Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans

Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

Decreases in low-frequency power (2–30 Hz) alongside high-frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously, this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel magnetoencephalography (MEG)–intracranial electroencephalography (iEEG) study in which healthy participants and epilepsy patients, respectively, studied either familiar verbal material or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time and space and by experimental manipulation. Both MEG and iEEG data show that decreases in alpha/beta power specifically predicted the encoding of words but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high-frequency gamma power increases occurred significantly earlier compared to low-frequency theta power decreases. These results show that simple “spectral tilt” cannot explain common oscillatory changes and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

There are two competing explanations for electrophysiological signatures during cognitive processes. One assumes simultaneous increases in high frequencies paired with decreases in low frequencies, whereas the other suggests that different frequencies index separate oscillatory processes. This study reports data that support the latter view.

Stimulation of the Posterior Cingulate Cortex Impairs Episodic Memory Encoding

Neuroimaging experiments implicate the posterior cingulate cortex (PCC) in episodic memory processing, making it a potential target for responsive neuromodulation strategies outside of the hippocampal network. However, causal evidence for the role that PCC plays in memory encoding is lacking. In human female and male participants (N = 17) undergoing seizure mapping, we investigated functional properties of the PCC using deep brain stimulation (DBS) and stereotactic electroencephalography. We used a verbal free recall paradigm in which the PCC was stimulated during presentation of half of the study lists, whereas no stimulation was applied during presentation of the remaining lists. We investigated whether stimulation affected memory and modulated hippocampal activity. Results revealed four main findings. First, stimulation during episodic memory encoding impaired subsequent free recall, predominantly for items presented early in the study lists. Second, PCC stimulation increased hippocampal gamma-band power. Third, stimulation-induced hippocampal gamma power predicted the magnitude of memory impairment. Fourth, functional connectivity between the hippocampus and PCC predicted the strength of the stimulation effect on memory. Our findings offer causal evidence implicating the PCC in episodic memory encoding. Importantly, the results indicate that stimulation targeted outside of the temporal lobe can modulate hippocampal activity and impact behavior. Furthermore, measures of connectivity between brain regions within a functional network can be informative in predicting behavioral effects of stimulation. Our findings have significant implications for developing therapies to treat memory disorders and cognitive impairment using DBS.SIGNIFICANCE STATEMENT Cognitive impairment and memory loss are critical public health challenges. Deep brain stimulation (DBS) is a promising tool for developing strategies to ameliorate memory disorders by targeting brain regions involved in mnemonic processing. Using DBS, our study sheds light on the lesser-known role of the posterior cingulate cortex (PCC) in memory encoding. Stimulating the PCC during encoding impairs subsequent recall memory. The degree of impairment is predicted by stimulation-induced hippocampal gamma oscillations and functional connectivity between PCC and hippocampus. Our findings provide the first causal evidence implicating PCC in memory encoding and highlight the PCC as a favorable target for neuromodulation strategies using a priori connectivity measures to predict stimulation effects. This has significant implications for developing therapies for memory diseases.

Memory Prosthesis: Is It Time for a Deep Neuromimetic Computing Approach?

Memory loss, one of the most dreaded afflictions of the human condition, presents considerable burden on the world's health care system and it is recognized as a major challenge in the elderly. There are only a few neuromodulation treatments for memory dysfunctions. Open loop deep brain stimulation is such a treatment for memory improvement, but with limited success and conflicting results. In recent years closed-loop neuroprosthesis systems able to simultaneously record signals during behavioral tasks and generate with the use of internal neural factors the precise timing of stimulation patterns are presented as attractive alternatives and show promise in memory enhancement and restoration. A few such strides have already been made in both animals and humans, but with limited insights into their mechanisms of action. Here, I discuss why a deep neuromimetic computing approach linking multiple levels of description, mimicking the dynamics of brain circuits, interfaced with recording and stimulating electrodes could enhance the performance of current memory prosthesis systems, shed light into the neurobiology of learning and memory and accelerate the progress of memory prosthesis research. I propose what the necessary components (nodes, structure, connectivity, learning rules, and physiological responses) of such a deep neuromimetic model should be and what type of data are required to train/test its performance, so it can be used as a true substitute of damaged brain areas capable of restoring/enhancing their missing memory formation capabilities. Considerations to neural circuit targeting, tissue interfacing, electrode placement/implantation, and multi-network interactions in complex cognition are also provided.

Decoding the tradeoff between encoding and retrieval to predict memory for overlapping events

When new events overlap with past events, there is a natural tradeoff between encoding the new event and retrieving the past event. Given the ubiquity of overlap among memories, this tradeoff between memory encoding and retrieval is of central importance to computational models of episodic memory (O'Reilly & McClelland 1994; Hasselmo 2005). However, prior studies have not directly linked neural markers of encoding/retrieval tradeoffs to behavioral measures of how overlapping events are remembered. Here, by decoding patterns of scalp electroencephalography (EEG) from male and female human subjects, we show that tradeoffs between encoding and retrieval states are reflected in distributed patterns of neural activity and, critically, these neural tradeoffs predict how overlapping events will later be remembered. Namely, new events that overlapped with past events were more likely to be subsequently remembered if neural patterns were biased toward a memory encoding state-or, conversely, away from a retrieval state. Additionally, we show that neural markers of encoding vs. retrieval states are surprisingly independent from previously-described EEG predictors of subsequent memory. Instead, we demonstrate that previously-described EEG predictors of subsequent memory are better explained by task engagement than by memory encoding, per se. Collectively, our findings provide important insight into how the memory system balances memory encoding and retrieval states and, more generally, into the neural mechanisms that support successful memory formation.

Functional control of electrophysiological network architecture using direct neurostimulation in humans

Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multimodal intracranial recordings and diffusion-weighted imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.

Brain stimulation devices capable of perturbing the physiological state of neural systems are rapidly gaining popularity for their potential to treat neurological and psychiatric disease. A root problem is that underlying dysfunction spans a large-scale network of brain regions, requiring the ability to control the complex interactions between multiple brain areas. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. We demonstrate the ability to predictably reconfigure patterns of interactions between functional brain areas by modulating the strength and location of stimulation. Our findings have high significance for designing stimulation protocols capable of modulating distributed neural circuits in the human brain.

Modulating Human Memory via Entrainment of Brain Oscillations

In the human brain, oscillations occur during neural processes that are relevant for memory. This has been demonstrated by a plethora of studies relating memory processes to specific oscillatory signatures. Several recent studies have gone beyond such correlative approaches and provided evidence supporting the idea that modulating oscillations via frequency-specific entrainment can alter memory functions. Such causal evidence is important because it allows distinguishing mechanisms directly related to memory from mere epiphenomenal oscillatory signatures of memory. This review provides an overview of stimulation studies using different approaches to entrain brain oscillations for modulating human memory. We argue that these studies demonstrate a causal link between brain oscillations and memory, speaking against an epiphenomenal perspective of brain oscillations.

Optogenetic Stimulation of the Basolateral Amygdala Increased Theta-Modulated Gamma Oscillations in the Hippocampus

The amygdala can modulate declarative memory. For example, previous research in rats and humans showed that brief electrical stimulation to the basolateral complex of the amygdala (BLA) prioritized specific objects to be consolidated into long term memory in the absence of emotional stimuli and without awareness of stimulation. The capacity of the BLA to influence memory depends on its substantial projections to many other brain regions, including the hippocampus. Nevertheless, how activation of the BLA influences ongoing neuronal activity in other regions is poorly understood. The current study used optogenetic stimulation of putative glutamatergic neurons in the BLA of freely exploring rats to determine whether brief activation of the BLA could increase in the hippocampus gamma oscillations for which the amplitude was modulated by the phase of theta oscillations, an oscillatory state previously reported to correlate with good memory. BLA neurons were stimulated in 1-s bouts with pulse frequencies that included the theta range (8 Hz), the gamma range (50 Hz), or a combination of both ranges (eight 50-Hz bursts). Local field potentials were recorded in the BLA and in the pyramidal layer of CA1 in the intermediate hippocampus. A key question was whether BLA stimulation at either theta or gamma frequencies could combine with ongoing hippocampal oscillations to result in theta-modulated gamma or whether BLA stimulation that included both theta and gamma frequencies would be necessary to increase theta–gamma comodulation in the hippocampus. All stimulation conditions elicited robust responses in BLA and CA1, but theta-modulated gamma oscillations increased in CA1 only when BLA stimulation included both theta and gamma frequencies. Longer bouts (5-s) of BLA stimulation resulted in hippocampal activity that evolved away from the initial oscillatory states and toward those characterized more by prominent low-frequency oscillations. The current results indicated that one mechanism by which the amygdala might influence declarative memory is by eliciting neuronal oscillatory states in the hippocampus that benefit memory.

Neural activity reveals interactions between episodic and semantic memory systems during retrieval

Whereas numerous findings support a distinction between episodic and semantic memory, it is now widely acknowledged that these two forms of memory interact during both encoding and retrieval. The precise nature of this interaction, however, remains poorly understood. To examine the role of semantic organization during episodic encoding and retrieval, we recorded intracranial encephalographic signals as 69 neurosurgical patients studied and subsequently recalled categorized and unrelated word lists. Applying multivariate classifiers to neural recordings, we were able to reliably predict encoding success, retrieval success, and temporal and categorical clustering during recall. By assessing how these classifiers generalized across list types, we identified specific retrieval processes that predicted recall of categorized lists and distinguished between recall transitions within and between category clusters. These results particularly implicate retrieval (rather than encoding) processes in the categorical organization of episodic memories. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Direct Stimulation of Human Hippocampus During Verbal Associative Encoding Enhances Subsequent Memory Recollection

Previous studies have reported conflicting results regarding the effect of direct electrical stimulation of the human hippocampus on memory performance. A major function of the hippocampus is to form associations between individual elements of experience. However, the effect of direct hippocampal stimulation on associative memory remains largely inconclusive, with most evidence coming from studies employing non-invasive stimulation. Here, we therefore tested the hypothesis that direct electrical stimulation of the hippocampus specifically enhances hippocampal-dependent associative memory. To test this hypothesis, we recruited surgical patients with implanted subdural electrodes to perform a word pair memory task during which the hippocampus was stimulated. Our results indicate that stimulation of the hippocampus during encoding helped to build strong associative memories and enhanced recollection in subsequent trials. Moreover, stimulation significantly increased theta power in the lateral middle temporal cortex during successful memory encoding. Overall, our findings indicate that hippocampal stimulation positively impacts performance during a word pair memory task, suggesting that successful memory encoding involves the temporal cortex, which may act together with the hippocampus.

Changing temporal context in human temporal lobe promotes memory of distinct episodes

Memories of experiences that occur around the same time are linked together by a shared temporal context, represented by shared patterns of neural activity. However, shared temporal context may be problematic for selective retrieval of specific memories. Here, we examine intracranial EEG (iEEG) in the human temporal lobe as participants perform a verbal paired associates memory task that requires the encoding of distinct word pairs in memory. We find that the rate of change in patterns of low frequency (3–12 Hz) power distributed across the temporal lobe is significantly related to memory performance. We also find that exogenous electrical stimulation affects how quickly these neural representations of temporal context change with time, which directly affects the ability to successfully form memories for distinct items. Our results indicate that the ability to retrieve distinct episodic memories is related to how quickly neural representations of temporal context change over time during encoding.

Memories formed around the same time are linked together by a shared temporal context. Here, the authors show that the ability to selectively retrieve distinct episodic memories formed close together in time is related to how quickly neural representations of temporal context change over time during encoding.

Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance

The neural substrates of working memory are spread across prefrontal, parietal and cingulate cortices and are thought to be coordinated through low frequency cortical oscillations in the theta (3-8 Hz) and alpha (8-12 Hz) frequency bands. While the functional role of many subregions have been elucidated using neuroimaging studies, the role of superior frontal gyrus (SFG) is not yet clear. Here, we combined electrocorticography and direct cortical stimulation in three patients implanted with subdural electrodes to assess if superior frontal gyrus is indeed involved in working memory. We found left SFG exhibited task-related modulation of oscillations in the theta and alpha frequency bands specifically during the encoding epoch. Stimulation at the frequency matched to the endogenous oscillations resulted in reduced reaction times in all three participants. Our results provide evidence for SFG playing a functional role in working memory and suggest that SFG may coordinate working memory through low-frequency oscillations thus bolstering the feasibility of using intracranial electric stimulation for restoring cognitive function.

Reporting Guidelines and Issues to Consider for Using Intracranial Brain Stimulation in Studies of Human Declarative Memory

Participants with stimulating and recording electrodes implanted within the brain for clinical evaluation and treatment provide a rare opportunity to unravel the neuronal correlates of human memory, as well as offer potential for modulation of behavior. Recent intracranial stimulation studies of memory have been inconsistent in methodologies employed and reported conclusions, which renders generalizations and construction of a framework impossible. In an effort to unify future study efforts and enable larger meta-analyses we propose in this mini-review a set of guidelines to consider when pursuing intracranial stimulation studies of human declarative memory and summarize details reported by previous relevant studies. We present technical and safety issues to consider when undertaking such studies and a checklist for researchers and clinicians to use for guidance when reporting results, including targeting, placement, and localization of electrodes, behavioral task design, stimulation and electrophysiological recording methods, details of participants, and statistical analyses. We hope that, as research in invasive stimulation of human declarative memory further progresses, these reporting guidelines will aid in setting standards for multicenter studies, in comparison of findings across studies, and in study replications.

Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography

OBJECTIVE

Cortical oscillations, electrophysiological activity patterns, associated with cognitive functions and impaired in many psychiatric disorders can be observed in intracranial electroencephalography (iEEG). Direct cortical stimulation (DCS) may directly target these oscillations and may serve as therapeutic approaches to restore functional impairments. However, the presence of electrical stimulation artifacts in neurophysiological data limits the analysis of the effects of stimulation. Currently available methods suffer in performance in the presence of nonstationarity inherent in biological data.

APPROACH

Our algorithm, shape adaptive nonlocal artifact removal (SANAR) is based on unsupervised manifold learning. By estimating the Euclidean median of k-nearest neighbors of each artifact in a nonlocal fashion, we obtain a faithful representation of the artifact which is then subtracted. This approach overcomes the challenges presented by nonstationarity.

MAIN RESULTS

SANAR is effective in removing stimulation artifacts in the time domain while preserving the spectral content of the endogenous neurophysiological signal. We demonstrate the performance in a simulated dataset as well as in human iEEG data. Using two quantitative measures, that capture how much of information from endogenous activity is retained, we demonstrate that SANAR's performance exceeds that of one of the widely used approaches, independent component analysis, in the time domain as well as the frequency domain.

SIGNIFICANCE

This approach allows for the analysis of iEEG data, single channel or multiple channels, during DCS, a crucial step in advancing our understanding of the effects of periodic stimulation and developing new therapies.

Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics

Brain computer interfaces (BCIs) have been applied to sensorimotor systems for many years. However, BCI technology has broad potential beyond sensorimotor systems. The emerging field of cognitive prosthetics, for example, promises to improve learning and memory for patients with cognitive impairment. Unfortunately, our understanding of the neural mechanisms underlying these cognitive processes remains limited in part due to the extensive individual variability in neural coding and circuit function. As a consequence, the development of methods to ascertain optimal control signals for cognitive decoding and restoration remains an active area of inquiry. To advance the field, robust tools are required to quantify time-varying and task-dependent brain states predictive of cognitive performance. Here, we suggest that network science is a natural language in which to formulate and apply such tools. In support of our argument, we offer a simple demonstration of the feasibility of a network approach to BCI control signals, which we refer to as network BCI (nBCI). Finally, in a single subject example, we show that nBCI can reliably predict online cognitive performance and is superior to certain common spectral approaches currently used in BCIs. Our review of the literature and preliminary findings support the notion that nBCI could provide a powerful approach for future applications in cognitive prosthetics.

Medial temporal lobe functional connectivity predicts stimulation-induced theta power

Focal electrical stimulation of the brain incites a cascade of neural activity that propagates from the stimulated region to both nearby and remote areas, offering the potential to control the activity of brain networks. Understanding how exogenous electrical signals perturb such networks in humans is key to its clinical translation. To investigate this, we applied electrical stimulation to subregions of the medial temporal lobe in 26 neurosurgical patients fitted with indwelling electrodes. Networks of low-frequency (5–13 Hz) spectral coherence predicted stimulation-evoked increases in theta (5–8 Hz) power, particularly when stimulation was applied in or adjacent to white matter. Stimulation tended to decrease power in the high-frequency broadband (HFB; 50–200 Hz) range, and these modulations were correlated with HFB-based networks in a subset of subjects. Our results demonstrate that functional connectivity is predictive of causal changes in the brain, capturing evoked activity across brain regions and frequency bands.

Direct electrical brain stimulation can induce widespread changes in neural activity, offering a means to modulate network-wide activity and treat disease. Here, the authors show that the low-frequency functional connectivity profile of a stimulation target predicts where induced theta activity occurs.

Grid-like hexadirectional modulation of human entorhinal theta oscillations

The entorhinal cortex contains a network of grid cells that play a fundamental part in the brain's spatial system, supporting tasks such as path integration and spatial memory. In rodents, grid cells are thought to rely on network theta oscillations, but such signals are not evident in all species, challenging our understanding of the physiological basis of the grid network. We analyzed intracranial recordings from neurosurgical patients during virtual navigation to identify oscillatory characteristics of the human entorhinal grid network. The power of entorhinal theta oscillations showed six-fold modulation according to the virtual heading during navigation, which is a hypothesized signature of grid representations. Furthermore, modulation strength correlated with spatial memory performance. These results demonstrate the connection between theta oscillations and the human entorhinal grid network and show that features of grid-like neuronal representations can be identified from population electrophysiological recordings.

Cognitive tasks and human ambulatory electrocorticography using the RNS System

BACKGROUND

Electrocorticography studies are typically conducted in patients undergoing video EEG monitoring, but these studies are subject to confounds such as the effects of pain, recent anesthesia, analgesics, drug changes, antibiotics, and implant effects.

NEW METHOD

Techniques were developed to obtain electrocorticographic (ECoG) data from freely moving subjects performing navigational tasks using the RNS^® System (NeuroPace, Inc., Mountain View, CA), a brain-responsive neurostimulation medical device used to treat focal onset epilepsy, and to align data from the RNS System with cognitive task events with high precision. These subjects had not had recent surgery, and were therefore not confounded by the perioperative variables that affect video EEG studies.

RESULTS

Task synchronization using the synchronization marker technique provides a quantitative measure of clock uncertainty, and can align data to task events with less than 4 ms of uncertainty. Hippocampal ECoG activity was found to change immediately before an incorrect response to a math problem compared to hippocampal activity before a correct response. In addition, subjects were found to have variable but significant changes in theta band power in the hippocampus during navigation compared to when subjects were not navigating. We found that there is theta-gamma phase-amplitude coupling in the right hippocampus while subjects stand still during a navigation task.

COMPARISON WITH EXISTING METHODS

An alignment technique described in this study improves the upper bound on task-ECoG alignment uncertainty from approximately 30 ms to under 4 ms. The RNS System is one of the first platforms capable of providing untethered ambulatory ECoG recording in humans, allowing for the study of real world instead of virtual navigation. Compared to intracranial video EEG studies, studies using the RNS System platform are not subject to confounds caused by the drugs and recent surgery inherent to the perioperative environment. Furthermore, these subjects provide the opportunity to record from the same electrodes over the course of many years.

CONCLUSIONS

The RNS System enables us to study human navigation with unprecedented clarity. While RNS System patients have fewer electrodes implanted than video EEG patients, the lack of external artifact and confounds from recent surgery make this system a useful tool to further human electrophysiology research.

Integrating Brain Implants With Local and Distributed Computing Devices: A Next Generation Epilepsy Management System

Brain stimulation has emerged as an effective treatment for a wide range of neurological and psychiatric diseases. Parkinson’s disease, epilepsy, and essential tremor have FDA indications for electrical brain stimulation using intracranially implanted electrodes. Interfacing implantable brain devices with local and cloud computing resources have the potential to improve electrical stimulation efficacy, disease tracking, and management. Epilepsy, in particular, is a neurological disease that might benefit from the integration of brain implants with off-the-body computing for tracking disease and therapy. Recent clinical trials have demonstrated seizure forecasting, seizure detection, and therapeutic electrical stimulation in patients with drug-resistant focal epilepsy. In this paper, we describe a next-generation epilepsy management system that integrates local handheld and cloud-computing resources wirelessly coupled to an implanted device with embedded payloads (sensors, intracranial EEG telemetry, electrical stimulation, classifiers, and control policy implementation). The handheld device and cloud computing resources can provide a seamless interface between patients and physicians, and realtime intracranial EEG can be used to classify brain state (wake/sleep, preseizure, and seizure), implement control policies for electrical stimulation, and track patient health. This system creates a flexible platform in which low demand analytics requiring fast response times are embedded in the implanted device and more complex algorithms are implemented in offthebody local and distributed cloud computing environments. The system enables tracking and management of epileptic neural networks operating over time scales ranging from milliseconds to months.

Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings

OBJECTIVE

We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordings obtained from human stereo EEG subjects. We also sought to test the impact of applying t-distributed stochastic neighbor embedding (tSNE) for unsupervised dimensionality reduction, as well as testing the effect of reducing input features to a core set of memory relevant brain areas. This work builds upon published efforts to develop a closed-loop stimulation device to improve memory performance.

APPROACH

We used a unique data set consisting of 30 stereo EEG patients with electrodes implanted into a core set of five common brain regions (along with other areas) who performed the free recall episodic memory task as brain activity was recorded. Using three different machine learning strategies, we trained classifiers to predict successful versus unsuccessful memory encoding and compared the difference in classifier performance (as measured by the AUC) at the subject level and in aggregate across modalities. We report the impact of feature reduction on the classifiers, including reducing the number of input brain regions, frequency bands, and the impact of tSNE.

RESULTS

Deep learning classifiers outperformed both support vector machines (SVM) and logistic regression (LR). A priori selection of core brain regions also improved classifier performance for LR and SVM models, especially when combined with tSNE.

SIGNIFICANCE

We report for the first time a direct comparison among traditional and deep learning methods of binary classification to the problem of predicting successful memory encoding using human brain electrophysiological data. Our findings will inform the design of brain machine interface devices to affect memory processing.

Excitatory TMS modulates memory representations

Brain stimulation technologies have seen increasing application in basic science investigations, specifically toward the goal of improving memory function. However, proposals concerning the neural mechanisms underlying cognitive enhancement often rely on simplified notions of excitation. As a result, most applications examining the effects of transcranial magnetic stimulation (TMS) on functional neuroimaging measures have been limited to univariate analyses of brain activity. We present here analyses using representational similarity analysis (RSA) and encoding-retrieval similarity (ERS) analysis to quantify the effect of TMS on memory representations. To test whether an increase in local excitability in PFC can have measurable influences on upstream representations in earlier temporal memory regions, we compared 1 and 5Hz stimulation to the left dorsolateral PFC (DLPFC). We found that 5Hz rTMS, relative to 1Hz, had multiple effects on neural representations: 1) greater representational similarity during both encoding and retrieval in ventral stream regions, 2) greater ERS in the hippocampus, and, critically, 3) increasing ERS in MTL was correlated with increasing univariate activity in DLPFC, and greater functional connectivity for hits than misses between these regions. These results provide the first evidence of rTMS modulating semantic representations and strengthen the idea that rTMS may affect the reinstatement of previously experienced events in upstream regions.

Auras localized to the temporal lobe disrupt verbal memory and learning - Causal evidence from direct electrical stimulation of the hippocampus

Auras (focal aware seizure; FAS) are subjective ictal events with retained consciousness. Epileptiform activities can disrupt cognitive tasks, but studies are limited to seizures with impaired awareness. As a proof of concept, we examined the cognitive effects of direct electrical stimulation to the left hippocampus which induced a habitual FAS in a patient with left mesial temporal lobe epilepsy. During the induced habitual FAS, verbal memory performance declined significantly as compared to pre-stimulation testing. Tasks measuring auditory working memory and psychomotor processing speed were not affected by the stimulation. The study confirms that FAS can impair episodic verbal memory and learning.

Representation, Pattern Information, and Brain Signatures: From Neurons to Neuroimaging

Human neuroimaging research has transitioned from mapping local effects to developing predictive models of mental events that integrate information distributed across multiple brain systems. Here we review work demonstrating how multivariate predictive models have been utilized to provide quantitative, falsifiable predictions; establish mappings between brain and mind with larger effects than traditional approaches; and help explain how the brain represents mental constructs and processes. Although there is increasing progress toward the first two of these goals, models are only beginning to address the latter objective. By explicitly identifying gaps in knowledge, research programs can move deliberately and programmatically toward the goal of identifying brain representations underlying mental states and processes.

WONOEP APPRAISAL: The many facets of epilepsy networks

The brain is a complex system composed of networks of interacting elements, from genes to circuits, whose function (and dysfunction) is not derivable from the superposition of individual components. Epilepsy is frequently described as a network disease, but to date, there is no standardized framework within which network concepts applicable to all levels from genes to whole brain can be used to generate deeper insights into the pathogenesis of seizures or the associated morbidities. To address this shortcoming, the Neurobiology Commission of the International League Against Epilepsy dedicated a Workshop on Neurobiology of Epilepsy (XIV WONOEP 2017) with the aim of formalizing network concepts as they apply to epilepsy and to critically discuss whether and how such concepts could augment current research endeavors. Here, we review concepts and strategies derived by considering epilepsy as a disease of different network hierarchies that range from genes to clinical phenotypes. We propose that the concept of networks is important for understanding epilepsy and is critical for developing new study designs. These approaches could ultimately facilitate the development of novel diagnostic and therapeutic strategies.

Lateralized hippocampal oscillations underlie distinct aspects of human spatial memory and navigation

The hippocampus plays a vital role in various aspects of cognition including both memory and spatial navigation. To understand electrophysiologically how the hippocampus supports these processes, we recorded intracranial electroencephalographic activity from 46 neurosurgical patients as they performed a spatial memory task. We measure signals from multiple brain regions, including both left and right hippocampi, and we use spectral analysis to identify oscillatory patterns related to memory encoding and navigation. We show that in the left but not right hippocampus, the amplitude of oscillations in the 1–3-Hz “low theta” band increases when viewing subsequently remembered object–location pairs. In contrast, in the right but not left hippocampus, low-theta activity increases during periods of navigation. The frequencies of these hippocampal signals are slower than task-related signals in the neocortex. These results suggest that the human brain includes multiple lateralized oscillatory networks that support different aspects of cognition.

Theta oscillations are implicated in memory formation. Here, the authors show that low-theta oscillations in the hippocampus are differentially modulated between each hemisphere, with oscillations in the left increasing when successfully learning object–location pairs and in the right during spatial navigation.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

Single-Trial Phase Entrainment of Theta Oscillations in Sensory Regions Predicts Human Associative Memory Performance

Episodic memories are rich in sensory information and often contain integrated information from different sensory modalities. For instance, we can store memories of a recent concert with visual and auditory impressions being integrated in one episode. Theta oscillations have recently been implicated in playing a causal role synchronizing and effectively binding the different modalities together in memory. However, an open question is whether momentary fluctuations in theta synchronization predict the likelihood of associative memory formation for multisensory events. To address this question we entrained the visual and auditory cortex at theta frequency (4 Hz) and in a synchronous or asynchronous manner by modulating the luminance and volume of movies and sounds at 4 Hz, with a phase offset at 0° or 180°. EEG activity from human subjects (both sexes) was recorded while they memorized the association between a movie and a sound. Associative memory performance was significantly enhanced in the 0° compared with the 180° condition. Source-level analysis demonstrated that the physical stimuli effectively entrained their respective cortical areas with a corresponding phase offset. The findings suggested a successful replication of a previous study (Clouter et al., 2017). Importantly, the strength of entrainment during encoding correlated with the efficacy of associative memory such that small phase differences between visual and auditory cortex predicted a high likelihood of correct retrieval in a later recall test. These findings suggest that theta oscillations serve a specific function in the episodic memory system: binding the contents of different modalities into coherent memory episodes.SIGNIFICANCE STATEMENT How multisensory experiences are bound to form a coherent episodic memory representation is one of the fundamental questions in human episodic memory research. Evidence from animal literature suggests that the relative timing between an input and theta oscillations in the hippocampus is crucial for memory formation. We precisely controlled the timing between visual and auditory stimuli and the neural oscillations at 4 Hz using a multisensory entrainment paradigm. Human associative memory formation depends on coincident timing between sensory streams processed by the corresponding brain regions. We provide evidence for a significant role of relative timing of neural theta activity in human episodic memory on a single-trial level, which reveals a crucial mechanism underlying human episodic memory.

Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex

Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time.

Fornical Closed-Loop Stimulation for Alzheimer's Disease

Pharmacological neuromodulation strategies have shown limited efficacy in treating memory deficits related to Alzheimer's disease (AD). Despite encouraging results from a few preclinical studies, clinical trials investigating open-loop deep brain stimulation (DBS) for AD have not been successful. Recent refinements in understanding the various phases of memory processes, animal studies investigating phase-specific modulation of hippocampal activity during memorization, and clinical studies using closed-loop DBS strategies to treat patients with movement disorders, all point to the need to investigate closed-loop fornical DBS strategies to better understand memory dynamics and potentially treat memory deficits in AD preclinical models.

Electrical Stimulation in Hippocampus and Entorhinal Cortex Impairs Spatial and Temporal Memory

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients of both sexes who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects' abilities to remember items located far away from boundaries. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.SIGNIFICANCE STATEMENT Numerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

OBJECTIVE

We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient's own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval.

APPROACH

We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task.

MAIN RESULTS

MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information.

SIGNIFICANCE

These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

Pain is a subjective experience that alerts an individual to actual or potential tissue damage. Through mechanisms that are still unclear, normal physiological pain can lose its adaptive value and evolve into pathological chronic neuropathic pain. Chronic pain is a multifaceted experience that can be understood in terms of somatosensory, affective, and cognitive dimensions, each with associated symptoms and neural signals. While there have been many attempts to treat chronic pain, in this article we will argue that feedback-controlled ‘closed-loop’ deep brain stimulation (DBS) offers an urgent and promising route for treatment. Contemporary DBS trials for chronic pain use “open-loop” approaches in which tonic stimulation is delivered with fixed parameters to a single brain region. The impact of key variables such as the target brain region and the stimulation waveform is unclear, and long-term efficacy has mixed results. We hypothesize that chronic pain is due to abnormal synchronization between brain networks encoding the somatosensory, affective and cognitive dimensions of pain, and that multisite, closed-loop DBS provides an intuitive mechanism for disrupting that synchrony. By (1) identifying biomarkers of the subjective pain experience and (2) integrating these signals into a state-space representation of pain, we can create a predictive model of each patient's pain experience. Then, by establishing how stimulation in different brain regions influences individual neural signals, we can design real-time, closed-loop therapies tailored to each patient. While chronic pain is a complex disorder that has eluded modern therapies, rich historical data and state-of-the-art technology can now be used to develop a promising treatment.

Pupil size reflects successful encoding and recall of memory in humans

Pupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most constricted in the initial fixation phase and was gradually more dilated through the subsequent encoding, distractor and recall phases of the task, as the word items were maintained in memory. Within the final recall phase, retrieving memory for individual words was associated with pupil dilation in absence of visual stimulation. Words that were successfully recalled showed significant differences in pupil response during their encoding compared to those that were forgotten – the pupil was more constricted before and more dilated after the onset of word presentation. Our results suggest pupil size as a potential biomarker for probing and modulation of memory processing.

Age-related Differences in Prestimulus Subsequent Memory Effects Assessed with Event-related Potentials

Prestimulus subsequent memory effects (preSMEs)-differences in neural activity elicited by a task cue at encoding that are predictive of later memory performance-are thought to reflect differential engagement of preparatory processes that benefit episodic memory encoding. We investigated age differences in preSMEs indexed by differences in ERP amplitude just before the onset of a study item. Young and older adults incidentally encoded words for a subsequent memory test. Each study word was preceded by a task cue that signaled a judgment to perform on the word. Words were presented for either a short (300 msec) or long (1000 msec) duration with the aim of placing differential benefits on engaging preparatory processes initiated by the task cue. ERPs associated with subsequent successful and unsuccessful recollection, operationalized here by source memory accuracy, were estimated time-locked to the onset of the task cue. In a late time window (1000-2000 msec after onset of the cue), young adults demonstrated frontally distributed preSMEs for both the short and long study durations, albeit with opposite polarities in the two conditions. This finding suggests that preSMEs in young adults are sensitive to perceived task demands. Although older adults showed no evidence of preSMEs in the same late time window, significant preSMEs were observed in an earlier time window (500-1000 msec) that was invariant with study duration. These results are broadly consistent with the proposal that older adults differ from their younger counterparts in how they engage preparatory processes during memory encoding.

Multimodal Encoding of Novelty, Reward, and Learning in the Primate Nucleus Basalis of Meynert

Associative learning is crucial for daily function, involving a complex network of brain regions. One region, the nucleus basalis of Meynert (NBM), is a highly interconnected, largely cholinergic structure implicated in multiple aspects of learning. We show that single neurons in the NBM of nonhuman primates (NHPs; n = 2 males; Macaca mulatta) encode learning a new association through spike rate modulation. However, the power of low-frequency local field potential (LFP) oscillations decreases in response to novel, not-yet-learned stimuli but then increase as learning progresses. Both NBM and the dorsolateral prefrontal cortex encode confidence in novel associations by increasing low- and high-frequency LFP power in anticipation of expected rewards. Finally, NBM high-frequency power dynamics are anticorrelated with spike rate modulations. Therefore, novelty, learning, and reward anticipation are separately encoded through differentiable NBM signals. By signaling both the need to learn and confidence in newly acquired associations, NBM may play a key role in coordinating cortical activity throughout the learning process.SIGNIFICANCE STATEMENT Degradation of cells in a key brain region, the nucleus basalis of Meynert (NBM), correlates with Alzheimer's disease and Parkinson's disease progression. To better understand the role of this brain structure in learning and memory, we examined neural activity in the NBM in behaving nonhuman primates while they performed a learning and memory task. We found that single neurons in NBM encoded both salience and an early learning, or cognitive state, whereas populations of neurons in the NBM and prefrontal cortex encode learned state and reward anticipation. The NBM may thus encode multiple stages of learning. These multimodal signals might be leveraged in future studies to develop neural stimulation to facilitate different stages of learning and memory.

Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation.

Network-based brain stimulation selectively impairs spatial retrieval

BACKGROUND

Direct brain stimulation via electrodes implanted for intracranial electroencephalography (iEEG) permits the modulation of endogenous electrical signals with significantly greater spatial and temporal specificity than non-invasive approaches. It also allows for the stimulation of deep brain structures important to memory, such as the hippocampus, that are difficult, if not impossible, to target non-invasively. Direct stimulation studies of these deep memory structures, though, have produced mixed results, with some reporting improvement, some impairment, and others, no consistent changes.

OBJECTIVE/HYPOTHESIS

We hypothesize that to modulate cognitive function using brain stimulation, it is essential to modulate connected nodes comprising a network, rather than just alter local activity.

METHODS

iEEG data collected while patients performed a spatiotemporal memory retrieval task were used to map frequency-specific, coherent oscillatory activity between different brain regions associated with successful memory retrieval. We used these to identify two target nodes that exhibited selectively stronger coupling for spatial vs. temporal retrieval. In a subsequent session, electrical stimulation - theta-bursts with a fixed phase-lag (0° or 180°) - was applied to the two target regions while patients performed spatiotemporal retrieval.

RESULTS

Stimulation selectively impaired spatial retrieval while not affecting temporal retrieval, and this selective impairment was associated with theta decoupling of the spatial retrieval network.

CONCLUSION

These findings suggest that stimulating tightly connected nodes in a functional network at the appropriate phase-lag may effectively modulate the network function, and while in this case it impaired memory processes, it sets a foundation for further network-based perturbation studies.

Stochastic resonance mediates the state-dependent effect of periodic stimulation on cortical alpha oscillations

Brain stimulation can be used to engage and modulate rhythmic activity in brain networks. However, the outcomes of brain stimulation are shaped by behavioral states and endogenous fluctuations in brain activity. To better understand how this intrinsic oscillatory activity controls the susceptibility of the brain to stimulation, we analyzed a computational model of the thalamo-cortical system in two distinct states (rest and task-engaged) to identify the mechanisms by which endogenous alpha oscillations (8Hz–12Hz) are modulated by periodic stimulation. Our analysis shows that the different responses to stimulation observed experimentally in these brain states can be explained by a passage through a bifurcation combined with stochastic resonance — a mechanism by which irregular fluctuations amplify the response of a nonlinear system to weak periodic signals. Indeed, our findings suggest that modulation of brain oscillations is best achieved in states of low endogenous rhythmic activity, and that irregular state-dependent fluctuations in thalamic inputs shape the susceptibility of cortical population to periodic stimulation.

Direct electrical stimulation of the amygdala enhances declarative memory in humans

Emotional events are often remembered better than neutral events, a benefit that many studies have hypothesized to depend on the amygdala's interactions with memory systems. These studies have indicated that the amygdala can modulate memory-consolidation processes in other brain regions such as the hippocampus and perirhinal cortex. Indeed, rodent studies have demonstrated that direct activation of the amygdala can enhance memory consolidation even during nonemotional events. However, the premise that the amygdala causally enhances declarative memory has not been directly tested in humans. Here we tested whether brief electrical stimulation to the amygdala could enhance declarative memory for specific images of neutral objects without eliciting a subjective emotional response. Fourteen epilepsy patients undergoing monitoring of seizures via intracranial depth electrodes viewed a series of neutral object images, half of which were immediately followed by brief, low-amplitude electrical stimulation to the amygdala. Amygdala stimulation elicited no subjective emotional response but led to reliably improved memory compared with control images when patients were given a recognition-memory test the next day. Neuronal oscillations in the amygdala, hippocampus, and perirhinal cortex during this next-day memory test indicated that a neural correlate of the memory enhancement was increased theta and gamma oscillatory interactions between these regions, consistent with the idea that the amygdala prioritizes consolidation by engaging other memory regions. These results show that the amygdala can initiate endogenous memory prioritization processes in the absence of emotional input, addressing a fundamental question and opening a path to future therapies.

Principled Approaches to Direct Brain Stimulation for Cognitive Enhancement

In this brief review, we identify key areas of research that inform a systematic and targeted approach for invasive brain stimulation with the goal of modulating higher cognitive functions such as memory. We outline several specific challenges that must be successfully navigated in order to achieve this goal. Specifically, using direct brain stimulation to support memory requires demonstrating that (1) there are reliable neural patterns corresponding to different events and memory states, (2) stimulation can be used to induce these target activity patterns, and (3) inducing such patterns modulates memory in the expected directions. Invasive stimulation studies typically have not taken into account intrinsic brain states and dynamics, nor have they a priori targeted specific neural patterns that have previously been identified as playing an important role in memory. Moreover, the effects of stimulation on neural activity are poorly understood and are sensitive to multiple factors including the specific stimulation parameters, the processing state of the brain at the time of stimulation, and neuroanatomy of the stimulated region. As a result, several studies have reported conflicting results regarding the use of direct stimulation for memory modulation. Here, we review the latest findings relevant to these issues and discuss how we can gain better control over the effects of direct brain stimulation for modulating human memory and cognition.

Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition

The idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral neural activity, based on data from 294 neurosurgical patients fitted with indwelling electrodes. Here we report that gamma networks desynchronize and theta networks synchronize during encoding and retrieval. Furthermore, for nearly all brain regions we studied, gamma power rises as that region desynchronizes with gamma activity elsewhere in the brain, establishing gamma as a largely asynchronous phenomenon. The abundant phenomenon of theta synchrony is positively correlated with a brain region's gamma power, suggesting a predominant low-frequency mechanism for inter-regional communication.

Transcranial Alternating Current Stimulation (tACS) Mechanisms and Protocols

Perception, cognition and consciousness can be modulated as a function of oscillating neural activity, while ongoing neuronal dynamics are influenced by synaptic activity and membrane potential. Consequently, transcranial alternating current stimulation (tACS) may be used for neurological intervention. The advantageous features of tACS include the biphasic and sinusoidal tACS currents, the ability to entrain large neuronal populations, and subtle control over somatic effects. Through neuromodulation of phasic, neural activity, tACS is a powerful tool to investigate the neural correlates of cognition. The rapid development in this area requires clarity about best practices. Here we briefly introduce tACS and review the most compelling findings in the literature to provide a starting point for using tACS. We suggest that tACS protocols be based on functional brain mechanisms and appropriate control experiments, including active sham and condition blinding.