Event Abstract

Quantitative network features of the basal ganglia and connectome based population simulations

  • 1 University of Rostock, Anatomy, Germany

The processing of motoric information in the basal ganglia and thalamic nuclei of the rat is related to 11 regions (primary motor cortex (M1), caudate putamen complex (CPu), substantia nigra compact part (SNC), substantia nigra reticular part (SNR), medial globus pallidus (MGP), lateral globus pallidus (LGP), subthalamic nucleus (STh), ventrolateral thalamic nucleus, ventromedial thalamic nuleus, parafascicular nucleus (PF), mediodorsal thalamic nucleus) and sometimes the ventral tegmental area (VTA), accumbens nucleus (AC) and habenular nuclei are considered. These regions have been selected in the rat connectome of the rat connectome (state in mai 2012: 15346 regions, 212823 directed and weighted connections) project realized in neuroVIISAS. The adjacency matrix of these 14 core regions of extrapyramidal motoric processing has large a line density of 67% and a low mean pathlength of 1.3 edges in average.The cluster coefficient is also large (0.735), however, the modularity is low (0.079) indicating that all regions have connections to most others. The CPu has the most inputs (12) and outputs (12) and lowest Shapley rate (-0.23) followed by the SNR (input: 11, output: 11), MGP (input: 10, output: 11), SNC (input: 9, output: 12), subthalamic nucleus (input: 10, output: 11) and VTA (input: 8, output: 13). The frequency of 2 to 14 region-cycles (path where source is the same as target region) indicated that the caudate putamen is involved in most cycles followed by the substantia nigra reticular part and subthalamic nucleus. The statistical analysis of 13 directed 3-motifs and 199 directed 4-motifs in 1000 rewiring simulations offers a significant more frequent appearance of the completely reciprocally connected 3- and 4-motifs. The CPu, STh and SNC are involved in these completely reciprocal motifs most frequently. Interestingly, the latter regions (beside PF) have also local maxima in the communicability matrix. The connections that leads to the large vulnerability of the network is the projection from the ventrolateral thalamic nucleus to the CPu, from the CPu to SNC, VTA, LGP and AC. Using this 14 node network in a population simulation (NEST) containing 1000 IAF neurons per region (20% inhibitory, 80% excitatory, synaptic delay 0.1 ms, total frequency of spike injection into the primary motor cortex: 10 kHz) different patterns of oscillatory responses of different regions were found (Figure 1, column 1 (c 1): distribution of spikes, c 2: # of IAF / region, c 3: # of spikes, c 4: spikes / neuron, c 5: first spike appearance [ms], c 6: distance from spike injection region, c 7: # of firing IAF, c 8: mean interspike interval, c 9: standard deviation of ISI, c 10: coefficient of variation of mean ISI). The spike distribution of the LGP shows the the largest similarity with 8 other regions of the 14 node network, however, the MGP and SNR possess the largest average similarity of spike distributions.
In conclusion, the 14 node network possesses global and local network features that can not been simulated by different randomizations. Not all regions in this network that seem to be highly important with regard to network parameters (CPu) does not generate largest coherency in simulations.

Figure 1

Keywords: Basal Ganglia, connectome, integrate and fire, motif analysis, network parameters, population simulation, rat, Vulnerability

Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012.

Presentation Type: Poster

Topic: Other

Citation: Schmitt O, Eipert P, Kettlitz R, Philipp K and Wree A (2012). Quantitative network features of the basal ganglia and connectome based population simulations. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00005

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Received: 18 Sep 2012; Published Online: 12 Sep 2012.

* Correspondence: Prof. Oliver Schmitt, University of Rostock, Anatomy, Rostock, 18057, Germany, schmitt@med.uni-rostock.de