The dynamic properties of a brain network during working memory based on the algorithm of cross-frequency coupling

Attentional control influence habituation through modulation of connectivity patterns within the prefrontal cortex: Insights from stereo-EEG

Attentional control, guided by top-down processes, enables selective focus on pertinent information, while habituation, influenced by bottom-up factors and prior experiences, shapes cognitive responses by emphasizing stimulus relevance. These two fundamental processes collaborate to regulate cognitive behavior, with the prefrontal cortex and its subregions playing a pivotal role. Nevertheless, the intricate neural mechanisms underlying the interaction between attentional control and habituation are still a subject of ongoing exploration. To our knowledge, there is a dearth of comprehensive studies on the functional connectivity between subsystems within the prefrontal cortex during attentional control processes in both primates and humans. Utilizing stereo-electroencephalogram (SEEG) recordings during the Stroop task, we observed top-down dominance effects and corresponding connectivity patterns among the orbitofrontal cortex (OFC), the middle frontal gyrus (MFG), and the inferior frontal gyrus (IFG) during heightened attentional control. These findings highlighting the involvement of OFC in habituation through top-down attention. Our study unveils unique connectivity profiles, shedding light on the neural interplay between top-down and bottom-up attentional control processes, shaping goal-directed attention.

Altered cortical thickness and structural covariance networks in chronic low back pain

BACKGROUND

Despite regional brain structural changes having been reported in patients with chronic low back pain (CLBP), the topological properties of structural covariance networks (SCNs), which refer to the organization of the SCNs, remain unclear. This study applied graph theoretical analysis to explore the alterations of the topological properties of SCNs, aiming to comprehend the integration and separation of SCNs in patients with CLBP.

METHODS

A total of 38 patients with CLBP and 38 healthy controls (HCs), balanced for age and sex, were scanned using three-dimensional T1-weighted magnetic resonance imaging. The cortical thickness was extracted from 68 brain regions, according to the Desikan-Killiany atlas, and used to reconstruct the SCNs. Subsequently, graph theoretical analysis was employed to evaluate the alterations of the topological properties in the SCNs of patients with CLBP.

RESULTS

In comparison to HCs, patients with CLBP had less cortical thickness in the left superior frontal cortex. Additionally, the cortical thickness of the left superior frontal cortex was negatively correlated with the Visual Analogue Scale scores of patients with CLBP. Furthermore, patients with CLBP, relative to HCs, exhibited lower global efficiency and small-worldness, as well as a longer characteristic path length. This indicates a decline in the brain's capacity to transmit and process information, potentially impacting the processing of pain signals in patients with CLBP and contributing to the development of CLBP. In contrast, there were no significant differences in the clustering coefficient, local efficiency, nodal efficiency, nodal betweenness centrality, or nodal degree between the two groups.

CONCLUSIONS

From the regional cortical thickness to the complex brain network level, our study demonstrated changes in the cortical thickness and topological properties of the SCNs in patients with CLBP, thus aiding in a better understanding of the pathophysiological mechanisms of CLBP.

Mapping brain functional networks topological characteristics in new daily persistent headache: a magnetoencephalography study

BACKGROUND

The brain functional network topology in new daily persistent headache (NDPH) is not well understood. In this study, we aim to assess the cortical functional network topological characteristics of NDPH using non-invasive neural signal recordings.

METHODS

Resting-state magnetoencephalography (MEG) was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 35 patients with NDPH and 40 healthy controls (HCs). Their structural data were collected by 3T MRI. Functional connectivity (FC) of neural networks from 1 to 80 Hz frequency ranges was analyzed with topographic patterns and calculated network topological parameters with graph theory.

RESULTS

In the delta (1-4 Hz) and beta (13-30 Hz) bands, the lateral occipital cortex and superior frontal gyrus FC were increased in NDPH groups compared to HCs. Graph theory analysis revealed that the NDPH had significantly increased global efficiency in the delta band and decreased nodal clustering coefficient (left medial orbitofrontal cortex) in the theta (4-8 Hz) band. The clinical characteristics had a significant correlation with network topological parameters. Age at onset of patients showed a positive correlation with global efficiency in the delta band. The degree of depression of patients showed a negative correlation with the nodal clustering coefficient (left medial orbitofrontal cortex) in the theta band.

CONCLUSION

The FC and topology of NDPH in brain networks may be altered, potentially leading to cortical hyperexcitability. Moreover, medial orbitofrontal cortex is involved in the pathophysiological mechanism of depression in patients with NDPH. Increased FC observed in the lateral occipital cortex and superior frontal gyrus during resting-state MEG could serve as one of the imaging characteristics associated with NDPH.

Effects of high-frequency transcranial magnetic stimulation on theta-gamma oscillations and coupling in the prefrontal cortex of rats during working memory task

High-frequency rTMS has been widely used to improve working memory (WM) impairment; however, the underlying neurophysiological mechanisms are unclear. We evaluated the effect of high-frequency rTMS on behaviors relevant to WM as well as coupling between theta and gamma oscillations in the prefrontal cortex (PFC) of rats. Accordingly, Wistar rats received high-frequency rTMS daily for 14 days (5 Hz, 10 Hz, and 15 Hz stimulation; 600 pulses; n = 6 per group), whereas the control group received sham stimulation. Electrophysiological signals were recorded simultaneously to obtain the local field potential (LFP) from the PFC, while the rats performed T-maze tasks for the evaluation of WM. Phase-amplitude coupling (PAC) was utilized to determine the effect of high-frequency rTMS on the theta-gamma coupling of LFPs. We observed that rats in the rTMS groups needed a smaller number of training days to complete the WM task as compared to the control group. High-frequency rTMS reinforced the coupling connection strength in the PFC of rats. Notably, the effect of rTMS at 15 Hz was the most effective among the three frequencies, i.e., 5 Hz, 10 Hz, and 15 Hz. The results suggested that rTMS can improve WM impairment in rats by modulating the coupling of theta and gamma rhythms. Hence, the current study provides a scientific basis for the optimization of TMS models, which would be relevant for clinical application.

Frequency-dependent effective connections between local signals and the global brain signal during resting-state

The psychological and physiological meanings of resting-state global brain signal (GS) and GS topography have been well confirmed. However, the causal relationship between GS and local signals was largely unknown. Based on the Human Connectome Project dataset, we investigated the effective GS topography using the Granger causality (GC) method. In consistent with GS topography, both effective GS topographies from GS to local signals and from local signals to GS showed greater GC values in sensory and motor regions in most frequency bands, suggesting that the unimodal superiority is an intrinsic architecture of GS topography. However, the significant frequency effect for GC values from GS to local signals was primarily located in unimodal regions and dominated at slow 4 frequency band whereas that from local signals to GS was mainly located in transmodal regions and dominated at slow 6 frequency band, consisting with the opinion that the more integrated the function, the lower the frequency. These findings provided valuable insight for the frequency-dependent effective GS topography, improving the understanding of the underlying mechanism of GS topography.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09831-0.

Toward the Identification of Neurophysiological Biomarkers for Alzheimer's Disease in Down Syndrome: A Potential Role for Cross-Frequency Phase-Amplitude Coupling Analysis

Cross-frequency coupling (CFC) mechanisms play a central role in brain activity. Pathophysiological mechanisms leading to many brain disorders, such as Alzheimer's disease (AD), may produce unique patterns of brain activity detectable by electroencephalography (EEG). Identifying biomarkers for AD diagnosis is also an ambition among research teams working in Down syndrome (DS), given the increased susceptibility of people with DS to develop early-onset AD (DS-AD). Here, we review accumulating evidence that altered theta-gamma phase-amplitude coupling (PAC) may be one of the earliest EEG signatures of AD, and therefore may serve as an adjuvant tool for detecting cognitive decline in DS-AD. We suggest that this field of research could potentially provide clues to the biophysical mechanisms underlying cognitive dysfunction in DS-AD and generate opportunities for identifying EEG-based biomarkers with diagnostic and prognostic utility in DS-AD.

Longitudinal changes in global structural brain connectivity and cognitive performance in former hospitalized COVID-19 survivors: an exploratory study

BACKGROUND

Long-term sequelae of COVID-19 can result in reduced functionality of the central nervous system and substandard quality of life. Gaining insight into the recovery trajectory of admitted COVID-19 patients on their cognitive performance and global structural brain connectivity may allow a better understanding of the diseases' relevance.

OBJECTIVES

To assess whole-brain structural connectivity in former non-intensive-care unit (ICU)- and ICU-admitted COVID-19 survivors over 2 months following hospital discharge and correlate structural connectivity measures to cognitive performance.

METHODS

Participants underwent Magnetic Resonance Imaging brain scans and a cognitive test battery after hospital discharge to evaluate structural connectivity and cognitive performance. Multilevel models were constructed for each graph measure and cognitive test, assessing the groups' influence, time since discharge, and interactions. Linear regression models estimated whether the graph measurements affected cognitive measures and whether they differed between ICU and non-ICU patients.

RESULTS

Six former ICU and six non-ICU patients completed the study. Across the various graph measures, the characteristic path length decreased over time (β = 0.97, p = 0.006). We detected no group-level effects (β = 1.07, p = 0.442) nor interaction effects (β = 1.02, p = 0.220). Cognitive performance improved for both non-ICU and ICU COVID-19 survivors on four out of seven cognitive tests 2 months later (p < 0.05).

CONCLUSION

Adverse effects of COVID-19 on brain functioning and structure abate over time. These results should be supported by future research including larger sample sizes, matched control groups of healthy non-infected individuals, and more extended follow-up periods.

Transcerebral information coordination in directional hippocampus-prefrontal cortex network during working memory based on bimodal neural electrical signals

Working memory (WM) is a kind of advanced cognitive function, which requires the participation and cooperation of multiple brain regions. Hippocampus and prefrontal cortex are the main responsible brain regions for WM. Exploring information coordination between hippocampus and prefrontal cortex during WM is a frontier problem in cognitive neuroscience. In this paper, an advanced information theory analysis based on bimodal neural electrical signals (local field potentials, LFPs and spikes) was employed to characterize the transcerebral information coordination across the two brain regions. Firstly, LFPs and spikes were recorded simultaneously from rat hippocampus and prefrontal cortex during the WM task by using multi-channel in vivo recording technique. Then, from the perspective of information theory, directional hippocampus-prefrontal cortex networks were constructed by using transfer entropy algorithm based on spectral coherence between LFPs and spikes. Finally, transcerebral coordination of bimodal information at the brain-network level was investigated during acquisition and performance of the WM task. The results show that the transfer entropy in directional hippocampus-prefrontal cortex networks is related to the acquisition and performance of WM. During the acquisition of WM, the information flow, local information transmission ability and information transmission efficiency of the directional hippocampus-prefrontal networks increase over learning days. During the performance of WM, the transfer entropy from the hippocampus to prefrontal cortex plays a leading role for bimodal information coordination across brain regions and hippocampus has a driving effect on prefrontal cortex. Furthermore, bimodal information coordination in the hippocampus → prefrontal cortex network could predict WM during the successful performance of WM.

Mapping intrinsic functional network topological architecture in major depression disorder after electroconvulsive therapy

Disrupted topological organization of functional brain networks has been well documented in major depressive disorder (MDD). However, there is no report about how electroconvulsive therapy (ECT), a rapid way for depression remission, affects whole-brain functional network topological architecture to improve clinical symptoms in individuals with MDD. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for twenty-four MDD patients before and after receiving ECT and 25 gender-, age- and education-matched healthy controls (HC). The functional brain network for each subject was mapped using Brainnetome Atlas and graph-theory was applied to measure topological properties for both binary and weighted network. The results showed that ECT can significantly increase shortest path length and decrease global efficiency in MDD patients. In addition, significant alterations in nodal degree, nodal efficiency as well as between nodal functional connectivity strength were found in MDD patients after ECT. The network nodes showing changed degree, efficiency and connectivity were primarily distributed in default mode network (DMN), fronto-parietal network (FPN), and limbic system. Our findings demonstrates that ECT improves depressive symptoms by reorganizing disrupted network topological architecture in MDD patients and highlights the important role of functional reorganization of DMN, FPN, and limbic network contributing to depression remission.

Information transmission in action video gaming experts: Inferences from the lateralized readiness potential

Research showed that action real-time strategy gaming (ARSG) experience is related to cognitive and neural plasticity, including visual selective attention and working memory, executive control, and information processing. This study explored the relationship between ARSG experience and information transmission in the auditory channel. Using an auditory, two-choice, go/no-go task and lateralized readiness potential (LRP) as the index to partial information transmission, this study examined information transmission patterns in ARSG experts and amateurs. Results showed that experts had a higher accuracy rate than amateurs. More importantly, experts had a smaller stimulus-locked LRP component (250 – 450 ms) than amateurs on no-go trials, while the response-locked LRP component (0 – 300 ms) on go trials did not differ between groups. Thus, whereas amateurs used an asynchronous information transmission pattern, experts used a reduced asynchronous information transmission pattern or a synchronous pattern where most of processing occurred prior to response execution – an information transmission pattern that supports rapid, error-free performance. Thus, experts and amateurs may use different information transmission patterns in auditory processing. In addition, the information transmission pattern used by experts is typically observed only after long-term auditory training according to past research. This study supports the relationship between ARSG experience and the development of information processing patterns.

A model of working memory for encoding multiple items and ordered sequences exploiting the theta-gamma code

Recent experimental evidence suggests that oscillatory activity plays a pivotal role in the maintenance of information in working memory, both in rodents and humans. In particular, cross-frequency coupling between theta and gamma oscillations has been suggested as a core mechanism for multi-item memory. The aim of this work is to present an original neural network model, based on oscillating neural masses, to investigate mechanisms at the basis of working memory in different conditions. We show that this model, with different synapse values, can be used to address different problems, such as the reconstruction of an item from partial information, the maintenance of multiple items simultaneously in memory, without any sequential order, and the reconstruction of an ordered sequence starting from an initial cue. The model consists of four interconnected layers; synapses are trained using Hebbian and anti-Hebbian mechanisms, in order to synchronize features in the same items, and desynchronize features in different items. Simulations show that the trained network is able to desynchronize up to nine items without a fixed order using the gamma rhythm. Moreover, the network can replicate a sequence of items using a gamma rhythm nested inside a theta rhythm. The reduction in some parameters, mainly concerning the strength of GABAergic synapses, induce memory alterations which mimic neurological deficits. Finally, the network, isolated from the external environment (“imagination phase”) and stimulated with high uniform noise, can randomly recover sequences previously learned, and link them together by exploiting the similarity among items.

The Functional Interactions between Cortical Regions through Theta-Gamma Coupling during Resting-State and a Visual Working Memory Task

Theta phase-gamma amplitude coupling (TGC) plays an important role in several different cognitive processes. Although spontaneous brain activity at the resting state is crucial in preparing for cognitive performance, the functional role of resting-state TGC remains unclear. To investigate the role of resting-state TGC, electroencephalogram recordings were obtained for 56 healthy volunteers while they were in the resting state, with their eyes closed, and then when they were engaged in a retention interval period in the visual memory task. The TGCs of the two different conditions were calculated and compared. The results indicated that the modulation index of TGC during the retention interval of the visual working memory (VWM) task was not higher than that during the resting state; however, the topographical distribution of TGC during the resting state was negatively correlated with TGC during VWM task at the local level. The topographical distribution of TGC during the resting state was negatively correlated with TGC coordinates’ engagement of brain areas in local and large-scale networks and during task performance at the local level. These findings support the view that TGC reflects information-processing and signal interaction across distant brain areas. These results demonstrate that TGC could explain the efficiency of competing brain networks.

Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

Epilepsy is a chronic brain disease with dysfunctional brain networks, and electroencephalography (EEG) is an important tool for epileptogenic zone (EZ) identification, with rich information about frequencies. Different frequency oscillations have different contributions to brain function, and cross-frequency coupling (CFC) has been found to exist within brain regions. Cross-channel and inter-channel analysis should be both focused because they help to analyze how epilepsy networks change and also localize the EZ. In this paper, we analyzed long-term stereo-electroencephalography (SEEG) data from 17 patients with temporal lobe epilepsy. Single-channel and cross-channel CFC features were combined to establish functional brain networks, and the network characteristics under different periods and the localization of EZ were analyzed. It was observed that theta–gamma phase amplitude coupling (PAC) within the electrodes in the seizure region increased during the ictal (p < 0.05). Theta–gamma and delta–gamma PAC of cross-channel were enhanced in the early and mid-late ictal, respectively. It was also found that there was a strong cross-frequency coupling state between channels of EZ in the functional network during the ictal, along with a more regular network than interictal. The accuracy rate of EZ localization was 82.4%. Overall, the combination of single-channel and multi-channel cross-band coupling analysis can help identify seizures and localize EZ for temporal lobe epilepsy. Rhythmic coupling reveals a relationship between the functional network and the seizure status of epilepsy.

Angiotensin II induces cognitive decline and anxiety-like behavior via disturbing pattern of theta-gamma oscillations

Hypertension is the most common chronic disease accompanied by cognitive decline and anxiety-like behavior. Angiotensin II (Ang II) induces hypertension by activating angiotensin II receptor subtype 1 (AT1R). The purpose of the study was to examine the potential underlying mechanism of alterations in cognition and anxiety-like behavior induced by Ang II. Adult C57 mice were intraperitoneal injected with either 1 mg/kg/d Ang II or saline individually for 14 consecutive days. Ang II resulted in cognitive decline and anxious like behavior in C57 mice. Moreover, Ang II disturbed bidirectional synaptic plasticity and neural oscillation coupling between high theta and gamma on PP (perforant pathway)-DG (dentate gyrus) pathway. In addition, Ang II decreased the expression of N-methyl-d-aspartate receptor (NR) 2A and NR 2B and increased the expression of GABA_AR α1. The data suggest that Ang II disturb neural oscillations via altering excitatory and inhibitory (E/I) balance and eventually damage cognition and anxiety-like behavior in mice.

rTMS alleviates cognitive and neural oscillatory deficits induced by hindlimb unloading in mice via maintaining balance between glutamatergic and GABAergic systems

Microgravity, as a part of the stress of space flight, has several negative effects on cognitive functions. Repetitive transcranial magnetic stimulation (rTMS), as a novel non-invasive technique, could be an effective approach to alleviated cognitive decline, applied in both preclinical and clinical studies. Neural oscillations and their interactions are involved in cognitive functions and support the communication of neural information. The neural oscillation could be a window from which we may understand what happens in the brain. The current study aimed to explore if 15 Hz rTMS plays a neural modulation role in a mouse model of hindlimb unloading. We hypothezed that rTMS can improve the cognitive and neural oscillatory deficits induced by hindlimb unloading via maintaining the balance between glutamatergic and GABAergic systems. Our data show that rTMS can significantly alleviate behavior deficits, modulate theta oscillation, improve the disturbed power distribution of theta oscillation and the decreased strength of Cross-Frequency Coupling in the dentate gyrus region, and effectively mitigated the blocked communication of neural information in the perforant pathway (PP)-dentate gyrus (DG) neural pathway in Hu mice. Furthermore, biochemical analysis using high-performance liquid chromatography and Western blot assay confirmed that rTMS increases the low expression of glutamate (Glu) and N-Methyl d-Aspartate receptor subtype 2B (NR2B) and decreases the high expression of γ-aminobutyric acid (GABA), 67 KDa isoform of glutamate decarboxylase (GAD67), and GABA type A receptor subunit alpha1 (GABAAR_α1) in the hippocampus of Hu mice. Taken together, the results suggest that rTMS plays a significant neural modulation role in the hippocampal neural activity disorders induced by Hu, which possibly depends on rTMS maintaining the balance of glutamatergic and gamma-aminobutyric acidergic (GABAergic) systems.

Research on Differential Brain Networks before and after WM Training under Different Frequency Band Oscillations

Previous studies have shown that different frequency band oscillations are associated with cognitive processing such as working memory (WM). Electroencephalogram (EEG) coherence and graph theory can be used to measure functional connections between different brain regions and information interaction between different clusters of neurons. At the same time, it was found that better cognitive performance of individuals indicated stronger small-world characteristics of resting-state WM networks. However, little is known about the neural synchronization of the retention stage during ongoing WM tasks (i.e., online WM) by training on the whole-brain network level. Therefore, combining EEG coherence and graph theory analysis, the present study examined the topological changes of WM networks before and after training based on the whole brain and constructed differential networks with different frequency band oscillations (i.e., theta, alpha, and beta). The results showed that after WM training, the subjects' WM networks had higher clustering coefficients and shorter optimal path lengths than before training during the retention period. Moreover, the increased synchronization of the frontal theta oscillations seemed to reflect the improved executive ability of WM and the more mature resource deployment; the enhanced alpha oscillatory synchronization in the frontoparietal and fronto-occipital regions may reflect the enhanced ability to suppress irrelevant information during the delay and pay attention to memory guidance; the enhanced beta oscillatory synchronization in the temporoparietal and frontoparietal regions may indicate active memory maintenance and preparation for memory-guided attention. The findings may add new evidence to understand the neural mechanisms of WM on the changes of network topological attributes in the task-related mode.

Disc1 gene down-regulation impaired synaptic plasticity and recognition memory via disrupting neural activity in mice

The gene of Disrupted-in-schizophrenia 1 (Disc1) is closely related to mental diseases with cognitive deficits, but there are few studies on the changes in neural oscillations and recognition memory. Neural oscillations plays a key role in the nervous system in a dynamic form, which is closely related to advanced cognitive activities such as information processing and memory consolidation. Hence, we aimed to investigate if Disc1 knockdown disrupted the normal pattern of neural activities in the mouse hippocampus network, and determined if quantitative neural oscillation approach could be a potential diagnostic tool for mental disorders. In the study, we reported that Disc1 gene, downregulated by short-hairpin RNA (shRNA), not only induced anxiety-like behavior and sociability impairment but also damaged both synaptic plasticity and recognition memory in mice. Moreover, Disc1 knockdown mice exhibited evidently abnormal power spectral distributions, reduced phase synchronizations, and decreased phase-amplitude coupling strength compared to that of normal animals. In addition, transcriptome analyses showed that there were clearly transcriptional changes in Disc1 knockdown mice. Altogether, our findings suggest that the abnormal pattern of neural activities in the hippocampus network disrupts information processing and finally leads to the impairments of synaptic plasticity and recognition in Disc1 knockdown mice, which are possibly associated with the obstruction of neurotransmitter transmission. Importantly, the data imply that the analysis of neural oscillation pattern provides a potential diagnosis approach for mental disorders.

EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions

Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed.

Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise

With the continuous improvement of automation and informatization, the electromagnetic environment has become increasingly complex. Traditional protection methods for electronic systems are facing with serious challenges. Biological nervous system has the self-adaptive advantages under the regulation of the nervous system. It is necessary to explore a new thought on electromagnetic protection by drawing from the self-adaptive advantage of the biological nervous system. In this study, the scale-free spiking neural network (SFSNN) is constructed, in which the Izhikevich neuron model is employed as a node, and the synaptic plasticity model including excitatory and inhibitory synapses is employed as an edge. Under white Gaussian noise, the noise suppression abilities of the SFSNNs with the high average clustering coefficient (ACC) and the SFSNNs with the low ACC are studied comparatively. The noise suppression mechanism of the SFSNN is explored. The experiment results demonstrate that the following. (1) The SFSNN has a certain degree of noise suppression ability, and the SFSNNs with the high ACC have higher noise suppression performance than the SFSNNs with the low ACC. (2) The neural information processing of the SFSNN is the linkage effect of dynamic changes in neuron firing, synaptic weight and topological characteristics. (3) The synaptic plasticity is the intrinsic factor of the noise suppression ability of the SFSNN.

Cross-frequency and iso-frequency estimation of functional corticomuscular coupling after stroke

Functional corticomuscular coupling (FCMC) between the brain and muscles has been used for motor function assessment after stroke. Two types, iso-frequency coupling (IFC) and cross-frequency coupling (CFC), are existed in sensory-motor system for healthy people. However, in stroke, only a few studies focused on IFC between electroencephalogram (EEG) and electromyogram (EMG) signals, and no CFC studies have been found. Considering the intrinsic complexity and rhythmicity of the biological system, we first used the wavelet package transformation (WPT) to decompose the EEG and EMG signals into several subsignals with different frequency bands, and then applied transfer entropy (TE) to analyze the IFC and CFC relationship between each pair-wise subsignal. In this study, eight stroke patients and eight healthy people were enrolled. Results showed that both IFC and CFC still existed in stroke patients (EEG → EMG: 1:1, 3:2, 2:1; EMG → EEG: 1:1, 2:1, 2:3, 3:1). Compared with the stroke-unaffected side and healthy controls, the stroke-affected side yielded lower alpha, beta and gamma synchronization (IFC: beta; CFC: alpha, beta and gamma). Further analysis indicated that stroke patients yielded no significant difference of the FCMC between EEG → EMG and EMG → EEG directions. Our study indicated that alpha and beta bands were essential to concentrating and maintaining the motor capacities, and provided a new insight in understanding the propagation and function in the sensory-motor system.

Role of joint language control during cross-language communication: evidence from cross-frequency coupling

How do bilingual interlocutors inhibit interference from the non-target language to achieve brain-to-brain information exchange in a task to simulate a bilingual speaker-listener interaction. In the current study, two electroencephalogram devices were employed to record pairs of participants' performances in a joint language switching task. Twenty-eight (14 pairs) unbalanced Chinese-English bilinguals (L1 Chinese) were instructed to name pictures in the appropriate language according to the cue. The phase-amplitude coupling analysis was employed to reveal the large-scale brain network responsible for joint language control between interlocutors. We found that (1) speakers and listeners coordinately suppressed cross-language interference through cross-frequency coupling, as shown in the increased delta/theta phase-amplitude and delta/alpha phase-amplitude coupling when switching to L2 than switching to L1; (2) speakers and listeners were both able to simultaneously inhibit cross-person item-level interference which was demonstrated by stronger cross-frequency coupling in the cross person condition compared to the within person condition. These results indicate that current bilingual models (e.g., the inhibitory control model) should incorporate mechanisms that address inhibiting interference sourced in both language and person (i.e., cross-language and cross-person item-level interference) synchronously through joint language control in dynamic cross-language communication.