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We propose a theoretical motivation to quantify actual physiological features, such as the shape index distributions measured by Jones and Palmer in cats and by Ringach in macaque monkeys. We will adopt the Uncertainty Principle associated…

Cell Behavior · Quantitative Biology 2013-03-05 Davide Barbieri , Giovanna Citti , Alessandro Sarti

Most computational accounts of cognitive maps assume that stability is achieved primarily through sensory anchoring, with self-motion contributing to incremental positional updates only. However, biological spatial representations often…

Neurons and Cognition · Quantitative Biology 2025-12-24 Yingchao Yu , Pengfei Sun , Yaochu Jin , Kuangrong Hao , Hao Zhang , Yifeng Zhang , Wenxuan Pan , Wei Chen , Danyal Akarca , Yuchen Xiao

The grid cells (GCs) of the medial entorhinal cortex (MEC) and place cells (PCs) of the hippocampus are key elements of the brain network for the metric representation of space. Currently, any of the existing theoretical models can explain…

Neurons and Cognition · Quantitative Biology 2015-07-01 Andrey Stepanyuk

We propose a model of the functional architecture of curvature-sensitive cells in the primary visual cortex. The model accounts for the modular and hierarchical organization of the cortex, the horizontal connectivity, and the shape of…

Neurons and Cognition · Quantitative Biology 2026-03-23 Giovanna Citti , Vasiliki Liontou

The topologies permitted in joint ocular dominance (OD), orientation preference (OP), and direction preference (DP) maps in the primary visual cortex (V1) are considered, with the aim of finding a maximally symmetric periodic case that can…

Biological Physics · Physics 2021-12-14 X. Liu , P. A. Robinson

We propose a model of the functional architecture of curvature sensible cells in the visual cortex that associates curvature with scale. The feature space of orientation and position is naturally enhanced via its oriented prolongation,…

Neurons and Cognition · Quantitative Biology 2025-04-24 Vasiliki Liontou

Classical models describe primary visual cortex (V1) as a filter bank of orientation-selective linear-nonlinear (LN) or energy models, but these models fail to predict neural responses to natural stimuli accurately. Recent work shows that…

The Context-Content Uncertainty Principle (CCUP) proposes that inference under uncertainty is governed by an entropy asymmetry between context and content: high-entropy contexts must be interpreted through alignment with low-entropy,…

Machine Learning · Computer Science 2025-06-27 Xin Li

Despite their success, modern convolutional neural networks (CNNs) exhibit fundamental limitations, including data inefficiency, poor out-of-distribution generalization, and vulnerability to adversarial perturbations. These shortcomings can…

Neural and Evolutionary Computing · Computer Science 2025-11-25 Brennen A. Hill , Zhang Xinyu , Timothy Putra Prasetio

Coordinating multi-articulated bodies to generate purposeful movement is a formidable computational challenge. Yet the human motor system performs this task robustly in dynamic, uncertain environments, despite noisy and delayed feedback,…

Neurons and Cognition · Quantitative Biology 2026-02-24 Alessandro Salatiello

This paper introduces a unifying framework that links the Context-Content Uncertainty Principle (CCUP) with optimal transport (OT) via primal-dual inference. We propose that cognitive representations are not static encodings but active dual…

Neurons and Cognition · Quantitative Biology 2025-06-19 Xin Li

Just as the arrow of time structures physics, the arrow of inference organizes cognition, directing the flow of information in perception, action, and memory. The Context-Content Uncertainty Principle (CCUP) formalizes this asymmetry,…

Neurons and Cognition · Quantitative Biology 2025-06-12 Xin Li

While our understanding of the way single neurons process chromatic stimuli in the early visual pathway has advanced significantly in recent years, we do not yet know how these cells interact to form stable representations of hue. Drawing…

Neurons and Cognition · Quantitative Biology 2023-04-18 Zily Burstein , David D. Reid , Peter J. Thomas , Jack D. Cowan

Neural codes are binary codes that are used for information processing and representation in the brain. In previous work, we have shown how an algebraic structure, called the {\it neural ring}, can be used to efficiently encode geometric…

Neurons and Cognition · Quantitative Biology 2019-02-14 Carina Curto , Nora Youngs

Mapping of human brain structural connectomes via diffusion MRI offers a unique opportunity to understand brain structural connectivity and relate it to various human traits, such as cognition. However, head displacement during image…

Neurons and Cognition · Quantitative Biology 2024-09-13 Yizi Zhang , Meimei Liu , Zhengwu Zhang , David Dunson

Orientation selectivity is a remarkable feature of the neurons located in the primary visual cortex. Provided that the visual neurons acquire orientation selectivity through activity-dependent Hebbian learning, the development process could…

Neurons and Cognition · Quantitative Biology 2016-01-20 Myoung Won Cho

Predictive coding has emerged as an influential normative model of neural computation, with numerous extensions and applications. As such, much effort has been put into mapping PC faithfully onto the cortex, but there are issues that remain…

Neurons and Cognition · Quantitative Biology 2023-03-07 Siavash Golkar , Tiberiu Tesileanu , Yanis Bahroun , Anirvan M. Sengupta , Dmitri B. Chklovskii

There has been great progress in understanding of anatomical and functional microcircuitry of the primate cortex. However, the fundamental principles of cortical computation - the principles that allow the visual cortex to bind retinal…

Computer Vision and Pattern Recognition · Computer Science 2016-08-24 Micah Richert , Dimitry Fisher , Filip Piekniewski , Eugene M. Izhikevich , Todd L. Hylton

Top-down feedback in cortex is critical for guiding sensory processing, which has prominently been formalized in the theory of hierarchical predictive coding (hPC). However, experimental evidence for error units, which are central to the…

Neurons and Cognition · Quantitative Biology 2022-11-23 Fabian A. Mikulasch , Lucas Rudelt , Michael Wibral , Viola Priesemann

We propose to use bifurcation theory and pattern formation as theoretical probes for various hypotheses about the neural organization of the brain. This allows us to make predictions about the kinds of patterns that should be observed in…

Pattern Formation and Solitons · Physics 2015-05-13 Pascal Chossat , Olivier Faugeras