Literature DB >> 15483598

Neural networks and perceptual learning.

Misha Tsodyks1, Charles Gilbert.   

Abstract

Sensory perception is a learned trait. The brain strategies we use to perceive the world are constantly modified by experience. With practice, we subconsciously become better at identifying familiar objects or distinguishing fine details in our environment. Current theoretical models simulate some properties of perceptual learning, but neglect the underlying cortical circuits. Future neural network models must incorporate the top-down alteration of cortical function by expectation or perceptual tasks. These newly found dynamic processes are challenging earlier views of static and feedforward processing of sensory information.

Mesh:

Year:  2004        PMID: 15483598      PMCID: PMC1201476          DOI: 10.1038/nature03013

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  44 in total

1.  Perceptual learning without perception.

Authors:  T Watanabe; J E Náñez; Y Sasaki
Journal:  Nature       Date:  2001-10-25       Impact factor: 49.962

2.  Psychophysics: Is subliminal learning really passive?

Authors:  Aaron R Seitz; Takeo Watanabe
Journal:  Nature       Date:  2003-03-06       Impact factor: 49.962

3.  Fast perceptual learning in visual hyperacuity.

Authors:  T Poggio; M Fahle; S Edelman
Journal:  Science       Date:  1992-05-15       Impact factor: 47.728

4.  Changes in the distributed temporal response properties of SI cortical neurons reflect improvements in performance on a temporally based tactile discrimination task.

Authors:  G H Recanzone; M M Merzenich; C E Schreiner
Journal:  J Neurophysiol       Date:  1992-05       Impact factor: 2.714

5.  Statistical mechanics of learning from examples.

Authors: 
Journal:  Phys Rev A       Date:  1992-04-15       Impact factor: 3.140

6.  Modeling perceptual learning: difficulties and how they can be overcome.

Authors:  M H Herzog; M Fahle
Journal:  Biol Cybern       Date:  1998-02       Impact factor: 2.086

7.  The role of feedback in learning a vernier discrimination task.

Authors:  M H Herzog; M Fahle
Journal:  Vision Res       Date:  1997-08       Impact factor: 1.886

8.  Excitatory and inhibitory interactions in localized populations of model neurons.

Authors:  H R Wilson; J D Cowan
Journal:  Biophys J       Date:  1972-01       Impact factor: 4.033

9.  Neural network models of perceptual learning of angle discrimination.

Authors:  G Mato; H Sompolinsky
Journal:  Neural Comput       Date:  1996-02-15       Impact factor: 2.026

10.  Physiological correlates of perceptual learning in monkey V1 and V2.

Authors:  Geoffrey M Ghose; Tianming Yang; John H R Maunsell
Journal:  J Neurophysiol       Date:  2002-04       Impact factor: 2.714

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  40 in total

Review 1.  Insights into cortical mechanisms of behavior from microstimulation experiments.

Authors:  Mark H Histed; Amy M Ni; John H R Maunsell
Journal:  Prog Neurobiol       Date:  2012-01-28       Impact factor: 11.685

2.  Feedback and feedforward control of frequency tuning to naturalistic stimuli.

Authors:  Maurice J Chacron; Leonard Maler; Joseph Bastian
Journal:  J Neurosci       Date:  2005-06-08       Impact factor: 6.167

Review 3.  Neurotransmitter receptor heteromers and their integrative role in 'local modules': the striatal spine module.

Authors:  Sergi Ferré; Luigi F Agnati; Francisco Ciruela; Carme Lluis; Amina S Woods; Kjell Fuxe; Rafael Franco
Journal:  Brain Res Rev       Date:  2007-01-27

4.  Broad bandwidth of perceptual learning in the visual system of adults with anisometropic amblyopia.

Authors:  Chang-Bing Huang; Yifeng Zhou; Zhong-Lin Lu
Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-03       Impact factor: 11.205

5.  Image interpretation by a single bottom-up top-down cycle.

Authors:  Boris Epshtein; Ita Lifshitz; Shimon Ullman
Journal:  Proc Natl Acad Sci U S A       Date:  2008-09-16       Impact factor: 11.205

6.  Response feedback triggers long-term consolidation of perceptual learning independently of performance gains.

Authors:  Jonathan Dobres; Takeo Watanabe
Journal:  J Vis       Date:  2012-08-17       Impact factor: 2.240

7.  Precise Long-Range Microcircuit-to-Microcircuit Communication Connects the Frontal and Sensory Cortices in the Mammalian Brain.

Authors:  Si-Qiang Ren; Zhizhong Li; Susan Lin; Matteo Bergami; Song-Hai Shi
Journal:  Neuron       Date:  2019-07-29       Impact factor: 17.173

8.  Vestibular signals in macaque extrastriate visual cortex are functionally appropriate for heading perception.

Authors:  Sheng Liu; Dora E Angelaki
Journal:  J Neurosci       Date:  2009-07-15       Impact factor: 6.167

9.  Altered sensory experience induces targeted rewiring of local excitatory connections in mature neocortex.

Authors:  Claire E J Cheetham; Martin S L Hammond; Rachael McFarlane; Gerald T Finnerty
Journal:  J Neurosci       Date:  2008-09-10       Impact factor: 6.167

10.  Adaptive gain modulation in V1 explains contextual modifications during bisection learning.

Authors:  Roland Schäfer; Eleni Vasilaki; Walter Senn
Journal:  PLoS Comput Biol       Date:  2009-12-18       Impact factor: 4.475

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