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Understanding the internal dynamics of Recurrent Neural Networks (RNNs) is crucial for advancing their interpretability and improving their design. This study introduces an innovative information-theoretic method to identify and analyze…

Machine Learning · Computer Science 2025-10-03 Arend Hintze , Asadullah Najam , Jory Schossau

Synchronous neural activity can improve neural processing and is believed to mediate neuronal interaction by providing temporal windows during which information is more easily transferred. We demonstrate a pulse gating mechanism in a…

Neurons and Cognition · Quantitative Biology 2014-10-07 Andrew T. Sornborger , Louis Tao

Organisms move through the world by changing their shape, and here we explore the mapping from shape space to movements in the nematode C. elegans as it crawls on a planar agar surface. We characterize the statistics of the trajectories…

Neurons and Cognition · Quantitative Biology 2016-01-05 Greg J Stephens , Bethany Johnson-Kerner , William Bialek , William S Ryu

Given the inner complexity of the human nervous system, insight into the dynamics of brain activity can be gained from understanding smaller and simpler organisms, such as the nematode C. Elegans. The behavioural and structural biology of…

Neurons and Cognition · Quantitative Biology 2021-07-15 Gonçalo Mestre , Ruxandra Barbulescu , Arlindo L. Oliveira , L. Miguel Silveira

Many animals meander in environments and avoid collisions. How the underlying neuronal machinery can yield robust behaviour in a variety of environments remains unclear. In the fly brain, motion-sensitive neurons indicate the presence of…

Neural and Evolutionary Computing · Computer Science 2021-02-18 Thorben Schoepe , Ella Janotte , Moritz B. Milde , Olivier J. N. Bertrand , Martin Egelhaaf , Elisabetta Chicca

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with…

Neurons and Cognition · Quantitative Biology 2008-12-05 Kilian Koepsell , Friedrich T. Sommer

Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive…

Living entities in a group communicate and transfer information to one another for a variety of reasons. It might be for foraging food, migration, or escaping threats and obstacles, etc. They do so by interacting with each other and also…

Biological Physics · Physics 2024-04-03 Md. Samsuzzaman , Mohammad Hasanuzzaman , Ahmed Sayeed , Arnab Saha

To establish the relationship between locomotory behavior and dynamics of neural circuits in the nematode C. elegans we combined molecular and theoretical approaches. In particular, we quantitatively analyzed the motion of C. elegans with…

Neurons and Cognition · Quantitative Biology 2008-06-10 Jan Karbowski , Gary Schindelman , Chris J. Cronin , Adeline Seah , Paul W. Sternberg

Molecular motors belonging to the kinesin and myosin super family hydrolyze ATP by cycling through a sequence of chemical states. These cytoplasmic motors are dimers made up of two linked identical monomeric globular proteins. Fueled by the…

Biological Physics · Physics 2022-12-28 Ryota Takaki , Mauro L. Mugnai , D. Thirumalai

Caenorhabditis elegans, a free-living soil nematode, propels itself by producing undulatory body motion and displays a rich variety of body shapes and trajectories during its locomotion in complex environments. Here we show that the complex…

We study external, electrical perturbations and their responses in the brain dynamic network of the \textit{Caenorhabditis elegans} soil worm, given by the connectome of its large somatic nervous system. Our analysis is inspired by a…

Neurons and Cognition · Quantitative Biology 2016-02-17 Chris G. Antonopoulos

Information flow between components of a system takes many forms and is key to understanding the organization and functioning of large-scale, complex systems. We demonstrate three modalities of information flow from time series X to time…

Statistical Mechanics · Physics 2018-08-22 Ryan G. James , Blanca Daniella Mansante Ayala , Bahti Zakirov , James P. Crutchfield

Understanding the inner workings of neural networks is essential for enhancing model performance and interpretability. Current research predominantly focuses on examining the connection between individual neurons and the model's final…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Tue M. Cao , Nhat X. Hoang , Hieu H. Pham , Phi Le Nguyen , My T. Thai

Analysing how information flows along the layers of a multilayer perceptron is a topic of paramount importance in the field of artificial neural networks. After framing the problem from the point of view of information theory, in this…

Information Theory · Computer Science 2025-10-17 Giuliano Armano

The relation between EEG rhythms, brain functions, and behavioral correlates is well-established. Some mechanisms underlying rhythm generation are understood, enabling the replication of brain rhythms $in\; silico$. This allows to explore…

Neurons and Cognition · Quantitative Biology 2024-08-02 Gustavo Menesse , Joaquin J. Torres

Correlating neural communication in brain networks with behavior and cognition can provide fundamental insights into the functionality of both healthy and diseased brains. We demonstrate how communication in the brain can be estimated from…

Signal Processing · Electrical Eng. & Systems 2023-06-21 Felix Schwock , Julien Bloch , Les Atlas , Shima Abadi , Azadeh Yazdan-Shahmorad

To push commercial electronics beyond its current size limits, atomic-scale communication channels and logic units need to be designed, making the use of quantum entities an imperative. In this regime, quantum fluctuations naturally become…

Mesoscale and Nanoscale Physics · Physics 2017-04-12 Leonardo Banchi , Joaquin Fernandez-Rossier , Cyrus F. Hirjibehedin , Sougato Bose

The characterisation of neuronal connectivity is one of the most important matters in neuroscience. In this work, we show that a recently proposed informational quantity, the causal mutual information, employed with an appropriate…

Neurons and Cognition · Quantitative Biology 2018-02-14 F. S. Borges , E. L. Lameu , K. C. Iarosz , P. R. Protachevicz , I. L. Caldas , R. L. Viana , E. E. N. Macau , A. M. Batista , M. S. Baptista

Transitional accounts of evolution emphasise a few changes that shape what is evolvable, with dramatic consequences for derived lineages. More recently it has been proposed that cognition might also have evolved via a series of major…

Artificial Intelligence · Computer Science 2025-09-18 Konstantinos Voudouris , Andrew Barron , Marta Halina , Colin Klein , Matishalin Patel