Theta Oscillations in Human Memory

Direct Comparison of EEG Resting State and Task Functional Connectivity Patterns for Predicting Working Memory Performance Using Connectome-Based Predictive Modeling

Background: The integration of machine learning with advanced neuroimaging has emerged as a powerful approach for uncovering the relationship between neuronal activity patterns and behavioral traits. While resting-state neuroimaging has significantly contributed to understanding the neural basis of cognition, recent fMRI studies suggest that task-based paradigms may offer superior predictive power for cognitive outcomes. However, this hypothesis has never been tested using electroencephalography (EEG) data. Methods: We conducted the first experimental comparison of predictive models built on high-density EEG data recorded during both resting-state and an auditory working memory task. Multiple data processing pipelines were employed to ensure robustness and reliability. Model performance was evaluated by computing the Pearson correlation coefficient between predicted and observed behavioral scores, supplemented by mean absolute error and root mean square error metrics for each model configuration. Results: Consistent with prior fMRI findings, task-based EEG data yielded slightly better modeling performance than resting-state data. Both conditions demonstrated high predictive accuracy, with peak correlations between observed and predicted values reaching r = 0.5. Alpha and beta band functional connectivity were the strongest predictors of working memory performance, followed by theta and gamma bands. Additionally, the choice of parcellation atlas and connectivity method significantly influenced results, highlighting the importance of methodological considerations. Conclusion: Our findings support the advantage of task-based EEG over resting-state data in predicting cognitive performance, aligning with. The study underscores the critical role of frequency-specific functional connectivity and methodological choices in model performance. These insights should guide future experimental designs in cognitive neuroscience.

Processes and measurements: a framework for understanding neural oscillations in field potentials

Various neuroscientific theories maintain that brain oscillations are important for neuronal computation, but opposing views claim that these macroscale dynamics are 'exhaust fumes' of more relevant processes. Here, we approach the question of whether oscillations are functional or epiphenomenal by distinguishing between measurements and processes, and by reviewing whether causal or inferentially useful links exist between field potentials, electric fields, and neurobiological events. We introduce a vocabulary for the role of brain signals and their underlying processes, demarcating oscillations as a distinct entity where both processes and measurements can exhibit periodicity. Leveraging this distinction, we suggest that electric fields, oscillating or not, are causally and computationally relevant, and that field potential signals can carry information even without causality.

Identifying EEG markers related to acute cannabis consumption: A systematic review

BACKGROUND/RATIONALE

Electroencephalography (EEG) has potential to provide a sensitive measure of the acute neurophysiological response to cannabis administration. As delta-9-tetrahydrocannabinol (THC; the psychoactive constituent of cannabis) can induce transient neurocognitive impairments that differ as a function of tolerance and dose, understanding the neural profile related to intoxication would be of great benefit in the wake of increasing recreational and medicinal use. Accordingly, the present systematic review examined the current research literature related to acute cannabis administration and EEG measures.

METHODS

Peer-reviewed articles published from 2000 were assessed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies that administered non-synthetic cannabis, containing THC (orally or inhaled) and reported differences in EEG outcomes within the acute time frame (<6 hours post-administration) as compared to baseline or placebo, were eligible for inclusion.

RESULTS/DISCUSSION

A total of 16 studies were eligible for inclusion, of which 11 reported differences in the amplitude/latency of event-related potentials (ERPs) and 9 reported changes in frequency band power. Of the ERPs, the P3 was identified as a potential indicator of recent cannabis consumption, as demonstrated by decreased P3 amplitude across various doses (generally exhibiting small-to-moderate magnitude effects where effect sizes were reported). Oscillatory activity in the theta frequency band power range (typically 4-7 Hz) was impacted following cannabis administration, with some support for a dose-dependent change in power. The present results highlight the potential utility of some EEG measures as markers of recent cannabis consumption, although great heterogeneity in participant characteristics and reported data limits conclusions from these results. It is also evident that EEG changes in highly tolerant user groups (such as those who use cannabis medicinally), require further exploration.

Closed-loop control of theta oscillations enhances human hippocampal network connectivity

Theta oscillations are implicated in regulating information flow within cortico-hippocampal networks to support memory and cognition. However, causal evidence tying theta oscillations to network communication in humans is lacking. Here we report experimental findings using a closed-loop, phase-locking algorithm to apply direct electrical stimulation to neocortical nodes of the hippocampal network precisely timed to ongoing hippocampal theta rhythms in human neurosurgical patients. We show that repetitive stimulation of lateral temporal cortex synchronized to hippocampal theta increases hippocampal theta while it is delivered, suggesting theta entrainment of hippocampal neural activity. After stimulation, network connectivity is persistently increased relative to baseline, as indicated by theta-phase synchrony of hippocampus to neocortex and increased amplitudes of the hippocampal evoked response to isolated neocortical stimulation. These indicators of network connectivity are not affected by control stimulation delivered with approximately the same rhythm but without phase locking to hippocampal theta. These findings support the causal role of theta oscillations in routing neural signals across the hippocampal network and suggest phase-synchronized stimulation as a promising method to modulate theta- and hippocampal-dependent behaviors.

Interictal network dysfunction and cognitive impairment in epilepsy

Epilepsy is diagnosed when neural networks become capable of generating excessive or hypersynchronous activity patterns that result in observable seizures. In many cases, epilepsy is associated with cognitive comorbidities that persist between seizures and negatively impact quality of life. Dysregulation of the coordinated physiological network interactions that are required for cognitive function has been implicated in mediating these enduring symptoms, but the causal mechanisms are often elusive. Here, we provide an overview of neural network abnormalities with the potential to contribute to cognitive dysfunction in epilepsy. We examine these pathological interactions across spatial and temporal scales, additionally highlighting the dynamics that arise in response to the brain's intrinsic capacity for plasticity. Understanding these processes will facilitate development of network-level interventions to address cognitive comorbidities that remain undertreated by currently available epilepsy therapeutics.

Phase-dependent closed-loop deep brain stimulation of the fornix provides bidirectional manipulation of hippocampal theta oscillations

INTRODUCTION

Alzheimer's disease (AD) has very limited treatment options and therapies to prevent or reverse neurodegeneration remain elusive. Deep brain stimulation (DBS), whereby high-frequency pulses of electricity are delivered continuously to a specific part of the brain, has been trialled as an experimental treatment for AD. In AD patients, continuous, high frequency DBS targeted to the fornix (fx-DBS) has been shown to be safe, but not reliably effective across patients. In movement disorders, high-frequency DBS is thought to act as a virtual lesion, disrupting pathophysiological activity. In AD, it may be more advantageous to use stimulation to reinforce or rebuild oscillatory activities that are disrupted by the disease process. A primary candidate for such a target is the hippocampal theta oscillation, which provides a temporal framework for mnemonic processing and is altered in rodent models of AD.

MATERIAL AND METHODS

We applied closed-loop electrical stimulation to the fornix of rats traversing a linear track, triggered by different phases of the ongoing theta oscillation in the hippocampal local field potential (LFP) using the OscillTrack algorithm.

RESULTS

Stimulation at different target phases could robustly suppress or amplify the theta oscillation, and these effects were significantly larger than those caused by open-loop replay of the same stimulation pattern. Amplification of the theta oscillation could be achieved irrespective of the locomotor speed of the animal, showing that it did not result from a secondary effect of behavioural change.

CONCLUSIONS

Our findings demonstrate that closed-loop fx-DBS is a viable method of modulating the amplitude of hippocampal theta oscillations that could be applied in human devices to provide a constructive intervention with the potential to boost memory circuit function in AD.

Synchronous Theta Networks Characterize Successful Memory Retrieval

Memory retrieval activates regions across the brain, including not only the hippocampus and medial temporal lobe (MTL), but also frontal, parietal, and lateral temporal cortical regions. What remains unclear, however, is how these regions communicate to organize retrieval-specific processing. Here, we elucidate the role of theta (3-8 Hz) synchronization, broadly implicated in memory function, during the spontaneous retrieval of episodic memories. Analyzing a dataset of 382 neurosurgical patients (213 males, 168 females, and 1 unknown) implanted with intracranial electrodes who completed a free-recall task, we find that synchronous networks of theta phase synchrony span the brain in the moments before spontaneous recall, in comparison to periods of deliberation and incorrect recalls. Hubs of the retrieval network, which systematically synchronize with other regions, appear throughout the prefrontal cortex and lateral and medial temporal lobes, as well as other areas. Theta synchrony increases appear more prominently for slow (3 Hz) theta than for fast (8 Hz) theta in the recall-deliberation contrast, but not in the encoding or recall-intrusion contrasts, and theta power and synchrony correlate positively throughout the theta band. These results implicate diffuse brain-wide synchronization of theta rhythms, especially slow theta, in episodic memory retrieval.

Time-Resolved Aperiodic and Oscillatory Dynamics during Human Visual Memory Encoding

Biological neural networks translate sensory information into neural code that is held in memory over long timescales. Theories for how this occurs often posit a functional role of neural oscillations. However, recent advances show that neural oscillations are often confounded with non-oscillatory, aperiodic neural activity. Here we analyze a dataset of intracranial human EEG recordings (N = 13; 10 female) to test the hypothesis that aperiodic activity plays a role in visual memory, independent and distinct from oscillations. By leveraging a new approach to time-resolved parameterization of neural spectral activity, we find event-related changes in both oscillations and aperiodic activity during memory encoding. During memory encoding, aperiodic-adjusted alpha oscillatory power significantly decreases while, simultaneously, aperiodic neural activity "flattens out". These results provide novel evidence for task-related dynamics of both aperiodic and oscillatory activity in human memory, paving the way for future investigations into the unique functional roles of these two neural processes in human cognition.

Theta oscillations between the ventromedial prefrontal cortex and amygdala support dynamic representations of threat and safety

The amygdala exhibits distinct different activity patterns to threat and safety stimuli. Animal studies have demonstrated that the fear (i.e., threat) and extinction (i.e., safety) memory are encoded by the amygdala and its interaction with the ventromedial prefrontal cortex (vmPFC). Recent studies in both animals and humans suggest that the inter-regional interaction between amygdala and vmPFC can be supported by theta oscillations during fear processing. However, the mechanism by which the human vmPFC-amygdala pathway dynamically supports neural representations of the same stimulus remains elusive, as it alternatively reflects threat and safety situations. To investigate this phenomenon, we conducted intracranial EEG recordings in drug-resistant epilepsy patients (n = 8) with implanted depth electrodes who performed a fear conditioning and extinction task. This task was designed with a fixed structure whereby specific CS+ stimulus could be either safe (never paired with US) or threatening (possibly paired with US) based on an implicit rule during fear acquisition. Our findings showed that the stimulus embodying potential threat information was accompanied by increased theta activities in amygdala during both fear acquisition and early extinction. Furthermore, the learning of safety information was associated with enhanced theta-related direction from the vmPFC to the amygdala. This study provided directly electrophysiological evidence supporting the dynamic oscillatory modulation of threat and safety representations in the human amygdala-vmPFC circuit, and suggests that amygdala safety processing depends on theta inputs from the vmPFC in both fear acquisition and extinction.

Distributed Intracranial Activity Underlying Human Decision-making Behavior

Value-based decision-making involves multiple cortical and subcortical brain areas, but the distributed nature of neurophysiological activity underlying economic choices in the human brain remains largely unexplored. Specifically, the nature of the neurophysiological representation of reward-guided choices, as well as whether they are represented in a subset of reward-related regions or in a more distributed fashion, is unknown. Here, we hypothesize that reward choices, as well as choice-related computations (win probability, risk), are primarily represented in high-frequency neural activity reflecting local cortical processing and that they are highly distributed throughout the human brain, engaging multiple brain regions. To test these hypotheses, we used intracranial recordings from multiple areas (including orbitofrontal, lateral prefrontal, parietal, cingulate cortices as well as subcortical regions such as the hippocampus and amygdala) from neurosurgical patients of both sexes playing a decision-making game. We show that high-frequency activity (HFA; ɣ and HFA) represents both individual choice-related computations (e.g., risk, win probability) and choice information with different prevalence and regional representation. Choice-related computations are locally and unevenly present in multiple brain regions, whereas choice information is widely distributed and more prevalent and appears later across all regions examined. These results suggest brain-wide reward processing, with local HFA reflecting the coalescence of choice-related information into a final choice, and shed light on the distributed nature of neural activity underlying economic choices in the human brain.

Oscillatory control over representational geometry of sequence working memory in macaque frontal cortex

To process sequential streams of information, e.g., language, the brain must encode multiple items in sequence working memory (SWM) according to their ordinal relationship. While the geometry of neural states could represent sequential events in the frontal cortex, the control mechanism over these neural states remains unclear. Using high-throughput electrophysiology recording in the macaque frontal cortex, we observed widespread theta responses after each stimulus entry. Crucially, by applying targeted dimensionality reduction to extract task-relevant neural subspaces from both local field potential (LFP) and spike data, we found that theta power transiently encoded each sequentially presented stimulus regardless of its order. At the same time, theta-spike interaction was rank-selectively associated with memory subspaces, thereby potentially supporting the binding of items to appropriate ranks. Furthermore, this putative theta control can generalize to length-variable and error sequences, predicting behavior. Thus, decomposed entry/rank-WM subspaces and theta-spike interactions may underlie the control of SWM.

Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks

The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials (921 channels) in the medial temporal lobe of 16 patients with epilepsy performing a working-memory task for temporal order. During memory maintenance, we observe theta oscillations, preferential firing of single neurons to theta phase and a close relationship between phase of firing and item position. However, the firing order did not match item order. Training recurrent neural networks to perform an analogous task, we also show the generation of theta oscillations, theta phase-dependent firing related to item position and, again, no match between firing and item order. Rather, our results suggest a mechanistic link between phase order, stimulus timing and oscillation frequency. In both biological and artificial neural networks, we provide evidence supporting the role of phase of firing in working-memory processing.

Hydrogen Sulfide (H2S- or H2Sn-Polysulfides) in Synaptic Plasticity: Modulation of NMDA Receptors and Neurotransmitter Release in Learning and Memory

Hydrogen sulfide (H2S) has emerged as a pivotal gaseous transmitter in the central nervous system, influencing synaptic plasticity, learning, and memory by modulating various molecular pathways. This review examines recent evidence regarding how H2S regulates NMDA receptor function and neurotransmitter release in neuronal circuits. By synthesizing findings from animal and cellular models, we investigate the impacts of enzymatic H2S production and exogenous H2S on excitatory synaptic currents, long-term potentiation, and intracellular calcium signaling. Data suggest that H2S interacts directly with NMDA receptor subunits, altering receptor function and modulating neuronal excitability. Simultaneously, H2S promotes the release of neurotransmitters such as glutamate and GABA, shaping synaptic dynamics and plasticity. Furthermore, reports indicate that disruptions in H2S metabolism contribute to cognitive impairments and neurodegenerative disorders, underscoring the potential therapeutic value of targeting H2S-mediated pathways. Although the precise mechanisms of H2S-induced changes in synaptic strength remain elusive, a growing body of evidence positions H2S as a significant regulator of memory formation processes. This review calls for more rigorous exploration into the molecular underpinnings of H2S in synaptic plasticity, paving the way for novel pharmacological interventions in cognitive dysfunction.

Neural Dynamics of Visual Stream Interactions During Memory-Guided Actions Investigated by Intracranial EEG

The dorsal and ventral visual streams have been considered to play distinct roles in visual processing for action: the dorsal stream is assumed to support real-time actions, while the ventral stream facilitates memory-guided actions. However, recent evidence suggests a more integrated function of these streams. We investigated the neural dynamics and functional connectivity between them during memory-guided actions using intracranial EEG. We tracked neural activity in the inferior parietal lobule in the dorsal stream, and the ventral temporal cortex in the ventral stream as well as the hippocampus during a delayed action task involving object identity and location memory. We found increased alpha power in both streams during the delay, indicating their role in maintaining spatial visual information. In addition, we recorded increased alpha power in the hippocampus during the delay, but only when both object identity and location needed to be remembered. We also recorded an increase in theta band phase synchronization between the inferior parietal lobule and ventral temporal cortex and between the inferior parietal lobule and hippocampus during the encoding and delay. Granger causality analysis indicated dynamic and frequency-specific directional interactions among the inferior parietal lobule, ventral temporal cortex, and hippocampus that varied across task phases. Our study provides unique electrophysiological evidence for close interactions between dorsal and ventral streams, supporting an integrated processing model in which both streams contribute to memory-guided actions.

Entrainment by transcranial alternating current stimulation: Insights from models of cortical oscillations and dynamical systems theory

Signature of neuronal oscillations can be found in nearly every brain function. However, abnormal oscillatory activity is linked with several brain disorders. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that can potentially modulate neuronal oscillations and influence behavior both in health and disease. Yet, a complete understanding of how interacting networks of neurons are affected by tACS remains elusive. Entrainment effects by which tACS synchronizes neuronal oscillations is one of the main hypothesized mechanisms, as evidenced in animals and humans. Computational models of cortical oscillations may shed light on the entrainment effects of tACS, but current modeling studies lack specific guidelines to inform experimental investigations. This study addresses the existing gap in understanding the mechanisms of tACS effects on rhythmogenesis within the brain by providing a comprehensive overview of both theoretical and experimental perspectives. We explore the intricate interactions between oscillators and periodic stimulation through the lens of dynamical systems theory. Subsequently, we present a synthesis of experimental findings that demonstrate the effects of tACS on both individual neurons and collective oscillatory patterns in animal models and humans. Our review extends to computational investigations that elucidate the interplay between tACS and neuronal dynamics across diverse cortical network models. To illustrate these concepts, we conclude with a simple oscillatory neuron model, showcasing how fundamental theories of oscillatory behavior derived from dynamical systems, such as phase response of neurons to external perturbation, can account for the entrainment effects observed with tACS. Studies reviewed here render the necessity of integrated experimental and computational approaches for effective neuromodulation by tACS in health and disease.

Neuronal theta oscillation of hippocampal ensemble and memory function

Memory is the ability to acquire and store information following an experience, which can be retrieved by related context exposure. Pioneering studies have demonstrated that sparsely distributed neuronal ensembles or engram cells can serve as neural substrates for storing and recalling memory traces. Many studies of neuronal ensembles have focused on the hippocampus, and increasing evidence has indicated that the neuronal oscillation is closely associated with hippocampal memory functions, including both encoding and retrieval processes. In particular, the theta synchronization of hippocampal ensembles with other brain regions mediates the retrieval of multiple types of memory. The recent progress of theta oscillations in the formation of memory engrams is reviewed, as well as the increased theta power and neurotransmitter regulation on memory function. Detailed information based on an analysis of hippocampal local theta rhythms is presented. Moreover, the hippocampus theta synchronization with the sensory cortex, prefrontal cortex and amygdala, which mediate different types of memory retrieval, are also reviewed. Together, these findings contribute to understanding the important role of hippocampal theta oscillation in the storage and recall of memory traces.

Correlations of pilot trainees' brainwave dynamics with subjective performance evaluations: insights from EEG microstate analysis

Objective

This study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in the subjective flight control evaluations, shedding light on the neurophysiological mechanisms underlying aviation expertise and possible directions for future improvements in pilot training.

Background

Proficiency in aircraft control is crucial for aviation safety and modern aviation where pilots need to maneuver aircraft through an array of situations, ranging from routine takeoffs and landings to complex weather conditions and emergencies. However, the neurophysiological aspects of aviation expertise remain largely unexplored. This research bridges the gap by examining the relationship between pilot trainees' specific brainwave patterns and their subjective evaluations of flight control levels, offering insights into the cognitive underpinnings of pilot skill efficiency and development.

Method

EEG microstate analysis was employed to examine the brainwave dynamics of pilot trainees while they performed aircraft control tasks under a flight simulator-based pilot training process. Trainees' control performance was evaluated by experienced instructors across five dimensions and their EEG data were analyzed to investigate the associations between the parameters of specific microstates with successful aircraft control.

Results

The experimental results revealed significant associations between aircraft control levels and the parameters of distinct EEG microstates. Notably, these associations varied across control dimensions, highlighting the multifaceted nature of control proficiency. Noteworthy correlations included positive correlations between microstate class E and class G with aircraft control, emphasizing the role of attentional processes, perceptual integration, working memory, cognitive flexibility, decision-making, and executive control in aviation expertise. Conversely, negative correlations between microstate class C and class F with aircraft control indicated links between pilot trainees' cognitive control and their control performance on flight tasks.

Conclusion

The findings underscore the multidimensional nature of aircraft control proficiency and emphasize the significance of attentional and cognitive processes in achieving aviation expertise. These neurophysiological markers offer a basis for designing targeted pilot training programs and interventions to enhance trainees' aircraft control skills.

High-Frequency rTMS Improves Visual Working Memory in Patients With aMCI: A Cognitive Neural Mechanism Study

BACKGROUND

Visual working memory (VWM), which is an essential component of higher cognitive processes, declines with age and is associated with the progression from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD). Cognitive impairment, particularly in VWM, is prominent in aMCI and may indicate disease progression. This study investigates the cognitive neural mechanisms responsible for VWM impairment in aMCI, with a focus on identifying the VWM processing stages affected. The study targets the dorsolateral prefrontal cortex (DLPFC) for repetitive transcranial magnetic stimulation (rTMS) to investigate its influence on VWM in aMCI patients. The role of the DLPFC in the top-down control of VWM processing is central to understanding rTMS effects on the stages of information processing in aMCI-related VWM impairments.

METHODS

A 7-day rTMS intervention was performed in 25 aMCI patients and 15 healthy elderly controls to investigate its effects on VWM and cognitive functions. Tasks included VWM change detection, digital symbol transformation, and the Stroop task for attention and executive functions. EEG analyses consisting of ERP, ERSP, and functional connectivity (wPLI) were integrated. The first part of the study addressed the cognitive neural mechanism of VWM impairment in aMCI and differentiated the processing stages using EEG. The second part investigated the effects of rTMS on EEG processing at different VWM stages and revealed cognitive neural mechanisms that improve visual working memory in aMCI.

RESULTS

The results indicated a significant deterioration of VWM tasks in aMCI, especially in accuracy and memory capacity, with prolonged reaction time and increased duration of the Stroop task. In the VWM memory encoding phase, N2pc amplitude, α-oscillation in the parieto-occipital region, and θ-band synchronization in the frontoparietal connectivity decreased. Conversely, rTMS improved N2pc amplitude, α-oscillation, and θ-band synchronization, which correlated with improved frontoparietal connectivity, parieto-occipital α-oscillation, and attentional capacity.

CONCLUSIONS

Patients with aMCI experience significant deterioration in VWM function, particularly during the encoding phase. This deterioration manifests in reduced accuracy and capacity of memory performance, accompanied by a significant decrease in N2pc amplitude, alpha oscillations, and theta-band connectivity in frontoparietal and fronto-occipital brain regions. rTMS proves to be a promising intervention that improves VWM, attention, and executive functions. In particular, it supports attention during target selection by increasing N2pc amplitude during encoding, enhancing alpha oscillations for better suppression of irrelevant information, and increasing synchronization in frontoparietal and occipital functional connectivity, which ultimately improves visual working memory.

Emotional influences on remembering and forgetting explained by frontal and parietal dynamics

Based on item-method directed forgetting (DF) task, 60 participants were recruited to explore the influence of emotion (negative, neutral, and positive) on memory encoding processing, with all data referring to the encoding phase of the task. Behavioral results showed that participants were more successful at remembering negative pictures that needed to be forgotten, with both higher recognition rates and discrimination accuracy (Pr) compared with neutral pictures. In the brain, parietal activities reflected preferential processing during negative picture viewing through enhanced late parietal positive potentials (LPP) relative to neutral ones. In addition, "Remember" (R) instruction evoked a larger parietal P3 component, whereas "Forget" (F) instruction evoked a stronger frontal N2 component, each of which component was significantly associated with the DF effect (i.e., more recognized items of R-cue than that of F-cue), reflecting the fact that inhibitory control and selective rehearsal mechanisms were jointly responsible for the directed forgetting of emotional materials. Finally, we showed the presence of instruction-evoked low-frequency phase synchronization between frontal and parietal regions, and that these synchronization patterns differed between R-cue and F-cue in an emotion-dependent manner. Together, these findings reveal cognitive mechanisms and specific patterns of large-scale phase synchronization underlying active forgetting of emotional memories, deepening our comprehension of the interplay between cognition and emotion.NEW & NOTEWORTHY This study provides experimental evidence that emotional memories, especially negative ones, are more difficult to intentionally forget than neutral memories within the item-method directed forgetting paradigm. It explores the cognitive mechanisms underlying this process, highlighting the role of selective rehearsal and inhibitory control. In addition, it reveals emotion-dependent low-frequency phase synchronization between frontal and parietal regions, offering new insights into active forgetting of emotional memories.

Learning to operate an imagined speech Brain-Computer Interface involves the spatial and frequency tuning of neural activity

Brain-Computer Interfaces (BCI) will revolutionize the way people with severe impairment of speech production can communicate. While current efforts focus on training classifiers on vast amounts of neurophysiological signals to decode imagined speech, much less attention has been given to users' ability to adapt their neural activity to improve BCI-control. To address whether BCI-control improves with training and characterize the underlying neural dynamics, we trained 15 healthy participants to operate a binary BCI system based on electroencephalography (EEG) signals through syllable imagery for five consecutive days. Despite considerable interindividual variability in performance and learning, a significant improvement in BCI-control was globally observed. Using a control experiment, we show that a continuous feedback about the decoded activity is necessary for learning to occur. Performance improvement was associated with a broad EEG power increase in frontal theta activity and focal enhancement in temporal low-gamma activity, showing that learning to operate an imagined-speech BCI involves dynamic changes in neural features at different spectral scales. These findings demonstrate that combining machine and human learning is a successful strategy to enhance BCI controllability.

Simultaneous tACS-fMRI reveals state- and frequency-specific modulation of hippocampal-cortical functional connectivity

Non-invasive indirect hippocampal-targeted stimulation is of broad scientific and clinical interest. Transcranial alternating current stimulation (tACS) is appealing because it allows oscillatory stimulation to study hippocampal theta (3-8 Hz) activity. We found that tACS administered during functional magnetic resonance imaging yielded a frequency-, mental state- and topologically-specific effect of theta stimulation (but not other frequencies) enhancing right (but not left) hippocampal-cortical connectivity during resting blocks but not during task blocks. Control analyses showed that this effect was not due to possible stimulation-induced changes in signal quality or head movement. Our findings are promising for targeted network modulations of deep brain structures for research and clinical intervention.

High-density theta oscillatory-modulated tDCS over the parietal cortex for targeted memory enhancement

OBJECTIVES

Associative memory (AM) declines due to healthy aging as well as in various neurological conditions. Standard transcranial electrical stimulation (tES) protocols show inconclusive facilitatory effects on AM, often lacking function specificity and stimulation focality. We tested the effectiveness of high-density electrode montage delivering anodal theta oscillatory-modulated transcranial direct current stimulation (HD-Theta-otDCS) over the left posterior parietal cortex (PPC), aiming to target AM in a spatially focused and function-specific manner.

METHODS

In a sham-controlled cross-over experiment we explored the differential effects of HD-Theta-otDCS applied during either encoding or the retrieval phases of two AM tasks (Face-Word and Object-Location). The stimulation protocol consisted of an anode over the left PPC (P3) and four surrounding return electrodes (CP1, CP5, PO3, POz) with electrical current oscillating in theta rhythm (5 Hz, 1.5 ± 0.5 mA).

RESULTS

HD-Theta-otDCS stimulation applied during both encoding and retrieval increased AM performance compared to sham control in the Face-Word task. We found no differences between the two active stimulation conditions.

CONCLUSIONS

HD-Theta-otDCS showed to be a promising tool for enhancing AM, regardless of the stimulation timing. The results provide further support for our previous findings with bipolar otDCS and confirm that PPC stimulation can induce behaviorally relevant modulation in the memory-related cortico-subcortical networks.

SIGNIFICANCE

The presented approach is one step forward towards precision brain stimulation for memory neuromodulation. The novelty lies in the combination of increased focality and function-specific current waveform. Positive results set the ground for further research on HD-theta-otDCS effectiveness in clinical populations.

Memory-guided perception is shaped by dynamic two-stage theta- and alpha-mediated retrieval

How does memory influence auditory perception, and what are the underlying mechanisms that drive these interactions? Most empirical studies on the neural correlates of memory-guided perception have used static visual tasks, resulting in a bias in the literature that contrasts with recent research highlighting the dynamic nature of memory retrieval. Here, we used electroencephalography to track the retrieval of auditory associative memories in a cue-target paradigm. Participants (N = 64) listened to real-world soundscapes that were either predictive of an upcoming target tone or nonpredictive. Three key results emerged. First, targets were detected faster when embedded in predictive than in nonpredictive soundscapes (memory-guided perceptual benefit). Second, changes in theta and alpha power differentiated soundscape contexts that were predictive from nonpredictive contexts at two distinct temporal intervals from soundscape onset (early-950 ms peak for theta and alpha, and late-1650 ms peak for alpha only). Third, early theta activity in the left anterior temporal lobe was correlated with memory-guided perceptual benefits. Together, these findings underscore the role of distinct neural processes at different time points during associative retrieval. By emphasizing temporal sensitivity and by isolating cue-related activity, we reveal a two-stage retrieval mechanism that advances our understanding of how memory influences auditory perception.

Experimental Manipulation of the Bilateral Posterior Parietal Cortex Strengthens Associative Memory in Healthy Participants: A Continuous Theta-burst Stimulation

To test whether targeting left and right posterior parietal cortex (PPC) with continuous theta-burst stimulation (cTBS) in healthy adults would strengthen associative memory (AM) performance. This study consisted of two experiments (a behavioral experiment and a formal experiment during each of the two experimental sessions). In Experiment 1, 18 adults (one male, ages = 22.83 ± 3.92 years) were included in the behavioral phase and 18 adults (seven male, ages = 40.11 ± 12.27 years) in the stimulation phase. There were 120 neutral facial images paired with 120 two-character nouns and then divided into six test versions (10 male faces and 10 female faces paired with 20 different nouns were considered as one version). In the behavioral experiment, participants were tested by six-version tests to assess memory materials, and in the formal experiment, participants' face-word AM performance was measured by certified tests based on a cued recall paradigm. Furthermore, 30 adults (seven male, ages = 20.97 ± 1.85 years) and 15 adults (five male, ages = 22.27 ± 1.29 years) participated in Experiment 2, respectively. Stimuli and procedure were the same as in Experiment 1, but the AM test was based on a forced-choice paradigm. Experiment 1 did not yield anticipated outcomes; Experiment 2 showed that cTBS of left and right PPC strengthened the AM performance compared with the control condition. In conclusion, cTBS to left and right PPC improved AM in healthy adults, which provided further experimental evidence for strengthening AM by cTBS.

Medial entorhinal-hippocampal desynchronization parallels the emergence of memory impairment in a mouse model of Alzheimer's disease pathology

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive impairments in episodic and spatial memory, as well as circuit and network-level dysfunction. While functional impairments in medial entorhinal cortex (MEC) and hippocampus (HPC) have been observed in patients and rodent models of AD, it remains unclear how communication between these regions breaks down in disease, and what specific physiological changes are associated with the onset of memory impairment. We used silicon probes to simultaneously record neural activity in MEC and hippocampus before or after the onset of spatial memory impairment in the 3xTg mouse model of AD pathology. We found that reduced hippocampal theta power, reduced MEC-CA1 theta coherence, and altered phase locking of MEC and hippocampal neurons all coincided with the emergence of spatial memory impairment in 3xTg mice. Together, these findings indicate that disrupted temporal coordination of neural activity in the MEC-hippocampal system parallels the emergence of memory impairment in a model of AD pathology.

The role of brain oscillatory activity in processing the informative value of feedback during rule acquisition

Information conveyed through feedback enables individuals to learn new routines and better adapt to their environment. However, the neural mechanisms of rule-related information of feedback have not been fully elucidated. Herein, we quantified the effect of informative value on feedback via a rule induction task (RIT), in which participants were required to find the correct sorting rule based on feedback. To disengage the effects of informative value and valence on feedback in the RIT, a control task was developed in which feedback only involved the valence aspect and no reference for subsequent selections. We measured power and intertrial phase clustering (ITPC) values via EEG to determine the neural mechanisms of rule-related feedback. The results revealed that (1) differences in oscillatory activities between positive and negative feedback were only observed during the control task, and no such effect was found in the RIT task. This finding suggests that the participants paid more attention to rule-related information than to the correctness of feedback during rule learning. (2) The task differences under positive or negative feedback were associated with the delta-theta and alpha-beta bands, and this pattern was similar within the frontal and parietal regions. These findings suggest that the processing of rule-related information of feedback relies on broad frequency bands within the frontoparietal cortex to facilitate rule information integration. In summary, these findings indicate that multiple frequency bands are involved in encoding the informative value aspect of feedback, and individuals rely on this aspect of feedback rather than valence during rule learning.

A minimal model of cognition based on oscillatory and current-based reinforcement processes

Building mathematical models of brains is difficult because of the sheer complexity of the problem. One potential starting point is basal cognition, which gives an abstract representation of a range of organisms without central nervous systems, including fungi, slime moulds and bacteria. We propose one such model, demonstrating how a combination of oscillatory and current-based reinforcement processes can be used to couple resources in an efficient manner, mimicking the way these organisms function. A key ingredient in our model, not found in previous basal cognition models, is that we explicitly model oscillations in the number of particles (i.e. the nutrients, chemical signals or similar, which make up the biological system) and the flow of these particles within the modelled organisms. Using this approach, our model builds efficient solutions, provided the environmental oscillations are sufficiently out of phase. We further demonstrate that amplitude differences can promote efficient solutions and that the system is robust to frequency differences. In the context of these findings, we discuss connections between our model and basal cognition in biological systems and slime moulds, in particular, how oscillations might contribute to self-organized problem-solving by these organisms.

The role of ventral hippocampal-medial prefrontal glutamatergic pathway on the non-affected side in post-stroke cognitive impairment

Elucidate the pathogenesis mechanism of post-stroke cognitive impairment (PSCI) can help to develop precision interventions. In this study, we established a mouse model of PSCI using the photochemical method, and behavioral tests including Y-maze and Novel object recognition task for accessing cognitive impairment were observed at week 2 post-stroke. Besides, synaptic plasticity, theta nerve oscillatory and the activity of glutamatergic neurons related to the ventral hippocampal-medial prefrontal glutamatergic neural pathway in the non-affected hemisphere (contralateral hemisphere to the lesion site) were observed. The result indicated the cognitive function declined at week 2 post-stroke. Synaptic plasticity, theta nerve oscillatory synchronization and the activity of glutamatergic neurons of the ventral hippocampal-medial prefrontal glutamatergic neural pathway in the non-affected hemisphere was down-regulated in the PSCI group compared to those of the SHAM group. Therefore, we concluded that the declined function of the ventral hippocampal-medial prefrontal glutamatergic pathway in the non-affected hemisphere is a biomarker in the occurrence of cognitive dysfunction after stroke.

Closed-loop auditory stimulation targeting alpha and theta oscillations during rapid eye movement sleep induces phase-dependent power and frequency changes

STUDY OBJECTIVES

Alpha and theta oscillations characterize the waking human electroencephalogram (EEG) and can be modulated by closed-loop auditory stimulation (CLAS). These oscillations also occur during rapid eye movement (REM) sleep, but their function here remains elusive. CLAS represents a promising tool to pinpoint how these brain oscillations contribute to brain function in humans. Here we investigate whether CLAS can modulate alpha and theta oscillations during REM sleep in a phase-dependent manner.

METHODS

We recorded high-density EEG during an extended overnight sleep period in 18 healthy young adults. Auditory stimulation was delivered during both phasic and tonic REM sleep in alternating 6-second ON and 6-second OFF windows. During the ON windows, stimuli were phase-locked to four orthogonal phases of ongoing alpha or theta oscillations detected in a frontal electrode.

RESULTS

The phases of ongoing alpha and theta oscillations were targeted with high accuracy during REM sleep. Alpha and theta CLAS induced phase-dependent changes in power and frequency at the target location. Frequency-specific effects were observed for alpha trough (speeding up) and rising (slowing down) and theta trough (speeding up) conditions. CLAS-induced phase-dependent changes were observed during both REM sleep substages, even though auditory evoked potentials were very much reduced in phasic compared to tonic REM sleep.

CONCLUSIONS

This study provides evidence that faster REM sleep rhythms can be modulated by CLAS in a phase-dependent manner. This offers a new approach to investigating how modulation of REM sleep oscillations affects the contribution of this vigilance state to brain function.

The neural dynamics of familiar face recognition

Humans are highly efficient at recognising familiar faces. However, previous EEG/ERP research has given a partial and fragmented account of the neural basis of this remarkable ability. We argue that this is related to insufficient consideration of fundamental characteristics of familiar face recognition. These include image-independence (recognition across different pictures), levels of familiarity (familiar faces vary hugely in duration and intensity of our exposure to them), automaticity (we cannot voluntarily withhold from recognising a familiar face), and domain-selectivity (the degree to which face familiarity effects are selective). We review recent EEG/ERP work, combining uni- and multivariate methods, that has systematically targeted these shortcomings. We present a theoretical account of familiar face recognition, dividing it into early visual, domain-sensitive and domain-general phases, and integrating image-independence and levels of familiarity. Our account incorporates classic and more recent concepts, such as multi-dimensional face representation and course-to-fine processing. While several questions remain to be addressed, this new account represents a major step forward in our understanding of the neurophysiological basis of familiar face recognition.

Motor-related oscillations reveal the involvement of sensorimotor processes during recognition memory

Certain object properties may render an item as more memorable than others. One such property is manipulability, or the extent to which an object can be interacted with using our hands. This study sought to determine if the manipulability of an item modulates memory task performance on both a behavioural and neural level. We recorded electroencephalography (EEG) from a large sample of right-handed individuals (N = 53) during a visual item recognition memory task. The task contained stimuli of both high and low manipulability. Analysis focused on activity in the theta rhythm (3.5-7 Hz), which has been implicated in sensorimotor integration, and the mu rhythm (8-14 Hz), the primary oscillation associated with sensorimotor related behaviours. At both encoding and retrieval, theta oscillations were greater over the left motor region for high manipulability stimuli, suggesting that an item's sensorimotor properties are assessed immediately upon presentation. Manipulability did not affect activity in the mu rhythm. However, mu oscillations over the left motor region were lower during the retrieval of old versus new items and response time was faster for old items, aligning with the cortical reinstatement hypothesis. These results collectively reveal an association between motor oscillations and memory processes, highlight the involvement of sensorimotor processing at both encoding and retrieval.

The brain's duck test in phantom percepts: Multisensory congruence in neuropathic pain and tinnitus

Chronic neuropathic pain and chronic tinnitus have been likened to phantom percepts, in which a complete or partial sensory deafferentation results in a filling in of the missing information derived from memory. 150 participants, 50 with tinnitus, 50 with chronic pain and 50 healthy controls underwent a resting state EEG. Source localized current density is recorded from all the sensory cortices (olfactory, gustatory, somatosensory, auditory, vestibular, visual) as well as the parahippocampal area. Functional connectivity by means of lagged phase synchronization is also computed between these regions of interest. Pain and tinnitus are associated with gamma band activity, reflecting prediction errors, in all sensory cortices except the olfactory and gustatory cortex. Functional connectivity identifies theta frequency connectivity between each of the sensory cortices except the chemical senses to the parahippocampus, but not between the individual sensory cortices. When one sensory domain is deprived, the other senses may provide the parahippocampal 'contextual' area with the most likely sound or somatosensory sensation to fill in the gap, applying an abductive 'duck test' approach, i.e., based on stored multisensory congruence. This novel concept paves the way to develop novel treatments for pain and tinnitus, using multisensory (i.e. visual, vestibular, somatosensory, auditory) modulation with or without associated parahippocampal targeting.

Advances in non-invasive brain stimulation: enhancing sports performance function and insights into exercise science

The cerebral cortex, as the pinnacle of human complexity, poses formidable challenges to contemporary neuroscience. Recent advancements in non-invasive brain stimulation have been pivotal in enhancing human locomotor functions, a burgeoning area of interest in exercise science. Techniques such as transcranial direct current stimulation, transcranial alternating current stimulation, transcranial random noise stimulation, and transcranial magnetic stimulation are widely recognized for their neuromodulator capabilities. Despite their broad applications, these methods are not without limitations, notably in spatial and temporal resolution and their inability to target deep brain structures effectively. The advent of innovative non-invasive brain stimulation modalities, including transcranial focused ultrasound stimulation and temporal interference stimulation technology, heralds a new era in neuromodulation. These approaches offer superior spatial and temporal precision, promising to elevate athletic performance, accelerate sport science research, and enhance recovery from sports-related injuries and neurological conditions. This comprehensive review delves into the principles, applications, and future prospects of non-invasive brain stimulation in the realm of exercise science. By elucidating the mechanisms of action and potential benefits, this study aims to arm researchers with the tools necessary to modulate targeted brain regions, thereby deepening our understanding of the intricate interplay between brain function and human behavior.

Disrupting stroke-induced GAT-1-syntaxin1A interaction promotes functional recovery after stroke

Although stroke is a frequent cause of permanent disability, our ability to promote stroke recovery is limited. Here, we design a small-molecule stroke recovery promoting agent that works by dissociating γ-aminobutyric acid (GABA) transporter 1 (GAT-1) from syntaxin1A (Synt1A), a soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein. Stroke induces an increase in GAT-1-Synt1A interaction in the subacute phase, a critical period for functional recovery. Uncoupling GAT-1-Synt1A reverses stroke-induced GAT-1 dysfunction and cortical excitability decline and enhances synaptic GABAergic inhibition and consequently cortical oscillations and network plasticity by facilitating the assembly of the SNARE complex at the synapse. Based on the molecular mechanism of GAT-1 binding to Synt1A, we design GAT-1-Synt1A blockers. Among them, ZLQ-3 exhibits the greatest potency. Intranasal use of ZLQ-3-1, a glycosylation product of ZLQ-3, substantially lessens impairments of sensorimotor and cognitive functions in rodent models. This compound, or its analogs, may serve as a promoting agent for stroke recovery.

The development of aperiodic neural activity in the human brain

The neurophysiological mechanisms supporting brain maturation are fundamental to attention and memory capacity across the lifespan. Human brain regions develop at different rates, with many regions developing into the third and fourth decades of life. Here, in this preregistered study (https://osf.io/gsru7), we analyzed intracranial EEG (iEEG) recordings from widespread brain regions in a large developmental cohort. Using task-based (i.e., attention to-be-remembered visual stimuli) and task-free (resting-state) data from 101 children and adults (5.93 - 54.00 years, 63 males; n electrodes = 5691), we mapped aperiodic (1/ƒ-like) activity, a proxy of excitation:inhibition (E:I) balance with steeper slopes indexing inhibition and flatter slopes indexing excitation. We reveal that aperiodic slopes flatten with age into young adulthood in both association and sensorimotor cortices, challenging models of early sensorimotor development based on brain structure. In prefrontal cortex (PFC), attentional state modulated age effects, revealing steeper task-based than task-free slopes in adults and the opposite in children, consistent with the development of cognitive control. Age-related differences in task-based slopes also explained age-related gains in memory performance, linking the development of PFC cognitive control to the development of memory. Last, with additional structural imaging measures, we reveal that age-related differences in gray matter volume are differentially associated with aperiodic slopes in association and sensorimotor cortices. Our findings establish developmental trajectories of aperiodic activity in localized brain regions and illuminate the development of PFC inhibitory control during adolescence in the development of attention and memory.

Test-Retest Reliability of EEG Aperiodic Components in Resting and Mental Task States

Aperiodic activity is derived from the electroencephalography (EEG) power spectrum and reflects changes in the slope and shifts of the broadband spectrum. Studies have shown inconsistent test-retest reliability of the aperiodic components. This study systematically measured how the test-retest reliability of the aperiodic components was affected by data duration (1, 2, 3, 4, and 5 min), states (resting with eyes closed, resting with eyes open, performing mental arithmetic, recalling the events of the day, and mentally singing songs), and methods (the Fitting Oscillations and One-Over-F (FOOOF) and Linear Mixed-Effects Regression (LMER)) at both short (90-min) and long (one-month) intervals. The results showed that aperiodic components had fair, good, or excellent test-retest reliability (ranging from 0.53 to 0.91) at both short and long intervals. It is recommended that better reliability of the aperiodic components be obtained using data durations longer than 3 min, the resting state with eyes closed, the mental arithmetic task state, and the LMER method.

Beta-to-Theta Entropy Ratio of EEG in Aging, Frontotemporal Dementia, and Alzheimer's Dementia

BACKGROUND

Aging, frontotemporal dementia (FTD), and Alzheimer's dementia (AD) manifest electroencephalography (EEG) alterations, particularly in the beta-to-theta power ratio derived from linear power spectral density (PSD). Given the brain's nonlinear nature, the EEG nonlinear features could provide valuable physiological indicators of aging and cognitive impairment. Multiscale dispersion entropy (MDE) serves as a sensitive nonlinear metric for assessing the information content in EEGs across biologically relevant time scales.

OBJECTIVE

To compare the MDE-derived beta-to-theta entropy ratio with its PSD-based counterpart to detect differences between healthy young and elderly individuals and between different dementia subtypes.

METHODS

Scalp EEG recordings were obtained from two datasets: 1) Aging dataset: 133 healthy young and 65 healthy older adult individuals; and 2) Dementia dataset: 29 age-matched healthy controls (HC), 23 FTD, and 36 AD participants. The beta-to-theta ratios based on MDE vs. PSD were analyzed for both datasets. Finally, the relationships between cognitive performance and the beta-to-theta ratios were explored in HC, FTD, and AD.

RESULTS

In the Aging dataset, older adults had significantly higher beta-to-theta entropy ratios than young individuals. In the Dementia dataset, this ratio outperformed the beta-to-theta PSD approach in distinguishing between HC, FTD, and AD. The AD participants had a significantly lower beta-to-theta entropy ratio than FTD, especially in the temporal region, unlike its corresponding PSD-based ratio. The beta-to-theta entropy ratio correlated significantly with cognitive performance.

CONCLUSION

Our study introduces the beta-to-theta entropy ratio using nonlinear MDE for EEG analysis, highlighting its potential as a sensitive biomarker for aging and cognitive impairment.

Differential modulations of theta and beta oscillations by audiovisual congruency in letter-speech sound integration

The integration of visual letters and speech sounds is a crucial part of learning to read. Previous studies investigating this integration have revealed a modulation by audiovisual (AV) congruency, commonly known as the congruency effect. To investigate the cortical oscillations of the congruency effects across different oscillatory frequency bands, we conducted a Japanese priming task in which a visual letter was followed by a speech sound. We analyzed the power and phase properties of oscillatory activities in the theta and beta bands between congruent and incongruent letter-speech sound (L-SS) pairs. Our results revealed stronger theta-band (5-7 Hz) power in the congruent condition and cross-modal phase resetting within the auditory cortex, accompanied by enhanced inter-trial phase coherence (ITPC) in the auditory-related areas in response to the congruent condition. The observed congruency effect of theta-band power may reflect increased neural activities in the left auditory region during L-SS integration. Additionally, theta ITPC findings suggest that visual letters amplify neuronal responses to the following corresponding auditory stimulus, which may reflect the differential cross-modal influences in the primary auditory cortex. In contrast, decreased beta-band (20-35 Hz) oscillatory power was observed in the right centroparietal regions for the congruent condition. The reduced beta power seems to be unrelated to the processing of AV integration, but may be interpreted as the brain response to predicting auditory sounds during language processing. Our data provide valuable insights by indicating that oscillations in different frequency bands contribute to the disparate aspects of L-SS integration.

[Analysis of nerve excitability in the dentate gyrus of the hippocampus in cerebral ischaemia-reperfusion mice]

Ischemic stroke often leads to cognitive dysfunction, which delays the recovery process of patients. However, its pathogenesis is not yet clear. In this study, the cerebral ischemia-reperfusion model was built as the experimental object, and the hippocampal dentate gyrus (DG) was the target brain area. TTC staining was used to evaluate the degree of cerebral infarction, and nerve cell membrane potentials and local field potentials (LFPs) signals were collected to explore the mechanism of cognitive impairment in ischemia-reperfusion mice. The results showed that the infarcted area on the right side of the brain of the mice in the model group was white. The resting membrane potential, the number of action potential discharges, the post-hyperpolarization potential and the maximum ascending slope of the hippocampal DG nerve cells in the model mice were significantly lower than those in the control group ( P < 0.01); the peak time, half-wave width, threshold and maximum descending slope of the action potential were significantly higher than those in the control group ( P < 0.01). The time-frequency energy values of LFPs signals in the θ and γ bands of mice in the ischemia and reperfusion groups were significantly reduced ( P < 0.01), and the time-frequency energy values in the reperfusion group were increased compared with the ischemia group ( P < 0.01). The signal complexity of LFPs in the ischemia and reperfusion group was significantly reduced ( P < 0.05), and the signal complexity in the reperfusion group was increased compared with the ischemia group ( P < 0.05). In summary, cerebral ischemia-reperfusion reduced the excitability of nerve cells in the DG area of the mouse hippocampus; cerebral ischemia reduced the discharge activity and signal complexity of nerve cells, and the electrophysiological indicators recovered after reperfusion, but it failed to reach the healthy state during the experiment period.

Monitoring pilot trainees' cognitive control under a simulator-based training process with EEG microstate analysis

The objective of pilot training is to equip trainees with the knowledge, judgment, and skills to maintain control of an aircraft and respond to critical flight tasks. The present research aims to investigate changes in trainees' cognitive control levels during a pilot training process while they underwent basic flight maneuvers. EEG microstate analysis was applied together with spectral power features to quantitatively monitor trainees' cognitive control under varied flight tasks during different training sessions on a flight simulator. Not only could EEG data provide an objective measure of cognitive control to complement the current subjective assessments, but the application of EEG microstate analysis is particularly well-suited for capturing rapid dynamic changes in cognitive states that may happen under complex human activities in conducting flight maneuvers. Comparisons were conducted between two types of tasks and across different training stages to monitor how pilot trainees' cognitive control responds to varied flight task types and training stages. The present research provides insights into the changes in trainees' cognitive control during a pilot training process and highlights the potential of EEG microstate analysis for monitoring cognitive control.

Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people

The relationship between working memory (WM) and neuronal oscillations can be studied in detail using brain stimulation techniques, which provide a method for modulating these oscillations and thus influencing WM. The endogenous coupling between the amplitude of gamma oscillations and the phase of theta oscillations is crucial for cognitive control. Theta/gamma peak-coupled transcranial alternating current stimulation (TGCp-tACS) can modulate this coupling and thus influence WM performance. This study investigated the effects of TGCp-tACS on WM in older adults and compared their responses with those of younger participants from our previous work who underwent the same experimental design. Twenty-eight older subjects underwent both TGCp-tACS and sham stimulation sessions at least 72 h apart. Resting-state electroencephalography (EEG) was recorded before and after the interventions, and a WM task battery with five different WM tasks was performed during the interventions to assess various WM components. Outcomes measured included WM task performance (e.g., accuracy, reaction time (RT)) and changes in power spectral density (PSD) in different frequency bands. TGCp-tACS significantly decreased accuracy and RT on the 10- and 14-point Sternberg tasks and increased RT on the Digit Symbol Substitution Test in older adults. In contrast, younger participants showed a significant increase in accuracy only on the 14-item Sternberg task. Electrophysiological analysis revealed a decrease in delta and theta PSD and an increase in high gamma PSD in both younger and older participants after verum stimulation. In conclusion, theta-gamma coupling is essential for WM and modulation of this coupling affects WM performance. The effects of TGCp-tACS on WM vary with age due to natural brain changes. To better support older adults, the study suggests several strategies to improve cognitive function, including: Adjusting stimulation parameters, applying stimulation to two sites, conducting multiple sessions, and using brain imaging techniques for precise targeting.

Cortical activation among young adults during mobility in an indoor real-world environment: A mobile EEG approach

Human mobility requires neurocognitive inputs to safely navigate the environment. Previous research has examined neural processes that underly walking using mobile neuroimaging technologies, yet few studies have incorporated true real-world methods without a specific task imposed on participants (e.g., dual-task, motor demands). The present study included 40 young adults (M = 22.60, SD = 2.63, 24 female) and utilized mobile electroencephalography (EEG) to examine and compare theta, alpha, and beta frequency band power (μV2) during sitting and walking in laboratory and real-world environments. EEG data was recorded using the Muse S brain sensing headband, a portable system equipped with four electrodes (two frontal, two temporal) and one reference sensor. Qualitative data detailing the thoughts of each participant were collected after each condition. For the quantitative data, a 2 × 2 repeated measures ANOVA with within subject factors of environment and mobility was conducted with full participant datasets (n = 17, M = 22.59, SD = 2.97, 10 female). Thematic analysis was performed on the qualitative data (n = 40). Our findings support that mobility and environment may modulate neural activity, as we observed increased brain activation for walking compared to sitting, and for real-world walking compared to laboratory walking. We identified five qualitative themes across the four conditions 1) physical sensations and bodily awareness, 2) responsibilities and planning, 3) environmental awareness, 4) mobility, and 5) spotlight effect. Our study highlights the importance and potential for real-world methods to supplement standard research practices to increase the ecological validity of studies conducted in the fields of neuroscience and kinesiology.

Motifs of human hippocampal and cortical high frequency oscillations structure processing and memory of naturalistic stimuli

The discrete events of our narrative experience are organized by the neural substrate that underlies episodic memory. This narrative process is segmented into discrete units by event boundaries. This permits a replay process that acts to consolidate each event into a narrative memory. High frequency oscillations (HFOs) are a potential mechanism for synchronizing neural activity during these processes. Here, we use intracranial recordings from participants viewing and freely recalling a naturalistic stimulus. We show that hippocampal HFOs increase following event boundaries and that coincident hippocampal-cortical HFOs (co-HFOs) occur in cortical regions previously shown to underlie event segmentation (inferior parietal, precuneus, lateral occipital, inferior frontal cortices). We also show that event-specific patterns of co-HFOs that occur during event viewing re-occur following the subsequent three event boundaries (in decaying fashion) and also during recall. This is consistent with models that support replay as a mechanism for memory consolidation. Hence, HFOs may coordinate activity across brain regions serving widespread event segmentation, encode naturalistic memory, and bind representations to assemble memory of a coherent, continuous experience.

Challenges and Approaches in the Study of Neural Entrainment

When exposed to rhythmic stimulation, the human brain displays rhythmic activity across sensory modalities and regions. Given the ubiquity of this phenomenon, how sensory rhythms are transformed into neural rhythms remains surprisingly inconclusive. An influential model posits that endogenous oscillations entrain to external rhythms, thereby encoding environmental dynamics and shaping perception. However, research on neural entrainment faces multiple challenges, from ambiguous definitions to methodological difficulties when endogenous oscillations need to be identified and disentangled from other stimulus-related mechanisms that can lead to similar phase-locked responses. Yet, recent years have seen novel approaches to overcome these challenges, including computational modeling, insights from dynamical systems theory, sophisticated stimulus designs, and study of neuropsychological impairments. This review outlines key challenges in neural entrainment research, delineates state-of-the-art approaches, and integrates findings from human and animal neurophysiology to provide a broad perspective on the usefulness, validity, and constraints of oscillatory models in brain-environment interaction.

Differential online and offline effects of theta-tACS on memory encoding and retrieval

Theta oscillations support memory formation, but their exact contribution to the communication between prefrontal cortex (PFC) and the hippocampus is unknown. We tested the functional relevance of theta oscillations as a communication link between both areas for memory formation using transcranial alternating current stimulation (tACS). Healthy, young participants learned two lists of Dutch-German word pairs and retrieved them immediately and with a 30-min delay. In the encoding group (N = 30), tACS was applied during the encoding of list 1. List 2 was used to test stimulation aftereffects. In the retrieval group (N = 23), we stimulated during the delayed recall. In both groups, we applied tACS bilaterally at prefrontal and tempo-parietal sites, using either individualized theta frequency or 15 Hz (as control), according to a within-subject design. Stimulation with theta-tACS did not alter overall learning performance. An exploratory analysis revealed that immediate recall improved when word-pairs were learned after theta-tACS (list 2). Applying theta-tACS during retrieval had detrimental effects on memory. No changes in the power of the respective frequency bands were observed. Our results do not support the notion that impacting the communication between PFC and the hippocampus during a task by bilateral tACS improves memory. However, we do find evidence that direct stimulation had a trend for negatively interfering effects during immediate and delayed recall. Hints for beneficial effects on memory only occurred with aftereffects of the stimulation. Future studies need to further examine the effects during and after stimulation on memory formation.

Why does invasive brain stimulation sometimes improve memory and sometimes impair it?

Invasive brain stimulation is used to treat individuals with episodic memory loss; however, studies to date report both enhancement and impairment of memory. This Essay discusses the sources of this variability, and suggests a path towards developing customized stimulation protocols for more consistent memory enhancement.

Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models

Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigation tasks. Frontal theta oscillations are thought to play an important role in spatial navigation and memory. Electroencephalography (EEG) datasets are very complex, making any changes in the neural signal related to behaviour difficult to interpret. However, multiple analytical methods are available to examine complex data structures, especially machine learning-based techniques. These methods have shown high classification performance, and their combination with feature engineering enhances their capability. This paper proposes using hidden Markov and linear mixed effects models to extract features from EEG data. Based on the engineered features obtained from frontal theta EEG data during a spatial navigation task in two key trials (first, last) and between two conditions (learner and non-learner), we analysed the performance of six machine learning methods on classifying learner and non-learner participants. We also analysed how different standardisation methods used to pre-process the EEG data contribute to classification performance. We compared the classification performance of each trial with data gathered from the same subjects, including solely coordinate-based features, such as idle time and average speed. We found that more machine learning methods perform better classification using coordinate-based data. However, only deep neural networks achieved an area under the ROC curve higher than 80% using the theta EEG data alone. Our findings suggest that standardising the theta EEG data and using deep neural networks enhances the classification of learner and non-learner subjects in a spatial learning task.

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.

How is social dominance related to our short-term memory? An EEG/ERP investigation of encoding and retrieval during a working memory task

Social hierarchies exist in all societies and impact cognitive functions, brain mechanisms, social interactions, and behaviors. High status individuals often exhibit enhanced working memory (WM) performance compared to lower status individuals. This study examined whether individual differences in social dominance, as a predictor of future status, relate to WM abilities. Five hundred and twenty-five students completed the Personality Research Form dominance subscale questionnaire. From this sample, students with the highest and lowest scores were invited to participate in the study. Sixty-four participants volunteered to take part and were subsequently categorized into high- and low-dominance groups based on their dominance subscale questionnaire (PRF_d) scores. They performed a Sternberg WM task with set sizes of 1, 4, or 7 letters while their EEG was recorded. Event-related potential (ERP) and power spectral analysis revealed significantly reduced P3b amplitude and higher event-related synchronization (ERS) of theta and beta during encoding and retrieval phases in the high-than low-dominance group. Despite these neural processing differences, behavioral performance was equivalent between groups, potentially reflecting comparable cognitive load demands of the task across dominance levels. Further, there were similar P3b patterns for each set-size within groups. These findings provide initial evidence that individual differences in social dominance trait correlate with WM functioning, as indexed by neural processing efficiency during WM performance.