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Constraining the many biological parameters that govern cortical dynamics is computationally and conceptually difficult because of the curse of dimensionality. This paper addresses these challenges by proposing (1) a novel data-informed…

Neurons and Cognition · Quantitative Biology 2021-12-30 Zhuo-Cheng Xiao , Kevin K. Lin , Lai-Sang Young

Mathematical optimization is one of the cornerstones of modern engineering research and practice. Yet, throughout all application domains, mathematical optimization is, for the most part, considered to be a numerical discipline.…

Optimization and Control · Mathematics 2024-01-09 Adrian Hauswirth , Zhiyu He , Saverio Bolognani , Gabriela Hug , Florian Dörfler

The visual information in V1 is processed by an array of modules called orientation preference columns. In some species including humans, orientation columns are radially arranged around singular points like the spokes of a wheel, that are…

Mathematical Physics · Physics 2010-07-09 Davide Barbieri , Giovanna Citti , Gonzalo Sanguinetti , Alessandro Sarti

Despite differences in brain sizes and cognitive niches among mammals, their cerebral cortices posses many common features and regularities. These regularities have been a subject of experimental investigation in neuroanatomy for the last…

Neurons and Cognition · Quantitative Biology 2007-05-23 Jan Karbowski

The mammalian brain is a metabolically expensive device, and evolutionary pressures have presumably driven it to make productive use of its resources. For sensory areas, this concept has been expressed more formally as an optimality…

Neurons and Cognition · Quantitative Biology 2016-03-02 Deep Ganguli , Eero P. Simoncelli

In this paper a novel architecture for cortical computation has been proposed. This architecture is composed of computing paths consisting of neurons and synapses only. These paths have been decomposed into lateral, longitudinal and…

Neurons and Cognition · Quantitative Biology 2007-12-12 Kaushik Majumdar

Making sense of the world and acting in it relies on building simplified mental representations that abstract away aspects of reality. This principle of cognitive mapping is universal to agents with limited resources. Living organisms,…

Artificial Intelligence · Computer Science 2025-04-30 Marta Kryven , Cole Wyeth , Aidan Curtis , Kevin Ellis

An important component of computer vision research is object detection. In recent years, there has been tremendous progress in the study of construction site images. However, there are obvious problems in construction object detection,…

Computer Vision and Pattern Recognition · Computer Science 2022-10-31 Mahdi Bonyani , Maryam Soleymani

We analytically study the Out-of-Time-Order Correlation functions (OTOC) for two spatially separated primary operators in two-dimensional unitary minimal models. Besides giving general arguments using the conformal symmetry, we also use the…

High Energy Physics - Theory · Physics 2018-09-20 Ruihua Fan

Humans are expert explorers. Understanding the computational cognitive mechanisms that support this efficiency can advance the study of the human mind and enable more efficient exploration algorithms. We hypothesize that humans explore new…

Machine Learning · Computer Science 2022-03-21 Sugandha Sharma , Aidan Curtis , Marta Kryven , Josh Tenenbaum , Ila Fiete

We study a mathematical model for ocular dominance patterns (ODPs) in primary visual cortex. This model is based on the premise that ODP is an adaptation to minimize the length of intra-cortical wiring. Thus we attempt to understand the…

Neurons and Cognition · Quantitative Biology 2007-05-23 Alexei A. Koulakov , Dmitri B. Chklovskii

The adaptation of neural codes to the statistics of their environment is well captured by efficient coding approaches. Here we solve an inverse problem: characterizing the objective and constraint functions that efficient codes appear to be…

Neurons and Cognition · Quantitative Biology 2021-02-25 Luke Rast , Jan Drugowitsch

Recently, the joint design of optical systems and downstream algorithms is showing significant potential. However, existing rays-described methods are limited to optimizing geometric degradation, making it difficult to fully represent the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Zheng Ren , Jingwen Zhou , Wenguan Zhang , Jiapu Yan , Bingkun Chen , Huajun Feng , Shiqi Chen

We typically construct optimal designs based on a single objective function. To better capture the breadth of an experiment's goals, we could instead construct a multiple objective optimal design based on multiple objective functions. While…

Methodology · Statistics 2023-03-09 Lucy L. Gao , Jane J. Ye , Shangzhi Zeng , Julie Zhou

We propose a framework for jointly modeling the geometry and functionality in high dimensional functional surfaces. The proposed mixed effects model characterizes effects of subject-specific covariates and exogenous stimuli on functional…

Applications · Statistics 2023-02-10 Jingjing Zou , Chi-Hua Chen , John A. D. Aston

In this work, we study optimization specified only through a comparison oracle: given two points, it reports which one is preferred. We call it function-free optimization because we do not assume access to, nor the existence of, a canonical…

Optimization and Control · Mathematics 2026-05-20 Katya Scheinberg , Zikai Xiong

This study aims to investigate topological organization of cortical thickness and functional networks by cortical lobes. First, I demonstrated modular organization of these networks by the cortical surface frontal, temporal, parietal and…

Neurons and Cognition · Quantitative Biology 2025-05-27 Vesna Vuksanović

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at organism level the…

Molecular Networks · Quantitative Biology 2016-05-11 Xiao-Jun Tian , Hang Zhang , Jens Sannerud , Jianhua Xing

This study investigates the use of local optima network (LON) analysis, a derivative of the fitness landscape of candidate solutions, to characterise and visualise the neural architecture space. The search space of feedforward neural…

Neural and Evolutionary Computing · Computer Science 2022-06-15 Isak Potgieter , Christopher W. Cleghorn , Anna S. Bosman

In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to…

Neurons and Cognition · Quantitative Biology 2011-06-29 Tobias C. Potjans , Markus Diesmann