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Coordinate-based meta-analysis (CBMA) is a powerful technique in the field of human brain imaging research. Due to its intense usage, several procedures for data preparation and post hoc analyses have been proposed so far. However, these steps are often performed manually by the researcher, and are therefore potentially prone to error and time-consuming. We hence developed the Coordinate-Based Meta-Analyses Toolbox (CBMAT) to provide a suite of user-friendly and automated MATLAB® functions allowing one to perform all these procedures in a fast, reproducible and reliable way. Besides the description of the code, in the present paper we also provide an annotated example of using CBMAT on a dataset including 34 experiments. CBMAT can therefore substantially improve the way data are handled when performing CBMAs. The code can be downloaded from https://github.com/Jordi-Manuello/CBMAT.git. [ABSTRACT FROM AUTHOR]

Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age ≤ 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology. [ABSTRACT FROM AUTHOR]

Activation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection criterion for the null hypothesis according to the critical p-value selected. However, this is not informative in terms of probabilities of the validity of the hypotheses. Here, we describe an innovative thresholding procedure based on the concept of minimum Bayes factor (mBF). The use of the Bayesian framework allows to consider different levels of probability, each of these being equally significant. In order to simplify the translation between the common ALE practice and the proposed approach, we analised six task-fMRI/VBM datasets and determined the mBF values equivalent to the currently recommended frequentist thresholds based on Family Wise Error (FWE). Sensitivity and robustness toward spurious findings were also analyzed. Results showed that the cutoff log10(mBF) = 5 is equivalent to the FWE threshold, often referred as voxel-level threshold, while the cutoff log10(mBF) = 2 is equivalent to the cluster-level FWE (c-FWE) threshold. However, only in the latter case voxels spatially far from the blobs of effect in the c-FWE ALE map survived. Therefore, when using the Bayesian thresholding the cutoff log10(mBF) = 5 should be preferred. However, being in the Bayesian framework, lower values are all equally significant, while suggesting weaker level of force for that hypothesis. Hence, results obtained through less conservative thresholds can be legitimately discussed without losing statistical rigor. The proposed technique adds therefore a powerful tool to the human-brain-mapping field. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) exhibits diverse symptomology and neuroimaging studies report widespread disruption of key brain areas. Numerous theories underpinning the network degeneration hypothesis (NDH) posit that neuropsychiatric diseases selectively target brain areas via meaningful network mechanisms rather than as indistinct disease effects. The present study tests the hypothesis that MDD is a network-based disorder, both structurally and functionally. Coordinate-based meta-analysis and Activation Likelihood Estimation (CBMA-ALE) were used to assess the convergence of findings from 92 previously published studies in depression. An extension of CBMA-ALE was then used to generate a node-and-edge network model representing the co-alteration of brain areas impacted by MDD. Standardized measures of graph theoretical network architecture were assessed. Co-alteration patterns among the meta-analytic MDD nodes were then tested in independent, clinical T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional (rs-fMRI) data. Differences in co-alteration profiles between MDD patients and healthy controls, as well as between controls and clinical subgroups of MDD patients, were assessed. A 65-node 144-edge co-alteration network model was derived for MDD. Testing of co-alteration profiles in replication data using the MDD nodes provided distinction between MDD and healthy controls in structural data. However, co-alteration profiles were not distinguished between patients and controls in rs-fMRI data. Improved distinction between patients and healthy controls was observed in clinically homogenous MDD subgroups in T1 data. MDD abnormalities demonstrated both structural and functional network architecture, though only structural networks exhibited between-groups differences. Our findings suggest improved utility of structural co-alteration networks for ongoing biomarker development. [ABSTRACT FROM AUTHOR]

An element of great interest in functional connectivity is 'homotopic connectivity' (HC), namely the connectivity between two mirrored areas of the two hemispheres, mainly mediated by the fibers of the corpus callosum. Despite a long tradition of studying sexual dimorphism in the human brain, to our knowledge only one study has addressed the influence of sex on HC. We investigated the issue of homotopic co-activations in women and men using a coordinate-based meta-analytic method and data from the BrainMap database. A first unexpected observation was that the database was affected by a sex bias: women-only groups are investigated less often than men-only ones, and they are more often studied in certain domains such as emotion compared to men, and less in cognition. Implementing a series of sampling procedures to equalize the size and proportion of the datasets, our results indicated that females exhibit stronger interhemispheric co-activation than males, suggesting that the female brain is less lateralized and more integrated than that of males. In addition, males appear to show less intense but more extensive co-activation than females. Some local differences also appeared. In particular, it appears that primary motor and perceptual areas are more co-activated in males, in contrast to the opposite trend in the rest of the brain. This argues for a multidimensional view of sex brain differences and suggests that the issue should be approached with more complex models than previously thought. [ABSTRACT FROM AUTHOR]

The cingulate cortex is known to be a complex structure, involved in several cognitive and emotional functions, as well as being altered by a variety of brain disorders. This heterogeneity is reflected in the multiple parceling models proposed in the literature. At the present, sub-regions of the cingulate cortex had been identified taking into account functional and structural connectivity, as well as cytological and electrochemical properties. In the present work, we propose an innovative node-wise parceling approach based on meta-analytic Bayesian co-alteration. To this aim, 193 case–control voxel-based morphometry experiments were analyzed, and the Patel's κ index was used to assess probability of morphometric co-alteration between nodes placed in the cingulate cortex and in the rest of the brain. Hierarchical clustering was then applied to identify nodes in the cingulate cortex exhibiting a similar pattern of whole-brain co-alteration. The obtained dendrogram highlighted a robust fronto-parietal cluster compatible with the default mode network, and being supported by the interplay between the retrosplenial cortex and the anterior and posterior cingulate cortex, rarely described in the literature. This ensemble was further confirmed by the analysis of functional patterns. Leveraging on co-alteration to investigate cortical organization could, therefore, allow to combine multimodal information, resolving conflicting results sometimes coming from the separate use of singular modalities. Crucially, this provides a valuable way to understand the pathological brain using data driven, whole-brain informed and context-specific evidence in a way not yet explored in the field. [ABSTRACT FROM AUTHOR]

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic–extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy. [ABSTRACT FROM AUTHOR]

Asymmetries in gray matter alterations raise important issues regarding the pathological co-alteration between hemispheres. Since homotopic areas are the most functionally connected sites between hemispheres and gray matter co-alterations depend on connectivity patterns, it is likely that this relationship might be mirrored in homologous interhemispheric co-altered areas. To explore this issue, we analyzed data of patients with Alzheimer's disease, schizophrenia, bipolar disorder and depressive disorder from the BrainMap voxel-based morphometry database. We calculated a map showing the pathological homotopic anatomical co-alteration between homologous brain areas. This map was compared with the meta-analytic homotopic connectivity map obtained from the BrainMap functional database, so as to have a meta-analytic connectivity modeling map between homologous areas. We applied an empirical Bayesian technique so as to determine a directional pathological co-alteration on the basis of the possible tendencies in the conditional probability of being co-altered of homologous brain areas. Our analysis provides evidence that: the hemispheric homologous areas appear to be anatomically co-altered; this pathological co-alteration is similar to the pattern of connectivity exhibited by the couples of homologues; the probability to find alterations in the areas of the left hemisphere seems to be greater when their right homologues are also altered than vice versa, an intriguing asymmetry that deserves to be further investigated and explained. [ABSTRACT FROM AUTHOR]

According to the predictive coding (PC) theory, the brain is constantly engaged in predicting its upcoming states and refining these predictions through error signals. Despite extensive research investigating the neural bases of this theory, to date no previous study has systematically attempted to define the neural mechanisms of predictive coding across studies and sensory channels, focussing on functional connectivity. In this study, we employ a coordinate-based meta-analytical approach to address this issue. We first use the Activation Likelihood Estimation (ALE) algorithm to detect spatial convergence across studies, related to prediction error and encoding. Overall, our ALE results suggest the ultimate role of the left inferior frontal gyrus and left insula in both processes. Moreover, we employ a meta-analytic connectivity method (Seed-Voxel Correlations Consensus). This technique reveals a large, bilateral predictive network, which resembles large-scale networks involved in task-driven attention and execution. In sum, we find that: (i) predictive processing seems to occur more in certain brain regions than others, when considering different sensory modalities at a time; (ii) there is no evidence, at the network level, for a distinction between error and prediction processing. [ABSTRACT FROM AUTHOR]

Network architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic 'cost' significantly differs along this transdiagnostic/multimodal gradient. Peter Fox & Thomas Vanasse et al. compare atrophy patterns in 40+ brain disorders with healthy task-activation networks across 100+ behavioral domains. Their analyses demonstrate strong spatial correspondence between disease-related structural coalterations and functional networks, an observation that greatly extends the scope of the network-degeneration hypothesis. Further, the metabolic cost of network hubs (nodal stress) is implicated as a common mechanism across a wide range of brain disorders. [ABSTRACT FROM AUTHOR]

Vasopressin receptor 2 (V2R) mutations causing the nephrogenic syndrome of inappropriate antidiuresis (NSIAD) can generate two constitutively active receptor phenotypes. One type results from residue substitutions in several V2R domains and is sensitive to vaptan inverse agonists. The other is only caused by Arg 137 replacements and is vaptan resistant. We compared constitutive and agonist-driven interactions of the vaptan-sensitive F229V and vaptan-resistant R137C/L V2R mutations with β-arrestin 1, β-arrestin 2, and Gαs, using null fibroblasts reconstituted with individual versions of the ablated transduction protein genes. F229V displayed very high level of constitutive activation for Gs but not for β-arrestins, and enhanced or normal responsiveness to agonists and inverse agonists. In contrast, R137C/L mutants exhibited maximal levels of constitutive activation for βarrestin 2 and Gs, minimal levels for β-arrestin 1, but a sharp decline of ligands sensitivity at all transducer interactions. The enhanced constitutive activity and reduced ligand sensitivity of R137 mutants on cAMP signaling persisted in cells lacking β-arrestins, indicating that these are intrinsic molecular properties of the mutations, not the consequence of altered receptor trafficking. The results suggest that the two groups of NSIAD mutations represent two distinct molecular mechanisms of constitutive activation in GPCRs. [ABSTRACT FROM AUTHOR]

Nephrogenic syndrome of inappropriate antidiuresis (NSIAD) is a recently identified chromosome X-linked disease associated with gain-of-function mutations of the V2 vasopressin receptor (V2R), a G-protein-coupled receptor. It is characterized by inability to excrete a free water load, hyponatremia, and undetectable vasopressin-circulating levels. Hyponatremia can be quite severe in affected male children. To gain a deeper insight into the functional properties of the V2R active mutants and how they might translate into the pathological outcome of NSIAD, in this study, we have expressed the wild-type V2R and three constitutively active V2R mutants associated with NSIAD (R137L, R137C, and the F229V) in MCD4 cells, a cell line derived from renal mouse collecting duct, stably expressing the vasopressin-sensitive water channel aquaporin-2 (AQP2). Our findings indicate that in cells expressing each active mutant, AQP2 was constitutively localized to the apical plasma membrane in the absence of vasopressin stimulation. In line with these observations, under basal conditions, osmotic water permeability in cells expressing the constitutively active mutants was significantly higher compared to that of cells expressing the wild-type V2R. Our findings demonstrate a direct link between activating mutations of the V2R and the perturbation of water balance in NSIAD. In addition, this study provides a useful cell-based assay system to assess the functional consequences of newly discovered activating mutations of the V2R on water permeability in kidney cells and to screen the effect of drugs on the mutated receptors. [ABSTRACT FROM AUTHOR]

Although very difficult to define, happiness is becoming a core concept within contemporary psychology and affective neuroscience. In the last two decades, the increased use of neuroimaging techniques has facilitated empirical study of the neural correlates of happiness. This area of research utilizes procedures that induce positive emotion and mood, and autobiographical recall is one of the most widely used and effective approaches. In this article, we review eight positron emission tomography and seven functional magnetic resonance imaging studies that have investigated happiness by using autobiographical recall to induce emotion. Regardless of the neuroimaging technique used, the studies conducted so far have shown that remembering happy events is primarily associated with the activation of many areas, including anterior cingulate cortex, prefrontal cortex, and insula. Importantly, these areas are also found to be connected with other basic emotions, such as sadness and anger. In the conclusion, we integrate these findings, discussing important limitations of the extant literature and suggesting new research directions. [ABSTRACT FROM AUTHOR]

The author discusses the ASF model which states that two reqisites are required for a ligand to be an agonist at the receptor. It states that the ligand should not only bind to a receptor but also trigger a biologically readable impulse known as stimulus. Also presents a list of questions and answers that reflect modern views on allosteric effects and cooperativity.

Equilibrium binding isotherms of [H]diprenorphine in membranes from NG 108-15 cells are consistent with a homogenous population of binding sites. Upon addition of Na, Mg and GTP, only a 2-fold reduction in affinity with a minor decrease in the number of sites is observed. Dissociation curves of [H]diprenorphine, however, are clearly biphasic: in the absence of Na, Mg and GTP, 80% of the bound ligand dissociates slowly with a t of 100 min, and only 20% rapidly ( t 4.5 min). In the presence of Mg, nearly all the binding is found in the slowly dissociating form. Upon the addition of either Na or GTP, 20-30% of the binding dissociates more rapidly. The rate constant of the rapidly dissociating form generated by Na, however, is 2.5 times greater than that induced by the presence of GTP. Thus, the addition of both, Na and GTP, converts about 80% of the receptor into a very fast dissociating form ( t 1.7 min). Exposure of intact cells to pertussis toxin (10 ng/ml) or treatment of membranes with N-ethyl maleimide (500 μM), strongly reduces the proportion of the slowly dissociating component. Following these treatments, the effect of GTP is reduced or abolished, but that of Na remains unaffected. We conclude from these data that the effects of Na and GTP are not only distinct in site but also in mechanism of action and that there are three forms of opioid receptors that can be differentiated by their kinetic properties. The slowly dissociating receptor form requires a functional N unit. [ABSTRACT FROM AUTHOR]

Homotopic connectivity (HC) is the connectivity between mirror areas of the brain hemispheres. It can exhibit a marked and functionally relevant spatial variability, and can be perturbed by several pathological conditions. The voxel-mirrored homotopic connectivity (VMHC) is a technique devised to enquire this pattern of brain organization, based on resting state functional connectivity. Since functional connectivity can be revealed also in a meta-analytical fashion using co-activations, here we propose to calculate the meta-analytic homotopic connectivity (MHC) as the meta-analytic counterpart of the VMHC. The comparison between the two techniques reveals their general similarity, but also highlights regional differences associated with how HC varies from task to rest. Two main differences were found from rest to task: (i) regions known to be characterized by global hubness are more similar than regions displaying local hubness; and (ii) medial areas are characterized by a higher degree of homotopic connectivity, while lateral areas appear to decrease their degree of homotopic connectivity during task performance. These findings show that MHC can be an insightful tool to study how the hemispheres functionally interact during task and rest conditions. [ABSTRACT FROM AUTHOR]

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective. [ABSTRACT FROM AUTHOR]

Discovering biased agonists requires a method that can reliably distinguish the bias in signalling due to unbalanced activation of diverse transduction proteins from that of differential amplification inherent to the system being studied, which invariably results from the non-linear nature of biological signalling networks and their measurement. We have systematically compared the performance of seven methods of bias diagnostics, all of which are based on the analysis of concentration-response curves of ligands according to classical receptor theory. We computed bias factors for a number of β-adrenergic agonists by comparing BRET assays of receptor-transducer interactions with Gs, Gi and arrestin. Using the same ligands, we also compared responses at signalling steps originated from the same receptor-transducer interaction, among which no biased efficacy is theoretically possible. In either case, we found a high level of false positive results and a general lack of correlation among methods. Altogether this analysis shows that all tested methods, including some of the most widely used in the literature, fail to distinguish true ligand bias from 'system bias' with confidence. We also propose two novel semi quantitative methods of bias diagnostics that appear to be more robust and reliable than currently available strategies. [ABSTRACT FROM AUTHOR]