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The Integrated Information is a quantitative measure from information theory how tightly all parts of a system are interconnected in terms of information exchange. In this study we show that astrocyte, playing an important role in…

Neurons and Cognition · Quantitative Biology 2019-01-30 Oleg Kanakov , Susanna Gordleeva , Anastasia Ermolaeva , Sarika Jalan , Alexey Zaikin

In the last decade, there have been major advances in clusterless decoding algorithms for neural data analysis. These algorithms use the theory of marked point processes to describe the joint activity of many neurons simultaneously, without…

Neurons and Cognition · Quantitative Biology 2025-12-09 Azar Ghahari , Uri T. Eden

An outstanding problem in neuroscience is to understand how information is integrated across the many modules of the brain. While classic information-theoretic measures have transformed our understanding of feedforward information…

Neurons and Cognition · Quantitative Biology 2019-02-12 Daniel Toker , Friedrich T. Sommer

It has been shown that sets of oscillators in a modular network can exhibit a rich variety of metastable chimera states, in which synchronisation and desynchronisation coexist. Independently, under the guise of integrated information…

Neurons and Cognition · Quantitative Biology 2016-06-28 Pedro A. M. Mediano , Juan Carlos Farah , Murray Shanahan

The aim of this paper is to investigate various information-theoretic measures, including entropy, mutual information, and some systematic measures that based on mutual information, for a class of structured spiking neuronal network. In…

Neurons and Cognition · Quantitative Biology 2019-12-04 Wenjie Li , Yao Li

Information about external world is delivered to the brain in the form of structured in time spike trains. During further processing in higher areas, information is subjected to a certain condensation process, which results in formation of…

Neurons and Cognition · Quantitative Biology 2015-03-17 Alexander K. Vidybida

Most nervous systems encode information about stimuli in the responding activity of large neuronal networks. This activity often manifests itself as dynamically coordinated sequences of action potentials. Since multiple electrode recordings…

Neurons and Cognition · Quantitative Biology 2011-11-09 Kristina Lisa Klinkner , Cosma Rohilla Shalizi , Marcelo F. Camperi

We consider a collection of distributed units that interact with one another through the sending of messages. Each message carries a positive ($+1$) or negative ($-1$) tag and causes the receiving unit to send out messages as a function of…

Neurons and Cognition · Quantitative Biology 2017-01-12 Valmir C. Barbosa

The mutual information between stimulus and spike-train response is commonly used to monitor neural coding efficiency, but neuronal computation broadly conceived requires more refined and targeted information measures of input-output joint…

Neurons and Cognition · Quantitative Biology 2015-04-21 Sarah E. Marzen , Michael R. DeWeese , James P. Crutchfield

The nervous system encodes continuous information from the environment in the form of discrete spikes, and then decodes these to produce smooth motor actions. Understanding how spikes integrate, represent, and process information to produce…

Neural and Evolutionary Computing · Computer Science 2017-11-15 Madhavun Candadai Vasu , Eduardo Izquierdo

A core feature of complex systems is that the interactions between elements in the present causally constrain each-other as the system evolves through time. To fully model all of these interactions (between elements, as well as ensembles of…

Neurons and Cognition · Quantitative Biology 2023-04-26 Thomas F. Varley

There has been increasing interest in the integrated information theory (IIT) ofconsciousness, which hypothesizes that consciousness is integrated information withinneuronal dynamics. However, the current formulation of IIT poses both…

Neurons and Cognition · Quantitative Biology 2017-07-04 Satohiro Tajima , Ryota Kanai

What does the informational complexity of dynamical networked systems tell us about intrinsic mechanisms and functions of these complex systems? Recent complexity measures such as integrated information have sought to operationalize this…

Neural and Evolutionary Computing · Computer Science 2017-07-06 Xerxes D. Arsiwalla , Pedro A. M. Mediano , Paul F. M. J. Verschure

The apparent dichotomy between information-processing and dynamical approaches to complexity science forces researchers to choose between two diverging sets of tools and explanations, creating conflict and often hindering scientific…

Neurons and Cognition · Quantitative Biology 2022-01-26 Pedro A. M. Mediano , Fernando E. Rosas , Juan Carlos Farah , Murray Shanahan , Daniel Bor , Adam B. Barrett

Spiking neural network is a type of artificial neural network in which neurons communicate between each other with spikes. Spikes are identical Boolean events characterized by the time of their arrival. A spiking neuron has internal…

Neural and Evolutionary Computing · Computer Science 2016-02-16 Oleg Y. Sinyavskiy

The activity of neurons within brain circuits has been ubiquitously reported to be correlated. The impact of these correlations on brain function has been extensively investigated. Correlations can in principle increase or decrease the…

Neurons and Cognition · Quantitative Biology 2025-07-24 Miguel Ibáñez-Berganza , Giulio Bondanelli , Stefano Panzeri

The integrated information theory is thought to be a key clue towards the theoretical understanding of consciousness. In this study, we propose a simple numerical model comprising a set of coupled double quantum dots, where the…

Quantum Physics · Physics 2020-09-30 Katsuaki Tanabe

While information processing in complex systems can be described in abstract, general terms, there are cases in which the relation between these computations and the physical substrate of the underlying system is itself of interest.…

Neurons and Cognition · Quantitative Biology 2017-08-16 Pedro A. M. Mediano , Murray Shanahan

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its centre measures that quantify the extent to which a system generates more information than the sum of its parts. While several candidate measures of…

Neurons and Cognition · Quantitative Biology 2019-01-30 Pedro A. M. Mediano , Anil K. Seth , Adam B. Barrett

In spiking neural networks (SNNs), the main unit of information processing is the neuron with an internal state. The internal state generates an output spike based on its component associated with the membrane potential. This spike is then…

Machine Learning · Computer Science 2025-08-11 Sanja Karilanova , Subhrakanti Dey , Ayça Özçelikkale
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