Gorka Zamora-López

Gorka Zamora-López
University Pompeu Fabra | UPF · Center of Brain and Cognition (CBC)

Ph.D.

About

56
Publications
11,549
Reads
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2,023
Citations
Introduction
My research interests lie at the cross-roads between neuroscience and the theory of complex networks. I am particularly interested in understanding behaviour from a global and integrative perspective. Brain connectivity should help us understand how different parts of the brain communicate with each other.
Additional affiliations
October 2004 - July 2010
Universität Potsdam
Education
October 2004 - February 2009
Universität Potsdam
Field of study
  • Complex Networks / Brain Connectivity
October 2002 - June 2003
University of Oulu
Field of study
  • Theoretical Physics / Computation / Biophysics
September 1997 - October 2003

Publications

Publications (56)
Article
Full-text available
Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated) from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration). The corticocortical networks of cats and macaque monkeys display three prominent...
Article
Full-text available
The intrinsic relationship between the architecture of the brain and the range of sensory and behavioral phenomena it produces is a relevant question in neuroscience. Here, we review recent knowledge gained on the architecture of the anatomical connectivity by means of complex network analysis. It has been found that cortico-cortical networks displ...
Article
Full-text available
The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the c...
Article
Full-text available
Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for oth...
Article
Full-text available
Among the many features of natural and man-made complex networks the small-world phenomenon is a relevant and popular one. But, how small is a small-world network and how does it compare to others? Despite its importance, a reliable and comparable quantification of the average pathlength of networks has remained an open challenge over the years. He...
Preprint
The study of the brain’s static and dynamical activity is opening a valuable source of assistance for the clinical assessment of patients with disorders of consciousness. For example, glucose uptake and dysfunctional spread of naturalistic and synthetic stimuli has proven useful to characterize hampered consciousness. However, understanding of the...
Preprint
Full-text available
The study of the brain’s dynamical activity is opening a valuable source of assistance for the clinical diagnosis of patients with disorders of consciousness (DOC). For example, dysfunctional spread of naturalistic and synthetic stimuli has proven useful to characterize hampered consciousness. However, understanding of the mechanisms behind loss of...
Article
Full-text available
Low-level states of consciousness are characterized by disruptions of brain activity that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we study fMRI brain dynamics from patients that suffered brain injuries leading to a disorder...
Article
Full-text available
During the sleep-wake cycle, the brain undergoes profound dynamical changes, which manifest subjectively as transitions between conscious experience and unconsciousness. Yet, neurophysiological signatures that can objectively distinguish different consciousness states based are scarce. Here, we show that differences in the level of brain-wide signa...
Article
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The ability of different groups of cortical neurons to engage in causal interactions that are at once differentiated and integrated results in complex dynamic patterns. Complexity is low during periods of unconsciousness (deep sleep, anesthesia, unresponsive wakefulness syndrome) in which the brain tends to generate a stereotypical pattern consisti...
Preprint
Full-text available
Low-level states of consciousness are characterised by disruptions of brain dynamics that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we studied the fMRI brain dynamics from patients that suffered brain injuries leading to a di...
Article
Full-text available
Neuroimaging techniques are now widely used to study human cognition. The functional associations between brain areas have become a standard proxy to describe how cognitive processes are distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been developed to overcome the limitations of...
Article
Neuroimaging techniques such as MRI have been widely used to explore the associations between brain areas. Structural connectivity (SC) captures the anatomical pathways across the brain and functional connectivity (FC) measures the correlation between the activity of brain regions. These connectivity measures have been much studied using network th...
Preprint
Full-text available
Neuroimaging techniques are increasingly used to study brain cognition in humans. Beyond their individual activation, the functional associations between brain areas have become a standard proxy to describe how information is distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been de...
Article
Our environment is full of statistical regularities, and we are attuned to learn about these regularities by employing Statistical Learning (SL), a domain-general ability that enables the implicit detection of probabilistic regularities in our surrounding environment. The role of brain connectivity on SL has been previously explored, highlighting t...
Preprint
Full-text available
Among all characteristics exhibited by natural and man-made networks the small-world phenomenon is surely the most relevant and popular. But despite its significance, a reliable and comparable quantification of the question "how small is a small-world network and how does it compare to others" has remained a difficult challenge to answer. Here we e...
Preprint
Full-text available
Neuroimaging techniques such as MRI have been widely used to explore the associations between brain areas. Structural connectivity (SC) captures the anatomical pathways across the brain and functional connectivity (FC) measures the correlation between the activity of brain regions. These connectivity measures have been much studied using network th...
Article
Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such a...
Preprint
Full-text available
Graph theory has become a widely used toolbox to investigate complex networks estimated from real-life data. A specific direction of research has used collective dynamics obtained for propagation-like processes, such as oscillators and random walks, in order to characterize intricate topologies. However, the study of complex network dynamics lacks...
Preprint
Graph theory has become a widely used toolbox to investigate complex networks estimated from real-life data. A specific direction of research has used collective dynamics obtained for propagation-like processes, such as oscillators and random walks, in order to characterize intricate topologies. However, the study of complex network dynamics lacks...
Preprint
Full-text available
Intrinsic brain activity is characterized by highly structured co-activations between different regions, whose origin is still under debate. In this paper, we address the question whether it is possible to unveil how the underlying anatomical connectivity shape the brain's spontaneous correlation structure. We start from the assumption that in orde...
Article
Full-text available
The major structural ingredients of the brain and neural connectomes have been identified in recent years. These are (i) the arrangement of the networks into modules and (ii) the presence of highly connected regions (hubs) forming so-called rich-clubs. It has been speculated that the combination of these features allows the brain to segregate and i...
Article
Full-text available
Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey ch...
Article
Full-text available
The analysis of complex networks is devoted to the statistical characterization of the topology of graphs at different scales of organization in order to understand their functionality. While the modular structure of networks has become an essential element to better apprehend their complexity, the efforts to characterize the mesoscale of networks...
Article
Full-text available
Although the most common clinical presentation of multiple sclerosis (MS) is the so called Relapsing-Remitting MS (RRMS), the molecular mechanisms responsible for its progression are currently unknown. To tackle this problem, a whole-genome gene expression analysis has been performed on RRMS patients. The comparative analysis of the Affymetrix Huma...
Article
Full-text available
Complex networks provide an excellent framework for studying the function of the human brain activity. Yet estimating functional networks from measured signals is not trivial, especially if the data is non-stationary and noisy as it is often the case with physiological recordings. In this article we propose a method that uses the local rank structu...
Article
Full-text available
We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connecti...
Article
Full-text available
Recent studies of brain connectivity and language with methods of complex networks have revealed common features of organization. These observations open a window to better understand the intrinsic relationship between the brain and the mind by studying how information is either physically stored or mentally represented. In this paper, we review so...
Thesis
Full-text available
The recent discovery of an intricate and nontrivial interaction topology among the elements of a wide range of natural systems has altered the manner we understand complexity. For example, the axonal fibres transmitting electrical information between cortical regions form a network which is neither regular nor completely random. Their structure see...
Article
The recent years have seen the emergence of graph theoretical analysis of complex, functional brain networks estimated from neurophysiological measurements. The research has mainly focused on the graph characterization of the resting-state/default network, and its potential for clinical application. Functional resting-state networks usually display...
Article
Full-text available
Recent studies have pointed out the importance of transient synchronization between widely distributed neural assemblies to understand conscious perception. These neural assemblies form intricate networks of neurons and synapses whose detailed map for mammals is still unknown and far from our experimental capabilities. Only in a few cases, for exam...
Article
Full-text available
The modular structure is pervasive in many complex networks of interactions observed in natural, social and technological sciences. Its study sheds light on the relation between the structure and the function of complex systems. Generally speaking, modules are islands of highly connected nodes separated by a relatively small number of links. Every...
Article
Full-text available
Understanding the functional dynamics of the mammalian brain is one of the central aims of modern neuroscience. Mathematical modeling and computational simulations of neural networks can help in this quest. In recent publications, a multilevel model has been presented to simulate the resting-state dynamics of the cortico-cortical connectivity of th...
Article
Full-text available
Over the last decade, we have witnessed the birth of a new movement of interest and research in the study of complex networks. These networks often have irregular structural properties, but also encompass rich dynamics. The interplay between the network topological structure and the associated dynamics attracts a lot of interest. In this research l...
Article
Full-text available
Sensory information entering the nervous system follows independent paths of processing such that specific features are individually detected. However, sensory perception, awareness, and cognition emerge from the combination of information. Here we have analyzed the corticocortical network of the cat, looking for the anatomical substrate which perm...
Article
Full-text available
Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. A challenging task is to understand the implications of such network structures on the functional organisation of the brain activities. We investigate synchronisation dynamics on the corticocortical network of the cat by modelling...
Article
The generation of random networks is a very common problem in complex network research. In this paper, we have studied the correlation nature of several real networks and found that, typically, a large number of links are deterministic, i.e. they cannot be randomized. This finding permits fast generation of ensembles of maximally random networks wi...
Article
Full-text available
Although most of the real networks contain a mixture of directed and bidirectional (reciprocal) connections, the reciprocity r has received little attention as a subject of theoretical understanding. We study the expected reciprocity of networks with arbitrary input and output degree sequences and given 2-node degree correlations by means of statis...
Chapter
In this chapter, Graph Theory will be introduced using cat corticocortical connectivity data as an example. Distinct graph measures will be summarized and examples of their usage shown, as well as hints about the kind of information one can obtain from them. Special attention will be paid to conflicting points in graph theory that often generate co...
Article
Full-text available
The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and funct...
Article
Full-text available
How do diverse dynamical patterns arise from the topology of complex networks? We study synchronization dynamics in the cortical brain network of the cat, which displays a hierarchically clustered organization, by modeling each node (cortical area) with a subnetwork of interacting excitable neurons. We find that in the biologically plausible regime...
Article
The problem of the evaluation of brain connectivity has become a fundamental one in the neurosciences during the latest years, as a way to understand the organization and the interaction of several cortical areas during the execution of cognitive or motor tasks. Following an approach that derives from the graph theory, we analyzed the architectural...

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