Linking brain activation to topological organization in the frontal lobe as a synergistic indicator to characterize the difference between various cognitive processes of executive functions

Abstract

Executive functions (EFs) associated with the frontal lobe are vital for goal-orientated behavior. To date, limited efforts have been made to examine the relationships among the behavior, brain activation, and topological organization of functional networks in the frontal lobe underlying various EF tasks, including inhibition, working memory, and cognitive flexibility. In this study, functional near-infrared spectroscopy neuroimaging technique was used to systematically inspect the differences in the brain activation and the topological organization of brain networks between various EF tasks in the frontal lobe. In addition, the relationships between brain activation/network properties and task performances and the relationships between brain activation and network properties were, respectively, examined for different EF tasks. Consequently, we have discovered that the nodal and global properties of the resting-state and task-evoked networks, respectively, exhibited significant correlations with the activation of various brain regions during various EF tasks. In particular, the measure that links the neural activation to the topological organization of the brain networks in the frontal lobe can serve as a synergistic indicator to examine the difference between various EF tasks, which paves a way toward a comprehensive understanding of the neural mechanism underlying EFs.

Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy

“…This study showed that children with ADHD, compared to the HCs, exhibited decreased homotopic, intrahemispheric, and heterotopic functional connectivity (i.e., disconnection). Specifically, the decreased homotopic connectivity was primarily located in the prefrontal cortices and bilateral posterior cortices involving dorsal attention networks and visual networks, which are, respectively, related to executive, 63 attention, 64 and visual sensory processing. 65 Impairments in these cognitive processes have long been associated with ADHD.…”

Alterations of Cerebral Hemodynamics and Network Properties Induced by Newsvendor Problem in the Human Prefrontal Cortex

“…This observation also implies that more communications among regional segregations and/or clusters take place to achieve decision-making tasks. Also, increases in Eloc and Cp (in sparsity range of 0.05–0.5) as well as Lp (in sparsity range of 0.05–0.4) by NP reveal that NP decision-making needs the brain to boost or enhance network segregation/clustering, which also leads to an increase of Lp and Eloc consistently (Hu et al, 2019 ). As evidenced, Figures 4A,B illustrate that only a few cortical regions (i.e., DLPFC and OFC+FPA), not the entire prefrontal cortex, were involved in the decision-making process, regardless of either LM or HM treatment.…”

“…Similarly, fNIRS can reach OFC partially through recordings right on top of the eyebrows. To make sure that our fNIRS was able to acquire signals from OFC, we identified and listed in Table 2 the anatomical registrations of channels 1 to 4 (see Figure 1B ) generated by NIRS-SPM (Ye et al, 2009 ) according to the optode locations (Hu et al, 2019 ), as an example. Specifically, this table shows two major BAs (BAs 10 and 11) and respective brain areas (i.e., frontopolar area (FPA) and OFC) that were covered by each of the four channels as well as the percentage of FPA and OFC covered by each channel.…”

“…Graph theory is a renowned mathematical model to study characteristics of a network system (Erdös, 1959 ; Bondy and Murty, 1976 ), and it has been applied to investigate resting state functional connectivity of the human brain as measured with fMRI, Electroencephalography (EEG), and Magnetoencephalographic (MEG) (Salvador et al, 2005 ; Achard et al, 2006 ; Bassett et al, 2006 ; Iturria-Medina et al, 2008 ), as well as fNIRS (Niu et al, 2012 ; Niu and He, 2014 ; Li et al, 2018 ). A recent study demonstrated that based on GTA, brain networks were altered when the human brain transitioned from resting state to task-evoked states (Hu et al, 2019 ). In this study, we also applied GTA to primarily focus on how brain networks were altered from resting state to the decision-making state in a dynamic context.…”

“…Neuronal alterations occur in a millisecond scale while cerebral blood flow changes within seconds. Thus, dynamic brain connectivity and networks characterize the time-dependent neurophysiological processes that are associated with prompt decision making and cognition (Telesford et al, 2016 ; Hu et al, 2019 ). Recent literature has reported that dynamic connectivity can be quantified for time ranges in 15–120 s, and that a minimum temporal window for calculating connectivity is 30 s (Thompson and Fransson, 2015 ; Telesford et al, 2016 ; Farahani et al, 2019 ).…”