Search · four archives
Search · four archives
22 papers · ranked by Valyu relevance
Byron H. Price, Jeffrey P. Gavornik
While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information…
Linshan Wang, Reza Farivar
Research suggests that spatial frequency (SF) channels in the visual system operate with a degree of independence. However, the independence model has been questioned by evidence of non-additive effects in compound gratings, indicating complex interactions between SF channels. These studies, however, typically employ…
Stefan F. Bucher, Adam M. Brandenburger
Title: Significance Divisive normalization is a ubiquitous computation commonly thought to be an implementation of the efficient coding principle. Despite empirical evidence that it reduces statistical redundancy present in naturalistic stimuli, making the relationship between this neural code and the statistics of a…
Veronika Koren, Simone Blanco Malerba, Tilo Schwalger, Stefano Panzeri
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be…
Veronika Koren, Alan J. Emanuel, Stefano Panzeri
How do biological neural systems efficiently encode, transform and propagate information between the sensory periphery and the sensory cortex about sensory features evolving at different time scales? Are these computations efficient in normative information processing terms? While previous work has suggested that…
William Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington
The efficient coding hypothesis presents a compelling success story for theoretical and systems neuroscience. It marshals a unifying idea, that neural codes can be understood as efficient encodings of natural stimuli, to explain phenomena from across sensory systems, sometimes with exquisite precision. However, similar…
Duho Sihn, Oh-Sang Kwon, Sung-Phil Kim
Introduction Efficient coding that minimizes informational redundancy of neural representations is a widely accepted neural coding principle. Despite the benefit, maximizing efficiency in neural coding can make neural representation vulnerable to random noise. One way to achieve robustness against random noise is…
Miguel de Llanza Varona, Christopher L. Buckley, Beren Millidge
Rate-Distortion Theory Authors: ['Miguel de Llanza Varona' 'Christopher L. Buckley' 'Beren Millidge'] Abstract. Organisms have to keep track of the information in the environment that is relevant for adaptive behaviour. Transmitting information in an economical and efficient way becomes crucial for limitedresourced…
Zhou, Dale, Noh, Sharon Mina + 10 more
The ability to discriminate similar visual stimuli has been used as an important index of memory function. This ability is widely thought to be supported by expanding the dimensionality of relevant neural codes, such that neural representations for the similar stimuli are maximally distinct, or "separated." An…
Tianhe Wang, Yifan Fang, David Whitney
A paramount challenge for the brain is to precisely model the world and control behavior within the confines of limited encoding capacities. Efficient coding theory posits a unified framework for understanding how neural systems enhance encoding accuracy by tuning to environmental statistics. While this theory has been…
Duho Sihn, Sung-Phil Kim
Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given…
Gaia Tavoni
The existence of pathways connecting different sensory modalities in the brain challenges the traditional view of sensory systems as operating independently. However, the reasons and mechanisms underlying these interactions remain largely unknown, and no computational framework currently addresses these questions. We…
Ananya Passi, Brian S. Robinson, Michael F. Bonner
Biological visual systems learn from limited experience, unlike deep learning models that rely on millions of training images. What learning principles make this possible? We tested whether efficient coding, the idea that neural representations capture the statistical structure of natural inputs, can build a hierarchy…
Jesús Malo, Gholamreza Anbarjafari
Biological neural networks for color vision (also known as color appearance models) consist of a cascade of linear + nonlinear layers that modify the linear measurements at the retinal photo-receptors leading to an internal (nonlinear) representation of color that correlates with psychophysical experience. The basic…
Dittrich, Christian, Kinne, Jennifer Flygare
Existing frameworks converge on the centrality of compression to intelligence but leave underspecified why this process enforces the discovery of causal structure rather than superficial statistical patterns. We introduce a two-level framework to address this gap. The Information-Theoretic Imperative (ITI) establishes…
Elsa Dupraz, Ismaila Salihou Adamou, Reza Asvadi, Tad Matsumoto
Testing Authors: ['Elsa Dupraz' 'Ismaila Salihou Adamou' 'Reza Asvadi' 'Tad Matsumoto'] Abstract—This paper investigates practical coding schemes for Distributed Hypothesis Testing (DHT). While the literature has extensively analyzed the information-theoretic performance of DHT and established bounds on Type-II error…
Thach V. Bui
Neural coding is an important tool to discover the inner workings of mind. In this work, we propose and consider a simple but novel self-decoding model for neural coding based on the principle that the neuron body represents ongoing stimulus while dendrites are used to store that stimulus as a memory. In particular…
Ismaila Salihou Adamou, Elsa Dupraz, Reza Asvadi, Tad Matsumoto
—This paper addresses the design of practical shortlength coding schemes for Distributed Hypothesis Testing (DHT). While most prior work on DHT has focused on informationtheoretic analyses—deriving bounds on Type-II error exponents via achievability schemes based on quantization and quantizebinning—the practical…
Tadahiro Taniguchi
Understanding the emergence of symbol systems, especially language, requires the construction of a computational model that reproduces both the developmental learning process in everyday life and the evolutionary dynamics of symbol emergence throughout history. This study introduces the collective predictive coding…
Authors not listed
The exponentially growing body of scientific literature has made manual synthesis and hypothesis generation increasingly impractical, introducing an essential bottleneck in the scientific discovery pipeline. While large language models (LLMs) have unprecedented capability to process and summarize textual knowledge…
Authors not listed
Quantum state tomography has been widely used to reconstruct the quantum state of a system from a set of informationally-complete measurements. Obtaining enough information about, e.g., the wavefunction of a molecule allows its complete characterization. On the other hand, deep learning models for molecular property…
Miloje Rakočević
In some previous works (2018a,b; 2019, 2021a,b, 2022) we presented a new type of mirror symmetry, expressed in the set of protein amino acids; such a symmetry, that it simultaneously represents the semiotic essence of the genetic code. In this paper we provide new evidences that the genetic code represents the unity of…