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Disrupted cholinergic modulation can underlie abnormal gamma rhythms in schizophrenia and auditory hallucination

Overview of attention for article published in Journal of Computational Neuroscience, October 2017
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Title
Disrupted cholinergic modulation can underlie abnormal gamma rhythms in schizophrenia and auditory hallucination
Published in
Journal of Computational Neuroscience, October 2017
DOI 10.1007/s10827-017-0666-4
Pubmed ID
Authors

Jung Hoon Lee

Abstract

The pathophysiology of auditory hallucination, a common symptom of schizophrenia, has yet been understood, but during auditory hallucination, primary auditory cortex (A1) shows paradoxical responses. When auditory stimuli are absent, A1 becomes hyperactive, while A1 responses to auditory stimuli are reduced. Such activation pattern of A1 responses during auditory hallucination is consistent with aberrant gamma rhythms in schizophrenia observed during auditory tasks, raising the possibility that the pathology underlying abnormal gamma rhythms can account for auditory hallucination. Moreover, A1 receives top-down signals in the gamma frequency band from an adjacent association area (Par2), and cholinergic modulation regulates interactions between A1 and Par2. In this study, we utilized a computational model of A1 to ask if disrupted cholinergic modulation could underlie abnormal gamma rhythms in schizophrenia. Furthermore, based on our simulation results, we propose potential pathology by which A1 can directly contribute to auditory hallucination.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 16%
Student > Ph. D. Student 3 16%
Student > Doctoral Student 2 11%
Student > Bachelor 2 11%
Other 2 11%
Other 4 21%
Unknown 3 16%
Readers by discipline Count As %
Neuroscience 9 47%
Agricultural and Biological Sciences 2 11%
Engineering 2 11%
Social Sciences 1 5%
Physics and Astronomy 1 5%
Other 0 0%
Unknown 4 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2018.
All research outputs
#18,574,814
of 23,006,268 outputs
Outputs from Journal of Computational Neuroscience
#225
of 309 outputs
Outputs of similar age
#250,658
of 327,016 outputs
Outputs of similar age from Journal of Computational Neuroscience
#9
of 10 outputs
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