An Application of Affective Computing on Mental Disorders: A Resting State fNIRS Study

Wu, Cheng-Shong; Sun, Jieqiong; Wang, Tao; Zhao, Chengjian; Zheng, Shuzhen; Chang, Ling‐Yi; Peng, Hong

doi:10.1016/j.ifacol.2021.04.195

Cited by 5 publications

(9 citation statements)

References 20 publications

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“…Some previous studies adopt the Pearson correlation analysis, the coherence coefficient, and the phase lock value for the network connection analysis ( Wu et al, 2020 ), among which the phase lock value reflected the synchronization connectivity. The phase lock value not only represented the phase difference tendency of the overall signal but also provide more information interaction compare to correlation analysis and coherence coefficient.…”

Section: Methodsmentioning

confidence: 99%

“…By the wavelet transform, we can extract the dynamic phase information from the different frequency bands of the time series to transform the time series to phase series for further channel-channel correlation analysis. Some previous studies adopt the Pearson correlation analysis, the coherence coefficient, and the phase lock value for the network connection analysis (Wu et al, 2020), among which the phase lock value reflected the synchronization connectivity. The phase lock value not only represented the phase difference tendency of the overall signal but also provide more information interaction compare to correlation analysis and coherence coefficient.…”

Section: Brain Network Analysismentioning

confidence: 99%

“…For instance, daily tasks, such as eating, dressing, and using tools, require the coordinated movement of multiple muscles in the upper body ( Yu et al, 2017 ), often consisting of the symmetrical way of the hands (such as serving a plate) or asymmetrical way (such as opening a can). Previous studies have revealed that coordination ability training evokes brain activation that may contribute to the reorganization of the motor cortex ( Li et al, 2013 ; Han and Kim, 2016 ; Wu et al, 2020 ). Recently, it has been demonstrated that bilateral coordinated movement can promote the neurotic recombination of the motor region of patients after stroke ( Wu et al, 2020 ) and benefit stroke patients’ recovery ( Fu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have revealed that coordination ability training evokes brain activation that may contribute to the reorganization of the motor cortex ( Li et al, 2013 ; Han and Kim, 2016 ; Wu et al, 2020 ). Recently, it has been demonstrated that bilateral coordinated movement can promote the neurotic recombination of the motor region of patients after stroke ( Wu et al, 2020 ) and benefit stroke patients’ recovery ( Fu et al, 2021 ). However, the underlying neural mechanisms remain unclear in coordination ability training.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The correlations between kinematic profiles and cerebral hemodynamics suggest changes of motor coordination in single and bilateral finger movement

Zhou

Chen

Wang

et al. 2022

Front. Hum. Neurosci.

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ObjectiveThe correlation between the performance of coordination movement and brain activity is still not fully understood. The current study aimed to identify activated brain regions and brain network connectivity changes for several coordinated finger movements with different difficulty levels and to correlate the brain hemodynamics and connectivity with kinematic performance.MethodsTwenty-one right-dominant-handed subjects were recruited and asked to complete circular motions of single and bilateral fingers in the same direction (in-phase, IP) and in opposite directions (anti-phase, AP) on a plane. Kinematic data including radius and angular velocity at each task and synchronized blood oxygen concentration data using functional near-infrared spectroscopy (fNIRS) were recorded covering six brain regions including the prefrontal cortex, motor cortex, and occipital lobes. A general linear model was used to locate activated brain regions, and changes compared with baseline in blood oxygen concentration were used to evaluate the degree of brain region activation. Small-world properties, clustering coefficients, and efficiency were used to measure information interaction in brain activity during the movement.ResultIt was found that the radius error of the dominant hand was significantly lower than that of the non-dominant hand (p < 0.001) in both clockwise and counterclockwise movements. The fNIRS results confirmed that the contralateral brain region was activated during single finger movement and the dominant motor area was activated in IP movement, while both motor areas were activated simultaneously in AP movement. The Δhbo were weakly correlated with radius errors (p = 0.002). Brain information interaction in IP movement was significantly larger than that from AP movement in the brain network (p < 0.02) in the right prefrontal cortex. Brain activity in the right motor cortex reduces motor performance (p < 0.001), while the right prefrontal cortex region promotes it (p < 0.05).ConclusionOur results suggest there was a significant correlation between motion performance and brain activation level, as well as between motion deviation and brain functional connectivity. The findings may provide a basis for further exploration of the operation of complex brain networks.

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Section: Methodsmentioning

confidence: 99%

Section: Brain Network Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The correlations between kinematic profiles and cerebral hemodynamics suggest changes of motor coordination in single and bilateral finger movement

Zhou

Chen

Wang

et al. 2022

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Small-world parameters (

): modular processing and efficient transmission of information between network characteristics modules and generally defined as [ 53 , 54 ]:

where

, and

are the clustering coefficients, AL and

are the characteristic path lengths,

and

are the average clustering coefficient and characteristic path length of the real network and a random network (

) [ 52 ].…”

Section: Methodsmentioning

confidence: 99%

Effect of Shift Work on Cognitive Function in Chinese Coal Mine Workers: A Resting-State fNIRS Study

Tian

et al. 2022

IJERPH

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Aim: Pilot study to examine the impact of shift work on cognitive function in Chinese coal mine workers. Background: Shift work is commonly used in modern industries such as the coal industry, and there is growing concern over the impact that shift work has on miners’ work performance and personal well-being. Method: A total of 54 miners working three shifts (17 in morning shift, 18 in afternoon, and 19 in night shift) participated in this exploratory study. A resting-state fNIRS functional connectivity method was conducted to assess the cognitive ability before and after the work shift. Results: Results showed significant differences in cognitive ability between before and after the work shifts among the three-shift workers. The brain functional connectivity was reduced ranking as the night, afternoon, and morning shifts. Decreased brain functional connectivity at the end of the working shift was found compared with before in the morning and afternoon shifts. Opposite results were obtained during the night shift. The resting-state functional brain networks in the prefrontal cortex of all groups exhibited small-world properties. Significant differences in betweenness centrality and nodal local efficiency were found in the prefrontal cortex in the morning and night shifts. Conclusions: The current findings provide new insights regarding the effect of shift work on the cognitive ability of Chinese coal mine workers from the view of brain science.

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FNIRS based study of brain network characteristics in children with cerebral palsy during bilateral lower limb movement

Xie,

Nie,

Zhang

et al. 2024

Medical Physics

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BackgroundMotor dysfunctions in children with cerebral palsy (CP) are caused by nonprogressive brain damage. Understanding the functional characteristics of the brain is important for rehabilitation.PurposeThis paper aimed to study the brain networks of children with CP during bilateral lower limb movement using functional near‐infrared spectroscopy (fNIRS) and to explore effective fNIRS indices for reflecting functional brain activity.MethodsUsing fNIRS, cerebral oxygenation signals in the bilateral prefrontal cortex (LPFC/RPFC) and motor cortex (LMC/RMC) were recorded from fifteen children with spastic CP and seventeen children with typical development (CTDs) in the resting state and during bilateral lower limb movement. Functional connectivity matrices based on phase‐locking values (PLVs) were calculated using Hilbert transformation, and binary networks were constructed at different sparsity levels. Network metrics such as the clustering coefficient, global efficiency, local efficiency, and transitivity were calculated. Furthermore, the time‐varying curves of network metrics during movement were obtained by dividing the time window and using sparse inverse covariance matrices. Finally, conditional Granger causality (GC) was used to explore the causal relationships between different brain regions.ResultsCompared to CTDs, the connectivity between RMC‐RPFC (p = 0.017) and RMC‐LMC (p = 0.002) in the brain network was decreased in children with CP, and the clustering coefficient (p = 0.003), global efficiency (p = 0.034), local efficiency (p = 0.015), and transitivity (p = 0.009) were significantly lower. The standard deviation of the changes in global efficiency of children with CP during motion was also greater than that of CTDs. Using GC, it was found that there was a significant increase in causal strength from the RMC to the RPFC (p = 0.04) and from the RMC to the LMC (p = 0.042) in children with CP during motion. Additionally, there were significant negative correlations between the PLV of LMC‐RMC (p = 0.002) and the Gross Motor Function Classification System (GMFCS) and between the GMFCS and the clustering coefficient (p = 0.01).ConclusionsDuring rehabilitation training of the lower limbs, there were significant differences in brain network indices between children with CP and CTDs. The indicators proposed in this paper are effective at evaluating motor function and the real‐time impact of rehabilitation training on the brain network and have great potential for application in guiding clinical motor function assessment and planning rehabilitation strategies.

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An Application of Affective Computing on Mental Disorders: A Resting State fNIRS Study

Cited by 5 publications

References 20 publications

The correlations between kinematic profiles and cerebral hemodynamics suggest changes of motor coordination in single and bilateral finger movement

The correlations between kinematic profiles and cerebral hemodynamics suggest changes of motor coordination in single and bilateral finger movement

Effect of Shift Work on Cognitive Function in Chinese Coal Mine Workers: A Resting-State fNIRS Study

FNIRS based study of brain network characteristics in children with cerebral palsy during bilateral lower limb movement

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