@Article{LameuBoIaPrAnMaBa:2021:ShSpPl,
               author = "Lameu, Ewandson Luiz and Borges, Fernando S. and Iarosz, Kelly C. 
                         and Protachevicz, Paulo R. and Antonopoulos, Chris G. and Macau, 
                         Elbert Einstein Nehrer and Batista, Antonio M.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal do ABC (UFABC)} and {Universidade de 
                         S{\~a}o Paulo (USP)} and {Universidade de S{\~a}o Paulo (USP)} 
                         and {University of Essex} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Estadual de Ponta Grossa 
                         (UEPG)}",
                title = "Short-term and spike-timing-dependent plasticity facilitate the 
                         formation of modular neural networks",
              journal = "Communications in Nonlinear Science and Numerical Simulation",
                 year = "2021",
               volume = "96",
                pages = "e105689",
                month = "May",
             keywords = "short-term plasticity, spike-time dependent plasticity, modular 
                         networks.",
             abstract = "The brain has the phenomenal ability to reorganise itself by 
                         forming new connections among neurons and by pruning others. The 
                         so-called neural or brain plasticity facilitates the modification 
                         of brain structure and function over different time scales. 
                         Plasticity might occur due to external stimuli received from the 
                         environment, during recovery from brain injury, or due to 
                         modifications within the body and brain itself. In this paper, we 
                         study the combined effect of short-term (STP) and 
                         spike-timing-dependent plasticity (STDP) on the synaptic strength 
                         of excitatory coupled Hodgkin-Huxley neurons and show that 
                         plasticity can facilitate the formation of modular neural networks 
                         with complex topologies that resemble those of networks with 
                         preferential attachment properties. In particular, we use an STDP 
                         rule that alters the synaptic coupling intensity based on time 
                         intervals between spikes of postsynaptic and presynaptic neurons. 
                         Previous work has shown that STDP may induce the emergence of 
                         directed connections from high to low frequency spiking neurons. 
                         On the other hand, STP is attributed to the release of 
                         neurotransmitters in the synaptic cleft of neurons that alter its 
                         synaptic efficiency. Our results suggest that the combined effect 
                         of STP and STDP with long recovery times facilitates the formation 
                         of connections among neurons with similar spike frequencies only, 
                         a kind of preferential attachment. We then pursue this further and 
                         show that, when starting with all-to-all neural configurations, 
                         depending on the STP recovery time and distribution of neural 
                         frequencies, modular neural networks can emerge as a direct result 
                         of the combined effect of STP and STDP.",
                  doi = "10.1016/j.cnsns.2020.105689",
                  url = "http://dx.doi.org/10.1016/j.cnsns.2020.105689",
                 issn = "1007-5704",
             language = "en",
           targetfile = "lameu_short.pdf",
        urlaccessdate = "20 maio 2024"
}