Meta-analytic connectivity modelling of deception-related brain regions.
Ontology highlight
ABSTRACT:
SUBMITTER: Meier SK
PROVIDER: S-EPMC8386837 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: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.
| S-EPMC6399443 | biostudies-literature
Project description:The superior temporal sulcus (STS) is a critical region for multiple neural processes in the human brain Hein and Knight (J Cogn Neurosci 20(12): 2125-2136, 2008). To better understand the multiple functions of the STS it would be useful to know more about its consistent functional coactivations with other brain regions. We used the meta-analytic connectivity modeling technique to determine consistent functional coactivation patterns across experiments and behaviors associated with bilateral anterior, middle, and posterior anatomical STS subregions. Based on prevailing models for the cortical organization of audition and language, we broadly hypothesized that across various behaviors the posterior STS (pSTS) would coactivate with dorsal-stream regions, whereas the anterior STS (aSTS) would coactivate with ventral-stream regions. The results revealed distinct coactivation patterns for each STS subregion, with some overlap in the frontal and temporal areas, and generally similar coactivation patterns for the left and right STS. Quantitative comparison of STS subregion coactivation maps demonstrated that the pSTS coactivated more strongly than other STS subregions in the same hemisphere with dorsal-stream regions, such as the inferior parietal lobule (only left pSTS), homotopic pSTS, precentral gyrus and supplementary motor area. In contrast, the aSTS showed more coactivation with some ventral-stream regions, such as the homotopic anterior temporal cortex and left inferior frontal gyrus, pars orbitalis (only right aSTS). These findings demonstrate consistent coactivation maps across experiments and behaviors for different anatomical STS subregions, which may help future studies consider various STS functions in the broader context of generalized coactivations for individuals with and without neurological disorders.
| S-EPMC6040641 | biostudies-literature
Project description:Co-activation of distinct brain regions is a measure of functional interaction, or connectivity, between those regions. The co-activation pattern of a given region can be investigated using seed-based activation likelihood estimation meta-analysis of functional neuroimaging data stored in databases such as BrainMap. This method reveals inter-regional functional connectivity by determining brain regions that are consistently co-activated with a given region of interest (the "seed") across a broad range of experiments. In current implementations of this meta-analytic connectivity modeling (MACM), significant spatial convergence (i.e. consistent co-activation) is distinguished from noise by comparing it against an unbiased null-distribution of random spatial associations between experiments according to which all gray-matter voxels have the same chance of convergence. As the a priori probability of finding activation in different voxels markedly differs across the brain, computing such a quasi-rectangular null-distribution renders the detection of significant convergence more likely in those voxels that are frequently activated. Here, we propose and test a modified MACM approach that takes this activation frequency bias into account. In this new specific co-activation likelihood estimation (SCALE) algorithm, a null-distribution is generated that reflects the base rate of reporting activation in any given voxel and thus equalizes the a priori chance of finding across-study convergence in each voxel of the brain. Using four exemplary seed regions (right visual area V4, left anterior insula, right intraparietal sulcus, and subgenual cingulum), our tests corroborated the enhanced specificity of the modified algorithm, indicating that SCALE may be especially useful for delineating distinct core networks of co-activation.
| S-EPMC4112007 | biostudies-literature
Project description:The cerebellum historically has been thought to mediate motor and sensory signals between the body and cerebral cortex, yet cerebellar lesions are also associated with altered cognitive behavioral performance. Neuroimaging evidence indicates that the cerebellum contributes to a wide range of cognitive, perceptual, and motor functions. Here, we used the BrainMap database to investigate whole-brainco-activation patterns between cerebellar structures and regions of the cerebral cortex, as well as associations with behavioral tasks. Hierarchical clustering was performed to meta-analytically identify cerebellar structures with similar cortical co-activation, and independently, with similar correlations to specific behavioral tasks. Strong correspondences were observed in these separate but parallel analyses of meta-analytic connectivity and behavioral metadata. We recovered differential zones of cerebellar co-activation that are reflected across the literature. Furthermore, the behaviors and tasks associated with the different cerebellar zones provide insight into the specialized function of the cerebellum, relating to high-order cognition, emotion, perception, interoception, and action. Taken together, these task-basedmeta-analytic results implicate distinct zones of the cerebellum as critically involved in the monitoring and mediation of psychological responses to internal and external stimuli.
| S-EPMC4512917 | biostudies-literature
Project description:The human insula has been parcellated on the basis of resting state functional connectivity and diffusion tensor imaging. Little is known about the organization of the insula when involved in active tasks. We explored this issue using a novel meta-analytic clustering approach. We queried the BrainMap database asking for papers involving normal subjects that recorded activations in the insular cortex, retrieving 1305 papers, involving 22,872 subjects and a total of 2957 foci. Data were analyzed with several different methodologies, some of which expressly designed for this work. We used meta-analytic connectivity modeling and meta-analytic clustering of data obtained from the BrainMap database. We performed cluster analysis to subdivide the insula in areas with homogeneous connectivity, and density analysis of the activated foci using Voronoi tessellation. Our results confirm and extend previous findings obtained investigating the resting state connectivity of the anterior-posterior and left-right insulae. They indicate, for the first time, that some blocks of the anterior insula play the role of hubs between the anterior and the posterior insulae, as confirmed by their activation in several different paradigms. This finding supports the view that the network to which the anterior insula belongs is related to saliency detection. The insulae of both sides can be parcellated in two clusters, the anterior and the posterior: the anterior is characterized by an attentional pattern of connectivity with frontal, cingulate, parietal, cerebellar and anterior insular highly connected areas, whereas the posterior is characterized by a more local connectivity pattern with connections to sensorimotor, temporal and posterior cingulate areas. This antero-posterior subdivision, better characterized on the right side, results sharper with the connectivity based clusterization than with the behavioral based clusterization. The circuits belonging to the anterior insula are very homogeneous and their blocks in multidimensional scaling of MACM-based profiles are in central position, whereas those belonging to the posterior insula, especially on the left, are located at the periphery and sparse, thus suggesting that the posterior circuits bear a more heterogeneous connectivity. The anterior cluster is mostly activated by cognition, whereas the posterior is mostly activated by interoception, perception and emotion.
| S-EPMC4782788 | biostudies-literature
Project description:The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures--search information and path transitivity--which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.
| S-EPMC3896172 | biostudies-literature
Project description:The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies. The analysis revealed a clear divergence in the pattern of connectivity for the medial OFC (mOFC) and lateral OFC (lOFC) regions. The lOFC showed coactivations with a network of prefrontal regions and areas involved in cognitive functions including language and memory. In contrast, the mOFC showed connectivity with default mode, autonomic, and limbic regions. Convergent patterns of coactivations were observed in the amygdala, hippocampus, striatum, and thalamus. A small number of regions showed connectivity specific to the anterior or posterior sectors of the OFC. Task domains involving memory, semantic processing, face processing, and reward were additionally analyzed in order to identify the different patterns of OFC functional connectivity associated with specific cognitive and affective processes. These data provide a framework for understanding the human OFC's position within widespread functional networks.
| S-EPMC3862271 | biostudies-literature
Project description:BackgroundThyroid-associated ophthalmopathy (TAO) is an orbital disease closely related to thyroid disease with a long-lasting duration that can be blinding and disabling. Recently, structural and functional neuroimaging studies have been performed in TAO patients, but studies have reported inconsistent results. This quantitative meta-analysis was conducted to identify convergent patterns of abnormal brain function among different studies in TAO.MethodsWe searched PubMed, EMBASE, Cochrane, and Web of Science, performed reference tracking, and retrieved 15 eligible studies. Peak coordinates were extracted from these studies and subsequently tested for convergence using activation likelihood estimation (ALE).ResultsCompared to healthy subjects, resting-state brain activity in the whole brain of TAO patients was significantly increased in the left superior frontal gyrus (SFG) and decreased in the left cuneus/precuneus. Functional decoding analysis of the BrainMap database revealed that these regions are predominantly associated with cognitive and emotional impairment. In this study, task-related meta-analytic connectivity modeling (MACM) analysis was used to describe the connectivity and function of the two seed regions. Significant coactivation of these regions was found primarily in the bilateral superior parietal lobule, medial frontal gyrus, left fusiform gyrus, left cingulate gyrus, supplementary motor area and thalamus.ConclusionOur findings underscore the role of the SFG and the cuneus/precuneus in the pathophysiology of TAO, highlighting the crucial impact of working memory deficits.
| S-EPMC10788440 | biostudies-literature
Project description:Most everyday behaviors and laboratory tasks rely on visual, auditory and/or motor-related processes. Yet, to date, there has been no large-scale quantitative synthesis of functional neuroimaging studies mapping the brain regions consistently recruited during such perceptuo-motor processing. We therefore performed three coordinate-based meta-analyses, sampling the results of neuroimaging experiments on visual (n = 114), auditory (n = 122), or motor-related (n = 251) processing, respectively, from the BrainMap database. Our analyses yielded both regions known to be recruited for basic perceptual or motor processes and additional regions in posterior frontal cortex. Comparing our results with data-driven network definitions based on resting-state functional connectivity revealed good overlap in expected regions but also showed that perceptual and motor task-related activations consistently involve additional frontal, cerebellar, and subcortical areas associated with "higher-order" cognitive functions, extending beyond what is captured when the brain is at "rest." Our resulting sets of domain-typical brain regions can be used by the neuroimaging community as robust functional definitions or masks of regions of interest when investigating brain correlates of perceptual or motor processes and their interplay with other mental functions such as cognitive control or affective processing. The maps are made publicly available via the ANIMA database.
| S-EPMC8113600 | biostudies-literature
Project description:Human beings are social animals and they vary in the degree to which they share information about themselves with others. Although brain networks involved in self-related cognition have been identified, especially via the use of resting-state experiments, the neural circuitry underlying individual differences in the sharing of self-related information is currently unknown. Therefore, we investigated the intrinsic functional organization of the brain with respect to participants' degree of self-related information sharing using resting state functional magnetic resonance imaging and self-reported social media use. We conducted seed-based correlation analyses in cortical midline regions previously shown in meta-analyses to be involved in self-referential cognition: the medial prefrontal cortex (MPFC), central precuneus (CP), and caudal anterior cingulate cortex (CACC). We examined whether and how functional connectivity between these regions and the rest of the brain was associated with participants' degree of self-related information sharing. Analyses revealed associations between the MPFC and right dorsolateral prefrontal cortex (DLPFC), as well as the CP with the right DLPFC, the left lateral orbitofrontal cortex and left anterior temporal pole. These findings extend our present knowledge of functional brain connectivity, specifically demonstrating how the brain's intrinsic functional organization relates to individual differences in the sharing of self-related information.
| S-EPMC4780087 | biostudies-other