Identifying Functional Bases for Multidimensional Neural Computations

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Neural Computation

• Publication date

  2013-07-01

• Fields of study

  Mathematics, Computer Science, Medicine

• Identifiers
  DOI 10.1162/NECO_a_00465PMID 23607565PMCID PMC3672375
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Computational identification of receptive fields.

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  2011cited by this paper
• Second Order Dimensionality Reduction Using Minimum and Maximum Mutual Information Models

  2011cited by this paper
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• System identification of Drosophila olfactory sensory neurons

  2011cited by this paper
• Minimal Models of Multidimensional Computations

  2011cited by this paper
• Active learning of neural response functions with Gaussian processes

  2011cited by this paper
• Two-dimensional adaptation in the auditory forebrain.

  2011cited by this paper
• Fine Spatial Information Represented in a Population of Retinal Ganglion Cells

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• Non-Centered Spike-Triggered Covariance Analysis Reveals Neurotrophin-3 as a Developmental Regulator of Receptive Field Properties of ON-OFF Retinal Ganglion Cells

  2010cited by this paper
• Functional connectivity in the retina at the resolution of photoreceptors

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• Eye smarter than scientists believed: neural computations in circuits of the retina.

  2010cited by this paper
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• Preserving Information in Neural Transmission

  2009cited by this paper
• Receptive Fields in Primate Retina Are Coordinated to Sample Visual Space More Uniformly

  2009cited by this paper
• Predictable irregularities in retinal receptive fields

  2009influential reference
• Cooperative nonlinearities in auditory cortical neurons.

  2008cited by this paper
• Cone inputs to simple and complex cells in V1 of awake macaque.

  2007cited by this paper
• Excitatory and suppressive receptive field subunits in awake monkey primary visual cortex (V1)

  2007cited by this paper
• Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex

  2007cited by this paper
• An Introduction to the Bootstrap

  2007cited by this paper
• Robust Object Recognition with Cortex-Like Mechanisms

  2007cited by this paper
• Spike-triggered neural characterization.

  2006cited by this paper
• Selectivity for multiple stimulus features in retinal ganglion cells.

  2006influential reference
• Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis.

  2006cited by this paper
• Single Neuron Computation: From Dynamical System to Feature Detector

  2006cited by this paper
• Features and dimensions: Motion estimation in fly vision

  2005cited by this paper
• Spatiotemporal elements of macaque v1 receptive fields.

  2005cited by this paper
• Cortical Sensitivity to Visual Features in Natural Scenes

  2005cited by this paper
• Convergence properties of three spike-triggered analysis techniques

  2003cited by this paper
• Isolation of Relevant Visual Features from Random Stimuli for Cortical Complex Cells

  2002cited by this paper
• Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions

  2002cited by this paper
• A simple white noise analysis of neuronal light responses

  2001cited by this paper
• Characterizing Neural Gain Control using Spike-triggered Covariance

  2001cited by this paper
• The Neural Code of the Retina Review A Sample Problem

  1999cited by this paper
• Hierarchical models of object recognition in cortex

  1999cited by this paper
• The neural code of the retina.

  1999cited by this paper
• Theory of orientation tuning in visual cortex.

  1995cited by this paper
• Fine structure of receptive-field centers of X and Y cells of the cat

  1991cited by this paper
• Microcircuitry related to the receptive field center of the on-beta ganglion cell.

  1991cited by this paper
• Numerical Recipes in C: The Art of Scientific Computing

  1989cited by this paper
• Axonal delay lines for time measurement in the owl's brainstem.

  1988cited by this paper
• Real-time performance of a movement-sensitive neuron in the blowfly visual system: coding and information transfer in short spike sequences

  1988cited by this paper
• Numerical Recipes in C: The Art of Sci-entific Computing

  1986cited by this paper
• Second-harmonic and sum-frequency generation in reflection: probing of GaAs surface structure and laser-induced phase transitions

  1985cited by this paper
• Spatiotemporal energy models for the perception of motion.

  1985cited by this paper
• A method of nonlinear analysis in the frequency domain.

  1980cited by this paper
• Triggered correlation.

  1968cited by this paper
• The mechanism of directionally selective units in rabbit's retina.

  1965cited by this paper

• Modeling spatial contrast sensitivity in responses of primate retinal ganglion cells to natural movies

  2025cites this paper
• Accelerated spike-triggered non-negative matrix factorization reveals coordinated ganglion cell subunit mosaics in the primate retina

  2024cites this paper
• Data-driven modelling of visual receptive fields: comparison between the generalized quadratic model and the nonlinear input model

  2024cites this paper
• Sparse ensemble neural code for a complete vocal repertoire

  2023cites this paper
• Retinal receptive-field substructure: scaffolding for coding and computation.

  2022cites this paper
• Systematic reduction of the dimensionality of natural scenes allows accurate predictions of retinal ganglion cell spike outputs

  2021cites this paper
• Mechanisms of Feature Selectivity and Invariance in Primary Visual Cortex

  2020cites this paper
• Inference of nonlinear receptive field subunits with spike-triggered clustering

  2020cites this paper
• Computational challenges and opportunities for a bi-directional artificial retina

  2020cites this paper
• Modern Machine Learning as a Benchmark for Fitting Neural Responses

  2018cites this paper
• Sensory Processing Describing complex cells in primary visual cortex : a comparison of context and multifilter LN models X

  2018cites this paper
• Describing complex cells in primary visual cortex: a comparison of context and multifilter LN models

  2018cites this paper
• Revealing Fine Structures of the Retinal Receptive Field by Deep-Learning Networks

  2018cites this paper
• Inferring hidden structure in multilayered neural circuits

  2017influential citation
• Linking normative models of natural tasks to descriptive models of neural response

  2017cites this paper
• Cross-orientation suppression in visual area V2

  2017cites this paper
• A Low-Rank Method for Characterizing High-Level Neural Computations

  2017cites this paper
• Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization

  2017cites this paper
• Analysis of Neuronal Spike Trains, Deconstructed.

  2016cites this paper
• Neuron Primer Analysis of Neuronal Spike Trains , Deconstructed

  2016cites this paper
• How Invariant Feature Selectivity Is Achieved in Cortex

  2016cites this paper
• Understanding spike-triggered covariance using Wiener theory for receptive field identification.

  2015cites this paper
• Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

  2015cites this paper
• A Convolutional Subunit Model for Neuronal Responses in Macaque V1

  2015cites this paper
• Primer : The deconstruction of neuronal spike trains

  2015cites this paper
• recombination functions Central auditory neurons display flexible feature

  2014cites this paper
• Central auditory neurons display flexible feature recombination functions.

  2014cites this paper
• Computational identification of receptive fields.

  2013cites this paper
• Characterizing Responses of Translation-Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions

  2012cites this paper
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  year unknowncites this paper