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Related papers: Obstructions to convexity in neural codes

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Networks of neurons in the brain encode preferred patterns of neural activity via their synaptic connections. Despite receiving considerable attention, the precise relationship between network connectivity and encoded patterns is still…

Neurons and Cognition · Quantitative Biology 2015-02-25 Carina Curto , Anda Degeratu , Vladimir Itskov

Convex neural codes are combinatorial structures describing the intersection pattern of a collection of convex sets. Inductively pierced codes are a particularly nice subclass of neural codes introduced in the information visualization…

Combinatorics · Mathematics 2019-07-01 Caitlin Lienkaemper

Primary visual cortex (V1) is the first stage of cortical image processing, and a major effort in systems neuroscience is devoted to understanding how it encodes information about visual stimuli. Within V1, many neurons respond selectively…

Neurons and Cognition · Quantitative Biology 2017-06-21 William F. Kindel , Elijah D. Christensen , Joel Zylberberg

Neural codes are collections of binary strings motivated by patterns of neural activity. In this paper, we study algorithmic and enumerative aspects of convex neural codes in dimension 1 (i.e. on a line or a circle). We use the theory of…

Combinatorics · Mathematics 2017-02-23 Zvi Rosen , Yan X. Zhang

Learning to read places a strong challenge on the visual system. Years of expertise lead to a remarkable capacity to separate highly similar letters and encode their relative positions, thus distinguishing words such as FORM and FROM,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Aakash Agrawal , Stanislas Dehaene

Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that…

Neurons and Cognition · Quantitative Biology 2018-05-17 David M. Schwartz , O. Ozan Koyluoglu

Hippocampal neurons track positions of self, others, and gaze direction. However, it is unclear how their respective neural codes differ enough to avoid confusion while allowing for abstraction. We recorded from populations of hippocampal…

Neurons in the brain represent external stimuli via neural codes. These codes often arise from stimulus-response maps, associating to each neuron a convex receptive field. An important problem confronted by the brain is to infer properties…

Neurons and Cognition · Quantitative Biology 2014-09-10 Nora Youngs

Neurons in the brain represent external stimuli via neural codes. These codes often arise from stereotyped stimulus-response maps, associating to each neuron a convex receptive field. An important problem confronted by the brain is to infer…

Neurons and Cognition · Quantitative Biology 2015-02-25 Carina Curto , Vladimir Itskov , Alan Veliz-Cuba , Nora Youngs

This dissertation explores applications of discrete geometry in mathematical neuroscience. We begin with convex neural codes, which model the activity of hippocampal place cells and other neurons with convex receptive fields. In Chapter 4,…

Neurons and Cognition · Quantitative Biology 2022-09-19 Caitlin Lienkaemper

This note is a brief survey of some results of the recent collaboration of neurobiologists and mathematicians dedicated to stimulus reconstruction from neuronal spiking activity. This collaboration, in particular, led to the consideration…

History and Overview · Mathematics 2015-01-06 Yuri I. Manin

Hyperplane codes are a class of convex codes that arise as the output of a one layer feed-forward neural network. Here we establish several natural properties of stable hyperplane codes in terms of the {\it polar complex} of the code, a…

Neurons and Cognition · Quantitative Biology 2019-02-05 Vladimir Itskov , Alex Kunin , Zvi Rosen

Grid cells in the entorhinal cortex encode the position of an animal in its environment using spatially periodic tuning curves of varying periodicity. Recent experiments established that these cells are functionally organized in discrete…

Neurons and Cognition · Quantitative Biology 2016-01-13 Noga Weiss Mosheiff , Haggai Agmon , Avraham Moriel , Yoram Burak

Grid cells in the medial entorhinal cortex (MEC) of the mammalian brain exhibit a strikingly regular hexagonal firing field over space. These cells are learned after birth and are thought to support spatial navigation but also more abstract…

Neurons and Cognition · Quantitative Biology 2024-10-07 Mufeng Tang , Helen Barron , Rafal Bogacz

The hippocampal system contains neural populations that encode an animal's position and velocity as it navigates through space. Here, we show that such populations can embed two codes within their spike trains: a firing rate code (R)…

Neural and Evolutionary Computing · Computer Science 2019-12-25 Ryan Grgurich , Hugh T. Blair

We define a notion of morphism between combinatorial codes, making the class of all combinatorial codes into a category $\mathbf{Code}$. We show that morphisms can be used to remove redundant information from a code, and that morphisms…

Combinatorics · Mathematics 2021-10-06 R. Amzi Jeffs

The entorhinal-hippocampal circuit plays a critical role in higher brain functions, especially spatial cognition. Grid cells in the medial entorhinal cortex (MEC) periodically fire with different grid spacing and orientation, which makes a…

Neurons and Cognition · Quantitative Biology 2019-10-11 Taiping Zeng , XiaoLi Li , Bailu Si

The brain's spatial orientation system uses different neuron ensembles to aid in environment-based navigation. Two of the ways brains encode spatial information is through head direction cells and grid cells. Brains use head direction cells…

Neural and Evolutionary Computing · Computer Science 2023-09-07 Edward C. Mitchell , Brittany Story , David Boothe , Piotr J. Franaszczuk , Vasileios Maroulas

We take the testing perspective to understand what the minimal discrimination time between two stimuli is for different types of rate coding neurons. Our main goal is to describe the testing abilities of two different encoding systems:…

Statistics Theory · Mathematics 2024-02-14 Guilherme Ost , Patricia Reynaud-Bouret

Neural codes are binary codes in $\{0,1\}^n$; here we focus on the ones which represent the firing patterns of a type of neurons called place cells. There is much interest in determining which neural codes can be realized by a collection of…

Neurons and Cognition · Quantitative Biology 2018-07-09 Molly Hoch , Samuel Muthiah , Nida Obatake