• Energy Research
• 2021-2025close
• DE close
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Abstract Aims Alcohol use alters the reward signaling processes contributing to the development of addiction. We studied the effects of alcohol use disorder (AUD) on brain regions and blood of deceased women and men to examine sex-dependent differences in epigenetic changes associated with AUD. We investigated the effects of alcohol use on the gene promoter methylation of GABBR1 coding for GABAB receptor subunit 1 in blood and brain. Methods We chose six brain regions associated with addiction and the reward pathway (nucleus arcuatus, nucleus accumbens, the mamillary bodies, amygdala, hippocampus and anterior temporal cortex) and performed epigenetic profiling of the proximal promoter of the GABBR1 gene of post-mortem brain and blood samples of 17 individuals with AUD pathology (4 female, 13 male) and 31 healthy controls (10 female, 21 male). Results Our results show sex-specific effects of AUD on GABBR1 promoter methylation. Especially, CpG −4 showed significant tissue-independent changes and significantly decreased methylation levels for the AUD group in the amygdala and the mammillary bodies of men. We saw prominent and consistent change in CpG-4 across all investigated tissues. For women, no significant loci were observed. Conclusion We found sex-dependent differences in GABBR1 promoter methylation in relation to AUD. CpG-4 hypomethylation in male individuals with AUD is consistent for most brain regions. Blood shows similar results without reaching significance, potentially serving as a peripheral marker for addiction-associated neuronal adaptations. Further research is needed to discover more contributing factors in the pathological alterations of alcohol addiction to offer sex-specific biomarkers and treatment.

We present a protocol for the biosensor Cell-Fit-HD4D. It enables long-term monitoring and correlation of single-cell fate with subcellular-deposited energy of ionizing radiation. Cell fate tracking using widefield time-lapse microscopy is uncoupled in time from confocal ion track imaging. Registration of both image acquisition steps allows precise ion track assignment to cells and correlation with cellular readouts. For complete details on the use and execution of this protocol, please refer to Niklas et al. (2022).

Stress and alcohol cues trigger alcohol consumption and relapse in alcohol use disorder. However, the neurobiological processes underlying their interaction are not well understood. Thus, we conducted a randomized, controlled neuroimaging study to investigate the effects of psychosocial stress on neural cue reactivity and addictive behaviors.Neural alcohol cue reactivity was assessed in 91 individuals with alcohol use disorder using a validated functional magnetic resonance imaging (fMRI) task. Activation patterns were measured twice, at baseline and during a second fMRI session, prior to which participants were assigned to psychosocial stress (experimental condition) or a matched control condition or physical exercise (control conditions). Together with fMRI data, alcohol craving and cortisol levels were assessed, and alcohol use data were collected during a 12-month follow-up. Analyses tested the effects of psychosocial stress on neural cue reactivity and associations with cortisol levels, craving, and alcohol use.Compared with both control conditions, psychosocial stress elicited higher alcohol cue-induced activation in the left anterior insula (familywise error-corrected p < .05) and a stress- and cue-specific dynamic increase in insula activation over time (F22,968 = 2.143, p = .007), which was predicted by higher cortisol levels during the experimental intervention (r = 0.310, false discovery rate-corrected p = .016). Cue-induced insula activation was positively correlated with alcohol craving during fMRI (r = 0.262, false discovery rate-corrected p = .032) and alcohol use during follow-up (r = 0.218, false discovery rate-corrected p = .046).Results indicate a stress-induced sensitization of cue-induced activation in the left insula as a neurobiological correlate of the effects of psychosocial stress on alcohol craving and alcohol use in alcohol use disorder, which likely reflects changes in salience attribution and goal-directed behavior.

Co-use of alcohol and cannabis is associated with increased frequency and intensity of use and related problems. This study examined acute effects of alcohol and cannabis on mood, subjective experience, cognition, and psychomotor performance. Twenty-eight healthy cannabis users aged 19-29 years with recent history of binge drinking completed this within-subjects, double-blind, double-dummy, placebo-controlled, randomized clinical trial. Participants received: placebo alcohol and placebo cannabis (<0.1% THC); alcohol (target breath alcohol content [BrAC] 80 mg/dL) and placebo cannabis; placebo alcohol and active cannabis (12.5% THC); and active alcohol and cannabis over four sessions. Profile of Mood States (POMS), Addiction Research Centre Inventory (ARCI), verbal free recall (VFR), Digit Symbol Substitution Test (DSST), Continuous Performance Test (CPT), and grooved pegboard (GPB) task were administered before and approximately 75 min after drinking alcohol (1 h after smoking cannabis ad libitum). Significant effects of condition were found for the POMS (Tension-Anxiety, Confusion) and ARCI (MBG, LSD, PCAG, Euphoria, Sedation), predominantly with greater increases emerging after cannabis or alcohol-cannabis combined relative to placebo. Significant effects were found for VFR (immediate total and delayed recall, percent retained), DSST (trials attempted, trials correct, reaction time), and GPB (non-dominant hand) predominantly with greater declines in performance after alcohol and alcohol-cannabis combined relative to placebo and/or cannabis. Cannabis appeared to affect mood and subjective experience, with minimal impact on cognitive performance. Alcohol appeared to impair cognitive and psychomotor performance, with minimal impact on mood and subjective experience. Acute effects of alcohol and cannabis combined were additive at most.

AbstractWith the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks. In this study, we implement the neuromark pipeline in COINSTAC, an open-source neuroimaging framework for collaborative/decentralized analysis. Decentralized analysis of nearly 2000 resting-state functional magnetic resonance imaging datasets collected at different sites across two cohorts and co-located in different countries was performed to study the resting brain functional network connectivity changes in adolescents who smoke and consume alcohol. Results showed hypoconnectivity across the majority of networks including sensory, default mode, and subcortical domains, more for alcohol than smoking, and decreased low frequency power. These findings suggest that global reduced synchronization is associated with both tobacco and alcohol use. This work demonstrates the utility and incentives associated with large-scale decentralized collaborations spanning multiple sites.

<b><i>Introduction:</i></b> The emergence of Pavlovian-to-instrumental transfer (PIT) research in the human neurobehavioral domain has been met with increased interest over the past two decades. A variety of PIT tasks were developed during this time; while successful in demonstrating transfer phenomena, existing tasks have limitations that should be addressed. Herein, we introduce two PIT paradigms designed to assess outcome-specific and general PIT within the context of addiction. <b><i>Materials and Methods:</i></b> The single-lever PIT task, based on an established paradigm, replaced button presses with joystick motion to better assess avoidance behavior. The full transfer task uses alcohol and nonalcohol rewards associated with Pavlovian cues and instrumental responses, along with other gustatory and monetary rewards. We constructed mixed-effects models with the addition of other statistical analyses as needed to interpret various behavioral measures. <b><i>Results:</i></b> Single-lever PIT: both versions were successful in eliciting a PIT effect (joystick: <i>p</i> &#x3c; 0.001, η_p² = 0.36, button-box: <i>p</i> &#x3c; 0.001, η_p² = 0.30). Full transfer task: it was determined that the alcohol and nonalcoholic reward cues selectively primed their respective reward-associated responses (gustatory version: <i>p</i> &#x3c; 0.001, <i>r</i> = 0.59, and monetary version: <i>p</i> &#x3c; 0.001, <i>r</i> = 0.84). The appetitive/aversive cues resulted in a general transfer effect (gustatory: <i>p</i> &#x3c; 0.001, η_p² = 0.09, and monetary: <i>p</i> &#x3c; 0.001, η_p² = 0.17). <b><i>Discussion/Conclusion:</i></b> Single-lever PIT: PIT was observed in both task versions. We posit that the use of a joystick is more advantageous for the analysis of avoidance behavior. It evenly distributes movement between approach and avoid trials, which is relevant to analyzing fMRI data. Full transfer task: While gustatory conditioning has been used in the past to elicit transfer effects, we present the first paradigm that successfully elicits both specific and general transfers in humans with gustatory alcohol rewards.

ABSTRACTThe environment influences mental health, both detrimentally and beneficially. Current research has emphasized the individual psychosocial ‘microenvironment’. Less attention has been paid to ‘macro-environmental’ challenges including climate change, pollution, urbanicity and socioeconomic disparity. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

Cue-reward associations form distinct memories that can drive appetitive behaviors and cravings for both drugs and natural rewards. It is still unclear how such memories are encoded in the brain's reward system. We trained rats to concurrently self-administer either alcohol or a sweet saccharin solution as drug or natural rewards, respectively. Memory recall due to cue exposure reactivated reward-associated functional ensembles in reward-related brain regions, marked by a neural cFos response. While the local ensembles activated by cue presentation for either reward consisted of similar numbers of neurons, using advanced statistical network theory, we found robust reward-specific co-activation patterns across brain regions. Interestingly, the resulting meta-ensemble networks differed by the most influential regions, which in case of saccharin comprised the prefrontal cortex, while for alcohol seeking control shifted to insular cortex with strong involvement of the amygdala. Our results support the view of memory representation as a differential co-activation of local neuronal ensembles. This article is part of the special issue on 'Neurocircuitry Modulating Drug and Alcohol Abuse'.

AbstractAlcohol consumption is a widespread behaviour that may eventually result in the development of alcohol use disorder (AUD). Alcohol, however, is rarely consumed in pure form but in fruit‐ or corn‐derived preparations, like beer. These preparations add other compounds to the consumption, which may critically modify alcohol intake and AUD risk. We investigated the effects of hordenine, a barley‐derived beer compound on alcohol use‐related behaviours. We found that the dopamine D2 receptor agonist hordenine (50 mg/kg) limited ongoing alcohol consumption and prophylactically diminished relapse drinking after withdrawal in mice. Although not having reinforcing effects on its own, hordenine blocked the establishment of alcohol‐induced conditioned place preference (CPP). However, it independently enhanced alcohol CPP retrieval. Hordenine had a dose‐dependent inhibitory effect on locomotor activity. Chronic hordenine exposure enhanced monoamine tissue levels in many brain regions. Further characterization revealed monoaminergic binding sites of hordenine and found a strong binding on the serotonin and dopamine transporters, and dopamine D3, and adrenergic α1A and α2A receptor activation but no effects on GABAA receptor or glycinergic signalling. These findings suggest that natural ingredients of beer, like hordenine, may work as an inhibitory and use‐regulating factor by their modulation of monoaminergic signalling in the brain.

Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, mathematics, sensor physics, robotics, and computer science are needed to address remaining crucial scientific challenges. In this paper, we argue for a bio-inspired approach to solve autonomous flying challenges, outline the frontier of sensing, data processing, and flight control within a neuromorphic paradigm, and chart directions of research needed to achieve operational capabilities comparable to those we observe in nature. One central problem of neuromorphic computing is learning. In biological systems, learning is achieved by adaptive and relativistic information acquisition characterized by near-continuous information retrieval with variable rates and sparsity. This results in both energy and computational resource savings being an inspiration for autonomous systems. We consider pertinent features of insect, bat and bird flight behavior as examples to address various vital aspects of autonomous flight. Insects exhibit sophisticated flight dynamics with comparatively reduced complexity of the brain. They represent excellent objects for the study of navigation and flight control. Bats and birds enable more complex models of attention and point to the importance of active sensing for conducting more complex missions. The implementation of neuromorphic paradigms for autonomous flight will require fundamental changes in both traditional hardware and software. We provide recommendations for sensor hardware and processing algorithm development to enable energy efficient and computationally effective flight control.