Accelerated long-term forgetting of recall and recognition memory in people with epilepsy.

PURPOSE: Persons with epilepsy (PWE) report memory deficits as one of the most distressing aspects of their disorder. Recently, a long-term memory deficit known as Accelerated Long-Term Forgetting (ALF) has been described in PWE. ALF is characterized by the initial retention of learned information, followed by an accelerated rate of memory decay. However, the rate of ALF varies widely across literature and it is unclear how it impacts different memory retrieval types. The current study aimed to capture the time course of ALF on both free recall and recognition memory using a movie-based task in PWE. METHODS: A sample of 30 PWE and 30 healthy comparison (HC) subjects watched a nature documentary and were tested on their recall and recognition of the film's content immediately after viewing and at delays of 24 hours, 48 hours, and 72 hours. Participants also rated the confidence they had in their recognition memory trial responses. RESULTS: For recall, PWE exhibit ALF at 72 hours (ß = -19.840, SE = 3.743, z(226) = -5.301, p < 0.001). For recognition, PWE had decreased performance compared to controls at the 24-hour (ß = -10.165, SE = 4.174, z(224) = -3.166, p = 0.004), 48-hour (ß = -8.113, SE = 3.701, z(224) = -2.195, p = 0.044), and 72-hour (ß = -10.794, SE = 3.017, z(224) = -3.295, p = 0.003) delays. The PWE group showed positive correlations (tau = 0.165, p < 0.001) between confidence ratings and accuracy, with higher confidence reflecting successful recognition. PWE were 49% less likely to answer either retrieval type correctly at 72 hours (OR 0.51, 95% CI [0.35, 0.74], p < 0.001). Left hemispheric seizure onset decreased the odds of successful retrieval by 88% (OR 0.12, 95% CI [0.01, 0.42], p = 0.019). CONCLUSIONS: These findings provide evidence of ALF in PWE, with a differential impact on recall and recognition memory. This further supports the call to include ALF assessments in standard memory evaluations in PWE. Additionally, identifying the neural correlates of ALF in the future will be important in developing targeted therapies to alleviate the burden of memory impairment for PWE.

Supervised machine learning to predict reduced depression severity in people with epilepsy through epilepsy self-management intervention.

OBJECTIVE: To develop a classifier that predicts reductions in depression severity in people with epilepsy after participation in an epilepsy self-management intervention. METHODS: Ninety-three people with epilepsy from three epilepsy self-management randomized controlled trials from the Managing Epilepsy Well (MWE) Network integrated research database met the inclusion criteria. Supervised machine learning algorithms were utilized to develop prediction models for changes in self-reported depression symptom severity. Features considered by the machine learning classifiers include age, gender, race, ethnicity, education, study type, baseline quality of life, and baseline depression symptom severity. The models were trained and evaluated on their ability to predict clinically meaningful improvement (i.e., a reduction of greater than three points on the nine-item Patient Health Questionnaire (PHQ-9)) between baseline and follow-up (<=12 weeks) depression scores. Models tested were a Multilayer Perceptron (ML), Random Forest (RF), Support Vector Machine (SVM), Logistic Regression with Stochastic Gradient Descent (SGD), K-nearest Neighbors (KNN), and Gradient Boosting (GB). A separate, outside dataset of 41 people with epilepsy was used in a validation exercise to examine the top-performing model's generalizability and performance with external data. RESULTS: All six classifiers performed better than our baseline mode classifier. Support Vector Machine had the best overall performance (average area under the curve [AUC] = 0.754, highest subpopulation AUC = 0.963). Our analysis of the SVM features revealed that higher baseline depression symptom severity, study type (i.e., intervention program goals), higher baseline quality of life, and race had the strongest influence on increasing the likelihood that a subject would experience a clinically meaningful improvement in depression scores. From the validation exercise, our top-performing SVM model performed similarly or better than the average SVM model with the outside dataset (average AUC = 0.887). SIGNIFICANCE: We trained an SVM classifier that offers novel insight into subject-specific features that are important for predicting a clinically meaningful improvement in subjective depression scores after enrollment in a self-management program. We provide evidence for machine learning to select subjects that may benefit most from a self-management program and indicate important factors that self-management programs should collect to develop improved digital tools.

Factors correlated with intracranial interictal epileptiform discharges in refractory epilepsy.

OBJECTIVE: This study was undertaken to evaluate the influence that subject-specific factors have on intracranial interictal epileptiform discharge (IED) rates in persons with refractory epilepsy. METHODS: One hundred fifty subjects with intracranial electrodes performed multiple sessions of a free recall memory task; this standardized task controlled for subject attention levels. We utilized a dominance analysis to rank the importance of subject-specific factors based on their relative influence on IED rates. Linear mixed-effects models were employed to comprehensively examine factors with highly ranked importance. RESULTS: Antiseizure medication (ASM) status, time of testing, and seizure onset zone (SOZ) location were the highest-ranking factors in terms of their impact on IED rates. The average IED rate of electrodes in SOZs was 34% higher than the average IED rate of electrodes outside of SOZs (non-SOZ; p < .001). However, non-SOZ electrodes had similar IED rates regardless of the subject's SOZ location (p = .99). Subjects on older generation (p < .001) and combined generation (p < .001) ASM regimens had significantly lower IED rates relative to the group taking no ASMs; newer generation ASM regimens demonstrated a nonsignificant association with IED rates (p = .13). Of the ASMs included in this study, the following ASMs were associated with significant reductions in IED rates: levetiracetam (p < .001), carbamazepine (p < .001), lacosamide (p = .03), zonisamide (p = .01), lamotrigine (p = .03), phenytoin (p = .03), and topiramate (p = .01). We observed a nonsignificant association between time of testing and IED rates (morning-afternoon p = .15, morning-evening p = .85, afternoon-evening p = .26). SIGNIFICANCE: The current study ranks the relative influence that subject-specific factors have on IED rates and highlights the importance of considering certain factors, such as SOZ location and ASM status, when analyzing IEDs for clinical or research purposes.

Features of intracranial interictal epileptiform discharges associated with memory encoding.

OBJECTIVE: Interictal epileptiform discharges (IEDs) were shown to be associated with cognitive impairment in persons with epilepsy. Previous studies indicated that IED rate, location, timing, and spatial relation to the seizure onset zone could predict an IED's impact on memory encoding and retrieval if they occurred in lateral temporal, mesial temporal, or parietal regions. In this study, we explore the influence that other IED properties (e.g., amplitude, duration, white matter classification) have on memory performance. We were specifically interested in investigating the influence that lateral temporal IEDs have on memory encoding. METHODS: Two hundred sixty-one subjects with medication-refractory epilepsy undergoing intracranial electroencephalographic monitoring performed multiple sessions of a delayed free-recall task (n = 671). Generalized linear mixed models were utilized to examine the relationship between IED properties and memory performance. RESULTS: We found that increased IED rate, IEDs propagating in white matter, and IEDs localized to the left middle temporal region were associated with poorer memory performance. For lateral temporal IEDs, we observed a significant interaction between IED white matter categorization and amplitude, where IEDs with an increased amplitude and white matter propagation were associated with reduced memory performance. Additionally, changes in alpha power after an IED showed a significant positive correlation with memory performance. SIGNIFICANCE: Our results suggest that IED properties may be useful for predicting the impact an IED has on memory encoding. We provide an essential step toward understanding pathological versus potentially beneficial interictal epileptiform activity.

40-Hz auditory stimulation for intracranial interictal activity: A pilot study.

OBJECTIVES: To study the effects of auditory stimuli on interictal epileptiform discharge (IED) rates evident with intracranial monitoring. MATERIALS AND METHODS: Eight subjects undergoing intracranial EEG monitoring for refractory epilepsy participated in this study. Auditory stimuli consisted of a 40-Hz tone, a 440-Hz tone modulated by a 40-Hz sinusoid, Mozart's Sonata for Two Pianos in D Major (K448), and K448 modulated by a 40-Hz sinusoid (modK448). Subjects were stratified into high- and low-IED rate groups defined by baseline IED rates. Subject-level analyses identified individual responses to auditory stimuli, discerned specific brain regions with significant reductions in IED rates, and examined the influence auditory stimuli had on whole-brain sigma power (12-16 Hz). RESULTS: All subjects in the high baseline IED group had a significant 35.25% average reduction in IEDs during the 40-Hz tone; subject-level reductions localized to mesial and lateral temporal regions. Exposure to Mozart K448 showed significant yet less homogeneous responses. A post hoc analysis demonstrated two of the four subjects with positive IED responses had increased whole-brain power at the sigma frequency band during 40-Hz stimulation. CONCLUSIONS: Our study is the first to evaluate the relationship between 40-Hz auditory stimulation and IED rates in refractory epilepsy. We reveal that 40-Hz auditory stimuli may be a noninvasive adjunctive intervention to reduce IED burden. Our pilot study supports the future examination of 40-Hz auditory stimuli in a larger population of subjects with high baseline IED rates.

Neurostimulation for Memory Enhancement in Epilepsy.

PURPOSE OF REVIEW: Memory is one of the top concerns of epilepsy patients, but there are no known treatments to directly alleviate the memory deficits associated with epilepsy. Neurostimulation may provide new therapeutic tools to enhance memory in epilepsy patients. Here, we critically review recent investigations of memory enhancement using transcranial electrical stimulation (tES), transcranial magnetic stimulation (TMS), vagus nerve stimulation (VNS), chronic intracranial stimulation, and acute intracranial stimulation. RECENT FINDINGS: Existing literature suggests that transcranial direct current stimulation (tDCS) produces a small enhancement in memory in neuropsychological patients, but transcranial alternating current stimulation (tACS) and transcranial random noise stimulation (tRNS) have not been found to have an effect on memory. Most studies of transcranial magnetic stimulation (TMS) have found that TMS has no positive effect on memory. Vagus nerve stimulation can acutely enhance memory, while chronic therapy does not appear to alter memory performance. We found that there is the most evidence for significant memory enhancement using intracranial stimulation techniques, especially chronic stimulation of the fornix and task-responsive stimulation of the lateral temporal lobe. Presently, there are no existing therapeutic options for directly treating epilepy-related memory deficits. While neurostimulation technologies for memory enhancement are largely still in the experimental phase, neurostimulation appears promising as a future technique for treating epilepsy-related memory deficits.

Interictal epileptiform discharges impair word recall in multiple brain areas.

OBJECTIVES: Interictal epileptiform discharges (IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory. METHODS: Eighty epilepsy patients participated in a delayed free recall task while undergoing intracranial electroencephalography (EEG) monitoring. We analyzed the locations and timing of IEDs relative to the behavioral data in order to measure their effects on memory. RESULTS: Overall IED rates did not correlate with task performance across subjects (r = 0.03, p = 0.8). However, at a finer temporal scale, within-subject memory was negatively affected by IEDs during the encoding and recall periods of the task but not during the rest and distractor periods (p < 0.01, p < 0.001, p = 0.3, and p = 0.8, respectively). The effects of IEDs during encoding and recall were stronger in the left hemisphere than in the right (p < 0.05). Of six brain areas analyzed, IEDs in the inferior-temporal, medial-temporal, and parietal areas significantly affected memory (false discovery rate < 0.05). SIGNIFICANCE: These findings reveal a network of brain areas sensitive to IEDs with key nodes in temporal as well as parietal lobes. They also demonstrate the time-dependent effects of IEDs in this network on memory.

Probing the human brain at single-neuron resolution with high-density cortical recordings.

Recording in vivo from large numbers of neurons is a core neuroscience technique not typically possible in humans. In this issue of Neuron, Chung et al. (2022) show high-density acute recordings in human cortex using the Neuropixels probe.

AiED: Artificial intelligence for the detection of intracranial interictal epileptiform discharges.

OBJECTIVE: Deep learning provides an appealing solution for the ongoing challenge of automatically classifying intracranial interictal epileptiform discharges (IEDs). We report results from an automated method consisting of a template-matching algorithm and convolutional neural network (CNN) for the detection of intracranial IEDs ("AiED"). METHODS: 1000 intracranial electroencephalogram (EEG) epochs extracted randomly from 307 subjects with refractory epilepsy were annotated independently by two expert neurophysiologists. These annotated epochs were divided into 1062 two-second epochs with IEDs and 1428 two-second epochs without IEDs, which were transformed into spectrograms prior to training the neural network. The highest performing network was validated on an annotated external test set. RESULTS: The final network had an F1-score of 0.95 (95% CI: 0.91-0.98) and an average Area Under the Receiver Operating Characteristic of 0.98 (95% CI: 0.96-1.00). For the external test set, it showed an overall F1-score of 0.71, correctly identifying 100% of all high-amplitude IED complexes, 96.23% of all high-amplitude isolated IEDs, and 66.15% of all IEDs of atypical morphology. CONCLUSIONS: Template-matching combined with a CNN offers a fast, robust method for detecting intracranial IEDs. SIGNIFICANCE: "AiED" is generalizable and achieves comparable performance to human reviewers; it may support clinical and research EEG analyses.

Interictal Epileptiform Discharges are Task Dependent and are Associated with Lasting Electrocorticographic Changes.

The factors that control the occurrence of interictal epileptiform discharges (IEDs) are not well understood. We suspected that this phenomenon reflects an attention-dependent suppression of interictal epileptiform activity. We hypothesized that IEDs would occur less frequently when a subject viewed a task-relevant stimulus compared with viewing a blank screen. Furthermore, IEDs have been shown to impair memory when they occur in certain regions during the encoding or recall phases of a memory task. Although these discharges have a short duration, their impact on memory suggests that they have longer lasting electrophysiological effects. We found that IEDs were associated with an increase in low-frequency power and a change in the balance between low- and high-frequency oscillations for several seconds. We found that the occurrence of IEDs is modified by whether a subject is attending to a word displayed on screen or is observing a blank screen. In addition, we found that discharges in brain regions in every lobe impair memory. These findings elucidate the relationship between IEDs and memory impairment and reveal the task dependence of the occurrence of IEDs.

Musical components important for the Mozart K448 effect in epilepsy.

There is growing evidence for the efficacy of music, specifically Mozart's Sonata for Two Pianos in D Major (K448), at reducing ictal and interictal epileptiform activity. Nonetheless, little is known about the mechanism underlying this beneficial "Mozart K448 effect" for persons with epilepsy. Here, we measured the influence that K448 had on intracranial interictal epileptiform discharges (IEDs) in sixteen subjects undergoing intracranial monitoring for refractory focal epilepsy. We found reduced IEDs during the original version of K448 after at least 30-s of exposure. Nonsignificant IED rate reductions were witnessed in all brain regions apart from the bilateral frontal cortices, where we observed increased frontal theta power during transitions from prolonged musical segments. All other presented musical stimuli were associated with nonsignificant IED alterations. These results suggest that the "Mozart K448 effect" is dependent on the duration of exposure and may preferentially modulate activity in frontal emotional networks, providing insight into the mechanism underlying this response. Our findings encourage the continued evaluation of Mozart's K448 as a noninvasive, non-pharmacological intervention for refractory epilepsy.

Changes in Local Network Activity Approximated by Reverse Spike-Triggered Local Field Potentials Predict the Focus of Attention.

The effects of visual spatial attention on neuronal firing rates have been well characterized for neurons throughout the visual processing hierarchy. Interestingly, the mechanisms by which attention generates more or fewer spikes in response to a visual stimulus remain unknown. One possibility is that attention boosts the likelihood that synaptic inputs to a neuron result in spikes. We performed a novel analysis to measure local field potentials (LFPs) just prior to spikes, or reverse spike-triggered LFP "wavelets," for neurons recorded in primary visual cortex (V1) of monkeys performing a contrast change detection task requiring covert shifts in visual spatial attention. We used dimensionality reduction to define LFP wavelet shapes with single numerical values, and we found that LFP wavelet shape changes correlated with changes in neuronal firing rate. We then tested whether a simple classifier could predict monkeys' focus of attention from LFP wavelet shape. LFP wavelet shapes sampled in discrete windows were predictive of the locus of attention for some neuronal types. These findings suggest that LFP wavelets are a useful proxy for local network activity influencing spike generation, and changes in LFP wavelet shape are predictive of the focus of attention.

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.

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.