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Brain responses to transcranial magnetic stimulation (TMS) as measured with electroencephalography (EEG) have so far been assessed either by TMS-evoked EEG potentials (TEPs), mostly reflecting phase-locked neuronal activity, or time-frequency-representations (TFRs), reflecting oscillatory power arising from a mixture of both evoked (i.e., phase-locked) and induced (i.e., non-phase-locked) responses. Single-pulse TMS of the human primary motor cortex induces a specific pattern of oscillatory changes, characterized by an early (30–200 ms after TMS) synchronization in the α- and β-bands over the stimulated sensorimotor cortex and adjacent lateral frontal cortex, followed by a late (200–400 ms) α- and β-desynchronization over the stimulated and contralateral sensorimotor cortex. As GABAergic inhibition plays an important role in shaping oscillatory brain activity, we sought here to understand if GABAergic inhibition contributes to these TMS-induced oscillations. We tested single oral doses of alprazolam, diazepam, zolpidem (positive modulators of the GABAA receptor), and baclofen (specific GABAB receptor agonist). Diazepam and zolpidem enhanced, and alprazolam tended to enhance while baclofen decreased the early α-synchronization. Alprazolam and baclofen enhanced the early β-synchronization. Baclofen enhanced the late α-desynchronization, and alprazolam, diazepam and baclofen enhanced the late β-desynchronization. The observed GABAergic drug effects on TMS-induced α- and β-band oscillations were not explained by drug-induced changes on corticospinal excitability, muscle response size, or resting-state EEG power. Our results provide first insights into the pharmacological profile of TMS-induced oscillatory responses of motor cortex. •The response to TMS of M1 is composed of evoked and induced oscillatory activity.•TMS induced early α-/β-synchronization and late α-/β-desynchronization in M1.•GABAAergic vs. GABABergic drugs had opposite effects on early α-synchronization.•GABAAergic and GABABergic drugs enhanced the late β-desynchronization.

\"At once elegant and riveting, SYNC tells the story of the dawn of a new science. As one of its pioneers, Steven Strogatz, a leading mathematician in the fields of chaos and complexity theory, it explains how enormous systems can synchronize themselves, from the electrons in a superconductor to the pacemaker cells in our hearts. He shows that although these phenomena might seem unrelated on the surface, at a deeper level there is a connection, forged by the unifying power of mathematics.\"

Teacher–student interaction allows students to combine prior knowledge with new information to develop new knowledge. It is widely understood that both communication mode and students' knowledge state contribute to the teaching effectiveness (i.e., higher students' scores), but the nature of the interplay of these factors and the underlying neural mechanism remain unknown. In the current study, we manipulated the communication modes (face-to-face [FTF] communication mode/computer-mediated communication [CMC] mode) and prior knowledge states (with vs. without) when teacher–student dyads participated in a teaching task. Using functional near-infrared spectroscopy, the brain activities of both the teacher and student in the dyads were recorded simultaneously. After teaching, perceived teacher–student interaction and teaching effectiveness were assessed. The behavioral results demonstrated that, during teaching with prior knowledge, FTF communication improved students' academic performance, as compared with CMC. Conversely, no such effect was found for teaching without prior knowledge. Accordingly, higher task-related interpersonal neural synchronization (INS) in the left prefrontal cortex (PFC) was found in the FTF teaching condition with prior knowledge. Such INS mediated the relationship between perceived interaction and students' test scores. Furthermore, the cumulative INS in the left PFC could predict the teaching effectiveness early in the teaching process (around 25–35 s into the teaching task) only in FTF teaching with prior knowledge. These findings provide insight into how the interplay between the communication mode and students’ knowledge state affects teaching effectiveness. Moreover, our findings suggest that INS could be a possible neuromarker for dynamic evaluation of teacher–student interaction and teaching effectiveness.

In recent years there has been growing interest in measuring time-varying functional connectivity between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data. One way to assess the relationship between signals from different brain regions is to measure their phase synchronization (PS) across time. There are several ways to perform such analyses, and we compare methods that utilize a PS metric together with a sliding window, referred to here as windowed phase synchronization (WPS), with those that directly measure the instantaneous phase synchronization (IPS). In particular, IPS has recently gained popularity as it offers single time-point resolution of time-resolved fMRI connectivity. In this paper, we discuss the underlying assumptions required for performing PS analyses and emphasize the importance of band-pass filtering the data to obtain valid results. Further, we contrast this approach with the use of Empirical Mode Decomposition (EMD) to achieve similar goals. We review various methods for evaluating PS and introduce a new approach within the IPS framework denoted the cosine of the relative phase (CRP). We contrast methods through a series of simulations and application to rs-fMRI data. Our results indicate that CRP outperforms other tested methods and overcomes issues related to undetected temporal transitions from positive to negative associations common in IPS analysis. Further, in contrast to phase coherence, CRP unfolds the distribution of PS measures, which benefits subsequent clustering of PS matrices into recurring brain states.

•We aimed to investigate the underlying neural correlates of interpersonal emotion regulation (IER) facilitating interpersonal relationship closeness (IRC) using a multi-brain neuroimaging (i.e., hyperscanning) in friend partners.•Cognitive reappraisal (CR) is more effective to down-regulate the target's sadness, and expressive suppression (ES) is more effective to decrease other's anger.•Interpersonal brain synchronization (IBS) associated regions within intrapersonal emotion regulation, mentalizing and social cognition systems played an important role in facilitating the IRC through the effectiveness of IER. Interpersonal emotion regulation (IER) refers to the dynamic process where a regulator employs specific strategies to alleviate a target's distress. It remains unclear whether successful IER could facilitate interpersonal relationship closeness (IRC). The present study aimed to explore whether successful IER, based on two typical strategies—cognitive reappraisal (CR) and expressive suppression (ES)—for down-regulating the target's negative emotions, could enhance IRC among friend dyads, and to identify the underlying neural correlates of this process using functional near-infrared spectroscopy system. Seventy-four female dyads (friends) were randomly assigned to one of two strategy groups (CR vs. ES), with one participant as the target and the other as the regulator. Our findings revealed that both strategies have down-regulated the target's negative emotions, however, CR strategy was associated with more successful IER outcomes (more improvement of the targets’ negative emotions; higher IRC) than ES strategy. IER recruited the enhanced interpersonal brain synchronization (IBS) of the prefrontal and temporal areas among friend dyads. CR strategy recruited higher IBS of the above-mentioned brain networks than ES strategy in down-regulating the target's sadness, and the reversed IBS pattern was found in down-regulating the target's anger, inferring that CR was more successive in IER of sadness, and ES was more effective in IER of anger. The increased IBS pattern of these brain regions played a mediational role between the effectiveness of down-regulating targets’ negative emotions and the increment of IRC. Our findings revealed a neural coupling mechanism through which successful IER fostered supportive social bonds.

The EEG/MEG signal is generated primarily by the summation of the post-synaptic potentials of cortical principal cells. At a microcircuit level, these glutamatergic principal cells are reciprocally connected to GABAergic interneurons and cortical oscillations are thought to be dependent on the balance of excitation and inhibition between these cell types. To investigate the dependence of movement-related cortical oscillations on excitation–inhibition balance, we pharmacologically manipulated the GABA system using tiagabine, which blocks GABA Transporter 1(GAT-1), the GABA uptake transporter and increases endogenous GABA activity. In a blinded, placebo-controlled, crossover design, in 15 healthy participants we administered either 15mg of tiagabine or a placebo. We recorded whole-head magnetoencephalograms, while the participants performed a movement task, prior to, one hour post, three hour post and five hour post tiagabine ingestion. Using time-frequency analysis of beamformer source reconstructions, we quantified the baseline level of beta activity (15–30Hz), the post-movement beta rebound (PMBR), beta event-related desynchronisation (beta-ERD) and movement-related gamma synchronisation (MRGS) (60–90Hz). Our results demonstrated that tiagabine, and hence elevated endogenous GABA levels causes, an elevation of baseline beta power, enhanced beta-ERD and reduced PMBR, but no modulation of MRGS. Comparing our results to recent literature (Hall et al., 2011) we suggest that beta-ERD may be a GABAA receptor mediated process while PMBR may be GABAB receptor mediated. ► Recorded MEG during a movement task before and after tiagabine or placebo ► Tiagabine elevates the activity of endogenous GABA. ► Results showed increased beta-ERD, decreased PMBR and no change in MRGS. ► It is suggested that beta-ERD depends on GABAA while PMBR depends on GABAB.

Aberrant gamma-band (30-80 Hz) oscillations may underlie cognitive deficits in schizophrenia (SZ). Gamma oscillations and their regulation by NMDA receptors can be studied via their evoked power (γEP) and phase locking (γPL) in response to auditory steady-state stimulation; these auditory steady-state responses (ASSRs) may be biomarkers for target engagement and early therapeutic effects. We previously reported that memantine, an NMDA receptor antagonist, enhanced two biomarkers of early auditory information processing: prepulse inhibition and mismatch negativity (MMN) in SZ patients and healthy subjects (HS). Here, we describe memantine effects on γEP and γPL in those subjects. SZ patients (n=18) and HS (n=14) received memantine 20 mg (p.o.) and placebo over 2 test days in a double-blind, randomized, counterbalanced, cross-over design. The ASSR paradigm (1 ms, 85 dB clicks in 250-0.5 s trains at a frequency of 40 Hz; 0.5 s inter-train interval) was used to assess γEP and γPL. SZ patients had reduced γEP and γPL; memantine enhanced γEP and γPL (p<0.025 and 0.002, respectively) in both SZ and HS. In patients, significant correlations between age and memantine effects were detected for γEP and γPL: greater memantine sensitivity on γEP and γPL were present in younger SZ patients, similar to our reported findings with MMN. Memantine acutely normalized cortical oscillatory dynamics associated with NMDA receptor dysfunction in SZ patients. Ongoing studies will clarify whether these acute changes predict beneficial clinical, neurocognitive and functional outcomes. These data support the use of gamma-band ASSR as a translational end point in pro-cognitive drug discovery and early-phase clinical trials.

Memristive electromagnetic induction effect has been widely explored in bi-neuron network with homogeneous neurons, but rarely in bi-neuron network with heterogeneous ones. This paper builds a bi-neuron network by coupling heterogeneous Rulkov neurons with memristor and investigates the memristive electromagnetic induction effect. Theoretical analysis discloses that the bi-neuron network possesses a line equilibrium state and its stability depends on the memristor coupling strength and initial condition. That is, the stability of the line equilibrium state has a transition between unstable saddle-focus and stable node-focus via Hopf bifurcation. By employing parameters located in the stable node-focus region, dynamical behaviors related to the memristor coupling strength and initial conditions are revealed by Julia- and MATLAB-based multiple numerical tools. Numerical results demonstrate that the proposed heterogeneous bi-neuron Rulkov network can generate point attractor, period, chaos, chaos crisis, and period-doubling bifurcation. Note that extreme multistability are disclosed with respect to initial conditions of memristor and gated ion concentration. Coexisting infinitely multiple firing patterns of periodic firing patterns with different periodicities and chaotic firing patterns for different memristor initial conditions are demonstrated by phase portrait and time-domain waveform. Besides, the phase synchronization related to the memristor coupling strength and its initial condition is explored, which suggests that the two heterogeneous neurons become phase synchronization with large memristor coupling strength and initial condition. This also reflects that the plasticity of memristor synapse enables adaptive regulation in keeping energy balance between the neurons. What’s more, MCU-based hardware experiments are executed to further confirm the numerical simulations.

This paper is concerned with the co-existence of different synchronization types for fractional-order discrete-time chaotic systems with different dimensions. In particular, we show that through appropriate nonlinear control, projective synchronization (PS), full state hybrid projective synchronization (FSHPS), and generalized synchronization (GS) can be achieved simultaneously. A second nonlinear control scheme is developed whereby inverse full state hybrid projective synchronization (IFSHPS) and inverse generalized synchronization (IGS) are shown to co-exist. Numerical examples are presented to confirm the findings.