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Neural coding is a field of study that concerns how sensory information is represented in the brain by networks of neurons. The link between external stimulus and neural response can be studied from two parallel points of view. The first,…

神经元与认知 · 定量生物学 2012-03-07 Shinsuke Koyama

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…

神经元与认知 · 定量生物学 2014-09-10 Nora Youngs

Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce a new analytical approach, using…

神经元与认知 · 定量生物学 2022-11-15 Federico W. Pasini , Alexandra N. Busch , Ján Mináč , Krishnan Padmanabhan , Lyle Muller

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…

神经元与认知 · 定量生物学 2015-02-25 Carina Curto , Vladimir Itskov , Alan Veliz-Cuba , Nora Youngs

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…

神经元与认知 · 定量生物学 2019-02-14 Carina Curto , Nora Youngs

To study information processing in the brain, neuroscientists manipulate experimental stimuli while recording participant brain activity. They can then use encoding models to find out which brain "zone" (e.g. which region of interest,…

神经元与认知 · 定量生物学 2022-02-22 Mariya Toneva , Jennifer Williams , Anand Bollu , Christoph Dann , Leila Wehbe

Neural codes, represented as collections of binary strings, encode neural activity and show relationships among stimuli. Certain neurons, called place cells, have been shown experimentally to fire in convex regions in space. A natural…

神经元与认知 · 定量生物学 2019-09-20 Sarah Ayman Goldrup , Kaitlyn Phillipson

The brain encodes spacial structure through a combinatorial code of neural activity. Experiments suggest such codes correspond to convex areas of the subject's environment. We present an intrinsic condition that implies a neural code may…

组合数学 · 数学 2016-10-20 Robert Williams

A neural code $\mathcal{C}$ is a collection of binary vectors of a given length n that record the co-firing patterns of a set of neurons. Our focus is on neural codes arising from place cells, neurons that respond to geographic stimulus. In…

神经元与认知 · 定量生物学 2016-07-05 Elizabeth Gross , Nida Kazi Obatake , Nora Youngs

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…

神经元与认知 · 定量生物学 2015-02-25 Carina Curto , Anda Degeratu , Vladimir Itskov

Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of…

神经元与认知 · 定量生物学 2017-03-13 Umut Güçlü , Marcel A. J. van Gerven

Neural codes allow the brain to represent, process, and store information about the world. Combinatorial codes, comprised of binary patterns of neural activity, encode information via the collective behavior of populations of neurons. A…

神经元与认知 · 定量生物学 2016-12-22 Carina Curto , Elizabeth Gross , Jack Jeffries , Katherine Morrison , Mohamed Omar , Zvi Rosen , Anne Shiu , Nora Youngs

Brain decoding involves the determination of a subject's cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a…

机器学习 · 统计学 2015-04-14 Nicole Croteau , Farouk S. Nathoo , Jiguo Cao , Ryan Budney

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…

The neural coding is yet to be discovered. The neuronal operational modes that arise with fixed inputs but with varying degrees of stimulation help to elucidate their coding properties. In neurons receiving {\it in vivo} stimulation, we…

神经元与认知 · 定量生物学 2025-11-05 Lindsey Knowles , Cesar Ceballos , Rodrigo Pena

A major area in neuroscience research is the study of how the brain processes spatial information. Neurons in the brain represent external stimuli via neural codes. These codes often arise from stereotyped stimulus-response maps,…

神经元与认知 · 定量生物学 2016-10-03 Ethan Petersen , Nora Youngs , Ryan Kruse , Dane Miyata , Rebecca Garcia , Luis David Garcia Puente

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…

神经元与认知 · 定量生物学 2018-05-17 David M. Schwartz , O. Ozan Koyluoglu

Brain decoding is a field of computational neuroscience that uses measurable brain activity to infer mental states or internal representations of perceptual inputs. Therefore, we propose a novel approach to brain decoding that also relies…

计算机视觉与模式识别 · 计算机科学 2023-03-23 Matteo Ferrante , Tommaso Boccato , Nicola Toschi

Neural codes, represented as collections of binary strings called codewords, are used to encode neural activity. A code is called convex if its codewords are represented as an arrangement of convex open sets in Euclidean space. Previous…

组合数学 · 数学 2022-08-10 Katherine Johnston , Anne Shiu , Clare Spinner

The development of algorithms to accurately decode neural information has long been a research focus in the field of neuroscience. Brain decoding typically involves training machine learning models to map neural data onto a preestablished…

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