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.

Neurofunctional Segmentation Shifts in the Hippocampus.

The hippocampus is one of the most phylogenetically preserved structures in the mammalian brain. Engaged in a host of diverse cognitive processes, there has been increasing interest in understanding how the hippocampus dynamically supports these functions. One of the lingering questions is how to reconcile the seemingly disparate cytoarchitectonic organization, which favors a dorsal-ventral layering, with the neurofunctional topography, which has strong support for longitudinal axis (anterior-posterior) and medial-lateral orientation. More recently, meta-analytically driven (e.g., big data) approaches have been employed, however, the question remains whether they are sensitive to important task-specific features such as context, cognitive processes recruited, or the type of stimulus being presented. Here, we used hierarchical clustering on functional magnetic resonance imaging (fMRI) data acquired from healthy individuals at 7T using a battery of tasks that engage the hippocampus to determine whether stimulus or task features influence cluster profiles in the left and right hippocampus. Our data suggest that resting state clustering appears to favor the cytoarchitectonic organization, while task-based clustering favors the neurofunctional clustering. Furthermore, encoding tasks were more sensitive to stimulus type than were recognition tasks. Interestingly, a face-name paired associate task had nearly identical clustering profiles for both the encoding and recognition conditions of the task, which were qualitatively morphometrically different than simple encoding of words or faces. Finally, corroborating previous research, the left hippocampus had more stable cluster profiles compared to the right hippocampus. Together, our data suggest that task-based and resting state cluster profiles are different and may account for the disparity or inconsistency in results across studies.

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.