Low impedance electrodes improve detection of high frequency oscillations in the intracranial EEG.

OBJECTIVE: Epileptic fast ripple oscillations (FR, 250-500 Hz) indicate epileptogenic tissue with high specificity. However, their low amplitude makes detection demanding against noise. Since thermal noise is reduced by low impedance electrodes (LoZ), we investigate here whether this noise reduction is relevant in the FR frequency range. METHODS: We analyzed intracranial electrocorticography during neurosurgery of 10 patients where a low impedance electrode was compared to a standard electrode (HiZ) with equal surface area during stimulation of the somatosensory evoked potential, which evokes a robust response in the FR frequency range. To estimate the noise level, we computed the difference between sweep 2n and sweep 2n + 1 for all sweeps. RESULTS: The power spectral density of the noise spectrum improved for the LoZ over all frequencies. In the FR range, the median noise level improved from HiZ (0.153 µV) to LoZ (0.089 µV). For evoked FR, the detection rate improved (91% for HiZ vs. 100% for LoZ). CONCLUSIONS: Low impedance electrodes for intracranial EEG reduce noise in the FR frequency range and may thereby improve FR detection. SIGNIFICANCE: Improving the measurement chain may enhance the diagnostic value of FR as biomarkers for epileptogenic tissue.

Optimization of signal-to-noise ratio in short-duration SEP recordings by variation of stimulation rate.

OBJECTIVE: The intraoperative averaging of the somatosensory evoked potential (SEP) requires reliable recordings within the shortest possible duration. We here systematically optimized the repetition rate of stimulus presentation. METHODS: We recorded medianus and tibial nerve SEP during 22 surgeries and varied the rate of stimulus presentation between 2.7 Hz and 28.7 Hz. We randomly sampled a number of sweeps corresponding to recording durations up to 20 s and calculated the signal-to-noise ratio (SNR). RESULTS: For the medianus nerve at 5 s recording duration, SEP stimulation rate at 12.7 Hz obtained the highest median SNR = 22.9 for the N20, which was higher than for rate 4.7 Hz (p = 1.5e-4). When increasing the stimulation rate, latency increased and amplitude decayed for cortical but not for peripheral recording sites. For the tibial nerve, the rate 4.7 Hz achieved the highest SNR for all durations. CONCLUSIONS: We determined the time-dependence of SNR for N20 and elucidated the underlying physiology. For short recordings, rapid reduction of noise through averaging at high stimulation rate outweighs the disadvantage of smaller amplitude. SIGNIFICANCE: For a short duration of medianus nerve SEP recording only, it may be advantageous to stimulate with a repetition rate of 12.7 Hz.

Information flows from hippocampus to auditory cortex during replay of verbal working memory items.

The maintenance of items in working memory (WM) relies on a widespread network of cortical areas and hippocampus where synchronization between electrophysiological recordings reflects functional coupling. We investigated the direction of information flow between auditory cortex and hippocampus while participants heard and then mentally replayed strings of letters in WM by activating their phonological loop. We recorded local field potentials from the hippocampus, reconstructed beamforming sources of scalp EEG, and - additionally in four participants - recorded from subdural cortical electrodes. When analyzing Granger causality, the information flow was from auditory cortex to hippocampus with a peak in the [4 8] Hz range while participants heard the letters. This flow was subsequently reversed during maintenance while participants maintained the letters in memory. The functional interaction between hippocampus and the cortex and the reversal of information flow provide a physiological basis for the encoding of memory items and their active replay during maintenance.

Every day, the brain's ability to temporarily store and recall information ­ called working memory ­ enables us to reason, solve complex problems or to speak. Holding pieces of information in working memory for short periods of times is a skill that relies on communication between neural circuits that span several areas of the brain. The hippocampus, a seahorse-shaped area at the centre of the brain, is well-known for its role in learning and memory. Less clear, however, is how brain regions that process sensory inputs, including visual stimuli and sounds, contribute to working memory. To investigate, Dimakopoulos et al. studied the flow of information between the hippocampus and the auditory cortex, which processes sound. To do so, various types of electrodes were placed on the scalp or surgically implanted in the brains of people with drug-resistant epilepsy. These electrodes measured the brain activity of participants as they read, heard and then mentally replayed strings of up to 8 letters. The electrical signals analysed reflected the flow of information between brain areas. When participants read and heard the sequence of letters, brain signals flowed from the auditory cortex to the hippocampus. The flow of electrical activity was reversed while participants recalled the letters. This pattern was found only in the left side of the brain, as expected for a language related task, and only if participants recalled the letters correctly. This work by Dimakopoulos et al. provides the first evidence of bidirectional communication between brain areas that are active when people memorise and recall information from their working memory. In doing so, it provides a physiological basis for how the brain encodes and replays information stored in working memory, which evidently relies on the interplay between the hippocampus and sensory cortex.

Protocol for multicentre comparison of interictal high-frequency oscillations as a predictor of seizure freedom.

In drug-resistant focal epilepsy, interictal high-frequency oscillations (HFOs) recorded from intracranial EEG (iEEG) may provide clinical information for delineating epileptogenic brain tissue. The iEEG electrode contacts that contain HFO are hypothesized to delineate the epileptogenic zone; their resection should then lead to postsurgical seizure freedom. We test whether our prospective definition of clinically relevant HFO is in agreement with postsurgical seizure outcome. The algorithm is fully automated and is equally applied to all data sets. The aim is to assess the reliability of the proposed detector and analysis approach. We use an automated data-independent prospective definition of clinically relevant HFO that has been validated in data from two independent epilepsy centres. In this study, we combine retrospectively collected data sets from nine independent epilepsy centres. The analysis is blinded to clinical outcome. We use iEEG recordings during NREM sleep with a minimum of 12 epochs of 5 min of NREM sleep. We automatically detect HFO in the ripple (80-250 Hz) and in the fast ripple (250-500 Hz) band. There is no manual rejection of events in this fully automated algorithm. The type of HFO that we consider clinically relevant is defined as the simultaneous occurrence of a fast ripple and a ripple. We calculate the temporal consistency of each patient's HFO rates over several data epochs within and between nights. Patients with temporal consistency <50% are excluded from further analysis. We determine whether all electrode contacts with high HFO rate are included in the resection volume and whether seizure freedom (ILAE 1) was achieved at ≥2 years follow-up. Applying a previously validated algorithm to a large cohort from several independent epilepsy centres may advance the clinical relevance and the generalizability of HFO analysis as essential next step for use of HFO in clinical practice.

Anterior-Posterior Hippocampal Dynamics Support Working Memory Processing.

The hippocampus is a locus of working memory (WM) with anterior and posterior subregions that differ in their transcriptional and external connectivity patterns. However, the involvement and functional connections between these subregions in WM processing are poorly understood. To address these issues, we recorded intracranial EEG from the anterior and the posterior hippocampi in humans (seven females and seven males) who maintained a set of letters in their WM. We found that WM maintenance was accompanied by elevated low-frequency activity in both the anterior and posterior hippocampus and by increased theta/alpha band (3-12 Hz) phase synchronization between anterior and posterior subregions. Cross-frequency and Granger prediction analyses consistently showed that the correct WM trials were associated with theta/alpha band-coordinated unidirectional influence from the posterior to the anterior hippocampus. In contrast, WM errors were associated with bidirectional interactions between the anterior and posterior hippocampus. These findings imply that theta/alpha band synchrony within the hippocampus may support successful WM via a posterior to anterior influence. A combination of intracranial recording and a fine-grained atlas may be of value in understanding the neural mechanisms of WM processing.SIGNIFICANCE STATEMENT Working memory (WM) is crucial to everyday functioning. The hippocampus has been proposed to be a subcortical node involved in WM processes. Previous studies have suggested that the anterior and posterior hippocampi differ in their external connectivity patterns and gene expression. However, it remains unknown whether and how human hippocampal subregions are recruited and coordinated during WM tasks. Here, by recording intracranial electroencephalography simultaneously from both hippocampal subregions, we found enhanced power in both areas and increased phase synchronization between them. Furthermore, correct WM trials were associated with a unidirectional influence from the posterior to the anterior hippocampus, whereas error trials were correlated with bidirectional interactions. These findings indicate a long-axis specialization in the human hippocampus during WM processing.

Blinded study: prospectively defined high-frequency oscillations predict seizure outcome in individual patients.

Interictal high-frequency oscillations are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich. We here validated the algorithm on intracranial EEG that was recorded in an independent epilepsy centre so that the analysis was blinded to seizure outcome. We selected consecutive patients who underwent resective epilepsy surgery in Geneva with post-surgical follow-up > 12 months. We analysed long-term recordings during sleep that we segmented into intervals of 5 min. High-frequency oscillations were defined in the ripple (80-250 Hz) and the fast ripple (250-500 Hz) frequency bands. Contacts with the highest rate of ripples co-occurring with fast ripples designated the relevant area. As a validity criterion, we calculated the test-retest reliability of the high-frequency oscillations area between the 5 min intervals (dwell time ≥50%). If the area was not fully resected and the patient suffered from recurrent seizures, this was classified as a true positive prediction. We included recordings from 16 patients (median age 32 years, range 18-53 years) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 months, range 12-55 months). For each patient, we included several 5 min intervals (median 17 intervals). The relevant area had high test-retest reliability across intervals (median dwell time 95%). In two patients, the test-retest reliability was too low (dwell time < 50%) so that outcome prediction was not possible. The area was fully included in the resected volume in 2/4 patients who achieved post-operative seizure freedom (specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (sensitivity 90%), leading to an accuracy of 79%. An additional exploratory analysis suggested that high-frequency oscillations were associated with interictal epileptic discharges only in channels within the relevant area and not associated in channels outside the area. We thereby validated the automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset and achieved the same good accuracy as in our previous studies. The reproducibility of our results across datasets is promising for a multicentre study to test the clinical application of high-frequency oscillations to guide epilepsy surgery.