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Additional file 1: Supplementary Table 1. Nutrient Profiles per Serving of Whole Food Plant-Based Proteins, Plant-Based Meat Alternatives, and Animal Meat. Supplementary Table 2. Weekly Adherence to Consistent Physical Activity Across Diet Phases. Supplementary Table 3. Rate of Perceived Exertion (RPE) on Athletic Field Test. Supplementary Table 4. Anthropometric Measures after 4-wk diet phases. Supplementary Fig. 1. Primary Athletic Field Test Outcome (Runners): 12-Minute Timed Run. Supplementary Fig. 2. Primary Athletic Field Test Outcome (Resistance Trainers): Machine Composite Strength. Supplementary Fig. 3. Secondary Athletic Field Test Outcome (Runners): VO2 max. Supplementary Fig. 4a. Secondary Athletic Field Test Outcome (Resistance Trainers): Push-Up. Supplementary Fig. 4b. Secondary Athletic Field Test Outcome (Resistance Trainers): Pull-Up. Supplementary Fig. 4c. Secondary Athletic Field Test Outcome (Resistance Trainers): Chest Press. Supplementary Fig. 4d. Secondary Athletic Field Test Outcome (Resistance Trainers): Leg Press. Supplementary Fig. 4e. Secondary Athletic Field Test Outcome (Resistance Trainers): Lat Pull-Down. Supplementary Fig. 5a. Athletic Performance over the 12-week intervention: 12-minute timed run. Supplementary Fig. 5b. Athletic Performance over the 12-week intervention: machine composite strength. Supplementary Fig. 6. Diet Satisfaction.

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.

The habenula, a small, bilateral region posterior to the medial thalamus and dorsal to the posterior commissure, has been of interest in research on reward processing and goal-directed behavior. It receives input from the prefrontal cortex and several subcortical regions and projects to the serotonergic dorsal raphe nucleus, as well as the dopaminergic substantia nigra (SN)1. Despite the habenula’s critical involvement in reward processing and dopamine modulation, few neuroimaging studies have focused on this region. To address this discrepancy, we used complementary approaches to assess the whole brain functional connectivity of the habenula both at rest and during task to uncover how this region may be differentially engaged across cognitive states. To assess resting-state functional connectivity (rsFC) of the habenula, data were collected from 28 healthy participants on a 7-Tesla Siemens MAGNETOM scanner at Auburn University. Structural T1 scans were acquired at a resolution of 0.63mmx0.63mmx0.60mm and 5 minutes of resting state data were acquired with an EPI sequence at a resolution of 0.85mmx0.85mmx1.5mm. Structural images were first aligned in in SPM8 and the habenula was manually defined in each subject’s native space, by a procedure described by Lawson et al.2. We then used FSL’s FEAT to regress each subject’s mean habenula time series on the voxel-wise time series across the brain. A nonparametric one-sample t-test was performed at the group-level with FSL’s randomise3. Meta-analytic coactivation modeling (MACM)4 was performed using an ROI drawn by a similar method on an MNI152 template brain, dilated to account for anatomical and data processing differences across studies. We used the BrainMap database to identify studies reporting activation in this ROI across a wide range of functional neuroimaging paradigms. ALE5,6 was used to assess coactivation across studies, thresholded at a cluster-level corrected threshold of pp7. We then performed a conjunction analysis on the results of the two analyses to determine areas in common, as well as a contrast analysis to identify regions of significant difference between rsFC and MACM. The rsFC analysis identified functional synchrony of the habenula with ventral anterior and posterior cingulate cortices (vACC, PCC), right anterior insula (AI), SN, periaqueductal gray (PAG), precuneus, and striatum (Figure 1A). MACM results identified coactivation in portions of the striatum, dorsal ACC (dACC), medial frontal gyrus, and in both left inferior frontal sulcus and posterior parietal lobule (Figure 1B). Both rsFC and MACM revealed connectivity with the nearby thalamus, ACC, SN, and PAG (Figure 1C). We demonstrate in both rsFC and MACM analyses habenula’s functional interactions with the SN, consistent with a well-documented role in modulating dopaminergic signaling associated with reward prediction error (RPE), indicating this relationship is central to habenula function, regardless of cognitive state. While we observed habenula connectivity with the ACC both at rest and during various tasks, the region of conjunction in ACC was small. The habenula’s rsFC was largely restricted to vACC, and task-based MACM, to dACC. This is an important distinction, as rsFC and MACM demonstrate differential connectivity of the habenula with respect to cognitive state. The habenula appeared to be connected with PCC, precuneus, and vACC at rest, which are medial nodes of the default mode network8. During tasks, the habenula was connected with both AI and dACC, which are key nodes of the salience network, connections that are supported by an underlying structural architecture1,9. Differential connectivity at rest and during task suggests context-specific functional roles of the habenula, potentially contributing to default mode processes at rest and likely providing RPE signaling to salience network regions during tasks. 1. Baker, P. M. et al. The Lateral Habenula Circuitry: Reward Processing and Cognitive Control. J. Neurosci. 36, (2016). 2. Lawson, R. P., Drevets, W. C. & Roiser, J. P. Defining the habenula in human neuroimaging studies. Neuroimage 64, 722–7 (2013). 3. Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M. & Nichols, T. E. Permutation inference for the general linear model. Neuroimage 92, 381–397 (2014). 4. Robinson, J. L., Laird, A. R., Glahn, D. C., Lovallo, W. R. & Fox, P. T. Meta-analytic connectivity modeling: Delineating the functional connectivity of the human amygdala. Hum. Brain Mapp. 31, 173–184 (2010). 5. Turkeltaub, P. E., Eden, G. F., Jones, K. M. & Zeffiro, T. A. Meta-Analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation. Neuroimage 16, 765–780 (2002). 6. Eickhoff, S. B. et al. Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Hum. Brain Mapp. 30, 2907–2926 (2009). 7. Eickhoff, S. B., Bzdok, D., Laird, A. R., Kurth, F. & Fox, P. T. Activation likelihood estimation meta-analysis revisited. Neuroimage 59, 2349–2361 (2012). 8. Greicius, M. D., Krasnow, B., Reiss, A. L. & Menon, V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. U. S. A. 100, 253–8 (2003). 9. Vadovičová, K. Affective and cognitive prefrontal cortex projections to the lateral habenula in humans. Front. Hum. Neurosci. 8, 819 (2014).

The habenula is a small region immediately posterior to the medial thalamus and dorsal to the posterior commissure. This region, implicated in reward processing, receives input from several subcortical regions via the stria medullaris and projects to midbrain regions, modulating serotonin and dopamine release. In order to more broadly investigate the interactions between the habenula and the rest of the brain, we used a seed-to-voxel analysis to probe the intrinsic connectivity of the habenula. Data were collected from 22 healthy, individuals on a 7-Tesla Siemens MAGNETOM scanner housed at Auburn University’s MRI Research Center. We acquired structural and resting-state functional images with sub-millimeter resolution. The habenula was manually defined in each subject’s native space and these ROIs were then used as seed regions from which we extracted the mean BOLD signal time-course and used FSL’s FEAT to assess correlations between time-courses voxels in the rest of the brain with that time-course. Higher-level analysis was performed using FSL’s linear analysis of mixed effects. Our seed-based analysis uncovered temporal correlations (Pcorrected < 0.0001) of the habenula’s BOLD signal with regions known to be structurally connected, including the caudate and putamen (CPu), internal globus pallidus (GPi), the nucleus accumbens (NAcc), and substantia nigra (SN). Connectivity was demonstrated between the habenula and multiple midline regions, as well, including portions of the anterior, mid- and posterior cingulate cortex (ACC, MCC, and PCC), ventromedial prefrontal cortex (vmPFC), thalamus, and cerebellar vermis. The cingulate clusters appear to extend into the paracingulate sulcus, supplementary motor area (SMA), and pre-SMA, as well. The correlation between habenula and ACC activity at rest suggests an integration of conflict monitoring into habenula’s negative feedback and reward prediction errors processing. Furthermore, habenular connectivity with nodes of the cortico-basal motor loop (CPu, GPi, SN, SMA, pre-SMA) supports the notion that the habenula is involved translation of negative feedback to goal-directed action (or the inhibition thereof). This, combined with implied connections to default mode network (DMN) hubs, PCC and vmPFC, indicates that the habenula might be playing a vital role in integrating the associations between actions and negative consequences into the mental rehearsal component of mind-wandering.

Introduction: The human hypothalamus is an intersection between several neural systems and is implicated in numerous processes and disorders related to homeostasis. Despite its vital role in autonomic regulation, very few studies have assessed its neural connectivity and associated functional relationship with the rest of the brain. In this study, we examined the functional connectivity of the human hypothalamus using a robust meta-analytic technique. Methods: Functional connectivity of the human hypothalamus was assessed using meta-analytic connectivity modeling (MACM) methods, which capitalize on the rigorous coding structure of the BrainMap database. ROI Selection. Because there is no readily available hypothalamic ROI, we applied a replicable method of ROI generation using Mango’s Talairach Loader plugin. In addition to a bilateral hypothalamic ROI, left and right ROIs were also created in order to identify hemisphere-specific functional connectivity. BrainMap Meta-Analysis. To search for studies that included activation of the hypothalamus, we used Sleuth to query the BrainMap database, with the above ROIs. We imposed additional search criteria to limit our dataset to only those studies reporting activation in healthy populations. The results for the bilateral ROI included data from 34 papers, 494 subjects, and 42 experiments. The right hypothalamus results included data from 20 papers, 287 subjects, and 25 experiments. The left hypothalamus results included data from 17 papers, 257 subjects, and 20 experiments. Activation Likelihood Estimation (ALE). ALE was performed on the coordinates included in the data generated by the BrainMap search. Analysis of these coordinates provided information about the convergence of regions of coactivation at the 99% confidence level. Behavioral Analysis. We used Mango, equipped with the Behavioral Analysis plug-in, which uses a brain ROI defined by the user in Talairach space as a target to perform regional behavioral analysis. The behavioral domains are representative of the spatial probability mapping of activation foci from the BrainMap database, indicative of the true probability distribution of each domain and sub-domain’s activation locations. Results: ALE. Coactivation with bilateral hypothalamus was identified in 17 regions of the brain, including the left insula, bilateral inferior frontal gyri, bilateral superior temporal gyri, bilateral parahippocampal gyri, and the right anterior cingulate.. Coactivation with the right hypothalamus was identified in bilateral thalami, bilateral superior temporal gyri, left parahippocampus, and the right amygdala. For the left hypothalamus, we identified coactivation in the left inferior and superior frontal gyri, the right middle frontal gyrus, the right parahippocampus, and the right anterior cingulate. Behavioral Analysis. Four behavioral domains were represented within the hypothalamus ROI, the most notable of which was Interoception. Among these behaviors identified were five sub-domains of interoception (sexuality, air-hunger, sleep, bladder, and hunger), which is consistent with the current literature concerning hypothalamic functions. Conclusions: Our data reveal distinct patterns of functional connectivity between the hypothalamus and regions of cognitive and emotional processes. Because of the intimate involvement of the hypothalamus with autonomic and neuroendocrine responses, these connectivity patterns may reveal potential regions of intervention for disorders that have known aberrant hypothalamic function such as post traumatic stress disorder, which is characterized by intense emotional responses that lead to distinct physiological responses. Future research should examine resting state and diffusion tensor imaging patterns to extend our understanding of the connectivity of this structure in relation to the rest of the brain.