4.5 Review

Revisiting neural information, computing and linking capacity

Related references

Note: Only part of the references are listed.
Article Multidisciplinary Sciences

Brain-inspired computing needs a master plan

A. Mehonic et al.

Summary: Brain-inspired computing technologies offer high energy efficiency and the ability to handle increasing volumes of unstructured and noisy data. To achieve this, a coordinated plan is needed to bring research communities together and provide the necessary funding, focus, and support.

NATURE (2022)

Article Physics, Multidisciplinary

Towards Generalizing the Information Theory for Neural Communication

Janos Vegh et al.

Summary: The use of information theory in neuroscience is vital for understanding neural communication and decoding neural coding. There is a discrepancy in the representation of information in the brain and debates on how it is transmitted. The paper challenges the assumption that neural communication follows the principles of electronic communication and proposes an alternative interpretation of information in biology. Additionally, the paper introduces a time-aware approach to information theory, providing evidence for the importance of processes in neural operations.

ENTROPY (2022)

Article Mathematical & Computational Biology

On the Role of Speed in Technological and Biological Information Transfer for Computations

Janos Vegh et al.

Summary: In all implementations of computing, the speed of information propagation is limited by the speed of its carrier. This limitation requires consideration of transfer time between computing units. Different mathematical methods result in different descriptions of computing systems' features. Our findings align with experimental evidence in both biological and technological computing.

ACTA BIOTHEORETICA (2022)

Article Computer Science, Artificial Intelligence

Interpretability of artificial neural network models in artificial intelligence versus neuroscience

Kohitij Kar et al.

Summary: This article discusses the differences and connections between neuroscientists and AI researchers in interpreting artificial neural networks (ANNs).

NATURE MACHINE INTELLIGENCE (2022)

Article Multidisciplinary Sciences

Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number

William B. Levy et al.

Summary: Darwinian evolution tends to lead to energy-efficient outcomes, while energy limitations can impact computation processes, whether neural or digital. By focusing on neural computation from an energy-efficient perspective, the study explores the relationship between energy consumption and computational function in the brain, revealing new insights into energy partitioning and efficiency in cortical computation.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

Article Multidisciplinary Sciences

Cytoskeletal Filaments Deep Inside a Neuron Are not Silent: They Regulate the Precise Timing of Nerve Spikes Using a Pair of Vortices

Pushpendra Singh et al.

Summary: Hodgkin and Huxley demonstrated that a neuron's membrane alone can generate and transmit nerve spikes, with the time modulation mechanism still being a mystery. Filaments hold millisecond time gaps between membrane spikes while transmitting microsecond signals of electromagnetic vortices.

SYMMETRY-BASEL (2021)

Article Physics, Multidisciplinary

On Entropy, Information, and Conservation of Information

Yunus A. Cengel

Summary: The term entropy is used in different contexts with different meanings, causing misunderstandings and confusion. While the mathematical expressions of entropy in statistical thermodynamics and information theory are similar, the physical meanings differ significantly.

ENTROPY (2021)

Review Computer Science, Artificial Intelligence

Which scaling rule applies to large artificial neural networks Technological limitations for biology-imitating computing

Janos Vegh

Summary: The limitations of cooperating and communicating computing systems, the impact of processor speed on computing performance, the inefficiency of large machines, and the challenges in mimicking biological operations using artificial neural networks are discussed. The low computational performance of AI systems and the influence of communication methods on efficiency are highlighted. The study also introduces ideas to estimate the efficiency of devices or applications in advance, considering the nonlinear scaling of processor-based ANN systems.

NEURAL COMPUTING & APPLICATIONS (2021)

Article Computer Science, Interdisciplinary Applications

Revising the Classic Computing Paradigm and Its Technological Implementations

Janos Vegh

Summary: Today's computing is no longer based on John von Neumann's classic paradigm, as technological developments have rendered it invalid. However, the computing model is still perfect. This paper discusses how to handle cases where transfer time cannot be neglected, and how to explain the issues in today's computing by omitting wrong omissions.

INFORMATICS-BASEL (2021)

Review Computer Science, Artificial Intelligence

Fitting elephants in modern machine learning by statistically consistent interpolation

Partha P. Mitra

Summary: This article discusses the good generalization ability of modern machine learning methods when interpolating noisy data, introduces the phenomenon of statistically consistent interpolation (SCI), explains the reasons for successful data interpolation, and compares the different approaches of modern machine learning, traditional physical theory, and biological brains in modeling natural phenomena.

NATURE MACHINE INTELLIGENCE (2021)

Article Computer Science, Hardware & Architecture

Finally, how many efficiencies the supercomputers have? And, what do they measure?

Janos Vegh

JOURNAL OF SUPERCOMPUTING (2020)

Article Multidisciplinary Sciences

Documentary follows implosion of billion-euro brain project

Alison Abbott

NATURE (2020)

Review Physics, Applied

Physics for neuromorphic computing

Danijela Markovic et al.

NATURE REVIEWS PHYSICS (2020)

Article Psychology, Biological

Is coding a relevant metaphor for the brain?

Romain Brette

BEHAVIORAL AND BRAIN SCIENCES (2019)

Article Multidisciplinary Sciences

Biological conservation law as an emerging functionality in dynamical neuronal networks

Boris Podobnik et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2017)

Article Mathematical & Computational Biology

Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series

Fleur Zeldenrust et al.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2017)

Article Neurosciences

Quantification of bursting and synchrony in cultured hippocampal neurons

Lawrence N. Eisenman et al.

JOURNAL OF NEUROPHYSIOLOGY (2015)

Article Mathematical & Computational Biology

The meaning of spikes from the neuron's point of view: predictive homeostasis generates the appearance of randomness

Christopher D. Fiorillo et al.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2014)

Article Biochemical Research Methods

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Biswa Sengupta et al.

PLOS COMPUTATIONAL BIOLOGY (2014)

Review Computer Science, Cybernetics

An introductory review of information theory in the context of computational neuroscience

Mark D. McDonnell et al.

BIOLOGICAL CYBERNETICS (2011)

Article Mathematical & Computational Biology

Transfer entropy-a model-free measure of effective connectivity for the neurosciences

Raul Vicente et al.

JOURNAL OF COMPUTATIONAL NEUROSCIENCE (2011)

Article Computer Science, Information Systems

A Mathematical Theory of Energy Efficient Neural Computation and Communication

Toby Berger et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2010)

Article Computer Science, Hardware & Architecture

Roofline: An Insightful Visual Performance Model for Multicore Architectures

Samuel Williams et al.

COMMUNICATIONS OF THE ACM (2009)

Article Multidisciplinary Sciences

Transient Responses to Rapid Changes in Mean and Variance in Spiking Models

Peyman Khorsand et al.

PLOS ONE (2008)

Article Biochemical Research Methods

Neural coding of natural stimuli: Information at sub-millisecond resolution

Ilya Nemenman et al.

PLOS COMPUTATIONAL BIOLOGY (2008)

Review Physics, Multidisciplinary

Causality detection based on information-theoretic approaches in time series analysis

Katerina Hlavackova-Schindler et al.

PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2007)

Article Biotechnology & Applied Microbiology

What is a hidden Markov model?

SR Eddy

NATURE BIOTECHNOLOGY (2004)

Article Computer Science, Artificial Intelligence

Neural coding and decoding: communication channels and quantization

AG Dimitrov et al.

NETWORK-COMPUTATION IN NEURAL SYSTEMS (2001)

Article Computer Science, Artificial Intelligence

Redundancy reduction revisited

H Barlow

NETWORK-COMPUTATION IN NEURAL SYSTEMS (2001)

Review Neurosciences

Energy as a constraint on the coding and processing of sensory information

SB Laughlin

CURRENT OPINION IN NEUROBIOLOGY (2001)

Article Computer Science, Artificial Intelligence

Synergy in a neural code

N Brenner et al.

NEURAL COMPUTATION (2000)