Phase-dependent amplification of working memory content and performance

Real-time TMS-EEG for brain state-controlled research and precision treatment: a narrative review and guide

Transcranial magnetic stimulation (TMS) modulates neuronal activity, but the efficacy of an open-loop approach is limited due to the brain state's dynamic nature. Real-time integration with electroencephalography (EEG) increases experimental reliability and offers personalized neuromodulation therapy by using immediate brain states as biomarkers. Here, we review brain state-controlled TMS-EEG studies since the first publication several years ago. A summary of experiments on the sensorimotor mu rhythm (8-13 Hz) shows increased cortical excitability due to TMS pulse at the trough and decreased excitability at the peak of the oscillation. Pre-TMS pulse mu power also affects excitability. Further, there is emerging evidence that the oscillation phase in theta and beta frequency bands modulates neural excitability. Here, we provide a guide for real-time TMS-EEG application and discuss experimental and technical considerations. We consider the effects of hardware choice, signal quality, spatial and temporal filtering, and neural characteristics of the targeted brain oscillation. Finally, we speculate on how closed-loop TMS-EEG potentially could improve the treatment of neurological and mental disorders such as depression, Alzheimer's, Parkinson's, schizophrenia, and stroke.

Working memory enhancement using real-time phase-tuned transcranial alternating current stimulation

BACKGROUND

Prior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8-14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS has not been feasible so far due to stimulation artifacts preventing continuous phase tracking.

OBJECTIVES AND HYPOTHESIS

We aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag.

METHODS

We developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead.

RESULTS

WM accuracy improved in a phase lag dependent manner (p = 0.0350) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330° phase lag between tACS and ongoing alpha oscillations (p = 0.00273, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p = 0.0248) and phase (p = 0.0270) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation.

CONCLUSIONS

Our results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications.

Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations.

Transcranial Ultrasound Stimulation Improves Memory Performance of Parkinsonian Mice

Cognitive impairment is one of the most common non-motor symptoms of Parkinson's disease (PD). Previous studies have demonstrated that low-intensity transcranial ultrasound stimulation can significantly suppress the motor symptoms of PD. However, whether ultrasound stimulation can improve cognitive ability in PD and the related neural oscillation mechanism remain unclear to date. To evaluate the effect of ultrasound stimulation on memory ability in PD and explore its neural oscillation mechanism. Ultrasonography was used for 7-day stimulation of the CA1 in transgenic mice with PD. The working memory ability of the PD mice was then tested using novel object discrimination, and the local field potential and spikes in the mice CA1 were recorded at the same time as in the behavioral test. We found that ultrasound stimulation of the PD mice CA1 for 4 days: 1) significantly increased their learning and memory ability, although the learning and memory ability on the 7th day after the stimulation stopped was not significantly different from that before stimulation (P>0.05); 2) significantly increased the relative power of theta, low gamma, and high gamma frequency bands of the local field potential, and the phase amplitude coupling strength between theta and low gamma and between theta and high gamma; and 3) modulated the phase-locking angle between the spike of interneuron and theta wave to a 180°-360° rise cycle. Transcranial ultrasound stimulation can improve the learning and memory abilities of PD mice, and evoking neural oscillations in the CA1 is the potential mechanism.

Safety, tolerability, and efficacy estimate of evoked gamma oscillation in mild to moderate Alzheimer's disease

Background

Alzheimer's Disease (AD) is a multifactorial, progressive neurodegenerative disease that disrupts synaptic and neuronal activity and network oscillations. It is characterized by neuronal loss, brain atrophy and a decline in cognitive and functional abilities. Cognito's Evoked Gamma Therapy System provides an innovative approach for AD by inducing EEG-verified gamma oscillations through sensory stimulation. Prior research has shown promising disease-modifying effects in experimental AD models. The present study (NCT03556280: OVERTURE) evaluated the feasibly, safety and efficacy of evoked gamma oscillation treatment using Cognito's medical device (CogTx-001) in participants with mild to moderate AD.

Methods

The present study was a randomized, double blind, sham-controlled, 6-months clinical trial in participants with mild to moderate AD. The trial enrolled 76 participants, aged 50 or older, who met the clinical criteria for AD with baseline MMSE scores between 14 and 26. Participants were randomly assigned 2:1 to receive self-administered daily, one-hour, therapy, evoking EEG-verified gamma oscillations or sham treatment. The CogTx-001 device was use at home with the help of a care partner, over 6 months. The primary outcome measures were safety, evaluated by physical and neurological exams and monthly assessments of adverse events (AEs) and MRI, and tolerability, measured by device use. Although the trial was not statistically powered to evaluate potential efficacy outcomes, primary and secondary clinical outcome measures included several cognitive and functional endpoints.

Results

Total AEs were similar between groups, there were no unexpected serious treatment related AEs, and no serious treatment-emergent AEs that led to study discontinuation. MRI did not show Amyloid-Related Imaging Abnormalities (ARIA) in any study participant. High adherence rates (85-90%) were observed in sham and treatment participants. There was no statistical separation between active and sham arm participants in primary outcome measure of MADCOMS or secondary outcome measure of CDR-SB or ADAS-Cog14. However, some secondary outcome measures including ADCS-ADL, MMSE, and MRI whole brain volume demonstrated reduced progression in active compared to sham treated participants, that achieved nominal significance.

Conclusion

Our results demonstrate that 1-h daily treatment with Cognito's Evoked Gamma Therapy System (CogTx-001) was safe and well-tolerated and demonstrated potential clinical benefits in mild to moderate AD.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03556280.

Electrophysiological hallmarks for event relations and event roles in working memory

The ability to maintain events (i.e., interactions between/among objects) in working memory is crucial for our everyday cognition, yet the format of this representation is poorly understood. The current ERP study was designed to answer two questions: How is maintaining events (e.g., the tiger hit the lion) neurally different from maintaining item coordinations (e.g., the tiger and the lion)? That is, how is the event relation (present in events but not coordinations) represented? And how is the agent, or initiator of the event encoded differently from the patient, or receiver of the event during maintenance? We used a novel picture-sentence match-across-delay approach in which the working memory representation was "pinged" during the delay, replicated across two ERP experiments with Chinese and English materials. We found that maintenance of events elicited a long-lasting late sustained difference in posterior-occipital electrodes relative to non-events. This effect resembled the negative slow wave reported in previous studies of working memory, suggesting that the maintenance of events in working memory may impose a higher cost compared to coordinations. Although we did not observe significant ERP differences associated with pinging the agent vs. the patient during the delay, we did find that the ping appeared to dampen the ongoing sustained difference, suggesting a shift from sustained activity to activity silent mechanisms. These results suggest a new method by which ERPs can be used to elucidate the format of neural representation for events in working memory.

Phase separation of competing memories along the human hippocampal theta rhythm

Competition between overlapping memories is considered one of the major causes of forgetting, and it is still unknown how the human brain resolves such mnemonic conflict. In the present magnetoencephalography (MEG) study, we empirically tested a computational model that leverages an oscillating inhibition algorithm to minimise overlap between memories. We used a proactive interference task, where a reminder word could be associated with either a single image (non-competitive condition) or two competing images, and participants were asked to always recall the most recently learned word-image association. Time-resolved pattern classifiers were trained to detect the reactivated content of target and competitor memories from MEG sensor patterns, and the timing of these neural reactivations was analysed relative to the phase of the dominant hippocampal 3 Hz theta oscillation. In line with our pre-registered hypotheses, target and competitor reactivations locked to different phases of the hippocampal theta rhythm after several repeated recalls. Participants who behaviourally experienced lower levels of interference also showed larger phase separation between the two overlapping memories. The findings provide evidence that the temporal segregation of memories, orchestrated by slow oscillations, plays a functional role in resolving mnemonic competition by separating and prioritising relevant memories under conditions of high interference.

The brain time toolbox, a software library to retune electrophysiology data to brain dynamics

Human thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue that this goal is impeded by the time format of our data-clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up and undergo abrupt changes, introducing a disharmony between the brain's internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the data's new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific enquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.

Voluntary Motor Command Release Coincides with Restricted Sensorimotor Beta Rhythm Phases

Sensory perception and memory are enhanced during restricted phases of ongoing brain rhythms, but whether voluntary movement is constrained by brain rhythm phase is not known. Voluntary movement requires motor commands to be released from motor cortex (M1) and transmitted to spinal motoneurons and effector muscles. Here, we tested the hypothesis that motor commands are preferentially released from M1 during circumscribed phases of ongoing sensorimotor rhythms. Healthy humans of both sexes performed a self-paced finger movement task during electroencephalography (EEG) and electromyography (EMG) recordings. We first estimated the time of motor command release preceding each finger movement by subtracting individually measured corticomuscular transmission latencies from EMG-determined movement onset times. Then, we determined the phase of ipsilateral and contralateral sensorimotor mu (8-12 Hz) and beta (13-35 Hz) rhythms during release of each motor command. We report that motor commands were most often released between 120 and 140° along the contralateral beta cycle but were released uniformly along the contralateral mu cycle. Motor commands were also released uniformly along ipsilateral mu and beta cycles. Results demonstrate that motor command release coincides with restricted phases of the contralateral sensorimotor beta rhythm, suggesting that sensorimotor beta rhythm phase may sculpt the timing of voluntary human movement.SIGNIFICANCE STATEMENT Perceptual and cognitive function is optimal during specific brain rhythm phases. Although brain rhythm phase influences motor cortical neuronal activity and communication between the motor cortex and spinal cord, its role in voluntary movement is poorly understood. Here, we show that the motor commands needed to produce voluntary movements are preferentially released from the motor cortex during contralateral sensorimotor beta rhythm phases. Our findings are consistent with the notion that sensorimotor rhythm phase influences the timing of voluntary human movement.

Neural dynamics differentially encode phrases and sentences during spoken language comprehension

Human language stands out in the natural world as a biological signal that uses a structured system to combine the meanings of small linguistic units (e.g., words) into larger constituents (e.g., phrases and sentences). However, the physical dynamics of speech (or sign) do not stand in a one-to-one relationship with the meanings listeners perceive. Instead, listeners infer meaning based on their knowledge of the language. The neural readouts of the perceptual and cognitive processes underlying these inferences are still poorly understood. In the present study, we used scalp electroencephalography (EEG) to compare the neural response to phrases (e.g., the red vase) and sentences (e.g., the vase is red), which were close in semantic meaning and had been synthesized to be physically indistinguishable. Differences in structure were well captured in the reorganization of neural phase responses in delta (approximately <2 Hz) and theta bands (approximately 2 to 7 Hz),and in power and power connectivity changes in the alpha band (approximately 7.5 to 13.5 Hz). Consistent with predictions from a computational model, sentences showed more power, more power connectivity, and more phase synchronization than phrases did. Theta-gamma phase-amplitude coupling occurred, but did not differ between the syntactic structures. Spectral-temporal response function (STRF) modeling revealed different encoding states for phrases and sentences, over and above the acoustically driven neural response. Our findings provide a comprehensive description of how the brain encodes and separates linguistic structures in the dynamics of neural responses. They imply that phase synchronization and strength of connectivity are readouts for the constituent structure of language. The results provide a novel basis for future neurophysiological research on linguistic structure representation in the brain, and, together with our simulations, support time-based binding as a mechanism of structure encoding in neural dynamics.

Breaking the boundaries of interacting with the human brain using adaptive closed-loop stimulation

The human brain is arguably one of the most complex systems in nature. To understand how it operates, it is essential to understand the link between neural activity and behavior. Experimental investigation of that link requires tools to interact with neural activity during behavior. Human neuroscience, however, has been severely bottlenecked by the limitations of these tools. While invasive methods can support highly specific interaction with brain activity during behavior, their applicability in human neuroscience is limited. Despite extensive development in the last decades, noninvasive alternatives have lacked spatial specificity and yielded results that are commonly fraught with variability and replicability issues, along with relatively limited understanding of the neural mechanisms involved. Here we provide a comprehensive review of the state-of-the-art in interacting with human brain activity and highlight current limitations and recent efforts to overcome these limitations. Beyond crucial technical and scientific advancements in electromagnetic brain stimulation, new frontiers in interacting with human brain activity such as task-irrelevant sensory stimulation and focal ultrasound stimulation are introduced. Finally, we argue that, along with technological improvements and breakthroughs in noninvasive methods, a paradigm shift towards adaptive closed-loop stimulation will be a critical step for advancing human neuroscience.

Sensory recruitment in visual short-term memory: A systematic review and meta-analysis of sensory visual cortex interference using transcranial magnetic stimulation

Sensory visual areas are involved in encoding information in visual short-term memory (VSTM). Yet it remains unclear whether sensory visual cortex is a necessary component of the brain network for maintenance of information in VSTM. Here, we aimed to systematically review studies that have investigated the role of the sensory visual cortex in VSTM using transcranial magnetic stimulation (TMS) and to quantitatively explore these effects using meta-analyses. Fourteen studies were identified and reviewed. Eight studies provided sufficient data for meta-analysis. Two meta-analyses, one regarding the VSTM encoding phase (17 effect sizes) and one regarding the VSTM maintenance phase (15 effect sizes), two meta-regressions (32 effect sizes in each), and one exploratory meta-analysis were conducted. Our results indicate that the sensory visual cortex is similarly involved in both the encoding and maintenance VSTM phase. We suggest that some cases where evidence did not show significant TMS effects was due to low memory or perceptual task demands. Overall, these findings support the idea that sensory visual areas are part of the brain network responsible for successfully maintaining information in VSTM.

Fronto-medial theta coordinates posterior maintenance of working memory content

How does the human brain manage multiple bits of information to guide goal-directed behavior? Successful working memory (WM) functioning has consistently been linked to oscillatory power in the theta frequency band (4–8 Hz) over fronto-medial cortex (fronto-medial theta [FMT]). Specifically, FMT is thought to reflect the mechanism of an executive sub-system that coordinates maintenance of memory contents in posterior regions. However, direct evidence for the role of FMT in controlling specific WM content is lacking. Here, we collected high-density electroencephalography (EEG) data while participants engaged in WM-dependent tasks and then used multivariate decoding methods to examine WM content during the maintenance period. Engagement of WM was accompanied by a focal increase in FMT. Importantly, decoding of WM content was driven by posterior sites, which, in turn, showed increased functional theta coupling with fronto-medial channels. Finally, we observed a significant slowing of FMT frequency with increasing WM load, consistent with the hypothesized broadening of a theta “duty cycle” to accommodate additional WM items. Together, these findings demonstrate that frontal theta orchestrates posterior maintenance of WM content. Moreover, the observed frequency slowing elucidates the function of FMT oscillations by specifically supporting phase-coding accounts of WM.

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FMT power supports WM functions

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During WM performance, posterior/parietal regions are coupled with FMT

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Multivariate decoding of WM content is mediated by these same posterior channels

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Frontal theta frequency slows with WM load supporting phase-coding models

Theta rhythmicity governs human behavior and hippocampal signals during memory-dependent tasks

Memory formation and reinstatement are thought to lock to the hippocampal theta rhythm, predicting that encoding and retrieval processes appear rhythmic themselves. Here, we show that rhythmicity can be observed in behavioral responses from memory tasks, where participants indicate, using button presses, the timing of encoding and recall of cue-object associative memories. We find no evidence for rhythmicity in button presses for visual tasks using the same stimuli, or for questions about already retrieved objects. The oscillations for correctly remembered trials center in the slow theta frequency range (1-5 Hz). Using intracranial EEG recordings, we show that the memory task induces temporally extended phase consistency in hippocampal local field potentials at slow theta frequencies, but significantly more for remembered than forgotten trials, providing a potential mechanistic underpinning for the theta oscillations found in behavioral responses.

Synchronization patterns reveal neuronal coding of working memory content

Neuronal oscillations are suggested to play an important role in auditory working memory (WM), but their contribution to content-specific representations has remained unclear. Here, we measure magnetoencephalography during a retro-cueing task with parametric ripple-sound stimuli, which are spectrotemporally similar to speech but resist non-auditory memory strategies. Using machine learning analyses, with rigorous between-subject cross-validation and non-parametric permutation testing, we show that memorized sound content is strongly represented in phase-synchronization patterns between subregions of auditory and frontoparietal cortices. These phase-synchronization patterns predict the memorized sound content steadily across the studied maintenance period. In addition to connectivity-based representations, there are indices of more local, “activity silent” representations in auditory cortices, where the decoding accuracy of WM content significantly increases after task-irrelevant “impulse stimuli.” Our results demonstrate that synchronization patterns across auditory sensory and association areas orchestrate neuronal coding of auditory WM content. This connectivity-based coding scheme could also extend beyond the auditory domain.

Mamashli et al. use machine learning analyses of human magnetoencephalography (MEG) recordings to study “working memory,” maintenance of information in mind over brief periods of time. Their results show that the human brain maintains working memory content in transient functional connectivity patterns across sensory and association areas.

Phase-dependent offline enhancement of human motor memory

BACKGROUND

Skill learning engages offline activity in the primary motor cortex (M1). Sensorimotor cortical activity oscillates between excitatory trough and inhibitory peak phases of the mu (8-12 Hz) rhythm. We recently showed that these mu phases influence the magnitude and direction of neuroplasticity induction within M1. However, the contribution of M1 activity during mu peak and trough phases to human skill learning has not been investigated.

OBJECTIVE

To evaluate the effects of phase-dependent TMS during mu peak and trough phases on offline learning of a newly-acquired motor skill.

METHODS

On Day 1, three groups of healthy adults practiced an explicit motor sequence learning task with their non-dominant left hand. After practice, phase-dependent TMS was applied to the right M1 during either mu peak or mu trough phases. The third group received sham TMS during random mu phases. On Day 2, all subjects were re-tested on the same task to evaluate offline learning.

RESULTS

Subjects who received phase-dependent TMS during mu trough phases showed increased offline skill learning compared to those who received phase-dependent TMS during mu peak phases or sham TMS during random mu phases. Additionally, phase-dependent TMS during mu trough phases elicited stronger whole-brain broadband oscillatory power responses than phase-dependent TMS during mu peak phases.

CONCLUSIONS

We conclude that sensorimotor mu trough phases reflect brief windows of opportunity during which TMS can strengthen newly-acquired skill memories.

Stable maintenance of multiple representational formats in human visual short-term memory

Visual short-term memory (VSTM) enables humans to form a stable and coherent representation of the external world. However, the nature and temporal dynamics of the neural representations in VSTM that support this stability are barely understood. Here we combined human intracranial electroencephalography (iEEG) recordings with analyses using deep neural networks and semantic models to probe the representational format and temporal dynamics of information in VSTM. We found clear evidence that VSTM maintenance occurred in two distinct representational formats which originated from different encoding periods. The first format derived from an early encoding period (250 to 770 ms) corresponded to higher-order visual representations. The second format originated from a late encoding period (1,000 to 1,980 ms) and contained abstract semantic representations. These representational formats were overall stable during maintenance, with no consistent transformation across time. Nevertheless, maintenance of both representational formats showed substantial arrhythmic fluctuations, i.e., waxing and waning in irregular intervals. The increases of the maintained representational formats were specific to the phases of hippocampal low-frequency activity. Our results demonstrate that human VSTM simultaneously maintains representations at different levels of processing, from higher-order visual information to abstract semantic representations, which are stably maintained via coupling to hippocampal low-frequency activity.