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Abstract Background Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature. Findings In this report, we describe recent technical updates to the project and provide an educational description for performing meta-analyses in the BrainMap environment. Conclusions The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities. Future work on the BrainMap project regarding software and hardware advances are also discussed.

Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain. [ABSTRACT FROM AUTHOR]

Functional neuroimaging has the spatial resolution to explain the neural basis of emotions. Activation likelihood estimation (ALE), as opposed to traditional qualitative meta-analysis, quantifies convergence of activation across studies within affective categories. Others have used ALE to investigate a broad range of emotions, but without the convenience of the BrainMap database. We used the BrainMap database and analysis resources to run separate meta-analyses on coordinates reported for anger, anxiety, disgust, fear, happiness, humor, and sadness. Resultant ALE maps were compared to determine areas of convergence between emotions, as well as to identify affect-specific networks. Five out of the seven emotions demonstrated consistent activation within the amygdala, whereas all emotions consistently activated the right inferior frontal gyrus, which has been implicated as an integration hub for affective and cognitive processes. These data provide the framework for models of affect-specific networks, as well as emotional processing hubs, which can be used for future studies of functional or effective connectivity. [ABSTRACT FROM AUTHOR]

Background: Many women living with HIV experience gendered power inequalities, particularly in their intimate relationships, that prevent them from achieving optimal sexual and reproductive health (SRH) and exercising their rights. We assessed the effectiveness of interventions to improve self-efficacy and empowerment of women living with HIV to make SRH decisions through a systematic review. Methods and findings: We included peer-reviewed articles indexed in PubMed, PsycINFO, CINAHL, Embase, and Scopus published through January 3, 2017, presenting multi-arm or pre-post intervention evaluations measuring one of the following outcomes: (1) self-efficacy, empowerment, or measures of SRH decision-making ability, (2) SRH behaviors (e.g., condom use, contraceptive use), or (3) SRH outcomes (e.g., sexually transmitted infections [STIs]). Twenty-one studies evaluating 11 intervention approaches met the inclusion criteria. All were conducted in the United States or sub-Saharan Africa. Two high-quality randomized controlled trials (RCTs) showed significant decreases in incident gonorrhea and chlamydia. Sixteen studies measuring condom use generally found moderate increases associated with the intervention, including in higher-quality RCTs. Findings on contraceptive use, condom self-efficacy, and other empowerment measures (e.g., sexual communication, equitable relationship power) were mixed. Studies were limited by small sample sizes, high loss to follow-up, and high reported baseline condom use. Conclusions: While more research is needed, the limited existing evidence suggests that these interventions may help support the SRH and rights of women living with HIV. This review particularly highlights the importance of these interventions for preventing STIs, which present a significant health burden for women living with HIV that is rarely addressed holistically. Empowerment-based interventions should be considered as part of a comprehensive package of STI and other SRH services for women living with HIV. [ABSTRACT FROM AUTHOR]

The high rate of fatal suicidal behavior (SB) in men is an urgent issue as highlighted in the public eye via news sources and media outlets. In this study, we have attempted to address this issue and understand the neural substrates underlying the gender differences in the rate of fatal SB. The Interpersonal-Psychological Theory of Suicide has proposed an explanation for the seemingly paradoxical relationship between gender and SB, i.e., greater non-fatal suicide attempts by women but higher number of deaths by suicide in men. This theory states that possessing suicidal desire (due to conditions such as depression) alone is not sufficient for a lethal suicide attempt. It is imperative for an individual to have the acquired capability for suicide (ACS) along with suicidal desire in order to die by suicide. Therefore, higher levels of ACS in men may explain why men are more likely to die by suicide than women, despite being less likely to experience suicidal ideation or depression. In this study, we used activation likelihood estimation meta-analysis to investigate a potential ACS network that involves neural substrates underlying emotional stoicism, sensation-seeking, pain tolerance, and fearlessness of death, along with a potential depression network that involves neural substrates that underlie clinical depression. Brain regions commonly found in ACS and depression networks for males and females were further used as seeds to obtain regions functionally and structurally connected to them. We found that the male-specific networks were more widespread and diverse than the female-specific ones. Also, while the former involved motor regions, such as the premotor cortex and cerebellum, the latter was dominated by limbic regions. This may support the fact that suicidal desire generally leads to fatal/ decisive action in males, while, in females, it manifests as depression, ideation, and generally non-fatal actions. The proposed model is a first attempt to characterize the neural networks underlying gender differences in SB. Future studies should examine the proposed network to better characterize and refine this network using tasks specifically targeted toward constructs underlying ACS. [ABSTRACT FROM AUTHOR]

Much of what was assumed about the functional topography of the hippocampus was derived from a single case study over half a century ago. Given advances in the imaging sciences, a new era of discovery is underway, with potential to transform the understanding of healthy processing as well as the ability to treat disorders. Coactivation-based parcellation, a meta-analytic approach, and ultra-high field, high-resolution functional and structural neuroimaging to characterize the neurofunctional topography of the hippocampus was employed. Data revealed strong support for an evolutionarily preserved topography along the long-axis. Specifically, the left hippocampus was segmented into three distinct clusters: an emotional processing cluster supported by structural and functional connectivity to the amygdala and parahippocampal gyrus, a cognitive operations cluster, with functional connectivity to the anterior cingulate and inferior frontal gyrus, and a posterior perceptual cluster with distinct structural connectivity patterns to the occipital lobe coupled with functional connectivity to the precuneus and angular gyrus. The right hippocampal segmentation was more ambiguous, with plausible 2- and 5-cluster solutions. Segmentations shared connectivity with brain regions known to support the correlated processes. This represented the first neurofunctional topographic model of the hippocampus using a robust, bias-free, multimodal approach. [ABSTRACT FROM AUTHOR]

Abstract: Meta-analysis based techniques are emerging as powerful, robust tools for developing models of connectivity in functional neuroimaging. Here, we apply meta-analytic connectivity modeling to the human caudate to 1) develop a model of functional connectivity, 2) determine if meta-analytic methods are sufficiently sensitive to detect behavioral domain specificity within region-specific functional connectivity networks, and 3) compare meta-analytic driven segmentation to structural connectivity parcellation using diffusion tensor imaging. Results demonstrate strong coherence between meta-analytic and data-driven methods. Specifically, we found that behavioral filtering resulted in cognition and emotion related structures and networks primarily localized to the head of the caudate nucleus, while perceptual and action specific regions localized to the body of the caudate, consistent with early models of nonhuman primate histological studies and postmortem studies in humans. Diffusion tensor imaging (DTI) revealed support for meta-analytic connectivity modeling''s (MACM) utility in identifying both direct and indirect connectivity. Our results provide further validation of meta-analytic connectivity modeling, while also highlighting an additional potential, namely the extraction of behavioral domain specific functional connectivity. [Copyright &y& Elsevier]

Abstract: Spatial normalization of neuroimaging data is a standard step when assessing group effects. As a result of divergent analysis procedures due to different normalization algorithms or templates, not all published coordinates refer to the same neuroanatomical region. Specifically, the literature is populated with results in the form of MNI or Talairach coordinates, and their disparity can impede the comparison of results across different studies. This becomes particularly problematic in coordinate-based meta-analyses, wherein coordinate disparity should be corrected to reduce error and facilitate literature reviews. In this study, a quantitative comparison was performed on two corrections, the Brett transform (i.e., “mni2tal”), and the Lancaster transform (i.e., “icbm2tal”). Functional magnetic resonance imaging (fMRI) data acquired during a standard paired associates task indicated that the disparity between MNI and Talairach coordinates was better reduced via the Lancaster transform, as compared to the Brett transform. In addition, an activation likelihood estimation (ALE) meta-analysis of the paired associates literature revealed that a higher degree of concordance was obtained when using the Lancaster transform in the form of fewer, smaller, and more intense clusters. Based on these results, we recommend that the Lancaster transform be adopted as the community standard for reducing disparity between results reported as MNI or Talairach coordinates, and suggest that future spatial normalization strategies be designed to minimize this variability in the literature. [Copyright &y& Elsevier]

Working memory (WM), or the ability to temporarily store and manipulate information, is one of the most widely studied constructs in cognitive psychology. Since its inception, it has become one of the leading explanations for how humans are able to operate on a cognitive level. The current study probed the neural networks underlying one of the most commonly used tasks, delayed match-to-sample (DMTS), to study WM. An activation likelihood estimation (ALE) analysis of 42 functional neuroimaging studies (626 participants) was conducted to demonstrate neural network engagement during DMTS. Results demonstrated strong convergence in brain regions commonly associated with the working memory construct (i.e., dorsolateral prefrontal cortex, fusiform gyrus, and posterior parietal cortex). However, neural activation in two regions frequently attributed to WM were absent from this meta-analysis: the anterior cingulate and the rostral prefrontal cortex, suggesting that these regions may be more sensitive to task or stimuli characteristics. In a post-hoc analysis, we deconstructed the DMTS meta-analysis to examine nonverbal versus verbal stimuli, and found notable neurofunctional differences such that DMTS using nonverbal stimuli consistently engaged the right middle frontal gyrus (BA 6/46) and precuneus (BA 7) more so than verbal stimuli based DMTS. These results provide a foundation for future models of functional connectivity that may elucidate subtle differences in working memory attributable to pathological processes. [ABSTRACT FROM AUTHOR]

Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. [ABSTRACT FROM AUTHOR]

Background: Although structural neuroimaging methods have been widely used to study brain morphology in schizophrenia, synthesizing this literature has been difficult. With the increasing popularity of voxel-based morphometric (VBM) methods in which group differences are reported in standardized coordinates, it is possible to apply powerful meta-analytic techniques initially designed for functional neuroimaging. In this study, we performed a voxelwise, coordinate-based meta-analysis to better conceptualize the neuroanatomic correlates of schizophrenia. Methods: Thirty-one peer-reviewed articles, with a total of 1195 patients with schizophrenia contrasted with 1262 healthy volunteers, were included in the meta-analysis. Coordinates from each article were used to create a statistical map that estimated the likelihood of between-group gray matter density differences at every brain voxel. These results were subsequently entered into a network analysis. Results: Patients had reduced gray matter density relative to control subjects in a distributed network of regions, including bilateral insular cortex, anterior cingulate, left parahippocampal gyrus, left middle frontal gyrus, postcentral gyrus, and thalamus. Network analysis grouped these regions into four distinct networks that potentially represent different pathologic processes. Patients had increased gray matter density in striatal regions. Conclusions: This study expands on previous meta-analyses of the neuroanatomy of schizophrenia by elucidating a series of brain networks disrupted by the illness. Because it is possible that these networks are influenced by independent etiologic factors, this work should foster more detailed neural models of the illness and focus research designed to discover the mechanisms of gray matter reduction in schizophrenia. [Copyright &y& Elsevier]