Literature DB >> 23516304

Neural changes with tactile learning reflect decision-level reweighting of perceptual readout.

K Sathian1, Gopikrishna Deshpande, Randall Stilla.   

Abstract

Despite considerable work, the neural basis of perceptual learning remains uncertain. For visual learning, although some studies suggested that changes in early sensory representations are responsible, other studies point to decision-level reweighting of perceptual readout. These competing possibilities have not been examined in other sensory systems, investigating which could help resolve the issue. Here we report a study of human tactile microspatial learning in which participants achieved >six-fold decline in acuity threshold after multiple training sessions. Functional magnetic resonance imaging was performed during performance of the tactile microspatial task and a control, tactile temporal task. Effective connectivity between relevant brain regions was estimated using multivariate, autoregressive models of hidden neuronal variables obtained by deconvolution of the hemodynamic response. Training-specific increases in task-selective activation assessed using the task × session interaction and associated changes in effective connectivity primarily involved subcortical and anterior neocortical regions implicated in motor and/or decision processes, rather than somatosensory cortical regions. A control group of participants tested twice, without intervening training, exhibited neither threshold improvement nor increases in task-selective activation. Our observations argue that neuroplasticity mediating perceptual learning occurs at the stage of perceptual readout by decision networks. This is consonant with the growing shift away from strictly modular conceptualization of the brain toward the idea that complex network interactions underlie even simple tasks. The convergence of our findings on tactile learning with recent studies of visual learning reconciles earlier discrepancies in the literature on perceptual learning.

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Year:  2013        PMID: 23516304      PMCID: PMC3700544          DOI: 10.1523/JNEUROSCI.3482-12.2013

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  94 in total

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Authors:  Christopher S Furmanski; Denis Schluppeck; Stephen A Engel
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3.  Posteromedial parietal cortical activity and inputs predict tactile spatial acuity.

Authors:  Randall Stilla; Gopikrishna Deshpande; Stephen LaConte; Xiaoping Hu; K Sathian
Journal:  J Neurosci       Date:  2007-10-10       Impact factor: 6.167

4.  Neural correlates of evidence accumulation in a perceptual decision task.

Authors:  Taosheng Liu; Timothy J Pleskac
Journal:  J Neurophysiol       Date:  2011-08-17       Impact factor: 2.714

5.  Perceptual learning in tactile hyperacuity: complete intermanual transfer but limited retention.

Authors:  K Sathian; A Zangaladze
Journal:  Exp Brain Res       Date:  1998-01       Impact factor: 1.972

6.  Learning-like phenomena in stereopsis.

Authors:  V S Ramachandran
Journal:  Nature       Date:  1976-07-29       Impact factor: 49.962

7.  Tactile perceptual learning: learning curves and transfer to the contralateral finger.

Authors:  Amanda L Kaas; Vincent van de Ven; Joel Reithler; Rainer Goebel
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Review 8.  Plastic corticostriatal circuits for action learning: what's dopamine got to do with it?

Authors:  Rui M Costa
Journal:  Ann N Y Acad Sci       Date:  2007-04-13       Impact factor: 5.691

9.  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

10.  Identifying neural drivers with functional MRI: an electrophysiological validation.

Authors:  Olivier David; Isabelle Guillemain; Sandrine Saillet; Sebastien Reyt; Colin Deransart; Christoph Segebarth; Antoine Depaulis
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  29 in total

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Authors:  Karthik Sreenivasan; Xiaowei Zhuang; Sarah J Banks; Virendra Mishra; Zhengshi Yang; Gopikrishna Deshpande; Dietmar Cordes
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2.  Predicting favorable and unfavorable consequences of perceptual learning: worsening and the peak shift.

Authors:  Matthew G Wisniewski
Journal:  Exp Brain Res       Date:  2017-02-11       Impact factor: 1.972

3.  Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

Authors:  Changfeng Jin; Hao Jia; Pradyumna Lanka; D Rangaprakash; Lingjiang Li; Tianming Liu; Xiaoping Hu; Gopikrishna Deshpande
Journal:  Hum Brain Mapp       Date:  2017-06-12       Impact factor: 5.038

Review 4.  Analysis of haptic information in the cerebral cortex.

Authors:  K Sathian
Journal:  J Neurophysiol       Date:  2016-07-20       Impact factor: 2.714

5.  Identifying disease foci from static and dynamic effective connectivity networks: Illustration in soldiers with trauma.

Authors:  D Rangaprakash; Michael N Dretsch; Archana Venkataraman; Jeffrey S Katz; Thomas S Denney; Gopikrishna Deshpande
Journal:  Hum Brain Mapp       Date:  2017-10-23       Impact factor: 5.038

6.  Threat-related learning relies on distinct dorsal prefrontal cortex network connectivity.

Authors:  M D Wheelock; K R Sreenivasan; K H Wood; L W Ver Hoef; Gopikrishna Deshpande; D C Knight
Journal:  Neuroimage       Date:  2014-08-08       Impact factor: 6.556

7.  Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

Authors:  Bhim M Adhikari; K Sathian; Charles M Epstein; Bidhan Lamichhane; Mukesh Dhamala
Journal:  Neuroimage       Date:  2014-01-13       Impact factor: 6.556

8.  Spatial imagery in haptic shape perception.

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Journal:  Neuropsychologia       Date:  2014-06-02       Impact factor: 3.139

9.  Diffusion of responsibility attenuates altruistic punishment: A functional magnetic resonance imaging effective connectivity study.

Authors:  Chunliang Feng; Gopikrishna Deshpande; Chao Liu; Ruolei Gu; Yue-Jia Luo; Frank Krueger
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10.  Patterns of effective connectivity during memory encoding and retrieval differ between patients with mild cognitive impairment and healthy older adults.

Authors:  B M Hampstead; M Khoshnoodi; W Yan; G Deshpande; K Sathian
Journal:  Neuroimage       Date:  2015-10-13       Impact factor: 6.556

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