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Tobacco smoking is associated with deleterious health outcomes. Most smokers want to quit smoking, yet relapse rates are high. Understanding neural differences associated with tobacco use may help generate novel treatment options. Several animal studies have recently highlighted the central role of the thalamus in substance use disorders, but this research focus has been understudied in human smokers. Here, we investigated associations between structural and functional magnetic resonance imaging measures of the thalamus and its subnuclei to distinct smoking characteristics. We acquired anatomical scans of 32 smokers as well as functional resting‐state scans before and after a cue‐reactivity task. Thalamic functional connectivity was associated with craving and dependence severity, whereas the volume of the thalamus was associated with dependence severity only. Craving, which fluctuates rapidly, was best characterized by differences in brain function, whereas the rather persistent syndrome of dependence severity was associated with both brain structural differences and function. Our study supports the notion that functional versus structural measures tend to be associated with behavioural measures that evolve at faster versus slower temporal scales, respectively. It confirms the importance of the thalamus to understand mechanisms of addiction and highlights it as a potential target for brain‐based interventions to support smoking cessation, such as brain stimulation and neurofeedback. [ABSTRACT FROM AUTHOR]

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behaviour is needed. Studies on cue‐driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving‐related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex and ventral striatum. However, most functional Magnetic Resonance Imaging (fMRI) cue‐reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving‐related brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving‐ and valence‐related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue‐reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence and, therefore, can lead to a more precise mapping of craving‐associated brain areas, an important step towards more tailored smoking cessation treatments. [ABSTRACT FROM AUTHOR]

Tobacco use is one of the leading causes of premature death and morbidity worldwide. For smokers trying to quit, relapse rates are high, even after prolonged periods of abstinence. Recent findings in animal models highlight the role of alterations in glutamatergic projections from the prefrontal cortex onto the nucleus accumbens (NAc) in relapse vulnerability. Moreover, inflammatory responses in the NAc have been reported during withdrawal. A novel proton magnetic resonance spectroscopy (1H‐MRS) protocol was applied in humans to measure molar concentrations for glutamate, its sum with glutamine (Glx), and myoinositol plus glycine (mI + Gly) in the NAc (19 smokers, 20 matched controls). Smokers were measured at baseline and during withdrawal and satiation. No difference between groups or smoking states was found for glutamate or Glx, but, in smokers, stronger craving and more severe nicotine dependence were associated with lower baseline glutamate and Glx levels, respectively. Interestingly, mI + Gly concentrations were higher during withdrawal than baseline and correlated negatively with nicotine dependence severity and pack years of smoking. The lack of glutamatergic changes between groups and smoking states may imply that glutamate homeostasis is not significantly altered in smokers or that changes are too small for detection by 1H‐MRS. Moreover, the observed increase in mI + Gly may imply that neuroinflammatory processes occur in the NAc during nicotine withdrawal. These findings shed light on neurobiological relapse mechanisms in smokers and may provide the opportunity to develop more effective treatment options targeting the glutamate and neuroinflammation system. [ABSTRACT FROM AUTHOR]

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning. [ABSTRACT FROM AUTHOR]

Background and aims: Opioid agonist treatment (OAT) is currently the most effective treatment for people with opioid dependence. In most countries, however, access to the whole range of effective medications is restricted. This study aims to model the distribution of different OAT medications within a naturalistic and relatively unrestricted treatment setting (Zurich, Switzerland) over time, and to identify patient characteristics associated with each medication. Methods: We used generalized estimating equation analysis with data from the OAT register of Zurich and the Swiss register for heroin‐assisted treatment (HAT) to model and forecast the annual proportion of opioids applying exponential distributions until 2018 and patient characteristics between 1992 and 2015. Results: Data from 11 895 patients were included in the analysis. Methadone remains the mainstay of OAT, being prescribed to two‐thirds of patients. Following its approval, the proportion of HAT increased rapidly and is now constant at 12.16% [95% confidence interval (CI) = 11.15–13.17]. The initial increase of proportions of buprenorphine or slow‐release oral morphine (SROM) following their approval for OAT was slower. While in 2014 both medications had a proportion of 10.2% and 10.3%, respectively, our model predicts a further increase of SROM to 19.9% in 2018, with a ceiling level of 25.19% (21.40–28.98%) thereafter. SROM patients display characteristics similar to those treated with methadone; buprenorphine patients show the highest social integration; and HAT patients are the most homogeneous group, with highest mean age, most widespread injecting experience and lowest social integration. Conclusions: Based on data from Zurich, Switzerland from 1992 to 2015, there is no evidence for an excessive demand for a single medication in a naturalistic and liberal opioid agonist treatment setting. Rather, the specific patient characteristics associated with each medication underline the need for diversified treatment options for opioid dependence. [ABSTRACT FROM AUTHOR]

Cocaine addiction is a chronically relapsing disorder that is associated with harmful consequences. Relapses occur frequently and effective pharmacotherapies are currently sparse. Preclinical studies suggest that altered glutamatergic signaling is crucial for the maintenance of cocaine self-administration. However, the translational validity of these models is currently unknown. Therefore, we investigated potential differences of glutamate, glutamine and further metabolite levels in the pregenual anterior cingulate cortex (pgACC) and the right dorsolateral prefrontal cortex (rDLPFC) of chronic cocaine users and controls using the PRior knOwledge FITting 2.0 tool in combination with two-dimensional J-resolved single-voxel (1) H-magnetic resonance spectroscopy at 3T and voxel tissue composition and relaxation correction. Glutamate and glutamine levels did not differ between cocaine users and controls, but higher weekly cocaine use and higher cocaine hair concentrations were associated with lower glutamine/creatine ratios in the pgACC. Interestingly, cocaine users exhibited higher glucose/total creatine ratios than controls in the pgACC and higher choline/creatine ratios in the pgACC and rDLPFC. These results imply that cocaine use is associated with altered cortical glucose metabolism and membrane turnover. Finally, cocaine use over the past 6 months appears to decrease cortical glutamine levels indicating changes in glutamate cycling. [ABSTRACT FROM AUTHOR]

Pre-attentive registration of aberrations in predictable sound patterns is attributed to the temporal cortex. However, electrophysiology suggests that frontal areas become more important when deviance complexity increases. To play an instrument in an ensemble, professional musicians have to rely on the ability to detect even slight deviances from expected musical patterns and therefore have highly trained aural skills. Here, we aimed to identify the neural correlates of experience-driven plasticity related to the processing of complex sound features. We used functional magnetic resonance imaging in combination with an event-related oddball paradigm and compared brain activity in professional musicians and non-musicians during pre-attentive processing of melodic contour variations. The melodic pattern consisted of a sequence of five tones each lasting 50 ms interrupted by silent interstimulus intervals of 50 ms. Compared to non-musicians, the professional musicians showed enhanced activity in the left middle and superior temporal gyri, the left inferior frontal gyrus and in the right ventromedial prefrontal cortex in response to pattern deviation. This differential brain activity pattern was correlated with behaviorally tested musical aptitude. Our results thus support an experience-related role of the left temporal cortex in fast melodic contour processing and suggest involvement of the prefrontal cortex. Hum Brain Mapp, 2009. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Edges are crucial for the formation of coherent objects from sequential sensory inputs within a single modality. Moreover, temporally coincident boundaries of perceptual objects across different sensory modalities facilitate crossmodal integration. Here, we used functional magnetic resonance imaging in order to examine the neural basis of temporal edge detection across modalities. Onsets of sensory inputs are not only related to the detection of an edge but also to the processing of novel sensory inputs. Thus, we used transitions from input to rest (offsets) as convenient stimuli for studying the neural underpinnings of visual and acoustic edge detection per se. We found, besides modality-specific patterns, shared visual and auditory offset-related activity in the superior temporal sulcus and insula of the right hemisphere. Our data suggest that right hemispheric regions known to be involved in multisensory processing are crucial for detection of edges in the temporal domain across both visual and auditory modalities. This operation is likely to facilitate cross-modal object feature binding based on temporal coincidence. Hum Brain Mapp, 2009. © 2008 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Tobacco use is one of the leading causes of premature death and morbidity worldwide. For smokers trying to quit, relapse rates are high, even after prolonged periods of abstinence. Recent findings in animal models highlight the role of alterations in glutamatergic projections from the prefrontal cortex onto the nucleus accumbens (NAc) in relapse vulnerability. Moreover, inflammatory responses in the NAc have been reported during withdrawal. A novel proton magnetic resonance spectroscopy ( 1 H-MRS) protocol was applied in humans to measure molar concentrations for glutamate, its sum with glutamine (Glx), and myoinositol plus glycine (mI + Gly) in the NAc (19 smokers, 20 matched controls). Smokers were measured at baseline and during withdrawal and satiation. No difference between groups or smoking states was found for glutamate or Glx, but, in smokers, stronger craving and more severe nicotine dependence were associated with lower baseline glutamate and Glx levels, respectively. Interestingly, mI + Gly concentrations were higher during withdrawal than baseline and correlated negatively with nicotine dependence severity and pack years of smoking. The lack of glutamatergic changes between groups and smoking states may imply that glutamate homeostasis is not significantly altered in smokers or that changes are too small for detection by 1 H-MRS. Moreover, the observed increase in mI + Gly may imply that neuroinflammatory processes occur in the NAc during nicotine withdrawal. These findings shed light on neurobiological relapse mechanisms in smokers and may provide the opportunity to develop more effective treatment options targeting the glutamate and neuroinflammation system., (© 2021 Society for the Study of Addiction.)