Effects of eustatic sea-level change, ocean dynamics, and nutrient utilization on atmospheric pCO2 and seawater composition over the last 130 000 years: a model study

We have developed and employed an Earth system model to explore the forcings of atmospheric pCO2 change and the chemical and isotopic evolution of seawater over the last glacial cycle. Concentrations of dissolved phosphorus (DP), reactive nitrogen, molecular oxygen, dissolved inorganic carbon (DIC), total alkalinity (TA), 13C-DIC, and 14CDIC were calculated for 24 ocean boxes. The bi-directional water fluxes between these model boxes were derived from a 3-D circulation field of the modern ocean (Opa 8.2, NEMO) and tuned such that tracer distributions calculated by the box model were consistent with observational data from the modern ocean. To model the last 130 kyr, we employed records of past changes in sea-level, ocean circulation, and dust deposition. According to the model, about half of the glacial pCO2 drawdown may be attributed to marine regressions. The glacial sea-level low-stands implied steepened ocean margins, a reduced burial of particulate organic carbon, phosphorus, and neritic carbonate at the margin seafloor, a decline in benthic denitrification, and enhanced weathering of emerged shelf sediments. In turn, low-stands led to a distinct rise in the standing stocks of DIC, TA, and nutrients in the global ocean, promoted the glacial sequestration of atmospheric CO2 in the ocean, and added 13C- and 14C-depleted DIC to the ocean as recorded in benthic foraminifera signals. The other half of the glacial drop in pCO2 was linked to inferred shoaling of Atlantic meridional overturning circulation and more efficient utilization of nutrients in the Southern Ocean. The diminished ventilation of deep water in the glacial Atlantic and Southern Ocean led to significant 14C depletions with respect to the atmosphere. According to our model, the deglacial rapid and stepwise rise in atmospheric pCO2 was induced by upwelling both in the Southern Ocean and subarctic North Pacific and promoted by a drop in nutrient utilization in the Southern Ocean. The deglacial sea-level rise led to a gradual decline in nutrient, DIC, and TA stocks, a slow change due to the large size and extended residence times of dissolved chemical species in the ocean. Thus, the rapid deglacial rise in pCO2 can be explained by fast changes in ocean dynamics and nutrient utilization whereas the gradual pCO2 rise over the Holocene may be linked to the slow drop in nutrient and TA stocks that continued to promote an ongoing CO2 transfer from the ocean into the atmosphere

Dr. Ilse Seibold, née Usbeck, 1925–2021: Considered by many as a consecutive memory of major geoscientists

Summary of Ilse Seibold's vita Ilse Seibold, née Usbeck, was born May 8, 1925 in Breslau, Silesia, and went to school in Halle/Saale during WW2. She started her studies of geology and paleontology at the University of Halle and at the Humboldt University in Berlin, and later at the University of Tübingen, where she received her doctorate as micropaleontologist in 1951 with Otto Schindewolf as her supervisor. She remained active as productive scientist over many decades. In 1952, she married Dr. Eugen Seibold, who in 1958 became professor at Kiel University, founded one of Europe's most important institutes for marine geology, and later became president of the German Science Foundation (DFG), and subsequently of the European Science Foundation (ESF). Being a scientist herself Ilse Seibold soon evolved to a deeply reflective insider of geological sciences. She followed her husband during his scientific career from his appointments in Tübingen, Bonn, Karlsruhe, Kiel, to Bonn and Strasbourg/Freiburg i.Br. She accompanied Eugen on his sabbatical leave at Scripps Institution of Oceanography in La Jolla, CA. She participated in countless international scientific meetings. Together with Eugen she published many papers that document her independence and autonomy as scientist. She gained deep insights into the origins of the geosciences and their historical evolution, up to the ideas of fine arts. We are happy that she documented in her publications a broad range of her scientific and distinguished-humane impressions

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

Motor-evoked potentials (MEP) during brainstem surgery to preserve corticospinal function

Background: Brainstem surgery bears a risk of damage to the corticospinal tract (CST). Motor-evoked potentials (MEPs) are used intraoperatively to monitor CST function in order to detect CST damage at a reversible stage and thus impede permanent neurological deficits. While the method of MEP is generally accepted, warning criteria in the context of brainstem surgery still have to be agreed on. Method: We analyzed 104 consecutive patients who underwent microsurgical resection of lesions affecting the brainstem. Motor grade was documented prior to surgery, early postoperatively and at discharge. A baseline MEP stimulation intensity threshold was defined and intraoperative testing aimed to keep MEP response amplitude constant. MEPs were considered deteriorated and the surgical team was notified whenever the threshold was elevated by ≥20mA or MEP response fell under 50%. Findings: On the first postoperative day, 18 patients experienced new paresis that resolved by discharge in 11. MEPs deteriorated in 39 patients, and 16 of these showed new postoperative paresis, indicating a 41% risk of new paresis. In the remaining 2/18 patients, intraoperative MEPs were stable, although new paresis appeared postoperatively. In one of these patients, intraoperative hemorrhage caused postoperative swelling, and the new motor deficit persisted until discharge. Of all 104 patients, 7 deteriorated in motor grade at discharge, 92 remained unchanged, and 5 patients have improved. Conclusions: Adjustment of surgical strategy contributed to good motor outcome in 33/39 patients. MEP monitoring may help significantly to prevent motor deficits during demanding neurosurgical procedures on the brainste

An electronic neuromorphic system for real-time detection of High Frequency Oscillations (HFOs) in intracranial EEG

In this work, we present a neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neural network (SNN) architecture on the same die for recording, processing, and detecting High Frequency Oscillations (HFO), which are biomarkers for the epileptogenic zone. The device was fabricated using a standard 0.18$\mu$m CMOS technology node and has a total area of 99mm$^{2}$. We demonstrate its application to HFO detection in the iEEG recorded from 9 patients with temporal lobe epilepsy who subsequently underwent epilepsy surgery. The total average power consumption of the chip during the detection task was 614.3$\mu$W. We show how the neuromorphic system can reliably detect HFOs: the system predicts postsurgical seizure outcome with state-of-the-art accuracy, specificity and sensitivity (78%, 100%, and 33% respectively). This is the first feasibility study towards identifying relevant features in intracranial human data in real-time, on-chip, using event-based processors and spiking neural networks. By providing "neuromorphic intelligence" to neural recording circuits the approach proposed will pave the way for the development of systems that can detect HFO areas directly in the operation room and improve the seizure outcome of epilepsy surgery.Comment: 16 pages. A short video describing the rationale underlying the study can be viewed on https://youtu.be/NuAA91fdma

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. Keywords: Erb’s point; High frequency oscillation; Intraoperative neuromonitoring; Neurosurgery; Peripheral nerve conduction; Stimulation frequency

Benthic Foraminiferal Oxygen Isotope Offsets Over The Last Glacial-Interglacial Cycle

The oxygen isotope (?18O) offset between contemporaneous benthic foraminiferal species is often assumed constant with time and geographic location. We present an inventory of benthic foraminiferal species ?18O offsets from the major ocean basins covering the last glacial-interglacial cycle, showing that of the twenty down-core records investigated, twelve show significant temporal changes in ?18O offsets that do not resemble stochastic variability. Some of the temporal changes may be related to kinetic fractionation effects causing deglacial/interglacial enrichment or glacial depletion in mainly infaunal species, but additional research is needed to confirm this. In addition to stratigraphic implications the finding of temporally varying offsets between co-existing benthic foraminiferal species could have implications for sea-level, deep water temperature, and regional deep water ?18O estimates

Random Teachers are Good Teachers

In this work, we investigate the implicit regularization induced by teacher-student learning dynamics in self-distillation. To isolate its effect, we describe a simple experiment where we consider teachers at random initialization instead of trained teachers. Surprisingly, when distilling a student into such a random teacher, we observe that the resulting model and its representations already possess very interesting characteristics; (1) we observe a strong improvement of the distilled student over its teacher in terms of probing accuracy. (2) The learned representations are data-dependent and transferable between different tasks but deteriorate strongly if trained on random inputs. (3) The student checkpoint contains sparse subnetworks, so-called lottery tickets, and lies on the border of linear basins in the supervised loss landscape. These observations have interesting consequences for several important areas in machine learning: (1) Self-distillation can work solely based on the implicit regularization present in the gradient dynamics without relying on any dark knowledge, (2) self-supervised learning can learn features even in the absence of data augmentation and (3) training dynamics during the early phase of supervised training do not necessarily require label information. Finally, we shed light on an intriguing local property of the loss landscape: the process of feature learning is strongly amplified if the student is initialized closely to the teacher. These results raise interesting questions about the nature of the landscape that have remained unexplored so far. Code is available at https://github.com/safelix/dinopl