Addiction neuroscience最新文献

With the rapidly accelerating adoption of machine-learning based rodent behavioral tracking tools, there is an unmet need for a method of acquiring high quality video data that is scalable, flexible, and relatively low-cost. Many experimenters use webcams, GoPros, or other commercially available cameras that can be expensive, offer minimal flexibility of recording parameters, and not optimized for recording rodent behavior, leading to suboptimal and inconsistent video quality. Furthermore, commercially available products are not conducive for synchronizing multiple cameras, or interfacing with third-party equipment to allow time-locking of video to other equipment such as microcontrollers for closed-loop experiments. We present a low-cost, customizable ecosystem of behavioral recording equipment, PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture) based on Raspberry Pi Camera Boards with the ability to acquire high quality recordings in bright/low light, or dark conditions under infrared light. PiRATeMC offers users control over nearly every recording parameter, and can be fine-tuned to produce optimal videos in any behavioral apparatus. This setup can be scaled up for synchronous control of any number of cameras via a self-contained network without burdening institutional network infrastructure. The Raspberry Pi is an excellent platform with a large online community designed for novice and inexperienced programmers interested in using an open-source recording system. Importantly, PiRATeMC supports TTL and serial communication, allowing for synchronization and interfacing of video recording with behavioral or other third-party equipment. In sum, PiRATeMC minimizes the cost-prohibitive nature of conducting and analyzing high quality behavioral neuroscience studies, thereby increasing accessibility to behavioral neuroscience.

Stimulant-use disorders can present with long-term cognitive and mental health deficits. Little is known about the underlying molecular mechanisms perpetuating sex differences in cognitive and behavioral deficits in preclinical models of addiction to stimulants such as methamphetamine (MA). The current study investigated the neurochemical shifts underlying sex disparities in MA-induced working memory deficits and an addictive phenotype following abstinence from chronic MA abuse. We used our previously reported mouse model of voluntary oral methamphetamine administration (VOMA) consisting of an acquisition phase (days 1–14) characterized by escalating doses of MA and a binge phase (days 14–28) characterized by static doses. Female VOMA mice exhibited sustained MA consumption during the binge phase, demonstrating sex-specific vulnerabilities to the maintenance of MA addiction. The 8-arm radial maze was used to test spatial working memory performance following abstinence from VOMA. Results indicate working memory deficits correlated to higher MA consumption in females only. Hippocampal and accumbal tissue were collected and analyzed by immunoblotting. Female VOMA mice had decreased GluA1, but not GluA2, in the hippocampus, which may perpetuate synaptic destabilization and working memory deficits. Female-specific increases in GluA1 and p-GSK3β expression in accumbal tissue suggest vulnerability toward abstinence-induced drug craving and heightened downstream neurotoxicity. Our study reveals female-specific neurochemical shifts in hippocampal and accumbal AMPA receptor signaling following abstinence from chronic MA consumption that may perpetuate female susceptibility to MA-induced cognitive deficits. These data demonstrate a novel molecular pathway that would exacerbate memory deficits and perpetuate an addictive phenotype in female populations following MA abuse.

The striatum, both dorsal and ventral, is strongly implicated in substance use disorder. Chronic consumption of abused substances, such as cocaine, can cause an oversaturation of mesostriatal dopamine, which results in alterations in the firing of striatal neurons. While most preclinical studies of drug self-administration (S-A) are focused on these alterations, individual differences in a subject's early responses to drugs can also account for substantial differences in addiction susceptibility. In this study, we modeled longitudinal pharmacokinetics using data from a previous longitudinal study (Coffey et al., 2015) and aimed to determine if firing in specific dorsal and ventral striatal subregions was subject to changes across chronic cocaine S-A, and if individual animal differences in striatal firing in response to early drug exposure correlated with increases in drug intake. We observed that the firing patterns of nucleus accumbens (NAc) core and shell neurons exhibited increasing sensitivity to cocaine over the first 6 S-A sessions and maintained a strong negative correlation between drug intake and neuronal firing rates across chronic S-A. Moreover, we observed that the early sensitivity of NAc shell neurons to cocaine correlated with future increases in drug intake. Specifically, rats whose NAc shell neurons were most inhibited by increasing levels of cocaine upon first exposure exhibited the strongest increases in cocaine intake over time. If this difference can be linked to a genetic difference, or druggable targets, it may be possible to screen for similar addiction susceptibility in humans or develop novel preemptive pharmacotherapies.

The use of Electronic Nicotine Delivery Systems (ENDS) is increasing in prevalence and popularity. ENDS are a rapidly evolving technology as devices and e-liquid formulations adapt to policy restrictions and market demand. To identify the impacts of nicotine formulation and concentration, we exposed female and male C57BL/6J mice to passive electronic vaporization of different nicotine formulations (freebase or salt) and concentrations (1% or 3%) and measured serum nicotine metabolite levels, brain activity by cFos expression, and anxiety-like and motivated behavior using the novelty suppressed feeding test. We found that the 3% freebase nicotine vapor group displayed significantly higher serum nicotine levels than either 1% or 3% nicotine salt formulations, and female mice displayed higher serum nicotine and cotinine levels compared to males. Central amygdala (CeA) activity was significantly elevated in male mice following nicotine vapor exposure, but the increase was not significantly different between nicotine vapor groups. CeA activity in female mice was unaffected. In contrast, increased activity in the ventral tegmental area (VTA) was only observed in female mice exposed to 3% nicotine freebase and specifically in the dopaminergic population. Anxiety-like behavior in female mice was relatively unaffected by nicotine vapor exposure, however male mice displayed increased anxiety-like behavior and reduced motivation to feed after vapor exposure, specifically in the 3% freebase group. These results identify important sex differences in the impact of nicotine formulation and concentration on nicotine metabolism, brain region-specific activity and anxiety-like behavior, which may have significant relevance for different consequences of vaping in men and women.

Adherence is a critical mediator of treatment outcome across health conditions and low rates of adherence undermine success in smoking cessation treatment. This narrative review provides an overview of different techniques that can be used to measure adherence to smoking cessation treatments and outlines strategies to address treatment adherence. Techniques to measure adherence include conducting pill counts, collecting self-reports of adherence, directly observed therapy, biochemical verification methods, and electronic data collection via medication events monitoring systems. Techniques examined for increasing tobacco cessation treatment adherence include counseling, automated adherence calls, feedback from electronic monitors, contingency management and directly observed therapy. Adherence monitoring and optimization should be a standard component of smoking cessation treatment research.

Cannabis use during pregnancy is becoming increasingly common despite a lack of knowledge regarding its long-term effects on developing offspring. Determining effects of prenatal cannabis exposure on cannabis use later in life has been especially difficult given the problems inherent to traditional models of cannabinoid self-administration. Thus, we adopted a model of response-contingent cannabis vapor delivery in pregnant rat dams to investigate impacts of maternal cannabis use on reinforcing properties of ∆⁹-tetrahydrocannabinol (THC)-rich cannabis vapor in offspring. Rat dams were trained to self-administer a vaporized cannabis extract or vehicle vapor in 1-hr sessions twice daily until 24-48 hr prior to parturition, while a third group received no vapor exposure. Cannabis vapor self-administration was assessed in adult offspring using a 22-day escalating reinforcement schedule that culminated in a 3 hr progressive ratio challenge. Dams reliably self-administered cannabis vapor during the gestational period and showed better discrimination for the vapor-paired nosepoke than vehicle self-administering dams. In accordance with human data, cannabis-exposed offspring displayed lower birthweights than vehicle-exposed offspring. Effects of prenatal cannabis exposure on vapor self-administration in adult offspring differed by sex. Male cannabis-exposed offspring made fewer active responses and earned fewer vapor deliveries than vehicle-exposed offspring, regardless of their assigned vapor condition. Conversely, female offspring showed higher rates of responding for cannabis relative to vehicle, but rates of self-administration were unaffected by prenatal cannabis exposure. Altogether, these data demonstrate feasibility of response-contingent cannabis vapor delivery in pregnant rat dams and indicate paradoxical suppressive effects on vapor self-administration in male offspring.

This perspective summarizes available evidence on biomarkers of exposure in electronic nicotine delivery system (ENDS) users to aid the overall assessment of the health consequences of using ENDS. Identification of novel biomarkers of exposure specific to ENDS use remains challenging because chemicals emitted from ENDS devices have many familiar sources. The biomarker levels of many tobacco-related toxicants measured in biological samples collected from ENDS users did not differ significantly from non-users, except for nicotine metabolites and a small number of biomarkers of exposure to volatile organic compounds and tobacco-specific tobacco nitrosamines. Several studies have shown that while exposed to nicotine, long-term exclusive ENDS users showed significantly lower levels of toxicant biomarkers than cigarette smokers. Studies have also shown that concurrent users of ENDS and combustible cigarettes (‘dual users’) are not reducing overall exposure to harmful toxicants compared to exclusive cigarette smokers. Because of an absence of validated ENDS-specific biomarkers, we recommend combining several biomarkers to differentiate tobacco product user groups in population-based studies and monitor ENDS compliance in randomized controlled trials. Using a panel of biomarkers would provide a better understanding of health effects related to ENDS use.

Neurobiological models of addiction attribute vulnerability to compulsive drug use to dysregulated activity within the neural networks that underlie reward and executive functions. Empirical evidence suggests that (a) attributing high motivational salience to drug-related stimuli leads to compulsive drug seeking and (b) cognitive control deficits lead to compulsive drug taking. Noninvasive neuroimaging techniques enable brain activity monitoring during affective and cognitive processing and could pave the way to precision medicine for substance use disorders. Identifying robust neuromarkers of affective and cognitive dysregulation would allow clinicians to personalize treatments by targeting individual psychophysiological vulnerabilities. However, methodological choices have biased the field toward experimental paradigms that cannot optimally assess individual differences in the motivational salience of drug-related cues and in the ability to control drug-related decisions, hindering the identification of clinically relevant neuromarkers. Here we show that (a) accounting for neuroaffective reactivity to non-drug-related motivationally relevant stimuli when measuring the attribution of motivational salience to drug-related cues, and (b) assessing brain activity while participants make drug-related decisions with immediate consequences, yield replicable neuromarkers with potential clinical relevance. While we use tobacco use disorder as a model, we also show that the methodological issues highlighted here are relevant to other disorders characterized by maladaptive appetitive behaviors.

In humans, exposure to early life stress (ELS) is an established risk factor for the development of substance use disorders (SUDs) during later life. Similarly, rodents exposed to ELS involving disrupted mother-infant interactions, such as maternal separation (MS) or adverse caregiving due to scarcity-adversity induced by limited bedding and nesting (LBN) conditions, also exhibit long-term alterations in alcohol and drug consumption. In both humans and rodents, there is a range of addiction-related behaviors that are associated with drug use and even predictive of subsequent SUDs. In rodents, these include increased anxiety-like behavior, impulsivity, and novelty-seeking, altered alcohol and drug intake patterns, as well as disrupted reward-related processes involving consummatory and social behaviors. Importantly, the expression of these behaviors often varies throughout the lifespan. Moreover, preclinical studies suggest that sex differences play a role in how exposure to ELS impacts reward and addiction-related phenotypes as well as underlying brain reward circuitry. Here, addiction-relevant behavioral outcomes and mesolimbic dopamine (DA) dysfunction resulting from ELS in the form of MS and LBN are discussed with a focus on age- and sex-dependent effects. Overall, these findings suggest that ELS may increase susceptibility for later life drug use and SUDs by interfering with the normal maturation of reward-related brain and behavioral function.

Influential recent work aims to ground psychiatric dysfunction in the brain's basic computational mechanisms. For instance, the compulsive symptoms that feature prominently in drug abuse and addiction have been argued to arise from over reliance on a habitual “model-free” system in contrast to a more laborious “model-based” system. Support for this account comes in part from failures to appropriately change behavior in light of new events. Notably, instrumental responding can, in some circumstances, persist despite reinforcer devaluation, perhaps reflecting control by model-free mechanisms that are driven by past reinforcement rather than knowledge of the (now devalued) outcome. However, another line of theory posits a different mechanism – latent causal inference – that can modulate behavioral change. It concerns how animals identify different contingencies that apply in different circumstances, by covertly clustering experiences into distinct groups. Here we combine both lines of theory to investigate the consequences of latent cause inference on instrumental sensitivity to reinforcer devaluation. We show that instrumental insensitivity to reinforcer devaluation can arise in this theory even using only model-based planning, and does not require or imply any habitual, model-free component. These ersatz habits (like laboratory ones) emerge after overtraining, interact with contextual cues, and show preserved sensitivity to reinforcer devaluation on a separate consumption test, a standard control. Together, this work highlights the need for caution in using reinforcer devaluation procedures to rule in (or out) the contribution of different learning mechanisms and offers a new perspective on the neurocomputational substrates of drug abuse.