{"id":20980,"date":"2026-09-06T18:00:43","date_gmt":"2026-09-06T16:00:43","guid":{"rendered":"https:\/\/scm.iec.cat\/?post_type=conference&#038;p=20980"},"modified":"2026-09-08T13:23:08","modified_gmt":"2026-09-08T11:23:08","slug":"2026-tfm-rosa-maria-delicado","status":"publish","type":"conference","link":"https:\/\/scm.iec.cat\/eng\/conference\/2026-tfm-rosa-maria-delicado\/","title":{"rendered":"2026-TFM-Rosa Maria Delicado"},"content":{"rendered":"<h5>Abstract<\/h5>\n<p>Many complex systems can be described as networks of coupled dynamical systems, formed by a set of units that interact with each other through a certain connection architecture. In this context, it is interesting to study how the interactions between the different units can give rise to collective behaviors and, in particular, under what conditions a state in which all units exhibit synchronized dynamics remains stable or becomes unstable under small perturbations. In this work we study this phenomenon in the context of large-scale brain networks, focusing on how the interaction between brain regions can give rise to complex spatiotemporal activity patterns.<\/p>\n<p>We consider a model formed by 90 brain regions connected according to experimental data of the brain's structural connectivity, where each region is described by excitatory and inhibitory neuronal populations. First we analyze the homogeneous dynamics, in which all regions evolve in a synchronized manner, and we study how it varies depending on external stimulation and on the coupling strength. Bifurcation analysis reveals transitions between stationary states, oscillations, and more complex dynamical regimes, including a sequence of period doublings that points toward the onset of chaos. Subsequently, by means of the Master Stability Function, we study under what conditions these homogeneous states lose stability in the face of small heterogeneous perturbations in the initial conditions of the different brain regions. The results show that these instabilities can give rise to complex spatiotemporal patterns, such as traveling waves and high-dimensional chaos, highlighting how the structure of brain connections can contribute to generating complex collective dynamics.<\/p>","protected":false},"featured_media":0,"parent":0,"template":"","categoria_sessions_conferences":[277],"class_list":["post-20980","conference","type-conference","status-publish","hentry","categoria_sessions_conferences-4a-jornada-tfm-2026"],"acf":[],"_links":{"self":[{"href":"https:\/\/scm.iec.cat\/eng\/wp-json\/wp\/v2\/conference\/20980","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scm.iec.cat\/eng\/wp-json\/wp\/v2\/conference"}],"about":[{"href":"https:\/\/scm.iec.cat\/eng\/wp-json\/wp\/v2\/types\/conference"}],"wp:attachment":[{"href":"https:\/\/scm.iec.cat\/eng\/wp-json\/wp\/v2\/media?parent=20980"}],"wp:term":[{"taxonomy":"categoria_sessions_conferences","embeddable":true,"href":"https:\/\/scm.iec.cat\/eng\/wp-json\/wp\/v2\/categoria_sessions_conferences?post=20980"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}