Time-dependent assessment of stimulus-evoked regional dopamine release

Effects of deep brain stimulation on dopamine D2 receptor binding in patients with treatment-refractory depression

BACKGROUND

Depression is a chronic psychiatric disorder related to diminished dopaminergic neurotransmission. Deep brain stimulation (DBS) has shown effectiveness in treating patients with treatment-refractory depression (TRD). This study aimed to evaluate the effect of DBS on dopamine D2 receptor binding in patients with TRD.

METHODS

Six patients with TRD were treated with bed nucleus of the stria terminalis (BNST)-nucleus accumbens (NAc) DBS were recruited. Ultra-high sensitivity [11C]raclopride dynamic total-body positron emission tomography (PET) imaging was used to assess the brain D2 receptor binding. Each patient underwent a [11C]raclopride PET scan for 60-min under DBS OFF and DBS ON, respectively. A simplified reference tissue model was used to generate parametric images of binding potential (BPND) with the cerebellum as reference tissue.

RESULTS

Depression and anxiety symptoms improved after 3-6 months of DBS treatment. Compared with two-day-nonstimulated conditions, one-day BNST-NAc DBS decreased [11C]raclopride BPND in the amygdala (15.9 %, p < 0.01), caudate nucleus (15.4 %, p < 0.0001) and substantia nigra (10.8 %, p < 0.01).

LIMITATIONS

This study was limited to the small sample size and lack of a healthy control group.

CONCLUSIONS

Chronic BNST-NAc DBS improved depression and anxiety symptoms, and short-term stimulation decreased D2 receptor binding in the amygdala, caudate nucleus, and substantia nigra. The findings suggest that DBS relieves depression and anxiety symptoms possibly by regulating the dopaminergic system.

Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release

Existing methods for voxelwise transient dopamine (DA) release detection rely on explicit kinetic modeling of the [11C]raclopride PET time activity curve, which at the voxel level is typically confounded by noise, leading to poor performance for detection of low-amplitude DA release-induced signals. Here we present a novel data-driven, task-informed method-referred to as Residual Space Detection (RSD)-that transforms PET time activity curves to a residual space where DA release-induced perturbations can be isolated and processed. Using simulations, we demonstrate that this method significantly increases detection performance compared to existing kinetic model-based methods for low-magnitude DA release (simulated +100% peak increase in basal DA concentration). In addition, results from nine healthy controls injected with a single bolus of [11C]raclopride performing a finger tapping motor task are shown as proof-of-concept. The ability to detect relatively low magnitudes of dopamine release in the human brain using a single bolus injection, while achieving higher statistical power than previous methods, may additionally enable more complex analyses of neurotransmitter systems. Moreover, RSD is readily generalizable to multiple tasks performed during a single PET scan, further extending the capabilities of task-based single-bolus protocols.

Deep brain stimulation by blood-brain-barrier-crossing piezoelectric nanoparticles generating current and nitric oxide under focused ultrasound

Deep brain stimulation via implanted electrodes can alleviate neuronal disorders. However, its applicability is constrained by side effects resulting from the insertion of electrodes into the brain. Here, we show that systemically administered piezoelectric nanoparticles producing nitric oxide and generating direct current under high-intensity focused ultrasound can be used to stimulate deep tissue in the brain. The release of nitric oxide temporarily disrupted tight junctions in the blood-brain barrier, allowing for the accumulation of the nanoparticles into brain parenchyma, and the piezoelectrically induced output current stimulated the release of dopamine by dopaminergic neuron-like cells. In a mouse model of Parkinson's disease, the ultrasound-responsive nanoparticles alleviated the symptoms of the disease without causing overt toxicity. The strategy may inspire the development of other minimally invasive therapies for neurodegenerative diseases.

Longitudinal Dopamine D2 Receptor Changes and Cerebrovascular Health in Aging

BACKGROUND AND OBJECTIVES

Cross-sectional studies suggest marked dopamine (DA) decline in aging, but longitudinal evidence is lacking. The aim of this study was to estimate within-person decline rates for DA D2-like receptors (DRD2) in aging and examine factors that may contribute to individual differences in DRD2 decline rates.

METHODS

We investigated 5-year within-person changes in DRD2 availability in a sample of older adults. At both occasions, PET with 11C-raclopride and MRI were used to measure DRD2 availability in conjunction with structural and vascular brain integrity.

RESULTS

Longitudinal analyses of the sample (baseline: n = 181, ages: 64-68 years, 100 men and 81 women; 5-year follow-up: n = 129, 69 men and 60 women) revealed aging-related striatal and extrastriatal DRD2 decline, along with marked individual differences in rates of change. Notably, the magnitude of striatal DRD2 decline was ∼50% of past cross-sectional estimates, suggesting that the DRD2 decline rate has been overestimated in past cross-sectional studies. Significant DRD2 reductions were also observed in select extrastriatal regions, including hippocampus, orbitofrontal cortex (OFC), and anterior cingulate cortex (ACC). Distinct profiles of correlated DRD2 changes were found across several associative regions (ACC, dorsal striatum, and hippocampus) and in the reward circuit (nucleus accumbens and OFC). DRD2 losses in associative regions were associated with white matter lesion progression, whereas DRD2 losses in limbic regions were related to reduced cortical perfusion.

DISCUSSION

These findings provide the first longitudinal evidence for individual and region-specific differences of DRD2 decline in older age and support the hypothesis that cerebrovascular factors are linked to age-related dopaminergic decline.

Cortical D1 and D2 dopamine receptor availability modulate methylphenidate-induced changes in brain activity and functional connectivity

Dopamine signaling plays a critical role in shaping brain functional network organization and behavior. Prominent theories suggest the relative expression of D1- to D2-like dopamine receptors shapes excitatory versus inhibitory signaling, with broad consequences for cognition. Yet it remains unknown how the balance between cortical D1R versus D2R signaling coordinates the activity and connectivity of functional networks in the human brain. To address this, we collected three PET scans and two fMRI scans in 36 healthy adults (13 female/23 male; average age 43 ± 12 years), including a baseline D1R PET scan and two sets of D2R PET scans and fMRI scans following administration of either 60 mg oral methylphenidate or placebo (two separate days, blinded, order counterbalanced). The drug challenge allowed us to assess how pharmacologically boosting dopamine levels alters network organization and behavior in association with D1R-D2R ratios across the brain. We found that the relative D1R-D2R ratio was significantly greater in high-level association cortices than in sensorimotor cortices. After stimulation with methylphenidate compared to placebo, brain activity (as indexed by the fractional amplitude of low frequency fluctuations) increased in association cortices and decreased in sensorimotor cortices. Further, within-network resting state functional connectivity strength decreased more in sensorimotor than association cortices following methylphenidate. Finally, in association but not sensorimotor cortices, the relative D1R-D2R ratio (but not the relative availability of D1R or D2R alone) was positively correlated with spatial working memory performance, and negatively correlated with age. Together, these data provide a framework for how dopamine-boosting drugs like methylphenidate alter brain function, whereby regions with relatively higher inhibitory D2R (i.e., sensorimotor cortices) tend to have greater decreases in brain activity and connectivity compared to regions with relatively higher excitatory D1R (i.e., association cortices). They also support the importance of a balanced interaction between D1R and D2R in association cortices for cognitive function and its degradation with aging.

Joint PET and MRI analyses of cortical D1 and D2 dopamine receptors in healthy adults provide a framework for understanding how dopamine-boosting drugs alter brain function.

Biophysical Modeling of Dopaminergic Denervation Landscapes in the Striatum Reveals New Therapeutic Strategy

Parkinson’s disease (PD) results from a loss of dopaminergic neurons. What triggers the break-down of neuronal signaling, and how this might be compensated, is not understood. The age of onset, progression and symptoms vary between patients, and our understanding of the clinical variability remains incomplete. In this study, we investigate this, by characterizing the dopaminergic landscape in healthy and denervated striatum, using biophysical modeling. Based on currently proposed mechanisms, we model three distinct denervation patterns, and show how this affect the dopaminergic network. Depending on the denervation pattern, we show how local and global differences arise in the activity of striatal neurons. Finally, we use the mathematical formalism to suggest a cellular strategy for maintaining normal dopamine (DA) signaling following neuronal denervation. This strategy is characterized by dual enhancement of both the release and uptake capacity of DA in the remaining neurons. Overall, our results derive a new conceptual framework for the impaired dopaminergic signaling related to PD and offers testable predictions for future research directions.

Carbon-Based Electrochemical Sensors for In Vivo and In Vitro Neurotransmitter Detection

As essential neurological chemical messengers, neurotransmitters play an integral role in the maintenance of normal mammalian physiology. Aberrant neurotransmitter activity is associated with a range of neurological conditions including Parkinson's disease, Alzheimer's disease, and Huntington's disease. Many studies to date have tested different approaches to detecting neurotransmitters, yet the detection of these materials within the brain, due to the complex environment of the brain and the rapid metabolism of neurotransmitters, remains challenging and an area of active research. There is a clear need for the development of novel neurotransmitter sensing technologies capable of rapidly and sensitively monitoring specific analytes within the brain without adversely impacting the local microenvironment in which they are implanted. Owing to their excellent sensitivity, portability, ease-of-use, amenability to microprocessing, and low cost, electrochemical sensors methods have been widely studied in the context of neurotransmitter monitoring. The present review, thus, surveys current progress in this research field, discussing developed electrochemical neurotransmitter sensors capable of detecting dopamine (DA), serotonin (5-HT), acetylcholine (Ach), glutamate (Glu), nitric oxide (NO), adenosine (ADO), and so on. Of these technologies, those based on carbon nanostructures-modified electrodes including carbon nanotubes (CNTs), graphene (GR), gaphdiyne (GDY), carbon nanofibers (CNFs), and derivatives thereof hold particular promise owing to their excellent biocompatibility and electrocatalytic performance. The continued development of these and related technologies is, thus, likely to lead to major advances in the clinical diagnosis of neurological diseases and the detection of novel biomarkers thereof.

Functional dynamics of dopamine synthesis during monetary reward and punishment processing

The assessment of dopamine release with the PET competition model is thoroughly validated but entails disadvantages for the investigation of cognitive processes. We introduce a novel approach incorporating 6-[¹⁸F]FDOPA uptake as index of the dynamic regulation of dopamine synthesis enzymes by neuronal firing. The feasibility of this approach is demonstrated by assessing widely described sex differences in dopamine neurotransmission. Reward processing was behaviorally investigated in 36 healthy participants, of whom 16 completed fPET and fMRI during the monetary incentive delay task. A single 50 min fPET acquisition with 6-[¹⁸F]FDOPA served to quantify task-specific changes in dopamine synthesis. In men monetary gain induced stronger increases in ventral striatum dopamine synthesis than loss. Interestingly, the opposite effect was discovered in women. These changes were further associated with reward (men) and punishment sensitivity (women). As expected, fMRI showed robust task-specific neuronal activation but no sex difference. Our findings provide a neurobiological basis for known behavioral sex differences in reward and punishment processing, with important implications in psychiatric disorders showing sex-specific prevalence, altered reward processing and dopamine signaling. The high temporal resolution and magnitude of task-specific changes make fPET a promising tool to investigate functional neurotransmitter dynamics during cognitive processing and in brain disorders.

Central Insulin Modulates Dopamine Signaling in the Human Striatum

OBJECTIVE

Activity in the dopaminergic pathways of the brain is highly sensitive to body weight and metabolic states. Animal studies show that dopamine neurons are important targets for the metabolic hormone insulin with abolished effects in the insulin-resistant state, leading to increases in body weight and food intake. In humans, the influence of central acting insulin on dopamine and effects of their interplay are still elusive.

RESEARCH DESIGN AND METHODS

We investigated whether central administered insulin influences dopaminergic activity in striatal regions and whole-brain neural activity. Using a positron emission tomography (PET)/magnetic resonance imaging (MRI) hybrid scanner, we simultaneously performed [11C]-raclopride-PET and resting-state functional MRI in 10 healthy normal-weight men after application of intranasal insulin or placebo on 2 separate days in a randomized, placebo-controlled, blinded, crossover trial.

RESULTS

In response to central insulin compared with placebo administration, we observed greater [11C]-raclopride binding potential in the bilateral ventral and dorsal striatum. This suggests an insulin-induced reduction in synaptic dopamine levels. Resting-state striatal activity was lower 15 and 30 minutes after nasal insulin compared with placebo. Functional connectivity of the mesocorticolimbic circuitry associated with differences in dopamine levels: individuals with a stronger insulin-induced effect on dopamine levels showed a stronger increase in functional connectivity 45 minutes after intranasal insulin.

CONCLUSIONS

This study indicates that central insulin modulates dopaminergic tone in the striatum, which may affect regional brain activity and connectivity. Our results deepen the understanding of the insulin-dopamine interaction and the complex network that underlies the regulation of whole-body metabolism.

Multi-scale neural decoding and analysis

Objective.

Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment.

Approach.

We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes.

Main results.

We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches.

Significance.

This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.

The chemical tools for imaging dopamine release

Dopamine is a modulatory neurotransmitter involved in learning, motor functions, and reward. Many neuropsychiatric disorders, including Parkinson's disease, autism, and schizophrenia, are associated with imbalances or dysfunction in the dopaminergic system. Yet, our understanding of these pervasive public health issues is limited by our ability to effectively image dopamine in humans, which has long been a goal for chemists and neuroscientists. The last two decades have witnessed the development of many molecules used to trace dopamine. We review the small molecules, nanoparticles, and protein sensors used with fluorescent microscopy/photometry, MRI, and PET that shape dopamine research today. None of these tools observe dopamine itself, but instead harness the biology of the dopamine system-its synthetic and metabolic pathways, synaptic vesicle cycle, and receptors-in elegant ways. Their advantages and weaknesses are covered here, along with recent examples and the chemistry and biology that allow them to function.

Recent Advances in In Vivo Neurochemical Monitoring

The brain is a complex network that accounts for only 5% of human mass but consumes 20% of our energy. Uncovering the mysteries of the brain's functions in motion, memory, learning, behavior, and mental health remains a hot but challenging topic. Neurochemicals in the brain, such as neurotransmitters, neuromodulators, gliotransmitters, hormones, and metabolism substrates and products, play vital roles in mediating and modulating normal brain function, and their abnormal release or imbalanced concentrations can cause various diseases, such as epilepsy, Alzheimer's disease, and Parkinson's disease. A wide range of techniques have been used to probe the concentrations of neurochemicals under normal, stimulated, diseased, and drug-induced conditions in order to understand the neurochemistry of drug mechanisms and develop diagnostic tools or therapies. Recent advancements in detection methods, device fabrication, and new materials have resulted in the development of neurochemical sensors with improved performance. However, direct in vivo measurements require a robust sensor that is highly sensitive and selective with minimal fouling and reduced inflammatory foreign body responses. Here, we review recent advances in neurochemical sensor development for in vivo studies, with a focus on electrochemical and optical probes. Other alternative methods are also compared. We discuss in detail the in vivo challenges for these methods and provide an outlook for future directions.

Maternal high-fat diet during lactation reprograms the dopaminergic circuitry in mice

The maternal perinatal environment modulates brain formation, and altered maternal nutrition has been linked to the development of metabolic and psychiatric disorders in the offspring. Here, we showed that maternal high-fat diet (HFD) feeding during lactation in mice elicits long-lasting changes in gene expression in the offspring's dopaminergic circuitry. This translated into silencing of dopaminergic midbrain neurons, reduced connectivity to their downstream targets, and reduced stimulus-evoked dopamine (DA) release in the striatum. Despite the attenuated activity of DA midbrain neurons, offspring from mothers exposed to HFD feeding exhibited a sexually dimorphic expression of DA-related phenotypes, i.e., hyperlocomotion in males and increased intake of palatable food and sucrose in females. These phenotypes arose from concomitantly increased spontaneous activity of D1 medium spiny neurons (MSNs) and profoundly decreased D2 MSN projections. Overall, we have unraveled a fundamental restructuring of dopaminergic circuitries upon time-restricted altered maternal nutrition to induce persistent behavioral changes in the offspring.

Functionally distinct POMC-expressing neuron subpopulations in hypothalamus revealed by intersectional targeting

Pro-opiomelanocortin (POMC)-expressing neurons in the arcuate nucleus of the hypothalamus represent key regulators of metabolic homeostasis. Electrophysiological and single-cell sequencing experiments have revealed a remarkable degree of heterogeneity of these neurons. However, the exact molecular basis and functional consequences of this heterogeneity have not yet been addressed. Here, we have developed new mouse models in which intersectional Cre/Dre-dependent recombination allowed for successful labeling, translational profiling and functional characterization of distinct POMC neurons expressing the leptin receptor (Lepr) and glucagon like peptide 1 receptor (Glp1r). Our experiments reveal that POMC^Lepr+ and POMC^Glp1r+ neurons represent largely nonoverlapping subpopulations with distinct basic electrophysiological properties. They exhibit a specific anatomical distribution within the arcuate nucleus and differentially express receptors for energy-state communicating hormones and neurotransmitters. Finally, we identify a differential ability of these subpopulations to suppress feeding. Collectively, we reveal a notably distinct functional microarchitecture of critical metabolism-regulatory neurons.

Dopamine release, diffusion and uptake: A computational model for synaptic and volume transmission

Computational modeling of dopamine transmission is challenged by complex underlying mechanisms. Here we present a new computational model that (I) simultaneously regards release, diffusion and uptake of dopamine, (II) considers multiple terminal release events and (III) comprises both synaptic and volume transmission by incorporating the geometry of the synaptic cleft. We were able to validate our model in that it simulates concentration values comparable to physiological values observed in empirical studies. Further, although synaptic dopamine diffuses into extra-synaptic space, our model reflects a very localized signal occurring on the synaptic level, i.e. synaptic dopamine release is negligibly recognized by neighboring synapses. Moreover, increasing evidence suggests that cognitive performance can be predicted by signal variability of neuroimaging data (e.g. BOLD). Signal variability in target areas of dopaminergic neurons (striatum, cortex) may arise from dopamine concentration variability. On that account we compared spatio-temporal variability in a simulation mimicking normal dopamine transmission in striatum to scenarios of enhanced dopamine release and dopamine uptake inhibition. We found different variability characteristics between the three settings, which may in part account for differences in empirical observations. From a clinical perspective, differences in striatal dopaminergic signaling contribute to differential learning and reward processing, with relevant implications for addictive- and compulsive-like behavior. Specifically, dopaminergic tone is assumed to impact on phasic dopamine and hence on the integration of reward-related signals. However, in humans DA tone is classically assessed using PET, which is an indirect measure of endogenous DA availability and suffers from temporal and spatial resolution issues. We discuss how this can lead to discrepancies with observations from other methods such as microdialysis and show how computational modeling can help to refine our understanding of DA transmission.

Evaluation of electrochemical methods for tonic dopamine detection in vivo

Dysfunction in dopaminergic neuronal systems underlie a number of neurologic and psychiatric disorders such as Parkinson's disease, drug addiction, and schizophrenia. Dopamine systems communicate via two mechanisms, a fast "phasic" release (sub-second to second) that is related to salient stimuli and a slower "tonic" release (minutes to hours) that regulates receptor tone. Alterations in tonic levels are thought to be more critically important in enabling normal motor, cognitive, and motivational functions, and dysregulation in tonic dopamine levels are associated with neuropsychiatric disorders. Therefore, development of neurochemical recording techniques that enable rapid, selective, and quantitative measurements of changes in tonic extracellular levels are essential in determining the role of dopamine in both normal and disease states. Here, we review state-of-the-art advanced analytical techniques for in vivo detection of tonic levels, with special focus on electrochemical techniques for detection in humans.

PET imaging of neurotransmission using direct parametric reconstruction

Receptor ligand-based dynamic Positron Emission Tomography (PET) permits the measurement of neurotransmitter release in the human brain. For single-scan paradigms, the conventional method of estimating changes in neurotransmitter levels relies on fitting a pharmacokinetic model to activity concentration histories extracted after PET image reconstruction. However, due to the statistical fluctuations of activity concentration data at the voxel scale, parametric images computed using this approach often exhibit low signal-to-noise ratio, impeding characterization of neurotransmitter release. Numerous studies have shown that direct parametric reconstruction (DPR) approaches, which combine image reconstruction and kinetic analysis in a unified framework, can improve the signal-to-noise ratio of parametric mapping. However, there is little experience with DPR in imaging of neurotransmission and the performance of the approach in this application has not been evaluated before in humans. In this report, we present and evaluate a DPR methodology that computes 3-D distributions of ligand transport, binding potential (BP_ND) and neurotransmitter release magnitude (γ) from a dynamic sequence of PET sinograms. The technique employs the linear simplified reference region model (LSRRM) of Alpert et al. (2003), which represents an extension of the simplified reference region model that incorporates time-varying binding parameters due to radioligand displacement by release of neurotransmitter. Estimation of parametric images is performed by gradient-based optimization of a Poisson log-likelihood function incorporating LSRRM kinetics and accounting for the effects of head movement, attenuation, detector sensitivity, random and scattered coincidences. A ¹¹C-raclopride simulation study showed that the proposed approach substantially reduces the bias and variance of voxel-wise γ estimates as compared to standard methods. Moreover, simulations showed that detection of release could be made more reliable and/or conducted using a smaller sample size using the proposed DPR estimator. Likewise, images of BP_ND computed using DPR had substantially improved bias and variance properties. Application of the method in human subjects was demonstrated using ¹¹C-raclopride dynamic scans and a reward task, confirming the improved quality of the estimated parametric images using the proposed approach.

High long-term test-retest reliability for extrastriatal 11C-raclopride binding in healthy older adults

In vivo dopamine D2-receptor availability is frequently assessed with ¹¹C-raclopride and positron emission tomography. Due to low signal-to-noise ratios for ¹¹C-raclopride in areas with low D2 receptor densities, the ligand has been considered unreliable for measurements outside the dopamine-dense striatum. Intriguingly, recent studies show that extrastriatal ¹¹C-raclopride binding potential (BP_ND) values are (i) reliably higher than in the cerebellum (where D2-receptor levels are negligible), (ii) correlate with behavior in the expected direction, and (iii) showed good test-retest reliability in a sample of younger adults. The present work demonstrates high seven-month test-retest reliability of striatal and extrastriatal ¹¹C-raclopride BP_ND values in healthy, older adults (n = 27, age: 64-78 years). Mean ¹¹C-raclopride BP_ND values were stable between test sessions in subcortical nuclei, and in frontal and temporal cortices (p > 0.05). Across all structures analyzed, intraclass correlation coefficients were high (0.85-0.96), absolute variability was low (mean: 4-8%), and coefficients of variance ranged between 9 and 25%. Furthermore, regional ¹¹C-raclopride BP_ND values correlated with previously determined ¹⁸F-fallypride BP_ND values (ρ = 0.97 and 0.92 in correlations with and without striatal values, respectively, p < 0.01) and postmortem determined D2-receptor densities (including striatum: ρ = 0.92; p < 0.001; excluding striatum: ρ = 0.75; p = 0.067). These observations suggest that extrastriatal ¹¹C-raclopride measurements represent a true D2 signal.

Methods for Quantifying Neurotransmitter Dynamics in the Living Brain With PET Imaging

Positron emission tomography (PET) neuroimaging in neuropsychiatry is a powerful tool for the quantification of molecular brain targets to characterize disease, assess disease subtype differences, evaluate short- and long-term effects of treatments, or even to measure neurotransmitter levels in healthy and psychiatric conditions. In this work, we present different methodological approaches (time-invariant models and models with time-varying terms) that have been used to measure dynamic changes in neurotransmitter levels induced by pharmacological or behavioral challenges in humans. The developments and potential use of hybrid PET/magnetic resonance imaging (MRI) for neurotransmission brain research will also be highlighted.

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.

Regional Variation in Striatal Dopamine Spillover and Release Plasticity

Recent optical observations of dopamine at axon terminals and kinetic modeling of evoked dopamine responses measured by fast scan cyclic voltammetry (FSCV) support local restriction of dopamine diffusion at synaptic release sites. Yet, how this diffusion barrier affects synaptic and volume transmission is unknown. Here, a deficiency in a previous kinetic model's fitting of stimulus trains is remedied by replacing an earlier assumption that dopamine transporters (DATs) are present only on the outer side of the diffusion barrier with the assumption that they are present on both sides. This is consistent with the known distribution of DATs, which does not show obvious DAT-free zones proximal to dopamine release sites. A simultaneous multifitting strategy is then shown to enable unique model fits to sets of evoked dopamine FSCV responses acquired in vivo or in brain slices. This data analysis technique permits, for the first time, the calculation of the fraction of dopamine which spills over from what appears to be the perisynaptic space, as well as other parameters such as dopamine release, release plasticity, and uptake. This analysis shows that dopamine's diffusion away from its release sites is remarkably hindered (τ = 5 s), but dopamine responses are rapid because of DAT activity. Furthermore, the new analysis reveals that uptake inhibitors can inhibit dopamine release during a stimulus train, apparently by depleting the releasable pool. It is suggested that ongoing uptake is critical for maintaining ongoing synaptic dopamine release and that the previously reported and also herein claimed increase of the initial dopamine release of some uptake inhibitors might be an important mechanism in addiction. Finally, brain mapping data reveal that the diffusion barrier is conserved, but there are variations in perisynaptic uptake, volume transmission, and release plasticity within the rat striatum. Therefore, an analysis paradigm is developed to quantify previously unmeasured features of brain dopaminergic transmission and to reveal regional functional differences among dopamine synapses.

Combining designer receptors exclusively activated by designer drugs and neuroimaging in experimental models: A powerful approach towards neurotheranostic applications

The combination of chemogenetics targeting specific brain cell populations with in vivo imaging techniques provides scientists with a powerful new tool to study functional neural networks at the whole-brain scale. A number of recent studies indicate the potential of this approach to increase our understanding of brain function in health and disease. In this review, we discuss the employment of a specific chemogenetic tool, designer receptors exclusively activated by designer drugs, in conjunction with non-invasive neuroimaging techniques such as PET and MRI. We highlight the utility of using this multiscale approach in longitudinal studies and its ability to identify novel brain circuits relevant to behaviour that can be monitored in parallel. In addition, some identified shortcomings in this technique and more recent efforts to overcome them are also presented. Finally, we discuss the translational potential of designer receptors exclusively activated by designer drugs in neuroimaging and the promise it holds for future neurotheranostic applications.

Food reward and gut-brain signalling

The increasing availability of ultra-processed, energy dense food is contributing to the spread of the obesity pandemic, which is a serious health threat in today’s world. One possible cause for this association arises from the fact that the brain is wired to derive pleasure from eating. Specifically, food intake activates reward pathways involving dopamine receptor signalling. The reinforcing value of specific food items results from the interplay between taste and nutritional properties. Increasing evidence suggests that nutritional value is sensed in the gut by chemoreceptors in the intestinal tract and the hepatic portal vein, and conveyed to the brain through neuronal and endocrine pathways to guide food selection behaviour. Ultra-processed food is designed to potentiate the reward response through a combination of high fat and high sugar, therebye seeming highly appetizing. There is increasing evidence that overconsumption of processed food distorts normal reward signalling, leading to compulsive eating behaviour and obesity. Hence, it is essential to understand food reward and gut-brain signalling to find an effective strategy to combat the obesity pandemic.

[Development of Novel Nuclear Medical Imaging Probes for Quantification of Matrix Metalloproteinases in Diseases]

Matrix metalloproteinases (MMPs) regulate various cellular functions, such as motility, invasion, differentiation, and apoptosis. Precise in vivo quantification of MMPs in disease can provide beneficial information for both basic and clinical research studies. To this end, various types of probes have been developed for imaging MMPs in vivo. In this review, representative MMP-targeted probes, such as binding probes and activatable probes, are outlined, including highlights of our own research. In addition, strategies for the development of probes that apply "theranostics," a concept that integrates therapy and diagnostics, are elucidated with reference to [¹⁸F]IPFP, a new probe developed in our laboratory. [¹⁸F]IPFP was prepared by iodination of a known MMP inhibitor to enhance its affinity and labeled with the compact prosthetic agent 4-nitrophenyl 2-[¹⁸F]fluoropropionate ([¹⁸F]NFP) for MMP-targeted positron-emission tomography (PET) and other therapeutic properties. IPFP demonstrated high inhibitory activity toward MMP-12 (IC₅₀ value=1.5 nM). Radioactivity accumulation in the lungs 90 min after administration of [¹⁸F]IPFP was 4-fold higher in chronic obstructive pulmonary disease (COPD) mice overexpressing MMPs compared with normal mice. Ex vivo PET confirmed the radioactivity distribution in tissues, and autoradiography analysis demonstrated accumulation differences between COPD and normal mice. Consequently, [¹⁸F]IPFP showed potent inhibitory activities against MMPs and suitable pharmacokinetics for imaging pulmonary disease. Thus, [¹⁸F]IPFP is a promising theranostic probe for pulmonary disease and is expected to be applied to various other MMP-related diseases. Strategies for MMP probe development introduced in this review are anticipated to lead to the development of superior imaging probes in the future.

In vivo functional diversity of midbrain dopamine neurons within identified axonal projections

Functional diversity of midbrain dopamine (DA) neurons ranges across multiple scales, from differences in intrinsic properties and connectivity to selective task engagement in behaving animals. Distinct in vitro biophysical features of DA neurons have been associated with different axonal projection targets. However, it is unknown how this translates to different firing patterns of projection-defined DA subpopulations in the intact brain. We combined retrograde tracing with single-unit recording and labelling in mouse brain to create an in vivo functional topography of the midbrain DA system. We identified differences in burst firing among DA neurons projecting to dorsolateral striatum. Bursting also differentiated DA neurons in the medial substantia nigra (SN) projecting either to dorsal or ventral striatum. We found differences in mean firing rates and pause durations among ventral tegmental area (VTA) DA neurons projecting to lateral or medial shell of nucleus accumbens. Our data establishes a high-resolution functional in vivo landscape of midbrain DA neurons.