A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test

Li, Xuan; Wu, Yunqiao; Wei, Mengting; Guo, Yiyun; Yu, Zhenhua; Wang, Haixian; Li, Zhanli; Fan, Hui

doi:10.1007/s11571-020-09646-x

Cited by 16 publications

(8 citation statements)

References 50 publications

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“…method is widely used in phase-synchrony experiments (Dumas et al, 2010;Yun et al, 2012;Hu et al, 2018). However, non-zero PLVs do not always represent synchrony but rather stem from volume conduction (Li et al, 2020). Volume conduction is the transmission of an electrical potential to multiple locations from a single source throughout a volume conductor (i.e., the brain) (Nunez et al, 1997).…”

Section: Methods For Interbrain Synchrony and Neurofeedbackmentioning

confidence: 99%

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

Saul

Black

et al. 2022

Front. Psychol.

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Social anxiety disorder has been widely recognised as one of the most commonly diagnosed mental disorders. Individuals with social anxiety disorder experience difficulties during social interactions that are essential in the regular functioning of daily routines; perpetually motivating research into the aetiology, maintenance and treatment methods. Traditionally, social and clinical neuroscience studies incorporated protocols testing one participant at a time. However, it has been recently suggested that such protocols are unable to directly assess social interaction performance, which can be revealed by testing multiple individuals simultaneously. The principle of two-person neuroscience highlights the interpersonal aspect of social interactions that observes behaviour and brain activity from both (or all) constituents of the interaction, rather than analysing on an individual level or an individual observation of a social situation. Therefore, two-person neuroscience could be a promising direction for assessment and intervention of the social anxiety disorder. In this paper, we propose a novel paradigm which integrates two-person neuroscience in a neurofeedback protocol. Neurofeedback and interbrain synchrony, a branch of two-person neuroscience, are discussed in their own capacities for their relationship with social anxiety disorder and relevance to the paradigm. The newly proposed paradigm sets out to assess the social interaction performance using interbrain synchrony between interacting individuals, and to employ a multi-user neurofeedback protocol for intervention of the social anxiety.

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Section: Methods For Interbrain Synchrony and Neurofeedbackmentioning

confidence: 99%

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

Saul

Black

et al. 2022

Front. Psychol.

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“…The weighted phase lag index (wPLI) measures the phase correlation between signals by weighting the cross-spectrum of the phases of the two signals. First, we need to calculate the phase lag index (PLI) between the signals (Li et al, 2021):…”

Section: Other Methods To Build Brain Networkmentioning

confidence: 99%

“…where sgn represents the sign function, |•| is absolute value, Δθ(t) represents the instantaneous phase difference between the input signal s 1 and the output signal s 2 . Then, wPLI is calculated to quantify the phase agreement between the signals (Li et al, 2021),…”

Section: Other Methods To Build Brain Networkmentioning

confidence: 99%

Localizing targets for neuromodulation in drug-resistant epilepsy using intracranial EEG and computational model

Liu

2022

Front. Physiol.

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Neuromodulation has emerged as a promising technique for the treatment of epilepsy. The target for neuromodulation is critical for the effectiveness of seizure control. About 30% of patients with drug-resistant epilepsy (DRE) fail to achieve seizure freedom after surgical intervention. It is difficult to find effective brain targets for neuromodulation in these patients because brain regions are damaged during surgery. In this study, we propose a novel approach for localizing neuromodulatory targets, which uses intracranial EEG and multi-unit computational models to simulate the dynamic behavior of epileptic networks through external stimulation. First, we validate our method on a multivariate autoregressive model and compare nine different methods of constructing brain networks. Our results show that the directed transfer function with surrogate analysis achieves the best performance. Intracranial EEGs of 11 DRE patients are further analyzed. These patients all underwent surgery. In three seizure-free patients, the localized targets are concordant with the resected regions. For the eight patients without seizure-free outcome, the localized targets in three of them are outside the resected regions. Finally, we provide candidate targets for neuromodulation in these patients without seizure-free outcome based on virtual resected epileptic network. We demonstrate the ability of our approach to locate optimal targets for neuromodulation. We hope that our approach can provide a new tool for localizing patient-specific targets for neuromodulation therapy in DRE.

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“…Notably, phase synchronization is a way of functional connectivity representation that may show functional connectivity across various cortical areas of the brain and reveal information about the synchronization of the regional cortical activity [ 18 ]. The phase lag index (PLI) is an important index of phase synchronization.…”

Section: Introductionmentioning

confidence: 99%

Phase Lag Index of Resting-State EEG for Identification of Mild Cognitive Impairment Patients with Type 2 Diabetes

Kuang

Xia³

et al. 2022

Brain Sciences

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Mild cognitive impairment (MCI) is one of the important comorbidities of type 2 diabetes mellitus (T2DM). It is critical to find appropriate methods for early diagnosis and objective assessment of mild cognitive impairment patients with type 2 diabetes (T2DM-MCI). Our study aimed to investigate potential early alterations in phase lag index (PLI) and determine whether it can distinguish between T2DM-MCI and normal controls with T2DM (T2DM-NC). EEG was recorded in 30 T2DM-MCI patients and 30 T2DM-NC patients. The phase lag index was computed and used in a logistic regression model to discriminate between groups. The correlation between the phase lag index and Montreal Cognitive Assessment (MoCA) score was assessed. The α-band phase lag index was significantly decreased in the T2DM-MCI group compared with the T2DM-NC group and showed a moderate degree of classification accuracy. The MoCA score was positively correlated with the α-band phase lag index (r = 0.4812, moderate association, p = 0.015). This work shows that the functional connectivity analysis of EEG may offer an effective way to track the cortical dysfunction linked to the cognitive deterioration of T2DM patients, and the α-band phase lag index may have a role in guiding the diagnosis of T2DM-MCI.

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A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test

Cited by 16 publications

References 50 publications

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

Localizing targets for neuromodulation in drug-resistant epilepsy using intracranial EEG and computational model

Phase Lag Index of Resting-State EEG for Identification of Mild Cognitive Impairment Patients with Type 2 Diabetes

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