontal lobe with known contributions in the execution of various higher order cognitive processes. However, recent cytoarchitectural studies of the FP in humans have shown that this portion of cortex contains two distinct cytoarchitectonic regions. Since architectonic differences are accompanied by differential connectivity and functions, the frontal pole qualifies as a candidate region for exploratory parcellation into functionally discrete sub-regions. We investigated whether this functional heterogeneity is reflected in distinct segregations within cytoarchitectonically defined FP-areas using meta-analytic co-activation based parcellation (CBP). The CBP method examined the co-activation patterns of all voxels within the FP as reported in functional neuroimaging studies archived in the BrainMap database. Voxels within the FP were subsequently clustered into sub-regions based on the similarity of their respective meta-analytically derived co-activation maps. Performing this CBP analysis on the FP via k-means clustering produced a distinct 3-cluster parcellation for each hemisphere corresponding to previously identified cytoarchitectural differences. Post-hoc functional characterization of clusters via BrainMap metadata revealed that lateral regions of the FP mapped to memory and emotion domains, while the dorso- and ventromedial clusters were associated broadly with emotion and social cognition processes. Furthermore, the dorsomedial regions contain an emphasis on theory of mind and affective related paradigms whereas ventromedial regions couple with reward tasks. Results from this study support previous segregations of the FP and provide meta-analytic contributions to the ongoing discussion of elucidating functional architecture within human FP.

Age-related decrease of functional connectivity additional to gray matter atrophy in a network for movement initiation.

Healthy aging is accompanied by a decrease in cognitive and motor capacities. In a network associated with movement initiation, we investigated age-related changes of functional connectivity (FC) as well as regional atrophy in a sample of 232 healthy subjects (age range 18-85 years). To this end, voxel-based morphometry and whole-brain resting-state FC were analyzed for the supplementary motor area (SMA), anterior midcingulate cortex (aMCC) and bilateral striatum (Str). To assess the specificity of age-related effects, bilateral primary sensorimotor cortex (S1/M1) closely associated with motor execution was used as control seeds. All regions showed strong reduction of gray matter volume with age. Corrected for this regional atrophy, the FC analysis revealed an age × seed interaction for each of the bilateral Str nodes against S1/M1 with consistent age-related decrease in FC with bilateral caudate nucleus and anterior putamen. Specific age-dependent FC decline of SMA was found in bilateral central insula and the adjacent frontal operculum. aMCC showed exclusive age-related decoupling from the anterior cingulate motor area. The present study demonstrates network as well as node-specific age-dependent FC decline of the SMA and aMCC to highly integrative cortical areas involved in cognitive motor control. FC decrease in addition to gray matter atrophy within the Str may provide a substrate for the declining motor control in elderly. Finally, age-related FC changes in both the network for movement initiation as well as the network for motor execution are not explained by regional atrophy in the healthy aging brain.

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associated with functional impairment in "individual" patients. We investigated whether fMRI allows classification of individual motor impairment after stroke using support vector machines (SVMs). Forty acute stroke patients and 20 control subjects underwent resting-state fMRI. Half of the patients showed significant impairment in hand motor function. Resting-state connectivity was computed by means of whole-brain correlations of seed time-courses in ipsilesional primary motor cortex (M1). Lesion location was identified using diffusion-weighted images. These features were used for linear SVM classification of unseen patients with respect to motor impairment. SVM results were compared with conventional mass-univariate analyses. Resting-state connectivity classified patients with hand motor deficits compared with controls and nonimpaired patients with 82.6-87.6% accuracy. Classification was driven by reduced interhemispheric M1 connectivity and enhanced connectivity between ipsilesional M1 and premotor areas. In contrast, lesion location provided only 50% sensitivity to classify impaired patients. Hence, resting-state fMRI reflects behavioral deficits more accurately than structural MRI. In conclusion, multivariate fMRI analyses offer the potential to serve as markers for endophenotypes of functional impairment.

The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis.

The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others' (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region.

Interoperable atlases of the human brain.

The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro- and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.

Neural network of cognitive emotion regulation--an ALE meta-analysis and MACM analysis.

Cognitive regulation of emotions is a fundamental prerequisite for intact social functioning which impacts on both well being and psychopathology. The neural underpinnings of this process have been studied intensively in recent years, without, however, a general consensus. We here quantitatively summarize the published literature on cognitive emotion regulation using activation likelihood estimation in fMRI and PET (23 studies/479 subjects). In addition, we assessed the particular functional contribution of identified regions and their interactions using quantitative functional inference and meta-analytic connectivity modeling, respectively. In doing so, we developed a model for the core brain network involved in emotion regulation of emotional reactivity. According to this, the superior temporal gyrus, angular gyrus and (pre) supplementary motor area should be involved in execution of regulation initiated by frontal areas. The dorsolateral prefrontal cortex may be related to regulation of cognitive processes such as attention, while the ventrolateral prefrontal cortex may not necessarily reflect the regulatory process per se, but signals salience and therefore the need to regulate. We also identified a cluster in the anterior middle cingulate cortex as a region, which is anatomically and functionally in an ideal position to influence behavior and subcortical structures related to affect generation. Hence this area may play a central, integrative role in emotion regulation. By focusing on regions commonly active across multiple studies, this proposed model should provide important a priori information for the assessment of dysregulated emotion regulation in psychiatric disorders.