High gamma power is phase-locked to theta oscillations in human neocortex

Identification of the epileptogenic zone using phase-amplitude coupling on ictal stereoelectroencephalography

OBJECTIVE

Phase-Amplitude Coupling (PAC) has been proposed to characterize electrophysiological changes at seizure onset. However, PAC can arise from actual relations between oscillations at different frequencies (authentic PAC) or from harmonic/transient effects (spurious PAC). To assess the importance of these PAC mechanisms, we investigated the Modulation Index (MI) and Time Locked Index (TLI) between Epileptogenic Zone (EZ) and non-EZ channels during seizures.

METHODS

We analyzed 34 patients with drug-resistant epilepsy who underwent stereoelectroencephalography (SEEG) implantation. SEEG data was classified into three periods: "preictal," "fast," and "rhythmic." The amplitude of ripple bands and the phase of three slow-wave bands were used for MI and TLI. The capacity of MI to detect the EZ was tested with precision and recall measures, summarized by the F1 score.

RESULTS

The MI was significantly greater in EZ channels than that in non-EZ channels for all periods. The best F1 results were obtained for the "fast" period and spurious PAC. Both authentic and spurious PAC were present during all periods and bands.

CONCLUSIONS

Different PAC values could be observed during different seizure periods. Care should be taken when interpreting MI as a measure of authentic PAC.

SIGNIFICANCE

MI and TLI can help the interpretation of ictal cross-frequency observations.

Neuronal oscillations in cognition: Down syndrome as a model of mouse to human translation

Down syndrome (DS), a prevalent cognitive disorder resulting from trisomy of human chromosome 21 (Hsa21), poses a significant global health concern. Affecting approximately 1 in 800 live births worldwide, DS is the leading genetic cause of intellectual disability and a major predisposing factor for early-onset Alzheimer's dementia. The estimated global population of individuals with DS is 6 million, with increasing prevalence due to advances in DS health care. Global efforts are dedicated to unraveling the mechanisms behind the varied clinical outcomes in DS. Recent studies on DS mouse models reveal disrupted neuronal circuits, providing insights into DS pathologies. Yet, translating these findings to humans faces challenges due to limited systematic electrophysiological analyses directly comparing human and mouse. Additionally, disparities in experimental procedures between the two species pose hurdles to successful translation. This review provides a concise overview of neuronal oscillations in human and rodent cognition. Focusing on recent DS mouse model studies, we highlight disruptions in associated brain function. We discuss various electrophysiological paradigms and suggest avenues for exploring molecular dysfunctions contributing to DS-related cognitive impairments. Deciphering neuronal oscillation intricacies holds promise for targeted therapies to alleviate cognitive disabilities in DS individuals.

Temporal Summation of Pain Varies Across Body Regions: A Cutaneous Laser Stimulation Study in Healthy Controls

Temporal summation of pain (TSP) is a psychophysical measure for assessing central facilitation of pain. This study examined sex differences and the effects of body region on TSP using contactless laser stimulation. Thirty-one right-handed healthy participants (16 female; mean age ± SD = 23.9 ± 7.4 years) were tested at the hand, leg, and low back. Painful laser stimulation reliably evoked behavioral TSP responses in a significant proportion of participants (p < 0.01, Cohen's h = 1.67; mean induction rate: 63.5% ± 18.2%; mean magnitude: 36.6% ± 34.5%). TSP magnitude varied significantly across body regions (p = 0.02, ηₚ² = 0.13 with the lowest responses at the low back (26.2% ± 17.4%) and highest at the leg (47.1% ± 50.0%). No sex differences were observed. Concurrent EEG recordings also showed TSP related gamma responses (i.e. gamma TSP) in a significant proportion of participants (p < 0.01, Cohen's h = 1.67; mean induction rate: 68.1% ± 12.9%; mean magnitude: 41.6% ± 23.3%). Gamma TSP magnitude also differed by region (p = 0.04, ηₚ² = 0.11), with the highest response at the low back (48.2% ± 31.4%), significantly greater than the leg (35.4% ± 13.3%; p = 0.04, r = 0.44). These findings highlight regional variability in central pain facilitation and provide initial insights into the cortical oscillatory mechanisms underlying TSP. Perspective This study identifies body region differences in temporal summation of pain (TSP) and associated gamma-band EEG responses elicited by contactless painful laser stimulation. Clarifying these regional variations in healthy individuals provides foundational insights into central pain processing and may help guide future research on pain mechanisms across different body regions.

Phase-amplitude coupling within MEG data can identify eloquent cortex

Objective.Proper identification of eloquent cortices is essential to minimize post-surgical deficits in patients undergoing resection for epilepsy and tumors. Current methods are subjective, vary across centers, and require significant expertise, underscoring the need for more objective pre-surgical mapping. Phase-amplitude coupling (PAC), the interaction between the phase of low-frequency oscillations and the amplitude of high-frequency activity, has been implicated in task-induced brain activity and may serve as a biomarker for functional mapping. Our objective was to develop a novel PAC-based algorithm to non-invasively identify somatosensory eloquent cortex using magnetoencephalography (MEG) data in epilepsy patients.Approach.We analyzed somatosensory and spontaneous MEG recordings from 30 subjects with drug-resistant epilepsy. PAC was calculated on source-reconstructed data (5-12 Hz for low frequencies and 30-300 Hz for high frequencies), followed by rank-2 tensor decomposition. Density-based clustering compared active brain regions during somatosensory task and spontaneous data at a population level. We employed a linear mixed-effects model to quantify changes in PAC between somatosensory and resting-state data. We developed a patient-specific support vector machine (SVM) classifier to identify active brain regions based on PAC values during the somatosensory task.Main results.Five of six expected brain regions were active during left and right-sided stimulation (p=1.08×10-8, hypergeometric probability test). The mixed-effects model confirmed task-specific PAC in anatomically relevant brain regions (p < 0.01). The SVM classifier gave a specificity of 99.46% and a precision of 66.9%. These results demonstrate that the PAC algorithm reliably identifies somatosensory cortex activation at both individual and population levels with statistical significance.Significance.This study demonstrates the feasibility of using PAC as a non-invasive marker for identifying functionally relevant brain regions during somatosensory task in epilepsy patients. Future work will evaluate its applicability for mapping other eloquent cortices, including language, motor, and auditory areas.

Partial normalization of hippocampal oscillatory activity during sleep in TgF344-AD rats coincides with increased cholinergic synapses at early-plaque stage of Alzheimer's disease

Sleep alterations are known to occur in Alzheimer's disease (AD), before cognitive symptoms become apparent, and are thought to play an important role in the pathophysiology of AD. However, knowledge on the extent of macro- and microstructural changes of sleep during early, presymptomatic stages of AD is limited. We hypothesize that Aβ-induced perturbations of neuronal activity disrupt this oscillatory activity during sleep at pre-plaque stages of AD. In this study, we aimed to assess hippocampal oscillatory activity during sleep at pre- and early-plaque stages of AD, by performing 24-hour hippocampal electrophysiological measurements in TgF344-AD rats and wildtype littermates at pre- and early-plaque stages of AD. To provide a mechanistic understanding, histological analysis was performed to quantify GABA-ergic, glutamatergic and cholinergic synapses. We observed a differential impact of AD on hippocampal activity during rapid eye movement (REM) and non-REM (NREM) sleep, in the absence of robust changes in circadian rhythm. TgF344-AD rats demonstrated increased duration of sharp wave-ripples during NREM sleep, irrespective of age. Interestingly, a significantly decreased theta-gamma coupling was observed in TgF344-AD rats, prior to amyloid plaque deposition, which was partially restored at the early-plaque stage. The partial recovery of hippocampal activity during REM sleep coincided with an increased number of cholinergic synapses in the hippocampus during the early-plaque stage in TgF344-AD rats, suggestive of basal forebrain cholinergic compensation mechanisms. The results from this study reveal early changes in hippocampal activity prior to Aβ plaque deposition in AD. In addition, the current findings imply an important role of the cholinergic system to compensate for AD-related network alterations, thereby partially restoring sleep architecture and hippocampal activity.

Anatomically distinct cortical tracking of music and speech by slow (1-8Hz) and fast (70-120Hz) oscillatory activity

Music and speech encode hierarchically organized structural complexity at the service of human expressiveness and communication. Previous research has shown that populations of neurons in auditory regions track the envelope of acoustic signals within the range of slow and fast oscillatory activity. However, the extent to which cortical tracking is influenced by the interplay between stimulus type, frequency band, and brain anatomy remains an open question. In this study, we reanalyzed intracranial recordings from thirty subjects implanted with electrocorticography (ECoG) grids in the left cerebral hemisphere, drawn from an existing open-access ECoG database. Participants passively watched a movie where visual scenes were accompanied by either music or speech stimuli. Cross-correlation between brain activity and the envelope of music and speech signals, along with density-based clustering analyses and linear mixed-effects modeling, revealed both anatomically overlapping and functionally distinct mapping of the tracking effect as a function of stimulus type and frequency band. We observed widespread left-hemisphere tracking of music and speech signals in the Slow Frequency Band (SFB, band-passed filtered low-frequency signal between 1-8Hz), with near zero temporal lags. In contrast, cortical tracking in the High Frequency Band (HFB, envelope of the 70-120Hz band-passed filtered signal) was higher during speech perception, was more densely concentrated in classical language processing areas, and showed a frontal-to-temporal gradient in lag values that was not observed during perception of musical stimuli. Our results highlight a complex interaction between cortical region and frequency band that shapes temporal dynamics during processing of naturalistic music and speech signals.

The effects of gamma-tACS on cognitive impairment in multiple sclerosis: A randomized, double-blind, sham-controlled, pilot study

BACKGROUND

Multiple sclerosis (MS) often causes impairment in working memory (WM), information processing speed (IPS), and verbal memory (VM). These deficits are linked to disrupted neural oscillatory activity. Transcranial alternating current stimulation (tACS), which modulates cortical oscillations, may hold promise for treating cognitive impairment in MS.

OBJECTIVES

To evaluate online and offline effects of gamma (γ)-tACS on WM, IPS, and VM while assessing changes in brain rhythms using electroencephalography (EEG).

METHODS

Thirty-six MS patients with single-domain impairment in WM (12), IPS (13), or VM (11) underwent γ-tACS and sham-tACS over the left dorsolateral prefrontal cortex (DLPFC) (WM, IPS) or precuneus (VM). Cognitive performance was assessed pre-tACS (T0), during (T1), and post-tACS (T2) using the Digit Span Backward (DSBW) for WM, Symbol Digit Modalities Test (SDMT) for IPS, and Rey Auditory Verbal Learning Test (RAVLT) for VM. EEG was recorded at T0 and T2 to analyze local power spectral density and local-to-global connectivity.

RESULTS

DSBW, SDMT, and RAVLT scores transiently improved during γ-tACS and not during sham. IPS-impaired patients showed a reduction in spectral power across all frequency bands, at the stimulation site, post-DLPFC γ-tACS.

CONCLUSION

γ-tACS briefly improves WM, IPS, and VM in MS patients, warranting further trials of this non-invasive intervention.

Theta-gamma transcranial alternating current stimulation enhances ballistic motor performance in healthy young and older adults

Theta-gamma transcranial alternating current stimulation (TG tACS) over primary motor cortex (M1) can improve ballistic motor performance in young adults, but the effect on older adults is unknown. This study investigated the effects of TG tACS on motor performance and M1 excitability in 18 young and 18 older adults. High-definition TG tACS (6 Hz theta, 75 Hz gamma) or sham tACS was applied over right M1 for 20 min during a ballistic left-thumb abduction motor training task performed in two experimental sessions. Motor performance was quantified as changes in movement acceleration during and up to 60 min after training. Transcranial magnetic stimulation (TMS) was used to assess changes in M1 excitability with motor-evoked potentials (MEP) and short-interval intracortical inhibition (SICI) before and after training. We found that TG tACS increased motor performance compared with sham tACS in young and older adults (P < 0.001), with greater effects for young adults (P = 0.01). The improved motor performance with TG tACS lasted at least 60 min after training in both age groups. Motor training was accompanied by greater MEP amplitudes with TG tACS compared to sham tACS in young and older adults (P < 0.001), but SICI did not vary between tACS sessions (P = 0.40). These findings indicate that TG tACS over M1 improves motor performance and alters training-induced changes in M1 excitability in healthy young and older adults. TG tACS may therefore be beneficial to alleviate motor deficits in the ageing population.

Shared spectral fingerprints of temporal memory precision and representation of the temporal structure of complex narratives

The ability to date events is fundamental to episodic memory. Separate lines of fMRI research have explored the neurobiological mechanisms underlying temporal precision and the representation of temporal structure in complex events. The present EEG study examined the oscillatory dynamics of both processes in participants performing a timeline positioning task with movie scenes. Multivariate analyses identified a high-beta/low-gamma electrophysiological signature of temporal precision during timeline presentation, involving a right-lateralized network. An independent representation similarity analysis revealed a strong coupling between behavioral and neural distance between pairs of movie parts in the same time-frequency band as the precision effect. Crucially, participants with higher temporal precision showed a stronger correlation between behavioral and neural distance, reinforcing the link between brain signals related to precision and temporal structure representation. These findings support the idea of a systematic temporal organization of experiences, which plays a role in guiding inferential processes.

Hippocampal and cortical high-frequency oscillations orchestrate human semantic networks during word list memory

Episodic memory requires the precise coordination between the hippocampus and distributed cortical regions. This may be facilitated by bursts of brain activity called high-frequency oscillations (HFOs). We hypothesized that HFOs activate specific networks during memory retrieval and aimed to describe the electrophysiological properties of HFO-associated activity. To study this, we recorded intracranial electroencephalography while human participants performed a list learning task. Hippocampal HFOs (hHFOs) increased during encoding and retrieval, and these increases correlated with memory performance. During retrieval, hHFOs demonstrated activation of semantic processing regions that were previously active during encoding. This consisted of broadband high-frequency activity (HFA) and cortical HFOs. HFOs in the anterior temporal lobe, a major semantic hub, co-occurred with hHFOs, particularly during retrieval. These coincident HFOs were associated with greater cortical HFA and cortical theta bursts. Hence, HFOs may support synchronization of activity across distributed nodes of the hippocampal-cortical memory network.

Event-related dynamic phase-amplitude coupling analysis reveals facial emotional processing deficits in patients with major depressive disorder: a cross-sectional study

BACKGROUND

Phase-amplitude coupling (PAC) measures the interaction between neural oscillations in different frequency bands and reflects brain functional network coordination in psychiatric patients. The event-related dynamic changes in PAC characteristics and their association with the neural physiological mechanisms under emotional stimulation in major depressive disorder (MDD) remain poorly understood.

METHODS

We proposed a cross-sectional study that investigated three PAC methods using simulated data and selected the Gaussian-Copula Event-Related PAC (GC-ERPAC) method for dynamic analysis of 128-channel electroencephalogram data from 53 participants, including 24 patients with MDD and 29 healthy controls (HCs). Participants were exposed to three emotional stimuli (fearful, happy, and sad). The correlation between PAC strengths and clinical scales was then analyzed in each condition.

RESULTS

The MDD group exhibited abnormal PAC patterns. With happy stimuli, the strengths of delta-gamma coupling (DGC), theta-gamma coupling (TGC), and alpha-gamma coupling (AGC) in the frontal-parietal regions of the MDD group were lower compared to HCs. With fearful stimuli, the strength of AGC in the occipital region was higher in the MDD group. The correlation between TGC and AGC was weaker for couplings among different frequencies in the MDD group. Additionally, AGC was negatively correlated with the clinical scale in MDD but positively correlated with HCs.

CLINICAL TRIAL NUMBER

Not applicable.

CONCLUSIONS

This study confirmed that GC-ERPAC was an effective method for revealing emotion recognition features in MDD. We provided novel evidence of abnormal spatiotemporal PAC patterns linked to emotional processing deficits. Reduced DGC and TGC, along with increased AGC, suggest potential biomarkers in MDD.

Dynamic prefrontal coupling coordinates adaptive decision-making

Adaptive decision-making requires flexibly maintaining or changing behavior in response to uncertainty. While the dorsomedial (dmPFC) and dorsolateral (dIPFC) prefrontal cortex are each essential for this ability, how they coordinate to drive adaptation remains unknown. Using intracranial EEG recordings from human participants performing a dynamic reward task, we identified distinct, frequency-specific computations: dmPFC high-gamma activity encoded uncertainty before stay decisions but transitioned to prediction error before switches, while theta activity shifted from uncertainty to value representation. In contrast, dIPFC theta activity signaled both value and uncertainty before stays, but predominantly value before switches. Crucially, these regions coordinated through two temporally specific coupling mechanisms that predicted behavioral changes: theta-theta amplitude coupling during feedback processing and theta-gamma phase coupling before decisions. Both coupling mechanisms strengthened before switches, suggesting that changing behavior requires greater dmPFC-dIPFC integration than maintaining. These findings reveal how the dorsal prefrontal cortex employs frequency-specific computations and precise temporal coordination to guide adaptive behavior.

Exploring anterior thalamus functional connectivity with cortical regions in prospective memory with ultra-high-field functional MRI

Prospective memory, or memory for future intentions, engages particular cortical regions. Lesion studies also implicate the thalamus, with prospective memory deterioration following thalamic stroke. Neuroimaging, anatomical and lesion studies suggest the anterior nuclei of the thalamus (ANT), in particular, are involved in episodic memory, with electrophysiological studies suggesting an active role in selecting neural assemblies underlying particular memory traces. Here, we hypothesized that the ANT are engaged in realizing prospectively-encoded intentions, detectable using ultra-high-field strength functional MRI. Using a within-subject design, participants (N = 14; age 20-35 years) performed an ongoing n-back working memory task with two cognitive loads, each with and without a prospective memory component, during 7-Tesla functional MRI. Seed-to-voxel whole brain functional connectivity analyses were performed to establish whether including a prospective memory component in an ongoing task results in greater connectivity between ANT and cortical regions engaged in prospective memory. Repeated measures ANOVAs were applied to behavioral and connectivity measures, with the factors Task Type (with prospective memory or not) and N-Back (2-back or 3-back). Response accuracy was greater and reaction times faster without the prospective memory component, and accuracy was higher in the 2- than 3-back condition. Task Type had a main effect on connectivity with an ANT seed, with greater ANT-DLPFC and ANT-STG connectivity when including a prospective memory component. Post hoc testing based on a significant interaction showed greater ANT-DLPFC connectivity (p-FWE = 0.007) when prospective memory was included with the low cognitive load and ANT-STG connectivity (p-FWE = 0.019) with the high cognitive load ongoing task. Direct comparison showed greater functional connectivity between these areas and the ANT than dorsomedial nucleus of the thalamus (DMNT) during prospective remembering. Enhanced ANT-DLPFC connectivity, a brain region with an established role in strategic monitoring for prospective memory cues, arose with a low cognitive load ongoing task that enabled monitoring. This connectivity was significantly less on direct comparison with increasing the cognitive load of the ongoing task without prospective memory, suggesting specificity for prospective memory. Greater ANT-STG connectivity on prospective memory inclusion in the higher cognitive load ongoing task fits with reported STG activation on prospective memory through spontaneous retrieval. Lower connectivity on direct comparison with a DMNT seed suggests ANT specificity. The findings fit with a coordinating role for the ANT in prospective remembering. Given the small sample, these findings should be considered preliminary, with replication required.

Is transcranial alternating current stimulation effective for improving working memory? A three-level meta-analysis

Working memory, an essential component of cognitive function, can be improved through specific methods. This meta-analysis evaluates the effectiveness of transcranial alternating current stimulation (tACS), an emerging technique for enhancing working memory, and explores its efficacy, influencing factors, and underlying mechanisms. A PRISMA systematic search was conducted. Hedges's g was used to quantify effect sizes. We constructed a three-level meta-analytic model to account for all effect sizes and performed subgroup analyses to assess moderating factors. Recognizing the distinct neural underpinnings of various working memory processes, we separately assessed the effects on n-back tasks and traditional working memory tasks. A total of 39 studies with 405 effect sizes were included (170 from n-back tasks and 235 from other tasks). The overall analysis indicated a net benefit of g = 0.060 of tACS on working memory. Separate analyses showed that tACS had a small positive effect on n-back tasks (g = 0.102), but almost no effect on traditional working memory tasks (g = 0.045). Further analyses revealed mainly: A moderately positive effect of theta tACS (without anti-phase stimulation) on n-back tasks (g = 0.207); and a small effect of offline stimulation on working memory maintenance (g = 0.127). Overall, tACS has minimal impact on working memory improvement, but it shows potential under certain conditions. Specifically, both online and offline theta tACS can improve n-back task performance, while only offline stimulation enhances working memory maintenance. More research is needed to understand the mechanisms behind these effects to make tACS an effective method.

Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer's disease dementia

BACKGROUND

Developing non-invasive and affordable biomarkers to detect Alzheimer's disease (AD) at a prodromal stage is essential, particularly in the context of new disease-modifying therapies. Mild cognitive impairment (MCI) is a critical stage preceding dementia, but not all patients with MCI will progress to AD. This study explores the potential of magnetoencephalography (MEG) to predict cognitive decline from MCI to AD dementia.

METHODS

We analysed resting-state MEG data from the BioFIND dataset including 117 patients with MCI among whom 64 developed AD dementia (AD progression), while 53 remained cognitively stable (stable MCI), using spectral analysis. Logistic regression models estimated the additive explanation of selected clinical, MEG, and MRI variables for AD progression risk. We then built a high-dimensional classification model to combine all modalities and variables of interest.

FINDINGS

MEG 16-38Hz spectral power, particularly over parieto-occipital magnetometers, was significantly reduced in the AD progression group. In logistic regression models, decreased MEG 16-38Hz spectral power and reduced hippocampal volume/total grey matter ratio on MRI were independently linked to higher AD progression risk. The data-driven classification model confirmed, among other factors, the complementary information of MEG covariance (AUC = 0.74, SD = 0.13) and MRI cortical volumes (AUC = 0.77, SD = 0.14) to predict AD progression. Combining all inputs led to markedly improved classification scores (AUC = 0.81, SD = 0.12).

INTERPRETATION

These findings highlight the potential of spectral power and covariance as robust non-invasive electrophysiological biomarkers to predict AD progression, complementing other diagnostic measures, including cognitive scores and MRI.

FUNDING

This work was supported by: Fondation pour la Recherche Médicale (grant FDM202106013579).

Salient objects in a scene trigger enhanced perceptual selection and memory encoding

Rapidly detecting salient objects from surrounding environments is crucial for survival. Our study demonstrates that salient objects in visual search arrays trigger von Restorff-like effects. In a search task, participants detected a tilted target bar among distractors with EEG recordings. The results revealed that salient objects elicited the largest and earliest N2pc component, reflecting early attentional selection, which enhanced multivariate decoding of target location. Importantly, early selection of highly salient targets (25° tilt) triggered a cascade of preferential processing downstream, marked by stronger P3b components, neural synchronization, and phase-amplitude coupling between low- and high-frequency activity, along with better recall performance of target orientation. The strength of memory-related activity on the current trial predicted the vigor of the next selection event, indicating that salience-driven learning influences future attentional control. Overall, object salience in spatial arrays drives a cascade of processing, facilitating rapid learning of object relevance while humans search their environment.

Long-term editing of brain circuits in mice using an engineered electrical synapse

Electrical signaling across distinct populations of brain cells underpins cognitive and emotional function; however, approaches that selectively regulate electrical signaling between two cellular components of a mammalian neural circuit remain sparse. Here, we engineered an electrical synapse composed of two connexin proteins found in Morone americana (white perch fish) - connexin34.7 and connexin35 - to accomplish mammalian circuit modulation. By exploiting protein mutagenesis, devising a new in vitro system for assaying connexin hemichannel docking, and performing computational modeling of hemichannel interactions, we uncovered a structural motif that contributes to electrical synapse formation. Targeting these motifs, we designed connexin34.7 and connexin35 hemichannels that dock with each other to form an electrical synapse, but not with other major connexins expressed in the mammalian central nervous system. We validated this electrical synapse in vivo using C. elegans and mice, demonstrating that it can strengthen communication across neural circuits composed of pairs of distinct cell types and modify behavior accordingly. Thus, we establish 'Long-term integration of Circuits using connexins' (LinCx) for precision circuit-editing in mammals.

Intravenous psilocybin induces dose-dependent changes in functional network organization in rat cortex

Psilocybin produces an altered state of consciousness in humans and is associated with complex spatiotemporal changes in cortical networks. Given the emphasis on rodent models for mechanistic studies, there is a need for characterization of the effect of psilocybin on cortex-wide network dynamics. Previous electroencephalographic studies of psychedelics in rodents have primarily used sparse electrode arrays with limited spatial resolution, precluding network level analysis, and have been restricted to lower gamma frequencies. Therefore, in this study, we used electroencephalographic recordings from 27 sites/electrodes across rat cortex (n = 6 male, 6 female) to characterize the effect of psilocybin (0.1, 1, and 10 mg/kg delivered over an hour) on brain network organization as inferred through changes in node degree (an index of network density) and connection strength (via weighted phase-lag index). The removal of aperiodic component from the electroencephalogram localized the primary oscillatory changes to theta (4-10 Hz), medium gamma (70-110 Hz), and high gamma (110-150 Hz) bands, which were used for the network analysis. Additionally, we determined the concurrent changes in theta-gamma phase-amplitude coupling. We report that psilocybin, in a dose-dependent manner, 1) disrupted theta-gamma coupling [p < 0.05], 2) increased frontal high gamma connectivity [p < 0.05] and posterior theta connectivity [p ≤ 0.049], and 3) increased frontal high gamma [p < 0.05] and posterior theta [p ≤ 0.046] network density. The behavioral activity and the medium gamma frontoparietal connectivity showed an inverted-U relationship with psilocybin dose. Our results suggest that high-frequency network organization, decoupled from local theta-phase, may be an important signature of psilocybin-induced non-ordinary state of consciousness.

Normative high-frequency oscillation phase-amplitude coupling and effective connectivity under sevoflurane

Resective surgery for pediatric drug-resistant focal epilepsy often requires extraoperative intracranial electroencephalography recording to accurately localize the epileptogenic zone. This procedure entails multiple neurosurgeries, intracranial electrode implantation and explantation, and days of invasive inpatient evaluation. There is a need for methods to reduce diagnostic burden and introduce objective epilepsy biomarkers. Our preliminary studies aimed to address these issues by using sevoflurane anesthesia to rapidly and reversibly activate intraoperative phase-amplitude coupling between delta and high-frequency activities, as well as high-frequency activity-based effective connectivity. Phase-amplitude coupling can serve as a proxy for spike-and-wave discharges, and effective connectivity describes the spatiotemporal dynamics of neural information flow among regions. Notably, sevoflurane activated these interictal electrocorticography biomarkers most robustly in areas whose resection led to seizure freedom. However, they were also increased in normative brain regions that did not require removal for seizure control. Before using these electrocorticography biomarkers prospectively to guide resection, we should understand their endogenous distribution and propagation pathways, at different anesthetic stages. In the current study, we highlighted the normative distribution of delta and high-frequency activity phase-amplitude coupling and effective connectivity under sevoflurane. Normative data was derived from nineteen patients, whose ages ranged from four to eighteen years and included eleven males. All achieved seizure control following focal resection. Electrocorticography was recorded at an isoflurane baseline, during stepwise increases in sevoflurane concentration, and also during extraoperative slow-wave sleep without anesthesia. Normative electrode sites were then mapped onto a standard cortical surface for anatomical visualization. Dynamic tractography traced white matter pathways that connected sites with significantly augmented biomarkers. Finally, we analyzed all sites -regardless of normal or abnormal status - to determine whether sevoflurane-enhanced biomarker values could intraoperatively localize the epileptogenic sites. We found that normative electrocorticography biomarkers increased as a function of sevoflurane concentration, especially in bilateral frontal and parietal lobe regions (Bonferroni-corrected p-values <0.05). Callosal fibers directly connected homotopic Rolandic regions exhibiting elevated phase-amplitude coupling. The superior longitudinal fasciculus linked frontal and parietal association cortices showing augmented effective connectivity. Higher biomarker values, particularly at three to four volume percent sevoflurane, characterized epileptogenicity and seizure-onset zone status (Bonferroni-corrected p-values <0.05). Supplementary analysis showed that epileptogenic sites exhibited less augmentation in delta-based effective connectivity. This study helps clarify the normative distribution of, and plausible propagation pathways supporting, sevoflurane enhanced electrocorticographic biomarkers. Future work should confirm that sevoflurane-activated electrocorticography biomarkers can predict postoperative seizure outcomes in larger cohorts, to establish their clinical utility.

Phase-lagged tACS between executive and default mode networks modulates working memory

Transcranial alternating current stimulation (tACS) is an efficient neuromodulation technique to enhance cognitive function in a non-invasive manner. Using functional magnetic resonance imaging, we investigated whether a cross-frequency coupled tACS protocol with a phase lag (45 and 180 degrees) between the central executive and the default mode networks modulated working-memory performance. We found tACS-phase-dependent modulation of task performance reflected in hippocampal activation and task-related functional connectivity. Our observations provide a neurophysiological basis for neuromodulation and a feasible non-invasive approach to selectively stimulate a task-relevant deep brain structure. Overall, our study highlights the potential of tACS as a powerful tool for enhancing cognitive function and sheds light on the underlying mechanisms of this technique.

Classifying mental motor tasks from chronic ECoG-BCI recordings using phase-amplitude coupling features

Introduction

Phase-amplitude coupling (PAC), the modulation of high-frequency neural oscillations by the phase of slower oscillations, is increasingly recognized as a marker of goal-directed motor behavior. Despite this interest, its specific role and potential value in decoding attempted motor movements remain unclear.

Methods

This study investigates whether PAC-derived features can be leveraged to classify different motor behaviors from ECoG signals within Brain-Computer Interface (BCI) systems. ECoG data were collected using the WIMAGINE implant during BCI experiments with a tetraplegic patient performing mental motor tasks. The data underwent preprocessing to extract complex neural oscillation features (amplitude, phase) through spectral decomposition techniques. These features were then used to quantify PAC by calculating different coupling indices. PAC metrics served as input features in a machine learning pipeline to evaluate their effectiveness in predicting mental tasks (idle state, right-hand movement, left-hand movement) in both offline and pseudo-online modes.

Results

The PAC features demonstrated high accuracy in distinguishing among motor tasks, with key classification features highlighting the coupling of theta/low-gamma and beta/high-gamma frequency bands.

Discussion

These preliminary findings hold significant potential for advancing our understanding of motor behavior and for developing optimized BCI systems.

Precise Spatial Tuning of Visually Driven Alpha Oscillations in Human Visual Cortex

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across occipital cortex, reflecting general cognitive states such as arousal and alertness. However, there is also evidence that modulation of alpha oscillations in visual cortex can be spatially specific. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We separated the alpha oscillatory power from broadband power changes. The variation in alpha oscillatory power with stimulus position was then fit by a population receptive field (pRF) model. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power (70-180 Hz) but are several times larger. The results demonstrate that alpha suppression in human visual cortex can be precisely tuned. Finally, we show how the pattern of alpha responses can explain several features of exogenous visual attention.

Significance Statement

The alpha oscillation is the largest electrical signal generated by the human brain. An important question in systems neuroscience is the degree to which this oscillation reflects system-wide states and behaviors such as arousal, alertness, and attention, versus much more specific functions in the routing and processing of information. We examined alpha oscillations at high spatial precision in human patients with intracranial electrodes implanted over visual cortex. We discovered a surprisingly high spatial specificity of visually driven alpha oscillations, which we quantified with receptive field models. We further use our discoveries about properties of the alpha response to show a link between these oscillations and the spread of visual attention.Grant support: NIH R01 MH111417 (Petridou, Winawer, Ramsey, Devinsky); JSPS Overseas Research Fellowship (Yuasa)The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

GABAergic Progenitor Cell Graft Rescues Cognitive Deficits in Fragile X Syndrome Mice

Fragile X syndrome (FXS) is an inherited neurodevelopmental disorder characterized by a range of clinical manifestations with no effective treatment strategy to date. Here, transplantation of GABAergic precursor cells from the medial ganglionic eminence (MGE) is demonstrated to significantly improve cognitive performance in Fmr1 knockout (KO) mice. Within the hippocampus of Fmr1-KO mice, MGE-derived cells from wild-type donor mice survive, migrate, differentiate into functionally mature interneurons, and form inhibitory synaptic connections with host pyramidal neurons. MGE cell transplantation restores Ras-PKB signaling in pyramidal neurons, enhances AMPA receptor trafficking, rescues synaptic plasticity, and corrects abnormal hippocampal neural oscillations. These findings highlight the potential of GABAergic precursor cell transplantation as a promising therapeutic strategy for FXS.

Emotion Induction Modulates Neural Dynamics Related to the Originality of Ideational Creativity

Emotions remarkably impact our creative minds; nevertheless, a comprehensive mapping of their underlying neural mechanisms remains elusive. Therefore, we examined the influence of emotion induction on ideational originality and its associated neural dynamics. Participants were randomly presented with three short videos with sad, neutral, and happy content. After each video, ideational originality was evaluated using the alternate uses task. Both happy and sad inductions significantly enhanced ideational originality relative to the neutral induction condition. However, no significant difference was observed in ideational originality between the happy and sad emotion inductions. Associated neural dynamics were assessed through EEG time-frequency (TF) power and phase-amplitude coupling (PAC) analyses. Our findings suggest that emotional states elicit distinct TF and PAC profiles associated with ideational originality. Relative to baseline, gamma activity was enhanced after the neutral induction and more enhanced after the induction of a happy emotion but reduced after the induction of sad emotion 2-4 s after starting the task. Our functional connectivity couplings suggest that inducing happy and sad emotions may influence the working memory and attentional system differently, leading to varying effects on associated processing modes. Inducing a happy emotion may result in decreased neural activity and processing of rich information in working memory for exploring more original ideas through cognitive flexibility. In contrast, inducing a sad emotion may enhance neural activity and increase coupling within the attention system to exploit and select fewer original ideas through cognitive persistence.

Decoding the rhythmic representation and communication of visual contents

Rhythmic neural activity is considered essential for adaptively modulating responses in the visual system. In this opinion article we posit that visual brain rhythms also serve a key function in the representation and communication of visual contents. Collating a set of recent studies that used multivariate decoding methods on rhythmic brain signals, we highlight such rhythmic content representations in visual perception, imagery, and prediction. We argue that characterizing representations across frequency bands allows researchers to elegantly disentangle content transfer in feedforward and feedback directions. We further propose that alpha dynamics are central to content-specific feedback propagation in the visual system. We conclude that considering rhythmic content codes is pivotal for understanding information coding in vision and beyond.

Theta-Gamma Decoupling - A neurophysiological marker of impaired reward processing in Parkinson's disease

Individuals with Parkinson's disease (PD) exhibit altered reward processing, reflected by a decreased amplitude of an event-related potential (ERP) marker called reward positivity (RewP). Most studies have used RewP to investigate reward behavior due to the high temporal resolution of EEG and its high sensitivity. However, traditional single-electrode ERP analyses often overlook the intricate dynamics of non-phase-locked oscillatory activity and the complex interactions within these neural oscillatory patterns. Studying oscillatory activity is crucial as it provides mechanistic insights into the functional, spatial, and temporal aspects of neuronal processing. To address this gap, we employed a data-driven approach to identify EEG-based markers associated with PD reward processing deficits. Using an openly available 64-channel EEG dataset of 28 age- and sex-matched PD and control participants during a reinforcement learning task, we conducted a comprehensive secondary analysis. First, we employed a cluster-based permutation method to extract ERP markers, finding a consistent decrease in reward positivity in PD, regardless of medication status. Additionally, through region of interest (ROI) analysis on time-frequency data, we identified specific oscillatory patterns during reward processing. PD patients exhibited attenuated theta power and increased gamma power compared to healthy controls (HC). Notably, within the PD group, those off medication showed anterior localization of high gamma power, while those on medication displayed higher posterior gamma power. Building upon these findings, we explored phase-amplitude coupling between theta phase and gamma amplitude measured by the modulation index. We observed a trend of decreased theta-gamma coupling in PD patients, with statistically significant differences between on and off medication conditions. These results highlight the potential role of theta-gamma coupling as a neuromodulatory target for improving goal-oriented behavior in PD. Our correlation analyses suggest that high gamma power is linked to longer disease duration, while reduced reward positivity and low theta-gamma coupling may serve as markers of the dopaminergic impact on reward processing. Thus, our study unveils the intricate time-frequency dynamics underlying reward processing deficits in PD, emphasizing the utility of a data-driven approach to elucidate neural mechanisms and to identify potential therapeutic targets.

Distinct functional roles of narrow and broadband high-gamma activities in human primary somatosensory cortex

Previous studies have shown that high-gamma (HG) activity in the primary visual cortex (V1) has distinct higher (broadband) and lower (narrowband) components with different functions and origins. However, it is unclear whether similar segregation exists in the primary somatosensory cortex (S1), and the origins and roles of HG activity in S1 remain unknown. Here, we investigate functional roles and origins of HG activity in S1 during tactile stimulation in humans and a rat model. In the human experiment, lower-frequency HG (50-70 Hz, LHG) was more sensitive to sustained tactile intensity compared with higher-frequency HG (70-150 Hz, HHG). HHG activity varied depending on the ratio of low and high mechanical frequencies, with its pattern reflecting a mixture of neural activities corresponding to them. Furthermore, classification analysis revealed that HHG activity contains more information about texture surfaces compared with LHG activity. In the rat experiment, we found that both HHG and LHG activities are strongest in the somatosensory input layer (layer IV), similar to findings in V1. Interestingly, spike-triggered local field potential (stLFP) analysis revealed significant HG oscillations exclusively in layer IV, indicating a dominant coupling between neuronal firing and HG oscillations in this layer. In summary, HHG activity is associated with detecting changes in the rate of contact force and subtle skin deformations whereas LHG activity reflects the absolute amount of applied contact force. Finally, both HHG and LHG originated in layer IV of S1.NEW & NOTEWORTHY We investigated the functional roles and origins of high-gamma (HG) activity in the primary somatosensory cortex (S1). The higher-frequency component of HG activity is associated with detecting changes in the rate of contact force and subtle skin deformations whereas the lower-frequency component reflects the absolute magnitude of the applied contact force. Both types of HG activity were found to originate in layer IV of S1.

Brain under surgical anesthesia: focus on nociception and attention network

Surgery endangers the integrity of the body through a continuous stream of noxious stimuli. General anesthesia helps patients cope with the surgery situation. In the first part of our literature review, we present our new knowledge about nociception as described by Sherrington. Anesthesiology researchers have discovered the common mechanism of action of various anesthetics for loss of consciousness (LOC). We review the neural correlates of anesthesia. Maintaining the unconscious state created by anesthetics during surgery is only possible by continuously counteracting nociception. Finally, we present the role of the opioid receptor system in antinociception. Understanding all these processes can help expand our knowledge about nociception, pain and formation of consciousness.

Improving pre-movement patterns detection with multi-dimensional EEG features for readiness potential decrease

Objective.The readiness potential (RP) is an important neural characteristic in motor preparation-based brain-computer interface. In our previous research, we observed a significant decrease of the RP amplitude in some cases, which severely affects the pre-movement patterns detection. In this paper, we aimed to improve the accuracy (Acc) of pre-movement patterns detection in the condition of RP decrease.Approach.We analyzed multi-dimensional EEG features in terms of time-frequency, brain networks, and cross-frequency coupling (CFC). And, a multi-dimensional Electroencephalogram feature combination (MEFC) algorithm was proposed. The features used include: (1) waveforms of the RP; (2) energy in alpha and beta bands; (3) brain network in alpha and beta bands; and (4) CFC value between 2 and 10 Hz.Main results.By employing support vector machines, the MEFC method achieved an average recognition rate of 88.9% and 85.5% under normal and RP decrease conditions, respectively. Compared to classical algorithm, the average Acc for both tasks improved by 7.8% and 8.8% respectively.Significance.This method can effectively improve the Acc of pre-movement patterns decoding in the condition of RP decrease.

Phase-amplitude coupling during auditory steady-state stimulation: a methodological review

Auditory steady-state response (ASSR) is a robust method to probe gamma (>30 Hz) activity in a controlled manner. While typically the magnitude and the phase synchronization over stimulus repetitions of ASSR is assessed, other measures are being investigated. One of them is phase-amplitude coupling (PAC), which reflects the interactions between lower frequency phase and higher frequency amplitude. Considering that the number of studies assessing PAC during auditory steady-state stimulation has grown recently, in the present work, we aimed to perform a comprehensive overview of PAC methodological approaches in ASSR studies. We sought to evaluate the studies according to PAC analysis issues emphasized in empirical and theoretical PAC studies. Our work showed considerable variability in the methodology among the reviewed studies. Furthermore, the reviewed works address methodological issues and confounding factors of PAC relatively poorly and are characterized by insufficient descriptions of the applied approaches. Our review shows that systematic research of PAC in the context of ASSR is imperative in order to properly evaluate the presence of PAC during the auditory steady-state stimulation.

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.

Contributions of action potentials to scalp EEG: Theory and biophysical simulations

Differences in the apparent 1/f component of neural power spectra require correction depending on the underlying neural mechanisms, which remain incompletely understood. Past studies suggest that neuronal spiking produces broadband signals and shapes the spectral trend of invasive macroscopic recordings, but it is unclear to what extent action potentials (APs) influence scalp EEG. Here, we combined biophysical simulations with statistical modelling to examine the amplitude and spectral content of scalp potentials generated by the electric fields from spiking activity. In physiological parameter regimes, we found that APs contribute negligibly to the EEG spectral trend. Consistent with this, comparing our biophysical simulations with previously published data from pharmacologically paralyzed subjects suggested that the EEG spectral trend can be explained by a combination of synaptic timescales and electromyogram contamination. We also modelled rhythmic EEG generation, finding that APs can generate detectable narrowband power between approximately 60 and 1000 Hz, reaching frequencies much faster than would be possible from synaptic currents. Finally, we show that different spectral detrending strategies are required for AP generated oscillations compared to synaptically generated oscillations, suggesting that existing detrending methods for EEG spectra need to be modified for high frequency signals.

High-gamma frequency flash stimulation as a possible cognitive facilitator in rat pups

High-gamma frequency flashes can enhance cognition by synchronizing neural oscillations in mammals. Early flash treatment promotes the development of improved cognitive functions in young children. However, it is unclear whether exposure to high-gamma frequency flashes in preschool-aged individuals affects cognition in preadolescents by regulating neural oscillations in the brain. Here, we aimed to investigate the effects of gamma-frequency flashes on cognitive ability. In this study, the effect of high-frequency flicker on cognitive performance was verified by behavioural experiments such as the open-field test and the water maze, but also proteomics. We found that external 40 Hz and 70 Hz frequency flashes synchronized neural oscillations at the corresponding frequencies in the primary visual cortex (V1) of rats. Rats that underwent 70 Hz flash intervention had better cognitive behavioural performance in the early stages of training. The 70 Hz flash frequency upregulated proteins associated with neuronal growth and differentiation, such as Snapin, FoxO3, Hspa12a, and Penk, and activated the MAPK signalling pathway, signalling pathway regulating stem cell pluripotency, and the neuroactive ligand-receptor interaction pathway. These proteins and pathways play important roles in cognitive functions. Our study revealed that 70 Hz flashes received by young children early in their development substantially promote the growth of cognitive capabilities in the brain. Exposure to 70 Hz flashes may be a new intervention method and a new strategy for improving cognition.

Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling

Working memory, a fundamental cognitive function of the brain, necessitates the evaluation of cognitive load intensity due to limited cognitive resources. Optimizing cognitive load can enhance task performance efficiency by preventing resource waste and overload. Therefore, identifying working memory load is an essential area of research. Deep learning models have demonstrated remarkable potential in identifying the intensity of working memory load. However, existing neural networks based on electroencephalogram (EEG) decoding primarily focus on temporal and spatial characteristics while neglecting frequency characteristics. Drawing inspiration from the role of cross-frequency coupling in the hippocampal region, which plays a crucial role in advanced cognitive processes such as working memory, this study proposes a Multi-Band Multi-Scale Hybrid Sinc Convolutional Neural Network (MBSincNex). This model integrates multi-frequency and multi-scale Sinc convolution to facilitate time-frequency conversion and extract time-frequency information from multiple rhythms and regions of the EEG data with the aim of effectively model the cross-frequency coupling across different cognitive domains. Due to its unique structural design, the proposed model proficiently extracts features in temporal, frequency, and spatial domains while its feature extraction capability is validated through post-hoc interpretability techniques. On our collected three-class working memory dataset, the proposed model achieved higher classification accuracy compared to other state-of-the-art methods. Furthermore, by analyzing the model's classification performance during different stages of working memory processes, this study emphasizes the significance of the encoding phase and confirms that behavioral response does not accurately reflect cognitive load.

Dissociation-related behaviors in mice emerge from the inhibition of retrosplenial cortex parvalbumin interneurons

Dissociation, characterized by altered consciousness and perception, underlies multiple mental disorders, but the specific neuronal subtypes involved remain elusive. In mice, we find that dissociation-inducing doses of ketamine significantly inhibit retrosplenial cortex (RSC) parvalbumin interneurons (PV-INs), enhancing delta oscillations (1-3 Hz) and delta-gamma phase-amplitude coupling (δ-γ PAC) and inducing dissociation-like behaviors. Optogenetic inhibition of RSC PV-INs triggers delta oscillations, δ-γ PAC, and some dissociation-like behaviors without ketamine. Furthermore, activation of RSC PV-INs or knockdown of the N-methyl-D-aspartate receptor subunit NR1 and the hyperpolarization-activated cyclic nucleotide-gated channel 1 (HCN1) in RSC PV-INs attenuates ketamine-induced delta oscillations, δ-γ PAC, and certain dissociation-like behaviors. These findings reveal that PV-INs regulate delta oscillations and δ-γ PAC and identify NR1 and HCN1 as ketamine targets in PV-INs that may cooperatively affect dissociation, possibly providing potential therapeutic targets for dissociative symptoms.

Layer 6 corticothalamic neurons induce high gamma oscillations through cortico-cortical and cortico-thalamo-cortical pathways

Layer 6 corticothalamic (L6CT) neurons project to both cortex and thalamus, inducing multiple effects including the modulation of cortical and thalamic firing, and the emergence of high gamma oscillations in the cortical local field potential (LFP). We hypothesize that the high gamma oscillations driven by L6CT neuron activation are shaped by the dynamic engagement of intracortical and cortico-thalamo-cortical circuits. To test this, we optogenetically activated L6CT neurons in NTSR1-cre mice expressing channelrhodopsin-2 in L6CT neurons. Leveraging the vibrissal pathway in awake, head-fixed mice, we presented ramp-and-hold light at different intensities while recording neural activity in the primary somatosensory barrel cortex (S1) and the ventral posteromedial nucleus (VPm) of the thalamus using silicon probes. We found that the activation of S1 L6CT neurons induces high-frequency LFP oscillations in S1 that are modulated in frequency, but not in amplitude, across light intensities and over time. To identify which neuronal classes contribute to these oscillations, we examined the temporal evolution of firing rate in S1 and VPm. While most S1 neurons were steadily suppressed, VPm and S1 Layer 4 fast spiking (L4 FS) neurons evolved from being suppressed to facilitated within 5OO ms, suggesting differential recruitment of the intracortical vs cortico-thalamo-cortical pathways. Finally, we found that LFP frequency selectively correlates with VPm firing rate. Taken together, our data suggest that L6CT neurons sculpt the frequency of S1 LFP high gamma oscillations through cortico-thalamo-cortical circuits, linking the recurrent interactions mediated by L6CT neurons to the high gamma oscillations observed across physiological and pathological conditions.

Temporal ablation of the ciliary protein IFT88 alters normal brainwave patterns

The primary cilium is a hair-like organelle that hosts molecular machinery for various developmental and homeostatic signaling pathways. Its alteration can cause rare ciliopathies such as the Bardet-Biedl and Joubert syndromes, but is also linked to Alzheimer's disease, clinical depression, and autism spectrum disorder. These afflictions are caused by disturbances in a wide variety of genes but a common phenotype amongst them is cognitive impairment. While cilia-mediated neural function has been widely examined in early neurodevelopment, their function in the adult brain is not well understood. To help elucidate the role of cilia in neural activity, we temporally induced the ablation of IFT88, a gene encoding the intraflagellar transport 88 protein which is neccessary for ciliogenesis, in adult mice before performing memory-related behavioral assays and electroencephalogram/electromyogram (EEG/EMG) recordings. Inducible IFT88 KO mice exhibited severe learning deficits in trace fear conditioning and Morris water maze tests. They had strongly affected brainwave activity both under isoflurane induced anesthesia and during normal activity. And additionally, inducible IFT88 KO mice had altered sleep architecture and attenuated phase-amplitude coupling, a process that underlies learning and memory formation. These results highlight the growing significance of primary cilia for healthy neural function in the adult brain.

Out of Sight, Out of Mind? Neuronal Gamma Oscillations During Occlusion Events in Infants

Object permanence allows infants to interact successfully with objects in the environment. What happens in the human infant brain when objects move in and out of sight? This study used high-density electroencephalography (hdEEG) to record induced oscillatory brain activities in 29 locomotor infants before, during, and after occlusion of a moving object traveling at different speeds. Temporal spectral evolution (TSE) showed that before and after the occlusion event, event-related synchronized (ERS) brain activity was observed, whereas event-related desynchronized (ERD) activity was detected when the car was hidden behind the occluder. Both synchronized and desynchronized brain activities were found in the gamma frequency band (>30 Hz) in visual areas. Coherence connectivity analysis showed significant cluster differences before and during occlusion, during and after occlusion, and before and after occlusion in the gamma (30-150 Hz) and theta range (4-7 Hz) in several brain sources of interest. It was concluded that locomotor infants between 8.5 and 12 months of age show high-frequency brain oscillations while perceiving a moving object going temporarily out of sight. The significant cluster differences indicate the beginning of specialized connectivity networks, where object permanence is processed within dedicated visual, parietal, and central areas along the dorsal processing stream.

Near-critical corticothalamic eigenmodes: Effects of nonuniform connectivity on modes, activity, and communication channels

The effects of nonuniformities in axonal connectivity on natural modes of brain activity are explored to determine their contributions to modal eigenvalues, structure, and communication and to clarify the limits of validity of widely used uniform-connectivity approximations. Preferred channels of communication are demonstrated that are supported by natural modes of mean connectivity and resulting activity. The effects of axonal tracts on these modes are calculated using perturbation methods, and it is found that modes and their spectra are only moderately perturbed by even the largest white matter tracts. However, perturbations of activity are greatly magnified when modes are near-critical and realistic connectivity and gain perturbations can then enable rapid responses to stimuli on the observed timescales of evoked responses. It is thus argued that dynamic mode-mode communication channels complement ones based on white matter tracts and that both rely on near-criticality to have their observed effects.

IpsiHand Brain-Computer Interface Therapy Induces Broad Upper Extremity Motor Rehabilitation in Chronic Stroke

BACKGROUND

Chronic hemiparetic stroke patients have very limited benefits from current therapies. Brain-computer interface (BCI) engaging the unaffected hemisphere has emerged as a promising novel therapeutic approach for chronic stroke rehabilitation.

OBJECTIVES

This study investigated the effectiveness of contralesionally-controlled BCI therapy in chronic stroke patients with impaired upper extremity motor function. We further explored neurophysiological features of motor recovery driven by BCI. We hypothesized that BCI therapy would induce a broad motor recovery in the upper extremity, and there would be corresponding changes in baseline theta and gamma oscillations, which have been shown to be associated with motor recovery.

METHODS

Twenty-six prospectively enrolled chronic hemiparetic stroke patients performed a therapeutic BCI task for 12 weeks. Motor function assessment data and resting state electroencephalogram signals were acquired before initiating BCI therapy and across BCI therapy sessions. The Upper Extremity Fugl-Meyer assessment served as a primary motor outcome assessment tool. Theta-gamma cross-frequency coupling (CFC) was computed and correlated with motor recovery.

RESULTS

Chronic stroke patients achieved significant motor improvement in both proximal and distal upper extremity with BCI therapy. Motor function improvement was independent of Botox application. Theta-gamma CFC enhanced bilaterally over the C3/C4 motor electrodes and positively correlated with motor recovery across BCI therapy sessions.

CONCLUSIONS

BCI therapy resulted in significant motor function improvement across the proximal and distal upper extremities of patients, which significantly correlated with theta-gamma CFC increases in the motor regions. This may represent rhythm-specific cortical oscillatory mechanism for BCI-driven rehabilitation in chronic stroke patients.

TRIAL REGISTRATION

Advarra Study: https://classic.clinicaltrials.gov/ct2/show/NCT04338971 and Washington University Study: https://classic.clinicaltrials.gov/ct2/show/NCT03611855.

Emergence of multiple spontaneous coherent subnetworks from a single configuration of human connectome coupled oscillators model

Multi-state metastability in neuroimaging signals reflects the brain's flexibility to transition between network configurations in response to changing environments or tasks. We modeled these dynamics with a Kuramoto network of 90 nodes oscillating at an intrinsic frequency of 40 Hz, interconnected using human brain structural connectivity strengths and delays. We simulated this model for 30 min to generate multi-state metastability. We identified global coupling and delay parameters that maximize spectral entropy, a proxy for multi-state metastability. At this operational point, multiple frequency-specific coherent sub-networks spontaneously emerge across oscillatory modes, persisting for periods between 140 and 4300 ms, reflecting flexible and sustained dynamic states. The topography of these sub-networks aligns with empirical resting-state neuroimaging data. Additionally, periodic components of the EEG spectra from young healthy participants correlate with maximal multi-state metastability, while dynamics away from this point correlate with sleep and anesthesia spectra. Our findings suggest that multi-state metastable functional dynamics observed in empirical data emerge from specific interactions of structural topography and connection delays, providing a platform to study mechanisms underlying flexible dynamics of cognition.

Electrophysiological Signatures in Global Cerebral Ischemia: Neuroprotection Via Chemogenetic Inhibition of CA1 Pyramidal Neurons in Rats

BACKGROUND

Although there has been limited research into the perturbation of electrophysiological activity in the brain after ischemia, the activity signatures during ischemia and reperfusion remain to be fully elucidated. We aim to comprehensively describe these electrophysiological signatures and interrogate their correlation with ischemic damage during global cerebral ischemia and reperfusion.

METHODS AND RESULTS

We used the 4-vessel occlusion method of inducing global cerebral ischemia in rats. We used in vivo electrophysiological techniques to simultaneously record single units, scalp electroencephalogram, and local field potentials in awake animals. Neuronal damage and astrocyte reactivation were examined by immunofluorescence, immunoblotting, and quantitative real-time reverse-transcription polymerase chain reaction under chemogenetic inhibition of glutamatergic neurons. Electroencephalogram/local field potentials power and phase-amplitude coupling of the theta and low-gamma bands were reduced during ischemia and the acute phase of reperfusion. The firing rate of single units was enhanced by ischemia-reperfusion, and the phase relationship between the local field potentials theta band and neuronal firing was altered. Precise inhibition of hippocampus CA1 pyramidal neuron hyperactivity by chemogenetics rescued the firing dysfunction, ischemic neuronal damage, and A1 astrocyte activation.

CONCLUSIONS

Our results provide a comprehensive description of the characteristics of electrophysiological activity that accompany ischemia-reperfusion and highlight the significance of this activity in ischemic damage.

Infant low-frequency EEG cortical power, cortical tracking and phase-amplitude coupling predicts language a year later

Cortical signals have been shown to track acoustic and linguistic properties of continuous speech. This phenomenon has been measured in both children and adults, reflecting speech understanding by adults as well as cognitive functions such as attention and prediction. Furthermore, atypical low-frequency cortical tracking of speech is found in children with phonological difficulties (developmental dyslexia). Accordingly, low-frequency cortical signals may play a critical role in language acquisition. A recent investigation with infants Attaheri et al., 2022 [1] probed cortical tracking mechanisms at the ages of 4, 7 and 11 months as participants listened to sung speech. Results from temporal response function (TRF), phase-amplitude coupling (PAC) and dynamic theta-delta power (PSD) analyses indicated speech envelope tracking and stimulus-related power (PSD) for delta and theta neural signals. Furthermore, delta- and theta-driven PAC was found at all ages, with theta phases displaying stronger PAC with high-frequency amplitudes than delta. The present study tests whether these previous findings replicate in the second half of the full cohort of infants (N = 122) who were participating in this longitudinal study (first half: N = 61, (1); second half: N = 61). In addition to demonstrating good replication, we investigate whether cortical tracking in the first year of life predicts later language acquisition for the full cohort (122 infants recruited, 113 retained) using both infant-led and parent-estimated measures and multivariate and univariate analyses. Increased delta cortical tracking in the univariate analyses, increased ~2Hz PSD power and stronger theta-gamma PAC in both multivariate and univariate analyses were related to better language outcomes using both infant-led and parent-estimated measures. By contrast, increased ~4Hz PSD power in the multi-variate analyses, increased delta-beta PAC and a higher theta/delta power ratio in the multi-variate analyses were related to worse language outcomes. The data are interpreted within a "Temporal Sampling" framework for developmental language trajectories.

Temporal Ablation of the Ciliary Protein IFT88 Alters Normal Brainwave Patterns

The primary cilium is a hair-like organelle that hosts molecular machinery for various developmental and homeostatic signaling pathways. Its alteration can cause rare ciliopathies such as the Bardet-Biedl and Joubert syndromes, but is also linked to Alzheimer's disease, clinical depression, and autism spectrum disorder. These afflictions are caused by disturbances in a wide variety of genes but a common phenotype amongst them is cognitive impairment. While cilia-mediated neural function has been widely examined in early neurodevelopment, their function in the adult brain is not well understood. To help elucidate the role of cilia in neural activity, we temporally induced the ablation of IFT88, a gene encoding the intraflagellar transport 88 protein which is neccessary for ciliogenesis, in adult mice before performing memory-related behavioral assays and electroencephalogram/electromyogram (EEG/EMG) recordings. Inducible IFT88 KO mice exhibited severe learning deficits in trace fear conditioning and Morris water maze tests. They had strongly affected brainwave activity both under isoflurane induced anesthesia and during normal activity. And additionally, inducible IFT88 KO mice had altered sleep architecture and attenuated phase-amplitude coupling, a process that underlies learning and memory formation. These results highlight the growing significance of primary cilia for healthy neural function in the adult brain.

Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall revealed through multi-experiment iEEG replication

Dynamic interactions between large-scale brain networks underpin human cognitive processes, but their electrophysiological mechanisms remain elusive. The triple network model, encompassing the salience network (SN), default mode network (DMN), and frontoparietal network (FPN), provides a framework for understanding these interactions. We analyzed intracranial electroencephalography (EEG) recordings from 177 participants across four diverse episodic memory experiments, each involving encoding as well as recall phases. Phase transfer entropy analysis revealed consistently higher directed information flow from the anterior insula (AI), a key SN node, to both DMN and FPN nodes. This directed influence was significantly stronger during memory tasks compared to resting state, highlighting the AI's task-specific role in coordinating large-scale network interactions. This pattern persisted across externally driven memory encoding and internally governed free recall. Control analyses using the inferior frontal gyrus (IFG) showed an inverse pattern, with DMN and FPN exerting higher influence on IFG, underscoring the AI's unique role. We observed task-specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the DMN during memory encoding, but not recall. Crucially, these results were replicated across all four experiments spanning verbal and spatial memory domains with high Bayes replication factors. Our findings advance understanding of how coordinated neural network interactions support memory processes, highlighting the AI's critical role in orchestrating large-scale brain network dynamics during both memory encoding and retrieval. By elucidating the electrophysiological basis of triple network interactions in episodic memory, our study provides insights into neural circuit dynamics underlying memory function and offer a framework for investigating network disruptions in memory-related disorders.

Convergent neural signatures of speech prediction error are a biological marker for spoken word recognition

We use MEG and fMRI to determine how predictions are combined with speech input in superior temporal cortex. We compare neural responses to words in which first syllables strongly or weakly predict second syllables (e.g., "bingo", "snigger" versus "tango", "meagre"). We further compare neural responses to the same second syllables when predictions mismatch with input during pseudoword perception (e.g., "snigo" and "meago"). Neural representations of second syllables are suppressed by strong predictions when predictions match sensory input but show the opposite effect when predictions mismatch. Computational simulations show that this interaction is consistent with prediction error but not alternative (sharpened signal) computations. Neural signatures of prediction error are observed 200 ms after second syllable onset and in early auditory regions (bilateral Heschl's gyrus and STG). These findings demonstrate prediction error computations during the identification of familiar spoken words and perception of unfamiliar pseudowords.

Filtered Point Processes Tractably Capture Rhythmic And Broadband Power Spectral Structure in Neural Electrophysiological Recordings

Neural electrophysiological recordings arise from interacting rhythmic (oscillatory) and broadband (aperiodic) biological subprocesses. Both rhythmic and broadband processes contribute to the neural power spectrum, which decomposes the variance of a neural recording across frequencies. Although an extensive body of literature has successfully studied rhythms in various diseases and brain states, researchers only recently have systematically studied the characteristics of broadband effects in the power spectrum. Broadband effects can generally be categorized as 1) shifts in power across all frequencies, which correlate with changes in local firing rates and 2) changes in the overall shape of the power spectrum, such as the spectral slope or power law exponent. Shape changes are evident in various conditions and brain states, influenced by factors such as excitation to inhibition balance, age, and various diseases. It is increasingly recognized that broadband and rhythmic effects can interact on a sub-second timescale. For example, broadband power is time-locked to the phase of <1 Hz rhythms in propofol induced unconsciousness. Modeling tools that explicitly deal with both rhythmic and broadband contributors to the power spectrum and that capture their interactions are essential to help improve the interpretability of power spectral effects. Here, we introduce a tractable stochastic forward modeling framework designed to capture both narrowband and broadband spectral effects when prior knowledge or theory about the primary biophysical processes involved is available. Population-level neural recordings are modeled as the sum of filtered point processes (FPPs), each representing the contribution of a different biophysical process such as action potentials or postsynaptic potentials of different types. Our approach builds on prior neuroscience FPP work by allowing multiple interacting processes and time-varying firing rates and by deriving theoretical power spectra and cross-spectra. We demonstrate several properties of the models, including that they divide the power spectrum into frequency ranges dominated by rhythmic and broadband effects, and that they can capture spectral effects across multiple timescales, including sub-second cross-frequency coupling. The framework can be used to interpret empirically observed power spectra and cross-frequency coupling effects in biophysical terms, which bridges the gap between theoretical models and experimental results.

Beta-gamma phase-amplitude coupling of scalp electroencephalography during walking preparation in Parkinson's disease differs depending on the freezing of gait

Introduction

Despite using beta oscillations within the subthalamic nucleus as a biomarker of akinesia or rigidity in Parkinson's disease, a specific biomarker for freezing of gait (FOG) remains unclear. Recently, scalp phase-amplitude coupling (PAC) measured through scalp electroencephalography (EEG) has emerged as a promising tool for analyzing brain function. In this study, we examined whether PAC could be a biomarker for FOG.

Methods

We enrolled 11 patients with Parkinson's disease and recorded scalp EEG in preparation for and during gait while simultaneously assessing motor function, including FOG. We investigated changes in cortical PAC during walking with and without FOG and examined its correlation with the postural instability and gait difficulty (PIGD) score.

Results

Patient characteristics were as follows: mean age 59.1 ± 6.9 years, disease duration 13.9 ± 4.1 years, and seven men. Four trials were excluded from the analysis owing to artifacts. In the trials without FOG (n = 18), beta-gamma PAC in the sensorimotor area decreased during gait preparation (p = 0.011; linear mixed-effects model), which was not the case in trials with FOG (n = 6) (p = 0.64; linear mixed-effects model). Using a support vector machine, machine learning of PAC during preparation for walking predicted the presence of FOG with an accuracy of 71.2%. Conversely, PAC increased during walking in trials with FOG (p = 0.0042; linear mixed-effects model), and PAC 20 s after the start of walking was positively correlated with the PIGD score (correlation coefficient = 0.406, p = 0.032; Pearson's rank correlation).

Conclusion

Beta-gamma PAC in the sensorimotor area during preparation for walking differs depending on the emergence of FOG. As gait symptoms worsened, beta-gamma PAC in the sensorimotor area during walking gradually increased. Cortical PAC may be a biomarker for FOG in Parkinson's disease and may lead to the development of strategies to prevent falls in the future.

Thalamocortical dysrhythmia and reward deficiency syndrome as uncertainty disorders

A common anatomical core has been described for psychiatric disorders, consisting of the dorsal anterior cingulate cortex (dACC) and anterior insula, processing uncertainty. A common neurophysiological core has been described for other brain related disorders, called thalamocortical dysrhythmia (TCD), consisting of persistent cross-frequency coupling between low and high frequencies. And a common genetic core has been described for yet another set of hypodopaminergic pathologies called reward deficiency syndromes (RDS). Considering that some RDS have the neurophysiological features of TCD, it can be hypothesized that TCD and RDS have a common anatomical core, yet a differentiating associated neurophysiological mechanism. The EEGs of 683 subjects are analysed in source space for both differences and conjunction between TCD and healthy controls, RDS and healthy controls, and between TCD and RDS. A balance between current densities of the pregenual anterior cingulate cortex (pgACC) extending into the ventromedial prefrontal cortex (vmPFC) and dACC is calculated as well. TCD and RDS share a common anatomical and neurophysiological core, consisting of beta activity in the dACC and theta activity in dACC extending into precuneus and dorsolateral prefrontal cortex. TCD and RDS differ in pgACC/vmPFC activity and demonstrate an opposite balance between pgACC/vmPFC and dACC. Based on the Bayesian brain model TCD and RDS can be defined as uncertainty disorders in which the pgACC/vmPFC and dACC have an opposite balance, possibly explained by an inverted-U curve profile of both pgACC/vmPFC and dACC.

Differential neural mechanisms underlie cortical gating of visual spatial attention mediated by alpha-band oscillations

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information.