Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans

Neural Patterns of Social Pain in the Brain-Wide Representations Across Social Contexts

Empathy can be elicited by physiological pain, as well as in social contexts. Although physiological and different social contexts induce a strong subjective experience of empathy, the general and context-specific neural representations remain elusive. Here, it is combined fMRI with multivariate pattern analysis (MVPA) to establish neurofunctional models for social pain triggered by observing social exclusion and separation naturistic stimuli. The findings revealed that both social contexts engaged the empathy and social function networks. Notably, the intensity of pain empathy elicited by these two social stimuli does not significantly differentiate the neural representations of social exclusion and separation, suggesting context-specific neural representations underlying these experiences. Furthermore, this study established a model that traces the progression from physiological pain to social pain empathy. In conclusion, this study revealed the neural pathological foundations and interconnectedness of empathy induced by social and physiological stimuli and provide robust neuromarkers to precisely evaluate empathy across physiological and social domains.

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

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

Modulating limbic circuits in temporal lobe epilepsy: impacts on seizures, memory, mood and sleep

Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures that often originate within limbic networks involving amygdala and hippocampus. The limbic network is involved in crucial physiologic functions involving memory, emotion and sleep. Temporal lobe epilepsy is frequently drug-resistant, and people often experience comorbidities related to memory, mood and sleep. Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is an established therapy for temporal lobe epilepsy. However, the optimal stimulation parameters and their impact on memory, mood and sleep comorbidities remain unclear. We used an investigational brain sensing-stimulation implanted device to accurately track seizures, interictal epileptiform spikes (IES), and memory, mood and sleep comorbidities in five ambulatory subjects. Wireless streaming of limbic network local field potentials (LFPs) and subject behaviour were captured on a mobile device integrated with a cloud environment. Automated algorithms applied to the continuous LFPs were used to accurately cataloged seizures, IES and sleep-wake brain state. Memory and mood assessments were remotely administered to densely sample cognitive and behavioural response during ANT-DBS in ambulatory subjects living in their natural home environment. We evaluated the effect of continuous low-frequency and duty cycle high-frequency ANT-DBS on epileptiform activity and memory, mood and sleep comorbidities. Both low-frequency and high-frequency ANT-DBS paradigms reduced seizures. However, continuous low-frequency ANT-DBS showed greater reductions in IES, electrographic seizures and better sleep and memory outcomes. These results highlight the potential of synchronized brain sensing and dense behavioural tracking during ANT-DBS for optimizing neuromodulation therapy. While studies with larger patient numbers are needed to validate the benefits of low-frequency ANT-DBS, these findings are potentially translatable to individuals currently implanted with ANT-DBS systems.

Exploring individual differences in amygdala-mediated memory modulation

Amygdala activation by emotional arousal during memory formation can prioritize events for long-term memory. Building upon our prior demonstration that brief electrical stimulation to the human amygdala reliably improved long-term recognition memory for images of neutral objects without eliciting an emotional response, our study aims to explore and describe individual differences and stimulation-related factors in amygdala-mediated memory modulation. Thirty-one patients undergoing intracranial monitoring for intractable epilepsy were shown neutral object images paired with direct amygdala stimulation during encoding with recognition memory tested immediately and one day later. Adding to our prior sample, we found an overall memory enhancement effect without subjective emotional arousal at the one-day delay, but not at the immediate delay, for previously stimulated objects compared to not stimulated objects. Importantly, we observed a larger variation in performance across this larger sample than our initial sample, including some participants who showed a memory impairment for stimulated objects. Of the explored individual differences, the factor that most accounted for variability in memory modulation was each participant's pre-operative memory performance. Worse memory performance on standardized neuropsychological tests was associated with a stronger susceptibility to memory modulation in a positive or negative direction. Sex differences and the frequency of interictal epileptiform discharges (IEDs) during testing also accounted for some variance in amygdala-mediated memory modulation. Given the potential and challenges of this memory modulation approach, we discuss additional individual and stimulation factors that we hope will differentiate between memory enhancement and impairment to further optimize the potential of amygdala-mediated memory enhancement for therapeutic interventions.

Context familiarity is a third kind of episodic memory distinct from item familiarity and recollection

Episodic memory is accounted for with two processes: "familiarity" when generally recognizing an item and "recollection" when retrieving the full contextual details bound with the item. We tested a combination of item recognition confidence and source memory, focusing upon three conditions: "item-only hits with source unknown" ('item familiarity'), "low-confidence hits with correct source memory" ('context familiarity'), and "high-confidence hits with correct source memory" ('recollection'). Behaviorally, context familiarity was slower than the others during item recognition, but faster during source memory. Electrophysiologically, a triple dissociation was evident in event-related potentials (ERPs), which was independently replicated. Context familiarity exhibited a negative effect from 800 to 1200 ms, differentiated from positive ERPs for item-familiarity (400-600 ms) and recollection (600-900 ms). These three conditions thus reflect mutually exclusive, fundamentally different processes of episodic memory, and we offer a new, tri-component model of memory. Context familiarity is a third distinct process of episodic memory.

A third kind of episodic memory: Context familiarity is distinct from item familiarity and recollection

Episodic memory is accounted for with two processes: 'familiarity' when generally recognizing an item and 'recollection' when retrieving the full contextual details bound with the item. Paradoxically, people sometimes report contextual information as familiar but without recollecting details, which is not easily accounted for by existing theories. We tested a combination of item recognition confidence and source memory, focusing upon 'item-only hits with source unknown' ('item familiarity'), 'low-confidence hits with correct source memory' ('context familiarity'), and 'high-confidence hits with correct source memory' ('recollection'). Results across multiple within-subjects (trial-wise) and between subjects (individual variability) levels indicated these were behaviorally and physiologically distinct. Behaviorally, a crossover interaction was evident in response times, with context familiarity being slower than each condition during item recognition, but faster during source memory. Electrophysiologically, a Condition x Time x Location triple dissociation was evident in event-related potentials (ERPs), which was then independently replicated. Context familiarity exhibited an independent negative central effect from 800-1200 ms, differentiated from positive ERPs for item-familiarity (400 to 600 ms) and recollection (600 to 900 ms). These three conditions thus reflect mutually exclusive, fundamentally different processes of episodic memory. Context familiarity is a third distinct process of episodic memory.

Summary

Memory for past events is widely believed to operate through two different processes: one called 'recollection' when retrieving confident, specific details of a memory, and another called 'familiarity' when only having an unsure but conscious awareness that an item was experienced before. When people successfully retrieve details such as the source or context of a prior event, it has been assumed to reflect recollection. We demonstrate that familiarity of context is functionally distinct from familiarity of items and recollection and offer a new, tri-component model of memory. The three memory responses were differentiated across multiple behavioral and brain wave measures. What has traditionally been thought to be two kinds of memory processes are actually three, becoming evident when using sensitive enough multi-measures. Results are independently replicated across studies from different labs. These data reveal that context familiarity is a third process of human episodic memory.

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

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

The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond

As the pace of research in implantable neurotechnology increases, it is important to take a step back and see if the promise lives up to our intentions. While direct electrical stimulation applied intracranially has been used for the treatment of various neurological disorders, such as Parkinson's, epilepsy, clinical depression, and Obsessive-compulsive disorder, the effectiveness can be highly variable. One perspective is that the inability to consistently treat these neurological disorders in a standardized way is due to multiple, interlaced factors, including stimulation parameters, location, and differences in underlying network connectivity, leading to a trial-and-error stimulation approach in the clinic. An alternate view, based on a growing knowledge from neural data, is that variability in this input (stimulation) and output (brain response) relationship may be more predictable and amenable to standardization, personalization, and, ultimately, therapeutic implementation. In this review, we assert that the future of human brain neurostimulation, via direct electrical stimulation, rests on deploying standardized, constrained models for easier clinical implementation and informed by intracranial data sets, such that diverse, individualized therapeutic parameters can efficiently produce similar, robust, positive outcomes for many patients closer to a prescriptive model. We address the pathway needed to arrive at this future by addressing three questions, namely: (1) why aren't we already at this prescriptive future?; (2) how do we get there?; (3) how far are we from this Neurostimulationist prescriptive future? We first posit that there are limited and predictable ways, constrained by underlying networks, for direct electrical stimulation to induce changes in the brain based on past literature. We then address how identifying underlying individual structural and functional brain connectivity which shape these standard responses enable targeted and personalized neuromodulation, bolstered through large-scale efforts, including machine learning techniques, to map and reverse engineer these input-output relationships to produce a good outcome and better identify underlying mechanisms. This understanding will not only be a major advance in enabling intelligent and informed design of neuromodulatory therapeutic tools for a wide variety of neurological diseases, but a shift in how we can predictably, and therapeutically, prescribe stimulation treatments the human brain.

Refining Brain Stimulation Therapies: An Active Learning Approach to Personalization

Brain stimulation holds promise for treating brain disorders, but personalizing therapy remains challenging. Effective treatment requires establishing a functional link between stimulation parameters and brain response, yet traditional methods like random sampling (RS) are inefficient and costly. To overcome this, we developed an active learning (AL) framework that identifies optimal relationships between stimulation parameters and brain response with fewer experiments. We validated this framework through three experiments: (1) in silico modeling with synthetic data from a Parkinson's disease model, (2) in silico modeling with real data from a non-human primate, and (3) in vivo modeling with a real-time rat optogenetic stimulation experiment. In each experiment, we compared AL models to RS models, using various query strategies and stimulation parameters (amplitude, frequency, pulse width). AL models consistently outperformed RS models, achieving lower error on unseen test data in silico (p<0.0056, N=1,000) and in vivo (p=0.0036, N=20). This approach represents a significant advancement in brain stimulation, potentially improving both research and clinical applications by making them more efficient and effective. Our findings suggest that AL can substantially reduce the cost and time required for developing personalized brain stimulation therapies, paving the way for more effective and accessible treatments for brain disorders.

Theta-burst direct electrical stimulation remodels human brain networks

Theta-burst stimulation (TBS), a patterned brain stimulation technique that mimics rhythmic bursts of 3-8 Hz endogenous brain rhythms, has emerged as a promising therapeutic approach for treating a wide range of brain disorders, though the neural mechanism of TBS action remains poorly understood. We investigated the neural effects of TBS using intracranial EEG (iEEG) in 10 pre-surgical epilepsy participants undergoing intracranial monitoring. Here we show that individual bursts of direct electrical TBS at 29 frontal and temporal sites evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic local field potential voltage changes over the course of stimulation presentations, including either increasing or decreasing responses, suggestive of short-term plasticity. Stronger stimulation augmented the mean TBS response amplitude and spread with more recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific with stronger TBS responses observed in regions with strong baseline stimulation effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, we could use these measures to predict stable and varying (e.g. short-term plasticity) TBS response locations. Future work may integrate pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.

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

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

Evoking artificial speech perception through invasive brain stimulation for brain-computer interfaces: current challenges and future perspectives

Encoding artificial perceptions through brain stimulation, especially that of higher cognitive functions such as speech perception, is one of the most formidable challenges in brain-computer interfaces (BCI). Brain stimulation has been used for functional mapping in clinical practices for the last 70 years to treat various disorders affecting the nervous system, including epilepsy, Parkinson's disease, essential tremors, and dystonia. Recently, direct electrical stimulation has been used to evoke various forms of perception in humans, ranging from sensorimotor, auditory, and visual to speech cognition. Successfully evoking and fine-tuning artificial perceptions could revolutionize communication for individuals with speech disorders and significantly enhance the capabilities of brain-computer interface technologies. However, despite the extensive literature on encoding various perceptions and the rising popularity of speech BCIs, inducing artificial speech perception is still largely unexplored, and its potential has yet to be determined. In this paper, we examine the various stimulation techniques used to evoke complex percepts and the target brain areas for the input of speech-like information. Finally, we discuss strategies to address the challenges of speech encoding and discuss the prospects of these approaches.

Modulation of hippocampal theta oscillations via deep brain stimulation of the parietal cortex depends on cognitive state

The angular gyrus (AG) and posterior cingulate cortex (PCC) demonstrate extensive structural and functional connectivity with the hippocampus and other core recollection network regions. Consequently, recent studies have explored neuromodulation targeting these and other regions as a potential strategy for restoring function in memory disorders such as Alzheimer's Disease. However, determining the optimal approach for neuromodulatory devices requires understanding how parameters like selected stimulation site, cognitive state during modulation, and stimulation duration influence the effects of deep brain stimulation (DBS) on electrophysiological features relevant to episodic memory. We report experimental data examining the effects of high-frequency stimulation delivered to the AG or PCC on hippocampal theta oscillations during the memory encoding (study) or retrieval (test) phases of an episodic memory task. Results showed selective enhancement of anterior hippocampal slow theta oscillations with stimulation of the AG preferentially during memory retrieval. Conversely, stimulation of the PCC attenuated slow theta oscillations. We did not observe significant behavioral effects in this (open-loop) stimulation experiment, suggesting that neuromodulation strategies targeting episodic memory performance may require more temporally precise stimulation approaches.

EEG decoders track memory dynamics

Encoding- and retrieval-related neural activity jointly determine mnemonic success. We ask whether electroencephalographic activity can reliably predict encoding and retrieval success on individual trials. Each of 98 participants performed a delayed recall task on 576 lists across 24 experimental sessions. Logistic regression classifiers trained on spectral features measured immediately preceding spoken recall of individual words successfully predict whether or not those words belonged to the target list. Classifiers trained on features measured during word encoding also reliably predict whether those words will be subsequently recalled and further predict the temporal and semantic organization of the recalled items. These findings link neural variability predictive of successful memory with item-to-context binding, a key cognitive process thought to underlie episodic memory function.

A platform for brain network sensing and stimulation with quantitative behavioral tracking: Application to limbic circuit epilepsy

Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures. These seizures often originate from limbic networks and people also experience chronic comorbidities related to memory, mood, and sleep (MMS). Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is a proven therapy, but the optimal stimulation parameters remain unclear. We developed a neurotechnology platform for tracking seizures and MMS to enable data streaming between an investigational brain sensing-stimulation implant, mobile devices, and a cloud environment. Artificial Intelligence algorithms provided accurate catalogs of seizures, interictal epileptiform spikes, and wake-sleep brain states. Remotely administered memory and mood assessments were used to densely sample cognitive and behavioral response during ANT-DBS. We evaluated the efficacy of low-frequency versus high-frequency ANT-DBS. They both reduced seizures, but low-frequency ANT-DBS showed greater reductions and better sleep and memory. These results highlight the potential of synchronized brain sensing and behavioral tracking for optimizing neuromodulation therapy.

Target Engagement and Brain State Dependence of Transcranial Magnetic Stimulation: Implications for Clinical Practice

Transcranial magnetic stimulation (TMS) is capable of noninvasively inducing lasting neuroplastic changes when applied repetitively across multiple treatment sessions. In recent years, repetitive TMS has developed into an established evidence-based treatment for various neuropsychiatric disorders such as depression. Despite significant advancements in our understanding of the mechanisms of action of TMS, there is still much to learn about how these mechanisms relate to the clinical effects observed in patients. If there is one thing about TMS that we know for sure, it is that TMS effects are state dependent. In this review, we describe how the effects of TMS on brain networks depend on various factors, including cognitive brain state, oscillatory brain state, and recent brain state history. These states play a crucial role in determining the effects of TMS at the moment of stimulation and are therefore directly linked to what is referred to as target engagement in TMS therapy. There is no control over target engagement without considering the different brain state dependencies of our TMS intervention. Clinical TMS protocols are largely ignoring this fundamental principle, which may explain the large variability and often still limited efficacy of TMS treatments. We propose that after almost 30 years of research on state dependency of TMS, it is time to change standard clinical practice by taking advantage of this fundamental principle. Rather than ignoring TMS state dependency, we can use it to our clinical advantage to improve the effectiveness of TMS treatments.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories

Objective

Here, we demonstrate the first successful use of static neural stimulation patterns for specific information content. These static patterns were derived by a model that was applied to a subject's own hippocampal spatiotemporal neural codes for memory.

Approach

We constructed a new model of processes by which the hippocampus encodes specific memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of targeted content into short-term memory. A memory decoding model (MDM) of hippocampal CA3 and CA1 neural firing was computed which derives a stimulation pattern for CA1 and CA3 neurons to be applied during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task.

Main results

MDM electrical stimulation delivered to the CA1 and CA3 locations in the hippocampus during the sample phase of DMS trials facilitated memory of images from the DMS task during a delayed recognition (DR) task that also included control images that were not from the DMS task. Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance. Across patients with impaired memory that received bilateral stimulation, significant changes in over 37.9% of patient and category combinations was seen with the changes in memory performance show a ratio of increased to decreased performance of over 4 to 1. Modification of memory performance was dependent on whether memory function was intact or impaired, and if stimulation was applied bilaterally or unilaterally, with nearly all increase in performance seen in subjects with impaired memory receiving bilateral stimulation.

Significance

These results demonstrate that memory encoding in patients with impaired memory function can be facilitated for specific memory content, which offers a stimulation method for a future implantable neural prosthetic to improve human memory.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered the stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

Intracranial Neurofeedback Modulating Neural Activity in the Mesial Temporal Lobe During Memory Encoding: A Pilot Study

Removal of the mesial temporal lobe (MTL) is an established surgical procedure that leads to seizure freedom in patients with intractable MTL epilepsy; however, it carries the potential risk of memory damage. Neurofeedback (NF), which regulates brain function by converting brain activity into perceptible information and providing feedback, has attracted considerable attention in recent years for its potential as a novel complementary treatment for many neurological disorders. However, no research has attempted to artificially reorganize memory functions by applying NF before resective surgery to preserve memory functions. Thus, this study aimed (1) to construct a memory NF system that used intracranial electrodes to feedback neural activity on the language-dominant side of the MTL during memory encoding and (2) to verify whether neural activity and memory function in the MTL change with NF training. Two intractable epilepsy patients with implanted intracranial electrodes underwent at least five sessions of memory NF training to increase the theta power in the MTL. There was an increase in theta power and a decrease in fast beta and gamma powers in one of the patients in the late stage of memory NF sessions. NF signals were not correlated with memory function. Despite its limitations as a pilot study, to our best knowledge, this study is the first to report that intracranial NF may modulate neural activity in the MTL, which is involved in memory encoding. The findings provide important insights into the future development of NF systems for the artificial reorganization of memory functions.

Hippocampal activity predicts contextual misattribution of false memories

Failure of contextual retrieval can lead to false recall, wherein people retrieve an item or experience that occurred in a different context or did not occur at all. Whereas the hippocampus is thought to play a crucial role in memory retrieval, we lack understanding of how the hippocampus supports retrieval of items related to a target context while disregarding related but irrelevant information. Using direct electrical recordings from the human hippocampus, we investigate the neural process underlying contextual misattribution of false memories. In two large datasets, we characterize key physiological differences between correct and false recalls that emerge immediately prior to vocalization. By differentiating between false recalls that share high or low contextual similarity with the target context, we show that low-frequency activity (6 to 18 Hz) in the hippocampus tracks similarity between the current and retrieved context. Applying multivariate decoding methods, we were able to reliably predict the contextual source of the to-be-recalled item. Our findings elucidate one of the hallmark features of episodic memory: our ability to distinguish between memories that were formed on different occasions.

Observing memory encoding while it unfolds: Functional interpretation and current debates regarding ERP subsequent memory effects

Our ability to remember the past depends on neural processes set in train in the moment an event is experienced. These processes can be studied by segregating brain activity according to whether an event is later remembered or forgotten. The present review integrates a large number of studies examining this differential brain activity, labeled subsequent memory effect (SME), with the ERP technique, into a functional organization and discusses routes for further research. Based on the reviewed literature, we suggest that memory encoding is implemented by multiple processes, typically reflected in three functionally different subcomponents of the ERP SME elicited by study stimuli, which presumably interact with preparatory SME activity preceding the to be encoded event. We argue that ERPs are a valuable method in the SME paradigm because they have a sufficiently high temporal resolution to disclose the subcomponents of encoding-related brain activity. Implications of the proposed functional organization for future studies using the SME procedure in basic and applied settings will be discussed.

Decoding Depression Severity From Intracranial Neural Activity

BACKGROUND

Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis.

METHODS

We recorded high-density neural activity from intracranial electrodes implanted in depression-relevant prefrontal cortical regions in 3 human subjects with severe depression. Neural recordings were labeled with depression severity scores across a wide dynamic range using an adaptive assessment that allowed sampling with a temporal frequency greater than that possible with typical rating scales. We modeled these data using regularized regression techniques with region selection to decode depression severity from the prefrontal recordings.

RESULTS

Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all 3 subjects. Relaxing this constraint revealed unique, individual-specific sets of spatiospectral features predictive of symptom severity, reflecting the heterogeneous nature of depression.

CONCLUSIONS

The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.

Paving the Way for Memory Enhancement: Development and Examination of a Neurofeedback System Targeting the Medial Temporal Lobe

Neurofeedback (NF) shows promise in enhancing memory, but its application to the medial temporal lobe (MTL) still needs to be studied. Therefore, we aimed to develop an NF system for the memory function of the MTL and examine neural activity changes and memory task score changes through NF training. We created a memory NF system using intracranial electrodes to acquire and visualise the neural activity of the MTL during memory encoding. Twenty trials of a tug-of-war game per session were employed for NF and designed to control neural activity bidirectionally (Up/Down condition). NF training was conducted with three patients with drug-resistant epilepsy, and we observed an increasing difference in NF signal between conditions (Up-Down) as NF training progressed. Similarities and negative correlation tendencies between the transition of neural activity and the transition of memory function were also observed. Our findings demonstrate NF's potential to modulate MTL activity and memory encoding. Future research needs further improvements to the NF system to validate its effects on memory functions. Nonetheless, this study represents a crucial step in understanding NF's application to memory and provides valuable insights into developing more efficient memory enhancement strategies.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

Perception and memory retrieval states are reflected in distributed patterns of background functional connectivity

The same visual input can serve as the target of perception or as a trigger for memory retrieval depending on whether cognitive processing is externally oriented (perception) or internally oriented (memory retrieval). While numerous human neuroimaging studies have characterized how visual stimuli are differentially processed during perception versus memory retrieval, perception and memory retrieval may also be associated with distinct neural states that are independent of stimulus-evoked neural activity. Here, we combined human fMRI with full correlation matrix analysis (FCMA) to reveal potential differences in "background" functional connectivity across perception and memory retrieval states. We found that perception and retrieval states could be discriminated with high accuracy based on patterns of connectivity across (1) the control network, (2) the default mode network (DMN), and (3) retrosplenial cortex (RSC). In particular, clusters in the control network increased connectivity with each other during the perception state, whereas clusters in the DMN were more strongly coupled during the retrieval state. Interestingly, RSC switched its coupling between networks as the cognitive state shifted from retrieval to perception. Finally, we show that background connectivity (1) was fully independent from stimulus-related variance in the signal and, further, (2) captured distinct aspects of cognitive states compared to traditional classification of stimulus-evoked responses. Together, our results reveal that perception and memory retrieval are associated with sustained cognitive states that manifest as distinct patterns of connectivity among large-scale brain networks.

Re-expression of CA1 and entorhinal activity patterns preserves temporal context memory at long timescales

Converging, cross-species evidence indicates that memory for time is supported by hippocampal area CA1 and entorhinal cortex. However, limited evidence characterizes how these regions preserve temporal memories over long timescales (e.g., months). At long timescales, memoranda may be encountered in multiple temporal contexts, potentially creating interference. Here, using 7T fMRI, we measured CA1 and entorhinal activity patterns as human participants viewed thousands of natural scene images distributed, and repeated, across many months. We show that memory for an image's original temporal context was predicted by the degree to which CA1/entorhinal activity patterns from the first encounter with an image were re-expressed during re-encounters occurring minutes to months later. Critically, temporal memory signals were dissociable from predictors of recognition confidence, which were carried by distinct medial temporal lobe expressions. These findings suggest that CA1 and entorhinal cortex preserve temporal memories across long timescales by coding for and reinstating temporal context information.

Biomarker-guided neuromodulation aids memory in traumatic brain injury

Traumatic brain injury (TBI) is a leading cause of cognitive disability in adults, often characterized by marked deficits in episodic memory and executive function. Prior studies have found that direct electrical stimulation of the temporal cortex yielded improved memory in epilepsy patients, but it is not clear if these results generalize to patients with a specific history of TBI. Here we asked whether applying closed-loop, direct electrical stimulation to lateral temporal cortex could reliably improve memory in a TBI cohort. Among a larger group of patients undergoing neurosurgical evaluation for refractory epilepsy, we recruited a subset of patients with a history of moderate-to-severe TBI. By analyzing neural data from indwelling electrodes as patients studied and recalled lists of words, we trained personalized machine-learning classifiers to predict momentary fluctuations in mnemonic function in each patient. We subsequently used these classifiers to trigger high-frequency stimulation of the lateral temporal cortex (LTC) at moments when memory was predicted to fail. This strategy yielded a 19% boost in recall performance on stimulated as compared with non-stimulated lists (P = 0.012). These results provide a proof-of-concept for using closed-loop stimulation of the brain in treatment of TBI-related memory impairment.

State-specific modulation of mood using intracranial electrical stimulation of the orbitofrontal cortex

BACKGROUND

Orbitofrontal cortex (OFC) is a promising target for intracranial electrical stimulation (iES) aimed at improving mood states. However, knowledge gaps remain regarding the underlying neural mechanisms of iES effects, such as the effect of the OFC target in comparison with other emotional network targets, the impact of brain state at the time of stimulation, and the neural response induced by iES at both local and network scales.

OBJECTIVE

Our study aims to address the neural mechanisms underlying the effects of iES in improving mood states.

METHODS

We conducted a study in 24 epilepsy patients who received iES through implanted electrodes in the emotional network and compared the effects of iES on multiple targets in the emotional network.

RESULTS

We found that only iES applied to the orbitofrontal cortex (OFC) led to mood improvement and changes in neural activity. We also observed that iES to the OFC suppressed the delta-theta power when the brain was in a low mood state. Moreover, the iES to the OFC decreased delta-theta power and increased gamma power at local regions within the emotional network, and enhanced the information flow through the frequency domain among regions within the emotional network.

CONCLUSIONS

These findings provide insight into the neural correlates of iES-induced mood improvement and support the potential of iES as a therapeutic intervention for mood disorders.

Direct brain recordings suggest a causal subsequent-memory effect

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analysing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output-a biomarker of successful encoding-tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas, in the prefrontal cortex, HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain's ability to learn new information.

Closed-Loop Deep Brain Stimulation for Psychiatric Disorders

ABSTRACT

Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.

A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans

Advances in technologies that can record and stimulate deep brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and restricted full-duplex bidirectional capability. In this study, we developed a wearable bidirectional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans and, consequently, bridge decades of neuroscientific findings across species.

Informative and uninformative prestimulus cues at encoding benefit familiarity and source memory

Previous research has shown that neural activity elicited by informative prestimulus cues during encoding differ with respect to subsequent memory outcomes. These findings indicate prestimulus cues create a "brain state" associated with subsequent memory that, potentially, also has downstream effects benefitting processes associated with successful encoding and subsequent memory performance. However, previous studies have not included the conditions necessary to appropriately test this latter assumption. The present study examines how informative and uninformative prestimulus encoding cues affect memory accuracy for upcoming stimuli compared to a no cue condition. At encoding, participants made one of two semantic judgments on words preceded by an informative prestimulus cue that identified the upcoming semantic judgment, an uninformative prestimulus cue that signalled an upcoming trial but no information about the semantic judgment, or no cue. Dual process estimates of familiarity, but not recollection, demonstrated a graded pattern with the informativeness of the prestimulus cues (i.e., informative > uninformative > no cues). Moreover, both informative and uninformative prestimulus cues enhanced subsequent source memory accuracy for the encoding task compared to the no cue condition. These findings suggest that prestimulus cues can strengthen the processes that support successful memory encoding and benefit subsequent familiarity and source memory.

Hippocampal Theta and Episodic Memory

Computational models of rodent physiology implicate hippocampal theta as a key modulator of learning and memory (Buzsáki and Moser, 2013; Lisman and Jensen, 2013), yet human hippocampal recordings have shown divergent theta correlates of memory formation. Herweg et al. (2020) suggest that decreases in memory-related broadband power mask narrowband theta increases. Their survey also notes that the theta oscillations appear most prominently in contrasts that isolate memory retrieval processes and when aggregating signals across large brain regions. We evaluate these hypotheses by analyzing human hippocampal recordings captured as 162 neurosurgical patients (n = 86 female) performed a free recall task. Using the Irregular-Resampling Auto-Spectral Analysis (IRASA) to separate broad and narrowband components of the field potential, we show that (1) broadband and narrowband components of theta exhibit opposite effects, with broadband signals decreasing and narrowband theta increasing during successful encoding; (2) whereas low-frequency theta oscillations increase before successful recall, higher-frequency theta and alpha oscillations decrease, masking the positive effect of theta when aggregating across the full band; and (3) the effects of theta on memory encoding and retrieval do not differ between reference schemes that accentuate local signals (bipolar) and those that aggregate signals globally (whole-brain average). In line with computational models that ascribe a fundamental role for hippocampal theta in memory, our large-scale study of human hippocampal recordings shows that 3-4 Hz theta oscillations reliably increase during successful memory encoding and before spontaneous recall of previously studied items.SIGNIFICANCE STATEMENT Analyzing recordings from 162 participants, we resolve a long-standing question regarding the role of hippocampal theta oscillations in the formation and retrieval of episodic memories. We show that broadband spectral changes confound estimates of narrowband theta activity, thereby accounting for inconsistent results in the literature. After accounting for broadband effects, we find that increased theta activity marks successful encoding and retrieval of episodic memories, supporting rodent models that ascribe a key role for hippocampal theta in memory function.

Neuroprosthetics: from sensorimotor to cognitive disorders

Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.

Advances in the understanding and enhancement of the human cognitive functions of learning and memory

Learning and memory are among the key cognitive functions that drive the human experience. As such, any defective condition associated with these cognitive domains could affect our navigation through everyday life. For years, researchers have been working toward having a clear understanding of how learning and memory work, as well as ways to improve them. Many advances have been made, as well as some challenges that have also been faced in the process. That notwithstanding, there are prospects with regards to the frontier of the enhancement of learning and memory in humans. This review article selectively highlights four broad areas of focus in research into the understanding and enhancement of learning and memory. Brain stimulation, effects of sleep, effects of stress and emotion, and synaptic plasticity are the main focal areas of this review, in terms of some pivotal research works, findings and theories.

Decoding declarative memory process for predicting memory retrieval based on source localization

Many studies have focused on understanding memory processes due to their importance in daily life. Differences in timing and power spectra of brain signals during encoding task have been linked to later remembered items and were recently used to predict memory retrieval performance. However, accuracies remain low when using non-invasive methods for acquiring brain signals, mainly due to the low spatial resolution. This study investigates the prediction of successful retrieval using estimated source activity corresponding either to cortical or subcortical structures through source localization. Electroencephalogram (EEG) signals were recorded while participants performed a declarative memory task. Frequency-time analysis was performed using signals from encoding and retrieval tasks to confirm the importance of neural oscillations and their relationship with later remembered and forgotten items. Significant differences in the power spectra between later remembered and forgotten items were found before and during the presentation of the stimulus in the encoding task. Source activity estimation revealed differences in the beta band power over the medial parietal and medial prefrontal areas prior to the presentation of the stimulus, and over the cuneus and lingual areas during the presentation of the stimulus. Additionally, there were significant differences during the stimuli presentation during the retrieval task. Prediction of later remembered items was performed using surface potentials and estimated source activity. The results showed that source localization increases classification performance compared to the one using surface potentials. These findings support the importance of incorporating spatial features of neural activity to improve the prediction of memory retrieval.

Hotspot of human verbal memory encoding in the left anterior prefrontal cortex

Background

Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation.

Methods

The areas that are critical for successful encoding of verbal memory as well as the underlying neural activities were determined directly in the human brain with intracranial electrophysiological recordings in epilepsy patients. We recorded a broad range of spectral activities across the cortex of 135 patients as they memorised word lists for subsequent free recall.

Findings

The greatest differences in the spectral power between encoding subsequently recalled and forgotten words were found in low theta frequency (3–5 Hz) activities of the left anterior prefrontal cortex. This subsequent memory effect was proportionally greater in the lower frequency bands and in the more anterior cortical regions. We found the peak of this memory signal in a distinct part of the prefrontal cortex at the junction between the Broca's area and the frontal pole. The memory effect in this confined area was significantly higher (Tukey–Kramer test, p<0.05) than in other anatomically distinct areas.

Interpretation

Our results suggest a focal hotspot of human verbal memory encoding located in the higher-order processing region of the prefrontal cortex, which presents a prospective target for modulating cognitive functions in the human patients. The memory effect provides an electrophysiological biomarker of low frequency neural activities, at distinct times of memory encoding, and in one hotspot location in the human brain.

Funding

Open-access datasets were originally collected as part of a BRAIN Initiative project called Restoring Active Memory (RAM) funded by the Defence Advanced Research Project Agency (DARPA). CT, ML, MTK and this research were supported from the First Team grant of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Mechanisms for Cognitive Impairment in Epilepsy: Moving Beyond Seizures

There has been a major emphasis on defining the role of seizures in the causation of cognitive impairments like memory deficits in epilepsy. Here we focus on an alternative hypothesis behind these deficits, emphasizing the mechanisms of information processing underlying healthy cognition characterized as rate, temporal and population coding. We discuss the role of the underlying etiology of epilepsy in altering neural networks thereby leading to both the propensity for seizures and the associated cognitive impairments. In addition, we address potential treatments that can recover the network function in the context of a diseased brain, thereby improving both seizure and cognitive outcomes simultaneously. This review shows the importance of moving beyond seizures and approaching the deficits from a system-level perspective with the guidance of network neuroscience.

Electrical Wada for pre-surgical memory testing: a case report

We report a case study of a surgical candidate, a 51-year-old woman with left temporal lobe epilepsy, who failed a left injection intracarotid amobarbital procedure (e.g., Wada test), scoring 0 of 8 items. This raised concerns for postoperative memory decline. However, the patient was uninterested in a neuromodulatory approach and wished to be reconsidered for surgery. A stereotactic laser amygdalohippocampotomy (SLAH) was considered, encouraging the need for an alternative test to evaluate risk of memory decline. We developed a novel approach to testing memory during stimulation of a depth electrode implanted in the hippocampus, i.e., an electric Wada. During multiple stimulation trials across a range of amplitudes, the patient scored up to 8 of 8 items, which suggested strong contralateral memory support. The surgical team proceeded with a radiofrequency ablation and a subsequent SLAH. The patient remains seizure-free at 12 months post SLAH with no evidence of verbal or visuospatial memory decline based on a post-surgical neuropsychological battery. We believe that this case study provides a proof of concept for the feasibility and possible utility of an electric version of the Wada procedure. Future studies are needed to develop an optimal paradigm and to validate this approach.

Decoding naturalistic affective behaviour from spectro-spatial features in multiday human iEEG

The neurological basis of affective behaviours in everyday life is not well understood. We obtained continuous intracranial electroencephalography recordings from the human mesolimbic network in 11 participants with epilepsy and hand-annotated spontaneous behaviours from 116 h of multiday video recordings. In individual participants, binary random forest models decoded affective behaviours from neutral behaviours with up to 93% accuracy. Both positive and negative affective behaviours were associated with increased high-frequency and decreased low-frequency activity across the mesolimbic network. The insula, amygdala, hippocampus and anterior cingulate cortex made stronger contributions to affective behaviours than the orbitofrontal cortex, but the insula and anterior cingulate cortex were most critical for differentiating behaviours with observable affect from those without. In a subset of participants (N = 3), multiclass decoders distinguished amongst the positive, negative and neutral behaviours. These results suggest that spectro-spatial features of brain activity in the mesolimbic network are associated with affective behaviours of everyday life.

Local and distant cortical responses to single pulse intracranial stimulation in the human brain are differentially modulated by specific stimulation parameters

BACKGROUND

Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses.

OBJECTIVE

To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated.

METHODS

We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites).

RESULTS

Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation.

CONCLUSION

These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.

Long-term changes in functional connectivity improve prediction of responses to intracranial stimulation of the human brain

OBJECTIVE

Targeted electrical stimulation of the brain perturbs neural networks and modulates their rhythmic activity both at the site of stimulation and at remote brain regions. Understanding, or even predicting, this neuromodulatory effect is crucial for any therapeutic use of brain stimulation. The objective of this study was to investigate if brain network properties prior to stimulation sessions hold associative and predictive value in understanding the neuromodulatory effect of electrical stimulation in a clinical context.

APPROACH

We analysed the stimulation responses in 131 stimulation sessions across 66 patients with focal epilepsy recorded through intracranial electroencephalogram (iEEG). We considered functional and structural connectivity features as predictors of the response at every iEEG contact. Taking advantage of multiple recordings over days, we also investigated how slow changes in interictal functional connectivity (FC) ahead of the stimulation, representing the long-term variability of FC, relate to stimulation responses.

MAIN RESULTS

The long-term variability of FC exhibits strong association with the stimulation-induced increases in delta and theta band power. Furthermore, we show through cross-validation that long-term variability of FC improves prediction of responses above the performance of spatial predictors alone.

SIGNIFICANCE

This study highlights the importance of the slow dynamics of functional connectivity in the prediction of brain stimulation responses. Furthermore, these findings can enhance the patient-specific design of effective neuromodulatory protocols for therapeutic interventions.

Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry

Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.

CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain

The emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor, assess, and control these higher brain functions without acquiring signals from the brain. Features of gaze position and pupil dilation can be effectively used to track our attention in healthy mental processes, to enable interaction in disorders of consciousness, or to even predict memory performance in various brain diseases. In this perspective article, we propose the term ‘CyberEye’ to encompass emerging cognitive applications of eye-tracking interfaces for neuroscience research, clinical practice, and the biomedical industry. As CyberEye technologies continue to develop, we expect BCIs to become less dependent on brain activities, to be less invasive, and to thus be more applicable.

Deep brain stimulation: is it time to change gears by closing the loop?

Objective.Adaptive deep brain stimulation (aDBS) is a form of invasive stimulation that was conceived to overcome the technical limitations of traditional DBS, which delivers continuous stimulation of the target structure without considering patients' symptoms or status in real-time. Instead, aDBS delivers on-demand, contingency-based stimulation. So far, aDBS has been tested in several neurological conditions, and will be soon extensively studied to translate it into clinical practice. However, an exhaustive description of technical aspects is still missing.Approach.in this topical review, we summarize the knowledge about the current (and future) aDBS approach and control algorithms to deliver the stimulation, as reference for a deeper undestending of aDBS model.Main results.We discuss the conceptual and functional model of aDBS, which is based on the sensing module (that assesses the feedback variable), the control module (which interpretes the variable and elaborates the new stimulation parameters), and the stimulation module (that controls the delivery of stimulation), considering both the historical perspective and the state-of-the-art of available biomarkers.Significance.aDBS modulates neuronal circuits based on clinically relevant biofeedback signals in real-time. First developed in the mid-2000s, many groups have worked on improving closed-loop DBS technology. The field is now at a point in conducting large-scale randomized clinical trials to translate aDBS into clinical practice. As we move towards implanting brain-computer interfaces in patients, it will be important to understand the technical aspects of aDBS.

Neurons in the human medial temporal lobe track multiple temporal contexts during episodic memory processing

Episodic memory requires associating items with temporal context, a process for which the medial temporal lobe (MTL) is critical. This study uses recordings from 27 human subjects who were undergoing surgical intervention for intractable epilepsy. These same data were also utilized in Umbach et al. (2020). We identify 103 memory-sensitive neurons in the hippocampus and entorhinal cortex, whose firing rates predicted successful episodic memory encoding as subjects performed a verbal free recall task. These neurons exhibit important properties. First, as predicted from the temporal context model, they demonstrate reinstatement of firing patterns observed during encoding at the time of retrieval. The magnitude of reinstatement predicted the tendency of subjects to cluster retrieved memory items according to input serial position. Also, we found that spiking activity of these neurons was locked to the phase of hippocampal theta oscillations, but that the mean phase of spiking shifted between memory encoding versus retrieval. This unique observation is consistent with predictions of the “Separate Phases at Encoding And Retrieval (SPEAR)” model. Together, the properties we identify for memory-sensitive neurons characterize direct electrophysiological mechanisms for the representation of contextual information in the human MTL.