The Hierarchy of Coupled Sleep Oscillations Reverses with Aging in Humans.

A well orchestrated coupling hierarchy of slow waves and spindles during slow-wave sleep supports memory consolidation. In old age, the duration of slow-wave sleep and the number of coupling events decrease. The coupling hierarchy deteriorates, predicting memory loss and brain atrophy. Here, we investigate the dynamics of this physiological change in slow wave-spindle coupling in a frontocentral electroencephalography position in a large sample (N = 340; 237 females, 103 males) spanning most of the human life span (age range, 15-83 years). We find that, instead of changing abruptly, spindles gradually shift from being driven by slow waves to driving slow waves with age, reversing the coupling hierarchy typically seen in younger brains. Reversal was stronger the lower the slow-wave frequency, and starts around midlife (age range, ∼40-48 years), with an established reversed hierarchy between 56 and 83 years of age. Notably, coupling strength remains unaffected by age. In older adults, deteriorating slow wave-spindle coupling, measured using the phase slope index (PSI) and the number of coupling events, is associated with blood plasma glial fibrillary acidic protein levels, a marker for astrocyte activation. Data-driven models suggest that decreased sleep time and higher age lead to fewer coupling events, paralleled by increased astrocyte activation. Counterintuitively, astrocyte activation is associated with a backshift of the coupling hierarchy (PSI) toward a "younger" status along with increased coupling occurrence and strength, potentially suggesting compensatory processes. As the changes in coupling hierarchy occur gradually starting at midlife, we suggest there exists a sizable window of opportunity for early interventions to counteract undesirable trajectories associated with neurodegeneration.SIGNIFICANCE STATEMENT Evidence accumulates that sleep disturbances and cognitive decline are bidirectionally and causally linked, forming a vicious cycle. Improving sleep quality could break this cycle. One marker for sleep quality is a clear hierarchical structure of sleep oscillations. Previous studies showed that sleep oscillations decouple in old age. Here, we show that, rather, the hierarchical structure gradually shifts across the human life span and reverses in old age, while coupling strength remains unchanged. This shift is associated with markers for astrocyte activation in old age. The shifting hierarchy resembles brain maturation, plateau, and wear processes. This study furthers our comprehension of this important neurophysiological process and its dynamic evolution across the human life span.

Speech Reception in Young Children with Autism Is Selectively Indexed by a Neural Oscillation Coupling Anomaly.

Communication difficulties are one of the core criteria in diagnosing autism spectrum disorder (ASD), and are often characterized by speech reception difficulties, whose biological underpinnings are not yet identified. This deficit could denote atypical neuronal ensemble activity, as reflected by neural oscillations. Atypical cross-frequency oscillation coupling, in particular, could disrupt the joint tracking and prediction of dynamic acoustic stimuli, a dual process that is essential for speech comprehension. Whether such oscillatory anomalies already exist in very young children with ASD, and with what specificity they relate to individual language reception capacity is unknown. We collected neural activity data using electroencephalography (EEG) in 64 very young children with and without ASD (mean age 3; 17 females, 47 males) while they were exposed to naturalistic-continuous speech. EEG power of frequency bands typically associated with phrase-level chunking (δ, 1-3 Hz), phonemic encoding (low-γ, 25-35 Hz), and top-down control (ß, 12-20 Hz) were markedly reduced in ASD relative to typically developing (TD) children. Speech neural tracking by δ and θ (4-8 Hz) oscillations was also weaker in ASD compared with TD children. After controlling gaze-pattern differences, we found that the classical θ/γ coupling was replaced by an atypical ß/γ coupling in children with ASD. This anomaly was the single most specific predictor of individual speech reception difficulties in ASD children. These findings suggest that early interventions (e.g., neurostimulation) targeting the disruption of ß/γ coupling and the upregulation of θ/γ coupling could improve speech processing coordination in young children with ASD and help them engage in oral interactions.SIGNIFICANCE STATEMENT Very young children already present marked alterations of neural oscillatory activity in response to natural speech at the time of autism spectrum disorder (ASD) diagnosis. Hierarchical processing of phonemic-range and syllabic-range information (θ/γ coupling) is disrupted in ASD children. Abnormal bottom-up (low-γ) and top-down (low-ß) coordination specifically predicts speech reception deficits in very young ASD children, and no other cognitive deficit.

Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

Data-driven MEG analysis to extract fMRI resting-state networks.

The electrophysiological basis of resting-state networks (RSN) is still under debate. In particular, no principled mechanism has been determined that is capable of explaining all RSN equally well. While magnetoencephalography (MEG) and electroencephalography are the methods of choice to determine the electrophysiological basis of RSN, no standard analysis pipeline of RSN yet exists. In this article, we compare the two main existing data-driven analysis strategies for extracting RSNs from MEG data and introduce a third approach. The first approach uses phase-amplitude coupling to determine the RSN. The second approach extracts RSN through an independent component analysis of the Hilbert envelope in different frequency bands, while the third new approach uses a singular value decomposition instead. To evaluate these approaches, we compare the MEG-RSN to the functional magnetic resonance imaging (fMRI)-RSN from the same subjects. Overall, it was possible to extract RSN with MEG using all three techniques, which matched the group-specific fMRI-RSN. Interestingly the new approach based on SVD yielded significantly higher correspondence to five out of seven fMRI-RSN than the two existing approaches. Importantly, with this approach, all networks-except for the visual network-had the highest correspondence to the fMRI networks within one frequency band. Thereby we provide further insights into the electrophysiological underpinnings of the fMRI-RSNs. This knowledge will be important for the analysis of the electrophysiological connectome.

Dynamic evolution of frontal-temporal network connectivity in temporal lobe epilepsy: A magnetoencephalography study.

Temporal lobe epilepsy (TLE) frequently involves an intricate, extensive epileptic frontal-temporal network. This study aimed to investigate the interactions between temporal and frontal regions and the dynamic patterns of the frontal-temporal network in TLE patients with different disease durations. The magnetoencephalography data of 36 postoperative seizure-free patients with long-term follow-up of at least 1 year, and 21 age- and sex-matched healthy subjects were included in this study. Patients were initially divided into LONG-TERM (n = 18, DURATION >10 years) and SHORT-TERM (n = 18, DURATION ≤10 years) groups based on 10-year disease duration. For reliability, supplementary analyses were conducted with alternative cutoffs, creating three groups: 0 < DURATION ≤7 years (n = 11), 7 < DURATION ≤14 years (n = 11), and DURATION >14 years (n = 14). This study examined the intraregional phase-amplitude coupling (PAC) between theta phase and alpha amplitude across the whole brain. The interregional directed phase transfer entropy (dPTE) between frontal and temporal regions in the alpha and theta bands, and the interregional cross-frequency directionality (CFD) between temporal and frontal regions from the theta phase to the alpha amplitude were further computed and compared among groups. Partial correlation analysis was conducted to investigate correlations between intraregional PAC, interregional dPTE connectivity, interregional CFD, and disease duration. Whole-brain intraregional PAC analyses revealed enhanced theta phase-alpha amplitude coupling within the ipsilateral temporal and frontal regions in TLE patients, and the ipsilateral temporal PAC was positively correlated with disease duration (r = 0.38, p <.05). Interregional dPTE analyses demonstrated a gradual increase in frontal-to-temporal connectivity within the alpha band, while the direction of theta-band connectivity reversed from frontal-to-temporal to temporal-to-frontal as the disease duration increased. Interregional CFD analyses revealed that the inhibitory effect of frontal regions on temporal regions gradually increased with prolonged disease duration (r = -0.36, p <.05). This study clarified the intrinsic reciprocal connectivity between temporal and frontal regions with TLE duration. We propose a dynamically reorganized triple-stage network that transitions from balanced networks to constrained networks and further develops into imbalanced networks as the disease duration increases.

Alteration in neural oscillatory activity and phase-amplitude coupling after sleep deprivation: Evidence for impairment and compensation effects.

Insufficient sleep can significantly affect vigilance and increase slow-wave electroencephalographic power as homeostatic sleep pressure accumulates. Phase-amplitude coupling is involved in regulating the spatiotemporal integration of physiological processes. This study aimed to examine the functional associations of resting-state electroencephalographic power and delta/theta-gamma phase-amplitude coupling from the prefrontal cortex (PFC) to posterior regions with vigilance performance after sleep deprivation. Forty-six healthy adults underwent 24-hr sleep deprivation with resting-state electroencephalographic recordings, and vigilant attention was measured using the Psychomotor Vigilance Task. Power spectral and phase-amplitude coupling analyses were conducted, and correlation analysis was utilized to reveal the relationship between electroencephalographic patterns and changes in vigilance resulting from sleep deprivation. Sleep deprivation significantly declined vigilance performance, accompanied by increased resting-state electroencephalographic power in all bands and delta/theta-gamma phase-amplitude coupling. The increased theta activity in centro-parieto-occipital areas significantly correlated with decreased mean and slowest response speed. Conversely, the increased delta-low gamma and theta-high gamma phase-amplitude couplings negatively correlated with the deceleration of the fastest Psychomotor Vigilance Task reaction times. These findings suggest that sleep deprivation affects vigilance by altering electroencephalographic spectral power and information communication across frequency bands in different brain regions. The distinct effects of increased theta power and delta/theta-gamma phase-amplitude coupling might reflect the impairment and compensation of sleep deprivation on vigilance performance, respectively.

Neural oscillations suggest periodicity encoding during auditory beat processing in the premature brain.

When exposed to rhythmic patterns with temporal regularity, adults exhibit an inherent ability to extract and anticipate an underlying sequence of regularly spaced beats, which is internally constructed, as beats are experienced even when no events occur at beat positions (e.g., in the case of rests). Perception of rhythm and synchronization to periodicity is indispensable for development of cognitive functions, social interaction, and adaptive behavior. We evaluated neural oscillatory activity in premature newborns (n = 19, mean age, 32 ± 2.59 weeks gestational age) during exposure to an auditory rhythmic sequence, aiming to identify early traces of periodicity encoding and rhythm processing through entrainment of neural oscillations at this stage of neurodevelopment. The rhythmic sequence elicited a systematic modulation of alpha power, synchronized to expected beat locations coinciding with both tones and rests, and independent of whether the beat was preceded by tone or rest. In addition, the periodic alpha-band fluctuations reached maximal power slightly before the corresponding beat onset times. Together, our results show neural encoding of periodicity in the premature brain involving neural oscillations in the alpha range that are much faster than the beat tempo, through alignment of alpha power to the beat tempo, consistent with observations in adults on predictive processing of temporal regularities in auditory rhythms. RESEARCH HIGHLIGHTS: In response to the presented rhythmic pattern, systematic modulations of alpha power showed that the premature brain extracted the temporal regularity of the underlying beat. In contrast to evoked potentials, which are greatly reduced when there is no sounds event, the modulation of alpha power occurred for beats coinciding with both tones and rests in a predictive way. The findings provide the first evidence for the neural coding of periodicity in auditory rhythm perception before the age of term.

Elevated phase amplitude coupling as a depression biomarker in epilepsy.

Depression is prevalent in epilepsy patients and their intracranial brain activity recordings can be used to determine the types of brain activity that are associated with comorbid depression. We performed case-control comparison of spectral power and phase amplitude coupling (PAC) in 34 invasively monitored drug resistant epilepsy patients' brain recordings. The values of spectral power and PAC for one-minute segments out of every hour in a patient's study were correlated with pre-operative assessment of depressive symptoms by Beck Depression Inventory-II (BDI). We identified an elevated PAC signal (theta-alpha-beta phase (5-25 Hz)/gamma frequency (80-100 Hz) band) that is present in high BDI scores but not low BDI scores adult epilepsy patients in brain regions implicated in primary depression, including anterior cingulate cortex, amygdala and orbitofrontal cortex. Our results showed the application of PAC as a network-specific, electrophysiologic biomarker candidate for comorbid depression and its potential as treatment target for neuromodulation.

Neural processes responsible for the translation of sustained nociceptive inputs into subjective pain experience.

Tracking and predicting the temporal structure of nociceptive inputs is crucial to promote survival, as proper and immediate reactions are necessary to avoid actual or potential bodily injury. Neural activities elicited by nociceptive stimuli with different temporal structures have been described, but the neural processes responsible for translating nociception into pain perception are not fully elucidated. To tap into this issue, we recorded electroencephalographic signals from 48 healthy participants receiving thermo-nociceptive stimuli with 3 different durations and 2 different intensities. We observed that pain perception and several brain responses are modulated by stimulus duration and intensity. Crucially, we identified 2 sustained brain responses that were related to the emergence of painful percepts: a low-frequency component (LFC, < 1 Hz) originated from the insula and anterior cingulate cortex, and an alpha-band event-related desynchronization (α-ERD, 8-13 Hz) generated from the sensorimotor cortex. These 2 sustained brain responses were highly coupled, with the α-oscillation amplitude that fluctuated with the LFC phase. Furthermore, the translation of stimulus duration into pain perception was serially mediated by α-ERD and LFC. The present study reveals how brain responses elicited by nociceptive stimulation reflect the complex processes occurring during the translation of nociceptive information into pain perception.

The frontooccipital interaction mechanism of high-frequency acoustoelectric signal.

Based on acoustoelectric effect, acoustoelectric brain imaging has been proposed, which is a high spatiotemporal resolution neural imaging method. At the focal spot, brain electrical activity is encoded by focused ultrasound, and corresponding high-frequency acoustoelectric signal is generated. Previous studies have revealed that acoustoelectric signal can also be detected in other non-focal brain regions. However, the processing mechanism of acoustoelectric signal between different brain regions remains sparse. Here, with acoustoelectric signal generated in the left primary visual cortex, we investigated the spatial distribution characteristics and temporal propagation characteristics of acoustoelectric signal in the transmission. We observed a strongest transmission strength within the frontal lobe, and the global temporal statistics indicated that the frontal lobe features in acoustoelectric signal transmission. Then, cross-frequency phase-amplitude coupling was used to investigate the coordinated activity in the AE signal band range between frontal and occipital lobes. The results showed that intra-structural cross-frequency coupling and cross-structural coupling co-occurred between these two lobes, and, accordingly, high-frequency brain activity in the frontal lobe was effectively coordinated by distant occipital lobe. This study revealed the frontooccipital long-range interaction mechanism of acoustoelectric signal, which is the foundation of improving the performance of acoustoelectric brain imaging.

Multivariate sharp-wave ripples in schizophrenia during awake state.

AIMS: Schizophrenia (SZ) is a brain disorder characterized by psychotic symptoms and cognitive dysfunction. Recently, irregularities in sharp-wave ripples (SPW-Rs) have been reported in SZ. As SPW-Rs play a critical role in memory, their irregularities can cause psychotic symptoms and cognitive dysfunction in patients with SZ. In this study, we investigated the SPW-Rs in human SZ. METHODS: We measured whole-brain activity using magnetoencephalography (MEG) in patients with SZ (n = 20) and sex- and age-matched healthy participants (n = 20) during open-eye rest. We identified SPW-Rs and analyzed their occurrence and time-frequency traits. Furthermore, we developed a novel multivariate analysis method, termed "ripple-gedMEG" to extract the global features of SPW-Rs. We also examined the association between SPW-Rs and brain state transitions. The outcomes of these analyses were modeled to predict the positive and negative syndrome scale (PANSS) scores of SZ. RESULTS: We found that SPW-Rs in the SZ (1) occurred more frequently, (2) the delay of the coupling phase (3) appeared in different brain areas, (4) consisted of a less organized spatiotemporal pattern, and (5) were less involved in brain state transitions. Finally, some of the neural features associated with the SPW-Rs were found to be PANSS-positive, a pathological indicator of SZ. These results suggest that widespread but disorganized SPW-Rs underlies the symptoms of SZ. CONCLUSION: We identified irregularities in SPW-Rs in SZ and confirmed that their alternations were strongly associated with SZ neuropathology. These results suggest a new direction for human SZ research.

Effect of Phase Clustering Bias on Phase-Amplitude Coupling for Emotional EEG.

BACKGROUND: Emotions are thought to be related to distinct patterns of neural oscillations, but the interactions among multi-frequency neural oscillations during different emotional states lack full exploration. Phase-amplitude coupling is a promising tool for understanding the complexity of the neurophysiological system, thereby playing a crucial role in revealing the physiological mechanisms underlying emotional electroencephalogram (EEG). However, the non-sinusoidal characteristics of EEG lead to the non-uniform distribution of phase angles, which could potentially affect the analysis of phase-amplitude coupling. Removing phase clustering bias (PCB) can uniform the distribution of phase angles, but the effect of this approach is unknown on emotional EEG phase-amplitude coupling. This study aims to explore the effect of PCB on cross-frequency phase-amplitude coupling for emotional EEG. METHODS: The technique of removing PCB was implemented on a publicly accessible emotional EEG dataset to calculate debiased phase-amplitude coupling. Statistical analysis and classification were conducted to compare the difference in emotional EEG phase-amplitude coupling prior to and post the removal of PCB. RESULTS: Emotional EEG phase-amplitude coupling values are overestimated due to PCB. Removing PCB enhances the difference in coupling strength between fear and happy emotions in the frontal lobe. Comparable emotion recognition performance was achieved with fewer features after removing PCB. CONCLUSIONS: These findings suggest that removing PCB enhances the difference in emotional EEG phase-amplitude coupling patterns and generates features that contain more emotional information. Removing PCB may be advantageous for analyzing emotional EEG phase-amplitude coupling and recognizing human emotions.

Correlation Analysis of Multi-Scale Ictal EEG Signals in Juvenile Myoclonic Epilepsy.

BACKGROUND: To explore the time-frequency structure and cross-scale coupling of electroencephalography (EEG) signals during seizure in juvenile myoclonic epilepsy (JME), correlations between different leads, as well as dynamic evolution in epileptic discharge, progression and end of seizure were examined. METHODS: EEG data were obtained for 10 subjects with JME and 10 normal controls and were decomposed using gauss continuous wavelet transform (CWT). The phase amplitude coupling (PAC) relationship between the 11th (4.57 Hz) and 17th (0.4 Hz) scale was investigated. Correlations were examined between the 11th and 17th scale EEG signals in different leads during seizure, using multi-scale cross correlation analysis. RESULTS: The time-frequency structure of JME subjects showed strong rhythmic activity in the 11th and 17th scales and a close PAC was identified. Correlation analysis revealed that the ictal JME correlation first increased in the anterior head early in seizure and gradually expanded to the posterior head. CONCLUSION: PAC was exhibited between the 11th and 17th scales during JME seizure. The results revealed that the correlation in the anterior leads was higher than the posterior leads. In the perictal period, the 17th scale EEG signal preceded the 11th scale signal and remained for some time after a seizure. This suggests that the 17th scale signal may play an important role in JME seizure.

Cross-Frequency Brain Network Dynamics Support Pitch Change Detection.

Processing auditory sequences involves multiple brain networks and is crucial to complex perception associated with music appreciation and speech comprehension. We used time-resolved cortical imaging in a pitch change detection task to detail the underlying nature of human brain network activity, at the rapid time scales of neurophysiology. In response to tone sequence presentation to the participants, we observed slow inter-regional signaling at the pace of tone presentations (2-4 Hz) that was directed from auditory cortex toward both inferior frontal and motor cortices. Symmetrically, motor cortex manifested directed influence onto auditory and inferior frontal cortices via bursts of faster (15-35 Hz) activity. These bursts occurred precisely at the expected latencies of each tone in a sequence. This expression of interdependency between slow/fast neurophysiological activity yielded a form of local cross-frequency phase-amplitude coupling in auditory cortex, which strength varied dynamically and peaked when pitch changes were anticipated. We clarified the mechanistic relevance of these observations in relation to behavior by including a group of individuals afflicted by congenital amusia, as a model of altered function in processing sound sequences. In amusia, we found a depression of inter-regional slow signaling toward motor and inferior frontal cortices, and a chronic overexpression of slow/fast phase-amplitude coupling in auditory cortex. These observations are compatible with a misalignment between the respective neurophysiological mechanisms of stimulus encoding and internal predictive signaling, which was absent in controls. In summary, our study provides a functional and mechanistic account of neurophysiological activity for predictive, sequential timing of auditory inputs.SIGNIFICANCE STATEMENT Auditory sequences are processed by extensive brain networks, involving multiple systems. In particular, fronto-temporal brain connections participate in the encoding of sequential auditory events, but so far, their study was limited to static depictions. This study details the nature of oscillatory brain activity involved in these inter-regional interactions in human participants. It demonstrates how directed, polyrhythmic oscillatory interactions between auditory and motor cortical regions provide a functional account for predictive timing of incoming items in an auditory sequence. In addition, we show the functional relevance of these observations in relation to behavior, with data from both normal hearing participants and a rare cohort of individuals afflicted by congenital amusia, which we considered here as a model of altered function in processing sound sequences.

Prioritizing flexible working memory representations through retrospective attentional strengthening.

Previous work has proposed two potential benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation is vital to high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude coupling was increased by valid retrospective attention and predicted the reduced random guessing rates. This long-range connection supported top-down information flow in the engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision by enhancing flexible target representation and emphasize the critical role of the frontoparietal attentional network in the control of WM representations.

Phasic modulation of beta power at movement-related frequencies during visuomotor conflict.

Rhythmic cortical activity is thought to underlie many cognitive functions including the flexible weighting of sensory information depending on the current behavioral context. Here, we tested for potential oscillatory alignment and power modulation at behaviorally relevant frequencies in magnetoencephalography (MEG) data acquired during a virtual reality-based, rhythmic hand-target phase matching task. The task contained conditions differing in terms of visuomotor incongruence and whether or not behavior (grasping movements) had to be adapted to keep vision aligned with the target. We tested for potential oscillatory alignment with movement frequencies and cross-frequency coupling with oscillations in the alpha, beta, and gamma bands. Our results revealed local peaks at 1 Hz power, corresponding to the frequency at which hand movements alternated between open and close; thus, potentially indicating an "entrainment" of neural oscillations at key movement frequencies. We found 1 Hz power was selectively enhanced when participants needed to align incongruent vision with the target. Moreover, the phase of the "movement-entrained" 1 Hz oscillations coupled significantly with the momentary amplitude of beta band oscillations-again, this coupling was selectively enhanced when incongruent vision was task relevant. We propose that this reflected a top-down mechanism, most likely related to selective attention and rhythmic sensory sampling. Thus, phasic low-frequency (beta) power suppression likely indicated a variable (attentional) sampling of visual movement feedback; i.e., related to increased sensitivity for visually matching alternating hand movements to a phasic target at ecologically important time points, rather than continually during the grasping cycle.NEW & NOTEWORTHY Our results reveal an increased spectral power at movement frequencies in a rhythmic hand-target phase matching task under visuomotor conflict; this effect was strongest when incongruent visual movement feedback was required to guide action. Moreover, the phase of these slow frequencies coupled with the momentary power beta oscillations; again, this coupling was selectively strengthened when incongruent vision was task relevant.

Cortical oscillations and interareal synchronization as a preparatory activity for postural response.

Neural mechanisms of human standing are expected to be elucidated for preventing fallings. Postural response evoked by sudden external perturbation originates from various areas in the central nervous system. Recent studies have revealed that the corticospinal pathway is one of the key nodes for an appropriate postural response. The corticospinal pathway that mediates the early part of the electromyographic response is modulated with prediction before a perturbation occurs. Temporal prediction explicitly exhibiting an onset timing contributes to enhancing corticospinal excitability. However, how the cortical activities in the sensorimotor area with temporal prediction are processed before the corticospinal pathway enhancement remains unclear. In this study, using electroencephalography, we investigated how temporal prediction affects both neural oscillations and synchronization between sensorimotor and distal areas. Our results revealed that desynchronization of cortical oscillation at α- and ß-bands was observed in the sensorimotor and parietooccipital areas (Cz, CPz, Pz and POz), and those are nested in the phase at θ-band frequency. Furthermore, a reduction in the interareal phase synchrony in the α-band was induced after the timing cue for the perturbation onset. The phase synchrony at the low frequency can relay the temporal prediction among the distant areas and initiate the modulation of the local cortical activities. Such modulations contribute to the preparation for sensory processing and motor execution that are necessary for optimal responses.

Direct modulation index: A measure of phase amplitude coupling for neurophysiology data.

Neural communication across different spatial and temporal scales is a topic of great interest in clinical and basic science. Phase-amplitude coupling (PAC) has attracted particular interest due to its functional role in a wide range of cognitive and motor functions. Here, we introduce a novel measure termed the direct modulation index (dMI). Based on the classical modulation index, dMI provides an estimate of PAC that is (1) bound to an absolute interval between 0 and +1, (2) resistant against noise, and (3) reliable even for small amounts of data. To highlight the properties of this newly-proposed measure, we evaluated dMI by comparing it to the classical modulation index, mean vector length, and phase-locking value using simulated data. We ascertained that dMI provides a more accurate estimate of PAC than the existing methods and that is resilient to varying noise levels and signal lengths. As such, dMI permits a reliable investigation of PAC, which may reveal insights crucial to our understanding of functional brain architecture in key contexts such as behaviour and cognition. A Python toolbox that implements dMI and other measures of PAC is freely available at https://github.com/neurophysiological-analysis/FiNN.

Effects on resting-state EEG phase-amplitude coupling in insomnia disorder patients following 1 Hz left dorsolateral prefrontal cortex rTMS.

Despite burgeoning evidence for cortical hyperarousal in insomnia disorder, the existing results on electroencephalography spectral features are highly heterogeneous. Phase-amplitude coupling, which refers to the modulation of the low-frequency phase to a high-frequency amplitude, is probably a more sensitive quantitative measure for characterizing abnormal neural oscillations and explaining the therapeutic effect of repetitive transcranial magnetic stimulation in the treatment of patients with insomnia disorder. Sixty insomnia disorder patients were randomly divided into the active and sham treatment groups to receive 4 weeks of repetitive transcranial magnetic stimulation treatment. Behavioral assessments, resting-state electroencephalography recordings, and sleep polysomnography recordings were performed before and after repetitive transcranial magnetic stimulation treatment. Forty good sleeper controls underwent the same assessment. We demonstrated that phase-amplitude coupling values in the frontal and temporal lobes were weaker in Insomnia disorder patients than in those with good sleeper controls at baseline and that phase-amplitude coupling values near the intervention area were significantly enhanced after active repetitive transcranial magnetic stimulation treatment. Furthermore, the enhancement of phase-amplitude coupling values was significantly correlated with the improvement of sleep quality. This study revealed the potential of phase-amplitude coupling in assessing the severity of insomnia disorder and the efficacy of repetitive transcranial magnetic stimulation treatment, providing new insights on the abnormal physiological mechanisms and future treatments for insomnia disorder.

Individual differences in information processing during sleep and wake predict sleep-based memory consolidation of complex rules.

Memory is critical for many cognitive functions, from remembering facts, to learning complex environmental rules. While memory encoding occurs during wake, memory consolidation is associated with sleep-related neural activity. Further, research suggests that individual differences in alpha frequency during wake (∼7 - 13 Hz) modulate memory processes, with higher individual alpha frequency (IAF) associated with greater memory performance. However, the relationship between wake-related EEG individual differences, such as IAF, and sleep-related neural correlates of memory consolidation has been largely unexplored, particularly in a complex rule-based memory context. Here, we aimed to investigate whether wake-derived IAF and sleep neurophysiology interact to influence rule learning in a sample of 35 healthy adults (16 males; mean age = 25.4, range: 18 - 40). Participants learned rules of a modified miniature language prior to either 8hrs of sleep or wake, after which they were tested on their knowledge of the rules in a grammaticality judgement task. Results indicate that sleep neurophysiology and wake-derived IAF do not interact but modulate memory for complex linguistic rules separately. Phase-amplitude coupling between slow oscillations and spindles during non-rapid eye-movement (NREM) sleep also promoted memory for rules that were analogous to the canonical English word order. As an exploratory analysis, we found that rapid eye-movement (REM) sleep theta power at posterior regions interacts with IAF to predict rule learning and proportion of time in REM sleep predicts rule learning differentially depending on grammatical rule type. Taken together, the current study provides behavioural and electrophysiological evidence for a complex role of NREM and REM sleep neurophysiology and wake-derived IAF in the consolidation of rule-based information.