Information decomposition and the informational architecture of the brain

AI Luppi, FE Rosas, PAM Mediano, DK Menon… - Trends in Cognitive …, 2024 - cell.com
To explain how the brain orchestrates information-processing for cognition, we must
understand information itself. Importantly, information is not a monolithic entity. Information …

[HTML][HTML] The strength of weak integrated information theory

PAM Mediano, FE Rosas, D Bor, AK Seth… - Trends in Cognitive …, 2022 - cell.com
The integrated information theory of consciousness (IIT) is divisive: while some believe it
provides an unprecedentedly powerful approach to address the 'hard problem', others …

Quantifying & modeling multimodal interactions: An information decomposition framework

PP Liang, Y Cheng, X Fan, CK Ling… - Advances in …, 2024 - proceedings.neurips.cc
The recent explosion of interest in multimodal applications has resulted in a wide selection
of datasets and methods for representing and integrating information from different …

Control of criticality and computation in spiking neuromorphic networks with plasticity

B Cramer, D Stöckel, M Kreft, M Wibral… - Nature …, 2020 - nature.com
The critical state is assumed to be optimal for any computation in recurrent neural networks,
because criticality maximizes a number of abstract computational properties. We challenge …

IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks

P Wollstadt, JT Lizier, R Vicente, C Finn… - arxiv preprint arxiv …, 2018 - arxiv.org
The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for
efficient inference of networks and their node dynamics from multivariate time series data …

Sequential transmission of task-relevant information in cortical neuronal networks

NA Francis, S Mukherjee, L Koçillari, S Panzeri… - Cell Reports, 2022 - cell.com
Cortical processing of task-relevant information enables recognition of behaviorally
meaningful sensory events. It is unclear how task-related information is represented within …

Gaussian partial information decomposition: Bias correction and application to high-dimensional data

P Venkatesh, C Bennett, S Gale… - Advances in …, 2024 - proceedings.neurips.cc
Recent advances in neuroscientific experimental techniques have enabled us to
simultaneously record the activity of thousands of neurons across multiple brain regions …

Information flow between motor cortex and striatum reverses during skill learning

SM Lemke, M Celotto, R Maffulli, K Ganguly, S Panzeri - Current Biology, 2024 - cell.com
The coordination of neural activity across brain areas during a specific behavior is often
interpreted as neural communication involved in controlling the behavior. However, whether …

A rigorous information-theoretic definition of redundancy and relevancy in feature selection based on (partial) information decomposition

P Wollstadt, S Schmitt, M Wibral - Journal of Machine Learning Research, 2023 - jmlr.org
Selecting a minimal feature set that is maximally informative about a target variable is a
central task in machine learning and statistics. Information theory provides a powerful …

An information-theoretic approach to self-organisation: Emergence of complex interdependencies in coupled dynamical systems

F Rosas, PAM Mediano, M Ugarte, HJ Jensen - Entropy, 2018 - mdpi.com
Self-organisation lies at the core of fundamental but still unresolved scientific questions, and
holds the promise of de-centralised paradigms crucial for future technological …