Chronic subthreshold cortical stimulation and stimulation-related EEG biomarkers for focal epilepsy.

Brain stimulation offers an alternative to focal resection for the treatment of focal drug-resistant epilepsy. Chronic subthreshold cortical stimulation is an individualized biomarker-informed open-loop continuous electrical stimulation approach targeting the seizure onset zone and surrounding areas. Before permanent implantation, trial stimulation is performed during invasive monitoring to assess stimulation efficacy as well as to optimize stimulation location and parameters by modifying interictal EEG biomarkers. We present clinical and neurophysiological results from a retrospective analysis of 21 patients, showing a median percent reduction in seizure frequency of 100% and responder rate of 89% with a median follow-up of 27 months. About 40% of patients were free of disabling seizures for a 12-month period or longer. We find that stimulation-induced decreases in delta (1-4 Hz) power and increases in alpha and beta (8-20 Hz) power during trial stimulation correlate with improved long-term clinical outcomes. These results suggest chronic subthreshold cortical stimulation may be an effective alternative approach to treating focal drug-resistant epilepsy and that short-term stimulation-related changes in spectral power may be a useful interictal biomarker and relate to long-term clinical outcome.

Human Verbal Memory Encoding Is Hierarchically Distributed in a Continuous Processing Stream.

Processing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here, we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High γ frequency activity (65-115 Hz) showed consistent power responses during encoding of subsequently recalled and forgotten words on a subset of electrodes localized in 16 distinct cortical areas activated in the tasks. More of the high γ power during word encoding, and less power before and after the word presentation, was characteristic of successful recall and observed across multiple brain regions. Latencies of the induced power changes and this subsequent memory effect (SME) between the recalled and forgotten words followed an anatomical sequence from visual to prefrontal cortical areas. Finally, the magnitude of the memory effect was unexpectedly found to be the largest in selected brain regions both at the top and at the bottom of the processing stream. These included the language processing areas of the prefrontal cortex and the early visual areas at the junction of the occipital and temporal lobes. Our results provide evidence for distributed encoding of verbal memory organized along a hierarchical posterior-to-anterior processing stream.

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

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

Visually validated semi-automatic high-frequency oscillation detection aides the delineation of epileptogenic regions during intra-operative electrocorticography.

OBJECTIVE: To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings. METHODS: Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually inspected and false positive detections were removed. We retrospectively determined the sensitivity, specificity, positive and negative predictive value (PPV/NPV) of HFO detections in unresected regions for determining post-operative seizure outcome. RESULTS: Visual validation revealed that 2.81% of ripple and 43.68% of fast ripple detections were false positive. Inter-reader agreement for false positive fast ripple on spike classification was good (ICC = 0.713, 95% CI: 0.632-0.779). After removing false positive detections, the PPV of a single fast ripple on spike in an unresected electrode site for post-operative non-seizure free outcome was 85.7 [50-100%]. Including false positive detections reduced the PPV to 64.2 [57.8-69.83%]. CONCLUSIONS: Applying automated HFO methods to intraoperative electrocorticography recordings results in false positive fast ripple detections. True fast ripples on spikes are rare, but predict non-seizure free post-operative outcome if found in an unresected site. SIGNIFICANCE: Semi-automated HFO detection methods are required to accurately identify fast ripple events in intra-operative ECoG recordings.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance.

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

Evidence for verbal memory enhancement with electrical brain stimulation in the lateral temporal cortex.

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.awx373media15704855796001.

Behavioral state classification in epileptic brain using intracranial electrophysiology.

OBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. MAIN RESULTS: Classification accuracy of 97.8 ± 0.3% (normal tissue) and 89.4 ± 0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8 ± 0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1 ± 1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy ⩾90% using a single electrode contact and single spectral feature. SIGNIFICANCE: Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain.

High-frequency oscillations (HFOs: 100 - 600 Hz) have been widely proposed as biomarkers of epileptic brain tissue. In addition, HFOs over a broader range of frequencies spanning 30 - 2000 Hz are potential biomarkers of both physiological and pathological brain processes. The majority of the results from humans with focal epilepsy have focused on HFOs recorded directly from the brain with intracranial EEG (iEEG) in the high gamma (65 - 100 Hz), ripple (100 - 250 Hz), and fast ripple (250 - 600 Hz) frequency ranges. These results are supplemented by reports of HFOs recorded with iEEG in the low gamma (30 - 65Hz) and very high frequency (500 - 2000 Hz) ranges. Visual detection of HFOs is laborious and limited by poor inter-rater agreement; and the need for accurate, reproducible automated HFOs detection is well recognized. In particular, the clinical translation of HFOs as a biomarker of the epileptogenic brain has been limited by the ability to reliably detect and accurately classify HFOs as physiological or pathological. Despite these challenges, there has been significant progress in the field, which is the subject of this review. Furthermore, we provide data and corresponding analytic code in an effort to promote reproducible research and accelerate clinical translation.

Higher-level motion detection deficit in Parkinson's disease.

Previous research has suggested that Parkinson's disease (PD) impairs motion perception. First-order motion consists of moving luminance-defined attributes. Second-order motion, on the other hand, consists of moving patterns whose motion attributes are not luminance-defined. The detection of first and second-order motion is thought to be mediated by different mechanisms. Here, we compare the ability of Parkinson's disease patients (PDPs) to detect first-order/second-order motion with normal subjects. Subjects had to discriminate the drift direction of first-order motion (luminance-modulated noise) and a second-order motion pattern (named as noise base motion) over a range of stimulus speeds and strengths. Results show that the first-order motion detection deficits could only be seen with lower motion strengths suggesting a ceiling effect with higher motion strengths. However, second order motion detection deficits were seen across high and low motion strengths, suggesting that the second order motion detection may be more affected in PD than the first-order motion detection. Our results indicate that higher-level visual cortex plays an important role in PD patients' disabilities in motion perception.

Reduction of negative afterimage duration in Parkinson's disease patients: a possible role for dopaminergic deficiency in the retinal Interplexiform cell layer.

Dopaminergic deficiency may affect Parkinson's disease patients (PD) in the central as well as the peripheral tissues. In the retina, the neuromodulatory role of the dopaminergic Interplexiform cell layer (IP) plays a major role in the retinal light adaptation and may account for the duration of the negative afterimage. Here we present results showing a significant reduction of negative afterimage duration in PD patients. This supports the hypothesis that the retinal dopaminergic system may be the main cause for the long duration of negative afterimage. We suggest that the observed reduction of afterimage duration is due to possible dopaminergic deficiency in patients with Parkinson's disease.