Modeling nicotinic neuromodulation from global functional and network levels to nAChR based mechanisms

Simulating Small Neural Circuits with a Discrete Computational Model

Simulations of neural activity are commonly based on differential equations. We address the question what can be achieved with a simplified discrete model. The proposed model resembles artificial neural networks enriched with additional biologically inspired features. A neuron has several states, and the state transitions follow endogenous patterns which roughly correspond to firing behavior observed in biological neurons: oscillatory, tonic, plateauing, etc. Neural interactions consist of two components: synaptic connections and extrasynaptic emission of neurotransmitters. The dynamics is asynchronous and event-based; the events correspond to the changes in neurons activity. This model is innovative in introducing discrete framework for modeling neurotransmitter interactions which play the important role in neuromodulation. We simulate rhythmic activity of small neural ensembles like central pattern generators (CPG). The modeled examples include: the biphasic rhythm generated by the half-center mechanism with the post-inhibitory rebound (like the leech heartbeat CPG), the triphasic rhythm (like in pond snail feeding CPG) and the pattern switch in the system of several neurons (like the switch between ingestion and egestion in Aplysia feeding CPG). The asynchronous dynamics allows to obtain multi-phasic rhythms with phase durations close to their biological prototypes. The perspectives of discrete modeling in biological research are discussed in the conclusion.

Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery

Stroke is a leading cause of worldwide disability, and up to 75% of survivors suffer from some degree of arm paresis. Recently, rehabilitation of stroke patients has focused on recovering motor skills by taking advantage of use-dependent neuroplasticity, where high-repetition of goal-oriented movement is at times combined with non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS). Merging the two approaches is thought to provide outlasting clinical gains, by enhancing synaptic plasticity and motor relearning in the motor cortex primary area. However, this general approach has shown mixed results across the stroke population. In particular, stroke location has been found to correlate with the likelihood of success, which suggests that different patients might require different protocols. Understanding how motor rehabilitation and stimulation interact with ongoing neural dynamics is crucial to optimize rehabilitation strategies, but it requires theoretical and computational models to consider the multiple levels at which this complex phenomenon operate. In this work, we argue that biophysical models of cortical dynamics are uniquely suited to address this problem. Specifically, biophysical models can predict treatment efficacy by introducing explicit variables and dynamics for damaged connections, changes in neural excitability, neurotransmitters, neuromodulators, plasticity mechanisms, and repetitive movement, which together can represent brain state, effect of incoming stimulus, and movement-induced activity. In this work, we hypothesize that effects of tDCS depend on ongoing neural activity and that tDCS effects on plasticity may be also related to enhancing inhibitory processes. We propose a model design for each step of this complex system, and highlight strengths and limitations of the different modeling choices within our approach. Our theoretical framework proposes a change in paradigm, where biophysical models can contribute to the future design of novel protocols, in which combined tDCS and motor rehabilitation strategies are tailored to the ongoing dynamics that they interact with, by considering the known biophysical factors recruited by such protocols and their interaction.

Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting

In the ventral tegmental area (VTA), interactions between dopamine (DA) and γ-aminobutyric acid (GABA) neurons are critical for regulating DA neuron activity and thus DA efflux. To provide a mechanistic explanation of how GABA neurons influence DA neuron firing, we developed a circuit model of the VTA. The model is based on feed-forward inhibition and recreates canonical features of the VTA neurons. Simulations revealed that γ-aminobutyric acid (GABA) receptor (GABAR) stimulation can differentially influence the firing pattern of the DA neuron, depending on the level of synchronization among GABA neurons. Asynchronous activity of GABA neurons provides a constant level of inhibition to the DA neuron and, when removed, produces a classical disinhibition burst. In contrast, when GABA neurons are synchronized by common synaptic input, their influence evokes additional spikes in the DA neuron, resulting in increased measures of firing and bursting. Distinct from previous mechanisms, the increases were not based on lowered firing rate of the GABA neurons or weaker hyperpolarization by the GABAR synaptic current. This phenomenon was induced by GABA-mediated hyperpolarization of the DA neuron that leads to decreases in intracellular calcium (Ca2+) concentration, thus reducing the Ca2+-dependent potassium (K+) current. In this way, the GABA-mediated hyperpolarization replaces Ca2+-dependent K+ current; however, this inhibition is pulsatile, which allows the DA neuron to fire during the rhythmic pauses in inhibition. Our results emphasize the importance of inhibition in the VTA, which has been discussed in many studies, and suggest a novel mechanism whereby computations can occur locally.

Mechanisms for multiple activity modes of VTA dopamine neurons

Midbrain ventral segmental area (VTA) dopaminergic neurons send numerous projections to cortical and sub-cortical areas, and diffusely release dopamine (DA) to their targets. DA neurons display a range of activity modes that vary in frequency and degree of burst firing. Importantly, DA neuronal bursting is associated with a significantly greater degree of DA release than an equivalent tonic activity pattern. Here, we introduce a single compartmental, conductance-based computational model for DA cell activity that captures the behavior of DA neuronal dynamics and examine the multiple factors that underlie DA firing modes: the strength of the SK conductance, the amount of drive, and GABA inhibition. Our results suggest that neurons with low SK conductance fire in a fast firing mode, are correlated with burst firing, and require higher levels of applied current before undergoing depolarization block. We go on to consider the role of GABAergic inhibition on an ensemble of dynamical classes of DA neurons and find that strong GABA inhibition suppresses burst firing. Our studies suggest differences in the distribution of the SK conductance and GABA inhibition levels may indicate subclasses of DA neurons within the VTA. We further identify, that by considering alternate potassium dynamics, the dynamics display burst patterns that terminate via depolarization block, akin to those observed in vivo in VTA DA neurons and in substantia nigra pars compacta (SNc) DA cell preparations under apamin application. In addition, we consider the generation of transient burst firing events that are NMDA-initiated or elicited by a sudden decrease of GABA inhibition, that is, disinhibition.

Cross-species analysis of nicotine-induced proteomic alterations in pancreatic cells

Toxic compounds in tobacco, such as nicotine, may adversely affect pancreatic function. We aim to determine nicotine-induced protein alterations in pancreatic cells, thereby revealing links between nicotine exposure and pancreatic disease. We compared the proteomic alterations induced by nicotine treatment in cultured pancreatic cells (mouse, rat, and human stellate cells and human duct cells) using MS-based techniques, specifically SDS-PAGE (gel) coupled with LC-MS/MS and spectral counting. We identified thousands of proteins in pancreatic cells, hundreds of which were identified exclusively or in higher abundance in either nicotine-treated or untreated cells. Interspecies comparisons of stellate cell proteins revealed several differentially abundant proteins (in nicotine treated versus untreated cells) common among the three species. Proteins appearing in all nicotine-treated stellate cells include amyloid beta (A4), procollagen type VI alpha 1, integral membrane protein 2B, and toll-interacting protein. Proteins that were differentially expressed upon nicotine treatment across cell lines were enriched in certain pathways, including nicotinic acetylcholine receptor, cytokine, and integrin signaling. At this analytical depth, we conclude that similar pathways are affected by nicotine, but alterations at the protein level among stellate cells of different species vary. Further interrogation of such pathways will lead to insights into the potential effect of nicotine on pancreatic cells at the biomolecular level and the extension of this concept to the effect of nicotine on pancreatic disease.

Cortical control of VTA function and influence on nicotine reward

Tobacco use is a major public health problem. Nicotine acts on widely distributed nicotinic acetylcholine receptors (nAChRs) in the brain and excites dopamine (DA) neurons in the ventral tegmental area (VTA). The elicited increase of DA neuronal activity is thought to be an important mechanism for nicotine reward and subsequently the transition to addiction. However, the current understanding of nicotine reward is based predominantly on the data accumulated from in vitro studies, often from VTA slices. Isolated VTA slices artificially terminate communications between neurons in the VTA and other brain regions that may significantly alter nicotinic effects. Consequently, the mechanisms of nicotinic excitation of VTA DA neurons under in vivo conditions have received only limited attention. Building upon the existing knowledge acquired in vitro, it is now time to elucidate the integrated mechanisms of nicotinic reward on intact systems that are more relevant to understanding the action of nicotine or other addictive drugs. In this review, we summarize recent studies that demonstrate the impact of prefrontal cortex (PFC) on the modulation of VTA DA neuronal function and nicotine reward. Based on existing evidence, we propose a new hypothesis that PFC-VTA functional coupling serves as an integration mechanism for nicotine reward. Moreover, addiction may develop due to nicotine perturbing the PFC-VTA coupling and thereby eliminating the PFC-dependent cognitive control over behavior.

Endogenous cholinergic inputs and local circuit mechanisms govern the phasic mesolimbic dopamine response to nicotine

Nicotine exerts its reinforcing action by stimulating nicotinic acetylcholine receptors (nAChRs) and boosting dopamine (DA) output from the ventral tegmental area (VTA). Recent data have led to a debate about the principal pathway of nicotine action: direct stimulation of the DAergic cells through nAChR activation, or disinhibition mediated through desensitization of nAChRs on GABAergic interneurons. We use a computational model of the VTA circuitry and nAChR function to shed light on this issue. Our model illustrates that the α4β2-containing nAChRs either on DA or GABA cells can mediate the acute effects of nicotine. We account for in vitro as well as in vivo data, and predict the conditions necessary for either direct stimulation or disinhibition to be at the origin of DA activity increases. We propose key experiments to disentangle the contribution of both mechanisms. We show that the rate of endogenous acetylcholine input crucially determines the evoked DA response for both mechanisms. Together our results delineate the mechanisms by which the VTA mediates the acute rewarding properties of nicotine and suggest an acetylcholine dependence hypothesis for nicotine reinforcement.

Nicotine is the major addictive substance in tobacco smoke. Nicotine exerts its control over neural circuits through nicotinic acetylcholine receptors that normally respond to endogenous acetylcholine. Activation of dopamine neurons in the mesolimbic dopaminergic circuits, which signal motivational properties of actions and stimuli, is at the heart of mediating nicotine reward and dependence. However, major questions have remained unsettled over the precise mechanisms by which nicotine usurps dopaminergic signaling: through receptor activation on dopamine neurons or through receptor desensitization on local inhibitory interneurons. Here we reconcile this debate by showing that both mechanisms are possible. Most notably we present a novel hypothesis suggesting that the mechanisms for nicotine action are state-dependent; they are controlled by the rate of the endogenous cholinergic input to the dopaminergic circuits.

Co-activation of VTA DA and GABA neurons mediates nicotine reinforcement

Smoking is the most important preventable cause of mortality and morbidity worldwide. This nicotine addiction is mediated through the nicotinic acetylcholine receptor (nAChR), expressed on most neurons, and also many other organs in the body. Even within the ventral tegmental area (VTA), the key brain area responsible for the reinforcing properties of all drugs of abuse, nicotine acts on several different cell types and afferents. Identifying the precise action of nicotine on this microcircuit, in vivo, is important to understand reinforcement, and finally to develop efficient smoking cessation treatments. We used a novel lentiviral system to re-express exclusively high-affinity nAChRs on either dopaminergic (DAergic) or γ-aminobutyric acid-releasing (GABAergic) neurons, or both, in the VTA. Using in vivo electrophysiology, we show that, contrary to widely accepted models, the activation of GABA neurons in the VTA plays a crucial role in the control of nicotine-elicited DAergic activity. Our results demonstrate that both positive and negative motivational values are transmitted through the dopamine (DA) neuron, but that the concerted activity of DA and GABA systems is necessary for the reinforcing actions of nicotine through burst firing of DA neurons. This work identifies the GABAergic interneuron as a potential target for smoking cessation drug development.

From occasional choices to inevitable musts: a computational model of nicotine addiction

Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed.

Impact of prefrontal cortex in nicotine-induced excitation of ventral tegmental area dopamine neurons in anesthetized rats

Systemic administration of nicotine increases dopaminergic (DA) neuron firing in the ventral tegmental area (VTA), which is thought to underlie nicotine reward. Here, we report that the medial prefrontal cortex (mPFC) plays a critical role in nicotine-induced excitation of VTA DA neurons. In chloral hydrate-anesthetized rats, extracellular single-unit recordings showed that VTA DA neurons exhibited two types of firing responses to systemic nicotine. After nicotine injection, the neurons with type-I response showed a biphasic early inhibition and later excitation, whereas the neurons with type-II response showed a monophasic excitation. The neurons with type-I, but not type-II, response exhibited pronounced slow oscillations (SOs) in firing. Pharmacological or structural mPFC inactivation abolished SOs and prevented systemic nicotine-induced excitation in the neurons with type-I, but not type-II, response, suggesting that these VTA DA neurons are functionally coupled to the mPFC and nicotine increases firing rate in these neurons in part through the mPFC. Systemic nicotine also increased the firing rate and SOs in mPFC pyramidal neurons. mPFC infusion of a non-α7 nicotinic acetylcholine receptor (nAChR) antagonist mecamylamine blocked the excitatory effect of systemic nicotine on the VTA DA neurons with type-I response, but mPFC infusion of nicotine failed to excite these neurons. These results suggest that nAChR activation in the mPFC is necessary, but not sufficient, for systemic nicotine-induced excitation of VTA neurons. Finally, systemic injection of bicuculline prevented nicotine-induced firing alterations in the neurons with type-I response. We propose that the mPFC plays a critical role in systemic nicotine-induced excitation of VTA DA neurons.

A reduced model of DA neuronal dynamics that displays quiescence, tonic firing and bursting

Midbrain dopaminergic neurons send numerous projections to cortical and sub-cortical areas, and in a manner dependent upon their activities, diffusely release dopamine (DA) to their targets. Recent experimental studies have shown that DAergic neuronal bursting is associated with a significantly greater degree of DA release than an equivalent tonic activity pattern. Past computational models for DA cell activity relied upon somatodendritic mechanisms in order to generate DA neuronal bursting. However, recent experimental studies indicate that burst firing can be generated somatically with the dendrites silenced. These somatically induced bursts have characteristics consistent with normal bursting, suggesting that a single-compartmental model should be sufficient for generating the observed DA neuronal dynamics. In this work, we introduce such a model for DA neuronal dynamics and demonstrate that this model captures the qualitative behavior of DAergic neuronal dynamics: quiescence, tonic firing and bursting. In our conductance-based approach, the interplay between the L-type calcium and the calcium dependent SK potassium channel provides a scaffold for the underlying oscillation for the pacemaker-like firing patterns. The model includes terms which can selectively block the SK conductance, which would correspond to pharmacological manipulations using the drug apamin. Our modeling studies are in line with experimental evidence that a reduction of the SK conductance often induces DA neuronal bursting. Moreover, our model can reproduce findings that burst firing can be elicited via stimulus driven events, manifested by rises in the amount of NMDA. This model for DA cell activity could be further sculpted to include more detailed second messenger signaling processes in order to elucidate key differences between the two principal classes of midbrain DA neurons: those of the ventral tegmental area and the substantia nigra pars compacta.