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PUBLICADO2 de dez de 2011
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osame kinouchi Edit
Professor of Statistical Physics, USP Edit
Complex Systems - Complex Networks - Neuroscience - Computational Biology -Astrobiology  Edit
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Citation indices

All Since 2006
Citations 960 648
h-index 15 13
i10-index 25 14
Citations to my articles
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 1-59

Title / Author Cited by Year
Is it possible to compare researchers with different scientific interests?
PD Batista, MG Campiteli, O Kinouchi
Scientometrics 68 (1), 179-189
187 2006
Optimal dynamical range of excitable networks at criticality
O Kinouchi, M Copelli
Nature Physics 2 (5), 348-351
121 2006
Optimal generalization in perceptions
O Kinouchi, N Caticha
Journal of Physics A: Mathematical and General 25, 6243
120 1992
Deterministic walks in random networks: An application to thesaurus graphs
O Kinouchi, AS Martinez, GF Lima, GM Lourenço, S Risau-Gusman
Physica A: Statistical Mechanics and its Applications 315 (3), 665-676
52 2002
Deterministic walks in random media
GF Lima, AS Martinez, O Kinouchi
Physical review letters 87 (1), 10603
43 2001
Physics of psychophysics: Stevens and Weber-Fechner laws are transfer functions of excitable media
M Copelli, AC Roque, RF Oliveira, O Kinouchi
Physical Review E 65 (6), 060901
33 2002
Lower bounds on generalization errors for drifting rules
O Kinouchi, N Caticha
Journal of Physics A: Mathematical and General 26, 6161
32 1993
Robustness of scale invariance in models with self-organized criticality
O Kinouchi, CPC Prado
Physical Review E 59 (5), 4964
30 1999
Thesaurus as a complex network
A de Jesus Holanda, I Torres Pisa, O Kinouchi, A Souto Martinez, E Eduardo …
Physica A: Statistical Mechanics and its Applications 344 (3), 530-536
30 2004
Escaping from cycles through a glass transition
S Risau-Gusman, AS Martinez, O Kinouchi
Physical Review E 68 (1), 016104
25 2003
Learning algorithm that gives the Bayes generalization limit for perceptrons
O Kinouchi, N Caticha
Physical Review E 54 (1), 54-57
22 1996
Universal behavior of a research productivity index
PD Batista, MG Campiteli, O Kinouchi, AS Martinez
Arxiv preprint physics/0510142
22 2005
Equivalence between learning in noisy perceptrons and tree committee machines
M Copelli, O Kinouchi, N Caticha
Physical Review E 53 (6), 6341
21 1996
Exploratory behavior, trap models, and glass transitions
AS Martinez, O Kinouchi, S Risau-Gusman
Physical Review E 69 (1), 017101
21 2004
On the random neighbor Olami-Feder-Christensen slip-stick model
O Kinouchi, STR Pinho, CPC Prado
Arxiv preprint cond-mat/9805175
18 1998
Signal compression in the sensory periphery
M Copelli, RF Oliveira, A Carlos Roque, O Kinouchi
Neurocomputing 65, 691-696
15 2005
Intensity coding in two-dimensional excitable neural networks
M Copelli, O Kinouchi
Physica A: Statistical Mechanics and its Applications 349 (3), 431-442
15 2005
Noise robustness in multilayer neural networks
M Copelli, R Eichhorn, O Kinouchi, M Biehl, R Simonetti, P Riegler, N Caticha
EPL (Europhysics Letters) 37, 427
14 1997
Statistical mechanics of online learning of drifting concepts: a variational approach
R Vicente, O Kinouchi, N Caticha
Machine learning 32 (2), 179-201
14 1998
Deterministic walks as an algorithm of pattern recognition
MG Campiteli, PD Batista, O Kinouchi, AS Martinez
Physical Review E 74 (2), 026703
13 2006
Modeling neurons by simple maps
O Kinouchi, MHR Tragtenberg
International Journal of Bifurcation and Chaos in Applied Sciences and …
13 1996
Optimal pruning in neural networks
DML Barbato, O Kinouchi
Physical Review E 62 (6), 8387
12 2000
On-line versus off-line learning in the linear perceptron: A comparative study
O Kinouchi, N Caticha
Physical Review E 52 (3), 2878
12 1995
A minimal model for excitable and bursting elements
SM Kuva, GF Lima, O Kinouchi, MHR Tragtenberg, AC Roque
Neurocomputing 38, 255-261
11 2001
Biased learning in boolean perceptrons
O Kinouchi, N Caticha
Physica A: Statistical Mechanics and its Applications 185 (1-4), 411-416
10 1992
Absence of self-organized criticality in a random-neighbor version of the OFC stick-slip model
STR Pinho, CPC Prado, O Kinouchi
Physica A: Statistical Mechanics and its Applications 257 (1), 488-494
9 1998
Active dendrites enhance neuronal dynamic range
LL Gollo, O Kinouchi, M Copelli
PLoS computational biology 5 (6), e1000402
8 2009
Time ordering in the evolution of information processing and modulation systems
N Caticha, O Kinouchi
Philosophical Magazine B 77 (5), 1565-1574
6 1998
Stability diagrams for bursting neurons modeled by three-variable maps
M Copelli, MHR Tragtenberg, O Kinouchi
Physica A: Statistical Mechanics and its Applications 342 (1), 263-269
5 2004
The non-equilibrium nature of culinary evolution
O Kinouchi, RW Diez-Garcia, AJ Holanda, P Zambianchi, AC Roque
New Journal of Physics 10, 073020
5 2008
Persistence solves Fermi paradox but challenges SETI projects
O Kinouchi
Arxiv preprint cond-mat/0112137
5 2001
Scaling law for the transient behavior of type-II neuron models
MAD Roa, M Copelli, O Kinouchi, N Caticha
Physical Review E 75 (2), 021911
5 2007
Chaotic itinerancy, temporal segmentation and spatio-temporal combinatorial codes
JR Dias, RF Oliveira, O Kinouchi
Physica D: Nonlinear Phenomena 237 (1), 1-5
4 2008
An index to quantify an individual’s scientific research valid across disciplines
PD Batista, MG Campiteli, O Kinouchi, AS Martinez
Arxiv preprint physics/0509048
4 2005
Basic word statistics for information retrieval: thesaurus as a complex network
A de Jesus Holanda, IT Pisa, O Kinouchi, AS Martinez, EES Ruiz
1oWorkshop em Tecnologia da Informaçao e Linguagem Humana in: Anais Sibgrapi …
1 2003
Learning a spin glass: determining Hamiltonians from metastable states
SM Kuva, O Kinouchi, N Caticha
Physica A: Statistical Mechanics and its Applications 257 (1), 28-35
1 1998
A precursor of the sciences of complexity in the XIX century
O Kinouchi
Arxiv preprint physics/0110041
1 2001
A reliable measure of similarity based on dependency for short time series: an application to gene expression networks
M Campiteli, F Soriani, I Malavazi, O Kinouchi, C Pereira, G Goldman
BMC bioinformatics 10 (1), 270
2009
Enhanced dynamic range in a sensory network of excitable elements
M Copelli, AC Roque, RF Oliveira, O Kinouchi
Arxiv preprint cond-mat/0112395
2001
An index to quantify an individual’s scientific research valid across disciplines
P Diniz Batista, M Guimaraes Campiteli, O Kinouchi, A Souto Martinez
2005
Physics of psychophysics: optimal dynamic range of critical excitable networks
M Copelli, O Kinouchi
BMC Neuroscience 8, 1-1
2007
On-line versus O-line Learning in the Linear Perceptron: a Comparative Study
O Kinouchi, N Catichay
A Statistical Physics approach to dendritic computation: the excitable-wave mean-field approximation
LL Gollo, O Kinouchi, M Copelli
Arxiv preprint arXiv:1109.2036
2011
Absence of self-organized criticality in a random-neighbor version of the OFC stick-slip model
STR Pinho, CPC Prado, O Kinouchi
Arxiv preprint adap-org/9711002
1997
Scientific Metaphors in the journalistic discourse
O Kinouchi, AA Mandrá
Arxiv preprint arXiv:1006.1128
2010
Dynamical phase diagrams of neural networks with asymmetric couplings
MN Tamashiro, O Kinouchi, SR Salinas
Physical Review E 55 (6), 7344
1997
PART 2-CHAOS, HYDRODYNAMICS, PLASMAS, AND RELATED TOPICS-BRIEF REPORTS-General methods of statistical physics-Exploratory behavior, trap models, and glass transitions
AS Martinez, O Kinouchi, S Risau-Gusman
Physical Review-Section E-Statistical Nonlinear and Soft Matter Physics 69 …
2004
Extended dynamical range as a collective property of excitable cells
O Kinouchi
Arxiv preprint cond-mat/0108404
2001
Self-organized (quasi-) criticality: the extremal Feder and Feder model
O Kinouchi
Arxiv preprint cond-mat/9802311
1998
RENATO VICENTE rvicente@ if. usp. br Instituto de F sica, Universidade de São Paulo, CP66318, CEP 05315-970, São Paulo, SP Brazil
O KINOUCHI, N CATICHA
Signal propagation and neuronal avalanches analysis in networks of formal neurons
M Girardi-Schappo, M Tragtenberg, O Kinouchi
BMC Neuroscience 12 (Suppl 1), P172
2011
On the robustness of scale invariance in SOC models
O Kinouchi, CPC Prado
Arxiv preprint cond-mat/9901222
1999
Universal Behavior of a Research Productivity Index
P Diniz Batista, M Guimaraes Campiteli, O Kinouchi, A Souto Martinez
2005
Deterministic walks in random media: evidence of generic scale invariance
GF Lima, AS Martinez, O Kinouchi
Arxiv preprint cond-mat/0005446
2000
Dreams, endocannabinoids and itinerant dynamics in neural networks: re elaborating Crick-Mitchison unlearning hypothesis
O Kinouchi, RR Kinouchi
Arxiv preprint cond-mat/0208590
2002
Índices de centralidade na comunidade de Física
LDH Soares, O Kinouchi
Hirsch index as a network centrality measure
MG Campiteli, AJ Holanda, PRC Soles, LHD Soares, O Kinouchi
Arxiv preprint arXiv:1005.4803
2010
Índice de Hirsch como medida de centralidade em Redes Complexas
PRC Soles, O Kinouchi
UNIVERSIDADE DE s/’10 PAULO% P U BLI C AQ 6 E S
O Kinouchi, N Caticha

Leis de potência em avalanches neuronais confirmadas

Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches

Andreas Klaus1,2,3*, Shan Yu1, Dietmar Plenz1

1 Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America, 2 Nobel Institute for Neurophysiology, Department of Neuroscience, Karolinska Institute, Stockholm, Sweden, 3 Stockholm Brain Institute, Stockholm, Sweden

Abstract Top

The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to −1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesis for neuronal avalanches by using more stringent statistical analyses. In particular, we performed the following steps: (i) analysis of finite-size scaling to identify scale-free dynamics in neuronal avalanches, (ii) model parameter estimation to determine the specific exponent of the power law, and (iii) comparison of the power law to alternative model distributions. Consistent with critical state dynamics, avalanche size distributions exhibited robust scaling behavior in which the maximum avalanche size was limited only by the spatial extent of sampling (“finite size” effect). This scale-free dynamics suggests the power law as a model for the distribution of avalanche sizes. Using both the Kolmogorov-Smirnov statistic and a maximum likelihood approach, we found the slope to be close to −1.5, which is in line with previous reports. Finally, the power law model for neuronal avalanches was compared to the exponential and to various heavy-tail distributions based on the Kolmogorov-Smirnov distance and by using a log-likelihood ratio test. Both the power law distribution without and with exponential cut-off provided significantly better fits to the cluster size distributions in neuronal avalanches than the exponential, the lognormal and the gamma distribution. In summary, our findings strongly support the power law scaling in neuronal avalanches, providing further evidence for critical state dynamics in superficial layers of cortex.