Julia Schiemann

K-ATP channels in dopamine substantia nigra neurons control bursting and novelty-induced exploration

Phasic activation of the dopamine (DA) midbrain system in response to unexpected reward or novelty is critical for adaptive behavioral strategies. This activation of DA midbrain neurons occurs via a synaptically triggered switch from low-frequency background spiking to transient high-frequency burst firing. We found that, in medial DA neurons of the substantia nigra (SN), activity of ATP-sensitive potassium (K-ATP) channels enabled NMDA-mediated bursting in vitro as well as spontaneous in vivo burst firing in anesthetized mice. Cell-selective silencing of K-ATP channel activity in medial SN DA neurons revealed that their K-ATP channel–gated burst firing was crucial for novelty-dependent exploratory behavior. We also detected a transcriptional upregulation of K-ATP channel and NMDA receptor subunits, as well as high in vivo burst firing, in surviving SN DA neurons from Parkinsons disease patients, suggesting that burst-gating K-ATP channel function in DA neurons affects phenotypes in both disease and health.

Dopamine midbrain neurons in health and Parkinson's disease: emerging roles of voltage-gated calcium channels and ATP-sensitive potassium channels.

Dopamine (DA) releasing midbrain neurons are essential for multiple brain functions, such as voluntary movement, working memory, emotion and cognition. DA midbrain neurons within the substantia nigra (SN) and the ventral tegmental area (VTA) exhibit a variety of distinct axonal projections and cellular properties, and are differentially affected in diseases like schizophrenia, attention deficit hyperactivity disorder, and Parkinsons disease (PD). Apart from having diverse functions in health and disease states, DA midbrain neurons display distinct electrical activity patterns, crucial for DA release. These activity patterns are generated and modulated by specific sets of ion channels. Recently, two ion channels have been identified, not only contributing to these activity patterns and to functional properties of DA midbrain neurons, but also seem to render SN DA neurons particularly vulnerable to degeneration in PD and its animal models: L-type calcium channels (LTCCs) and ATP-sensitive potassium channels (K-ATPs). In this review, we focus on the emerging physiological and pathophysiological roles of these two ion channels (and their complex interplay with other ion channels), particularly in highly vulnerable SN DA neurons, as selective degeneration of these neurons causes the major motor symptoms of PD.

Cav1.3 channels control D2-autoreceptor responses via NCS-1 in substantia nigra dopamine neurons

See Borgkvist et al. (doi:10.1093/brain/awu150) for a scientific commentary on this article. D2 autoreceptors and L-type calcium channels are both implicated in Parkinson’s disease, but how they interact is unclear. Dragicevic et al. reveal that L-type calcium channels can modulate D2-autoreceptor responses via the neuronal calcium sensor NCS-1. This dopamine-dependent signalling network is altered in Parkinson’s disease and could represent a therapeutic target.

Increased dopamine D2 receptor activity in the striatum alters the firing pattern of dopamine neurons in the ventral tegmental area.

Significance Patients with schizophrenia suffer from cognitive and negative deficits that are largely resistant to current therapeutic strategies. Here, using a genetic mouse model that displays phenotypes similar to these cognitive and negative symptoms, we found that increased postsynaptic D2 receptor (D2R) activity in the striatum leads to changes in the firing pattern of presynaptic dopamine (DA) neurons of the midbrain. These alterations occur in the ventral tegmental area (VTA) of the midbrain, but not in the substantia nigra, suggesting that DA pathways may be differently regulated by striatal D2R hyperactivity. The changes in neuron firing patterns were accompanied by a reduction in NMDA receptor subunits selectively in dopaminergic VTA neurons, providing a potential new target for the treatment of schizophrenia symptoms. There is strong evidence that the core deficits of schizophrenia result from dysfunction of the dopamine (DA) system, but details of this dysfunction remain unclear. We previously reported a model of transgenic mice that selectively and reversibly overexpress DA D2 receptors (D2Rs) in the striatum (D2R-OE mice). D2R-OE mice display deficits in cognition and motivation that are strikingly similar to the deficits in cognition and motivation observed in patients with schizophrenia. Here, we show that in vivo, both the firing rate (tonic activity) and burst firing (phasic activity) of identified midbrain DA neurons are impaired in the ventral tegmental area (VTA), but not in the substantia nigra (SN), of D2R-OE mice. Normalizing striatal D2R activity by switching off the transgene in adulthood recovered the reduction in tonic activity of VTA DA neurons, which is concordant with the rescue in motivation that we previously reported in our model. On the other hand, the reduction in burst activity was not rescued, which may be reflected in the observed persistence of cognitive deficits in D2R-OE mice. We have identified a potential molecular mechanism for the altered activity of DA VTA neurons in D2R-OE mice: a reduction in the expression of distinct NMDA receptor subunits selectively in identified mesolimbic DA VTA, but not nigrostriatal DA SN, neurons. These results suggest that functional deficits relevant for schizophrenia symptoms may involve differential regulation of selective DA pathways.

Cellular mechanisms underlying behavioral state-dependent bidirectional modulation of motor cortex output.

Summary Neuronal activity in primary motor cortex (M1) correlates with behavioral state, but the cellular mechanisms underpinning behavioral state-dependent modulation of M1 output remain largely unresolved. Here, we performed in vivo patch-clamp recordings from layer 5B (L5B) pyramidal neurons in awake mice during quiet wakefulness and self-paced, voluntary movement. We show that L5B output neurons display bidirectional (i.e., enhanced or suppressed) firing rate changes during movement, mediated via two opposing subthreshold mechanisms: (1) a global decrease in membrane potential variability that reduced L5B firing rates (L5Bsuppressed neurons), and (2) a coincident noradrenaline-mediated increase in excitatory drive to a subpopulation of L5B neurons (L5Benhanced neurons) that elevated firing rates. Blocking noradrenergic receptors in forelimb M1 abolished the bidirectional modulation of M1 output during movement and selectively impaired contralateral forelimb motor coordination. Together, our results provide a mechanism for how noradrenergic neuromodulation and network-driven input changes bidirectionally modulate M1 output during motor behavior.

Measuring burstiness and regularity in oscillatory spike trains.

The ability of neurons to emit different firing patterns such as bursts or oscillations is important for information processing in the brain. In dopaminergic neurons, prominent patterns include repetitive, oscillatory bursts, regular pacemakers, and irregular spike trains with nonstationary properties. In order to describe and measure the variability of these patterns, we describe burstiness and regularity in a single model framework. We present a doubly stochastic spike train model in which a background oscillation with independent and normally distributed intervals gives rise to either single spikes or bursty spike events with Gaussian firing intensities. Five easily interpretable parameters allow a classification into bursty or single spike and irregularly or regularly oscillating firing patterns. This classification is based primarily on features of the autocorrelation histogram which are usually studied qualitatively by visual inspection. The present model provides a quantitative and objective classification scheme and relates these features directly to the underlying processes. In addition, confidence intervals visualize the uncertainty of parameter estimation and classification precision. We apply the model to a data set obtained from single dopaminergic substantia nigra neurons recorded extracellularly in vivo. The model is able to represent a high variety of discharge patterns observed empirically, and the classification agrees closely with visual inspection. In addition, changes in the parameters can be studied quantitatively, including also the properties related to bursting behavior. Thus, the proposed model can be used for the description of neuronal firing patterns and the investigation of their dynamical changes with cellular and experimental conditions.

A multiple filter test for the detection of rate changes in renewal processes with varying variance

Nonstationarity of the event rate is a persistent problem in modeling time series of events, such as neuronal spike trains. Motivated by a variety of patterns in neurophysiological spike train recordings, we define a general class of renewal processes. This class is used to test the null hypothesis of stationary rate versus a wide alternative of renewal processes with finitely many rate changes (change points). Our test extends ideas from the filtered derivative approach by using multiple moving windows simultaneously. To adjust the rejection threshold of the test, we use a Gaussian process, which emerges as the limit of the filtered derivative process. We also develop a multiple filter algorithm, which can be used when the null hypothesis is rejected in order to estimate the number and location of change points. We analyze the benefits of multiple filtering and its increased detection probability as compared to a single window approach. Application to spike trains recorded from dopamine midbrain neurons in anesthetized mice illustrates the relevance of the proposed techniques as preprocessing steps for methods that assume rate stationarity. In over 70% of all analyzed spike trains classified as rate nonstationary, different change points were detected by different window sizes.

Multi‐Scale Detection of Variance Changes in Renewal Processes in the Presence of Rate Change Points

Non-stationarity of the rate or variance of events is a well-known problem in the description and analysis of time series of events, such as neuronal spike trains. A multiple filter test (MFT) for rate homogeneity has been proposed earlier that detects change points on multiple time scales simultaneously. It is based on a filtered derivative approach, and the rejection threshold derives from a Gaussian limit process

Detection and localization of multiple rate changes in Poisson spike trains

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A model for the joint evaluation of burstiness and regularity in oscillatory spike trains

which is independent of the point process parameters. Here we extend the MFT to variance homogeneity of life times. When the rate is constant, the MFT extends directly to the null hypothesis of constant variance. In the presence of rate change points, we propose to incorporate estimates of these in the test for variance homogeneity, using an adaptation of the test statistic. The resulting limit process shows slight deviations from