Space, time and dopamine

Parkinson's Disease: Cells Succumbing to Lifelong Dopamine-Related Oxidative Stress and Other Bioenergetic Challenges

The core pathological event in Parkinson's disease (PD) is the specific dying of dopamine (DA) neurons of the substantia nigra pars compacta (SNc). The reasons why SNc DA neurons are especially vulnerable and why idiopathic PD has only been found in humans are still puzzling. The two main underlying factors of SNc DA neuron vulnerability appear related to high DA production, namely (i) the toxic effects of cytoplasmic DA metabolism and (ii) continuous cytosolic Ca2+ oscillations in the absence of the Ca2+-buffer protein calbindin. Both factors cause oxidative stress by producing highly reactive quinones and increasing intra-mitochondrial Ca2+ concentrations, respectively. High DA expression in human SNc DA neuron cell bodies is suggested by the abundant presence of the DA-derived pigment neuromelanin, which is not found in such abundance in other species and has been associated with toxicity at higher levels. The oxidative stress created by their DA production system, despite the fact that the SN does not use unusually high amounts of energy, explains why SNc DA neurons are sensitive to various genetic and environmental factors that create mitochondrial damage and thereby promote PD. Aging increases multiple risk factors for PD, and, to a large extent, PD is accelerated aging. To prevent PD neurodegeneration, possible approaches that are discussed here are (1) reducing cytoplasmic DA accumulation, (2) blocking cytoplasmic Ca2+ oscillations, and (3) providing bioenergetic support.

GABAergic-like dopamine synapses in the brain

Dopamine synapses play a crucial role in volitional movement and reward-related behaviors, while dysfunction of dopamine synapses causes various psychiatric and neurological disorders. Despite this significance, the true biological nature of dopamine synapses remains poorly understood. Here, we show that dopamine transmission is strongly correlated with GABA co-transmission across the brain and dopamine synapses are structured and function like GABAergic synapses with marked regional heterogeneity. In addition, GABAergic-like dopamine synapses are clustered on the dendrites, and GABA transmission at dopamine synapses has distinct physiological properties. Interestingly, the knockdown of neuroligin-2, a key postsynaptic protein at GABAergic synapses, unexpectedly does not weaken GABA co-transmission but instead facilitates it at dopamine synapses in the striatal neurons. More importantly, the attenuation of GABA co-transmission precedes deficits in dopaminergic transmission in animal models of Parkinson's disease. Our findings reveal the spatial and functional nature of GABAergic-like dopamine synapses in health and disease.

Acetylcholine waves and dopamine release in the striatum

Striatal dopamine encodes reward, with recent work showing that dopamine release occurs in spatiotemporal waves. However, the mechanism of dopamine waves is unknown. Here we report that acetylcholine release in mouse striatum also exhibits wave activity, and that the spatial scale of striatal dopamine release is extended by nicotinic acetylcholine receptors. Based on these findings, and on our demonstration that single cholinergic interneurons can induce dopamine release, we hypothesized that the local reciprocal interaction between cholinergic interneurons and dopamine axons suffices to drive endogenous traveling waves. We show that the morphological and physiological properties of cholinergic interneuron - dopamine axon interactions can be modeled as a reaction-diffusion system that gives rise to traveling waves. Analytically-tractable versions of the model show that the structure and the nature of propagation of acetylcholine and dopamine traveling waves depend on their coupling, and that traveling waves can give rise to empirically observed correlations between these signals. Thus, our study provides evidence for striatal acetylcholine waves in vivo, and proposes a testable theoretical framework that predicts that the observed dopamine and acetylcholine waves are strongly coupled phenomena.

Flexible, Miniaturized Sensing Probes Inspired by Biofuel Cells for Monitoring Synaptically Released Glutamate in the Mouse Brain

Chemical biomarkers in the central nervous system can provide valuable quantitative measures to gain insight into the etiology and pathogenesis of neurological diseases. Glutamate, one of the most important excitatory neurotransmitters in the brain, has been found to be upregulated in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, stroke, epilepsy, chronic pain, and migraines. However, quantitatively monitoring glutamate release in situ has been challenging. This work presents a novel class of flexible, miniaturized probes inspired by biofuel cells for monitoring synaptically released glutamate in the nervous system. The resulting sensors, with dimensions as low as 50 by 50 μm, can detect real-time changes in glutamate within the biologically relevant concentration range. Experiments exploiting the hippocampal circuit in mice models demonstrate the capability of the sensors in monitoring glutamate release via electrical stimulation using acute brain slices. These advances could aid in basic neuroscience studies and translational engineering, as the sensors provide a diagnostic tool for neurological disorders. Additionally, adapting the biofuel cell design to other neurotransmitters can potentially enable the detailed study of the effect of neurotransmitter dysregulation on neuronal cell signaling pathways and revolutionize neuroscience.

Adolescent neurostimulation of dopamine circuit reverses genetic deficits in frontal cortex function

Dopamine system dysfunction is implicated in adolescent-onset neuropsychiatric disorders. Although psychosis symptoms can be alleviated by antipsychotics, cognitive symptoms remain unresponsive and novel paradigms investigating the circuit substrates underlying cognitive deficits are critically needed. The frontal cortex and its dopaminergic input from the midbrain are implicated in cognitive functions and undergo maturational changes during adolescence. Here, we used mice carrying mutations in Arc or Disc1 to model mesofrontal dopamine circuit deficiencies and test circuit-based neurostimulation strategies to restore cognitive functions. We found that in a memory-guided spatial navigation task, frontal cortical neurons were activated coordinately at the decision-making point in wild-type but not Arc-/- mice. Chemogenetic stimulation of midbrain dopamine neurons or optogenetic stimulation of frontal cortical dopamine axons in a limited adolescent period consistently reversed genetic defects in mesofrontal innervation, task-coordinated neuronal activity, and memory-guided decision-making at adulthood. Furthermore, adolescent stimulation of dopamine neurons also reversed the same cognitive deficits in Disc1+/- mice. Our findings reveal common mesofrontal circuit alterations underlying the cognitive deficits caused by two different genes and demonstrate the feasibility of adolescent neurostimulation to reverse these circuit and behavioral deficits. These results may suggest developmental windows and circuit targets for treating cognitive deficits in neurodevelopmental disorders.

Profiling transcriptomic responses of human stem cell-derived medium spiny neuron-like cells to exogenous phasic and tonic neurotransmitters

Transcriptomic responses to neurotransmitters contribute to the complex processes driving memory and addiction. Advances in both measurement methods and experimental models continue to improve our understanding of this regulatory layer. Here we focus on the experimental potential of stem cell derived neurons, currently the only ethical model that can be used in reductionist and experimentally perturbable studies of human cells. Prior work has focused on generating distinct cell types from human stem cells, and has also shown their utility in modeling development and cellular phenotypes related to neurodegeneration. Here we seek an understanding of how stem cell derived neural cultures respond to perturbations experienced during development and disease progression. This work profiles transcriptomic responses of human medium spiny neuron-like cells with three specific goals. We first characterize transcriptomic responses to dopamine and dopamine receptor agonists and antagonists presented in dosing patterns mimicking acute, chronic, and withdrawal regimens. We also assess transcriptomic responses to low and persistent tonic levels of dopamine, acetylcholine, and glutamate to better mimic the in vivo environment. Finally, we identify similar and distinct responses between hMSN-like cells derived from H9 and H1 stem cell lines, providing some context for the extent of variability these types of systems will likely pose for experimentalists. The results here suggest future optimizations of human stem cell derived neurons to increase their in vivo relevance and the biological insights that can be garnered from these models.

Enhancing reinforcement learning models by including direct and indirect pathways improves performance on striatal dependent tasks

A major advance in understanding learning behavior stems from experiments showing that reward learning requires dopamine inputs to striatal neurons and arises from synaptic plasticity of cortico-striatal synapses. Numerous reinforcement learning models mimic this dopamine-dependent synaptic plasticity by using the reward prediction error, which resembles dopamine neuron firing, to learn the best action in response to a set of cues. Though these models can explain many facets of behavior, reproducing some types of goal-directed behavior, such as renewal and reversal, require additional model components. Here we present a reinforcement learning model, TD2Q, which better corresponds to the basal ganglia with two Q matrices, one representing direct pathway neurons (G) and another representing indirect pathway neurons (N). Unlike previous two-Q architectures, a novel and critical aspect of TD2Q is to update the G and N matrices utilizing the temporal difference reward prediction error. A best action is selected for N and G using a softmax with a reward-dependent adaptive exploration parameter, and then differences are resolved using a second selection step applied to the two action probabilities. The model is tested on a range of multi-step tasks including extinction, renewal, discrimination; switching reward probability learning; and sequence learning. Simulations show that TD2Q produces behaviors similar to rodents in choice and sequence learning tasks, and that use of the temporal difference reward prediction error is required to learn multi-step tasks. Blocking the update rule on the N matrix blocks discrimination learning, as observed experimentally. Performance in the sequence learning task is dramatically improved with two matrices. These results suggest that including additional aspects of basal ganglia physiology can improve the performance of reinforcement learning models, better reproduce animal behaviors, and provide insight as to the role of direct- and indirect-pathway striatal neurons.

Sensory Reinforced Corticostriatal Plasticity

BACKGROUND

Regional changes in corticostriatal transmission induced by phasic dopaminergic signals are an essential feature of the neural network responsible for instrumental reinforcement during discovery of an action. However, the timing of signals that are thought to contribute to the induction of corticostriatal plasticity is difficult to reconcile within the framework of behavioural reinforcement learning, because the reinforcer is normally delayed relative to the selection and execution of causally-related actions.

OBJECTIVE

While recent studies have started to address the relevance of delayed reinforcement signals and their impact on corticostriatal processing, our objective was to establish a model in which a sensory reinforcer triggers appropriately delayed reinforcement signals relayed to the striatum via intact neuronal pathways and to investigate the effects on corticostriatal plasticity.

METHODS

We measured corticostriatal plasticity with electrophysiological recordings using a light flash as a natural sensory reinforcer, and pharmacological manipulations were applied in an in vivo anesthetized rat model preparation.

RESULTS

We demonstrate that the spiking of striatal neurons evoked by single-pulse stimulation of the motor cortex can be potentiated by a natural sensory reinforcer, operating through intact afferent pathways, with signal timing approximating that required for behavioural reinforcement. The pharmacological blockade of dopamine receptors attenuated the observed potentiation of corticostriatal neurotransmission.

CONCLUSION

This novel in vivo model of corticostriatal plasticity offers a behaviourally relevant framework to address the physiological, anatomical, cellular, and molecular bases of instrumental reinforcement learning.

Identifying Neural Signatures of Dopamine Signaling with Machine Learning

The emergence of new tools to image neurotransmitters, neuromodulators, and neuropeptides has transformed our understanding of the role of neurochemistry in brain development and cognition, yet analysis of this new dimension of neurobiological information remains challenging. Here, we image dopamine modulation in striatal brain tissue slices with near-infrared catecholamine nanosensors (nIRCat) and implement machine learning to determine which features of dopamine modulation are unique to changes in stimulation strength, and to different neuroanatomical regions. We trained a support vector machine and a random forest classifier to decide whether the recordings were made from the dorsolateral striatum (DLS) versus the dorsomedial striatum (DMS) and find that machine learning is able to accurately distinguish dopamine release that occurs in DLS from that occurring in DMS in a manner unachievable with canonical statistical analysis. Furthermore, our analysis determines that dopamine modulatory signals including the number of unique dopamine release sites and peak dopamine released per stimulation event are most predictive of neuroanatomy. This is in light of integrated neuromodulator amount being the conventional metric used to monitor neuromodulation in animal studies. Lastly, our study finds that machine learning discrimination of different stimulation strengths or neuroanatomical regions is only possible in adult animals, suggesting a high degree of variability in dopamine modulatory kinetics during animal development. Our study highlights that machine learning could become a broadly utilized tool to differentiate between neuroanatomical regions or between neurotypical and disease states, with features not detectable by conventional statistical analysis.

Cellular bases for reward-related dopamine actions

Dopamine neurons exhibit transient increases and decreases in their firing rate upon reward and punishment for learning. This bidirectional modulation of dopamine dynamics occurs on the order of hundreds of milliseconds, and it is sensitively detected to reinforce the preceding sensorimotor events. These observations indicate that the mechanisms of dopamine detection at the projection sites are of remarkable precision, both in time and concentration. A major target of dopamine projection is the striatum, including the ventral region of the nucleus accumbens, which mainly comprises dopamine D1 and D2 receptor (D1R and D2R)-expressing spiny projection neurons. Although the involvement of D1R and D2R in dopamine-dependent learning has been suggested, the exact cellular bases for detecting transient dopamine signaling remain unclear. This review discusses recent cellular studies on the novel synaptic mechanisms for detecting dopamine transient signals associated with learning. Analyses of behavior based on these mechanisms have further revealed new behavioral aspects that are closely associated with these synaptic mechanisms. Thus, it is gradually possible to mechanistically explain behavioral learning via synaptic and cellular bases in rodents.

Analogous cognitive strategies for tactile learning in the rodent and human brain

Evolution has molded individual species' sensory capacities and abilities. In rodents, who mostly inhabit dark tunnels and burrows, the whisker-based somatosensory system has developed as the dominant sensory modality, essential for environmental exploration and spatial navigation. In contrast, humans rely more on visual and auditory inputs when collecting information from their surrounding sensory space in everyday life. As a result of such species-specific differences in sensory dominance, cognitive relevance and capacities, the evidence for analogous sensory-cognitive mechanisms across species remains sparse. However, recent research in rodents and humans yielded surprisingly comparable processing rules for detecting tactile stimuli, integrating touch information into percepts, and goal-directed rule learning. Here, we review how the brain, across species, harnesses such processing rules to establish decision-making during tactile learning, following canonical circuits from the thalamus and the primary somatosensory cortex up to the frontal cortex. We discuss concordances between empirical and computational evidence from micro- and mesoscopic circuit studies in rodents to findings from macroscopic imaging in humans. Furthermore, we discuss the relevance and challenges for future cross-species research in addressing mutual context-dependent evaluation processes underpinning perceptual learning.

Identifying Neural Signatures of Dopamine Signaling with Machine Learning

The emergence of new tools to image neurotransmitters, neuromodulators, and neuropeptides has transformed our understanding of the role of neurochemistry in brain development and cognition, yet analysis of this new dimension of neurobiological information remains challenging. Here, we image dopamine modulation in striatal brain tissue slices with near infrared catecholamine nanosensors (nIRCat) and implement machine learning to determine which features of dopamine modulation are unique to changes in stimulation strength, and to different neuroanatomical regions. We trained a support vector machine and a random forest classifier to determine whether recordings were made from the dorsolateral striatum (DLS) versus the dorsomedial striatum (DMS) and find that machine learning is able to accurately distinguish dopamine release that occurs in DLS from that occurring in DMS in a manner unachievable with canonical statistical analysis. Furthermore, our analysis determines that dopamine modulatory signals including the number of unique dopamine release sites and peak dopamine released per stimulation event are most predictive of neuroanatomy yet note that integrated neuromodulator amount is the conventional metric currently used to monitor neuromodulation in animal studies. Lastly, our study finds that machine learning discrimination of different stimulation strengths or neuroanatomical regions is only possible in adult animals, suggesting a high degree of variability in dopamine modulatory kinetics during animal development. Our study highlights that machine learning could become a broadly-utilized tool to differentiate between neuroanatomical regions, or between neurotypical and disease states, with features not detectable by conventional statistical analysis.

Mesolimbic dopamine adapts the rate of learning from action

Recent success in training artificial agents and robots derives from a combination of direct learning of behavioural policies and indirect learning through value functions^1-3. Policy learning and value learning use distinct algorithms that optimize behavioural performance and reward prediction, respectively. In animals, behavioural learning and the role of mesolimbic dopamine signalling have been extensively evaluated with respect to reward prediction⁴; however, so far there has been little consideration of how direct policy learning might inform our understanding⁵. Here we used a comprehensive dataset of orofacial and body movements to understand how behavioural policies evolved as naive, head-restrained mice learned a trace conditioning paradigm. Individual differences in initial dopaminergic reward responses correlated with the emergence of learned behavioural policy, but not the emergence of putative value encoding for a predictive cue. Likewise, physiologically calibrated manipulations of mesolimbic dopamine produced several effects inconsistent with value learning but predicted by a neural-network-based model that used dopamine signals to set an adaptive rate, not an error signal, for behavioural policy learning. This work provides strong evidence that phasic dopamine activity can regulate direct learning of behavioural policies, expanding the explanatory power of reinforcement learning models for animal learning⁶.

Connectivity of the corticostriatal and thalamostriatal systems in normal and parkinsonian states: An update

The striatum receives abundant glutamatergic afferents from the cortex and thalamus. These inputs play a major role in the functions of the striatal neurons in normal conditions, and are significantly altered in pathological states, such as Parkinson's disease. This review summarizes the current knowledge of the connectivity of the corticostriatal and thalamostriatal pathways, with emphasis on the most recent advances in the field. We also discuss novel findings regarding structural changes in cortico- and thalamostriatal connections that occur in these connections as a consequence of striatal loss of dopamine in parkinsonism.

Nanomedicine in the Face of Parkinson's Disease: From Drug Delivery Systems to Nanozymes

The complexity and overall burden of Parkinson's disease (PD) require new pharmacological approaches to counteract the symptomatology while reducing the progressive neurodegeneration of affected dopaminergic neurons. Since the pathophysiological signature of PD is characterized by the loss of physiological levels of dopamine (DA) and the misfolding and aggregation of the alpha-synuclein (α-syn) protein, new proposals seek to restore the lost DA and inhibit the progressive damage derived from pathological α-syn and its impact in terms of oxidative stress. In this line, nanomedicine (the medical application of nanotechnology) has achieved significant advances in the development of nanocarriers capable of transporting and delivering basal state DA in a controlled manner in the tissues of interest, as well as highly selective catalytic nanostructures with enzyme-like properties for the elimination of reactive oxygen species (responsible for oxidative stress) and the proteolysis of misfolded proteins. Although some of these proposals remain in their early stages, the deepening of our knowledge concerning the pathological processes of PD and the advances in nanomedicine could endow for the development of potential treatments for this still incurable condition. Therefore, in this paper, we offer: (i) a brief summary of the most recent findings concerning the physiology of motor regulation and (ii) the molecular neuropathological processes associated with PD, together with (iii) a recapitulation of the current progress in controlled DA release by nanocarriers and (iv) the design of nanozymes, catalytic nanostructures with oxidoreductase-, chaperon, and protease-like properties. Finally, we conclude by describing the prospects and knowledge gaps to overcome and consider as research into nanotherapies for PD continues, especially when clinical translations take place.

Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo

Tonic extracellular neurotransmitter concentrations are important modulators of central network homeostasis. Disruptions in these tonic levels are thought to play a role in neurologic and psychiatric disease. Therefore, ways to improve their quantification are actively being investigated. Previously published voltammetric software packages have implemented FSCV, which is not capable of measuring tonic concentrations of neurotransmitters in vivo. In this paper, custom software was developed for near-real-time tracking (scans every 10 s) of neurotransmitters’ tonic concentrations with high sensitivity and spatiotemporal resolution both in vitro and in vivo using cyclic voltammetry combined with dynamic background subtraction (M-CSWV and FSCAV). This software was designed with flexibility, speed, and user-friendliness in mind. This software enables near-real-time measurement by reducing data analysis time through an optimized modeling algorithm, and efficient memory handling makes long-term measurement possible. The software permits customization of the cyclic voltammetric waveform shape, enabling experiments to detect a specific analyte of interest. Finally, flexibility considerations allow the user to alter the fitting parameters, filtering characteristics, and size and shape of the analyte kernel, based on data obtained live during the experiment to obtain accurate measurements as experimental conditions change. Herein, the design and advantages of this near-real-time voltammetric software are described, and its use is demonstrated in in vivo experiments.

Acute MPTP treatment decreases dendritic spine density of striatal Medium Spiny Neurons via SNK-SPAR pathway in C57BL/6 mice

Parkinson's disease (PD) is a well-known neurodegenerative disorder associated with a high risk in middle-aged and elderly individuals, severely impacting the patient's quality of life. 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is frequently used to establish PD in animals. Dendritic spines are dendritic processes that form the foundation of learning and memory. Reportedly, dendritic spine density of striatal medium spiny neurons (MSNs) declines in PD, and this decline has been associated with PD progression; however, the underlying mechanism remains elusive. Herein, we used the MPTP animal model to examine whether serum-induced kinase (SNK) and spine-associated Rap guanosine triphosphatase (SPAR) contribute to decreased dendritic spine density in striatal MSNs. MPTP was used to establish the animal model, which exhibits motor function impairment and dopaminergic cell loss. To assess spine density, Golgi staining was performed to count striatal dendritic spines, which were reduced in the MPTP group when compared with those in the normal control group. Immunohistochemistry was performed to analyze changes in SNK and SPAR expression. MPTP treatment significantly increased the expression of SNK in striatal MSNs, whereas that of SPAR was significantly decreased when compared with the normal control group. These findings offer clues to further explore the mechanism of declining dendritic spine density in patients with PD and provide evidence for potential target identification in PD. This article is protected by copyright. All rights reserved.

Differential Dopamine Receptor-Dependent Sensitivity Improves the Switch Between Hard and Soft Selection in a Model of the Basal Ganglia

The problem of selecting one action from a set of different possible actions, simply referred to as the problem of action selection, is a ubiquitous challenge in the animal world. For vertebrates, the basal ganglia (BG) are widely thought to implement the core computation to solve this problem, as its anatomy and physiology are well suited to this end. However, the BG still display physiological features whose role in achieving efficient action selection remains unclear. In particular, it is known that the two types of dopaminergic receptors (D1 and D2) present in the BG give rise to mechanistically different responses. The overall effect will be a difference in sensitivity to dopamine, which may have ramifications for action selection. However, which receptor type leads to a stronger response is unclear due to the complexity of the intracellular mechanisms involved. In this study, we use an existing, high-level computational model of the BG, which assumes that dopamine contributes to action selection by enabling a switch between different selection regimes, to predict which of D1 or D2 has the greater sensitivity. Thus, we ask, Assuming dopamine enables a switch between action selection regimes in the BG, what functional sensitivity values would result in improved action selection computation? To do this, we quantitatively assessed the model's capacity to perform action selection as we parametrically manipulated the sensitivity weights of D1 and D2. We show that differential (rather than equal) D1 and D2 sensitivity to dopaminergic input improves the switch between selection regimes during the action selection computation in our model. Specifically, greater D2 sensitivity compared to D1 led to these improvements.

A Multi-Scale Computational Model of Levodopa-Induced Toxicity in Parkinson's Disease

Parkinson's disease (PD) is caused by the progressive loss of dopaminergic cells in substantia nigra pars compacta (SNc). The root cause of this cell loss in PD is still not decisively elucidated. A recent line of thinking has traced the cause of PD neurodegeneration to metabolic deficiency. Levodopa (L-DOPA), a precursor of dopamine, used as a symptom-relieving treatment for PD, leads to positive and negative outcomes. Several researchers inferred that L-DOPA might be harmful to SNc cells due to oxidative stress. The role of L-DOPA in the course of the PD pathogenesis is still debatable. We hypothesize that energy deficiency can lead to L-DOPA-induced toxicity in two ways: by promoting dopamine-induced oxidative stress and by exacerbating excitotoxicity in SNc. We present a systems-level computational model of SNc-striatum, which will help us understand the mechanism behind neurodegeneration postulated above and provide insights into developing disease-modifying therapeutics. It was observed that SNc terminals are more vulnerable to energy deficiency than SNc somas. During L-DOPA therapy, it was observed that higher L-DOPA dosage results in increased loss of terminals in SNc. It was also observed that co-administration of L-DOPA and glutathione (antioxidant) evades L-DOPA-induced toxicity in SNc neurons. Our proposed model of the SNc-striatum system is the first of its kind, where SNc neurons were modeled at a biophysical level, and striatal neurons were modeled at a spiking level. We show that our proposed model was able to capture L-DOPA-induced toxicity in SNc, caused by energy deficiency.

Enhanced Dopamine Sensitivity Using Steered Fast-Scan Cyclic Voltammetry

Fast-scan cyclic voltammetry (FSCV) is a technique for measuring phasic release of neurotransmitters with millisecond temporal resolution. The current data are captured by carbon fiber microelectrodes, and non-Faradaic current is subtracted from the background current to extract the Faradaic redox current through a background subtraction algorithm. FSCV is able to measure neurotransmitter concentrations in vivo down to the nanomolar scale, making it a very robust and useful technique for probing neurotransmitter release dynamics and communication across neural networks. In this study, we describe a technique that can further lower the limit of detection of FSCV. By taking advantage of a "waveform steering" technique and by amplifying only the oxidation peak of dopamine to reduce noise fluctuations, we demonstrate the ability to measure dopamine concentrations down to 0.17 nM. Waveform steering is a technique to dynamically alter the input waveform to ensure that the background current remains stable over time. Specifically, the region of the input waveform in the vicinity of the dopamine oxidation potential (∼0.6 V) is kept flat. Thus, amplification of the input waveform will amplify only the Faradaic current, lowering the existing limit of detection for dopamine from 5.48 to 0.17 nM, a 32-fold reduction, and for serotonin, it lowers the limit of detection from 57.3 to 1.46 nM, a 39-fold reduction compared to conventional FSCV. Finally, the applicability of steered FSCV to in vivo dopamine detection was also demonstrated in this study. In conclusion, steered FSCV might be used as a neurochemical monitoring tool for enhancing detection sensitivity.

Calcium channels and iron metabolism: A redox catastrophe in Parkinson's disease and an innovative path to novel therapies?

Autonomously spiking dopaminergic neurons of the substantia nigra pars compacta (SNpc) are exquisitely specialized and suffer toxic iron-loading in Parkinson's disease (PD). However, the molecular mechanism involved remains unclear and critical to decipher for designing new PD therapeutics. The long-lasting (L-type) Ca_V1.3 voltage-gated calcium channel is expressed at high levels amongst nigral neurons of the SNpc, and due to its role in calcium and iron influx, could play a role in the pathogenesis of PD. Neuronal iron uptake via this route could be unregulated under the pathological setting of PD and potentiate cellular stress due to its redox activity. This Commentary will focus on the role of the Ca_V1.3 channels in calcium and iron uptake in the context of pharmacological targeting. Prospectively, the audacious use of artificial intelligence to design innovative Ca_V1.3 channel inhibitors could lead to breakthrough pharmaceuticals that attenuate calcium and iron entry to ameliorate PD pathology.

What Is the Role of Thalamostriatal Circuits in Learning Vocal Sequences?

Basal ganglia (BG) circuits integrate sensory and motor-related information from the cortex, thalamus, and midbrain to guide learning and production of motor sequences. Birdsong, like speech, is comprised of precisely sequenced vocal elements. Learning song sequences during development relies on Area X, a vocalization related region in the medial striatum of the songbird BG. Area X receives inputs from cortical-like pallial song circuits and midbrain dopaminergic circuits and sends projections to the thalamus. It has recently been shown that thalamic circuits also send substantial projections back to Area X. Here, we outline a gated-reinforcement learning model for how Area X may use signals conveyed by thalamostriatal inputs to direct song learning. Integrating conceptual advances from recent mammalian and songbird literature, we hypothesize that thalamostriatal pathways convey signals linked to song syllable onsets and offsets and influence striatal circuit plasticity via regulation of cholinergic interneurons (ChIs). We suggest that syllable sequence associated vocal-motor information from the thalamus drive precisely timed pauses in ChIs activity in Area X. When integrated with concurrent corticostriatal and dopaminergic input, this circuit helps regulate plasticity on medium spiny neurons (MSNs) and the learning of syllable sequences. We discuss new approaches that can be applied to test core ideas of this model and how associated insights may provide a framework for understanding the function of BG circuits in learning motor sequences.

Diverse midbrain dopaminergic neuron subtypes and implications for complex clinical symptoms of Parkinson's disease

Parkinson’s disease (PD), the most common degenerative movement disorder, is clinically manifested with various motor and non-motor symptoms. Degeneration of midbrain substantia nigra pas compacta (SNc) dopaminergic neurons (DANs) is generally attributed to the motor syndrome. The underlying neuronal mechanisms of non-motor syndrome are largely unexplored. Besides SNc, midbrain ventral tegmental area (VTA) DANs also produce and release dopamine and modulate movement, reward, motivation, and memory. Degeneration of VTA DANs also occurs in postmortem brains of PD patients, implying an involvement of VTA DANs in PD-associated non-motor symptoms. However, it remains to be established that there is a distinct segregation of different SNc and VTA DAN subtypes in regulating different motor and non-motor functions, and that different DAN subpopulations are differentially affected by normal ageing or PD. Traditionally, the distinction among different DAN subtypes was mainly based on the location of cell bodies and axon terminals. With the recent advance of single cell RNA sequencing technology, DANs can be readily classified based on unique gene expression profiles. A combination of specific anatomic and molecular markers shows great promise to facilitate the identification of DAN subpopulations corresponding to different behavior modules under normal and disease conditions. In this review, we first summarize the recent progress in characterizing genetically, anatomically, and functionally diverse midbrain DAN subtypes. Then, we provide perspectives on how the preclinical research on the connectivity and functionality of DAN subpopulations improves our current understanding of cell-type and circuit specific mechanisms of the disease, which could be critically informative for designing new mechanistic treatments.

Dopamine, vocalization, and astrocytes

Dopamine, the main catecholamine neurotransmitter in the brain, is predominately produced in the basal ganglia and released to various brain regions including the frontal cortex, midbrain and brainstem. Dopamine's effects are widespread and include modulation of a number of voluntary and innate behaviors. Vigilant regulation and modulation of dopamine levels throughout the brain is imperative for proper execution of motor behaviors, in particular speech and other types of vocalizations. While dopamine's role in motor circuitry is widely accepted, its unique function in normal and abnormal speech production is not fully understood. In this perspective, we first review the role of dopaminergic circuits in vocal production. We then discuss and propose the conceivable involvement of astrocytes, the numerous star-shaped glia cells of the brain, in the dopaminergic network modulating normal and abnormal vocal productions.

Alkyne-Tagged Dopamines as Versatile Analogue Probes for Dopaminergic System Analysis

The dopaminergic system is essential for the function of the brain in health and disease. Therefore, detailed studies focused on unraveling the mechanisms involved in dopaminergic signaling are required. However, the lack of probes that mimic dopamine in living tissues, owing to the neurotransmitter's small size, has hampered analysis of the dopaminergic system. The current study aimed to overcome this limitation by developing alkyne-tagged dopamine compounds (ATDAs) that have a minimally invasive and uniquely identifiable alkyne group as a tag. ATDAs were established as chemically and functionally similar to dopamine and readily detectable by methods such as specific click chemistry and Raman scattering. The ATDAs developed here were verified as analogue probes that mimic dopamine in neurons and brain tissues, allowing the detailed characterization of dopamine dynamics. Therefore, ATDAs can act as safe and versatile tools with wide applicability in detailed studies of the dopaminergic system. Furthermore, our results suggest that the alkyne-tagging approach can also be applied to other small-sized neurotransmitters to facilitate characterization of their dynamics in the brain.

Dopamine Transporter Is a Master Regulator of Dopaminergic Neural Network Connectivity

Dopaminergic neurons of the substantia nigra pars compacta (SNC) and ventral tegmental area (VTA) exhibit spontaneous firing activity. The dopaminergic neurons in these regions have been shown to exhibit differential sensitivity to neuronal loss and psychostimulants targeting dopamine transporter. However, it remains unclear whether these regional differences scale beyond individual neuronal activity to regional neuronal networks. Here, we used live-cell calcium imaging to show that network connectivity greatly differs between SNC and VTA regions with higher incidence of hub-like neurons in the VTA. Specifically, the frequency of hub-like neurons was significantly lower in SNC than in the adjacent VTA, consistent with the interpretation of a lower network resilience to SNC neuronal loss. We tested this hypothesis, in DAT-cre/loxP-GCaMP6f mice of either sex, when activity of an individual dopaminergic neuron is suppressed, through whole-cell patch clamp electrophysiology, in either SNC or VTA networks. Neuronal loss in the SNC increased network clustering, whereas the larger number of hub-neurons in the VTA overcompensated by decreasing network clustering in the VTA. We further show that network properties are regulatable via a dopamine transporter but not a D2 receptor dependent mechanism. Our results demonstrate novel regulatory mechanisms of functional network topology in dopaminergic brain regions.SIGNIFICANCE STATEMENT In this work, we begin to untangle the differences in complex network properties between the substantia nigra pars compacta (SNC) and VTA, that may underlie differential sensitivity between regions. The methods and analysis employed provide a springboard for investigations of network topology in multiple deep brain structures and disorders.

In trans neuregulin3-Caspr3 interaction controls DA axonal bassoon cluster development

Dopamine (DA) transmission is critical to motivation, movement, and emotion. Unlike glutamatergic and GABAergic synapses, the development of DA synapses is less understood. We show that bassoon (BSN) clusters along DA axons in the core of nucleus accumbens (NAcc) were increased in neonatal stages and reduced afterward, suggesting DA synapse elimination. Remarkably, DA neuron-specific ablating neuregulin 3 (NRG3), a protein whose levels correlate with BSN clusters, increased the clusters and impaired DA release and behaviors related to DA transmission. An unbiased screen of transmembrane proteins with the extracellular domain (ECD) of NRG3 identified Caspr3 (contactin associate-like protein 3) as a binding partner. Caspr3 was enriched in striatal medium spiny neurons (MSNs). NRG3 and Caspr3 interact in trans, which was blocked by Caspr3-ECD. Caspr3 null mice displayed phenotypes similar to those in DAT-Nrg3^f/f mice in DA axonal BSN clusters and DA transmission. Finally, in vivo disruption of the NRG3-Caspr3 interaction increased BSN clusters. Together, these results demonstrate that DA synapse development is controlled by trans interaction between NRG3 in DA neurons and Caspr3 in MSNs, identifying a novel pair of cell adhesion molecules for brain circuit wiring.

Nanowire-Enabled Bioelectronics

Bioelectronics explores the use of electronic devices for applications in signal transduction at their interfaces with biological systems. The miniaturization of the bioelectronic systems has enabled seamless integration at these interfaces and is providing new scientific and technological opportunities. In particular, nanowire-based devices can yield smaller sized and unique geometry detectors that are difficult to access with standard techniques, and thereby can provide advantages in sensitivity with reduced invasiveness. In this review, we focus on nanowire-enabled bioelectronics. First, we provide an overview of synthetic studies for designed growth of semiconductor nanowires of which structure and composition are controlled to enable key elements for bioelectronic devices. Second, we review nanowire field-effect transistor sensors for highly sensitive detection of biomolecules, their applications in diagnosis and drug discovery, and methods for sensitivity enhancement. We then turn to recent progress in nanowire-enabled studies of electrogenic cells, including cardiomyocytes and neurons. Representative advances in electrical recording using nanowire electronic devices for single cell measurements, cell network mapping, and three-dimensional recordings of synthetic and natural tissues, and in vivo brain mapping are highlighted. Finally, we overview the key challenges and opportunities of nanowires for fundamental research and translational applications.

Spatial and temporal scales of dopamine transmission

Dopamine is a prototypical neuromodulator that controls circuit function through G protein-coupled receptor signalling. Neuromodulators are volume transmitters, with release followed by diffusion for widespread receptor activation on many target cells. Yet, we are only beginning to understand the specific organization of dopamine transmission in space and time. Although some roles of dopamine are mediated by slow and diffuse signalling, recent studies suggest that certain dopamine functions necessitate spatiotemporal precision. Here, we review the literature describing dopamine signalling in the striatum, including its release mechanisms and receptor organization. We then propose the domain-overlap model, in which release and receptors are arranged relative to one another in micrometre-scale structures. This architecture is different from both point-to-point synaptic transmission and the widespread organization that is often proposed for neuromodulation. It enables the activation of receptor subsets that are within micrometre-scale domains of release sites during baseline activity and broader receptor activation with domain overlap when firing is synchronized across dopamine neuron populations. This signalling structure, together with the properties of dopamine release, may explain how switches in firing modes support broad and dynamic roles for dopamine and may lead to distinct pathway modulation.

Parkinson's disease: Alterations in iron and redox biology as a key to unlock therapeutic strategies

A plethora of studies indicate that iron metabolism is dysregulated in Parkinson's disease (PD). The literature reveals well-documented alterations consistent with established dogma, but also intriguing paradoxical observations requiring mechanistic dissection. An important fact is the iron loading in dopaminergic neurons of the substantia nigra pars compacta (SNpc), which are the cells primarily affected in PD. Assessment of these changes reveal increased expression of proteins critical for iron uptake, namely transferrin receptor 1 and the divalent metal transporter 1 (DMT1), and decreased expression of the iron exporter, ferroportin-1 (FPN1). Consistent with this is the activation of iron regulator protein (IRP) RNA-binding activity, which is an important regulator of iron homeostasis, with its activation indicating cytosolic iron deficiency. In fact, IRPs bind to iron-responsive elements (IREs) in the 3ꞌ untranslated region (UTR) of certain mRNAs to stabilize their half-life, while binding to the 5ꞌ UTR prevents translation. Iron loading of dopaminergic neurons in PD may occur through these mechanisms, leading to increased neuronal iron and iron-mediated reactive oxygen species (ROS) generation. The "gold standard" histological marker of PD, Lewy bodies, are mainly composed of α-synuclein, the expression of which is markedly increased in PD. Of note, an atypical IRE exists in the α-synuclein 5ꞌ UTR that may explain its up-regulation by increased iron. This dysregulation could be impacted by the unique autonomous pacemaking of dopaminergic neurons of the SNpc that engages L-type Ca+2 channels, which imparts a bioenergetic energy deficit and mitochondrial redox stress. This dysfunction could then drive alterations in iron trafficking that attempt to rescue energy deficits such as the increased iron uptake to provide iron for key electron transport proteins. Considering the increased iron-loading in PD brains, therapies utilizing limited iron chelation have shown success. Greater therapeutic advancements should be possible once the exact molecular pathways of iron processing are dissected.

Single Exposure to Cocaine Impairs Reinforcement Learning by Potentiating the Activity of Neurons in the Direct Striatal Pathway in Mice

Plasticity in the glutamatergic synapses on striatal medium spiny neurons (MSNs) is not only essential for behavioral adaptation but also extremely vulnerable to drugs of abuse. Modulation on these synapses by even a single exposure to an addictive drug may interfere with the plasticity required by behavioral learning and thus produce impairment. In the present work, we found that the negative reinforcement learning, escaping mild foot-shocks by correct nose-poking, was impaired by a single in vivo exposure to 20 mg/kg cocaine 24 h before the learning in mice. Either a single exposure to cocaine or reinforcement learning potentiates the glutamatergic synapses on MSNs expressing the striatal dopamine 1 (D1) receptor (D1-MSNs). However, 24 h after the cocaine exposure, the potentiation required for reinforcement learning was disrupted. Specific manipulation of the activity of striatal D1-MSNs in D1-cre mice demonstrated that activation of these MSNs impaired reinforcement learning in normal D1-cre mice, but inhibition of these neurons reversed the reinforcement learning impairment induced by cocaine. The results suggest that cocaine potentiates the activity of direct pathway neurons in the dorsomedial striatum and this potentiation might disrupt the potentiation produced during and required for reinforcement learning.

Axonal Modulation of Striatal Dopamine Release by Local γ-Aminobutyric Acid (GABA) Signalling

Striatal dopamine (DA) release is critical for motivated actions and reinforcement learning, and is locally influenced at the level of DA axons by other striatal neurotransmitters. Here, we review a wealth of historical and more recently refined evidence indicating that DA output is inhibited by striatal γ-aminobutyric acid (GABA) acting via GABAA and GABAB receptors. We review evidence supporting the localisation of GABAA and GABAB receptors to DA axons, as well as the identity of the striatal sources of GABA that likely contribute to GABAergic modulation of DA release. We discuss emerging data outlining the mechanisms through which GABAA and GABAB receptors inhibit the amplitude as well as modulate the short-term plasticity of DA release. Furthermore, we highlight recent data showing that DA release is governed by plasma membrane GABA uptake transporters on striatal astrocytes, which determine ambient striatal GABA tone and, by extension, the tonic inhibition of DA release. Finally, we discuss how the regulation of striatal GABA-DA interactions represents an axis for dysfunction in psychomotor disorders associated with dysregulated DA signalling, including Parkinson's disease, and could be a novel therapeutic target for drugs to modify striatal DA output.

Dynamic control of the dopamine transporter in neurotransmission and homeostasis

The dopamine transporter (DAT) transports extracellular dopamine into the intracellular space contributing to the regulation of dopamine neurotransmission. A reduction of DAT density is implicated in Parkinson's disease (PD) by neuroimaging; dopamine turnover is dopamine turnover is elevated in early symptomatic PD and in presymptomatic individuals with monogenic mutations causal for parkinsonism. As an integral plasma membrane protein, DAT surface expression is dynamically regulated through endocytic trafficking, enabling flexible control of dopamine signaling in time and space, which in turn critically modulates movement, motivation and learning behavior. Yet the cellular machinery and functional implications of DAT trafficking remain enigmatic. In this review we summarize mechanisms governing DAT trafficking under normal physiological conditions and discuss how PD-linked mutations may disturb DAT homeostasis. We highlight the complexity of DAT trafficking and reveal DAT dysregulation as a common theme in genetic models of parkinsonism.

PDE10A Inhibitors-Clinical Failure or Window Into Antipsychotic Drug Action?

PDE10A, a phosphodiesterase that inactivates both cAMP and cGMP, is a unique signaling molecule in being highly and nearly exclusively expressed in striatal medium spiny neurons. These neurons dynamically integrate cortical information with dopamine-signaled value to mediate action selection among available behavioral options. Medium spiny neurons are components of either the direct or indirect striatal output pathways. Selective activation of indirect pathway medium spiny neurons by dopamine D2 receptor antagonists is putatively a key element in the mechanism of their antipsychotic efficacy. While PDE10A is expressed in all medium spiny neurons, studies in rodents indicated that PDE10A inhibition has behavioral effects in several key assays that phenocopy dopamine D2 receptor inhibition. This finding gave rise to the hypothesis that PDE10A inhibition also preferentially activates indirect pathway medium spiny neurons, a hypothesis that is consistent with electrophysiological, neurochemical, and molecular effects of PDE10A inhibitors. These data underwrote industry-wide efforts to investigate and develop PDE10A inhibitors as novel antipsychotics. Disappointingly, PDE10A inhibitors from 3 companies failed to evidence antipsychotic activity in patients with schizophrenia to the same extent as standard-of-care D2 antagonists. Given the notable similarities between PDE10A inhibitors and D2 antagonists, gaining an understanding of why only the latter class is antipsychotic affords a unique window into the basis for this therapeutic efficacy. With this in mind, we review the data on PDE10A inhibition as a step toward back-translating the limited antipsychotic efficacy of PDE10A inhibitors, hopefully to inform new efforts to develop better therapeutics to treat psychosis and schizophrenia.

An Integrated Model of Nature and Nurture Factors that Contribute to Addiction and Recovery

BACKGROUND

In the context of the opioid epidemic and growing awareness of addiction as a public health concern, there are efforts to inform the public, patients, families, and policy makers about the factors that contribute to addiction and facilitate recovery. Several theoretical models provide useful frameworks for this discussion, but each of them has limitations.

OBJECTIVES

This paper presents an accessible yet comprehensive theoretical model that integrates empirical evidence about addiction etiology and recovery using the nature-nurture paradigm.

RESULTS

The model presents substance use along a continuum, and identifies risk and protective factors in multiple domains that have been identified by research. The domains on the nature side of the model include genetic and biological factors, comorbid psychiatric and medical disorders, physiological reinforcement of substance use, and changes to neural mechanisms. The domains on the nurture side of the model include sociocultural factors, environmental factors, personality, emotions, cognitions, psychological reinforcement of substance use, and cognitive and behavioral changes. The progression from increased or decreased substance use to addiction or recovery is mediated by changes in neural mechanisms and cognitive and behavioral changes, which have feedback loops with the physiological and psychological reinforcement.Conclusions/Importance: This model is a useful heuristic, consistent with a public health framework, for discussing addiction and recovery with patients, their families, and the public. This integrated model of nature and nurture factors has the potential to inform clinical practice, consultation, research, prevention programs, educational programs, and public policy.

Dopaminergic denervation impairs cortical motor and associative/limbic information processing through the basal ganglia and its modulation by the CB1 receptor

The basal ganglia (BG) are involved in cognitive/motivational functions in addition to movement control. Thus, BG segregated circuits, the sensorimotor (SM) and medial prefrontal (mPF) circuits, process different functional domains, such as motor and cognitive/motivational behaviours, respectively. With a high presence in the BG, the CB1 cannabinoid receptor modulates BG circuits. Furthermore, dopamine (DA), one of the principal neurotransmitters in the BG, also plays a key role in circuit functionality. Taking into account the interaction between DA and the endocannabinoid system at the BG level, we investigated the functioning of BG circuits and their modulation by the CB1 receptor under DA-depleted conditions. We performed single-unit extracellular recordings of substantia nigra pars reticulata (SNr) neurons with simultaneous cortical stimulation in sham and 6-hydroxydopamine (6-OHDA)-lesioned rats, together with immunohistochemical assays. We showed that DA loss alters cortico-nigral information processing in both circuits, with a predominant transmission through the hyperdirect pathway in the SM circuit and an increased transmission through the direct pathway in the mPF circuit. Moreover, although DA denervation does not change CB1 receptor density, it impairs its functionality, leading to a lack of modulation. These data highlight an abnormal transfer of information through the associative/limbic domains after DA denervation that may be related to the non-motor symptoms manifested by Parkinson's disease patients.

A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder caused by loss of dopaminergic neurons in substantia nigra pars compacta (SNc). Although the exact cause of cell death is not clear, the hypothesis that metabolic deficiency is a key factor has been gaining attention in recent years. In the present study, we investigated this hypothesis using a multi-scale computational model of the subsystem of the basal ganglia comprising the subthalamic nucleus (STN), globus pallidus externa (GPe), and SNc. The proposed model is a multiscale model in that interaction among the three nuclei are simulated using more abstract Izhikevich neuron models, while the molecular pathways involved in cell death of SNc neurons are simulated in terms of detailed chemical kinetics. Simulation results obtained from the proposed model showed that energy deficiencies occurring at cellular and network levels could precipitate the excitotoxic loss of SNc neurons in PD. At the subcellular level, the models show how calcium elevation leads to apoptosis of SNc neurons. The therapeutic effects of several neuroprotective interventions are also simulated in the model. From neuroprotective studies, it was clear that glutamate inhibition and apoptotic signal blocker therapies were able to halt the progression of SNc cell loss when compared to other therapeutic interventions, which only slowed down the progression of SNc cell loss.

Calcium, Bioenergetics, and Parkinson's Disease

Degeneration of substantia nigra (SN) dopaminergic (DAergic) neurons is responsible for the core motor deficits of Parkinson’s disease (PD). These neurons are autonomous pacemakers that have large cytosolic Ca²⁺ oscillations that have been linked to basal mitochondrial oxidant stress and turnover. This review explores the origin of Ca²⁺ oscillations and their role in the control of mitochondrial respiration, bioenergetics, and mitochondrial oxidant stress.

Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity

Animals remember temporal links between their actions and subsequent rewards. We previously discovered a synaptic mechanism underlying such reward learning in D1 receptor (D1R)-expressing spiny projection neurons (D1 SPN) of the striatum. Dopamine (DA) bursts promote dendritic spine enlargement in a time window of only a few seconds after paired pre- and post-synaptic spiking (pre-post pairing), which is termed as reinforcement plasticity (RP). The previous study has also identified underlying signaling pathways; however, it still remains unclear how the signaling dynamics results in RP. In the present study, we first developed a computational model of signaling dynamics of D1 SPNs. The D1 RP model successfully reproduced experimentally observed protein kinase A (PKA) activity, including its critical time window. In this model, adenylate cyclase type 1 (AC1) in the spines/thin dendrites played a pivotal role as a coincidence detector against pre-post pairing and DA burst. In particular, pre-post pairing (Ca2+ signal) stimulated AC1 with a delay, and the Ca2+-stimulated AC1 was activated by the DA burst for the asymmetric time window. Moreover, the smallness of the spines/thin dendrites is crucial to the short time window for the PKA activity. We then developed a RP model for D2 SPNs, which also predicted the critical time window for RP that depended on the timing of pre-post pairing and phasic DA dip. AC1 worked for the coincidence detector in the D2 RP model as well. We further simulated the signaling pathway leading to Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation and clarified the role of the downstream molecules of AC1 as the integrators that turn transient input signals into persistent spine enlargement. Finally, we discuss how such timing windows guide animals' reward learning.

Needle-type organic electrochemical transistor for spatially resolved detection of dopamine

In this work, the advantages of carbon nanoelectrodes (CNEs) and orgonic electrochemical transistors (OECTs) were merged to realise nanometre-sized, spearhead OECTs based on single- and double-barrel CNEs functionalised with a conducting polymer film. The needle-type OECT shows a high aspect ratio that allows its precise positioning by means of a macroscopic handle and its size is compatible with single-cell analysis. The device was characterised with respect to its electrolyte-gated behaviour and was employed as electrochemical sensor for the proof-of-concept detection of dopamine (DA) over a wide concentration range (10^-12-10^-6 M). Upon application of fixed drain and gate voltages (V_d = - 0.3 V, V_g = - 0.9 V, respectively), the nano-sized needle-type OECT sensor exhibited a linear response in the low pM range and from 0.002 to 7 μM DA, with a detection limit of 1 × 10^-12 M. Graphical abstract.

Selective neuronal vulnerability in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease, disabling millions worldwide. Despite the imperative PD poses, at present, there is no cure or means of slowing progression. This gap is attributable to our incomplete understanding of the factors driving pathogenesis. Research over the past several decades suggests that both cell-autonomous and non-cell autonomous processes contribute to the neuronal dysfunction underlying PD symptoms. The thesis of this review is that an intersection of these processes governs the pattern of pathology in PD. Studies of substantia nigra pars compacta (SNc) dopaminergic neurons, whose loss is responsible for the core motor symptoms of PD, suggest that they have a combination of traits-a long, highly branched axon, autonomous activity, and elevated mitochondrial oxidant stress-that predispose them to non-cell autonomous drivers of pathogenesis, like misfolded forms of alpha-synuclein (α-SYN) and inflammation. The literature surrounding these issues will be briefly summarized, and the translational implications of an intersectional hypothesis of PD pathogenesis discussed.

Dynamic resource allocation during reinforcement learning accounts for ramping and phasic dopamine activity

For an animal to learn about its environment with limited motor and cognitive resources, it should focus its resources on potentially important stimuli. However, too narrow focus is disadvantageous for adaptation to environmental changes. Midbrain dopamine neurons are excited by potentially important stimuli, such as reward-predicting or novel stimuli, and allocate resources to these stimuli by modulating how an animal approaches, exploits, explores, and attends. The current study examined the theoretical possibility that dopamine activity reflects the dynamic allocation of resources for learning. Dopamine activity may transition between two patterns: (1) phasic responses to cues and rewards, and (2) ramping activity arising as the agent approaches the reward. Phasic excitation has been explained by prediction errors generated by experimentally inserted cues. However, when and why dopamine activity transitions between the two patterns remain unknown. By parsimoniously modifying a standard temporal difference (TD) learning model to accommodate a mixed presentation of both experimental and environmental stimuli, we simulated dopamine transitions and compared them with experimental data from four different studies. The results suggested that dopamine transitions from ramping to phasic patterns as the agent focuses its resources on a small number of reward-predicting stimuli, thus leading to task dimensionality reduction. The opposite occurs when the agent re-distributes its resources to adapt to environmental changes, resulting in task dimensionality expansion. This research elucidates the role of dopamine in a broader context, providing a potential explanation for the diverse repertoire of dopamine activity that cannot be explained solely by prediction error.

Learned avoidance requires VTA KOR-mediated reductions in dopamine

Proper learning from an aversive experience is essential for survival, yet it is an aberrant process in a wide range of mental disorders, as well as dopaminergic neurodegenerative disease. While the mesolimbic dopamine system is known to be essential for reward learning, the characterization of a potential pattern of dopamine signaling that guides avoidance remains unknown. Aversive stimuli may directly modulate dopamine signaling through the dynorphin/kappa opioid receptor (KOR) system, as kappa opioid receptors are expressed in this neural circuit and their activation is aversive in both rodents and humans. Ventral tegmental area (VTA) KORs are ideally positioned to directly shape aversion-induced reductions in dopamine signaling, but their role in this process has received little consideration. To determine the necessity of VTA KOR activity in the regulation of dopamine signaling and avoidance, we tested the effects of VTA KOR blockade on real time dopaminergic responses to aversive stimuli and learned avoidance in male Sprague-Dawley rats. We found that blockade of VTA KORs attenuated aversion-induced reductions in dopamine, and this treatment also prevented avoidance following the aversive experience. To determine whether aversion-induced reductions in striatal dopamine are necessary for avoidance, we tested avoidance following treatment with an intra nucleus accumbens D2 receptor agonist. This treatment also prevented avoidance and is consistent with the view that aversion-induced reductions in dopamine reduce dopamine signaling at high affinity D2 receptors and disinhibit an aversion-sensitive striatal output circuit to promote avoidance.

Dystonia: Sparse Synapses for D2 Receptors in Striatum of a DYT1 Knock-out Mouse Model

Dystonia pathophysiology has been partly linked to downregulation and dysfunction of dopamine D2 receptors in striatum. We aimed to investigate the possible morpho-structural correlates of D2 receptor downregulation in the striatum of a DYT1 Tor1a mouse model. Adult control Tor1a+/+ and mutant Tor1a+/− mice were used. The brains were perfused and free-floating sections of basal ganglia were incubated with polyclonal anti-D2 antibody, followed by secondary immune-fluorescent antibody. Confocal microscopy was used to detect immune-fluorescent signals. The same primary antibody was used to evaluate D2 receptor expression by western blot. The D2 receptor immune-fluorescence appeared circumscribed in small disks (~0.3–0.5 µm diameter), likely representing D2 synapse aggregates, densely distributed in the striatum of Tor1a+/+ mice. In the Tor1a+/− mice the D2 aggregates were significantly smaller (µm² 2.4 ± SE 0.16, compared to µm² 6.73 ± SE 3.41 in Tor1a+/+) and sparse, with ~30% less number per microscopic field, value correspondent to the amount of reduced D2 expression in western blotting analysis. In DYT1 mutant mice the sparse and small D2 synapses in the striatum may be insufficient to “gate” the amount of presynaptic dopamine release diffusing in peri-synaptic space, and this consequently may result in a timing and spatially larger nonselective sphere of influence of dopamine action.

Transient and sustained effects of dopamine and serotonin signaling in motivation-related behavior

Pharmacological studies of antidepressants and atypical antipsychotics have suggested a role of dopamine and serotonin signaling in depression. However, depressive symptoms and treatment effects are difficult to explain based simply on brain-wide decrease or increase in the concentrations of these molecules. Recent animal studies using advanced neuronal manipulation and observation techniques have revealed detailed dopamine and serotonin dynamics that regulate diverse aspects of motivation-related behavior. Dopamine and serotonin transiently modulate moment-to-moment behavior at timescales ranging from sub-second to minutes and also produce persistent effects, such as reward-related learning and stress responses that last longer than several days. Transient and sustained effects often exhibit specific roles depending on the projection sites, where distinct synaptic and cellular mechanisms are required to process the neurotransmitters for each transient and sustained timescale. Therefore, it appears that specific aspects of motivation-related behavior are regulated by distinct synaptic and cellular mechanisms in specific brain regions that underlie the transient and sustained effects of dopamine and serotonin signaling. Recent clinical studies have implied that subjects with depressive symptoms show impaired transient and sustained signaling functions; moreover, they exhibit heterogeneity in depressive symptoms and neuronal dysfunction. Depressive symptoms may be explained by the dysfunction of each transient and sustained signaling mechanism, and distinct patterns of impairment in the relevant mechanisms may explain the heterogeneity of symptoms. Thus, detailed understanding of dopamine and serotonin signaling may provide new insight into depressive symptoms.

Dynamic control of neurochemical release with ultrasonically-sensitive nanoshell-tethered liposomes

The unique surface plasmon resonance of hollow gold nanoshells can be used to achieve drug release from liposomes upon laser stimulation, and adapted to mimic the intricate dynamics of neurotransmission ex vivo in brain preparations. However, to induce a physiological response in vivo requires the degree of temporal precision afforded by laser stimulation, but with a greater depth of penetration through tissue. Here we report that the attachment of hollow gold nanoshells to the surface of robust liposomes results in a construct that is highly sensitive to ultrasonic stimulation. The resulting construct can be remotely triggered by low intensity, therapeutic ultrasound. To our knowledge, this is the first example of nanoparticle-liposome system that can be activated by both laser and acoustic stimulation. The system is capable of encapsulating the neurochemical dopamine, and repeatedly releasing small amounts on-demand in a circulating environment, allowing for precise spatiotemporal control over the release profile.

Altered monoamine levels in the dorsal striatum of the rat are associated with alterations in behavioural selection and motivation following peripheral nerve injury and acute stress

Chronic neuropathic pain and psychological stress interact to compromise goal-directed control over behaviour following mild psychological stress. The dorsomedial (DMS) and dorsolateral (DLS) striatum in the rat are crucial for the expression of goal-directed and habitual behaviours, respectively. This study investigated whether changes in monoamine levels in the DMS and DLS following nerve injury and psychological stress reflect these behavioural differences. Neuropathic pain was induced by a chronic constriction injury (CCI) of the sciatic nerve in Sprague-Dawley rats. Acute stress was induced using a 15-min restraint. Behavioural flexibility was assessed using the outcome devaluation paradigm. Noradrenaline, serotonin, dopamine and associated metabolites were measured bilaterally from the DLS and DMS. In uninjured rats, restraint increased dopaminergic markers in the left and serotonergic markers in the right of both the DMS and DLS, indicating a possible left hemisphere-mediated dominance. CCI led to a slightly different lateralised effect, with a larger effect in the DMS than in the DLS. Individual differences in behavioural flexibility following CCI negatively correlated with dopaminergic markers in the right DLS, but positively correlated with these markers in the left DMS. A combination of CCI and restraint reduced behavioural flexibility, which was associated with the loss of the left/DMS dominance. These data suggest that behavioural flexibility following psychological stress or pain is associated with a left hemisphere dominance within the dorsal striatum. The loss of behavioural flexibility following the combined stressors is then associated with a transition from left to right, and DMS to DLS dominance.

Dementia associated with disorders of the basal ganglia

Dementia is now the leading cause of death in the United Kingdom, accounting for over 12% of all deaths and is the fifth most common cause of death worldwide. As treatments for heart disease and cancers improve and the population ages, the number of sufferers will only increase, with the chance of developing dementia doubling every 5 years after the age of 65. Finding an effective treatment is ever more critical to avert this pandemic health (and economic) crisis. To date, most dementia-related research has focused on the cortex and the hippocampus; however, with dementia becoming more fully recognized as aspects of diseases historically categorized as motor disorders (e.g., Parkinson's and Huntington's diseases), the role of the basal ganglia in dementia is coming to the fore. Conversely, it is highly likely that neuronal pathways in these structures traditionally considered as spared in Alzheimer's disease are also affected, particularly in later stages of the disease. In this review, we examine some of the limited evidence linking the basal ganglia to dementia.