BackgroundThe compound 3,4-methylenedioxymethamphetamine (MDMA) is a potent monoamine releaser that produces an acute euphoria in most individuals.MethodsIn a double-blind, placebo-controlled, balanced-order study, MDMA was orally administered to 25 physically and mentally healthy individuals. Arterial spin labeling and seed-based resting state functional connectivity (RSFC) were used to produce spatial maps displaying changes in cerebral blood flow (CBF) and RSFC after MDMA administration. Participants underwent two arterial spin labeling and two blood oxygen level–dependent scans in a 90-minute scan session; MDMA and placebo study days were separated by 1 week.ResultsMarked increases in positive mood were produced by MDMA. Decreased CBF only was observed after MDMA, and this was localized to the right medial temporal lobe (MTL), thalamus, inferior visual cortex, and the somatosensory cortex. Decreased CBF in the right amygdala and hippocampus correlated with ratings of the intensity of global subjective effects of MDMA. The RSFC results complemented the CBF results, with decreases in RSFC between midline cortical regions, the medial prefrontal cortex, and MTL regions, and increases between the amygdala and hippocampus. There were trend-level correlations between these effects and ratings of intense and positive subjective effects.ConclusionsThe MTLs appear to be specifically implicated in the mechanism of action of MDMA, but further work is required to elucidate how the drug’s characteristic subjective effects arise from its modulation of spontaneous brain activity.

Artifact removal in resting state fMRI (rfMRI) data remains a serious challenge, with even subtle head motion undermining reliability and reproducibility. Here we compared some of the most popular single-echo de-noising methods—regression of Motion parameters, White matter and Cerebrospinal fluid signals (MWC method), FMRIB’s ICA-based X-noiseifier (FIX) and ICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA)—with a multi-echo approach (ME-ICA) that exploits the linear dependency of BOLD on the echo time. Data were acquired using a clinical scanner and included 30 young, healthy participants (minimal head motion) and 30 Attention Deficit Hyperactivity Disorder patients (greater head motion). De-noising effectiveness was assessed in terms of data quality after each cleanup procedure, ability to uncouple BOLD signal and motion and preservation of default mode network (DMN) functional connectivity. Most cleaning methods showed a positive impact on data quality. However, based on the investigated metrics, ME-ICA was the most robust. It minimized the impact of motion on FC even for high motion participants and preserved DMN functional connectivity structure. The high-quality results obtained using ME-ICA suggest that using a multi-echo EPI sequence, reliable rfMRI data can be obtained in a clinical setting.

Alterations in reinforcement-based decision making may be associated with increased psychiatric vulnerability in children who have experienced maltreatment. A probabilistic passive avoidance task and a model-based functional magnetic resonance imaging analytic approach were implemented to assess the neurocomputational components underlying decision making: (a) reinforcement expectancies (the representation of the outcomes associated with a stimulus) and (b) prediction error signaling (the ability to detect the differences between expected and actual outcomes). There were three main findings. First, the maltreated group (n ¼ 18; mean age ¼ 13), relative to nonmaltreated peers (n ¼ 19; mean age ¼ 13), showed decreased activity during expected value processing in a widespread network commonly associated with reinforcement expectancies representation, including the striatum (especially the caudate), the orbitofrontal cortex, and medial temporal structures including the hippocampus and insula. Second, consistent with previously reported hyperresponsiveness to negative cues in the context of childhood abuse, the maltreated group showed increased prediction error signaling in the middle cingulate gyrus, somatosensory cortex, superior temporal gyrus, and thalamus. Third, the maltreated group showed increased activity in frontodorsal regions and in the putamen during expected value representation. These findings suggest that early adverse environments disrupt the development of decision-making processes, which in turn may compromise psychosocial functioning in ways that increase latent vulnerability to psychiatric disorder.

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Novelty seeking is characteristic of ADHD, but how this influences reward-related decision-making is unknown. Sethi et al. show that stimulant medication selectively attenuates ADHD participants’ tendency to repeatedly select non-optimal novel options, and reduces substantia nigra novelty signalling. Stimulant medication increases learning rates and enhances performance in ADHD participants compared to effects in controls.