Dissociation of prefrontal cortex and nucleus accumbens dopaminergic systems in conditional learning in rats

Both nicotine reward and withdrawal are enhanced in a rodent model of diabetes

RATIONALE

It is presently unclear whether diabetic rats experience greater rewarding effects of nicotine and/or negative affective states produced by nicotine withdrawal.

OBJECTIVE

The present study utilized a rodent model of diabetes to examine the rewarding effects of nicotine and negative affective states and physical signs produced by withdrawal.

METHODS

Separate groups of rats received systemic administration of either vehicle or streptozotocin (STZ), which destroys insulin-producing beta cells in the pancreas and elevates glucose levels. Place conditioning procedures were utilized to compare the rewarding effects of nicotine (conditioned place preference; CPP) and negative affective states produced by withdrawal (conditioned place aversion; CPA) in vehicle- and STZ-treated rats. CPA and physical signs of withdrawal were compared after administration of the nicotinic receptor antagonist mecamylamine to precipitate withdrawal in nicotine-dependent rats. A subsequent study utilized elevated plus maze (EPM) procedures to compare anxiety-like behavior produced by nicotine withdrawal in vehicle- and STZ-treated rats.

RESULTS

STZ-treated rats displayed greater rewarding effects of nicotine and a larger magnitude of aversive effects and physical signs produced by withdrawal as compared to vehicle-treated controls. STZ-treated rats also displayed higher levels of anxiety-like behavior on the EPM during nicotine withdrawal as compared to controls.

CONCLUSION

The finding that both nicotine reward and withdrawal are enhanced in a rodent model of diabetes implies that the strong behavioral effects of nicotine promote tobacco use in persons with metabolic disorders, such as diabetes.

Enhanced vulnerability to tobacco use in persons with diabetes: A behavioral and neurobiological framework

Tobacco use significantly magnifies the negative health complications associated with diabetes. Although tobacco use is strongly discouraged in persons with diabetes, clinical evidence suggests that they often continue to smoke and have more difficulty quitting despite serious contraindications. Here, we suggest that a potential reason for enhanced vulnerability to tobacco use in persons with diabetes is greater rewarding effects of nicotine. This review summarizes pre-clinical evidence indicating that the rewarding effects of nicotine are enhanced in rodent models of type 1 and type 2 diabetes. We also provide a framework of neurobiological mechanisms that are posited to promote tobacco use in persons with diabetes. This framework suggests that diabetes induces a disruption in insulin signaling that leads to a suppression of dopamine systems in the mesolimbic reward pathway. Lastly, we consider the clinical implications of enhanced rewarding effects of nicotine that may promote tobacco use in persons with diabetes. The clinical efficacy of smoking cessation medications that enhance dopamine are important to consider, given that persons with diabetes may display disrupted dopaminergic mechanisms. Future work is needed to better understand the complex interaction of dopamine and insulin in order to develop better smoking cessation medications for persons with diabetes.

Anatomical and pharmacological characterization of catecholamine transients in the medial prefrontal cortex evoked by ventral tegmental area stimulation

Voltammetric measurements of catecholamines in the medial prefrontal cortex (mPFC) are infrequent because of lack of chemical selectivity between dopamine and norepinephrine and their overlapping anatomical inputs. Here, we examined the contribution of norepinephrine to the catecholamine release in the mPFC evoked by electrical stimulation of the ventral tegmental area (VTA). Initially, electrical stimulation was delivered in the midbrain at incremental depths of -5 to -9.4 mm from bregma while catecholamine release was monitored in the mPFC. Although catecholamine release was observed at dorsal stimulation sites that may correspond to the dorsal noradrenergic bundle (DNB, containing noradrenergic axonal projections to the mPFC), maximal release was evoked by stimulation of the VTA (the source of dopaminergic input to the mPFC). Next, VTA-evoked catecholamine release was monitored in the mPFC before and after knife incision of the DNB, and no significant changes in the evoked catecholamine signals were found. These data indicated that DNB fibers did not contribute to the VTA-evoked catecholamine release observed in the mPFC. Finally, while the D2-receptor antagonist raclopride significantly altered VTA-evoked catecholamine release, the α₂-adrenergic receptor antagonist idazoxan did not. Specifically, raclopride reduced catecholamine release in the mPFC, opposite to that observed in the striatum, indicating differential autoreceptor regulation of mesocortical and mesostriatal neurons. Together, these findings suggest that the catecholamine release in the mPFC arising from VTA stimulation was predominately dopaminergic rather than noradrenergic.

Glutamate concentration in the medial prefrontal cortex predicts resting-state cortical-subcortical functional connectivity in humans

Communication between cortical and subcortical regions is integral to a wide range of psychological processes and has been implicated in a number of psychiatric conditions. Studies in animals have provided insight into the biochemical and connectivity processes underlying such communication. However, to date no experiments that link these factors in humans in vivo have been carried out. To investigate the role of glutamate in individual differences in communication between the cortex--specifically the medial prefrontal cortex (mPFC)--and subcortical regions in humans, a combination of resting-state fMRI, DTI and MRS was performed. The subcortical target regions were the nucleus accumbens (NAc), dorsomedial thalamus (DMT), and periaqueductal grey (PAG). It was found that functional connectivity between the mPFC and each of the NAc and DMT was positively correlated with mPFC glutamate concentrations, whilst functional connectivity between the mPFC and PAG was negatively correlated with glutamate concentration. The correlations involving mPFC glutamate and FC between the mPFC and each of the DMT and PAG were mirrored by correlations with structural connectivity, providing evidence that the glutamatergic relationship may, in part, be due to direct connectivity. These results are in agreement with existing results from animal studies and may have relevance for MDD and schizophrenia.

Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian-Bayesian Go-NoGo connectivity

Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian–Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect (NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available.