Learning the nonlinearity of neurons from natural visual stimuli

Kayser, Christoph; Kording, K. P.; Konig, P.

Learning the nonlinearity of neurons from natural visual stimuli

Kayser C, Kording KP, Konig P (2003)
Neural Comput 15(8): 1751-9.

Zeitschriftenaufsatz | Englisch

Download

Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!

DOI

https://doi.org/10.1162/08997660360675026

Autor*in

Kayser, Christoph^UniBi ; Kording, K. P.; Konig, P.

Einrichtung

Fakultät für Biologie > Kognitive Neurowissenschaften

Stichworte

Models; Neurological Neurons/ physiology Nonlinear Dynamics Photic Stimulation Visual Pathways/cytology/ physiology

Erscheinungsjahr

2003

Zeitschriftentitel

Neural Comput

Band

15

Ausgabe

8

Seite(n)

1751-9

ISBN

0899-7667 (Print) 0899-7667 (Linking)

ISSN

0899-7667

Page URI

https://pub.uni-bielefeld.de/record/2914186

Zitieren

Kayser C, Kording KP, Konig P. Learning the nonlinearity of neurons from natural visual stimuli. Neural Comput. 2003;15(8):1751-9.

Kayser, C., Kording, K. P., & Konig, P. (2003). Learning the nonlinearity of neurons from natural visual stimuli. Neural Comput, 15(8), 1751-9. doi:10.1162/08997660360675026

Kayser, Christoph, Kording, K. P., and Konig, P. 2003. “Learning the nonlinearity of neurons from natural visual stimuli”. Neural Comput 15 (8): 1751-9.

Kayser, C., Kording, K. P., and Konig, P. (2003). Learning the nonlinearity of neurons from natural visual stimuli. Neural Comput 15, 1751-9.

Kayser, C., Kording, K.P., & Konig, P., 2003. Learning the nonlinearity of neurons from natural visual stimuli. Neural Comput, 15(8), p 1751-9.

C. Kayser, K.P. Kording, and P. Konig, “Learning the nonlinearity of neurons from natural visual stimuli”, Neural Comput, vol. 15, 2003, pp. 1751-9.

Kayser, C., Kording, K.P., Konig, P.: Learning the nonlinearity of neurons from natural visual stimuli. Neural Comput. 15, 1751-9 (2003).

Kayser, Christoph, Kording, K. P., and Konig, P. “Learning the nonlinearity of neurons from natural visual stimuli”. Neural Comput 15.8 (2003): 1751-9.

Daten bereitgestellt von European Bioinformatics Institute (EBI)

14 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Learning Visual Spatial Pooling by Strong PCA Dimension Reduction.
Hosoya H, Hyvärinen A., Neural Comput 28(7), 2016
PMID: 27171856

Slowness and sparseness have diverging effects on complex cell learning.
Lies JP, Häfner RM, Bethge M., PLoS Comput Biol 10(3), 2014
PMID: 24603197

Relating BOLD fMRI and neural oscillations through convolution and optimal linear weighting.
Zumer JM, Brookes MJ, Stevenson CM, Francis ST, Morris PG., Neuroimage 49(2), 2010
PMID: 19778617

Psychophysically tuned divisive normalization approximately factorizes the PDF of natural images.
Malo J, Laparra V., Neural Comput 22(12), 2010
PMID: 20858127

Emergence of visual saliency from natural scenes via context-mediated probability distributions coding.
Xu J, Yang Z, Tsien JZ., PLoS One 5(12), 2010
PMID: 21209963

Transient cortical excitation at the onset of visual fixation.
Rajkai C, Lakatos P, Chen CM, Pincze Z, Karmos G, Schroeder CE., Cereb Cortex 18(1), 2008
PMID: 17494059

A maximum-likelihood interpretation for slow feature analysis.
Turner R, Sahani M., Neural Comput 19(4), 2007
PMID: 17348772

Complex cell pooling and the statistics of natural images.
Hyvärinen A, Köster U., Network 18(2), 2007
PMID: 17852755

V1 non-linear properties emerge from local-to-global non-linear ICA.
Malo J, Gutiérrez J., Network 17(1), 2006
PMID: 16613796

A model of the ventral visual system based on temporal stability and local memory.
Wyss R, König P, Verschure PF., PLoS Biol 4(5), 2006
PMID: 16605306

Learning of somatosensory representations for texture discrimination using a temporal coherence principle.
Hipp J, Einhäuser W, Conradt J, König P., Network 16(2-3), 2005
PMID: 16411497

Learning viewpoint invariant object representations using a temporal coherence principle.
Einhäuser W, Hipp J, Eggert J, Körner E, König P., Biol Cybern 93(1), 2005
PMID: 16021516

Cortical sensitivity to visual features in natural scenes.
Felsen G, Touryan J, Han F, Dan Y., PLoS Biol 3(10), 2005
PMID: 16171408

Energy levels of Moiré patterns: relation to human perception.
Batarseh KI., Biol Cybern 93(4), 2005
PMID: 16189673

23 References

Daten bereitgestellt von Europe PubMed Central.

Spatiotemporal energy models for the perception of motion.
Adelson EH, Bergen JR., J Opt Soc Am A 2(2), 1985
PMID: 3973762

Neural mechanisms for processing binocular information I. Simple cells.
Anzai A, Ohzawa I, Freeman RD., J. Neurophysiol. 82(2), 1999
PMID: 10444685

An information-maximization approach to blind separation and blind deconvolution.
Bell AJ, Sejnowski TJ., Neural Comput 7(6), 1995
PMID: 7584893

AUTHOR UNKNOWN, 0

Learning the invariance properties of complex cells from their responses to natural stimuli.
Einhauser W, Kayser C, Konig P, Kording KP., Eur. J. Neurosci. 15(3), 2002
PMID: 11876775

Nonlinear spectrotemporal sound analysis by neurons in the auditory midbrain.
Escabi MA, Schreiner CE., J. Neurosci. 22(10), 2002
PMID: 12019330

Independent component analysis: A flexible nonlinearity and decorrelating manifold approach.
Everson R, Roberts S., Neural Comput 11(8), 1999
PMID: 10578040

Nonlinear signal transfer from mouse rods to bipolar cells and implications for visual sensitivity.
Field GD, Rieke F., Neuron 34(5), 2002
PMID: 12062023

AUTHOR UNKNOWN, 0

Role of cortical feedback in the receptive field structure and nonlinear response properties of somatosensory thalamic neurons.
Ghazanfar AA, Krupa DJ, Nicolelis MA., Exp Brain Res 141(1), 2001
PMID: 11685413

Computational subunits of visual cortical neurons revealed by artificial neural networks.
Lau B, Stanley GB, Dan Y., Proc. Natl. Acad. Sci. U.S.A. 99(13), 2002
PMID: 12060706

AUTHOR UNKNOWN, 0

Receptive field organization of complex cells in the cat's striate cortex.
Movshon JA, Thompson ID, Tolhurst DJ., J. Physiol. (Lond.) 283(), 1978
PMID: 722592

AUTHOR UNKNOWN, 0

Information maximization and independent component analysis; is there a difference?
Obradovic D, Deco G., Neural Comput 10(8), 1998
PMID: 9804672

Influence of dendritic conductances on the input-output properties of neurons.
Reyes A., Annu. Rev. Neurosci. 24(), 2001
PMID: 11520915

AUTHOR UNKNOWN, 0

Quantitative studies of single-cell properties in monkey striate cortex. III. Spatial frequency.
Schiller PH, Finlay BL, Volman SF., J. Neurophysiol. 39(6), 1976
PMID: 825623

Temporal characteristics of response integration evoked by multiple whisker stimulations in the barrel cortex of rats.
Shimegi S, Ichikawa T, Akasaki T, Sato H., J. Neurosci. 19(22), 1999
PMID: 10559424

Natural image statistics and neural representation.
Simoncelli EP, Olshausen BA., Annu. Rev. Neurosci. 24(), 2001
PMID: 11520932

Classifying simple and complex cells on the basis of response modulation.
Skottun BC, De Valois RL, Grosof DH, Movshon JA, Albrecht DG, Bonds AB., Vision Res. 31(7-8), 1991
PMID: 1909826

The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs.
Softky WR, Koch C., J. Neurosci. 13(1), 1993
PMID: 8423479

Slow feature analysis: unsupervised learning of invariances.
Wiskott L, Sejnowski TJ., Neural Comput 14(4), 2002
PMID: 11936959

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB