Rebekah C. Evans

The Effects of NMDA Subunit Composition on Calcium Influx and Spike Timing-Dependent Plasticity in Striatal Medium Spiny Neurons

Calcium through NMDA receptors (NMDARs) is necessary for the long-term potentiation (LTP) of synaptic strength; however, NMDARs differ in several properties that can influence the amount of calcium influx into the spine. These properties, such as sensitivity to magnesium block and conductance decay kinetics, change the receptors response to spike timing dependent plasticity (STDP) protocols, and thereby shape synaptic integration and information processing. This study investigates the role of GluN2 subunit differences on spine calcium concentration during several STDP protocols in a model of a striatal medium spiny projection neuron (MSPN). The multi-compartment, multi-channel model exhibits firing frequency, spike width, and latency to first spike similar to current clamp data from mouse dorsal striatum MSPN. We find that NMDAR-mediated calcium is dependent on GluN2 subunit type, action potential timing, duration of somatic depolarization, and number of action potentials. Furthermore, the model demonstrates that in MSPNs, GluN2A and GluN2B control which STDP intervals allow for substantial calcium elevation in spines. The model predicts that blocking GluN2B subunits would modulate the range of intervals that cause long term potentiation. We confirmed this prediction experimentally, demonstrating that blocking GluN2B in the striatum, narrows the range of STDP intervals that cause long term potentiation. This ability of the GluN2 subunit to modulate the shape of the STDP curve could underlie the role that GluN2 subunits play in learning and development.

Synchronized firing of fast-spiking interneurons is critical to maintain balanced firing between direct and indirect pathway neurons of the striatum

The inhibitory circuits of the striatum are known to be critical for motor function, yet their contributions to Parkinsonian motor deficits are not clear. Altered firing in the globus pallidus suggests that striatal medium spiny neurons (MSN) of the direct (D1 MSN) and indirect pathway (D2 MSN) are imbalanced during dopamine depletion. Both MSN classes receive inhibitory input from each other and from inhibitory interneurons within the striatum, specifically the fast-spiking interneurons (FSI). To investigate the role of inhibition in maintaining striatal balance, we developed a biologically-realistic striatal network model consisting of multicompartmental neuron models: 500 D1 MSNs, 500 D2 MSNs and 49 FSIs. The D1 and D2 MSN models are differentiated based on published experiments of individual channel modulations by dopamine, with D2 MSNs being more excitable than D1 MSNs. Despite this difference in response to current injection, in the network D1 and D2 MSNs fire at similar frequencies in response to excitatory synaptic input. Simulations further reveal that inhibition from FSIs connected by gap junctions is critical to produce balanced firing. Although gap junctions produce only a small increase in synchronization between FSIs, removing these connections resulted in significant firing differences between D1 and D2 MSNs, and balanced firing was restored by providing synchronized cortical input to the FSIs. Together these findings suggest that desynchronization of FSI firing is sufficient to alter balanced firing between D1 and D2 MSNs.

Calcium: Amplitude, Duration, or Location?

Calcium plays a role in long-term plasticity by triggering postsynaptic signaling pathways for both the strengthening (LTP) and weakening (LTD) of synapses. Since these are opposing processes, several hypotheses have been developed to explain how calcium can trigger LTP in some situations and LTD in others. These hypotheses fall broadly into three categories, based on the amplitude of calcium concentration, the duration of the calcium elevation, and the location of the calcium influx. Here we review the experimental evidence for and against each of these hypotheses and the recent computational models utilizing each. We argue that with new experimental techniques for the precise visualization of calcium and new computational techniques for the modeling of calcium diffusion, it is time to take a new look at the location hypothesis.

Multimodal Plasticity in Dorsal Striatum While Learning a Lateralized Navigation Task.

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.

EVOLUTION OF PILED-UP COMPRESSIONS IN MODELED CORONAL MASS EJECTION SHEATHS AND THE RESULTING SHEATH STRUCTURES

We study coronal mass ejection (CME)-driven shocks and the resulting post-shock structures in the lower corona (2-7 R ☉). Two CMEs are erupted by modified Titov-Demoulin (TD) and Gibson-Low (GL) type flux ropes (FRs) with the Space Weather Modeling Framework. We observe a substantial pile-up of density compression and a narrow region of plasma depletion layer (PDL) in the simulations. As the CME/FR moves and expands in the solar wind medium, it pushes the magnetized material lying ahead of it. Hence, the magnetic field lines draping around the CME front are compressed in the sheath just ahead of the CME. These compressed field lines squeeze out the plasma sideways, forming PDL in the region. Solar plasma being pushed and displaced from behind forms a strong piled-up compression (PUC) of density downstream of the PDL. Both CMEs have comparable propagation speeds, while GL has larger expansion speed than TD due to its higher initial magnetic pressure. We argue that high CME expansion speed along with high solar wind density in the region is responsible for the large PUC found in the lower corona. In case of GL, the PUC is much wider, although the density compression ratio for both the cases is comparable. Although these simulations artificially initiate out-of-equilibrium CMEs and drive them in an artificial solar wind solution, we predict that PUCs, in general, will be large in the lower corona. This should affect the ion profiles of the accelerated solar energetic particles.

Sensitivity to theta-burst timing permits LTP in dorsal striatal adult brain slice

Long-term potentiation (LTP) of excitatory afferents to the dorsal striatum likely occurs with learning to encode new skills and habits, yet corticostriatal LTP is challenging to evoke reliably in brain slice under physiological conditions. Here we test the hypothesis that stimulating striatal afferents with theta-burst timing, similar to recently reported in vivo temporal patterns corresponding to learning, evokes LTP. Recording from adult mouse brain slice extracellularly in 1 mM Mg(2+), we find LTP in dorsomedial and dorsolateral striatum is preferentially evoked by certain theta-burst patterns. In particular, we demonstrate that greater LTP is produced using moderate intraburst and high theta-range frequencies, and that pauses separating bursts of stimuli are critical for LTP induction. By altering temporal pattern alone, we illustrate the importance of burst-patterning for LTP induction and demonstrate that corticostriatal long-term depression is evoked in the same preparation. In accord with prior studies, LTP is greatest in dorsomedial striatum and relies on N-methyl-d-aspartate receptors. We also demonstrate a requirement for both Gq- and Gs/olf-coupled pathways, as well as several kinases associated with memory storage: PKC, PKA, and ERK. Our data build on previous reports of activity-directed plasticity by identifying effective values for distinct temporal parameters in variants of theta-burst LTP induction paradigms. We conclude that those variants which best match reports of striatal activity during learning behavior are most successful in evoking dorsal striatal LTP in adult brain slice without altering artificial cerebrospinal fluid. Future application of this approach will enable diverse investigations of plasticity serving striatal-based learning.

Dynamic modulation of spike timing-dependent calcium influx during corticostriatal upstates

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.

Calcium-dependent inactivation of calcium channels in the medial striatum increases at eye opening

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.

Growing a garden of neurons

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 Memellis 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.

Removal of area CA3 from hippocampal slices induces postsynaptic plasticity at Schaffer collateral synapses that normalizes CA1 pyramidal cell discharge

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.