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

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.

Effect of Sevoflurane Anesthesia on Intraoperative Spikes, High-Frequency Oscillations, and Phase-Amplitude Coupling in MRI-Normal Hippocampus

PURPOSE

The purpose of this study was to determine the effect of sevoflurane anesthesia on spikes, high-frequency oscillations (HFOs), and phase-amplitude coupling using a modulation index in MRI-normal hippocampus, with the aim of evaluating the utility of intraoperative electrocorticography in identifying the epileptogenic hippocampus during sevoflurane administration.

METHODS

Eleven patients with intractable temporal lobe epilepsy with a normal hippocampus on MRI underwent extra-operative electrocorticography evaluation. Patients were assigned to the Ictal (+) or Ictal (-) group depending on whether the parahippocampal gyrus was included in the seizure onset zone. Intraoperative electrocorticography was performed under 0.5 and 1.5 minimum alveolar concentration of sevoflurane. The rates of spikes, ripples, fast ripples (FRs), ripples on spikes, FRs on spikes, and MI HFO(3-4 Hz) were evaluated.

RESULTS

During the intraoperative electrocorticography procedure, sevoflurane administration was found to significantly increase the rate of spikes, ripples on spikes, fast ripples on spikes, and MI HFO(3-4 Hz) in the Ictal (+) group ( P < 0.01). By contrast, the Ictal (-) group exhibited a paradoxical increase in the rate of ripples and fast ripple ( P < 0.05).

CONCLUSIONS

Our findings indicate that the administration of sevoflurane during intraoperative electrocorticography in patients with MRI-normal hippocampus can lead to a dose-dependent enhancement of epileptic biomarkers (spikes, ripples on spikes, fast ripples on spikes, and MI (HFO 3-4) ) in the epileptogenic hippocampus, while paradoxically increasing the rate of ripples and fast ripple in the nonepileptogenic hippocampus. These results have significant implications for the identification of the MRI-normal hippocampus that requires surgical intervention and preservation of the nonepileptogenic hippocampus.

Altered cortical synaptic lipid signaling leads to intermediate phenotypes of mental disorders

Excitation/inhibition (E/I) balance plays important roles in mental disorders. Bioactive phospholipids like lysophosphatidic acid (LPA) are synthesized by the enzyme autotaxin (ATX) at cortical synapses and modulate glutamatergic transmission, and eventually alter E/I balance of cortical networks. Here, we analyzed functional consequences of altered E/I balance in 25 human subjects induced by genetic disruption of the synaptic lipid signaling modifier PRG-1, which were compared to 25 age and sex matched control subjects. Furthermore, we tested therapeutic options targeting ATX in a related mouse line. Using EEG combined with TMS in an instructed fear paradigm, neuropsychological analysis and an fMRI based episodic memory task, we found intermediate phenotypes of mental disorders in human carriers of a loss-of-function single nucleotide polymorphism of PRG-1 (PRG-1R345T/WT). Prg-1R346T/WT animals phenocopied human carriers showing increased anxiety, a depressive phenotype and lower stress resilience. Network analysis revealed that coherence and phase-amplitude coupling were altered by PRG-1 deficiency in memory related circuits in humans and mice alike. Brain oscillation phenotypes were restored by inhibtion of ATX in Prg-1 deficient mice indicating an interventional potential for mental disorders.

EEG Spectral Power Changes in Patients With Dysexecutive Syndrome Following Cognitive Intervention

BACKGROUND

Acquired brain injury (ABI) leads to cognitive deficiencies, alteration of brain activity associated with an increase in slow-wave (delta and theta bands) power, and reduced fast-wave (alpha, beta, and gamma bands) power. To compensate for the cognitive deficits that impact autonomy and quality of life, patients in a chronic phase can benefit from cognitive intervention.

OBJECTIVE

This study explores the effects of cognitive intervention on brain activity, measured by electroencephalography (EEG), and on executive functioning, assessed by the Test of Attentional Performance (TAP) battery.

METHOD

We provided an ecological rehabilitation intervention, simulating real-life tasks adapted for patients with chronic cognitive disorders. A single-case experimental design (SCED) assessed patients' performance in terms of correct responses percentage (CRs) and reaction times (RTs), and EEG spectral powers before and 1 month after the intervention. The TAP tasks included working memory (WM), divided attention (DA), inhibition (GO), and flexibility (FL). EEG frequency powers were also measured during resting states.

RESULTS

One month after the intervention, significant improvements were observed in CRs and RTs for the FL task. Increases in all frequency band powers occurred during FL, WM, and DA tasks, except for alpha bands in DA. In the GO task, delta and gamma power also increased after the intervention. No significant changes were found during resting-state EEG. The results of this open study, without a control group, are preliminary.

CONCLUSION

The effects of the therapy are mostly reflected by changes in mental FL performance and altered EEG patterns during cognitive tasks, particularly in slow and fast-frequency bands. We argue that cognitive intervention could amplify the compensatory mechanisms following brain damage and/or ease restoration mechanisms in the fast-frequency activity bands. Further SCEDs or studies with control groups are needed to confirm these findings and the role of EEG biomarkers in rehabilitation.

Enhancing visual working memory in schizophrenia: effects of frontoparietal theta tACS in low-performing patients

Schizophrenia is a complex neuro-psychiatric disorder including positive symptoms, negative symptoms, and cognitive deficits. A key cognitive dysfunction in schizophrenia is a deficit in visual working memory (VWM). VWM involves three distinct stages: encoding, maintenance, and retrieval. The deficit in any one stage would produce the same symptom (i.e., poor VWM), although their causes are not the same. In this study, we used a retro-cue VWM task that provides helpful cues at different stages: early in maintenance (early cue), late in maintenance (late cue), or during retrieval (retrieval cue). This modification would help "tag" or identify the cognitive stage(s) most responsible for impaired VWM performance in schizophrenia. Additionally, we took advantage of this tagging feature and applied 6 Hz transcranial alternating current stimulation (tACS) over the right dorsolateral prefrontal cortex (DLPFC) and right posterior parietal cortex (PPC)-which has previously been shown to enhance VWM in low-performing healthy individuals-to examine whether tACS would improve a specific stage or all stages of VWM processing in schizophrenia. We observed that cues significantly enhanced performance in low-performing patients, who benefited equally from early and late maintenance cues, but not from retrieval cues. These low-performers also responded well to theta tACS in their overall VWM performance as opposed to a specific VWM stage. No improvement effect was observed in high-performing patients for both retro cue and tACS. Together, our data suggest that 1) low-performing patients' VWM deficits likely stem from poor memory consolidation rather than retrieval, 2) right frontoparietal theta tACS can improve low-performing patients' VWM performance, and 3) such facilitatory tACS effect is not selective of a specific VWM stage and thus is likely driven by an improvement in overall visual attention.

Layer-specific dynamics of local field potentials in monkey V1 during electrical stimulation

The mammalian neocortex, organized into six cellular layers or laminae, forms a cortical network within layers. Layer specific computations are crucial for sensory processing of visual stimuli within primary visual cortex. Laminar recordings of local field potentials (LFPs) are a powerful tool to study neural activity within cortical layers. Electric brain stimulation is widely used in basic neuroscience and in a large range of clinical applications. However, the layer-specific effects of electric stimulation on LFPs remain unclear. To address this gap, we conducted laminar LFP recordings of the primary visual cortex in monkeys while presenting a flash visual stimulus. Simultaneously, we applied a low frequency sinusoidal current to the occipital lobe with offset frequency to the flash stimulus repetition rate. We analyzed the modulation of visual-evoked potentials with respect to the applied phase of the electric stimulation. Our results reveal that only the deeper layers, but not the superficial layers, show phase-dependent changes in LFP components with respect to the applied current. Employing a cortical column model, we demonstrate that these in vivo observations can be explained by phase-dependent changes in the driving force within neurons of deeper layers. Our findings offer crucial insight into the selective modulation of cortical layers through electric stimulation, thus advancing approaches for more targeted neuromodulation.

The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension

Humans excel at extracting structurally-determined meaning from speech despite inherent physical variability. This study explores the brain's ability to predict and understand spoken language robustly. It investigates the relationship between structural and statistical language knowledge in brain dynamics, focusing on phase and amplitude modulation. Using syntactic features from constituent hierarchies and surface statistics from a transformer model as predictors of forward encoding models, we reconstructed cross-frequency neural dynamics from MEG data during audiobook listening. Our findings challenge a strict separation of linguistic structure and statistics in the brain, with both aiding neural signal reconstruction. Syntactic features have a more temporally spread impact, and both word entropy and the number of closing syntactic constituents are linked to the phase-amplitude coupling of neural dynamics, implying a role in temporal prediction and cortical oscillation alignment during speech processing. Our results indicate that structured and statistical information jointly shape neural dynamics during spoken language comprehension and suggest an integration process via a cross-frequency coupling mechanism.

Coordinated NREM sleep oscillations among hippocampal subfields modulate synaptic plasticity in humans

The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.

Physiology-inspired bifocal fronto-parietal tACS for working memory enhancement

Aging populations face significant cognitive challenges, particularly in working memory (WM). Transcranial alternating current stimulation (tACS) offer promising avenues for cognitive enhancement, especially when inspired by brain physiology. This study (NCT04986787) explores the effect of multifocal tACS on WM performance in healthy older adults, focusing on fronto-parietal network modulation. Individualized physiology-inspired tACS applied to the fronto-parietal network was investigated in two blinded cross-over experiments. The first experiment involved monofocal/bifocal theta-tACS to the fronto-parietal network, while in the second experiment cross-frequency theta-gamma interactions between these regions were explored. Participants have done online WM tasks under the stimulation conditions. Network connectivity was assessed via rs-fMRI and multichannel electroencephalography. Prefrontal monofocal theta tACS modestly improved WM accuracy over sham (d = 0.30). Fronto-parietal stimulation enhanced WM task processing speed, with the strongest effects for bifocal in-phase theta tACS (d = 0.41). Cross-frequency stimulations modestly boosted processing speed with or without impairing task accuracy depending on the stimulation protocol. This research adds to the understanding of physiology-inspired brain stimulation for cognitive enhancement in older subjects.

Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks

Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning frameworks, and demonstrate that end-to-end gradient descent training leads to the emergence of neural oscillations in the central spiking neural network. Significant cross-frequency couplings, indicative of these oscillations, are measured within and across network layers during speech processing, whereas no such interactions are observed when handling background noise inputs. Furthermore, our findings highlight the crucial inhibitory role of feedback mechanisms, such as spike frequency adaptation and recurrent connections, in regulating and synchronizing neural activity to improve recognition performance. Overall, on top of developing our understanding of synchronization phenomena notably observed in the human auditory pathway, our architecture exhibits dynamic and efficient information processing, with relevance to neuromorphic technology.

Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall: A 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 (SN), default mode (DMN), and frontoparietal (FPN) networks, provides a framework for understanding these interactions. We analyzed intracranial 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.

TRanscranial AlterNating current stimulation FOR patients with mild Alzheimer's Disease (TRANSFORM-AD): a randomized controlled clinical trial

BACKGROUND

The mechanistic effects of gamma transcranial alternating current stimulation (tACS) on hippocampal gamma oscillation activity in Alzheimer's Disease (AD) remains unclear. This study aimed to clarify beneficial effects of gamma tACS on cognitive functioning in AD and to elucidate effects on hippocampal gamma oscillation activity.

METHODS

This is a double-blind, randomized controlled single-center trial. Participants with mild AD were randomized to tACS group or sham group, and underwent 30 one-hour sessions of either 40 Hz tACS or sham stimulation over consecutive 15 days. Cognitive functioning, structural magnetic resonance imaging (MRI), and simultaneous electroencephalography-functional MRI (EEG-fMRI) were evaluated at baseline, the end of the intervention and at 3-month follow-up from the randomization.

RESULTS

A total of 46 patients were enrolled (23 in the tACS group, 23 in the sham group). There were no group differences in the change of the primary outcome, 11-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog) score after intervention (group*time, p = 0.449). For secondary outcomes, compared to the control group, the intervention group showed significant improvement in MMSE (group*time, p = 0.041) and MoCA scores (non-parametric test, p = 0.025), which were not sustained at 3-month follow-up. We found an enhancement of theta-gamma coupling in the hippocampus, which was positively correlated with improvements of MMSE score and delayed recall. Additionally, fMRI revealed increase of the local neural activity in the hippocampus.

CONCLUSION

Effects on the enhancement of theta-gamma coupling and neural activity within the hippocampus suggest mechanistic models for potential therapeutic mechanisms of tACS.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03920826; Registration Date: 2019-04-19.

Disrupted Hippocampal Theta-Gamma Coupling and Spike-Field Coherence Following Experimental Traumatic Brain Injury

Traumatic brain injury (TBI) often results in persistent learning and memory deficits, likely due to disrupted hippocampal circuitry underlying these processes. Precise temporal control of hippocampal neuronal activity is important for memory encoding and retrieval and is supported by oscillations that dynamically organize single unit firing. Using high-density laminar electrophysiology, we discovered a loss of oscillatory power across CA1 lamina, with a profound, layer-specific reduction in theta-gamma phase amplitude coupling in injured rats. Interneurons from injured animals were less strongly entrained to theta and gamma oscillations, suggesting a mechanism for the loss of coupling, while pyramidal cells were entrained to a later phase of theta. During quiet immobility, we report decreased ripple amplitudes from injured animals during sharp-wave ripple events. These results reveal deficits in information encoding and retrieval schemes essential to cognition that likely underlie TBI-associated learning and memory impairments, and elucidate potential targets for future neuromodulation therapies.

Novel cyclic homogeneous oscillation detection method for high accuracy and specific characterization of neural dynamics

Determining the presence and frequency of neural oscillations is essential to understanding dynamic brain function. Traditional methods that detect peaks over 1/f noise within the power spectrum fail to distinguish between the fundamental frequency and harmonics of often highly non-sinusoidal neural oscillations. To overcome this limitation, we define fundamental criteria that characterize neural oscillations and introduce the cyclic homogeneous oscillation (CHO) detection method. We implemented these criteria based on an autocorrelation approach to determine an oscillation's fundamental frequency. We evaluated CHO by verifying its performance on simulated non-sinusoidal oscillatory bursts and validated its ability to determine the fundamental frequency of neural oscillations in electrocorticographic (ECoG), electroencephalographic (EEG), and stereoelectroencephalographic (SEEG) signals recorded from 27 human subjects. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method's specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.

High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?

Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60-150 Hz), ripple (80-250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.

Prestimulus Alpha Phase Modulates Visual Temporal Integration

When presented shortly after another, discrete pictures are naturally perceived as continuous. The neuronal mechanism underlying such continuous or discrete perception is not well understood. While continuous alpha oscillations are a candidate for orchestrating such neuronal mechanisms, recent evidence is mixed. In this study, we investigated the influence of prestimulus alpha oscillation on visual temporal perception. Specifically, we were interested in whether prestimulus alpha phase modulates neuronal and perceptual processes underlying discrete or continuous perception. Participants had to report the location of a missing object in a visual temporal integration task, while simultaneously MEG data were recorded. Using source reconstruction, we evaluated local phase effects by contrasting phase angle values between correctly and incorrectly integrated trials. Our results show a phase opposition cluster between -0.8 and -0.5 s (relative to stimulus presentation) and between 6 and 20 Hz. These momentary phase angle values were correlated with behavioral performance and event-related potential amplitude. There was no evidence that frequency defined a window of temporal integration.

Serotonergic input from the dorsal raphe nucleus shapes learning-associated odor responses in the olfactory bulb

AIM

Neural activity in the olfactory bulb (OB) can represent odor information during different brain and behavioral states. For example, the odor responses of mitral/tufted (M/T) cells in the OB change during learning of odor-discrimination tasks and, at the network level, beta power increases and the high gamma (HG) power decreases during odor presentation in such tasks. However, the neural mechanisms underlying these observations remain poorly understood. Here, we investigate whether serotonergic modulation from the dorsal raphe nucleus (DRN) to the OB is involved in shaping activity during the learning process in a go/no-go task in mice.

METHODS

Fiber photometry was used to record the population activity of DRN serotonergic neurons during a go/no-go task. In vivo electrophysiology was used to record neural activity (single units and local field potentials) in the OB during the go/no-go task. Real-time place preference (RTPP) and intracranial light administration in a specific subarea (iClass) tests were used to assess the ability of mice to encoding reward information.

RESULTS

Odor-evoked population activity in serotonergic neurons in the DRN was shaped during the learning process in a go/no-go task. In the OB, neural activity from oscillations to single cells showed complex, learning-associated changes and ability to encode information during an odor discrimination task. However, these properties were not observed after ablation of DRN serotonergic neurons.

CONCLUSION

The activity of neural networks and single cells in the OB, and their ability to encode information about odor value, are shaped by serotonergic projections from the DRN.

Differential effects of theta-gamma tACS on motor skill acquisition in young individuals and stroke survivors: A double-blind, randomized, sham-controlled study

BACKGROUND

Theta-gamma transcranial alternating current stimulation (tACS) was recently found to enhance thumb acceleration in young, healthy participants, suggesting a potential role in facilitating motor skill acquisition. Given the relevance of motor skill acquisition in stroke rehabilitation, theta-gamma tACS may hold potential for treating stroke survivors.

OBJECTIVE

We aimed to examine the effects of theta-gamma tACS on motor skill acquisition in young, healthy participants and stroke survivors.

METHODS

In a pre-registered, double-blind, randomized, sham-controlled study, 78 young, healthy participants received either theta-gamma peak-coupled (TGP) tACS, theta-gamma trough-coupled (TGT) tACS or sham stimulation. 20 individuals with a chronic stroke received either TGP or sham. TACS was applied over motor cortical areas while participants performed an acceleration-dependent thumb movement task. Stroke survivors were characterized using standardized testing, with a subgroup receiving additional structural brain imaging.

RESULTS

Neither TGP nor TGT tACS significantly modified general motor skill acquisition in the young, healthy cohort. In contrast, in the stroke cohort, TGP diminished motor skill acquisition compared to sham. Exploratory analyses revealed that, independent of general motor skill acquisition, healthy participants receiving TGP or TGT exhibited greater peak thumb acceleration than those receiving sham.

CONCLUSION

Although theta-gamma tACS increased thumb acceleration in young, healthy participants, consistent with previous reports, it did not enhance overall motor skill acquisition in a more complex motor task. Furthermore, it even had detrimental effects on motor skill acquisition in stroke survivors.

Understanding the human conflict processing network: A review of the literature on direct neural recordings during performance of a modified stroop task

The Stroop Task is a well-known neuropsychological task developed to investigate conflict processing in the human brain. Our group has utilized direct intracranial neural recordings in various brain regions during performance of a modified color-word Stroop Task to gain a mechanistic understanding of non-emotional human conflict processing. The purpose of this review article is to: 1) synthesize our own studies into a model of human conflict processing, 2) review the current literature on the Stroop Task and other conflict tasks to put our research in context, and 3) describe how these studies define a network in conflict processing. The figures presented are reprinted from our prior publications and key publications referenced in the manuscript. We summarize all studies to date that employ invasive intracranial recordings in humans during performance of conflict-inducing tasks. For our own studies, we analyzed local field potentials (LFPs) from patients with implanted stereotactic electroencephalography (SEEG) electrodes, and we observed intracortical oscillation patterns as well as intercortical temporal relationships in the hippocampus, amygdala, and orbitofrontal cortex (OFC) during the cue-processing phase of a modified Stroop Task. Our findings suggest that non-emotional human conflict processing involves modulation across multiple frequency bands within and between brain structures.

Bursting gamma oscillations in neural mass models

Gamma oscillations (30-120 Hz) in the brain are not periodic cycles, but they typically appear in short-time windows, often called oscillatory bursts. While the origin of this bursting phenomenon is still unclear, some recent studies hypothesize its origin in the external or endogenous noise of neural networks. We demonstrate that an exact neural mass model of excitatory and inhibitory quadratic-integrate and fire-spiking neurons theoretically predicts the emergence of a different regime of intrinsic bursting gamma (IBG) oscillations without any noise source, a phenomenon due to collective chaos. This regime is indeed observed in the direct simulation of spiking neurons, characterized by highly irregular spiking activity. IBG oscillations are distinguished by higher phase-amplitude coupling to slower theta oscillations concerning noise-induced bursting oscillations, thus indicating an increased capacity for information transfer between brain regions. We demonstrate that this phenomenon is present in both globally coupled and sparse networks of spiking neurons. These results propose a new mechanism for gamma oscillatory activity, suggesting deterministic collective chaos as a good candidate for the origin of gamma bursts.

Does slow oscillation-spindle coupling contribute to sleep-dependent memory consolidation? A Bayesian meta-analysis

The active system consolidation theory suggests that information transfer between the hippocampus and cortex during sleep underlies memory consolidation. Neural oscillations during sleep, including the temporal coupling between slow oscillations (SO) and sleep spindles (SP), may play a mechanistic role in memory consolidation. However, differences in analytical approaches and the presence of physiological and behavioral moderators have led to inconsistent conclusions. This meta-analysis, comprising 23 studies and 297 effect sizes, focused on four standard phase-amplitude coupling measures including coupling phase, strength, percentage, and SP amplitude, and their relationship with memory retention. We developed a standardized approach to incorporate non-normal circular-linear correlations. We found strong evidence supporting that precise and strong SO-fast SP coupling in the frontal lobe predicts memory consolidation. The strength of this association is mediated by memory type, aging, and dynamic spatio-temporal features, including SP frequency and cortical topography. In conclusion, SO-SP coupling should be considered as a general physiological mechanism for memory consolidation.

Perineuronal Nets in the Rat Medial Prefrontal Cortex Alter Hippocampal-Prefrontal Oscillations and Reshape Cocaine Self-Administration Memories

The medial prefrontal cortex (mPFC) is a major contributor to relapse to cocaine in humans and to reinstatement in rodent models of cocaine use disorder. The output from the mPFC is potently modulated by parvalbumin (PV)-containing fast-spiking interneurons, the majority of which are surrounded by perineuronal nets. We previously showed that treatment with chondroitinase ABC (ABC) reduced the consolidation and reconsolidation of a cocaine conditioned place preference memory. However, self-administration memories are more difficult to disrupt. Here we report in male rats that ABC treatment in the mPFC attenuated the consolidation and blocked the reconsolidation of a cocaine self-administration memory. However, reconsolidation was blocked when rats were given a novel, but not familiar, type of retrieval session. Furthermore, ABC treatment prior to, but not after, memory retrieval blocked reconsolidation. This same treatment did not alter a sucrose memory, indicating specificity for cocaine-induced memory. In naive rats, ABC treatment in the mPFC altered levels of PV intensity and cell firing properties. In vivo recordings from the mPFC and dorsal hippocampus (dHIP) during the novel retrieval session revealed that ABC prevented reward-associated increases in high-frequency oscillations and synchrony of these oscillations between the dHIP and mPFC. Together, this is the first study to show that ABC treatment disrupts reconsolidation of the original memory when combined with a novel retrieval session that elicits coupling between the dHIP and mPFC. This coupling after ABC treatment may serve as a fundamental signature for how to disrupt reconsolidation of cocaine memories and reduce relapse.

Integrative role of attention networks in frequency-dependent modular organization of human brain

Despite converging evidence of hierarchical organization in the cerebral cortex, with sensory-motor and association regions at opposite ends, the mechanism of such hierarchical interactions remains elusive. This organization was primarily investigated regarding the spatiotemporal dynamics of intrinsic connectivity networks (ICNs). However, more effort is needed to investigate network dynamics in the frequency domain. We aimed to examine the integrative role of brain regions in the frequency domain with graph metrics. Phase-based connectivity estimation was performed in three frequency bands (0.011-0.038, 0.043-0.071, and 0.076-0.103 Hz) in the BOLD signal during rest. We applied modularity analysis to connectivity matrices and investigated those areas, which we called integrative regions, that showed frequency-domain flexibility. Integrative regions, mostly belonging to attention networks, were densely connected to higher-order cognitive ICNs in lower frequency bands but to sensory-motor ICNs in higher frequency bands. We compared the normalized participation coefficient (Pnorm) values of integrative and core regions with respect to their relation to higher-order cognition using a permutation-based t-test for multiple linear regression. Regression parameters of integrative regions in relation to three cognitive scores in executive functions, and working memory were significantly larger than those of core regions (Pfdr < 0.05) for salience ventral attention network. Parameters of integrative regions in relation to intelligence scores were significantly larger than those with core regions (Pfdr < 0.05) in dorsal attention network. Larger parameters of neuropsychological test scores in relation to these flexible parcels further indicate their essential role at an intermediate level in behavior. Results emphasize the importance of frequency-band analysis of brain networks.

Switching tinnitus on or off: An initial investigation into the role of the pregenual and rostral to dorsal anterior cingulate cortices

Research indicates that hearing loss significantly contributes to tinnitus, but it alone does not fully explain its occurrence, as many people with hearing loss do not experience tinnitus. To identify a secondary factor for tinnitus generation, we examined a unique dataset of individuals with intermittent chronic tinnitus, who experience fluctuating periods of tinnitus. EEGs of healthy controls were compared to EEGs of participants who reported perceiving tinnitus on certain days, but no tinnitus on other days.. The EEG data revealed that tinnitus onset is associated with increased theta activity in the pregenual anterior cingulate cortex and decreased theta functional connectivity between the pregenual anterior cingulate cortex and the auditory cortex. Additionally, there is increased alpha effective connectivity from the dorsal anterior cingulate cortex to the pregenual anterior cingulate cortex. When tinnitus is not perceived, differences from healthy controls include increased alpha activity in the pregenual anterior cingulate cortex and heightened alpha connectivity between the pregenual anterior cingulate cortex and auditory cortex. This suggests that tinnitus is triggered by a switch involving increased theta activity in the pregenual anterior cingulate cortex and decreased theta connectivity between the pregenual anterior cingulate cortex and auditory cortex, leading to increased theta-gamma cross-frequency coupling, which correlates with tinnitus loudness. Increased alpha activity in the dorsal anterior cingulate cortex correlates with distress. Conversely, increased alpha activity in the pregenual anterior cingulate cortex can transiently suppress the phantom sound by enhancing theta connectivity to the auditory cortex. This mechanism parallels chronic neuropathic pain and suggests potential treatments for tinnitus by promoting alpha activity in the pregenual anterior cingulate cortex and reducing alpha activity in the dorsal anterior cingulate cortex through pharmacological or neuromodulatory approaches.

Crossmodal hierarchical predictive coding for audiovisual sequences in the human brain

Predictive coding theory suggests the brain anticipates sensory information using prior knowledge. While this theory has been extensively researched within individual sensory modalities, evidence for predictive processing across sensory modalities is limited. Here, we examine how crossmodal knowledge is represented and learned in the brain, by identifying the hierarchical networks underlying crossmodal predictions when information of one sensory modality leads to a prediction in another modality. We record electroencephalogram (EEG) during a crossmodal audiovisual local-global oddball paradigm, in which the predictability of transitions between tones and images are manipulated at both the stimulus and sequence levels. To dissect the complex predictive signals in our EEG data, we employed a model-fitting approach to untangle neural interactions across modalities and hierarchies. The model-fitting result demonstrates that audiovisual integration occurs at both the levels of individual stimulus interactions and multi-stimulus sequences. Furthermore, we identify the spatio-spectro-temporal signatures of prediction-error signals across hierarchies and modalities, and reveal that auditory and visual prediction errors are rapidly redirected to the central-parietal electrodes during learning through alpha-band interactions. Our study suggests a crossmodal predictive coding mechanism where unimodal predictions are processed by distributed brain networks to form crossmodal knowledge.

Cell-class-specific electric field entrainment of neural activity

Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.

Alpha and theta rhythm support perceptual and attentional sampling in vision

The visual system operates rhythmically, through timely coordinated perceptual and attentional processes, involving coexisting patterns in the alpha range (7-13 Hz) at ∼10 Hz, and theta (3-6 Hz) range, respectively. Here we aimed to disambiguate whether variations in task requirements, in terms of attentional demand and side of target presentation, might influence the occurrence of either perceptual or attentional components in behavioral visual performance, also uncovering possible differences in the sampling mechanisms of the two cerebral hemispheres. To this aim, visuospatial performance was densely sampled in two versions of a visual detection task where the side of target presentation was fixed (Task 1), with participants monitoring one single hemifield, or randomly varying across trials, with participants monitoring both hemifields simultaneously (Task 2). Performance was analyzed through spectral decomposition, to reveal behavioral oscillatory patterns. For Task 1, when attentional resources where focused on one hemifield only, the results revealed an oscillatory pattern fluctuating at ∼10 Hz and ∼6-9 Hz, for stimuli presented to the left and the right hemifield, respectively, possibly representing a perceptual sampling mechanism with different efficiency within the left and the right hemispheres. For Task 2, when attentional resources were simultaneously deployed to the two hemifields, a ∼5 Hz rhythm emerged both for stimuli presented to the left and the right, reflecting an attentional sampling process, equally supported by the two hemispheres. Overall, the results suggest that distinct perceptual and attentional sampling mechanisms operate at different oscillatory frequencies and their prevalence and hemispheric lateralization depends on task requirements.

Laminar pattern of sensory-evoked dynamic high-frequency oscillatory activity in the macaque auditory cortex

High-frequency (>60 Hz) neuroelectric signals likely have functional roles distinct from low-frequency (<30 Hz) signals. While high-gamma activity (>60 Hz) does not simply equate to neuronal spiking, they are highly correlated, having similar information encoding. High-gamma activity is typically considered broadband and poorly phase-locked to sensory stimuli and thus is typically analyzed after transformations into absolute amplitude or spectral power. However, those analyses discard signal polarity, compromising the interpretation of neuroelectric events that are essentially dipolar. In the spectrotemporal profiles of field potentials in auditory cortex, we show high-frequency spectral peaks not phase-locked to sound onset, which follow the broadband peak of phase-locked onset responses. Isolating the signal components comprising the high-frequency peaks reveals narrow-band high-frequency oscillatory events, whose instantaneous frequency changes rapidly from >150 to 60 Hz, which may underlie broadband high-frequency spectral peaks in previous reports. The laminar amplitude distributions of the isolated activity had two peak positions, while the laminar phase patterns showed a counterphase relationship between those peaks, indicating the formation of dipoles. Our findings suggest that nonphase-locked HGA arises in part from oscillatory or recurring activity of supragranular-layer neuronal ensembles in auditory cortex.

Practical measurements distinguishing physiological and pathological stereoelectroencephalography channels based on high-frequency oscillations in the human brain

OBJECTIVE

The present study aimed to identify various distinguishing features for use in the accurate classification of stereoelectroencephalography (SEEG) channels based on high-frequency oscillations (HFOs) inside and outside the epileptogenic zone (EZ).

METHODS

HFOs were detected in patients with focal epilepsy who underwent SEEG. Subsequently, HFOs within the seizure-onset and early spread zones were defined as pathological HFOs, whereas others were defined as physiological. Three features of HFOs were identified at the channel level, namely, morphological repetition, rhythmicity, and phase-amplitude coupling (PAC). A machine-learning (ML) classifier was then built to distinguish two HFO types at the channel level by application of the above-mentioned features, and the contributions were quantified. Further verification of the characteristics and classifier performance was performed in relation to various conscious states, imaging results, EZ location, and surgical outcomes.

RESULTS

Thirty-five patients were included in this study, from whom 166  104 pathological HFOs in 255 channels and 53 374 physiological HFOs in 282 channels were entered into the analysis pipeline. The results revealed that the morphological repetitions of pathological HFOs were markedly higher than those of the physiological HFOs; this was also observed for rhythmicity and PAC. The classifier exhibited high accuracy in differentiating between the two forms of HFOs, as indicated by an area under the curve (AUC) of 0.89. Both PAC and rhythmicity contributed significantly to this distinction. The subgroup analyses supported these findings.

SIGNIFICANCE

The suggested HFO features can accurately distinguish between pathological and physiological channels substantially improving its usefulness in clinical localization.

PLAIN LANGUAGE SUMMARY

In this study, we computed three quantitative features associated with HFOs in each SEEG channel and then constructed a machine learning-based classifier for the classification of pathological and physiological channels. The classifier performed well in distinguishing the two channel types under different levels of consciousness as well as in terms of imaging results, EZ location, and patient surgical outcomes.

Attentional selection and communication through coherence: Scope and limitations

Synchronous neural oscillations are strongly associated with a variety of perceptual, cognitive, and behavioural processes. It has been proposed that the role of the synchronous oscillations in these processes is to facilitate information transmission between brain areas, the 'communication through coherence,' or CTC hypothesis. The details of how this mechanism would work, however, and its causal status, are still unclear. Here we investigate computationally a proposed mechanism for selective attention that directly implicates the CTC as causal. The mechanism involves alpha band (about 10 Hz) oscillations, originating in the pulvinar nucleus of the thalamus, being sent to communicating cortical areas, organizing gamma (about 40 Hz) oscillations there, and thus facilitating phase coherence and communication between them. This is proposed to happen contingent on control signals sent from higher-level cortical areas to the thalamic reticular nucleus, which controls the alpha oscillations sent to cortex by the pulvinar. We studied the scope of this mechanism in parameter space, and limitations implied by this scope, using a computational implementation of our conceptual model. Our results indicate that, although the CTC-based mechanism can account for some effects of top-down and bottom-up attentional selection, its limitations indicate that an alternative mechanism, in which oscillatory coherence is caused by communication between brain areas rather than being a causal factor for it, might operate in addition to, or even instead of, the CTC mechanism.

Gamma amplitude-envelope correlations are strongly elevated within hyperexcitable networks in focal epilepsy

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40-200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.

How to design optimal brain stimulation to modulate phase-amplitude coupling?

Objective.Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a significant role in brain activity and has been implicated in various neurological disorders. For example, in Parkinson's disease, PAC between the beta (13-30 Hz) and gamma (30-100 Hz) rhythms in the motor cortex is exaggerated, while in Alzheimer's disease, PAC between the theta (4-8 Hz) and gamma rhythms is diminished. Modulating PAC (i.e. reducing or enhancing PAC) using brain stimulation could therefore open new therapeutic avenues. However, while it has been previously reported that phase-locked stimulation can increase PAC, it is unclear what the optimal stimulation strategy to modulate PAC might be. Here, we provide a theoretical framework to narrow down the experimental optimisation of stimulation aimed at modulating PAC, which would otherwise rely on trial and error.Approach.We make analytical predictions using a Stuart-Landau model, and confirm these predictions in a more realistic model of coupled neural populations.Main results.Our framework specifies the critical Fourier coefficients of the stimulation waveform which should be tuned to optimally modulate PAC. Depending on the characteristics of the amplitude response curve of the fast population, these components may include the slow frequency, the fast frequency, combinations of these, as well as their harmonics. We also show that the optimal balance of energy between these Fourier components depends on the relative strength of the endogenous slow and fast rhythms, and that the alignment of fast components with the fast rhythm should change throughout the slow cycle. Furthermore, we identify the conditions requiring to phase-lock stimulation to the fast and/or slow rhythms.Significance.Together, our theoretical framework lays the foundation for guiding the development of innovative and more effective brain stimulation aimed at modulating PAC for therapeutic benefit.

Frequency-specific directed connectivity between the hippocampus and parietal cortex during verbal and spatial episodic memory: an intracranial EEG replication

Hippocampus-parietal cortex circuits are thought to play a crucial role in memory and attention, but their neural basis remains poorly understood. We employed intracranial intracranial electroencephalography (iEEG) to investigate the neurophysiological underpinning of these circuits across three memory tasks spanning verbal and spatial domains. We uncovered a consistent pattern of higher causal directed connectivity from the hippocampus to both lateral parietal cortex (supramarginal and angular gyrus) and medial parietal cortex (posterior cingulate cortex) in the delta-theta band during memory encoding and recall. This connectivity was independent of activation or suppression states in the hippocampus or parietal cortex. Crucially, directed connectivity from the supramarginal gyrus to the hippocampus was enhanced in participants with higher memory recall, highlighting its behavioral significance. Our findings align with the attention-to-memory model, which posits that attention directs cognitive resources toward pertinent information during memory formation. The robustness of these results was demonstrated through Bayesian replication analysis of the memory encoding and recall periods across the three tasks. Our study sheds light on the neural basis of casual signaling within hippocampus-parietal circuits, broadening our understanding of their critical roles in human cognition.

Respiratory Signal Extraction from ECG using a Phase-Amplitude Cross-Frequency Coupling Index

Direct measurement of respiration is comparatively rarer than recordings of ECG and EEG for patients under clinical study, especially those in epilepsy monitoring units. We propose a new method for extracting respiration from ECG using phase-amplitude cross-frequency coupling (PAC), which is more resilient to artifacts than existing extraction methods. When analysed with a standard ECG and respiration dataset, PAC performs comparably to ECG envelope extraction, the most commonly employed approach. There was no significant difference between the wavelet phase coherence of this method versus ECG envelope, calculated against actual respiration, nor any significant difference between the distribution of predicted respiration rates. The PAC method's decreased sensitivity to high-amplitude noise suggests it as a candidate for extracting respiration during high-amplitude seizure events when only ECG recordings are available.

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset

OBJECTIVE

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci.

METHODS

We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset.

RESULTS

In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM.

SIGNIFICANCE

It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

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

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

Individualized music induces theta-gamma phase-amplitude coupling in patients with disorders of consciousness

Objective

This study aimed to determine whether patients with disorders of consciousness (DoC) could experience neural entrainment to individualized music, which explored the cross-modal influences of music on patients with DoC through phase-amplitude coupling (PAC). Furthermore, the study assessed the efficacy of individualized music or preferred music (PM) versus relaxing music (RM) in impacting patient outcomes, and examined the role of cross-modal influences in determining these outcomes.

Methods

Thirty-two patients with DoC [17 with vegetative state/unresponsive wakefulness syndrome (VS/UWS) and 15 with minimally conscious state (MCS)], alongside 16 healthy controls (HCs), were recruited for this study. Neural activities in the frontal-parietal network were recorded using scalp electroencephalography (EEG) during baseline (BL), RM and PM. Cerebral-acoustic coherence (CACoh) was explored to investigate participants' abilitiy to track music, meanwhile, the phase-amplitude coupling (PAC) was utilized to evaluate the cross-modal influences of music. Three months post-intervention, the outcomes of patients with DoC were followed up using the Coma Recovery Scale-Revised (CRS-R).

Results

HCs and patients with MCS showed higher CACoh compared to VS/UWS patients within musical pulse frequency (p = 0.016, p = 0.045; p < 0.001, p = 0.048, for RM and PM, respectively, following Bonferroni correction). Only theta-gamma PAC demonstrated a significant interaction effect between groups and music conditions (F (2,44) = 2.685, p = 0.036). For HCs, the theta-gamma PAC in the frontal-parietal network was stronger in the PM condition compared to the RM (p = 0.016) and BL condition (p < 0.001). For patients with MCS, the theta-gamma PAC was stronger in the PM than in the BL (p = 0.040), while no difference was observed among the three music conditions in patients with VS/UWS. Additionally, we found that MCS patients who showed improved outcomes after 3 months exhibited evident neural responses to preferred music (p = 0.019). Furthermore, the ratio of theta-gamma coupling changes in PM relative to BL could predict clinical outcomes in MCS patients (r = 0.992, p < 0.001).

Conclusion

Individualized music may serve as a potential therapeutic method for patients with DoC through cross-modal influences, which rely on enhanced theta-gamma PAC within the consciousness-related network.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery

BACKGROUND

The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight.

OBJECTIVE

To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke.

METHODS

Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined.

RESULTS

Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively.

CONCLUSIONS

This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Extracting Transient Phase-Amplitude Coupling from Resting-State EEG Signals

Electroencephalography (EEG) allows us to observe brain activity through electrical signals. Phase-amplitude coupling (PAC) is a way to analyze EEG data by focusing on the interaction between the low- and high-frequency components of these signals. However, PAC analyses are often challenged by various methodological issues. We here propose a novel approach which alleviates these issues. Our method has the following features: (i) it addresses the transient nature of coupling through data epoching; (ii) it ensures the presence of low-frequency oscillations through peak detection in the power spectrum; (iii) it applies adaptive high-frequency filtering; and (iv) it performs statistical validation using surrogate data. The efficiency of our method is demonstrated through both a simulation study and the analysis of experimental EEG data, offering new insights into the intricate workings of brain signal interactions.

High-gamma and beta bursts in the Left Supramarginal Gyrus can accurately differentiate verbal memory states and performance

The left supramarginal gyrus (LSMG) may mediate attention to memory, and gauge memory state and performance. We performed a secondary analysis of 142 verbal delayed free recall experiments, in patients with medically-refractory epilepsy with electrode contacts implanted in the LSMG. In 14 of 142 experiments (in 14 of 113 patients), the cross-validated convolutional neural networks (CNNs) that used 1-dimensional(1-D) pairs of convolved high-gamma and beta tensors, derived from the LSMG recordings, could label recalled words with an area under the receiver operating curve (AUROC) of greater than 60% [range: 60-90%]. These 14 patients were distinguished by: 1) higher amplitudes of high-gamma bursts; 2) distinct electrode placement within the LSMG; and 3) superior performance compared with a CNN that used a 1-D tensor of the broadband recordings in the LSMG. In a pilot study of 7 of these patients, we also cross-validated CNNs using paired 1-D convolved high-gamma and beta tensors, from the LSMG, to: a) distinguish word encoding epochs from free recall epochs [AUC 0.6-1]; and distinguish better performance from poor performance during delayed free recall [AUC 0.5-0.86]. These experiments show that bursts of high-gamma and beta generated in the LSMG are biomarkers of verbal memory state and performance.

Phase locking of hippocampal CA3 neurons to distal CA1 theta oscillations selectively predicts memory performance

How the coordination of neuronal spiking and brain rhythms between hippocampal subregions supports memory function remains elusive. We studied the interregional coordination of CA3 neuronal spiking with CA1 theta oscillations by recording electrophysiological signals along the proximodistal axis of the hippocampus in rats that were performing a high-memory-demand recognition memory task adapted from humans. We found that CA3 population spiking occurs preferentially at the peak of distal CA1 theta oscillations when memory was tested but only when previously encountered stimuli were presented. In addition, decoding analyses revealed that only population cell firing of proximal CA3 together with that of distal CA1 can predict performance at test in the present non-spatial task. Overall, our work demonstrates an important role for the synchronization of CA3 neuronal activity with CA1 theta oscillations during memory testing.

Modeling the contribution of theta-gamma coupling to sequential memory, imagination, and dreaming

Gamma oscillations nested in a theta rhythm are observed in the hippocampus, where are assumed to play a role in sequential episodic memory, i.e., memorization and retrieval of events that unfold in time. In this work, we present an original neurocomputational model based on neural masses, which simulates the encoding of sequences of events in the hippocampus and subsequent retrieval by exploiting the theta-gamma code. The model is based on a three-layer structure in which individual Units oscillate with a gamma rhythm and code for individual features of an episode. The first layer (working memory in the prefrontal cortex) maintains a cue in memory until a new signal is presented. The second layer (CA3 cells) implements an auto-associative memory, exploiting excitatory and inhibitory plastic synapses to recover an entire episode from a single feature. Units in this layer are disinhibited by a theta rhythm from an external source (septum or Papez circuit). The third layer (CA1 cells) implements a hetero-associative net with the previous layer, able to recover a sequence of episodes from the first one. During an encoding phase, simulating high-acetylcholine levels, the network is trained with Hebbian (synchronizing) and anti-Hebbian (desynchronizing) rules. During retrieval (low-acetylcholine), the network can correctly recover sequences from an initial cue using gamma oscillations nested inside the theta rhythm. Moreover, in high noise, the network isolated from the environment simulates a mind-wandering condition, randomly replicating previous sequences. Interestingly, in a state simulating sleep, with increased noise and reduced synapses, the network can "dream" by creatively combining sequences, exploiting features shared by different episodes. Finally, an irrational behavior (erroneous superimposition of features in various episodes, like "delusion") occurs after pathological-like reduction in fast inhibitory synapses. The model can represent a straightforward and innovative tool to help mechanistically understand the theta-gamma code in different mental states.

Seizure Outcome After Intraoperative Electrocorticography-Tailored Epilepsy Surgery: A Systematic Review and Meta-Analysis

BACKGROUND AND OBJECTIVES

Tailoring epilepsy surgery using intraoperative electrocorticography (ioECoG) has been debated, and modest number of epilepsy surgery centers apply this diagnostic method. We assessed the current evidence to use ioECoG-tailored epilepsy surgery for improving postsurgical outcome.

METHODS

PubMed and Embase were searched for original studies reporting on ≥10 cases who underwent ioECoG-tailored surgery for epilepsy, with a follow-up of at least 6 months. We used a random-effects model to calculate the overall rate of patients achieving favorable seizure outcome (FSO), defined as Engel class I, ILAE class 1, or seizure-free status. Meta-regression was used to investigate potential sources of heterogeneity. We calculated the odds ratio (OR) for estimating variables on FSO:ioECoG vs non-ioECoG-tailored surgery (if included studies contained patients with non-ioECoG-tailored surgery), ioECoG-tailored epilepsy surgery in children vs adults, temporal (TL) vs extratemporal lobe (eTL), MRI-positive vs MRI-negative, and complete vs incomplete resection of tissue that generated interictal epileptiform discharges (IEDs). A Bayesian network meta-analysis was conducted for underlying pathologies. We assessed the evidence certainty using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE).

RESULTS

Eighty-three studies (82 observational studies, 1 trial) comprising 3,631 patients with ioECoG-tailored surgery were included. The overall pooled rate of patients who attained FSO after ioECoG-tailored surgery was 74% (95% CI 71-77) with significant heterogeneity, which was predominantly attributed to pathologies and seizure outcome classifications. Twenty-two studies contained non-ioECoG-tailored surgeries. IoECoG-tailored surgeries reached a higher rate of FSO than non-ioECoG-tailored surgeries (OR 2.10 [95% CI 1.37-3.24]; p < 0.01; very low certainty). Complete resection of tissue that displayed IEDs in ioECoG predicted FSO better compared with incomplete resection (OR 3.04 [1.76-5.25]; p < 0.01; low certainty). We found insignificant difference in FSO after ioECoG-tailored surgery in children vs adults, TL vs eTL, or MRI-positive vs MRI-negative. The network meta-analysis showed that the odds of FSO was lower for malformations of cortical development than for tumors (OR 0.47 95% credible interval 0.25-0.87).

DISCUSSION

Although limited by low-quality evidence, our meta-analysis shows a relatively good surgical outcome (74% FSO) after epilepsy surgery with ioECoG, especially in tumors, with better outcome for ioECoG-tailored surgeries in studies describing both and better outcome after complete removal of IED areas.

Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia

Slow cortical oscillations play a crucial role in processing the speech amplitude envelope, which is perceived atypically by children with developmental dyslexia. Here we use electroencephalography (EEG) recorded during natural speech listening to identify neural processing patterns involving slow oscillations that may characterize children with dyslexia. In a story listening paradigm, we find that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic versus other child control groups (typically-developing controls, other language disorder controls). We further isolate EEG common spatial patterns (CSP) during speech listening across delta and theta oscillations that identify dyslexic children. A linear classifier using four delta-band CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia when applied to EEG measured during a rhythmic syllable processing task. This transfer effect (i.e., the ability to use neural features derived from a story listening task as input features to a classifier based on a rhythmic syllable task) is consistent with a core developmental deficit in neural processing of speech rhythm. The findings are suggestive of distinct atypical neurocognitive speech encoding mechanisms underlying dyslexia, which could be targeted by novel interventions.

Interaction of acetylcholine and oxytocin neuromodulation in the hippocampus

A postulated role of subcortical neuromodulators is to control brain states. Mechanisms by which different neuromodulators compete or cooperate at various temporal scales remain an open question. We investigated the interaction of acetylcholine (ACh) and oxytocin (OXT) at slow and fast timescales during various brain states. Although these neuromodulators fluctuated in parallel during NREM packets, transitions from NREM to REM were characterized by a surge of ACh but a continued decrease of OXT. OXT signaling lagged behind ACh. High ACh was correlated with population synchrony and gamma oscillations during active waking, whereas minimum ACh predicts sharp-wave ripples (SPW-Rs). Optogenetic control of ACh and OXT neurons confirmed the active role of these neuromodulators in the observed correlations. Synchronous hippocampal activity consistently reduced OXT activity, whereas inactivation of the lateral septum-hypothalamus path attenuated this effect. Our findings demonstrate how cooperative actions of these neuromodulators allow target circuits to perform specific functions.

The direction of theta and alpha travelling waves modulates human memory processing

To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.

Same, Same but Different? A Multi-Method Review of the Processes Underlying Executive Control

Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions.

Optogenetic stimulation of medial septal glutamatergic neurons modulates theta-gamma coupling in the hippocampus

Hippocampal cross-frequency theta-gamma coupling (TGC) is a basic mechanism for information processing, retrieval, and consolidation of long-term and working memory. While the role of entorhinal afferents in the modulation of hippocampal TGC is widely accepted, the influence of other main input to the hippocampus, from the medial septal area (MSA, the pacemaker of the hippocampal theta rhythm) is poorly understood. Optogenetics allows us to explore how different neuronal populations of septohippocampal circuits control neuronal oscillations in vivo. Rhythmic activation of septal glutamatergic neurons has been shown to drive hippocampal theta oscillations, but the role of these neuronal populations in information processing during theta activation has remained unclear. Here we investigated the influence of phasic activation of MSA glutamatergic neurons expressing channelrhodopsin II on theta-gamma coupling in the hippocampus. During the experiment, local field potentials of MSA and hippocampus of freely behaving mice were modulated by 470 nm light flashes with theta frequency (2-10) Hz. It was shown that both the power and the strength of modulation of gamma rhythm nested on hippocampal theta waves depend on the frequency of stimulation. The modulation of the amplitude of slow gamma rhythm (30-50 Hz) prevailed over modulation of fast gamma (55-100 Hz) during flash trains and the observed effects were specific for theta stimulation of MSA. We discuss the possibility that phasic depolarization of septal glutamatergic neurons controls theta-gamma coupling in the hippocampus and plays a role in memory retrieval and consolidation.

Single session cross-frequency bifocal tACS modulates visual motion network activity in young healthy population and stroke patients

BACKGROUND

Phase synchronization over long distances underlies inter-areal communication and importantly, modulates the flow of information processing to adjust to cognitive demands.

OBJECTIVE

This study investigates the impact of single-session, cross-frequency (Alpha-Gamma) bifocal transcranial alternating current stimulation (cf-tACS) to the cortical visual motion network on inter-areal coupling between the primary visual cortex (V1) and the medio-temporal area (MT) and on motion direction discrimination.

METHODS

Based on the well-established phase-amplitude coupling (PAC) mechanism driving information processing in the visual system, we designed a novel directionally tuned cf-tACS protocol. Directionality of information flow was inferred from the area receiving low-frequency tACS (e.g., V1) projecting onto the area receiving high-frequency tACS (e.g., MT), in this case, promoting bottom-up information flow (Forward-tACS). The control condition promoted the opposite top-down connection (from MT to V1, called Backward-tACS), both compared to a Sham-tACS condition. Task performance and EEG activity were recorded from 45 young healthy subjects. An additional cohort of 16 stroke patients with occipital lesions and impairing visual processing was measured to assess the influence of a V1 lesion on the modulation of V1-MT coupling.

RESULTS

The results indicate that Forward cf-tACS successfully modulated bottom-up PAC (V1 α-phase-MT ɣ-amplitude) in both cohorts, while producing opposite effects on the reverse MT-to-V1 connection. Backward-tACS did not change V1-MT PAC in either direction in healthy participants but induced a slight decrease in bottom-up PAC in stroke patients. However, these changes in inter-areal coupling did not translate into cf-tACS-specific behavioural improvements.

CONCLUSIONS

Single session cf-tACS can alter inter-areal coupling in intact and lesioned brains but is probably not enough to induce longer-lasting behavioural effects in these cohorts. This might suggest that a longer daily visual training protocol paired with tACS is needed to unveil the relationship between externally applied oscillatory activity and behaviourally relevant brain processing.