Functional connectivity of the PFC via partial correlation

Dadgostar, Mehrdad; Setarehdan, Seyed Kamaledin; Shahzadi, Sohrab; Akin, Ata

doi:10.1016/j.ijleo.2016.01.139

Cited by 27 publications

(38 citation statements)

References 54 publications

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“…Employing 4 LEDs and 10 detectors, the device can sample 16 different channels in the brain simultaneously (see Fig. 2 for the details of the probe 47 ). LEDs and detectors were placed in a flexible printed circuit board that was specially designed to fit the curvature of the forehead.…”

Section: Data Acquisitionmentioning

confidence: 99%

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Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS

et al. 2017

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Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions. The algorithm starts with a wavelet-transform-based preprocessing, then uses partial correlation analysis to compute the functional connectivity matrices at each condition and then computes the global efficiency values. To this end, a continuous wave 16 channels fNIRS device (ARGES Cerebro, Hemosoft Inc., Turkey) was used to measure the changes in [Formula: see text] concentrations from 12 healthy volunteers. We have considered 10% of strongest connections in each network. A strong Stroop interference effect was found between the incongruent against neutral condition ([Formula: see text]) while a similar significance was observed for the global efficiency values decreased from neutral to congruent to incongruent conditions [[Formula: see text], [Formula: see text]]. The findings bring us closer to delivering a biomarker derived from fNIRS data that can be reliably and easily adopted by the clinicians.

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Section: Data Acquisitionmentioning

confidence: 99%

“…The reverse covariance matrix of X is called precision matrix or concentration matrix. 47, Thus, E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 2 ; 3 2 6 ; 4 2 6…”

Section: Partial Correlationmentioning

confidence: 99%

Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS

et al. 2017

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“…32 Similarly, FC analysis with the PC approach has been proposed both by our group and others. 17,23,33,34 Our group has shown that using the remaining 14 channels of a 16-channel fNIRS measurement system as the regressors of the PC analysis, we can provide reliable estimate of the FC analysis. The assumption behind this approach was that there are local systemic fluctuations at each measurement site (channel) and they are also picked up by any channel.…”

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confidence: 99%

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

Akın

2017

J. Biomed. Opt

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A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.

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“…Previous studies have emphasized the important role of the FC between interhemispheric PFCs in inhibition as well. Dadgostar et al (2016) found by fNIRS that the motor inhibition study using electroencephalogram (EEG). During grip tracking tasks, Derosiere et al (2014) also found increased cooperation and coactivation of bilateral rostral PFCs, which was consistent with our results.…”

Section: The Effect Of Grip Tracking Tasksmentioning

confidence: 99%

Detection of functional connectivity in the brain during visuo‐guided grip force tracking tasks: A functional near‐infrared spectroscopy study

Zheng

Luo

Deng

et al. 2020

J of Neuroscience Research

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The functional connectivity (FC) between multiple brain regions during tasks is currently gradually being explored with functional near-infrared spectroscopy (fNIRS). However, the FC present during grip force tracking tasks performed under visual feedback remains unclear. In the present study, we used fNIRS to measure brain activity during resting states and grip force tracking tasks at 25%, 50%, and 75% of maximum voluntary contraction (MVC) in 11 healthy subjects, and the activity was measured from four target brain regions: the left prefrontal cortex (lPFC), right prefrontal cortex (rPFC), left sensorimotor cortex (lSMC), and right sensorimotor cortex (rSMC). We determined the FC between these regions utilizing three different methods: Pearson's correlation method, partial correlation method, and a pairwise maximum entropy model (MEM). The results showed that the FC of lSMC-rSMC and lPFC-rPFC (interhemispheric homologous pairs) were significantly stronger than those of other brain region pairs. Moreover, FC of lPFC-rPFC was strengthened during the 75% MVC task compared to the other task states and the resting states. The FC of lSMC-lPFC and rSMC-rPFC (intrahemispheric region pairs) strengthened with a higher task load. The results provided new insights into the FC between brain regions during visuo-guided grip force tracking tasks. K E Y W O R D S functional connectivity, functional near-infrared spectroscopy (fNIRS), grip force tracking, pairwise MEM, partial correlation | 1109 ZHENG Et al.

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Functional connectivity of the PFC via partial correlation

Cited by 27 publications

References 54 publications

Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS

Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

Detection of functional connectivity in the brain during visuo‐guided grip force tracking tasks: A functional near‐infrared spectroscopy study

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