Dopamine-enabled anti-Hebbian timing-dependent plasticity in prefrontal circuitry

A mechanism for differential control of axonal and dendritic spiking underlying learning in a cerebellum-like circuit

In addition to the action potentials used for axonal signaling, many neurons generate dendritic "spikes" associated with synaptic plasticity. However, in order to control both plasticity and signaling, synaptic inputs must be able to differentially modulate the firing of these two spike types. Here, we investigate this issue in the electrosensory lobe (ELL) of weakly electric mormyrid fish, where separate control over axonal and dendritic spikes is essential for the transmission of learned predictive signals from inhibitory interneurons to the output stage of the circuit. Through a combination of experimental and modeling studies, we uncover a novel mechanism by which sensory input selectively modulates the rate of dendritic spiking by adjusting the amplitude of backpropagating axonal action potentials. Interestingly, this mechanism does not require spatially segregated synaptic inputs or dendritic compartmentalization but relies instead on an electrotonically distant spike initiation site in the axon-a common biophysical feature of neurons.

Long-term memory, synaptic plasticity and dopamine in rodent medial prefrontal cortex: Role in executive functions

Mnemonic functions, supporting rodent behavior in complex tasks, include both long-term and (short-term) working memory components. While working memory is thought to rely on persistent activity states in an active neural network, long-term memory and synaptic plasticity contribute to the formation of the underlying synaptic structure, determining the range of possible states. Whereas, the implication of working memory in executive functions, mediated by the prefrontal cortex (PFC) in primates and rodents, has been extensively studied, the contribution of long-term memory component to these tasks received little attention. This review summarizes available experimental data and theoretical work concerning cellular mechanisms of synaptic plasticity in the medial region of rodent PFC and the link between plasticity, memory and behavior in PFC-dependent tasks. A special attention is devoted to unique properties of dopaminergic modulation of prefrontal synaptic plasticity and its contribution to executive functions.

Adaptive control of synaptic plasticity integrates micro- and macroscopic network function

Synaptic plasticity configures interactions between neurons and is therefore likely to be a primary driver of behavioral learning and development. How this microscopic-macroscopic interaction occurs is poorly understood, as researchers frequently examine models within particular ranges of abstraction and scale. Computational neuroscience and machine learning models offer theoretically powerful analyses of plasticity in neural networks, but results are often siloed and only coarsely linked to biology. In this review, we examine connections between these areas, asking how network computations change as a function of diverse features of plasticity and vice versa. We review how plasticity can be controlled at synapses by calcium dynamics and neuromodulatory signals, the manifestation of these changes in networks, and their impacts in specialized circuits. We conclude that metaplasticity-defined broadly as the adaptive control of plasticity-forges connections across scales by governing what groups of synapses can and can't learn about, when, and to what ends. The metaplasticity we discuss acts by co-opting Hebbian mechanisms, shifting network properties, and routing activity within and across brain systems. Asking how these operations can go awry should also be useful for understanding pathology, which we address in the context of autism, schizophrenia and Parkinson's disease.

Translational neuronal ensembles: Neuronal microcircuits in psychology, physiology, pharmacology and pathology

Multi-recording techniques show evidence that neurons coordinate their firing forming ensembles and that brain networks are made by connections between ensembles. While “canonical” microcircuits are composed of interconnected principal neurons and interneurons, it is not clear how they participate in recorded neuronal ensembles: “groups of neurons that show spatiotemporal co-activation”. Understanding synapses and their plasticity has become complex, making hard to consider all details to fill the gap between cellular-synaptic and circuit levels. Therefore, two assumptions became necessary: First, whatever the nature of the synapses these may be simplified by “functional connections”. Second, whatever the mechanisms to achieve synaptic potentiation or depression, the resultant synaptic weights are relatively stable. Both assumptions have experimental basis cited in this review, and tools to analyze neuronal populations are being developed based on them. Microcircuitry processing followed with multi-recording techniques show temporal sequences of neuronal ensembles resembling computational routines. These sequences can be aligned with the steps of behavioral tasks and behavior can be modified upon their manipulation, supporting the hypothesis that they are memory traces. In vitro, recordings show that these temporal sequences can be contained in isolated tissue of histological scale. Sequences found in control conditions differ from those recorded in pathological tissue obtained from animal disease models and those recorded after the actions of clinically useful drugs to treat disease states, setting the basis for new bioassays to test drugs with potential clinical use. These findings make the neuronal ensembles theoretical framework a dynamic neuroscience paradigm.

Occlusion of dopamine-dependent synaptic plasticity in the prefrontal cortex mediates the expression of depressive-like behavior and is modulated by ketamine

Unpredictable chronic mild stress (CMS) is among the most popular protocols used to induce depressive-like behaviors such as anhedonia in rats. Differences in CMS protocols often result in variable degree of vulnerability, and the mechanisms behind stress resilience are of great interest in neuroscience due to their involvement in the development of psychiatric disorders, including major depressive disorder. Expression of depressive-like behaviors is likely driven by long-term alterations in the corticolimbic system and by downregulation of dopamine (DA) signaling. Although we have a deep knowledge about the dynamics of tonic and phasic DA release in encoding incentive salience and in response to acute/chronic stress, its modulatory action on cortical synaptic plasticity and the following implications on animal behavior remain elusive. Here, we show that the expression of DA-dependent synaptic plasticity in the medial prefrontal cortex (mPFC) is occluded in rats vulnerable to CMS, likely reflecting differential expression of AMPA receptors. Interestingly, such difference is not observed when rats are acutely treated with sub-anesthetic ketamine, possibly through the recruitment of dopaminergic nuclei such as the ventral tegmental area. In addition, by applying the synaptic activity sensor SynaptoZip in vivo, we found that chronic stress unbalances the synaptic drive from the infralimbic and prelimbic subregions of the mPFC toward the basolateral amygdala, and that this effect is counteracted by ketamine. Our results provide novel insights into the neurophysiological mechanisms behind the expression of vulnerability to stress, as well as behind the antidepressant action of ketamine.

Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology

Parkinson's disease (PD) is a multi-systemic neurodegenerative brain disorder. Motor symptoms of PD are linked to the significant dopamine (DA) loss in substantia nigra pars compacta (SNc) followed by basal ganglia (BG) circuit dysfunction. Increasing experimental and computational evidence indicates that (synaptic) plasticity plays a key role in the emergence of PD-related pathological changes following DA loss. Spike-timing-dependent plasticity (STDP) mediated by DA provides a mechanistic model for synaptic plasticity to modify synaptic connections within the BG according to the neuronal activity. To shed light on how DA-mediated STDP can shape neuronal activity and synaptic connectivity in the PD condition, we reviewed experimental and computational findings addressing the modulatory effect of DA on STDP as well as other plasticity mechanisms and discussed their potential role in PD pathophysiology and related network dynamics and connectivity. In particular, reshaping of STDP profiles together with other plasticity-mediated processes following DA loss may abnormally modify synaptic connections in competing pathways of the BG. The cascade of plasticity-induced maladaptive or compensatory changes can impair the excitation-inhibition balance towards the BG output nuclei, leading to the emergence of pathological activity-connectivity patterns in PD. Pre-clinical, clinical as well as computational studies reviewed here provide an understanding of the impact of synaptic plasticity and other plasticity mechanisms on PD pathophysiology, especially PD-related network activity and connectivity, after DA loss. This review may provide further insights into the abnormal structure-function relationship within the BG contributing to the emergence of pathological states in PD. Specifically, this review is intended to provide detailed information for the development of computational network models for PD, serving as testbeds for the development and optimization of invasive and non-invasive brain stimulation techniques. Computationally derived hypotheses may accelerate the development of therapeutic stimulation techniques and potentially reduce the number of related animal experiments.

Neuronal pericellular baskets: neurotransmitter convergence and regulation of network excitability

A pericellular basket is a presynaptic configuration of numerous axonal boutons outlining a target neuron soma and its proximal dendrites. Recent studies show neurochemical diversity of pericellular baskets and suggest that neurotransmitter usage together with the dense, soma-proximal boutons may permit strong input effects on different timescales. Here we review the development, distribution, neurochemical phenotypes, and possible functions of pericellular baskets. As an example, we highlight pericellular baskets formed by projections of certain Pet1/Fev neurons of the serotonergic raphe nuclei. We propose that pericellular baskets represent convergence sites of competition or facilitation between neurotransmitter systems on downstream circuitry, especially in limbic brain regions, where pericellular baskets are widespread. Study of these baskets may enhance our understanding of monoamine regulation of memory, social behavior, and brain oscillations.

Online Learning and Memory of Neural Trajectory Replays for Prefrontal Persistent and Dynamic Representations in the Irregular Asynchronous State

In the prefrontal cortex (PFC), higher-order cognitive functions and adaptive flexible behaviors rely on continuous dynamical sequences of spiking activity that constitute neural trajectories in the state space of activity. Neural trajectories subserve diverse representations, from explicit mappings in physical spaces to generalized mappings in the task space, and up to complex abstract transformations such as working memory, decision-making and behavioral planning. Computational models have separately assessed learning and replay of neural trajectories, often using unrealistic learning rules or decoupling simulations for learning from replay. Hence, the question remains open of how neural trajectories are learned, memorized and replayed online, with permanently acting biological plasticity rules. The asynchronous irregular regime characterizing cortical dynamics in awake conditions exerts a major source of disorder that may jeopardize plasticity and replay of locally ordered activity. Here, we show that a recurrent model of local PFC circuitry endowed with realistic synaptic spike timing-dependent plasticity and scaling processes can learn, memorize and replay large-size neural trajectories online under asynchronous irregular dynamics, at regular or fast (sped-up) timescale. Presented trajectories are quickly learned (within seconds) as synaptic engrams in the network, and the model is able to chunk overlapping trajectories presented separately. These trajectory engrams last long-term (dozen hours) and trajectory replays can be triggered over an hour. In turn, we show the conditions under which trajectory engrams and replays preserve asynchronous irregular dynamics in the network. Functionally, spiking activity during trajectory replays at regular timescale accounts for both dynamical coding with temporal tuning in individual neurons, persistent activity at the population level, and large levels of variability consistent with observed cognitive-related PFC dynamics. Together, these results offer a consistent theoretical framework accounting for how neural trajectories can be learned, memorized and replayed in PFC networks circuits to subserve flexible dynamic representations and adaptive behaviors.

Dopaminergic Neuromodulation of Spike Timing Dependent Plasticity in Mature Adult Rodent and Human Cortical Neurons

Synapses in the cerebral cortex constantly change and this dynamic property regulated by the action of neuromodulators such as dopamine (DA), is essential for reward learning and memory. DA modulates spike-timing-dependent plasticity (STDP), a cellular model of learning and memory, in juvenile rodent cortical neurons. However, it is unknown whether this neuromodulation also occurs at excitatory synapses of cortical neurons in mature adult mice or in humans. Cortical layer V pyramidal neurons were recorded with whole cell patch clamp electrophysiology and an extracellular stimulating electrode was used to induce STDP. DA was either bath-applied or optogenetically released in slices from mice. Classical STDP induction protocols triggered non-hebbian excitatory synaptic depression in the mouse or no plasticity at human cortical synapses. DA reverted long term synaptic depression to baseline in mouse via dopamine 2 type receptors or elicited long term synaptic potentiation in human cortical synapses. Furthermore, when DA was applied during an STDP protocol it depressed presynaptic inhibition in the mouse but not in the human cortex. Thus, DA modulates excitatory synaptic plasticity differently in human vs. mouse cortex. The data strengthens the importance of DA in gating cognition in humans, and may inform on therapeutic interventions to recover brain function from diseases.

Differential mapping spiking neural network for sensor-based robot control

In this work, a spiking neural network (SNN) is proposed for approximating differential sensorimotor maps of robotic systems. The computed model is used as a local Jacobian-like projection that relates changes in sensor space to changes in motor space. The SNN consists of an input (sensory) layer and an output (motor) layer connected through plastic synapses, with inter-inhibitory connections at the output layer. Spiking neurons are modeled as Izhikevich neurons with a synaptic learning rule based on spike timing-dependent plasticity. Feedback data from proprioceptive and exteroceptive sensors are encoded and fed into the input layer through a motor babbling process. A guideline for tuning the network parameters is proposed and applied along with the particle swarm optimization technique. Our proposed control architecture takes advantage of biologically plausible tools of an SNN to achieve the target reaching task while minimizing deviations from the desired path, and consequently minimizing the execution time. Thanks to the chosen architecture and optimization of the parameters, the number of neurons and the amount of data required for training are considerably low. The SNN is capable of handling noisy sensor readings to guide the robot movements in real-time. Experimental results are presented to validate the control methodology with a vision-guided robot.

Dopamine: The Neuromodulator of Long-Term Synaptic Plasticity, Reward and Movement Control

Dopamine (DA) is a key neurotransmitter involved in multiple physiological functions including motor control, modulation of affective and emotional states, reward mechanisms, reinforcement of behavior, and selected higher cognitive functions. Dysfunction in dopaminergic transmission is recognized as a core alteration in several devastating neurological and psychiatric disorders, including Parkinson's disease (PD), schizophrenia, bipolar disorder, attention deficit hyperactivity disorder (ADHD) and addiction. Here we will discuss the current insights on the role of DA in motor control and reward learning mechanisms and its involvement in the modulation of synaptic dynamics through different pathways. In particular, we will consider the role of DA as neuromodulator of two forms of synaptic plasticity, known as long-term potentiation (LTP) and long-term depression (LTD) in several cortical and subcortical areas. Finally, we will delineate how the effect of DA on dendritic spines places this molecule at the interface between the motor and the cognitive systems. Specifically, we will be focusing on PD, vascular dementia, and schizophrenia.

Loss of mGluR1-LTD following cocaine exposure accumulates Ca2+-permeable AMPA receptors and facilitates synaptic potentiation in the prefrontal cortex

Addiction results from drug-elicited alterations of synaptic plasticity mechanisms in dopaminergic reward circuits. Impaired metabotropic glutamate receptor (mGluR)-dependent long-term depression (LTD) and accumulation of synaptic Ca²⁺-permeable AMPA receptors (CP-AMPARs) following drug exposure have emerged as important mechanisms underlying drug craving and relapse. Here we show that repeated cocaine exposure in vivo causes transient but complete loss of mGluR1- and mTOR (mammalian target of rapamycin)-dependent LTD in layer 5 pyramidal neurons of mouse prefrontal cortex (PFC), a major dopaminergic target in the reward circuitry. This mGluR1-LTD impairment was prevented by in vivo administration of an mGluR1 positive allosteric modulator (PAM) and rescued by inhibition of dopamine D1 receptors, suggesting that impaired mGluR1 tone and excessive D1 signaling underlie this LTD deficit. Concurrently, CP-AMPARs were generated, indicated by increased sensitivity to the CP-AMPAR inhibitor Naspm and rectification of synaptic AMPAR currents, which were reversed by PAM in cocaine-exposed mice. Finally, these CP-AMPARs mediate an abnormal spike-timing-dependent long-term potentiation enabled by cocaine exposure. Our findings reveal a mechanism by which cocaine impairs LTD and remodels synaptic AMPARs to influence Hebbian plasticity in the PFC. Failure to undergo LTD may prevent the reversal of drug-potentiated brain circuits to their baseline states, perpetuating addictive behaviors.HIGHLIGHTSA mGluR1- and mTOR-dependent LTD is present in the mouse medial prefrontal cortex.Repeated cocaine exposure in vivo temporally but completely abolishes prefrontal mGluR1-LTD.Impaired mGluR1 function and excessive D1 DA signaling likely underlie cocaine impairment of mGluR1-LTD.Ca²⁺-permeable AMPA receptors are generated by cocaine exposure, likely resulting from mGluR1-LTD impairment, and contribute to a cocaine-induced extended spike timing LTP.

Achieving stable dynamics in neural circuits

The brain consists of many interconnected networks with time-varying, partially autonomous activity. There are multiple sources of noise and variation yet activity has to eventually converge to a stable, reproducible state (or sequence of states) for its computations to make sense. We approached this problem from a control-theory perspective by applying contraction analysis to recurrent neural networks. This allowed us to find mechanisms for achieving stability in multiple connected networks with biologically realistic dynamics, including synaptic plasticity and time-varying inputs. These mechanisms included inhibitory Hebbian plasticity, excitatory anti-Hebbian plasticity, synaptic sparsity and excitatory-inhibitory balance. Our findings shed light on how stable computations might be achieved despite biological complexity. Crucially, our analysis is not limited to analyzing the stability of fixed geometric objects in state space (e.g points, lines, planes), but rather the stability of state trajectories which may be complex and time-varying.

Inefficient neural system stabilization: a theory of spontaneous resolutions and recurrent relapses in psychosis

A striking feature of psychosis is its heterogeneity. Presentations of psychosis vary from transient symptoms with no functional consequence in the general population to a tenacious illness at the other extreme, with a wide range of variable trajectories in between. Even among patients with schizophrenia, who are diagnosed on the basis of persistent deterioration, marked variation is seen in response to treatment, frequency of relapses and degree of eventual recovery. Existing theoretical accounts of psychosis focus almost exclusively on how symptoms are initially formed, with much less emphasis on explaining their variable course. In this review, I present an account that links several existing notions of the biology of psychosis with the variant clinical trajectories. My aim is to incorporate perspectives of systems neuroscience in a staging framework to explain the individual variations in illness course that follow the onset of psychosis.

Rewards interact with repetition-dependent learning to enhance long-term retention of motor memories

The combination of behavioral experiences that enhance long-term retention remains largely unknown. Informed by neurophysiological lines of work, this study tested the hypothesis that performance-contingent monetary rewards potentiate repetition-dependent forms of learning, as induced by extensive practice at asymptote, to enhance long-term retention of motor memories. To this end, six groups of 14 participants (n = 84) acquired novel motor behaviors by adapting to a gradual visuomotor rotation while these factors were manipulated. Retention was assessed 24 h later. While all groups similarly acquired the novel motor behaviors, results from the retention session revealed an interaction indicating that rewards enhanced long-term retention, but only when practice was extended to asymptote. Specifically, the interaction indicated that this effect selectively occurred when rewards were intermittently available (i.e., 50%), but not when they were absent (i.e., 0%) or continuously available (i.e., 100%) during acquisition. This suggests that the influence of rewards on extensive practice and long-term retention is nonlinear, as continuous rewards did not further enhance retention as compared with intermittent rewards. One possibility is that rewards' intermittent availability allows to maintain their subjective value during acquisition, which may be key to potentiate long-term retention.

From membrane receptors to protein synthesis and actin cytoskeleton: Mechanisms underlying long lasting forms of synaptic plasticity

Synaptic plasticity, the activity dependent change in synaptic strength, forms the molecular foundation of learning and memory. Synaptic plasticity includes structural changes, with spines changing their size to accomodate insertion and removal of postynaptic receptors, which are correlated with functional changes. Of particular relevance for memory storage are the long lasting forms of synaptic plasticity which are protein synthesis dependent. Due to the importance of spine structural plasticity and protein synthesis, this review focuses on the signaling pathways that connect synaptic stimulation with regulation of protein synthesis and remodeling of the actin cytoskeleton. We also review computational models that implement novel aspects of molecular signaling in synaptic plasticity, such as the role of neuromodulators and spatial microdomains, as well as highlight the need for computational models that connect activation of memory kinases with spine actin dynamics.

Self-organising coordinate transformation with peaked and monotonic gain modulation in the primate dorsal visual pathway

We study a self-organising neural network model of how visual representations in the primate dorsal visual pathway are transformed from an eye-centred to head-centred frame of reference. The model has previously been shown to robustly develop head-centred output neurons with a standard trace learning rule, but only under limited conditions. Specifically it fails when incorporating visual input neurons with monotonic gain modulation by eye-position. Since eye-centred neurons with monotonic gain modulation are so common in the dorsal visual pathway, it is an important challenge to show how efferent synaptic connections from these neurons may self-organise to produce head-centred responses in a subpopulation of postsynaptic neurons. We show for the first time how a variety of modified, yet still biologically plausible, versions of the standard trace learning rule enable the model to perform a coordinate transformation from eye-centred to head-centred reference frames when the visual input neurons have monotonic gain modulation by eye-position.

Dopamine Receptor Activation Is Required for GABAergic Spike Timing-Dependent Plasticity in Response to Complex Spike Pairing in the Ventral Tegmental Area

One of the most influential synaptic learning rules explored in the past decades is activity dependent spike-timing-dependent plasticity (STDP). In STDP, synapses are either potentiated or depressed based on the order of pre- and postsynaptic neuronal activation within narrow, milliseconds-long, time intervals. STDP is subject to neuromodulation by dopamine (DA), a potent neurotransmitter that significantly impacts synaptic plasticity and reward-related behavioral learning. Previously, we demonstrated that GABAergic synapses onto ventral tegmental area (VTA) DA neurons are able to express STDP (Kodangattil et al., 2013), however it is still unclear whether DA modulates inhibitory STDP in the VTA. Here, we used whole-cell recordings in rat midbrain slices to investigate whether DA D1-like and/or D2-like receptor (D1R/D2R) activation is required for induction of STDP in response to a complex pattern of spiking. We found that VTA but not Substantia nigra pars compact (SNc) DA neurons exhibit long-term depression (LTD_GABA) in response to a combination of positive (pre-post) and negative (post-pre) timing of spiking (a complex STDP protocol). Blockade of either D1Rs or D2Rs prevented the induction of LTD_GABA while activation of D1Rs did not affect the plasticity in response to this complex STDP protocol in VTA DA neurons.Our data suggest that this DA-dependent GABAergic STDP is selectively expressed at GABAergic synapses onto VTA DA neurons which could be targeted by drugs of abuse to mediate drug-induced modulation of DA signaling within the VTA, as well as in VTA-projection areas, thereby affecting reward-related learning and drug-associated memories.

The Intersection of Central Dopamine System and Stroke: Potential Avenues Aiming at Enhancement of Motor Recovery

Dopamine, a major neurotransmitter, plays a role in a wide range of brain sensorimotor functions. Parkinson's disease and schizophrenia are two major human neuropsychiatric disorders typically associated with dysfunctional dopamine activity levels, which can be alleviated through the druggability of the dopaminergic systems. Meanwhile, several studies suggest that optimal brain dopamine activity levels are also significantly impacted in other serious neurological conditions, notably stroke, but this has yet to be fully appreciated at both basic and clinical research levels. This is of utmost importance as there is a need for better treatments to improve recovery from stroke. Here, we discuss the state of knowledge regarding the modulation of dopaminergic systems following stroke, and the use of dopamine boosting therapies in animal stroke models to improve stroke recovery. Indeed, studies in animals and humans show stroke leads to changes in dopamine functioning. Moreover, evidence from animal stroke models suggests stimulation of dopamine receptors may be a promising therapeutic approach for enhancing motor recovery from stroke. With respect to the latter, we discuss the evidence for several possible receptor-linked mechanisms by which improved motor recovery may be mediated. One avenue of particular promise is the subtype-selective stimulation of dopamine receptors in conjunction with physical therapy. However, results from clinical trials so far have been more mixed due to a number of potential reasons including, targeting of the wrong patient populations and use of drugs which modulate a wide array of receptors. Notwithstanding these issues, it is hoped that future research endeavors will assist in the development of more refined dopaminergic therapeutic approaches to enhance stroke recovery.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Dopamine terminals from the ventral tegmental area gate intrinsic inhibition in the prefrontal cortex

Spike frequency adaptation (SFA or accommodation) and calcium‐activated potassium channels that underlie after‐hyperpolarization potentials (AHP) regulate repetitive firing of neurons. Precisely how neuromodulators such as dopamine from the ventral tegmental area (VTA) regulate SFA and AHP (together referred to as intrinsic inhibition) in the prefrontal cortex (PFC) remains unclear. Using whole cell electrophysiology, we measured intrinsic inhibition in prelimbic (PL) layer 5 pyramidal cells of male adult rats. Results demonstrate that bath application of dopamine reduced intrinsic inhibition (EC₅₀: 25.0 μmol/L). This dopamine action was facilitated by coapplication of cocaine (1 μmol/L), a blocker of dopamine reuptake. To evaluate VTA dopamine terminals in PFC slices, we transfected VTA dopamine cells of TH::Cre rats in vivo with Cre‐dependent AAVs to express channelrhodopsin‐2 (ChR2) or designer receptors exclusively activated by designer drugs (DREADDS). In PFC slices from these animals, stimulation of VTA terminals with either blue light to activate ChR2 or bath application of clozapine‐N‐oxide (CNO) to activate Gq‐DREADDs produced a similar reduction in intrinsic inhibition in PL neurons. Electrophysiological recordings from cells expressing retrograde fluorescent tracers showed that this plasticity occurs in PL neurons projecting to the accumbens core. Collectively, these data highlight an ability of VTA terminals to gate intrinsic inhibition in the PFC, and under appropriate circumstances, enhance PL neuronal firing. These cellular actions of dopamine may be important for dopamine‐dependent behaviors involving cocaine and cue‐reward associations within cortical–striatal circuits.

Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex

Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca²⁺ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction.

SIGNIFICANCE STATEMENT

It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to relapse. We found that repeated cocaine exposure alters a Hebbian associative synaptic learning rule that governs activity-dependent synaptic plasticity in the mouse prefrontal cortex, characterized by a broader temporal window and a lower threshold for spike-timing-dependent LTP (t-LTP), a cellular form of learning and memory. This rule change is caused by cocaine-exacerbated D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons that in turn pathologically recruits l-type Ca²⁺ channels to facilitate coincidence detection during t-LTP induction. Our study provides novel insights on how cocaine, even with only brief exposure, may prime neural circuits for subsequent experience-dependent remodeling that may underlie certain addictive behavior.

Coexistence of Multiple Types of Synaptic Plasticity in Individual Hippocampal CA1 Pyramidal Neurons

Understanding learning and memory mechanisms is an important goal in neuroscience. To gain insights into the underlying cellular mechanisms for memory formation, synaptic plasticity processes are studied with various techniques in different brain regions. A valid model to scrutinize different ways to enhance or decrease synaptic transmission is recording of long-term potentiation (LTP) or long-term depression (LTD). At the single cell level, spike timing-dependent plasticity (STDP) protocols have emerged as a powerful tool to investigate synaptic plasticity with stimulation paradigms that also likely occur during memory formation in vivo. Such kind of plasticity can be induced by different STDP paradigms with multiple repeat numbers and stimulation patterns. They subsequently recruit or activate different molecular pathways and neuromodulators for induction and expression of STDP. Dopamine (DA) and brain-derived neurotrophic factor (BDNF) have been recently shown to be important modulators for hippocampal STDP at Schaffer collateral (SC)-CA1 synapses and are activated exclusively by distinguishable STDP paradigms. Distinct types of parallel synaptic plasticity in a given neuron depend on specific subcellular molecular prerequisites. Since the basal and apical dendrites of CA1 pyramidal neurons are known to be heterogeneous, and distance-dependent dendritic gradients for specific receptors and ion channels are described, the dendrites might provide domain specific locations for multiple types of synaptic plasticity in the same neuron. In addition to the distinct signaling and expression mechanisms of various types of LTP and LTD, activation of these different types of plasticity might depend on background brain activity states. In this article, we will discuss some ideas why multiple forms of synaptic plasticity can simultaneously and independently coexist and can contribute so effectively to increasing the efficacy of memory storage and processing capacity of the brain. We hypothesize that resolving the subcellular location of t-LTP and t-LTD mechanisms that are regulated by distinct neuromodulator systems will be essential to reach a more cohesive understanding of synaptic plasticity in memory formation.

Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity

The brain enables animals to behaviorally adapt in order to survive in a complex and dynamic environment, but how reward-oriented behaviors are achieved and computed by its underlying neural circuitry is an open question. To address this concern, we have developed a spiking model of the basal ganglia (BG) that learns to dis-inhibit the action leading to a reward despite ongoing changes in the reward schedule. The architecture of the network features the two pathways commonly described in BG, the direct (denoted D1) and the indirect (denoted D2) pathway, as well as a loop involving striatum and the dopaminergic system. The activity of these dopaminergic neurons conveys the reward prediction error (RPE), which determines the magnitude of synaptic plasticity within the different pathways. All plastic connections implement a versatile four-factor learning rule derived from Bayesian inference that depends upon pre- and post-synaptic activity, receptor type, and dopamine level. Synaptic weight updates occur in the D1 or D2 pathways depending on the sign of the RPE, and an efference copy informs upstream nuclei about the action selected. We demonstrate successful performance of the system in a multiple-choice learning task with a transiently changing reward schedule. We simulate lesioning of the various pathways and show that a condition without the D2 pathway fares worse than one without D1. Additionally, we simulate the degeneration observed in Parkinson's disease (PD) by decreasing the number of dopaminergic neurons during learning. The results suggest that the D1 pathway impairment in PD might have been overlooked. Furthermore, an analysis of the alterations in the synaptic weights shows that using the absolute reward value instead of the RPE leads to a larger change in D1.

Cholinergic modulation of dopamine pathways through nicotinic acetylcholine receptors

Nicotine addiction is highly prevalent in current society and is often comorbid with other diseases. In the central nervous system, nicotine acts as an agonist for nicotinic acetylcholine receptors (nAChRs) and its effects depend on location and receptor composition. Although nicotinic receptors are found in most brain regions, many studies on addiction have focused on the mesolimbic system and its reported behavioral correlates such as reward processing and reinforcement learning. Profound modulatory cholinergic input from the pedunculopontine and laterodorsal tegmentum to dopaminergic midbrain nuclei as well as local cholinergic interneuron projections to dopamine neuron axons in the striatum may play a major role in the effects of nicotine. Moreover, an indirect mesocorticolimbic feedback loop involving the medial prefrontal cortex may be involved in behavioral characteristics of nicotine addiction. Therefore, this review will highlight current understanding of the effects of nicotine on the function of mesolimbic and mesocortical dopamine projections in the mesocorticolimbic circuit.

Chronic cocaine disrupts mesocortical learning mechanisms

The addictive power of drugs of abuse such as cocaine comes from their ability to hijack natural reward and plasticity mechanisms mediated by dopamine signaling in the brain. Reward learning involves burst firing of midbrain dopamine neurons in response to rewards and cues predictive of reward. The resulting release of dopamine in terminal regions is thought to act as a teaching signaling to areas such as the prefrontal cortex and striatum. In this review, we posit that a pool of extrasynaptic dopaminergic D1-like receptors activated in response to dopamine neuron burst firing serve to enable synaptic plasticity in the prefrontal cortex in response to rewards and their cues. We propose that disruptions in these mechanisms following chronic cocaine use contribute to addiction pathology, in part due to the unique architecture of the mesocortical pathway. By blocking dopamine reuptake in the cortex, cocaine elevates dopamine signaling at these extrasynaptic receptors, prolonging D1-receptor activation and the subsequent activation of intracellular signaling cascades, and thus inducing long-lasting maladaptive plasticity. These cellular adaptations may account for many of the changes in cortical function observed in drug addicts, including an enduring vulnerability to relapse. Therefore, understanding and targeting these neuroadaptations may provide cognitive benefits and help prevent relapse in human drug addicts.