2014
DOI: 10.3389/fnsys.2014.00013
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Oscillatory motor network activity during rest and movement: an fNIRS study

Abstract: Coherent network oscillations (<0.1 Hz) linking distributed brain regions are commonly observed in the brain during both rest and task conditions. What oscillatory network exists and how network oscillations change in connectivity strength, frequency and direction when going from rest to explicit task are topics of recent inquiry. Here, we study network oscillations within the sensorimotor regions of able-bodied individuals using hemodynamic activity as measured by functional near-infrared spectroscopy (fNIRS)… Show more

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Cited by 36 publications
(44 citation statements)
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“…The primary motor area (M1), which is an integral part of basic motor network, due to its association with upper-limb recovery, is the most common target for stroke therapies. Other motor areas such as premotor cortex (PMC) and supplementary motor area (SMA) are functionally and anatomically in close association with M1 and play a crucial role to execute motor tasks (Bajaj et al, 2014, 2015a,b). Previous studies have discussed the role of the motor network in the unaffected hemisphere of stroke patients and its test–retest reliability with time.…”
Section: Introductionmentioning
confidence: 99%
“…The primary motor area (M1), which is an integral part of basic motor network, due to its association with upper-limb recovery, is the most common target for stroke therapies. Other motor areas such as premotor cortex (PMC) and supplementary motor area (SMA) are functionally and anatomically in close association with M1 and play a crucial role to execute motor tasks (Bajaj et al, 2014, 2015a,b). Previous studies have discussed the role of the motor network in the unaffected hemisphere of stroke patients and its test–retest reliability with time.…”
Section: Introductionmentioning
confidence: 99%
“…However, in previous research, the comparison of action execution and observation with resting state was not systematically conducted (Bajaj et al 2014). This comparison is crucial to explore the effective network implicated in motor functions compared to the absence of motor performance.…”
Section: Introductionmentioning
confidence: 98%
“…In the most commonly used formulations of Granger causality (Ding et al, 2006), the degree to which a causal variable help to predict an effective variable beyond the information contained in the effective variable's own past is measured either by the decrease of the residuals (Ding et al, 2006; Jiao et al, 2014; Kullmann et al, 2014), i.e., the time domain formulation, or by the frequency decomposition (Geweke, 1982; Bajaj et al, 2014, 2015), i.e., the frequency domain formulation, both through estimating an autoregression model with a fixed order. However, in some recent studies, another “signed path coefficient” version of Granger causality was proposed (Chen et al, 2009) and had been firstly used to reveal the causality from brain regions of patients with major depression disorder (Hamilton et al, 2011), and gradually it was popular among a number of researchers in the field of fMRI.…”
Section: Introductionmentioning
confidence: 99%