Calcium imaging is a versatile experimental approach capable of resolving single neurons with single-cell spatial resolution in the brain. Electrophysiological recordings provide high temporal, but limited spatial resolution, due to the geometrical inaccessibility of the brain. An approach that integrates the advantages of both techniques could provide new insights into functions of neural circuits. Here, we report a transparent, flexible neural electrode technology based on graphene, which enables simultaneous optical imaging and electrophysiological recording. We demonstrate that hippocampal slices can be imaged through transparent graphene electrodes by both confocal and two-photon microscopy without causing any light-induced artifacts in the electrical recordings. Graphene electrodes record high frequency bursting activity and slow synaptic potentials that are hard to resolve by multi-cellular calcium imaging. This transparent electrode technology may pave the way for high spatio-temporal resolution electrooptic mapping of the dynamic neuronal activity.
In the phenomenon of repetition suppression (RS), when a person views a stimulus, the neural activity involved in processing that item is relatively diminished if that stimulus had been previously viewed. Previous noninvasive imaging studies mapped the prevalence of RS for different stimulus types to identify brain regions involved in representing a range of cognitive information. However, these noninvasive findings are challenging to interpret because they do not provide information on how RS relates to the brain's electrophysiological activity. We examined the electrophysiological basis of RS directly using brain recordings from implanted electrocorticographic (ECoG) electrodes in neurosurgical patients. Patients performed a memory task during ECoG recording and we identified high-gamma signals (65–128 Hz) that distinguished the neuronal representation of specific memory items. We then compared the neural representation of each item between novel and repeated viewings. This revealed the presence of RS, in which the neuronal representation of a repeated item had a significantly decreased amplitude and duration compared with novel stimuli. Furthermore, the magnitude of RS was greatest for the stimuli that initially elicited the largest activation at each site. These results have implications for understanding the neural basis of RS and human memory by showing that individual cortical sites exhibit the largest RS for the stimuli that they most actively represent.
electrocorticography; gamma band; repetition suppression
The Fourth International Workshop on Advances in Electrocorticography (ECoG) convened in New Orleans, LA, on October 11-12, 2012. The proceedings of the workshop serves as an accurate record of the most contemporary clinical and experimental work on brain surface recording and represents the insights of a unique multidisciplinary ensemble of expert clinicians and scientists. Presentations covered a broad range of topics, including innovations in passive functional mapping, increased understanding of pathologic high-frequency oscillations, evolving sensor technologies, a human trial of ECoG-driven brain-machine interface, as well as fresh insights into brain electrical stimulation.
electrocorticography; brain-computer interface; high-frequency oscillations; brain mapping; seizure detection; gamma-frequency electroencephalography; neuroprosthetics; subdural grid
A device capable of detecting seizures and alerting caregivers would be a major advance for epilepsy management, and could be used to guide early intervention and prevent seizure-related injuries. The objective of this work was to evaluate a seizure advisory system (SAS) that alerts caregivers of seizures in canines with naturally occurring epilepsy. Four dogs with epilepsy were implanted with a SAS that wirelessly transmits continuous intracranial EEG (iEEG) to an external device embedded with a seizure detection algorithm and the capability to alert caregivers. In this study a veterinarian was alerted by automated text message if prolonged or repetitive seizures occurred, and a rescue therapy protocol was implemented. The performance of the SAS caregiver alert was evaluated over the course of 8 weeks. Following discontinuation of antiepileptic drugs, the dogs experienced spontaneous unprovoked partial seizures that secondarily generalized. Three prolonged or repetitive seizure episodes occurred in 2 of the dogs. On each occasion, the SAS caregiver alert successfully alerted an on call veterinarian who confirmed the seizure activity via remote video-monitoring. A rescue medication was then administered and the seizures were aborted. This study demonstrates the feasibility of a SAS caregiver alert for prolonged or repetitive seizures, and enabling rescue medications to be delivered in a timely manner. The SAS may improve the management of human epilepsy by alerting caregivers of seizures, enabling early interventions, and potentially improving outcomes and quality of life of patients and caregivers.
epilepsy; seizure management; seizure advisory; caregiver alert; EEG; device
Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material.
category clustering; episodic memory; free recall; neural integration; pattern classification
The Third International Workshop on Advances in Electrocorticography (ECoG) was convened in Washington, DC, on November 10-11, 2011. As in prior meetings, a true multidisciplinary fusion of clinicians, scientists, and engineers from many disciplines gathered to summarize contemporary experiences in brain surface recordings. The proceedings of this meeting serve as evidence of a very robust and transformative field, but will yet again require revision for the advances that the following year will surely bring.
electrocorticography; brain-computer interface; high-frequency oscillations; brain mapping; seizure detection; gamma-frequency electroencephalography; neuroprosthetics; subdural grid
Through decades of research, neuroscientists and clinicians have identified an array of brain areas that each activate when a person views a certain category of stimuli. However, we do not have a detailed understanding of how the brain represents individual stimuli within a category. Here we used direct human brain recordings and machine-learning algorithms to characterize the distributed patterns that distinguish specific cognitive states. Epilepsy patients with surgically implanted electrodes performed a working-memory task and we used machine-learning algorithms to predict the identity of each viewed stimulus. We found that the brain’s representation of stimulus-specific information is distributed across neural activity at multiple frequencies, electrodes, and timepoints. Stimulus-specific neuronal activity was most prominent in the high-gamma (65–128 Hz) and theta/alpha (4–16 Hz) bands, but the properties of these signals differed significantly between individuals and for novel stimuli compared to common ones. Our findings show that the brain distinguishes specific cognitive states by diverse spatiotemporal patterns of neuronal activity, which is helpful for understanding the neural basis of memory and developing brain–computer interfaces.
Electrocorticography; machine learning; visual perception; working memory
Identify seizure onset electrodes that need to be resected for seizure freedom in children undergoing intracranial electroencephalography recording for treatment of medically refractory epilepsy. All children undergoing intracranial electroencephalography subdural grid electrode placement at the Children’s Hospital of Philadelphia from 2002-2008 were asked to enroll. We utilized intraoperative pictures to determine the location of the electrodes and define the resection cavity. A total of 15 patients had surgical fields that allowed for complete identification of the electrodes over the area of resection. Eight of 15 patients were seizure free after a follow up of 1.7 to 8 yr. Only one seizure-free patient had complete resection of all seizure onset associated tissue. Seizure free patients had resection of 64.1% of the seizure onset electrode associated tissue, compared to 35.2% in the not seizure free patients (p=0.05). Resection of tissue associated with infrequent seizure onsets did not appear to be important for seizure freedom. Resecting ≥ 90% of the electrodes from the predominant seizure contacts predicted post-operative seizure freedom (p=0.007). The best predictor of seizure freedom was resecting ≥ 90% of tissue involved in majority of a patient’s seizures. Resection of tissue under infrequent seizure onset electrodes was not necessary for seizure freedom.
Epilepsy; epilepsy surgery; cortical dysplasia; neocortical epilepsy; intracranial electroencephalography
Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low-gamma (30–70 Hz), and high-gamma (70–180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.
The Second International Workshop on Advances in Electrocorticography (ECoG) was convened in San Diego, CA, USA, on November 11–12, 2010. Between this meeting and the inaugural 2009 event, a much clearer picture has been emerging of cortical ECoG physiology and its relationship to local field potentials and single-cell recordings. Innovations in material engineering are advancing the goal of a stable long-term recording interface. Continued evolution of ECoG-driven brain–computer interface technology is determining innovation in neuroprosthetics. Improvements in instrumentation and statistical methodologies continue to elucidate ECoG correlates of normal human function as well as the ictal state. This proceedings document summarizes the current status of this rapidly evolving field.
Electrocorticography; Brain–computer interface; High-frequency oscillations; Brain mapping; Seizure detection; Gamma-frequency electroencephalography; Neuroprosthetics; Subdural grid
Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30–100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG (<100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) post-surgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain.
Epileptic network; Interictal epileptic discharge; Pathological gamma oscillation; Detection; Mapping; Data-mining
Transient high-frequency (100–500 Hz) oscillations of the local field potential have been studied extensively in human mesial temporal lobe. Previous studies report that both ripple (100–250 Hz) and fast ripple (250–500 Hz) oscillations are increased in the seizure-onset zone of patients with mesial temporal lobe epilepsy. Comparatively little is known, however, about their spatial distribution with respect to seizure-onset zone in neocortical epilepsy, or their prevalence in normal brain. We present a quantitative analysis of high-frequency oscillations and their rates of occurrence in a group of nine patients with neocortical epilepsy and two control patients with no history of seizures. Oscillations were automatically detected and classified using an unsupervised approach in a data set of unprecedented volume in epilepsy research, over 12 terabytes of continuous long-term micro- and macro-electrode intracranial recordings, without human preprocessing, enabling selection-bias-free estimates of oscillation rates. There are three main results: (i) a cluster of ripple frequency oscillations with median spectral centroid = 137 Hz is increased in the seizure-onset zone more frequently than a cluster of fast ripple frequency oscillations (median spectral centroid = 305 Hz); (ii) we found no difference in the rates of high frequency oscillations in control neocortex and the non-seizure-onset zone neocortex of patients with epilepsy, despite the possibility of different underlying mechanisms of generation; and (iii) while previous studies have demonstrated that oscillations recorded by parenchyma-penetrating micro-electrodes have higher peak 100–500 Hz frequencies than penetrating macro-electrodes, this was not found for the epipial electrodes used here to record from the neocortical surface. We conclude that the relative rate of ripple frequency oscillations is a potential biomarker for epileptic neocortex, but that larger prospective studies correlating high-frequency oscillations rates with seizure-onset zone, resected tissue and surgical outcome are required to determine the true predictive value.
high-frequency oscillations; epilepsy; intracranial EEG
We present results from continuous intracranial electroencephalographic (iEEG) monitoring in 6 dogs with naturally occurring epilepsy, a disorder similar to the human condition in its clinical presentation, epidemiology, electrophysiology and response to therapy. Recordings were obtained using a novel implantable device wirelessly linked to an external, portable real-time processing unit. We demonstrate previously uncharacterized intracranial seizure onset patterns in these animals that are strikingly similar in appearance to human partial onset epilepsy. We propose: (1) canine epilepsy as an appropriate model for testing human antiepileptic devices and new approaches to epilepsy surgery, and (2) this new technology as a versatile platform for evaluating seizures and response to therapy in the natural, ambulatory setting.
Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we have developed new devices integrating ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors connected using many fewer wires. We used this system to record novel spatial properties of brain activity in vivo, including sleep spindles, single-trial visual evoked responses, and electrographic seizures. Our electrode array allowed us to discover that seizures may manifest as recurrent spiral waves which propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface (BMI) devices.
Multielectrode array; electrode array; flexible electronics; multiplexed electrode; cortical surface electrode; foldable electrode; ECoG; μECoG; brain machine interface; high temporal resolution; high spatial resolution; spindle; visual neuroscience; spiral wave; epilepsy; seizure; epileptiform spike; interhemispheric fissure; silicon nanoribbon
Focal seizures appear to start abruptly and unpredictably when recorded from volumes of brain probed by clinical intracranial electroencephalograms. To investigate the spatiotemporal scale of focal epilepsy, wide-bandwidth electrophysiological recordings were obtained using clinical macro- and research microelectrodes in patients with epilepsy and control subjects with intractable facial pain. Seizure-like events not detectable on clinical macroelectrodes were observed on isolated microelectrodes. These ‘microseizures’ were sparsely distributed, more frequent in brain regions that generated seizures, and sporadically evolved into large-scale clinical seizures. Rare microseizures observed in control patients suggest that this phenomenon is ubiquitous, but their density distinguishes normal from epileptic brain. Epileptogenesis may involve the creation of these topographically fractured microdomains and ictogenesis (seizure generation), the dynamics of their interaction and spread.
epilepsy; seizure; intracranial EEG; microseizure; microcircuit; seizure generation; ictogenesis; epileptogenesis
Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. We present innovations in both hardware and software that allow sampling and interpretation of data from brain networks from hundreds or thousands of sensors at submillimeter resolution. These innovations consist of novel flexible, active electrode arrays and unsupervised algorithms for detecting and classifying neurophysiologic biomarkers, specifically high frequency oscillations. We propose these innovations as the foundation for a new generation of closed loop diagnostic and therapeutic medical devices, and brain-machine interfaces.
Development of advanced surgical tools for minimally invasive procedures represents an activity of central importance to improvements in human health. A key materials challenge is in the realization of bio-compatible interfaces between the classes of semiconductor and sensor technologies that might be most useful in this context and the soft, curvilinear surfaces of the body. This paper describes a solution based on biocompatible materials and devices that integrate directly with the thin elastic membranes of otherwise conventional balloon catheters, to provide multimodal functionality suitable for clinical use. We present sensors for measuring temperature, flow, tactile, optical and electrophysiological data, together with radio frequency (RF) electrodes for controlled, local ablation of tissue. These components connect together in arrayed layouts designed to decouple their operation from large strain deformations associated with deployment and repeated inflation/deflation. Use of such ‘instrumented’ balloon catheter devices in live animal models and in vitro tests illustrates their operation in cardiac ablation therapy. These concepts have the potential for application in surgical systems of the future, not only those based on catheters but also on other platforms, such as surgical gloves.
Experimental prolonged febrile seizures (FS) lead to structural and molecular changes that promote hippocampal hyperexcitability and reduce seizure threshold to further convulsants. However, whether these seizures provoke later-onset epilepsy, as has been suspected in humans, has remained unclear. Previously, intermittent EEGs with behavioural observations for motor seizures failed to demonstrate spontaneous seizures in adult rats subjected to experimental prolonged FS during infancy. Because limbic seizures may be behaviourally subtle, here we determined the presence of spontaneous limbic seizures using chronic video monitoring with concurrent hippocampal and cortical EEGs, in adult rats (starting around 3 months of age) that had sustained experimental FS on postnatal day 10. These subjects were compared with groups that had undergone hyperthermia but in whom seizures had been prevented (hyperthermic controls), as well as with normothermic controls. Only events that fulfilled both EEG and behavioural criteria, i.e. electro-clinical events, were considered spontaneous seizures. EEGs (over 400 recorded hours) were normal in all normothermic and hyperthermic control rats, and none of these animals developed spontaneous seizures. In contrast, prolonged early-life FS evoked spontaneous electro-clinical seizures in 6 out of 17 experimental rats (35.2%). These seizures consisted of sudden freezing (altered consciousness) and typical limbic automatisms that were coupled with polyspike/sharp-wave trains with increasing amplitude and slowing frequency on EEG. In addition, interictal epileptiform discharges were recorded in 15 (88.2%) of the experimental FS group and in none of the controls. The large majority of hippocampally-recorded seizures were heralded by diminished amplitude of cortical EEG, that commenced half a minute prior to the hippocampal ictus and persisted after seizure termination. This suggests a substantial perturbation of normal cortical neuronal activity by these limbic spontaneous seizures. In summary, prolonged experimental FS lead to later-onset limbic (temporal lobe) epilepsy in a significant proportion of rats, and to interictal epileptifom EEG abnormalities in most others, and thus represent a model that may be useful to study the relationship between FS and human temporal lobe epilepsy.
prolonged febrile seizures; temporal lobe epilepsy; video-EEG; rat; prospective study
The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial EEG (IEEG). While ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure onset location, though these studies were based upon relatively short EEG epochs.
We employ a previously validated, computerized spike detector, to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extra temporal lobe epilepsy. Approximately 8 hours of IEEG, randomly selected thirty-minute segments of continuous interictal IEEG per patient were analyzed over all intracranial electrode contacts.
When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure onset region in 11 of 19 patients. There was significant variability between individual 30-minute segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure onset region.
Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori.
Spike density; intracranial EEG; Seizure onset; Pediatric Epilepsy
The sophistication and resolution of current implantable medical devices are limited by the need connect each sensor separately to data acquisition systems. The ability of these devices to sample and modulate tissues is further limited by the rigid, planar nature of the electronics and the electrode-tissue interface. Here, we report the development of a class of mechanically flexible silicon electronics for measuring signals in an intimate, conformal integrated mode on the dynamic, three dimensional surfaces of soft tissues in the human body. We illustrate this technology in sensor systems composed of 2016 silicon nanomembrane transistors configured to record electrical activity directly from the curved, wet surface of a beating heart in vivo. The devices sample with simultaneous sub-millimeter and sub-millisecond resolution through 288 amplified and multiplexed channels. We use these systems to map the spread of spontaneous and paced ventricular depolarization in real time, at high resolution, on the epicardial surface in a porcine animal model. This clinical-scale demonstration represents one example of many possible uses of this technology in minimally invasive medical devices.
[Conformal electronics and sensors intimately integrated with living tissues enable a new generation of implantable devices capable of addressing important problems in human health.]
Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain-machine interfaces. This paper describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable or surgical devices.
Increases in accumulated energy on intracranial EEG are associated with oncoming seizures in retrospective studies, supporting the idea that seizures are generated over time. Published seizure prediction methods require comparison to ‘baseline’ data, sleep staging, and selecting seizures that are not clustered closely in time. In this study, we attempt to remove these constraints by using a continuously adapting energy threshold, and to identify stereotyped energy variations through the seizure cycle (inter-, pre-, post- and ictal periods).
Accumulated energy was approximated by using moving averages of signal energy, computed for window lengths of 1 and 20 min, and an adaptive decision threshold. Predictions occurred when energy within the shorter running window exceeded the decision threshold.
Predictions for time horizons of less than 3 h did not achieve statistical significance in the data sets analyzed that had an average inter-seizure interval ranging from 2.9 to 8.6 h. 51.6% of seizures across all patients exhibited stereotyped pre-ictal energy bursting and quiet periods.
Accumulating energy alone is not sufficient for predicting seizures using a 20 min running baseline for comparison. Stereotyped energy patterns through the seizure cycle may provide clues to mechanisms underlying seizure generation.
Energy-based seizure prediction will require fusion of multiple complimentary features and perhaps longer running averages to compensate for post-ictal and sleep-induced energy changes.
Intracranial EEG energy; Interictal and ictal energy; Seizure prediction; Accumulated energy; Average inter-seizure interval
Many patients suffer from medically refractory epilepsy and are not candidates for resective brain surgery. Success of deep brain stimulation (DBS) in relieving a significant amount of symptoms of various movement disorders paved the way for investigations into this modality for epilepsy. Open-label and small blinded-trials have provided promising evidence for the use of DBS in refractory seizures. However, the first randomized control trial of DBS of the anterior thalamic nucleus is currently underway. Furthermore, there are multiple potential targets as many neural regions have been implicated in seizure propagation. Thus, it is difficult at this time to make any definitive judgments about the efficacy of DBS for seizure control. Future study is necessary to identify a patient population for whom this technique would be indicated, the most efficacious target, and optimal stimulation parameters.
Deep brain stimulation; epilepsy; thalamus; seizure; closed-loop systems
Although the hippocampus plays a crucial role in encoding and retrieval of contextually-mediated “episodic” memories, considerable controversy surrounds the role of the hippocampus in short-term or working memory. To examine both hippocampal and neocortical contributions to working memory function, we recorded electrocorticographic (ECoG) activity from widespread cortical and subcortical sites as 20 neurosurgical patients performed working memory tasks. These recordings revealed significant increases in 48–90 Hz gamma oscillatory power with memory load for two classes of stimuli: letters and faces. Sites exhibiting gamma increases with memory load appeared primarily in the hippocampus and medial temporal lobe. These findings implicate gamma oscillatory activity in the maintenance of both letters and faces in working memory, and provide the first direct evidence for modulation of hippocampal gamma oscillations as humans perform a working memory task.
oscillations; working memory; ECoG; memory; EEG; hippocampus