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Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum.

ABSTRACT: Neuron behavior results from the interplay between networks of biochemical processes and electrical signaling. Synaptic plasticity is one of the neuronal properties emerging from such an interaction. One of the current approaches to study plasticity is to model either its electrical aspects or its biochemical components. Among the chief reasons are the different time scales involved, electrical events happening in milliseconds while biochemical cascades respond in minutes or hours. In order to create multiscale models taking in consideration both aspects simultaneously, one needs to synchronize the two models, and exchange relevant variable values. We present a new event-driven algorithm to synchronize different neuronal models, which decreases computational time and avoids superfluous synchronizations. The algorithm is implemented in the TimeScales framework. We demonstrate its use by simulating a new multiscale model of the Medium Spiny Neuron of the Neostriatum. The model comprises over a thousand dendritic spines, where the electrical model interacts with the respective instances of a biochemical model. Our results show that a multiscale model is able to exhibit changes of synaptic plasticity as a result of the interaction between electrical and biochemical signaling. Our synchronization strategy is general enough to be used in simulations of other models with similar synchronization issues, such as networks of neurons. Moreover, the integration between the electrical and the biochemical models opens up the possibility to investigate multiscale process, like synaptic plasticity, in a more global manner, while taking into account a more realistic description of the underlying mechanisms.

SUBMITTER: Mattioni M

PROVIDER: S-EPMC3700997 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of 10 ~ 20% and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around 15% connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics - it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation.

Project description:The classical motor symptoms of Parkinson's disease (PD) are caused by degeneration of dopaminergic neurons in the substantia nigra, which is followed by secondary dendritic pruning and spine loss at striatal medium spiny neurons (MSN). We hypothesize that these morphological changes at MSN underlie at least in part long-term motor complications in PD patients. In order to define the potential benefits and limitations of dopamine substitution, we tested in a mouse model whether dendritic pruning and spine loss can be reversible when dopaminergic axon terminals regenerate. In order to induce degeneration of nigrostriatal dopaminergic neurons we used the toxicity of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) in C57BL/6J mice; 30 mg/kg MPTP was applied i.p. on five consecutive days. In order to assess the consequences of dopamine depletion, mice were analyzed 21 days after the last injection. In order to test reversibility of MSN changes we exploited the property of this model that striatal axon terminals regenerate by sprouting within 90 days and analyzed a second cohort 90 days after MPTP. Degeneration of dopaminergic neurons was confirmed by counting TH-positive neurons in the substantia nigra and by analyzing striatal catecholamines. Striatal catecholamine recovered 90 days after MPTP. MSN morphology was visualized by Golgi staining and quantified as total dendritic length, number of dendritic branch points, and density of dendritic spines. All morphological parameters of striatal MSN were reduced 21 days after MPTP. Statistical analysis indicated that dendritic pruning and the reduction of spine density represent two distinct responses to dopamine depletion. Ninety days after MPTP, all morphological changes recovered. Our findings demonstrate that morphological changes in striatal MSN resulting from dopamine depletion are reversible. They suggest that under optimal conditions, symptomatic dopaminergic therapy might be able to prevent maladaptive plasticity and long-term motor complications in PD patients.

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Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum.

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