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Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

Ponzi A, Wickens J - Front Syst Neurosci (2012)

Bottom Line: However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation.Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events.We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

View Article: PubMed Central - PubMed

Affiliation: Neurobiology Research Unit, Okinawa Institute of Science and Technology Okinawa, Japan.

ABSTRACT
The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

No MeSH data available.


Raster plot from a segment of a 174-s time series network simulation with 100 cells under input switching protocol 1 s × 3 stimuli, (see text) cells colored according to assigned cluster. Input strength rC = 0.018 spikes/ms, connectivity ρ = 0.1, tail parameter α = 1.5, synaptic strength bC = 0.001.
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Figure 11: Raster plot from a segment of a 174-s time series network simulation with 100 cells under input switching protocol 1 s × 3 stimuli, (see text) cells colored according to assigned cluster. Input strength rC = 0.018 spikes/ms, connectivity ρ = 0.1, tail parameter α = 1.5, synaptic strength bC = 0.001.

Mentions: Figure 11 shows a segment of a raster plot of all the active cells from a 100 cell network simulation under an stimulus switching protocol. Three different inputs A, B, and C, each of which consists of a set of i = 100 × l = 10000 firing rates, and are applied for 1 s, each alternately and repetitively. All the rates in the matrices ril are drawn independently randomly and then fixed for the duration of the 174 s simulation. The cells in Figure 11 have been ordered by the clustering algorithm with 15 clusters and colored according to their assigned clusters. Vertical lines denote the input switching times. Figure 12 shows the corresponding cluster PSTH locked to stimulus onset time. To construct this Figure the spikes of cells in a given cluster are merged and binned at given time lags from the onset of one of the stimuli, then the number of spikes in a bin is divided by the bin size (10 ms) and the number of cells in the cluster to give PSTH rates per second per cell.


Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

Ponzi A, Wickens J - Front Syst Neurosci (2012)

Raster plot from a segment of a 174-s time series network simulation with 100 cells under input switching protocol 1 s × 3 stimuli, (see text) cells colored according to assigned cluster. Input strength rC = 0.018 spikes/ms, connectivity ρ = 0.1, tail parameter α = 1.5, synaptic strength bC = 0.001.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3306002&req=5

Figure 11: Raster plot from a segment of a 174-s time series network simulation with 100 cells under input switching protocol 1 s × 3 stimuli, (see text) cells colored according to assigned cluster. Input strength rC = 0.018 spikes/ms, connectivity ρ = 0.1, tail parameter α = 1.5, synaptic strength bC = 0.001.
Mentions: Figure 11 shows a segment of a raster plot of all the active cells from a 100 cell network simulation under an stimulus switching protocol. Three different inputs A, B, and C, each of which consists of a set of i = 100 × l = 10000 firing rates, and are applied for 1 s, each alternately and repetitively. All the rates in the matrices ril are drawn independently randomly and then fixed for the duration of the 174 s simulation. The cells in Figure 11 have been ordered by the clustering algorithm with 15 clusters and colored according to their assigned clusters. Vertical lines denote the input switching times. Figure 12 shows the corresponding cluster PSTH locked to stimulus onset time. To construct this Figure the spikes of cells in a given cluster are merged and binned at given time lags from the onset of one of the stimuli, then the number of spikes in a bin is divided by the bin size (10 ms) and the number of cells in the cluster to give PSTH rates per second per cell.

Bottom Line: However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation.Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events.We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

View Article: PubMed Central - PubMed

Affiliation: Neurobiology Research Unit, Okinawa Institute of Science and Technology Okinawa, Japan.

ABSTRACT
The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

No MeSH data available.