Phase-Amplitude Coupling of Neural Oscillations Can Be Effectively Probed with Concurrent TMS-EEG

Increased theta-low gamma phase-amplitude coupling in resting electroencephalography after intermittent theta burst stimulation

OBJECTIVE

Intermittent theta burst stimulation (iTBS) is based on the phase-amplitude coupling (PAC) pattern. We aimed to investigate the effect of iTBS on PAC in resting electroencephalography (EEG), which may provide insight into the underlying mechanism.

METHODS

Twenty-one healthy volunteers were recruited and received both active and sham neuroimaging-guided iTBS on two separate days, which was precisely delivered to the right superior temporal gyrus. On each experimental day, resting EEG was recorded before and after stimulation for each participant. PACs across electrodes and frequency bands were calculated and compared to investigate the effect of iTBS.

RESULTS

Theta (4-6 Hz) -low gamma (45-55 Hz) PAC over the stimulation site had a significant interaction effect, which increased after the active iTBS but did not differ after the sham iTBS. No significant interaction effect occurred in other cross-frequency couplings such as delta-low gamma, alpha-low gamma, delta-high gamma, theta-high gamma, or alpha-high gamma PAC in the region of interest.

CONCLUSION

iTBS selectively modulated theta-low gamma PAC at the stimulation area, which exhibited both region- and frequency- specificity. This suggests that PAC may be a bridge connecting external neuromodulation to internal neuroplasticity.

Early adolescent psychological distress and cognition, correlates of resting-state EEG, interregional phase-amplitude coupling

Delineating neurobiological markers of youth mental health is crucial for early identification and treatment. One promising marker is phase-amplitude coupling (PAC), cross-frequency coupling between the phase of slower oscillatory activity and the amplitude of faster oscillatory activity in the brain. Prior research has demonstrated that PAC is associated with both cognition and mental health and can be modulated using neurostimulation. However, to date research investigating PAC has focused primarily on adults, and only within-region theta-gamma coupling in the context of mental health. We investigated associations between interregional resting-state PAC (posterior-anterior cortex), and cognition and psychological distress in N = 77 (M_age = 12.58 years, SD = 0.31; 51 % female) 12-year-olds. Firstly, while left theta-beta PAC showed a moderate positive correlation (r = 0.529, p < .01), right theta-gamma PAC showed a weak positive correlation, with psychological distress (r = 0.283, p < .05). In terms of cognition, moderate correlations were observed between: (i) increased left theta-beta PAC and increased psychomotor speed (r = -0.367, p < .05); (ii) increased left alpha-beta PAC and decreased attention (r = 0.355, p ≤0.01); and (iii) increased left alpha-beta PAC and decreased verbal learning and memory (r = -0.352, p < .01). Whereas weak associations were observed for: (i) increased left alpha-beta PAC and decreased executive functioning scores (r = 0.284, p < .05); and (ii) increased left alpha-gamma PAC and increased attention (r = -0.272, p < .05). The overall findings of this exploratory study are encouraging, although all the correlations were in the weak-to-moderate range and require replication. Further research may confirm interregional resting-state PAC as a biomarker that can help us better understand the link between mental health and cognition in adolescents and improve treatment of cognitive related deficits in mental illness.

Assessing the Longitudinal Relationship between Theta-Gamma Coupling and Working Memory Performance in Older Adults

Theta-gamma coupling (TGC) is a neurophysiologic mechanism that supports working memory (WM). TGC is associated with N-back performance, a WM task. Similar to TGC, theta and alpha event-related synchronization (ERS) and desynchronization (ERD) are also associated with WM. Few studies have examined the longitudinal relationship between WM performance and TGC, ERS, or ERD. This study aimed to determine if changes in WM performance are associated with changes in TGC (primary aim), as well as theta and alpha ERS or ERD over 6 to 12 weeks. Participants included 62 individuals aged 60 and older with no neuropsychiatric conditions or with remitted Major Depressive Disorder (MDD) and no cognitive disorders. TGC, ERS, and ERD were assessed using electroencephalography (EEG) during the N-back task (3-back condition). There was an association between changes in 3-back performance and changes in TGC, alpha ERD and ERS, and theta ERS in the control group. In contrast, there was only a significant association between changes in 3-back performance and changes in TGC in the subgroup with remitted MDD. Our results suggest that the relationship between WM performance and TGC is stable over time, while this is not the case for changes in theta and alpha ERS and ERD.

Peripheral Somatosensory Entrainment Modulates the Cross-Frequency Coupling of Movement-Related Theta-Gamma Oscillations

Background: Motor control requires a reciprocal volley between somatosensory and motor systems, with somatosensory feedback being essential for the online updating of motor commands to achieve behavioral outcomes. However, this dynamic interplay among sensorimotor brain systems serving motor control remains poorly understood. Methods: To address this, we designed a novel somatosensory entrainment-movement task, which 25 adults completed during magnetoencephalography (MEG). Specifically, participants completed a quasi-paced finger-tapping paradigm while subthreshold electrical stimulation was applied to the right median nerve at a sensorimotor-relevant frequency (15 Hz) and during a second condition where no electrical stimulation was applied. The MEG data were transformed into the time-frequency domain and imaged by using a beamformer to evaluate the effect of somatosensory feedback (i.e., entrainment) on movement-related oscillations and motor performance at the single trial level. Results: Our results indicated spectrally specific reductions in movement-related oscillatory power (i.e., theta, gamma) during 15 Hz stimulation in the contralateral motor cortex during motor execution. In addition, we observed robust cross-frequency coupling within the motor cortex and further, stronger theta-gamma coupling was predictive of faster reaction times, irrespective of condition (i.e., stim vs. no stim). Finally, in the presence of electrical stimulation, cross-frequency coupling of movement-related oscillations was reduced, and the stronger the entrained neuronal populations (i.e., increased oscillatory power) were before movement onset, the weaker the inherent theta-gamma coupling became in the motor cortex. Discussion: This novel exogenous manipulation paradigm provides key insights on how the somatosensory system modulates the motor cortical oscillations required for volitional movement in the normative sensorimotor system.

The metastable brain associated with autistic-like traits of typically developing individuals

Metastability in the brain is thought to be a mechanism involved in the dynamic organization of cognitive and behavioral functions across multiple spatiotemporal scales. However, it is not clear how such organization is realized in underlying neural oscillations in a high-dimensional state space. It was shown that macroscopic oscillations often form phase-phase coupling (PPC) and phase-amplitude coupling (PAC), which result in synchronization and amplitude modulation, respectively, even without external stimuli. These oscillations can also make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalographic signals and the autism-spectrum quotient scores acquired from healthy humans, we show experimental evidence that the PAC combined with PPC allows amplitude modulation to be transient, and that the metastable dynamics with this transient modulation is associated with autistic-like traits. In individuals with a longer attention span, such dynamics tended to show fewer transitions between states by forming delta-alpha PAC. We identified these states as two-dimensional metastable states that could share consistent patterns across individuals. Our findings suggest that the human brain dynamically organizes inter-individual differences in a hierarchy of macroscopic oscillations with multiple timescales by utilizing metastability.

The human brain organizes cognitive and behavioral functions dynamically. For decades, the dynamic organization of underlying neural oscillations has been a fundamental topic in neuroscience research. Even without external stimuli, macroscopic oscillations often form phase-phase coupling and phase-amplitude coupling (PAC) that result in synchronization and amplitude modulation, respectively, and can make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalography signals acquired from healthy humans, we show evidence that these two neural couplings enable amplitude modulation to be transient, and that this transient modulation can be viewed as the transition among oscillatory states with different PAC strengths. We also demonstrate that such transition dynamics are associated with the ability to maintain attention to detail and to switch attention, as measured by autism-spectrum quotient scores. These individual dynamics were visualized as a trajectory among states with attracting tendencies, and involved consistent brain states across individuals. Our findings have significant implications for unraveling the variability in the individual brains showing typical and atypical development.

Frequency- and Area-Specific Phase Entrainment of Intrinsic Cortical Oscillations by Repetitive Transcranial Magnetic Stimulation

Synchronous oscillations are ubiquitous throughout the cortex, but the frequency of oscillations differs from area to area. To elucidate the mechanistic architectures underlying various rhythmic activities, we tested whether spontaneous neural oscillations in different local cortical areas and large-scale networks can be phase-entrained by direct perturbation with distinct frequencies of repetitive transcranial magnetic stimulation (rTMS). While recording the electroencephalogram (EEG), we applied single-pulse TMS (sp-TMS) and rTMS at 5, 11, and 23 Hz over the motor or visual cortex. We assessed local and global modulation of phase dynamics using the phase-locking factor (PLF). sp-TMS to the motor and the visual cortex triggered a transient increase in PLF in distinct frequencies that peaked at 21 and 8 Hz, respectively. rTMS at 23 Hz over the motor cortex and 11 Hz over the visual cortex induced a prominent and progressive increase in PLF that lasted for a few cycles after the termination of rTMS. Moreover, the local increase in PLF propagated to other cortical areas. These results suggest that distinct cortical areas have area-specific oscillatory frequencies, and the manipulation of oscillations in local areas impacts other areas through the large-scale oscillatory network with the corresponding frequency specificity. We speculate that rTMS that is close to area-specific frequencies (natural frequencies) enables direct manipulation of brain dynamics and is thus useful for investigating the causal roles of synchronous neural oscillations. Moreover, this technique could be used to treat clinical symptoms associated with impaired oscillations and synchrony.

Objective Extraction of Evoked Event-Related Oscillation from Time-Frequency Representation of Event-Related Potentials

Evoked event-related oscillations (EROs) have been widely used to explore the mechanisms of brain activities for both normal people and neuropsychiatric disease patients. In most previous studies, the calculation of the regions of evoked EROs of interest is commonly based on a predefined time window and a frequency range given by the experimenter, which tends to be subjective. Additionally, evoked EROs sometimes cannot be fully extracted using the conventional time-frequency analysis (TFA) because they may be overlapped with each other or with artifacts in time, frequency, and space domains. To further investigate the related neuronal processes, a novel approach was proposed including three steps: (1) extract the temporal and spatial components of interest simultaneously by temporal principal component analysis (PCA) and Promax rotation and project them to the electrode fields for correcting their variance and polarity indeterminacies, (2) calculate the time-frequency representations (TFRs) of the back-projected components, and (3) compute the regions of evoked EROs of interest on TFRs objectively using the edge detection algorithm. We performed this novel approach, conventional TFA, and TFA-PCA to analyse both the synthetic datasets with different levels of SNR and an actual ERP dataset in a two-factor paradigm of waiting time (short/long) and feedback (loss/gain) separately. Synthetic datasets results indicated that N2-theta and P3-delta oscillations can be stably detected from different SNR-simulated datasets using the proposed approach, but, by comparison, only one oscillation was obtained via the last two approaches. Furthermore, regarding the actual dataset, the statistical results for the proposed approach revealed that P3-delta was sensitive to the waiting time but not for that of the other approaches. This study manifested that the proposed approach could objectively extract evoked EROs of interest, which allows a better understanding of the modulations of the oscillatory responses.

Information-theoretic approach to detect directional information flow in EEG signals induced by TMS

Effective connectivity analysis has been widely applied to noninvasive recordings such as functional magnetic resonance imaging and electroencephalograms (EEGs). Previous studies have aimed to extract the causal relations between brain regions, but the validity of the derived connectivity has not yet been fully determined. This is because it is generally difficult to identify causality in the usual experimental framework based on observations alone. Transcranial magnetic stimulation (TMS) provides a framework in which a controllable perturbation is applied to a local brain region and the effect is examined by comparing the neural activity with and without this stimulation. This study evaluates two methods for effective connectivity analysis, symbolic transfer entropy (STE) and vector autoregression (VAR), by applying them to TMS-EEG data. In terms of the consistency of results from different experimental sessions, STE is found to yield robust results irrespective of sessions, whereas VAR produces less correlation between sessions. Furthermore, STE preferentially detects the directional information flow from the TMS target. Taken together, our results suggest that STE is a reliable method for detecting the effect of TMS, implying that it would also be useful for identifying neural activity during cognitive tasks and resting states.