Activity in the right frontal cortex is dependent on inhibitory-demand: a functional near infrared spectroscopy study

2019 ◽  
Author(s):  
Jason He ◽  
Genevieve Steiner ◽  
Jack Fogarty ◽  
Nathan Nuzum ◽  
Miki Finch ◽  
...  

The ability to supress inappropriate or unwanted behaviour, known as inhibition, can be indexed using a variety of task paradigms, one of the more common being the Go/No-go task. Studies in which popular neuroimaging methods such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) were used to measure neural activity during participant performance of the Go/No-go task have often identified ‘inhibitory-related’ activity in the right prefrontal cortex (PFC). While studies using functional near-infrared spectroscopy (fNIRS) have also identified changes in activity in the right PFC, the variants of the Go/No-go tasks previously employed in those studies have made it difficult to be confident that those changes measured using fNIRS were specifically related to inhibition. To determine whether the change in activity identified in the right PFC with fNIRS by previous studies using the Go/No-go task were indeed related to inhibition, we had participants complete three conditions of the Go/No-go task, each with varying levels of inhibitory demand (manipulated by the relative frequency of Go to No-go trials). We found that as Go-trial frequency increased, participants performed faster on Go-trials and less accurately on No-go trials. More importantly, as inhibitory-demand increased, activity in the right but not left PFC increased. When taken together, these findings are in support of the idea that the changes measured in the right PFC in earlier studies using fNIRS during the Go/No-go task were indeed related to inhibition.

2018 ◽  
Vol 26 (2) ◽  
pp. 79-86 ◽  
Author(s):  
Gihyoun Lee ◽  
Seung Hyun Lee ◽  
Sang Hyeon Jin ◽  
Jinung An

Functional near infrared spectroscopy can measure hemodynamic signals, and the results are similar to functional magnetic resonance imaging of blood-oxygen-level-dependent signals. Thus, functional near infrared spectroscopy can be employed to investigate brain activity by measuring the absorption of near infrared light through an intact skull. Recently, a general linear model, which is a standard method for functional magnetic resonance imaging, was applied to functional near infrared spectroscopy imaging analysis. However, the general linear model fails when functional near infrared spectroscopy signals retain noise, such as that caused by the subject's movement during measurement. Although wavelet-based denoising and hemodynamic response function smoothing are popular denoising methods for functional near infrared spectroscopy signals, these methods do not exhibit impressive performances for very noisy environments and a specific class of noise. Thus, this paper proposes a new denoising algorithm that uses multiple wavelet shrinkage and a multiple threshold function based on a hemodynamic response model. Through the experiments, the performance of the proposed algorithm is verified using graphic results and objective indexes, and it is compared with existing denoising algorithms.


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