7 T characterization of excitatory and inhibitory systems of acute pain in healthy female participants.

Current understanding of the physiological underpinnings of normative pain processing is incomplete. Enhanced knowledge of these systems is necessary to advance our understanding of pain processes as well as to develop effective therapeutic interventions. Previous neuroimaging research suggests a network of interrelated brain regions that seem to be implicated in the processing and experience of pain. Among these, the dorsal anterior cingulate cortex (dACC) plays an important role in the affective aspects of pain signals. The current study leveraged functional MRS to investigate the underlying dynamic shifts in the neurometabolic signature of the human dACC at rest and during acute pain. Results provide support for increased glutamate levels following acute pain administration. Specifically, a 4.6% increase in glutamate was observed during moderate pressure pain compared with baseline. Exploratory analysis also revealed meaningful changes in dACC gamma aminobutyric acid in response to pain stimulation. These data contribute toward the characterization of neurometabolic shifts, which lend insight into the role of the dACC in the pain network. Further research in this area with larger sample sizes could contribute to the development of novel therapeutics or other advances in pain-related outcomes.

Systematic review and meta-analysis of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators tested for antinociceptive effects in animal models of injury-related or pathological persistent pain.

ABSTRACT: We report a systematic review and meta-analysis of studies that assessed the antinociceptive efficacy of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators on pain-associated behavioural outcomes in animal models of pathological or injury-related persistent pain. In April 2019, we systematically searched 3 online databases and used crowd science and machine learning to identify studies for inclusion. We calculated a standardised mean difference effect size for each comparison and performed a random-effects meta-analysis. We assessed the impact of study design characteristics and reporting of mitigations to reduce the risk of bias. We meta-analysed 374 studies in which 171 interventions were assessed for antinociceptive efficacy in rodent models of pathological or injury-related pain. Most experiments were conducted in male animals (86%). Antinociceptive efficacy was most frequently measured by attenuation of hypersensitivity to evoked limb withdrawal. Selective cannabinoid type 1, cannabinoid type 2, nonselective cannabinoid receptor agonists (including delta-9-tetrahydrocannabinol) and peroxisome proliferator-activated receptor-alpha agonists (predominantly palmitoylethanolamide) significantly attenuated pain-associated behaviours in a broad range of inflammatory and neuropathic pain models. Fatty acid amide hydrolase inhibitors, monoacylglycerol lipase inhibitors, and cannabidiol significantly attenuated pain-associated behaviours in neuropathic pain models but yielded mixed results in inflammatory pain models. The reporting of criteria to reduce the risk of bias was low; therefore, the studies have an unclear risk of bias. The value of future studies could be enhanced by improving the reporting of methodological criteria, the clinical relevance of the models, and behavioural assessments. Notwithstanding, the evidence supports the hypothesis of cannabinoid-induced analgesia.

Neurophysiological Effects of Whole Coffee Cherry Extract in Older Adults with Subjective Cognitive Impairment: A Randomized, Double-Blind, Placebo-Controlled, Cross-Over Pilot Study.

Bioactive plant-based compounds have shown promise as protective agents across multiple domains including improvements in neurological and psychological measures. Methodological challenges have limited our understanding of the neurophysiological changes associated with polyphenol-rich supplements such as whole coffee cherry extract (WCCE). In the current study, we (1) compared 100 mg of WCCE to a placebo using an acute, randomized, double-blind, within-subject, cross-over design, and we (2) conducted a phytochemical analysis of WCCE. The primary objective of the study was to determine the neurophysiological and behavioral changes that resulted from the acute administration of WCCE. We hypothesized that WCCE would increase brain-derived neurotrophic factor (BDNF) and glutamate levels while also increasing neurofunctional measures in cognitive brain regions. Furthermore, we expected there to be increased behavioral performance associated with WCCE, as measured by reaction time and accuracy. Participants underwent four neuroimaging scans (pre- and post-WCCE and placebo) to assess neurofunctional/metabolic outcomes using functional magnetic resonance imaging and magnetic resonance spectroscopy. The results suggest that polyphenol-rich WCCE is associated with decreased reaction time and may protect against cognitive errors on tasks of working memory and response inhibition. Behavioral findings were concomitant with neurofunctional changes in structures involved in decision-making and attention. Specifically, we found increased functional connectivity between the anterior cingulate and regions involved in sensory and decision-making networks. Additionally, we observed increased BDNF and an increased glutamate/gamma-aminobutyric acid (GABA) ratio following WCCE administration. These results suggest that WCCE is associated with acute neurophysiological changes supportive of faster reaction times and increased, sustained attention.

Effective Self-Management for Early Career Researchers in the Natural and Life Sciences.

Early career researchers (ECRs) are faced with a range of competing pressures in academia, making self-management key to building a successful career. The Organization for Human Brain Mapping undertook a group effort to gather helpful advice for ECRs in self-management.

Left, right, or bilateral amygdala activation? How effects of smoothing and motion correction on ultra-high field, high-resolution functional magnetic resonance imaging (fMRI) data alter inferences.

Given the amygdala's role in survival mechanisms, and its pivotal contributions to psychological processes, it is no surprise that it is one of the most well-studied brain regions. One of the common methods for understanding the functional role of the amygdala is the use of functional magnetic resonance imaging (fMRI). However, fMRI tends to be acquired using resolutions that are not optimal for smaller brain structures. Furthermore, standard processing includes spatial smoothing and motion correction which further degrade the resolution of the data. Inferentially, this may be detrimental when determining if the amygdalae are active during a task. Indeed, studies using the same task may show differential amygdala(e) activation. Here, we examine the effects of well-accepted preprocessing steps on whole-brain submillimeter fMRI data to determine the impact on activation patterns associated with a robust task known to activate the amygdala(e). We analyzed 7T fMRI data from 30 healthy individuals collected at sub-millimeter in-plane resolution and used a field standard preprocessing pipeline with different combinations of smoothing kernels and motion correction options. Resultant amygdalae activation patterns were altered depending on which combination of smoothing and motion correction were performed, indicating that whole-brain preprocessing steps have a significant impact on the inferences that can be drawn about smaller, subcortical structures like the amygdala.

Differential functional patterns of the human posterior cingulate cortex during activation and deactivation: a meta-analytic connectivity model.

The posterior cingulate cortex (PCC) has been implicated in a host of cognitive and behavioral processes in addition to serving as a central hub in the default mode network (DMN). Moreover, the PCC has been shown to be involved in a range of psychiatric and neurological disorders. However, very little is known about the specific activated/deactivated functional profiles of the PCC. Here, we employed a dual analytic approach using robust quantitative meta-analytical connectivity modeling (MACM) and ultra-high field, high resolution resting state functional magnetic resonance imaging (rs-fMRI) to identify state-specific functional activity patterns of the human PCC. The MACM results provided evidence for regions of convergence for PCC co-activation and co-deactivation (i.e., left medial frontal gyrus, left amygdala, and left anterior cingulate) as well as regions of divergence specific to either PCC activation (i.e., bilateral inferior frontal gyri) or PCC deactivation (i.e., left parahippocampal gyrus). In addition, exploratory MACMs on dorsal and ventral subregions of the PCC revealed differential functional activity patterns such as greater co-activation of the right PCC and left inferior parietal lobule with the dorsal PCC and greater co-activation of right precuneus with the ventral PCC. Resting state connectivity analyses showed widespread connectivity similar to that of the PCC co-activation-based MACM, but also demonstrated additional regions of activity, including bilateral superior parietal regions and right superior temporal regions. These analyses highlight the diverse neurofunctional repertoire of the human PCC, provide additional insight into its dynamic functional activity patterns as it switches between activated and deactivated states, and elucidates the cognitive processes that may be implicated in clinical populations.

A Systematic Review and Meta-Analysis of School-Based Stress, Anxiety, and Depression Prevention Programs for Adolescents.

Given the recent rise in adolescent mental health issues, many researchers have turned to school-based mental health programs as a way to reduce stress, anxiety, and depressive symptoms among large groups of adolescents. The purpose of the current systematic review and meta-analysis is to identify and evaluate the efficacy of school-based programming aimed at reducing internalizing mental health problems of adolescents. A total of 42 articles, including a total of 7310 adolescents, ages 11-18, met inclusion for the meta-analyses. Meta-analyses were completed for each of the three mental health outcomes (stress, depression, and anxiety) and meta-regression was used to determine the influence of type of program, program dose, sex, race, and age on program effectiveness. Overall, stress interventions did not reduce stress symptoms, although targeted interventions showed greater reductions in stress than universal programs. Overall, anxiety interventions significantly reduced anxiety symptoms, however higher doses may be necessary for universal programs. Lastly, depression interventions significantly reduced depressive symptoms, but this reduction was moderated by a combination of program type, dose, race, and age group. Although, school-based programs aimed at decreasing anxiety and depression were effective, these effects are not long-lasting. Interventions aimed at reducing stress were not effective, however very few programs targeted or included stress as an outcome variable. Implications for practice, policy and research are discussed.

Effects of cannabinoid administration for pain: A meta-analysis and meta-regression.

Chronic pain states have resulted in an overreliance on opioid pain relievers, which can carry significant risks when used long term. As such, alternative pain treatments are increasingly desired. Although emerging research suggests that cannabinoids have therapeutic potential regarding pain, results from studies across pain populations have been inconsistent. To provide meta-analytic clarification regarding cannabis's impact on subjective pain, we identified studies that assessed drug-induced pain modulations under cannabinoid and corresponding placebo conditions. A literature search yielded 25 peer-reviewed records that underwent data extraction. Baseline and end-point data were used to compute standardized effect size estimates (Cohen's d) across cannabinoid administrations (k = 39) and placebo administrations (k = 26). Standardized effects were inverse-variance weighted and pooled across studies for meta-analytic comparison. Results revealed that cannabinoid administration produced a medium-to-large effect across included studies, Cohen's d = -0.58, 95% confidence interval (CI) [-0.74, -0.43], while placebo administration produced a small-to-medium effect, Cohen's d = -0.39, 95% CI [-0.52, -0.26]. Meta-regression revealed that cannabinoids, ß = -0.43, 95% CI [-0.62, -0.24], p < .05, synthetic cannabinoids, ß = -0.39, 95% CI [-0.65, -0.14], p < .05, and sample size, ß = 0.01, 95% CI [0.00, 0.01], p < .05, were associated with marked pain reduction. These outcomes suggest that cannabinoid-based pharmacotherapies may serve as effective replacement/adjunctive options regarding pain, however, additional research is warranted. Additionally, given demonstrated neurocognitive side effects associated with some constituent cannabinoids (i.e., THC), subsequent work may consider developing novel therapeutic agents that capitalize on cannabis's analgesic properties without producing adverse effects. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks.

Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing.

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.

Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations.

BACKGROUND: Whereas acute nicotine administration alters brain function which may, in turn, contribute to enhanced attention and performance, chronic cigarette smoking is linked with regional brain atrophy and poorer cognition. However, results from structural magnetic resonance imaging (MRI) studies comparing smokers versus nonsmokers have been inconsistent and measures of gray matter possess limited ability to inform functional relations or behavioral implications. The purpose of this study was to address these interpretational challenges through meta-analytic techniques in the service of clarifying the impact of chronic smoking on gray matter integrity and more fully contextualizing such structural alterations. METHODS: We first conducted a coordinate-based meta-analysis of structural MRI studies to identify consistent structural alterations associated with chronic smoking. Subsequently, we conducted two additional meta-analytic assessments to enhance insight into potential functional and behavioral relations. Specifically, we performed a multimodal meta-analytic assessment to test the structural-functional hypothesis that smoking-related structural alterations overlapped those same regions showing acute nicotinic drug-induced functional modulations. Finally, we employed database driven tools to identify pairs of structurally impacted regions that were also functionally related via meta-analytic connectivity modeling, and then delineated behavioral phenomena associated with such functional interactions via behavioral decoding. RESULTS: Across studies, smoking was associated with convergent structural decreases in the left insula, right cerebellum, parahippocampus, multiple prefrontal cortex (PFC) regions, and the thalamus. Indicating a structural-functional relation, we observed that smoking-related gray matter decreases overlapped with the acute functional effects of nicotinic agonist administration in the left insula, ventromedial PFC, and mediodorsal thalamus. Suggesting structural-behavioral implications, we observed that the left insula's task-based, functional interactions with multiple other structurally impacted regions were linked with pain perception, the right cerebellum's interactions with other regions were associated with overt body movements, interactions between the parahippocampus and thalamus were linked with memory processes, and interactions between medial PFC regions were associated with face processing. CONCLUSIONS: Collectively, these findings emphasize brain regions (e.g., ventromedial PFC, insula, thalamus) critically linked with cigarette smoking, suggest neuroimaging paradigms warranting additional consideration among smokers (e.g., pain processing), and highlight regions in need of further elucidation in addiction (e.g., cerebellum).

Neurobiological impact of nicotinic acetylcholine receptor agonists: an activation likelihood estimation meta-analysis of pharmacologic neuroimaging studies.

BACKGROUND: Nicotinic acetylcholine receptor (nAChR) agonists augment cognition among cigarette smokers and nonsmokers, yet the systems-level neurobiological mechanisms underlying such improvements are not fully understood. Aggregating neuroimaging results regarding nAChR agonists provides a means to identify common functional brain changes that may be related to procognitive drug effects. METHODS: We conducted a meta-analysis of pharmacologic neuroimaging studies within the activation likelihood estimation framework. We identified published studies contrasting a nAChR drug condition versus a baseline and coded each contrast by activity change direction (decrease or increase), participant characteristics (smokers or nonsmokers), and drug manipulation employed (pharmacologic administration or cigarette smoking). RESULTS: When considering all studies, nAChR agonist administration was associated with activity decreases in multiple regions, including the ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), parahippocampus, insula, and the parietal and precentral cortices. Conversely, activity increases were observed in lateral frontoparietal cortices, the anterior cingulate cortex, thalamus, and cuneus. Exploratory analyses indicated that both smokers and nonsmokers showed activity decreases in the vmPFC and PCC, and increases in lateral frontoparietal regions. Among smokers, both pharmacologic administration and cigarette smoking were associated with activity decreases in the vmPFC, PCC, and insula and increases in the lateral PFC, dorsal anterior cingulate cortex, thalamus, and cuneus. CONCLUSIONS: These results provide support for the systems-level perspective that nAChR agonists suppress activity in default-mode network regions and enhance activity in executive control network regions in addition to reducing activation of some task-related regions. We speculate these are potential mechanisms by which nAChR agonists enhance cognition.