Surface EEG Recordings Research Articles

Studying memory processes at different levels with simultaneous depth and surface EEG recordings.

Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.

Hybrid machine learning method for a connectivity-based epilepsy diagnosis with resting-state EEG.

This study investigates the performance of a convolutional neural network (CNN) algorithm on epilepsy diagnosis. Without pathology, diagnosis involves long and costly electroencephalographic (EEG) monitoring. Novel approaches may overcome this by comparing brain connectivity using graph metrics. This study, however, uses deep learning to learn connectivity patterns directly from easily acquired EEG data. A CNN algorithm was applied on directed Granger causality (GC) connectivity measures, derived from 50s of resting-state surface EEG recordings from 30 subjects with epilepsy and a 30 subject control group. The trained CNN filters reflected reduced delta band connectivity in frontal regions and increased left lateralized frontal-posterior gamma band connectivity. A diagnosis accuracy of 85% (F1 score 85%) was achieved by an ensemble of CNN models, each trained on differently prepared data from different electrode combinations. Appropriate preparation of connectivity data enables generic CNN algorithms to be used for detection of multiple discriminative epileptic features. Differential patterns revealed in this study may help to shed light on underlying altered cognitive abilities in epilepsy patients. The accuracy achieved in this study shows that, in combination with other methods, this approach could prove a valuable clinical decision support system for epilepsy diagnosis. 1: EEG measurements and subsequent connectivity calculation, 2: training of a neural network on resulting connectivity matrices, 3: extraction of most efficient CNN filters, which are neuromarker for epilepsy.

P 40. β-γ phase-amplitude coupling during movements in Parkinson's disease

Question. Enhanced phase amplitude coupling (PAC) between β (13–30 Hz) and broadband γ (50–150 Hz) activities has been found in surface EEG recordings from Parkinson patients at rest [1]. However, the dynamics of PAC during voluntary movement and its relationship with motor impairment of Parkinson“s disease (PD) remain unclear. Methods. Experimental design : We recorded 64-channel EEG signals from 19 PD patients and 20 sex- and age-matched healthy controls at rest, during a repetitive pressing task and during repetitive index finger tapping performed at the patients“ own pace and at their fastest pace. Source analysis : We obtained source signals by projecting EEG sensor signals to the individual cortical surfaces. Independent component analysis (ICA) was applied for separating temporally independent subnetworks of each task in each of the 4 brain regions: premotor cortex, primary motor cortex, primary somatosensory cortex and primary somatosensory complex. PAC analysis: Pairwise transient PAC values were calculated among ICA components of each region by zscore-normalized mean vector length [2] in 300ms windows shifted with 50ms time steps in 3s epochs which included an interval of 1s before, and 2s after the onset of the movement. Statistics : We applied a non-parametric three-way ANOVA [3] to test the effects of the disease state, tasks and different brain regions on PAC. For post-hoc testing, a two tailed Wilcoxon ranksum test was used between groups and Wilcoxon signrank test within groups. Results. As expected, maximum tapping rate was lower, and fastest movements were executed more irregularly in patients compared to controls. ANOVA performed on the β-γ PAC values averaged over the entire 3s-epoch revealed an interaction of disease state and tasks ( p < 0.001). Post-hoc testing showed enhanced PAC in patients compared with controls in the resting state ( p = 0.018), in agreement with previous findings, but not in any of the tapping tasks. However, PAC during the pressing task remained elevated in the patients compared to controls ( p = 0.020). Analysis of the temporal dynamics revealed reduction of PAC after the onset of the movement (0–0.25 s) compared with that of the pre-onset period (−0.5 to −0.25 s). The reduction of PAC relative to pre-onset period correlated with the desynchronization in the β power. However, the PAC reduction relative to the resting state was not correlated with the β power reduction. Discussion. Persistence of PAC differences during the pressing task on one hand, and disappearance of PAC differences during the tapping tasks on the other hand, suggest that exaggerated β-broadband γ PAC, as detected in the resting EEG, is not necessarily directly related to impaired motor behavior in PD patients. As our previous findings [1] have shown that abnormal PAC at rest is unrelated to the β band power, partial renormalization of PAC by movement-related β band desynchronization may suggest that mechanisms modulating β activity during movement may selectively affect β activity involved in abnormal coupling.

Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes

Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.

Cell-Type-Specific Dynamics of Calcium Activity in Cortical Circuits over the Course of Slow-Wave Sleep and Rapid Eye Movement Sleep.

Sleep shapes cortical network activity, fostering global homeostatic downregulation of excitability while maintaining or even upregulating excitability in selected networks in a manner that supports memory consolidation. Here, we used two-photon calcium imaging of cortical layer 2/3 neurons in sleeping male mice to examine how these seemingly opposing dynamics are balanced in cortical networks. During slow-wave sleep (SWS) episodes, mean calcium activity of excitatory pyramidal (Pyr) cells decreased. Simultaneously, however, variance in Pyr population calcium activity increased, contradicting the notion of a homogenous downregulation of network activity. Indeed, we identified a subpopulation of Pyr cells distinctly upregulating calcium activity during SWS, which were highly active during sleep spindles known to support mnemonic processing. Rapid eye movement (REM) episodes following SWS were associated with a general downregulation of Pyr cells, including the subpopulation of Pyr cells active during spindles, which persisted into following stages of sleep and wakefulness. Parvalbumin-positive inhibitory interneurons (PV-In) showed an increase in calcium activity during SWS episodes, while activity remained unchanged during REM sleep episodes. This supports the view that downregulation of Pyr calcium activity during SWS results from increased somatic inhibition via PV-In, whereas downregulation during REM sleep is achieved independently of such inhibitory activity. Overall, our findings show that SWS enables upregulation of select cortical circuits (likely those which were involved in mnemonic processing) through a spindle-related process, whereas REM sleep mediates general downregulation, possibly through synaptic re-normalization.SIGNIFICANCE STATEMENT Sleep is thought to globally downregulate cortical excitability and, concurrently, to upregulate synaptic connections in neuron ensembles with newly encoded memory, with upregulation representing a function of sleep spindles. Using in vivo two-photon calcium imaging in combination with surface EEG recordings, we classified cells based on their calcium activity during sleep spindles. Spindle-active pyramidal (Pyr) cells persistently increased calcium activity during slow-wave sleep (SWS) episodes while spindle-inactive cells decreased calcium activity. Subsequent rapid eye movement (REM) sleep episodes profoundly reduced calcium activity in both cell clusters. Results indicate that SWS allows for a spindle-related differential upregulation of ensembles whereas REM sleep functions to globally downregulate networks.

An electrophysiological marker of arousal level in humans.

Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, 'wake-like' EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.

Florida research open-source synchronization tool (FROST) for electrophysiology experiments

BackgroundAccurate interpretation of electrophysiological data in cognitive and behavioral experiments requires the acquisition of time labels, such as marking the exact start of a condition or moment a stimulus is presented to a research subject. New MethodHere we present an inexpensive (∼30 USD) device used as a central relay for multiple peripheral devices, such as a computer screen presenting an experiment, a pressure-sensor push button, a multi-button responder, a pulse oximeter sensor, a light-emitting diode trigger for camera synchronization, and more. We refer to this device as the Florida Research Open-source Synchronization Tool (FROST). FROST allows for easy hardware and Arduino-based firmware modifications that enable a standard platform for the integration of novel peripheral sensors. ResultsWith two examples, we demonstrate the application of this device during human research experiments: intracranial-electroencephalography (EEG) recordings in a patient with epilepsy and surface-EEG recordings in a healthy participant. We provide an example setup for a rodent experiment as well. We also demonstrate the timing delays of our device. Comparison with existing methodsThere is currently very few existing open-source synchronization tools for electrophysiological research that enable customization with new device compatibility. We developed this tool to enable widespread replication for many applications through an open-source platform. ConclusionsFROST can be easily adapted for research experiments beyond the included example cases. All materials are open-source at github.com/Brain-Mapping-Lab/FROST.

Hilbert Vibration Decomposition-based epileptic seizure prediction with neural network

Epilepsy is one of the most prominent brain disorders in the world, and epileptic patients suffer from sudden seizures that have a substantial negative impact on their lives. A seizure prediction system, therefore, is essential in overcoming the difficulties that epileptic individuals experience. This study designs and demonstrates a non-patient specific seizure prediction system that uses the Hilbert Vibration Decomposition (HVD) method on surface EEG recordings of 10 patients from the CHB-MIT database. EEG signals with 18 channels are decomposed to 7 subcomponents with the HVD in sliding windows. These subcomponents from all channels are then used to calculate features to be fed into an MLP classifier. The classification process is performed for all patients simultaneously and without relaying information concerning patient identity to the classifier. After the classification stage, an alarm algorithm that evaluates the frequency of preictal predictions is developed. The classification sensitivity was, on average, 19.89% across patients. This sensitivity was increased to, on average 89.8% within 120 min and an average false alarm rate of 0.081/h was achieved with a seizure prediction horizon of 4 min across patients after alarm creation.

Clinico-electroencephalographic variants in pharmacoresistant mesial temporal lobe epilepsy

Focal epilepsy secondary to mesial temporal sclerosis (MTS) is one of the main causes of refractory epilepsy. It is typically associated with frontotemporal discharges in the electroencephalogram (EEG), a characteristic image in the magnetic resonance scan and a probability of post-operative remission above 70%. To identify different patterns of ictal propagation in surface EEG recordings in patients with refractory epilepsy and MTS, and to analyse their relation with the post-operative outcome. We conducted a retrospective review of the medical records of patients with refractory epilepsy secondary to MTS evaluated in the Epilepsy Surgery Programme of the Hospital de Clinicas, Montevideo (n = 30). The propagation of ictal rhythms was analysed in time windows of three seconds, and propagation maps were produced for each seizure. Six patterns were identified: ipsilateral temporal (type 1; 37%), bilateral frontotemporal with (type 2A; 22%) or without (type 2B; 17%) extension to suprasylvian regions, alternating temporal (type 3; 13%), unilateral suprasylvian (type 4; 7%) and bilateral at onset (type 5; 3%). The type 1 pattern was associated with classic clinical features and a favourable post-operative outcome. The clinical variants were associated with extratemporal EEG propagation. Patients with reflex seizures continued with post-operative seizures. Overall, no unambiguous relation was found between the ictal EEG pattern and the post-operative outcome. The ictal EEG pattern does not allow for a surgical prognosis in patients with epilepsy secondary to MTS. The history of reflex seizures in these patients may be a red flag suggesting a less favourable surgical outcome.

Electrophysiological Evidence for the Development of a Self-Sustained Large-Scale Epileptic Network in the Kainate Mouse Model of Temporal Lobe Epilepsy.

Most research on focal epilepsy focuses on mechanisms of seizure generation in the primary epileptic focus (EF). However, neurological deficits that are not directly linked to seizure activity and that may persist after focus removal are frequent. The recruitment of remote brain regions of an epileptic network (EN) is recognized as a possible cause, but a profound lack of experimental evidence exists concerning their recruitment and the type of pathological activities they exhibit. We studied the development of epileptic activities at the large-scale in male mice of the kainate model of unilateral temporal lobe epilepsy using high-density surface EEG and multiple-site intracortical recordings. We show that, along with focal spikes and fast ripples that remain localized to the injected hippocampus (i.e., the EF), a subpopulation of spikes that propagate across the brain progressively emerges even before the expression of seizures. The spatiotemporal propagation of these generalized spikes (GSs) is highly stable within and across animals, defining a large-scale EN comprising both hippocampal regions and frontal cortices. Interestingly, GSs are often concomitant with muscular twitches. In addition, while fast ripples are, as expected, highly frequent in the EF, they also emerge in remote cortical regions and in particular in frontal regions where GSs propagate. Finally, we demonstrate that these remote interictal activities are dependent on the focus in the early phase of the disease but continue to be expressed after focus silencing at later stages. Our results provide evidence that neuronal networks outside the initial focus are progressively altered during epileptogenesis.SIGNIFICANCE STATEMENT It has long been held that the epileptic focus is responsible for triggering seizures and driving interictal activities. However, focal epilepsies are associated with heterogeneous symptoms, calling into question the concept of a strictly focal disease. Using the mouse model of hippocampal sclerosis, this work demonstrates that focal epilepsy leads to the development of pathological activities specific to the epileptic condition, notably fast ripples, that appear outside of the primary epileptic focus. Whereas these activities are dependent on the focus early in the disease, focus silencing fails to control them in the chronic stage. Thus, dynamical changes specific to the epileptic condition are built up outside of the epileptic focus along with disease progression, which provides supporting evidence for network alterations in focal epilepsy.

Operculo-Insular Epilepsy: Scalp and Intracranial Electroencephalographic Findings.

Operculo-insular seizures are heterogeneous and may resemble seizures originating from the temporal, frontal, or parietal lobe. Although surface and invasive EEG recordings are often necessary to detect operculo-insular seizures, electrophysiological features of operculo-insular epilepsies remain poorly characterized. This study describes the EEG findings of patients with operculo-insular epilepsy. We reviewed electrophysiological data of all patients (n = 9) with operculo-insular seizures revealed by intracranial EEG and for whom operculo-insular epilepsy was confirmed by good seizure outcome after resective or radiosurgery at our center between 2005 and 2013. Patients were divided according to whether their seizure focus involved the anterior (group 1; n = 4) or posterior (group 2; n = 5) portion of the insula. Interictal scalp EEG was lateralizing and showed distinct topographical spike patterns between groups: frontal and temporal in group 1, temporal in group 2. Intracranial recordings showed abundant spikes limited to the operculo-insular region or involving distant areas in the frontal/temporal (group 1) and temporal/parietal lobes (group 2). Ictal intracranial EEG revealed discharges limited to the insula or simultaneously involving extrainsular contacts at onset, notably the orbitofrontal cortex (group 1) and the frontal and parietal opercula (group 2), and propagating to the frontal and temporal lobes in group 1 and to parietal and temporal lobes in group 2. Spike distribution and seizure propagation in operculo-insular epilepsy follows an anterior-to-posterior pattern mirroring an anterior or posterior insular focus localization. When presented with frontal and/or temporal epileptiform abnormalities, an operculo-insular focus should be considered.

P368 Epileptiform and sleep spindle activity in anterior nucleus of the thalamus in temporal lobe epilepsy patients

Introduction Deep brain stimulation of anterior nucleus of the thalamus (ANT-DBS) is an approved therapeutic approach for drug resistant epilepsy. Little is known about the participation of ANT in epileptic and sleep EEG processes. The appearance of the sleep spindles (SS) is related to interictal discharges (IID), and thalamus is considered as the generator of SSs, however, according to animal data, ANT do not participate in the genesis of sleep spindles. Methods In this present study we included 10 ANT-DBS bitemporal epilepsy patients with externalised leads and surface electrodes undergoing 2 days video-EEG monitoring (VEM). We investigated IIDs, ictal events (IE) and SSs in ANT and also in surface EEG recordings. IIDs and IEs were analysed by visual inspection, SSs were detected according to the patient own special spindle frequency, separately on the scalp (Fp1-2, F3-4, F7-8) and thalamus both sides. SS spectral peak frequency and synchronization between scalp and ANT was measured. Results IIDs appeared in the thalamus and on the scalp both dependent and independent manner. Three patients had seizures during VEM. Seizures did not start but start spread to the ANT electrodes. The slow, frontal type of SSs were prevailing in the ANT. Conclusion ANT participates in both sleep and epileptogenic processes. It seems that IIDs and IE spread to the ANT. Frontal, slow frequency SSs has local sources int he ANT indication its participation in sleep processes. Further evaluation for seizure outcome of ANT-DBS therapy and correlation with ANT recordings are underway.

Drug-resistant parietal lobe epilepsy: clinical manifestations and surgery outcome.

We reviewed a large surgical cohort to investigate the clinical manifestations, EEG and neuroimaging findings, and postoperative seizure outcome in patients with drug-resistant parietal lobe epilepsy (PLE). All drug-resistant PLE patients, who were investigated for epilepsy surgery at Jefferson Comprehensive Epilepsy Center between 1986 and 2015, were identified. Demographic data, seizure data, EEG recordings, brain MRI, pathological findings, and postsurgical seizure outcome were reviewed. In total, 18 patients (11 males and seven females) were identified. Sixteen patients (88%) had tonic-clonic seizures, 12 (66%) had focal seizures with impaired awareness, and 13 (72%) described auras. Among 15 patients who had brain MRI, 14 patients (93%) had parietal lobe lesions. Only three of 15 patients (20%) who had interictal scalp EEG recordings showed parietal interictal spikes. Of 12 patients with available ictal surface EEG recordings, only three patients (25%) had parietal ictal EEG onset. After a mean follow-up duration of 8.6 years, 14 patients (77.7%) showed a favourable postoperative seizure outcome. In patients with PLE, semiology and EEG may be misleading and brain MRI is the most valuable tool to localize the epileptogenic zone. Postsurgical seizure outcome was favourable in our patients with drug-resistant parietal lobe epilepsy.

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and neurodegenerative diseases as well as epilepsies. This powerful technique does not only provide valuable insights into the underlying pathophysiological mechanisms, i.e., the etiopathogenesis of CNS related diseases, it also facilitates the development of new translational, i.e., therapeutic approaches. Whereas competing techniques that make use of recorder systems used in jackets or tethered systems suffer from their unphysiological restraining to semi-restraining character, radiotelemetric EEG recordings overcome these disadvantages. Technically, implantable EEG radiotelemetry allows for precise and highly sensitive measurement of epidural and deep, intracerebral EEGs under various physiological and pathophysiological conditions. First, we present a detailed protocol of a straight forward, successful, quick and efficient technique for epidural (surface) EEG recordings resulting in high-quality electrocorticograms. Second, we demonstrate how to implant deep, intracerebral EEG electrodes, e.g., in the hippocampus (electrohippocampogram). For both approaches, a computerized 3D stereotaxic electrode implantation system is used. The radiofrequency transmitter itself is implanted into a subcutaneous pouch in both mice and rats. Special attention also has to be paid to pre-, peri- and postoperative treatment of the experimental animals. Preoperative preparation of mice and rats, suitable anesthesia as well as postoperative treatment and pain management are described in detail.

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement.

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and neurodegenerative diseases as well as epilepsies. This powerful technique does not only provide valuable insights into the underlying pathophysiological mechanisms, i.e., the etiopathogenesis of CNS related diseases, it also facilitates the development of new translational, i.e., therapeutic approaches. Whereas competing techniques that make use of recorder systems used in jackets or tethered systems suffer from their unphysiological restraining to semi-restraining character, radiotelemetric EEG recordings overcome these disadvantages. Technically, implantable EEG radiotelemetry allows for precise and highly sensitive measurement of epidural and deep, intracerebral EEGs under various physiological and pathophysiological conditions. First, we present a detailed protocol of a straight forward, successful, quick and efficient technique for epidural (surface) EEG recordings resulting in high-quality electrocorticograms. Second, we demonstrate how to implant deep, intracerebral EEG electrodes, e.g., in the hippocampus (electrohippocampogram). For both approaches, a computerized 3D stereotaxic electrode implantation system is used. The radiofrequency transmitter itself is implanted into a subcutaneous pouch in both mice and rats. Special attention also has to be paid to pre-, peri- and postoperative treatment of the experimental animals. Preoperative preparation of mice and rats, suitable anesthesia as well as postoperative treatment and pain management are described in detail.

Gender-Specific Hippocampal Dysrhythmia and Aberrant Hippocampal and Cortical Excitability in the APPswePS1dE9 Model of Alzheimer's Disease.

Alzheimer's disease (AD) is a multifactorial disorder leading to progressive memory loss and eventually death. In this study an APPswePS1dE9 AD mouse model has been analyzed using implantable video-EEG radiotelemetry to perform long-term EEG recordings from the primary motor cortex M1 and the hippocampal CA1 region in both genders. Besides motor activity, EEG recordings were analyzed for electroencephalographic seizure activity and frequency characteristics using a Fast Fourier Transformation (FFT) based approach. Automatic seizure detection revealed severe electroencephalographic seizure activity in both M1 and CA1 deflection in APPswePS1dE9 mice with gender-specific characteristics. Frequency analysis of both surface and deep EEG recordings elicited complex age, gender, and activity dependent alterations in the theta and gamma range. Females displayed an antithetic decrease in theta (θ) and increase in gamma (γ) power at 18-19 weeks of age whereas related changes in males occurred earlier at 14 weeks of age. In females, theta (θ) and gamma (γ) power alterations predominated in the inactive state suggesting a reduction in atropine-sensitive type II theta in APPswePS1dE9 animals. Gender-specific central dysrhythmia and network alterations in APPswePS1dE9 point to a functional role in behavioral and cognitive deficits and might serve as early biomarkers for AD in the future.

Basal forebrain cholinergic modulation of sleep transitions.

The basal forebrain cholinergic system is involved in cognitive processes that require an attentive state, an increased level of arousal, and/ or cortical activation associated with low amplitude fast EEG activity. The activity of most neurons in the basal forebrain cholinergic space is tightly correlated with the cortical EEG and the activity state. While most cholinergic neurons fire maximally during waking and REM sleep, the activity of other types of basal forebrain neurons vastly differs across different arousal and sleep states. Numerous studies have suggested a role for the basal forebrain cholinergic neurons in eliciting cortical activation and arousal. However, the intricate local connectivity within the region requires the use of cell-specific manipulation methods to demonstrate such a causal relationship. Here we have combined optogenetics with surface EEG recordings in freely moving mice in order to investigate the effects of acute cholinergic activation on the dynamics of sleep-to-wake transitions. We recorded from naturally sleeping animals and analyzed transitions from NREM sleep to REM sleep and/ or wakefulness in response to photo-stimulation of cholinergic neurons in substantia innominata. Our results show that optogenetic activation of BF cholinergic neurons during NREM sleep is sufficient to elicit cortical activation and facilitate state transitions, particularly transitions to wakefulness and arousal, at a time scale similar to the activation induced by other subcortical systems. Our results provide in vivo cell-specific demonstration for the role of basal forebrain cholinergic system in induction of wakefulness and arousal.

Wearable, wireless EEG solutions in daily life applications: what are we missing?

Monitoring human brain activity has great potential in helping us understand the functioning of our brain, as well as in preventing mental disorders and cognitive decline and improve our quality of life. Noninvasive surface EEG is the dominant modality for studying brain dynamics and performance in real-life interaction of humans with their environment. To take full advantage of surface EEG recordings, EEG technology has to be advanced to a level that it can be used in daily life activities. Furthermore, users have to see it as an unobtrusive option to monitor and improve their health. To achieve this, EEG systems have to be transformed from stationary, wired, and cumbersome systems used mostly in clinical practice today, to intelligent wearable, wireless, convenient, and comfortable lifestyle solutions that provide high signal quality. Here, we discuss state-of-the-art in wireless and wearable EEG solutions and a number of aspects where such solutions require improvements when handling electrical activity of the brain. We address personal traits and sensory inputs, brain signal generation and acquisition, brain signal analysis, and feedback generation. We provide guidelines on how these aspects can be advanced further such that we can develop intelligent wearable, wireless, lifestyle EEG solutions. We recognized the following aspects as the ones that need rapid research progress: application driven design, end-user driven development, standardization and sharing of EEG data, and development of sophisticated approaches to handle EEG artifacts.

Ictal local field potential recordings in anterior thalamus (ANT) and nucleus accumbens (NAC) in patients with temporal lobe epilepsy (TLE)

Rationale: Deep brain stimulation (DBS) of the ANT has recently been established as a therapeutic strategy for medically refractory focal epilepsy. However, the mechanistic underpinnings of this novel treatment option are still not sufficiently understood, partly because under normal clinical conditions the analysis of propagation of epileptic activity is restricted to information derived either from surface or intracranial EEG recordings restricted to the accessible cortical structures.

Characterization of seizure‐induced syncopes:EEG,ECG, and clinical features

Ictal bradycardia and ictal asystole (IA) are rare but severe complications of epileptic seizures. They are difficult to recognize within a seizure and their consequences remain unclear. Herein we aimed to extend the description of electrical and clinical features of seizures with IA and/or syncope. Among 828 patients with epilepsy who were admitted for presurgical video-electroencephalogram (EEG) monitoring evaluation between 2003 and 2012, we selected those presenting IA and/or syncope. We studied the electroclinical sequence of these manifestations and their correlation with electrocardiogram (ECG), and we compared seizures with or without IA among the same patients. Nine (1.08%) of 828 patients (four men, mean age 43 ± 6 years) showed IA. Six patients had temporal lobe epilepsy and the others had frontal, temporooccipital, or occipital epilepsy, demonstrated by intracranial EEG in two. In these patients, 59 of 103 recorded seizures induced a reduction of heart rate (HR), leading to IA in 26. IAs were mostly (80%) symptomatic, whereas ictal HR decreases alone were not. In seizures with IA, we identified usual ictal symptoms, and then symptoms related primarily to cerebral hypoperfusion (pallor, atonia, early myoclonic jerks, loss of consciousness, hypertonia, and fall) and secondarily to cerebral reperfusion (skin flushing, late myoclonic jerks). At 32 ± 18 s after the onset of the seizure, the HR decreased progressively during 11 ± 6 s, reaching a sinusal pause for 13 ± 7 s. The duration of the IA was strongly correlated with electroclinical consequences. IA was longer in patients with atonia (14.8 ± 7 vs. 5.7 ± 3 s), late myoclonic jerks (15.8 ± 7 vs. 8 ± 6 s), hypertonia (19 ± 4.5 vs. 8.3 ± 5 s), and EEG hypoperfusion changes (16 ± 5.6 vs. 6.9 ± 5.5 s). IA may induce a fall during atonia or hypertonia. Surface and intracerebral EEG recordings showed that ictal HR decrease and IA often occurred when seizure activity became bilateral. Finally, we identified one patient with ictal syncopes but without IA, presumably related to vasoplegia. We provide a more complete description of the electroclinical features of seizures with IA, of the mechanism of falls, and distinguish between hypoperfusion and reperfusion symptoms of syncope. Identification of the mechanisms of syncope may improve management of patients with epilepsy. A pacemaker can be proposed, when parasympathetic activation provokes a negative chronotropic effect that leads to asystole. It is less likely to be useful when vasoplegic effects predominate.