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Neural inhibition can explain negative BOLD responses : A mechanistic modelling and fMRI study

Authors :
Sten, Sebastian
Lundengård, Karin
Witt, Suzanne Tyson
Cedersund, Gunnar
Elinder, Fredrik
Engström, Maria
Sten, Sebastian
Lundengård, Karin
Witt, Suzanne Tyson
Cedersund, Gunnar
Elinder, Fredrik
Engström, Maria
Publication Year :
2017

Abstract

Functional magnetic resonance imaging (fMRI) of hemodynamic changes captured in the blood oxygen level-dependent (BOLD) response contains information of brain activity. The BOLD response is the result of a complex neurovascular coupling and comes in at least two fundamentally different forms: a positive and a negative deflection. Because of the complexity of the signaling, mathematical modelling can provide vital help in the data analysis. For the positive BOLD response, there are plenty of mathematical models, both physiological and phenomenological. However, for the negative BOLD response, no physiologically based model exists. Here, we expand our previously developed physiological model with the most prominent mechanistic hypothesis for the negative BOLD response: the neural inhibition hypothesis. The model was trained and tested on experimental data containing both negative and positive BOLD responses from two studies: 1) a visual-motor task and 2) a workin-gmemory task in conjunction with administration of the tranquilizer diazepam. Our model was able to predict independent validation data not used for training and provides a mechanistic underpinning for previously observed effects of diazepam. The new model moves our understanding of the negative BOLD response from qualitative reasoning to a quantitative systems-biology level, which can be useful both in basic research and in clinical use.<br />Funding Agencies|Swedish Research Council [20146249]; Knut and Alice Wallenbergs foundation, KAW [2013.0076]; Research council of Southeast Sweden [FORSS-481691]; Linkoping University local funds

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1234747692
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.neuroimage.2017.07.002