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Substantia nigra (SNc) dopaminergic neurons respond to aversive stimuli with inhibitory pauses in firing followed by transient rebound activation. We tested integration of inhibitory synaptic inputs onto SNc neurons from genetically defined populations in dorsal striatum (striosome and matrix) and external globus pallidus (GPe; parvalbumin- and Lhx6-positive), and examined their contribution to pause-rebound firing. Activation of striosome projections, which target "dendron bouquets" in the pars reticulata (SNr), consistently quiets firing and relief from striosome inhibition triggers rebound activity. Striosomal inhibitory postsynaptic currents (IPSCs) display a prominent GABA-B receptor-mediated component that strengthens the impact of SNr dendrite synapses on somatic excitability and enables rebounding. By contrast, GPe projections activate GABA-A receptors on the soma and proximal dendrites but do not result in rebounding. Lastly, optical mapping shows that dorsal striatum selectively inhibits the ventral population of SNc neurons, which are intrinsically capable of rebounding. Therefore, we define a distinct striatonigral circuit for generating dopamine rebound.

Substania nigra (SNc) dopaminergic neurons show a pause-rebound firing pattern in response to aversive events. Because these neurons integrate information from predominately inhibitory brain areas, it is important to determine which inputs functionally inhibit the dopamine neurons and whether this pause-rebound firing pattern can be produced by a solely inhibitory input. Here, we functionally map genetically-defined inhibitory projections from the dorsal striatum (striosome and matrix) and globus pallidus (GPe; parvalbumin and Lhx6) onto SNc neurons. We find that GPe and striosomal inputs both pause firing in SNc neurons, but rebound firing only occurs after inhibition from striosomes. Indeed, we find that striosomes are synaptically optimized to produce rebound and preferentially inhibit a subpopulation of ventral, intrinsically rebound-ready SNc dopaminergic neurons on their reticulata dendrites. Therefore, we describe a self-contained dendrite-specific striatonigral circuit that can produce pause-rebound firing in the absence of excitatory input.

Neural networks that undergo acute insults display remarkable reorganization. This injury related plasticity is thought to permit recovery of function in the face of damage that cannot be reversed. Previously, an increase in the transmission strength at Schaffer collateral to CA1 pyramidal cell synapses was observed after long-term activity reduction in organotypic hippocampal slices. Here we report that, following acute preparation of adult rat hippocampal slices and surgical removal of area CA3, input to area CA1 was reduced and Schaffer collateral synapses underwent functional strengthening. This increase in synaptic strength was limited to Schaffer collateral inputs (no alteration to temporoammonic synapses) and acted to normalize postsynaptic discharge, supporting a homeostatic or compensatory response. Short-term plasticity was not altered, but an increase in immunohistochemical labeling of GluA1 subunits was observed in the stratum radiatum (but not stratum moleculare), suggesting increased numbers of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors and a postsynaptic locus of expression. Combined, these data support the idea that, in response to the reduction in presynaptic activity caused by removal of area CA3, Schaffer collateral synapses undergo a relatively rapid increase in functional efficacy likely supported by insertion of more AMPARs, which maintains postsynaptic excitability in CA1 pyramidal neurons. This novel fast compensatory plasticity exhibits properties that would allow it to maintain optimal network activity levels in the hippocampus, a brain structure lauded for its ongoing experience-dependent malleability.

Neural circuits in mammalian brains consist of large numbers of different cell types having different functional properties. To better understand the separate roles of individual neuron types in specific aspects of spatial learning and memory, we perturbed the function of principal neurons in vivo during maze performance or in hippocampal slices during recording of evoked excitatory synaptic potentials. Transgenic mice expressing the Drosophila allatostatin receptor (AlstR) in cortical and hippocampal pyramidal cells were tested on an elevated plus maze, in a Y-maze, and in the Morris water maze. Relative to a control cohort, AlstR-positive mice treated with allatostatin exhibited no difference in open arm dwell time on the elevated plus maze or total number of arm entries in a Y-maze, but displayed reduced spontaneous alternation. When animals received massed or spaced training trials in the Morris water maze, and the peptide was delivered prior to an immediate probe, no effects on performance were observed. When the peptide was delivered during a probe trial performed 24 h after seven days of spaced training, allatostatin delivery to AlstR positive mice enhanced direct navigation to the escape platform. Combined, these results suggest that cortical and hippocampal pyramidal neurons are required during spatial decision-making in a novel environment and compete with other neural systems after extended training in a long-term reference memory task. In hippocampal slices collected from AlstR positive animals, allatostatin delivery produced frequency dependent alterations in the Schaffer collateral fiber volley (attenuated accommodation at 100 Hz) and excitatory postsynaptic potential (attenuated facilitation at 5 Hz). Combined, the neural and behavioral discoveries support the involvement of short-term plasticity of Schaffer collateral axons and synapses during exploration of a novel environment and during initial orientation to a goal in a well-learned setting.

This review addresses the present state of single-cell models of the firing pattern of midbrain dopamine neurons and the insights that can be gained from these models into the underlying mechanisms for diseases such as Parkinson's, addiction, and schizophrenia. We will explain the analytical technique of separation of time scales and show how it can produce insights into mechanisms using simplified single-compartment models. We also use morphologically realistic multicompartmental models to address spatially heterogeneous aspects of neural signaling and neural metabolism. Separation of time scale analyses are applied to pacemaking, bursting, and depolarization block in dopamine neurons. Differences in subpopulations with respect to metabolic load are addressed using multicompartmental models.

Summary: Parkinson’s disease causes the most profound loss of the aldehyde dehydrogenase 1A1-positive (ALDH1A1+) nigrostriatal dopaminergic neuron (nDAN) subpopulation. The connectivity and functionality of ALDH1A1+ nDANs, however, remain poorly understood. Here, we show in rodent brains that ALDH1A1+ nDANs project predominantly to the rostral dorsal striatum, from which they also receive most monosynaptic inputs, indicating extensive reciprocal innervations with the striatal spiny projection neurons (SPNs). Functionally, genetic ablation of ALDH1A1+ nDANs causes severe impairments in motor skill learning, along with a reduction in high-speed walking. While dopamine replacement therapy accelerated walking speed, it failed to improve motor skill learning in ALDH1A1+ nDAN-ablated mice. Altogether, our study provides a comprehensive whole-brain connectivity map and reveals a key physiological function of ALDH1A1+ nDANs in motor skill acquisition, suggesting the motor learning processes require ALDH1A1+ nDANs to integrate diverse presynaptic inputs and supply dopamine with dynamic precision. : Wu et al. show that aldehyde dehydrogenase 1A1-positive nigrostriatal dopaminergic neurons, which display the most profound degeneration in Parkinson’s disease, are essential in the acquisition of skilled movements in rodent models. The proper synaptic inputs to these neurons are critical for providing the timely dopamine release required in the learning process. Keywords: aldehyde dehydrogenase 1a1, ALDH1A1, Parkinson’s disease, dopamine, dopaminergic neurons, substantia nigra, striatum, brain mapping, motor skill learning

Influx of calcium through voltage-gated calcium channels (VGCCs) is essential for striatal function and plasticity. VGCCs expressed in striatal neurons have varying kinetics, voltage dependences, and densities resulting in heterogeneous subcellular calcium dynamics. One factor that determines the calcium dynamics in striatal medium spiny neurons is inactivation of VGCCs. Aside from voltage-dependent inactivation, VGCCs undergo calcium-dependent inactivation (CDI): inactivating in response to an influx of calcium. CDI is a negative feedback control mechanism; however, its contribution to striatal neuron function is unknown. Furthermore, although the density of VGCC expression changes with development, it is unclear whether CDI changes with development. Because calcium influx through L-type calcium channels is required for striatal synaptic depression, a change in CDI could contribute to age-dependent changes in striatal synaptic plasticity. Here we use whole cell voltage clamp to characterize CDI over developmental stages and across striatal regions. We find that CDI increases at the age of eye opening in the medial striatum but not the lateral striatum. The developmental increase in CDI mostly involves L-type channels, although calcium influx through non-L-type channels contributes to the CDI in both age groups. Agents that enhance protein kinase A (PKA) phosphorylation of calcium channels reduce the magnitude of CDI after eye opening, suggesting that the developmental increase in CDI may be related to a reduction in the phosphorylation state of the L-type calcium channel. These results are the first to show that modifications in striatal neuron properties correlate with changes to sensory input.

While there is growing appreciation for diversity among ventral tegmental area dopamine neurons, much less is known regarding functional heterogeneity among the substantia nigra pars compacta (SNc) neurons. Here, we show that calbindin-positive dorsal tier and calbindin-negative ventral tier SNc dopaminergic neurons in mice comprise functionally distinct subpopulations distinguished by their dendritic calcium signaling, rebound excitation, and physiological responses to dopamine D2-receptor (D2) autoinhibition. While dopamine is known to inhibit action potential backpropagation, our experiments revealed an unexpected enhancement of excitatory responses and dendritic calcium signals in the presence of D2-receptor inhibition. Specifically, dopamine inhibition and direct hyperpolarization enabled the generation of low-threshold depolarizations that occurred in an all-or-none or graded manner, due to recruitment of T-type calcium channels. Interestingly, these effects occurred selectively in calbindin-negative dopaminergic neurons within the SNc. Thus, calbindin-positive and calbindin-negative SNc neurons differ substantially in their calcium channel composition and efficacy of excitatory inputs in the presence of dopamine inhibition.SIGNIFICANCE STATEMENTSubstantia nigra dopaminergic neurons can be divided into two populations: the calbindin-negative ventral tier, which is vulnerable to neurodegeneration in Parkinson's disease, and the calbindin-positive dorsal tier, which is relatively resilient. Although tonic firing is similar in these subpopulations, we find that their responses to dopamine-mediated inhibition are strikingly different. During inhibition, calbindin-negative neurons exhibit increased sensitivity to excitatory inputs, which can then trigger large dendritic calcium transients due to strong expression of T-type calcium channels. Therefore, SNc neurons differ substantially in their calcium channel composition, which may contribute to their differential vulnerability. Furthermore, T-currents increase excitation efficacy onto calbindin-negative cells during dopamine inhibition, suggesting that shared inputs are differentially processed in subpopulations resulting in distinct downstream dopamine signals.

Midbrain dopamine neurons recordedin vivopause their firing in response to reward omission and aversive stimuli. While the initiation of pauses typically involves synaptic or modulatory input, intrinsic membrane properties may also enhance or limit hyperpolarization, raising the question of how intrinsic conductances shape pauses in dopamine neurons. Using retrograde labeling and electrophysiological techniques combined with computational modeling, we examined the intrinsic conductances that shape pauses evoked by current injections and synaptic stimulation in subpopulations of dopamine neurons grouped according to their axonal projections to the nucleus accumbens or dorsal striatum in mice. Testing across a range of conditions and pulse durations, we found that mesoaccumbal and nigrostriatal neurons differ substantially in rebound properties with mesoaccumbal neurons displaying significantly longer delays to spiking following hyperpolarization. The underlying mechanism involves an inactivating potassium (IA) current with decay time constants of up to 225 ms, and small-amplitude hyperpolarization-activated currents (IH), characteristics that were most often observed in mesoaccumbal neurons. Pharmacological block of IAcompletely abolished rebound delays and, importantly, shortened synaptically evoked inhibitory pauses, thereby demonstrating the involvement of A-type potassium channels in prolonging pauses evoked by GABAergic inhibition. Therefore, these results show that mesoaccumbal and nigrostriatal neurons display differential responses to hyperpolarizing inhibitory stimuli that favors a higher sensitivity to inhibition in mesoaccumbal neurons. These findings may explain, in part, observations fromin vivoexperiments that ventral tegmental area neurons tend to exhibit longer aversive pauses relative to SNc neurons.SIGNIFICANCE STATEMENTOur study examines rebound, postburst, and synaptically evoked inhibitory pauses in subpopulations of midbrain dopamine neurons. We show that pauses in dopamine neuron firing, evoked by either stimulation of GABAergic inputs or hyperpolarizing current injections, are enhanced by a subclass of potassium conductances that are recruited at voltages below spike threshold. Importantly, A-type potassium currents recorded in mesoaccumbal neurons displayed substantially slower inactivation kinetics, which, combined with weaker expression of hyperpolarization-activated currents, lengthened hyperpolarization-induced delays in spiking relative to nigrostriatal neurons. These results suggest that input integration differs among dopamine neurons favoring higher sensitivity to inhibition in mesoaccumbal neurons and may partially explainin vivoobservations that ventral tegmental area neurons exhibit longer aversive pauses relative to SNc neurons.

Dopamine neuron dendrites integrate synaptic information arriving from a diverse set of cell classes including excitatory and inhibitory neurons. The majority of synapses formed onto substantia nigra (SNc) dopamine neurons (>70 %) arrive from inhibitory GABAergic neurons [1]. Activation of GABA receptors pauses tonic firing and hyperpolarizes cells. Although the pause in dopamine neuron firing has behavioral relevance during reward omission [2], the hyperpolarization may also enable burst firing through disinhibition [3] or engagement of voltage-gated ion channels [4]. However, it is not clear how hyperpolarization influences dendritic integration. Here we use detailed single-cell computational modeling, patch-clamp electrophysiology, and two-photon calcium imaging to investigate the dendritic response to hyperpolarization. We find that at hyperpolarized potentials, some dopamine neurons respond to brief somatic current injections with a long-lasting depolarizing plateau that is accompanied by a large calcium transient in the dendrites. Because this depolarizing plateau requires prior hyperpolarization, we will refer to it as a hyperpolarization induced afterdepolarization (HI-ADP). Using electrophysiology and calcium imaging, we found that pharmacological block of T-type calcium currents with TTA-P2 completely eliminated the dendritic calcium transient and greatly reduced the size of the HI-ADP. In contrast, blocking L-type calcium channels with nifedipine did not significantly alter the dendritic calcium or size of the HI-ADP. To further investigate the involvement of dendritic T-currents in generating the HI-ADP, we developed a multi-compartmental, multi-channel model of an SNc dopamine neuron in Genesis simulation software. This model contains a spherical soma with two dendritic trees extending from it, each containing identical primary, secondary and tertiary branches. Our simulations showed that a high density of dendritic T-type calcium channels is critical to the generation of the HI-ADP. Specifically, we found that reducing the T-type channel conductance by half throughout the entire cell completely abolished the HI-ADP. On the other hand, removing T-type channels from only one dendritic tree slightly reduced, but did not eliminate the HI-ADP. These simulations show that a high, localized density of T-type channels is more important to the generation of the HI-ADP than the total number of T-type channels in the cell. Further simulations predict that the tightly coupled, electrotonically compact dendrites characteristic of SNc dopamine neurons are also necessary for the production of the HI-ADP. In particular, reducing the membrane input resistance of the model cell eliminated the HI-ADP. Confirming this prediction, our experimental data show that reducing the input resistance of SNc dopamine neurons through activation of G-protein coupled inwardly-rectifying potassium channels (GIRKs) abolished the HI-ADP and reduced the concomitant dendritic calcium transient. In conclusion, we have shown that T-type calcium channels and electrotonically compact dendrites are essential for generating a HI-ADP in SNc dopamine neurons. These HI-ADPs represent an interesting response to hyperpolarization that may be unique to SNc dopamine neurons having the specific combination of high T-type channel density and tight electrotonically compact dendrites. This particular combination of characteristics may allow SNc dopamine neurons to respond to inhibition or the release of inhibition with an increased ability to burst.

Growing evidence supports a critical role for the dorsal striatum in cognitive as well as motor control. Both lesions and in vivo recordings demonstrate a transition in the engaged dorsal striatal subregion, from dorsomedial to dorsolateral, as skill performance shifts from an attentive phase to a more automatic or habitual phase. What are the neural mechanisms supporting the cognitive and behavioral transitions in skill learning? To pursue this question, we used T-maze training during which rats transition from early, attentive (dorsomedial) to late habitual (dorsolateral) performance. Following early or late training, we performed the first direct comparison of bidirectional synaptic plasticity in striatal brain slices, and the first evaluation of striatal synaptic plasticity by hemisphere relative to a learned turn. Consequently, we find that long-term potentiation and long-term depression are independently modulated with learning rather than reciprocally linked as previously suggested. Our results establish that modulation of evoked synaptic plasticity with learning depends on striatal subregion, training stage, and hemisphere relative to the learned turn direction. Exclusive to the contralateral hemisphere, intrinsic excitability is enhanced in dorsomedial relative to dorsolateral medium spiny neurons early in training and population responses are dampened late in training. Neuronal reconstructions indicate dendritic remodeling after training, which may represent a novel form of pruning. In conclusion, we describe region- and hemisphere-specific changes in striatal synaptic, intrinsic, and morphological plasticity which correspond to T-maze learning stages, and which may play a role in the cognitive transition between attentive and habitual strategies. Significance statement: We investigated neural plasticity in dorsal striatum from rats that were briefly or extensively trained on a directional T-maze task. Our results demonstrate that both the extent of training and the direction a rat learns to turn control the location and type of change in synaptic plasticity. In addition, brief training produces changes in neuron excitability only within one striatal subregion, whereas all training produces widespread changes in dendritic morphology. Our results suggest that activity in dorsomedial striatum strengthens the rewarded turn after brief training, whereas activity in dorsolateral striatum suppresses unrewarded turns after extensive training. This study illuminates how plasticity mediates learning using a task recognized for transitioning subjects from attentive to automatic performance.

The striatum of the basal ganglia demonstrates distinctive upstate and downstate membrane potential oscillations during slow-wave sleep and under anesthetic. The upstates generate calcium transients in the dendrites, and the amplitude of these calcium transients depends strongly on the timing of the action potential (AP) within the upstate. Calcium is essential for synaptic plasticity in the striatum, and these large calcium transients during the upstates may control which synapses undergo plastic changes. To investigate the mechanisms that underlie the relationship between calcium and AP timing, we have developed a realistic biophysical model of a medium spiny neuron (MSN). We have implemented sophisticated calcium dynamics including calcium diffusion, buffering, and pump extrusion, which accurately replicate published data. Using this model, we found that either the slow inactivation of dendritic sodium channels (NaSI) or the calcium inactivation of voltage-gated calcium channels (CDI) can cause high calcium corresponding to early APs and lower calcium corresponding to later APs. We found that only CDI can account for the experimental observation that sensitivity to AP timing is dependent on NMDA receptors. Additional simulations demonstrated a mechanism by which MSNs can dynamically modulate their sensitivity to AP timing and show that sensitivity to specifically timed pre- and postsynaptic pairings (as in spike timing-dependent plasticity protocols) is altered by the timing of the pairing within the upstate. These findings have implications for synaptic plasticity in vivo during sleep when the upstate-downstate pattern is prominent in the striatum.

Computational models of biologically realistic neuronal networks have advanced neuroscience in the past 20 years. With an ultimate goal of simulating a whole brain, these networks must become larger and more complex. However, a sheer massive number of neurons do not make a brain. Neurons are all different, with different kinetics, neurotransmitters, and importantly different morphologies. A network can be made by connecting copies of the same cell together, but this kind of homogenous network can only explain so much. Real neuronal networks are heterogeneous and are made up of neurons that follow both intrinsic and extrinsic cues to grow their unique dendritic arbors (Scott and Luo, 2001). In addition to homogenous and heterogeneous network models, hybrid network models have been implemented by creating a small heterogeneous network and replicating it to establish a larger network (Kozloski, 2011). However, modeling studies have shown that homogenous networks act differently than realistic heterogeneous ones (Maki-Marttunen et al., 2011). Because computational neuronal networks need to grow larger to simulate complete brain regions, and because heterogeneity in a network is critical to modeling a realistic brain, algorithms for digitally generating neural morphologies are a necessary step toward this goal. A new paper by Memelli et al. (2013) joins the field of papers providing algorithms for growing digital neurons. Their algorithm can be used to build a network consisting of millions of neurons each with a unique morphology. The current models, L-Neuron (Ascoli et al., 2001), NeuGen2.0 (Wolf et al., 2013), NetMorph (Koene et al., 2009), and CD3X (Zubler and Douglas, 2009) have made great strides in advancing the process of generating digital neurons. These models are all publicly available, and can be used to generate large networks of neurons. Recently L-Neuron was used to generate a 0.5 million cell model of the dentate gyrus (Schneider et al., 2012). Each algorithm has its own specific advantages. NetMorph has a synapse-generating algorithm, NeuGen2.0 is modular and adaptable to new data, and CD3X can isolate intrinsic and extrinsic factors of neuron development by growing the same neurons in different model environments. In combination with the parallelization of simulation software [such as NEURON (Migliore et al., 2006)], these neuron generators are laying the groundwork for enabling massive biologically realistic simulations. Memelli et al. (2013) do not attempt to model the molecular mechanisms of dendritic growth, but instead work to make a concise, computationally efficient model that can capture the structure and variability of realistic morphologies. Their work adds two elements to this field. First, it simplifies the neural growth algorithm to contain a combination of three biologically inspired intrinsic parameters: soma-oriented tropism, dendritic self-avoidance, and membrane stiffness. The three parameters of their growth algorithm are all intrinsic to the cell itself and do not take into account any extrinsic signals that could come from other neurons or physical constraints. Each of these parameters has been previously described, but Memelli et al. are the first to combine them in one simple model. Second, their algorithm is written to be fast and massively parallel, creating the possibility for generating billions of neurons on the IBM Bluegene computer. Their algorithm can generate a neuron in less than two seconds, and when run on parallel cores is capable of generating enough neurons to simulate an entire brain region. Together, these elements fit the need to have morphological diversity within a network as well as the need to have extremely large networks. Each of the current morphology simulators has their particular strengths. The ideal situation would be for Memelli's new algorithm to be incorporated into one of the existing ready-to-use packages. For example, the application of this algorithm within the external constraints of CX3D could help isolate the extrinsic and intrinsic aspects of dendritic arborization. When used together these simulators can help create massive-scale heterogeneous networks for computational modelers and can help investigate how dendrites actually grow.