Biology subjects

Pfeiffer, C.

Publications and source records attributed to Pfeiffer, C..

8 recordsLinked to original sources

bioRxiv2026

Comparing advanced interference suppression algorithms for OPM-MEG

On-scalp MEG using optically pumped magnetometers (OPMs) have become more widespread with the recent introduction of the first whole-head systems that offer comparable spatial sampling to conventional MEG systems. For these systems to become truly useful in neuroscience and clinically they need to be able to deal with the kind of interference seen in typical lab and hospital environments - both environmental and participant related (e.g., dental wires). Conventional MEG uses sophisticated interference suppression algorithms to deal with this, but these tend to become instable at lower sensor counts - which makes up the majority of OPM-MEG systems to date. Alternative methods for OPM-MEG are needed. Several alternative algorithms have been proposed but a clear comparison between them is lacking. Here, we test and compare 5 of the most promising candidates, namely homogenous field correction (HFC), adaptive multipole models (AMM), signal space projection (SSP), signal space separation (SSS) and its iterative implementation (SSSit) using simulations and data recorded with a whole-head system. Recorded data includes a participant with dental wire - an especially difficult to deal with source of interference. We find that all algorithms tested achieve good interference suppression with dual-axis data. With single-axis data, SSS exhibited stability problems and several algorithms showed large signal loss (up to ~25%). SSP, temporal SSS and temporal AMM were able to suppress the dental artifact. Finally, we provide recommendations for researchers to determine help decide how to deal with interference in their OPM-MEG studies.

neuroscience↗

bioRxiv2022

Cardio-audio synchronization elicits prediction in auditory sequences during human wakefulness and sleep

The human brain can infer temporal regularities in auditory sequences with fixed sound-to-sound intervals and in pseudo-regular sequences where sound onsets are locked to cardiac inputs. Here, we investigated auditory and cardio-audio regularity encoding during sleep, when reduced vigilance may result in altered bodily and environmental stimulus processing. Using electroencephalography and electrocardiography in healthy volunteers (N=26) during wakefulness and sleep, we measured the response to unexpected sound omissions within three auditory regularity conditions: synchronous, where sound and heartbeat are temporally locked, isochronous, with fixed sound-to-sound intervals, and a control condition without specific regularity. During wakefulness and all sleep stages, the cardiac signal following sound omissions exhibited a deceleration over time in the synchronous condition only. At the neural level, both the synchronous and isochronous sequences gave rise to a neural omission response in wakefulness and N2 sleep. Regularity encoding in the synchronous and isochronous conditions was characterized by a modulation of the background oscillatory activity in N2 sleep, outlining a possible mechanism through which the brain aligns periods of high neuronal excitability to the expected sound onset. The violation of auditory and cardio-audio regularity elicits cardiac and neural surprise responses across vigilance stages. Significance StatementAcross vigilance states, the human brain can generate predictions about the future based on past sensory regularities. While this is evident for environmental stimuli, the role of bodily signals in forming sensory prediction remains unknown. Here, we show that the human brain utilizes the temporal relationship between cardiac and auditory inputs in order to anticipate upcoming sounds during wakefulness and sleep. After presenting sounds in synchrony with the ongoing heartbeat, a sound omission elicited both a heartbeat deceleration and a prediction error signal as measured by the electroencephalographic response. Heartbeat signals support auditory regularity encoding during sleep and wakefulness, highlighting one mechanism for optimizing the detection of unexpected stimuli by taking advantage of the continuously monitored cardiac signals.

neuroscience↗

bioRxiv2021

MICS1 is the Ca2+ /H+ antiporter of mammalian mitochondria

Mitochondrial Ca2+ ions are crucial regulators of bioenergetics, cell death pathways and cytosolic Ca2+ homeostasis. Mitochondrial Ca2+ content strictly depends on Ca2+ transporters. In recent decades, the major players responsible for mitochondrial Ca2+ uptake and release have been identified, except the mitochondrial Ca2+/H+ exchanger (CHE). Originally identified as the mitochondrial K+/H+ exchanger, LETM1 was also considered as a candidate for the mitochondrial CHE. Defining the mitochondrial interactome of LETM1, we identified MICS1, the only mitochondrial member of the TMBIM family. Applying cell-based and cell-free biochemical assays, here we demonstrate that MICS1 is responsible for the Na+- and permeability transition pore-independent mitochondrial Ca2+ release and identify MICS1 as the long-sought mitochondrial CHE. This finding provides the final piece of the puzzle of mitochondrial Ca2+ transporters and opens the door to exploring its importance in health and disease, and to developing drugs modulating Ca2+ exchange.

biochemistry↗

bioRxiv2021

Decomposing age effects in EEG alpha power

Increasing life expectancy is prompting the need to understand how the brain changes during healthy aging. Research utilizing Electroencephalography (EEG) has found that the power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in the data may confound results and thus require re-investigation of these findings. The present report aims at analyzing a pilot and two additional independent samples (total N = 533) of resting-state EEG from healthy young and elderly individuals. A newly developed algorithm will be utilized that allows the decomposition of the measured signal into aperiodic and aperiodic-adjusted signal components. By using multivariate sequential Bayesian updating of the age effect in each signal component, evidence across the datasets will be accumulated. It is hypothesized that previously reported age-related alpha power differences will disappear when absolute power is adjusted for the aperiodic signal component. Consequently, age-related differences in the intercept and slope of the aperiodic signal component are expected. Importantly, using a battery of neuropsychological tests, we will assess how the previously reported relationship between cognitive functions and alpha oscillations changes when taking the aperiodic signal into account; this will be done on data of the young and aged individuals separately. The aperiodic signal components and adjusted alpha parameters could potentially offer a promising biomarker for cognitive decline, thus finally the test-retest reliability of the aperiodic and aperiodic-adjusted signal components will be assessed.

neuroscience↗

bioRxiv2019

Detection of interictal epileptiform discharges:A comparison of on-scalp MEG and conventional MEGmeasurements

Magnetoencephalography (MEG) is an important part of epilepsy evaluations because of its unsurpassed ability to detect interictal epileptiform discharges (IEDs). This ability may be improved by next-generation MEG sensors, where sensors are placed directly on the scalp instead of in a fixed-size helmet, as in todays conventional MEG systems. In order to investigate the usefulness of on-scalp MEG measurements we performed the first-ever measurements of on-scalp MEG on an epilepsy patient. The measurement was conducted as a benchmarking study, with special focus on IED detection. An on-scalp high-temperature SQUID system was utilized alongside a conventional low-temperature "in-helmet" SQUID system. EEG was co-registered during both recordings. Visual inspection of IEDs in the raw on-scalp MEG data was unfeasible why a novel machine learning-based IED-detection algorithm was developed to guide IED detection in the on-scalp MEG data. A total of 24 IEDs were identified visually from the conventional in-helmet MEG session (of these, 16 were also seen in the EEG data; eight were detected only by MEG). The on-scalp MEG data contained a total of 47 probable IEDs of which 16 IEDs were co-registered by the EEG, and 31 IEDs were on-scalp MEG-unique IEDs found by the IED detection algorithm. We present a successful benchmarking study where on-scalp MEG are compared to conventional in-helmet MEG in a temporal lobe epilepsy patient. Our results demonstrate that on-scalp MEG measurements are feasible on epilepsy patients, and indicate that on-scalp MEG might capture IEDs not seen by other non-invasive modalities.

neuroscience↗

bioRxiv2019

On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG

Magnetoencephalography (MEG) has a unique capacity to resolve the spatio-temporal development of brain activity from non-invasive measurements. Conventional MEG, however, relies on sensors that sample from a distance (20-40 mm) to the head due to thermal insulation requirements (the MEG sensors function at 4 K in a helmet). A gain in signal strength and spatial resolution may be achieved if sensors are moved closer to the head. Here, we report a study comparing measurements from a seven-channel on-scalp SQUID MEG system to those from a conventional (in-helmet) SQUID MEG system.\n\nWe compared spatio-temporal resolution between on-scalp and conventional MEG by comparing the discrimination accuracy for neural activity patterns resulting from stimulating five different phalanges of the right hand. Because of proximity and sensor density differences between on-scalp and conventional MEG, we hypothesized that on-scalp MEG would allow for a more high-resolved assessment of these activity patterns, and therefore also a better classification performance in discriminating between neural activations from the different phalanges.\n\nWe observed that on-scalp MEG provided better classification performance during an early post-stimulus period (15-30 ms). This corresponded to electroencephalographic (EEG) response components N16 and P23, and was an unexpected observation as these components are usually not observed in conventional MEG. They indicate that on-scalp MEG opens up for a richer registration of the cortical signal, allowing for sensitivity to what are potentially sources in the thalamo-cortical radiation and to quasi-radial sources.\n\nWe had originally expected that on-scalp MEG would provide better classification accuracy based on activity in proximity to the P60m component compared to conventional MEG. This component indeed allowed for the best classification performance for both MEG systems (60-75%, chance 50%). However, we did not find that on-scalp MEG allowed for better classification than conventional MEG at this latency. We believe this may be due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We discuss how sensor density and coverage as well as between-phalange source field dissimilarities may influence our hypothesis testing, which we believe to be useful for future benchmarking measurements.

neuroscience↗

bioRxiv2019

Sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration in on-scalp MEG

Source modelling in magnetoencephalography (MEG) requires precise co-registration of the sensor array and the anatomical structure of the measured individuals head. In conventional MEG, positions and orientations of the sensors relative to each other are fixed and known beforehand, requiring only localization of the head relative to the sensor array. Since the sensors in on-scalp MEG are positioned on the scalp, locations of the individual sensors depend on the subjects head shape and size. The positions and orientations of on-scalp sensors must therefore be measured at every recording. This can be achieved by inverting conventional head localization, localizing the sensors relative to the head - rather than the other way around.\n\nIn this study we present a practical method for localizing sensors using magnetic dipole-like coils attached to the subjects head. We implement and evaluate the method in a set of on-scalp MEG recordings using a 7-channel on-scalp MEG system based on high critical temperature superconducting quantum interference devices (high-Tc SQUIDs). The method provides accurate estimates of individual sensor positions and orientations with short averaging time ([≤] 2 mm and < 3 degrees, respectively, with 1-second averaging), enabling continuous sensor localization. Calibrating and jointly localizing the sensor array can further improve the localization accuracy (< 1 mm and < 2.5 degrees, respectively, with 1-second coil recordings).\n\nWe demonstrate source localization of on-scalp recorded somatosensory evoked activity based on co-registration with our method. Equivalent current dipole fits of the evoked responses corresponded well (within 5.3 mm) with those based on a commercial, whole-head MEG system.

neuroscience↗

bioRxiv2019

A 7-channel high-Tc SQUID-based on-scalp MEG system

Due to their higher operating temperature, high-Tc superconducting quantum interference devices (SQUIDs) require less thermal insulation than the low-Tc sensors that are utilized in commercial magnetoen-cephalography (MEG) systems. As a result, they can be placed closer to the head, where neuromagnetic fields are higher and more focal, potentially leading to higher spatial resolution. The first such on-scalp MEG measurements using high-Tc SQUIDs have shown the potential of the technology. In order to be useful for neuroscience and clinical applications, however, multi-channel systems are required. Herein, we present a 7-channel on-scalp MEG system based on high-Tc SQUIDs. The YBCO SQUID magnetometers are arranged in a dense, head-aligned hexagonal array inside a single, liquid nitrogen-cooled cryostat. The spacing between the magnetometers and the head is adjustable down to 1 mm. The sensors are side-mounted on the cryostat that is mounted on an articulated armature for recordings on arbitrary head locations of a seated subject. We demonstrate white noise levels of 50-130 fT/Hz1/2 at 10 Hz, sensor-to-sensor crosstalk values of <0.6%, and single-fill operation times of 16 hours. We validate the system with MEG recordings of visual alpha modulation and auditory evoked fields. The system is thus useful for densely and sensitively sampling neuromagnetic fields over any[~] 10 cm2 patch of the scalp surface over the course of a day.

neuroscience↗