Automatic seizure detection in long-term scalp EEG using an adaptive thresholding technique: a validation study for clinical routine - Hopfengärtner, Rüdiger; Kasper, Burkhard; Graf, Wolfgang; Gollwitzer, Stephanie; Kreiselmeyer, Gernot; Stefan, Hermann; Hamer, Hajo (Clinical Neurophysiology, 2014)
In a previous study we proposed a robust method for automatic seizure detection in scalp EEG recordings. The goal of the current study was to validate an improved algorithm in a much larger group of patients in order to show its general applicability in clinical routine.For the detection of seizures we developed an algorithm based on Short Time Fourier Transform, calculating the integrated power in the frequency band 2.5-12 Hz for a multi-channel seizure detection montage referenced against the average of Fz-Cz-Pz. For identification of seizures an adaptive thresholding technique was applied. Complete data sets of each patient were used for analyses for a fixed set of parameters.159 patients (117 temporal-lobe epilepsies (TLE), 35 extra-temporal lobe epilepsies (ETLE), 7 other) were included with a total of 25,278 h of EEG data, 794 seizures were analyzed. The sensitivity was 87.3% and number of false detections per hour (FpH) was 0.22/h. The sensitivity for TLE patients was 89.9% and FpH=0.19/h; for ETLE patients sensitivity was 77.4% and FpH=0.25/h.The seizure detection algorithm provided high values for sensitivity and selectivity for unselected large EEG data sets without a priori assumptions of seizure patterns.The algorithm is a valuable tool for fast and effective screening of long-term scalp EEG recordings.
EVALuna2:22295

Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA) - Michelmann, Sebastian; Treder, Matthias S.; Griffiths, Benjamin; Kerren, Casper; Roux, Frederic; Wimber, Maria; Rollings, David; Sawlani, Vijay; Chelvarajah, Ramesh; Gollwitzer, Stephanie; Kreiselmeyer, Gernot; Hamer, Hajo; et al. (Journal of Neuroscience Methods, 2018)
BACKGROUND: Intracranial recordings from patients implanted with depth electrodes are a valuable source of information in neuroscience. They allow for the unique opportunity to record brain activity with high spatial and temporal resolution. A common pre-processing choice in stereotactic EEG (S-EEG) is to re-reference the data with a bipolar montage. In this, each channel is subtracted from its neighbor, to reduce commonalities between channels and isolate activity that is spatially confined. NEW METHOD: We challenge the assumption that bipolar reference effectively performs this task. To extract local activity, the distribution of the signal source of interest, interfering distant signals, and noise need to be considered. Referencing schemes with fixed coefficients can decrease the signal to noise ratio (SNR) of the data, they can lead to mislocalization of activity and consequently to misinterpretation of results. We propose to use Independent Component Analysis (ICA), to derive filter coefficients that reflect the statistical dependencies of the data at hand. RESULTS: We describe and demonstrate this on human S-EEG recordings. In a simulation with real data, we quantitatively show that ICA outperforms the bipolar referencing operation in sensitivity and importantly in specificity when revealing local time series from the superposition of neighboring channels. COMPARISON WITH EXISTING METHOD(S): We argue that ICA already performs the same task that bipolar referencing pursues, namely undoing the linear superposition of activity and will identify activity that is local. CONCLUSIONS: When investigating local sources in human S-EEG, ICA should be preferred over re-referencing the data with a bipolar montage.
EVALuna2:201937

Directional coupling of slow and fast hippocampal gamma with neocortical alpha/beta oscillations in human episodic memory - Griffiths, Benjamin J.; Parish, George; Roux, Frederic; Michelmann, Sebastian; van der Plas, Mircea; Kolibius, Luca D.; Chelvarajah, Ramesh; Rollings, David T.; Sawlani, Vijay; Hamer, Hajo; Gollwitzer, Stephanie; Kreiselmeyer, Gernot; et al. (Proceedings of the National Academy of Sciences of the United States of America, 2019)
Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these 2 processes are thought to be supported by neocortical alpha/beta desynchronization and hippocampal theta/gamma synchronization, respectively. Intuitively, these 2 processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analyzing human intracranial electroencephalogram data recorded during 2 associative memory tasks. We find that neocortical alpha/beta (8 to 20 Hz) power decreases reliably precede and predict hippocampal "fast" gamma (60 to 80 Hz) power increases during episodic memory formation; during episodic memory retrieval, however, hippocampal "slow" gamma (40 to 50 Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from the neocortex to the hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.
EVALuna2:204498

Hippocampal neurons code individual episodic memories in humans - Kolibius, Luca D.; Roux, Frederic; Parish, George; Ter Wal, Marije; Van Der Plas, Mircea; Chelvarajah, Ramesh; Sawlani, Vijay; Rollings, David T.; Lang, Johannes; Gollwitzer, Stephanie; Walther, Katrin; Hopfengärtner, Rüdiger; et al. (Nature Human Behaviour, 2023)
The hippocampus is an essential hub for episodic memory processing. However, how human hippocampal single neurons code multi-element associations remains unknown. In particular, it is debated whether each hippocampal neuron represents an invariant element within an episode or whether single neurons bind together all the elements of a discrete episodic memory. Here we provide evidence for the latter hypothesis. Using single-neuron recordings from a total of 30 participants, we show that individual neurons, which we term episode-specific neurons, code discrete episodic memories using either a rate code or a temporal firing code. These neurons were observed exclusively in the hippocampus. Importantly, these episode-specific neurons do not reflect the coding of a particular element in the episode (that is, concept or time). Instead, they code for the conjunction of the different elements that make up the episode.
CRIS-Team Scopus Importer:2023-10-20

Oscillations support short latency co-firing of neurons during human episodic memory formation - Roux, Frédéric; Parish, George; Chelvarajah, Ramesh; Rollings, David T.; Sawlani, Vijay; Hamer, Hajo; Gollwitzer, Stephanie; Kreiselmeyer, Gernot; Ter Wal, Marije J.; Kolibius, Luca; Staresina, Bernhard P.; Wimber, Maria; et al. (eLife, 2022)
Theta and gamma oscillations in the medial temporal lobe are suggested to play a critical role for human memory formation via establishing synchrony in neural assemblies. Arguably, such synchrony facilitates efficient information transfer between neurons and enhances synaptic plasticity, both of which benefit episodic memory formation. However, to date little evidence exists from humans that would provide direct evidence for such a specific role of theta and gamma oscillations for episodic memory formation. Here, we investigate how oscillations shape the temporal structure of neural firing during memory formation in the medial temporal lobe. We measured neural firing and local field potentials in human epilepsy patients via micro-wire electrode recordings to analyze whether brain oscillations are related to co-incidences of firing between neurons during successful and unsuccessful encoding of episodic memories. The results show that phase-coupling of neurons to faster theta and gamma oscillations correlates with co-firing at short latencies ( 20-30 ms) and occurs during successful memory formation. Phase-coupling at slower oscillations in these same frequency bands, in contrast, correlates with longer co-firing latencies and occurs during memory failure. Thus, our findings suggest that neural oscillations play a role for the synchronization of neural firing in the medial temporal lobe during the encoding of episodic memories.
CRIS-Team Scopus Importer:2022-12-23
Keywords: human; memory; neural firing; neuroscience; oscillations; single units; spikes; STDP

Slow-theta power decreases during item-place encoding predict spatial accuracy of subsequent context recall - Crespo-Garcia, Maite; Zeiller, Monika; Leupold, Claudia; Kreiselmeyer, Gernot; Rampp, Stefan; Hamer, Hajo; Dalal, Sarang S. (NeuroImage, 2016)
Human hippocampal theta oscillations play a key role in accurate spatial coding. Associative encoding involves similar hippocampal networks but, paradoxically, is also characterized by theta power decreases. Here, we investigated how theta activity relates to associative encoding of place contexts resulting in accurate navigation. Using MEG, we found that slow-theta (2-5Hz) power negatively correlated with subsequent spatial accuracy for virtual contextual locations in posterior hippocampus and other cortical structures involved in spatial cognition. A rare opportunity to simultaneously record MEG and intracranial EEG in an epilepsy patient provided crucial insights: during power decreases, slow-theta in right anterior hippocampus and left inferior frontal gyrus phase-led the left temporal cortex and predicted spatial accuracy. Our findings indicate that decreased slow-theta activity reflects local and long-range neural mechanisms that encode accurate spatial contexts, and strengthens the view that local suppression of low-frequency activity is essential for more efficient processing of detailed information.
EVALuna2:22490