A complexity measure for selective matching of signals by the brain.
about
From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0Qualia: the geometry of integrated informationNetwork, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune systemAn information integration theory of consciousnessAnatomical connectivity influences both intra- and inter-brain synchronizationsDwelling quietly in the rich club: brain network determinants of slow cortical fluctuations.Integrated information increases with fitness in the evolution of animatsBrain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear modelDegeneracy and complexity in biological systems.Theories and measures of consciousness: an extended framework.Measures of degeneracy and redundancy in biological networksEvolution of integrated causal structures in animats exposed to environments of increasing complexity.Stimulus set meaningfulness and neurophysiological differentiation: a functional magnetic resonance imaging study.Critical Changes in Cortical Neuronal Interactions in Anesthetized and Awake Rats.Alzheimer's disease: models of computation and analysis of EEGs.The neural correlates of consciousness: an update.Hypothesizing the body's genius to trigger and self-organize its healing: 25 years using a standardized neurophysics therapy.The use of information theory in evolutionary biology.Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration.A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.The Effect of Electroencephalogram (EEG) Reference Choice on Information-Theoretic Measures of the Complexity and Integration of EEG Signals.Integrated Information and State Differentiation.Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks.Brain organization and psychodynamics.Sleep-Dependent Synaptic Down-Selection (II): Single-Neuron Level Benefits for Matching, Selectivity, and Specificity.Influence of affect on social-information processing.Synchronization in complex networks with a modular structure.Computationally efficient measure of topological redundancy of biological and social networks.From Complex Networks to Intelligent SystemsNew Paths for the Application of DCI in Social Sciences: Theoretical Issues Regarding an Empirical Analysis
P2860
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P2860
A complexity measure for selective matching of signals by the brain.
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on April 1996
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
A complexity measure for selective matching of signals by the brain.
@en
A complexity measure for selective matching of signals by the brain.
@nl
type
label
A complexity measure for selective matching of signals by the brain.
@en
A complexity measure for selective matching of signals by the brain.
@nl
prefLabel
A complexity measure for selective matching of signals by the brain.
@en
A complexity measure for selective matching of signals by the brain.
@nl
P2860
P356
P1476
A complexity measure for selective matching of signals by the brain.
@en
P2093
Edelman GM
P2860
P304
P356
10.1073/PNAS.93.8.3422
P407
P577
1996-04-01T00:00:00Z