**Effect of synaptic plasticity on functional connectivity and global activity of a cortical network model**

*Renan O. Shimoura, Rodrigo F. O. Pena, and Antonio C. Roque*

*Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, SP, Brazil*

**Keywords:**hierarchical modular networks, cortical network models, intrinsic neuronal diversity, cerebral córtex, graph theory, synaptic plasticity

The cerebral cortex plays essential role in diverse brain functions. The understanding of this role involves the study of collective neural activity patterns under different situations, and how these patterns relate to the structural and functional organization of the cortex. This study has recently received a new impetus with the introduction of the complex networks approach to cortical connectivity. This approach allows to relate measures of neural spiking activity to graph-theoretic measures of network connectivity. It is also known that the dynamics of cortical activity patterns depends on short and long-term synaptic plasticity phenomena. In principle, then, it would be possible to relate measures of cortical spiking activity and of network connectivity to parameters controlling synaptic plasticity dynamics.

The objective of this work is to study the effect of synaptic plasticity rules on the behavior of neural spiking activity patterns in a cortical network model. The idea is to measure changes in neural spiking patterns due to changes in the synaptic strengths among neurons and to relate these to changes in the functional connectivity of the network as disclosed by graph-theoretic measures.

Our cortical network model was composed of excitatory and inhibitory neurons in the proportion of four excitatory cells for each inhibitory cell. Neurons were described by the Izhikevich model. The parameters of the Izhikevich model were adjusted so that the excitatory neurons were of the regular spiking (RS) type and the inhibitory neurons were of the low threshold spiking (LTS) type. Synapses were modeled as event-based, and two types of synaptic dynamics were considered: a simple one in which the synaptic weight received a fixed increment after the pre-synaptic event and decayed exponentially after that (no synaptic plasticity), and one in which the synapse obeyed an asymmetric spike-time-dependent plasticity (STDP) rule (synaptic plasticity). Neurons were organized into four layers (2/3, 4, 5 and 6) with layer- and cell-specific statistical connectivity rules based on published data from the literature. The total number of neurons in the model was about 4,000. The model constitutes a reduced version (scale 1:75) of a cortical column of 3 mm2 of surface area of the visual cortex. Two versions of the model were constructed: one with synapses described by the model with no synaptic plasticity, and the other with synapses described by the model with synaptic plasticity. In both cases, the model was stimulated by external current injection of random amplitude applied to neurons of layer 4 (L4), which is the main input layer of the cortex. The spiking activity of the network was evaluated by measures extracted from the raster plot of the spikes produced by the neurons, e.g. layer-specific and network mean and time-dependent firing rates. The structural and functional connectivities of the network were represented by the respective structural and functional adjacency matrices. The functional adjacency matrix was constructed by taking in consideration neuron pairs with strength of their synaptic coupling above a specific threshold. The topology of the adjacency matrices was characterized by graph-theoretic measures, e.g. clustering coefficient.

We determined a set of parameters for which the spiking activity generated in L4 by the external input propagated to the entire network. This network-wide activity was oscillatory, and we found that its mean frequency was higher for the network version with synaptic plasticity than for the version with no synaptic plasticity. We also found that in the version with synaptic plasticity the formation of clusters of synchronous neural activity was facilitated in comparison with the case with no synaptic plasticity.

Our results suggest that synaptic plasticity may induce changes in the functional connectivity of the cortical network with impact on its global activity.

**Acknowledgments**

This work is part of the activities of the NeuroMat project funded by FAPESP (grant no. 2013/07699-0). ROS is supported by a CAPES MSc scholarship, RFOP is supported by a FAPESP PhD scholarship (grant no. 2013/25667-8), and ACR is supported by a CNPq research productivity grant (no. 306040/2010-7).