Within-Mice Comparison of Microdialysis and Fiber Photometry-Recorded Dopamine Biosensor during Amphetamine Response.

A fundamental concept in neuroscience is the transmission of information between neurons via neurotransmitters, -modulators, and -peptides. For the past decades, the gold standard for measuring neurochemicals in awake animals has been microdialysis (MD). The emergence of genetically encoded fluorescence-based biosensors, as well as in vivo optical techniques such as fiber photometry (FP), has introduced technologically distinct means of measuring neurotransmission. To directly compare MD and FP, we performed concurrent within-animal recordings of extracellular dopamine (DA) in the dorsal striatum (DS) before and after administration of amphetamine in awake, freely behaving mice expressing the dopamine sensor dLight1.3b. We show that despite temporal differences, MD- and FP-based readouts of DA correlate well within mice. Down-sampling of FP data showed temporal correlation to MD data, with less variance observed using FP. We also present evidence that DA fluctuations periodically reach low levels, and naïve animals have rapid, predrug DA dynamics measured with FP that correlate to the subsequent pharmacodynamics of amphetamine as measured with MD and FP.

Behavioral encoding across timescales by region-specific dopamine dynamics.

The dorsal (DS) and ventral striatum (VS) receive dopaminergic projections that control motor functions and reward-related behavior. It remains poorly understood how dopamine release dynamics across different temporal scales in these regions are coupled to behavioral outcomes. Here, we employ the dopamine sensor dLight1.3b together with multiregion fiber photometry and machine learning-based analysis to decode dopamine dynamics across the striatum during self-paced exploratory behavior in mice. Our data show a striking coordination of rapidly fluctuating signal in the DS, carrying information across dopamine levels, with a slower signal in the VS, consisting mainly of slow-paced transients. Importantly, these release dynamics correlated with discrete behavioral motifs, such as turns, running, and grooming on a subsecond-to-minute time scale. Disruption of dopamine dynamics with cocaine caused randomization of action selection sequencing and disturbance of DS-VS coordination. The data suggest that distinct dopamine dynamics of DS and VS jointly encode behavioral sequences during unconstrained activity with DS modulating the stringing together of actions and VS the signal to initiate and sustain the selected action.

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.

A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing.

Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT effects could be exploited, traditional compressive-sensing methods cannot be directly applied as the system matrix in FMT is highly coherent. To overcome these issues, we propose and assess a three-step reconstruction method. First, truncated singular value decomposition is applied on the data to reduce matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via ℓ1 regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm-1, absorption coefficient: 0.1 cm-1) and tomographic measurements made using pixelated detectors. In different experiments, fluorescent sources of varying size and intensity were simulated. The proposed reconstruction method provided accurate estimates of the fluorescent source intensity, with a 20% lower root mean square error on average compared to the pure-homotopy method for all considered source intensities and sizes. Further, compared with conventional ℓ2 regularized algorithm, overall, the proposed method reconstructed substantially more accurate fluorescence distribution. The proposed method shows considerable promise and will be tested using more realistic simulations and experimental setups.

Unsupervised Idealization of Ion Channel Recordings by Minimum Description Length: Application to Human PIEZO1-Channels.

Researchers can investigate the mechanistic and molecular basis of many physiological phenomena in cells by analyzing the fundamental properties of single ion channels. These analyses entail recording single channel currents and measuring current amplitudes and transition rates between conductance states. Since most electrophysiological recordings contain noise, the data analysis can proceed by idealizing the recordings to isolate the true currents from the noise. This de-noising can be accomplished with threshold crossing algorithms and Hidden Markov Models, but such procedures generally depend on inputs and supervision by the user, thus requiring some prior knowledge of underlying processes. Channels with unknown gating and/or functional sub-states and the presence in the recording of currents from uncorrelated background channels present substantial challenges to such analyses. Here we describe and characterize an idealization algorithm based on Rissanen's Minimum Description Length (MDL) Principle. This method uses minimal assumptions and idealizes ion channel recordings without requiring a detailed user input or a priori assumptions about channel conductance and kinetics. Furthermore, we demonstrate that correlation analysis of conductance steps can resolve properties of single ion channels in recordings contaminated by signals from multiple channels. We first validated our methods on simulated data defined with a range of different signal-to-noise levels, and then showed that our algorithm can recover channel currents and their substates from recordings with multiple channels, even under conditions of high noise. We then tested the MDL algorithm on real experimental data from human PIEZO1 channels and found that our method revealed the presence of substates with alternate conductances.

Representation of spontaneous movement by dopaminergic neurons is cell-type selective and disrupted in parkinsonism.

Midbrain dopaminergic neurons are essential for appropriate voluntary movement, as epitomized by the cardinal motor impairments arising in Parkinson's disease. Understanding the basis of such motor control requires understanding how the firing of different types of dopaminergic neuron relates to movement and how this activity is deciphered in target structures such as the striatum. By recording and labeling individual neurons in behaving mice, we show that the representation of brief spontaneous movements in the firing of identified midbrain dopaminergic neurons is cell-type selective. Most dopaminergic neurons in the substantia nigra pars compacta (SNc), but not in ventral tegmental area or substantia nigra pars lateralis, consistently represented the onset of spontaneous movements with a pause in their firing. Computational modeling revealed that the movement-related firing of these dopaminergic neurons can manifest as rapid and robust fluctuations in striatal dopamine concentration and receptor activity. The exact nature of the movement-related signaling in the striatum depended on the type of dopaminergic neuron providing inputs, the striatal region innervated, and the type of dopamine receptor expressed by striatal neurons. Importantly, in aged mice harboring a genetic burden relevant for human Parkinson's disease, the precise movement-related firing of SNc dopaminergic neurons and the resultant striatal dopamine signaling were lost. These data show that distinct dopaminergic cell types differentially encode spontaneous movement and elucidate how dysregulation of their firing in early Parkinsonism can impair their effector circuits.

Functionally Distinct Dopamine Signals in Nucleus Accumbens Core and Shell in the Freely Moving Rat.

Dynamic signaling of mesolimbic dopamine (DA) neurons has been implicated in reward learning, drug abuse, and motivation. However, this system is complex because firing patterns of these neurons are heterogeneous; subpopulations receive distinct synaptic inputs, and project to anatomically and functionally distinct downstream targets, including the nucleus accumbens (NAc) shell and core. The functional roles of these cell populations and their real-time signaling properties in freely moving animals are unknown. Resolving the real-time DA signal requires simultaneous knowledge of the synchronized activity of DA cell subpopulations and assessment of the down-stream functional effect of DA release. Because this is not yet possible solely by experimentation in vivo, we combine computational modeling and fast-scan cyclic voltammetry data to reconstruct the functionally relevant DA signal in DA neuron subpopulations projecting to the NAc core and shell in freely moving rats. The approach provides a novel perspective on real-time DA neuron firing and concurrent activation of presynaptic autoreceptors and postsynaptic targets. We first show that individual differences in DA release arise from differences in autoreceptor feedback. The model predicts that extracellular DA concentrations in NAc core result from constant baseline DA firing, whereas DA concentrations in NAc shell reflect highly dynamic firing patters, including synchronized burst firing and pauses. Our models also predict that this anatomical difference in DA signaling is exaggerated by intravenous infusion of cocaine. SIGNIFICANCE STATEMENT: Orchestrated signaling from mesolimbic dopamine (DA) neurons is important for initiating appropriate behavior in response to salient stimuli. Thus, subpopulations of mesolimbic DA neurons show different in vitro properties and synaptic inputs depending on their specific projections to the core and shell subterritories of the nucleus accumbens (NAc). However, the functional consequence of these differences is unknown. Here we analyze and model DA dynamics in different areas of the NAc to establish the real-time DA signal. In freely behaving animals, we find that the DA signal from mesencephalic neurons projecting to the NAc shell is dominated by synchronized bursts and pauses, whereas signaling is uniform for core-projecting neurons; this difference is amplified by cocaine.

Three mechanisms by which striatal denervation causes breakdown of dopamine signaling.

Progressive loss of nigrostriatal dopamine (DA) neurons is the neuropathological hallmark of Parkinson's disease (PD). Symptoms of the disease can often be treated by DA D2 agonists and thus seem related to disinhibition of the indirect striatal pathway. However, there is no evidence that symptoms arise by low extracellular DA concentration or are associated with reduced D2 receptor binding. Here I provide a theoretical analysis of the pathophysiology and postsynaptic adaptation resulting from striatal DA denervation. I found that progressive denervation may alter DA signaling by three independent mechanisms depending on degree of denervation and macroscopic morphology of the lesion. As long as the remaining innervation stays anatomically coherent, denervation reduces phasic variations in extracellular DA, but the DA tone is not changed. The reduction of phasic signaling can be partially compensated by upregulating postsynaptic signaling cascades. However, changes in DA dynamics evade compensation. With 80-99% denervation, a persistent aberrant signal develops in D2-regulated pathways caused by random fluctuations in tonic DA release. Permanent low DA levels occur in regions completely void of innervation. Simulation of l-dopa therapy reduced the aberrant D2 signal. With a high degree of denervation, l-dopa enhanced another aberrant signal, this time in the D1 pathway. This analysis provides a quantitative, physiologically consistent view of the early and late stages of PD, the effect of main therapeutic medications, and potential side effects. The mechanisms described here may also provide an explanation to currently inexplicable pathological phenomena such as psycho stimulant-induced contraversive rotations in animal models.

Influence of phasic and tonic dopamine release on receptor activation.

Tonic and phasic dopamine release is implicated in learning, motivation, and motor functions. However, the relationship between spike patterns in dopaminergic neurons, the extracellular concentration of dopamine, and activation of dopamine receptors remains unresolved. In the present study, we develop a computational model of dopamine signaling that give insight into the relationship between the dynamics of release and occupancy of D(1) and D(2) receptors. The model is derived from first principles using experimental data. It has no free parameters and offers unbiased estimation of the boundaries of dopaminergic volume transmission. Bursts primarily increase occupancy of D(1) receptors, whereas pauses translate into low occupancy of D(1) and D(2) receptors. Phasic firing patterns, composed of bursts and pauses, reduce the average D(2) receptor occupancy and increase average D(1) receptor occupancy compared with equivalent tonic firing. Receptor occupancy is crucially dependent on synchrony and the balance between tonic and phasic firing modes. Our results provide quantitative insight in the dynamics of volume transmission and complement experimental data obtained with electrophysiology, positron emission tomography, microdialysis, amperometry, and voltammetry.

Dynamic strength of the interaction between lung surfactant protein D (SP-D) and saccharide ligands.

In order to investigate the dynamic strength of the interaction between lung surfactant protein D (SP-D) and different sugars, maltose, mannose, glucose, and galactose, we have used an atomic force microscope to monitor the interaction on a single molecule scale. The experiment is performed by measuring the rupture force when the SP-D-sugar bond is subjected to a continuously increasing force. Under these dynamic conditions, SP-D binds strongest to d-mannose and weakest to maltose and d-galactose. These results differ from equilibrium measurements wherein SP-D exhibits preference for maltose. On the basis of this finding, we propose that the binding of the disaccharide maltose to SP-D, which is energetically stronger than the binding of any of the monosacchrides, alters the structure of the binding site in a way that lowers the dynamic strength of the bond. We conclude that determining the strength of a protein-ligand bond under dynamic stress using an atomic force microscope is possibly more relevant for mimicking the actual nonequilibrium physiological situation in the lungs.