arXiv subjects

Osame Kinouchi

Publications and source records attributed to Osame Kinouchi.

At least 37 records · Page 2Linked to original sources

arXiv2013

Lobby index as a network centrality measure

We study the lobby index (l-index for short) as a local node centrality measure for complex networks. The l-inde is compared with degree (a local measure), betweenness and Eigenvector centralities (two global measures) in the case of biological network (Yeast interaction protein-protein network) and a linguistic network (Moby Thesaurus II). In both networks, the l-index has poor correlation with betweenness but correlates with degree and Eigenvector. Being a local measure, one can take advantage by using the l-index because it carries more information about its neighbors when compared with degree centrality, indeed it requires less time to compute when compared with Eigenvector centrality. Results suggests that l-index produces better results than degree and Eigenvector measures for ranking purposes, becoming suitable as a tool to perform this task.

cs.SI↗

arXiv2013

Critical Avalanches and Subsampling in Map-based Neural Networks

We investigate the synaptic noise as a novel mechanism for creating critical avalanches in the activity of neural networks. We model neurons and chemical synapses by dynamical maps with a uniform noise term in the synaptic coupling. An advantage of utilizing maps is that the dynamical properties (action potential profile, excitability properties, post synaptic potential summation etc.) are not imposed to the system, but occur naturally by solving the system equations. We discuss the relevant neuronal and synaptic properties to achieve the critical state. We verify that networks of excitatory by rebound neurons with fast synapses present power law avalanches. We also discuss the measuring of neuronal avalanches by subsampling our data, shedding light on the experimental search for Self-Organized Criticality in neural networks.

cond-mat.dis-nn↗

arXiv2012

Statistical Physics approach to dendritic computation: The excitable-wave mean-field approximation

We analytically study the input-output properties of a neuron whose active dendritic tree, modeled as a Cayley tree of excitable elements, is subjected to Poisson stimulus. Both single-site and two-site mean-field approximations incorrectly predict a non-equilibrium phase transition which is not allowed in the model. We propose an excitable-wave mean-field approximation which shows good agreement with previously published simulation results [Gollo et al., PLoS Comput. Biol. 5(6) e1000402 (2009)] and accounts for finite-size effects. We also discuss the relevance of our results to experiments in neuroscience, emphasizing the role of active dendrites in the enhancement of dynamic range and in gain control modulation.

q-bio.NC↗

arXiv2010

Dreams, endocannabinoids and itinerant dynamics in neural networks: re elaborating Crick-Mitchison unlearning hypothesis

In this work we reevaluate and elaborate Crick-Mitchison's proposal that REM-sleep corresponds to a self-organized process for unlearning attractors in neural networks. This reformulation is made at the face of recent findings concerning the intense activation of the amygdalar complex during REM-sleep, the role of endocannabinoids in synaptic weakening and neural network models with itinerant associative dynamics. We distinguish between a neurological REM-sleep function and a related evolutionary/behavioral dreaming function. At the neurological level, we propose that REM-sleep regulates excessive plasticity and weakens over stable brain activation patterns, specially in the amygdala, hippocampus and motor systems. At the behavioral level, we propose that dream narrative evolved as exploratory behavior made in a virtual environment promoting "emotional (un)learning", that is, habituation of emotional responses, anxiety and fear. We make several experimental predictions at variance with those of Memory Consolidation Hipothesis. We also predict that the "replay" of cells ensembles is done at an increasing faster pace along REM-sleep.

cond-mat.dis-nn↗

arXiv2010

Hirsch index as a network centrality measure

We study the h Hirsch index as a local node centrality measure for complex networks in general. The h index is compared with the Degree centrality (a local measure), the Betweenness and Eigenvector centralities (two non-local measures) in the case of a biological network (Yeast interaction protein-protein network) and a linguistic network (Moby Thesaurus II) as test environments. In both networks, the Hirsch index has poor correlation with Betweenness centrality but correlates well with Eigenvector centrality, specially for the more important nodes that are relevant for ranking purposes, say in Search Machine Optimization. In the thesaurus network, the h index seems even to outperform the Eigenvector centrality measure as evaluated by simple linguistic criteria.

physics.soc-ph↗

arXiv2010

Scientific Metaphors in the journalistic discourse

Scientific education and divulgation not only amplify people's vocabulary and repertory of scientific concepts but, at the same time, promote the diffusion of certain conceptual and cognitive metaphors. Here we make some hypothesis about this process, proposing a classification in terms of visible, invisible, basic and derived metaphors. We focus our attention in contemporary and classical physics metaphors applied to psychological and socio-economical phenomena, and we study two exemplar cases through an exhaustive exam of the online content of large Brazilian journalistic portals. Finally, we present implications and suggestions from the cognitive metaphor theory for the scientific education and divulgation process.

physics.hist-ph↗

arXiv2009

Active dendrites enhance neuronal dynamic range

Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the last decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of active dendritic trees is a highly non-linear function of their afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease of dynamic range.

q-bio.NC↗

arXiv2008

The Nonequilibrium Nature of Culinary Evolution

Food is an essential part of civilization, with a scope that ranges from the biological to the economic and cultural levels. Here we study the statistics of ingredients and recipes taken from Brazilian, British, French, and Medieval cookbooks. We find universal distributions with scale invariant behavior. We propose a copy-mutate process to model culinary evolution that fits very well our empirical data. We find a cultural founder effect produced by the nonequilibrium dynamics of the model. Both the invariant and idiosyncratic aspects of culture are accounted by our model, which may have applications in other kinds of evolutionary processes.

physics.soc-ph↗

arXiv2007

Optimal Dynamical Range of Excitable Networks at Criticality

A recurrent idea in the study of complex systems is that optimal information processing is to be found near bifurcation points or phase transitions. However, this heuristic hypothesis has few (if any) concrete realizations where a standard and biologically relevant quantity is optimized at criticality. Here we give a clear example of such a phenomenon: a network of excitable elements has its sensitivity and dynamic range maximized at the critical point of a non-equilibrium phase transition. Our results are compatible with the essential role of gap junctions in olfactory glomeruli and retinal ganglionar cell output. Synchronization and global oscillations also appear in the network dynamics. We propose that the main functional role of electrical coupling is to provide an enhancement of dynamic range, therefore allowing the coding of information spanning several orders of magnitude. The mechanism could provide a microscopic neural basis for psychophysical laws.

q-bio.NC↗

arXiv2007

Scaling law for the transient behavior of type-II neuron models

We study the transient regime of type-II biophysical neuron models and determine the scaling behavior of relaxation times $τ$ near but below the repetitive firing critical current, $τ\simeq C (I_c-I)^{-Δ}$. For both the Hodgkin-Huxley and Morris-Lecar models we find that the critical exponent is independent of the numerical integration time step and that both systems belong to the same universality class, with $Δ= 1/2$. For appropriately chosen parameters, the FitzHugh-Nagumo model presents the same generic transient behavior, but the critical region is significantly smaller. We propose an experiment that may reveal nontrivial critical exponents in the squid axon.

q-bio.NC↗

arXiv2006

Chaotic itinerancy, temporal segmentation and spatio-temporal combinatorial codes

We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (``patterns'') we add a slow coupling dynamics that makes the visited patterns to loose stability leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated.

q-bio.NC↗

arXiv2005

An index to quantify an individual's scientific research valid across disciplines

The number h of papers with at least h citations has been proposed to evaluate individual's scientific research production. This index is robust in several ways but yet strongly dependent on the research field. We propose a complementary index hI = h^2/N_t, with N_t being the total number of authors in the considered h papers. A researcher with index hI has hI papers with at least hI citation if he/she had published alone. We have obtained the rank plots of h and hI for four Brazilian scientific communities. Contrasting to the h-index curve, the hI index present a perfect data collapse into a unique allowing comparison among different research areas.

physics.soc-ph↗

arXiv2005

Universal Behavior of a Research Productivity Index

Indexes that account for good representations of an individual's productivity are theme of major importance for the evaluation and comparison among researchers. Recently, a new index was proposed combining productivity with impact such that a researcher with index h has h papers with at least h citations. A drawback of this is the sensitivity to the research field. Here we propose a new index (hI) that accounts for the coauthorship effect. The statistics of h and hI are presented for Brazilian research. We have found a universal curve for different disciplines, allowing a comparison among scientists of different research areas.

physics.soc-ph↗

arXiv2004

Physics of Psychophysics: Stevens and Weber-Fechner laws are transfer functions of excitable media

Sensory arrays made of coupled excitable elements can improve both their input sensitivity and dynamic range due to collective non-linear wave properties. This mechanism is studied in a neural network of electrically coupled (e.g. via gap junctions) elements subject to a Poisson signal process. The network response interpolates between a Weber-Fechner logarithmic law and a Stevens power law depending on the relative refractory period of the cell. Therefore, these non-linear transformations of the input level could be performed in the sensory periphery simply due to a basic property: the transfer function of excitable media.

cond-mat.dis-nn↗

arXiv2004

Intensity Coding in Two-Dimensional Excitable Neural Networks

In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.

q-bio.NC↗

arXiv2003

Thesaurus as a complex network

A thesaurus is one, out of many, possible representations of term (or word) connectivity. The terms of a thesaurus are seen as the nodes and their relationship as the links of a directed graph. The directionality of the links retains all the thesaurus information and allows the measurement of several quantities. This has lead to a new term classification according to the characteristics of the nodes, for example, nodes with no links in, no links out, etc. Using an electronic available thesaurus we have obtained the incoming and outgoing link distributions. While the incoming link distribution follows a stretched exponential function, the lower bound for the outgoing link distribution has the same envelope of the scientific paper citation distribution proposed by Albuquerque and Tsallis. However, a better fit is obtained by simpler function which is the solution of Ricatti's differential equation. We conjecture that this differential equation is the continuous limit of a stochastic growth model of the thesaurus network. We also propose a new manner to arrange a thesaurus using the ``inversion method''.

cond-mat.stat-mech↗

arXiv2003

Exploratory Behavior, Trap Models and Glass Transitions

A random walk is performed on a disordered landscape composed of $N$ sites randomly and uniformly distributed inside a $d$-dimensional hypercube. The walker hops from one site to another with probability proportional to $\exp [- βE(D)]$, where $β= 1/T$ is the inverse of a formal temperature and $E(D)$ is an arbitrary cost function which depends on the hop distance $D$. Analytic results indicate that, if $E(D) = D^{d}$ and $N \to \infty$, there exists a glass transition at $β_d = π^{d/2}/Γ(d/2 + 1)$. Below $T_d$, the average trapping time diverges and the system falls into an out-of-equilibrium regime with aging phenomena. A Lévy flight scenario and applications to exploratory behavior are considered.

cond-mat.dis-nn↗

arXiv2003

Escaping from cycles through a glass transition

A random walk is performed over a disordered media composed of $N$ sites random and uniformly distributed inside a $d$-dimensional hypercube. The walker cannot remain in the same site and hops to one of its $n$ neighboring sites with a transition probability that depends on the distance $D$ between sites according to a cost function $E(D)$. The stochasticity level is parametrized by a formal temperature $T$. In the case $T = 0$, the walk is deterministic and ergodicity is broken: the phase space is divided in a ${\cal O}(N)$ number of attractor basins of two-cycles that trap the walker. For $d = 1$, analytic results indicate the existence of a glass transition at $T_1 = 1/2$ as $N \to \infty$. Below $T_1$, the average trapping time in two-cycles diverges and out-of-equilibrium behavior appears. Similar glass transitions occur in higher dimensions choosing a proper cost function. We also present some results for the statistics of distances for Poisson spatial point processes.

cond-mat.dis-nn↗