scholarly journals Data‐driven model optimization for optically pumped magnetometer sensor arrays

2019 ◽  
Vol 40 (15) ◽  
pp. 4357-4369 ◽  
Author(s):  
Leonardo Duque‐Muñoz ◽  
Tim M. Tierney ◽  
Sofie S. Meyer ◽  
Elena Boto ◽  
Niall Holmes ◽  
...  
Keyword(s):  
Sensor Arrays ◽  
Data Driven ◽  
Model Optimization ◽  
Optically Pumped

scholarly journals Measuring MEG closer to the brain: Performance of on-scalp sensor arrays

2016 ◽  
Author(s):  
Joonas Iivanainen ◽  
Matti Stenroos ◽  
Lauri Parkkonen
Keyword(s):  
Sensor Arrays ◽  
Element Model ◽  
Magnetic Resonance Images ◽  
Field Pattern ◽  
Optically Pumped ◽  
Point Spread Functions ◽  
Field Patterns ◽  
Compartment Boundary ◽  
Volume Currents ◽  
Squid Magnetometers

AbstractOptically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalogra-phy (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the invidual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers).We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle.Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively.

scholarly journals On-scalp MEG system utilizing an actively shielded array of optically-pumped magnetometers

2018 ◽  
Author(s):  
Joonas Iivanainen ◽  
Rasmus Zetter ◽  
Mikael Grön ◽  
Karoliina Hakkarainen ◽  
Lauri Parkkonen
Keyword(s):  
Spin Exchange ◽  
Dynamic Control ◽  
Sensor Arrays ◽  
Low Frequency ◽  
Sensor Calibration ◽  
Optically Pumped ◽  
Magnetic Shields ◽  
Brain Responses ◽  
Shielding Factor ◽  
Magnetically Shielded Room

AbstractThe spatial resolution of magnetoencephalography (MEG) can be increased from that of conventional SQUID-based systems by employing on-scalp sensor arrays of e.g. optically-pumped magnetometers (OPMs). However, OPMs reach sufficient sensitivity for neuromagnetic measurements only when operated in a very low absolute magnetic field of few nanoteslas or less, usually not reached in a typical magnetically shielded room constructed for SQUID-based MEG. Moreover, field drifts affect the calibration of OPMs. Static and dynamic control of the ambient field is thus necessary for good-quality neuromagnetic measurements with OPMs. Here, we describe an on-scalp MEG system that utilizes OPMs and external compensation coils that provide static and dynamic shielding against ambient fields.In a conventional two-layer magnetically shielded room, our coil system reduced the maximum remanent DC-field component within an 8-channel OPM array from 70 to less than 1 nT, enabling the sensors to operate in the sensitive spin exchange relaxation-free regime. When compensating field drifts below 4 Hz, a low-frequency shielding factor of 22 dB was achieved, which reduced the peak-to-peak drift from 1.3 to 0.4 nT and thereby the standard deviation of the sensor calibration from 1.6% to 0.4%. Without band-limiting the field that is compensated, a low-frequency shielding factor of 43 dB was achieved.We validated the system by measuring brain responses to electric stimulation of the median nerve. With dynamic shielding and digital interference suppression methods, single-trial somatosensory evoked responses could be detected. Our results advance the deployment of OPM-based on-scalp MEG in lighter magnetic shields.

scholarly journals The EBRAINS NeuroFeatureExtract: An Online Resource for the Extraction of Neural Activity Features From Electrophysiological Data

2021 ◽  
Vol 15 ◽  
Author(s):  
Luca L. Bologna ◽  
Roberto Smiriglia ◽  
Dario Curreri ◽  
Michele Migliore
Keyword(s):  
Neural Activity ◽  
Ad Hoc ◽  
Neural Model ◽  
Data Driven ◽  
Neural Dynamics ◽  
Model Optimization ◽  
Activity Data ◽  
Online Resource ◽  
Public Repositories ◽  
Scientific Questions

The description of neural dynamics, in terms of precise characterizations of action potential timings and shape and voltage related measures, is fundamental for a deeper understanding of the neural code and its information content. Not only such measures serve the scientific questions posed by experimentalists but are increasingly being used by computational neuroscientists for the construction of biophysically detailed data-driven models. Nonetheless, online resources enabling users to perform such feature extraction operation are lacking. To address this problem, in the framework of the Human Brain Project and the EBRAINS research infrastructure, we have developed and made available to the scientific community the NeuroFeatureExtract, an open-access online resource for the extraction of electrophysiological features from neural activity data. This tool allows to select electrophysiological traces of interest, fetched from public repositories or from users’ own data, and provides ad hoc functionalities to extract relevant features. The output files are properly formatted for further analysis, including data-driven neural model optimization.

scholarly journals Compensation System for Biomagnetic Measurements with Optically Pumped Magnetometers inside a Magnetically Shielded Room

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4563 ◽  
Author(s):  
Anna Jodko-Władzińska ◽  
Krzysztof Wildner ◽  
Tadeusz Pałko ◽  
Michał Władziński
Keyword(s):  
Magnetic Field ◽  
Quantum Interference ◽  
Spin Exchange ◽  
Initial Conditions ◽  
Sensor Arrays ◽  
Compensation System ◽  
Zero Field ◽  
Optically Pumped ◽  
Ambient Magnetic Field ◽  
Magnetically Shielded Room

Magnetography with superconducting quantum interference device (SQUID) sensor arrays is a well-established technique for measuring subtle magnetic fields generated by physiological phenomena in the human body. Unfortunately, the SQUID-based systems have some limitations related to the need to cool them down with liquid helium. The room-temperature alternatives for SQUIDs are optically pumped magnetometers (OPM) operating in spin exchange relaxation-free (SERF) regime, which require a very low ambient magnetic field. The most common two-layer magnetically shielded rooms (MSR) with residual magnetic field of 50 nT may not be sufficiently magnetically attenuated and additional compensation of external magnetic field is required. A cost-efficient compensation system based on square Helmholtz coils was designed and successfully used for preliminary measurements with commercially available zero-field OPM. The presented setup can reduce the static ambient magnetic field inside a magnetically shielded room, which improves the usability of OPMs by providing a proper environment for them to operate, independent of initial conditions in MSR.

scholarly journals Pragmatic spatial sampling for wearable MEG arrays

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tim M. Tierney ◽  
Stephanie Mellor ◽  
George C. O’Neill ◽  
Niall Holmes ◽  
Elena Boto ◽  
...  
Keyword(s):  
New Technologies ◽  
Signal To Noise Ratio ◽  
Sensor Arrays ◽  
Spatial Sampling ◽  
Spatial Discrimination ◽  
Optically Pumped ◽  
Deep Sources ◽  
Gain Errors ◽  
The Impact ◽  
Sensor Gain

AbstractSeveral new technologies have emerged promising new Magnetoencephalography (MEG) systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped MEG (OP-MEG) allows for a scalp mounted system that provides measurements within millimetres of the scalp surface. A question that arises in developing on-scalp systems is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to consider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources, density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (< 1 cm) can be achieved with relatively few sensors (< 100) at coarse spatial samplings (~ 30 mm) at high SNR. After this point approximately 50 more sensors are required for every 1 mm improvement in spatial discrimination. Comparable discrimination for traditional cryogenic systems require more channels by these same metrics. We also show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR. Finally, we also examine the limitation that aliasing due to undersampling has on the effective SNR of on-scalp sensors.

scholarly journals A Data-Driven Based Framework of Model Optimization and Neural Network Modeling for Microbial Fuel Cells

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 162036-162049 ◽  
Author(s):  
Fengying Ma ◽  
Yankai Yin ◽  
Shaopeng Pang ◽  
Jiaxun Liu ◽  
Wei Chen
Keyword(s):  
Neural Network ◽  
Fuel Cells ◽  
Microbial Fuel Cells ◽  
Network Modeling ◽  
Data Driven ◽  
Neural Network Modeling ◽  
Model Optimization

scholarly journals Requirements for coregistration accuracy in on-scalp MEG

2017 ◽  
Author(s):  
Rasmus Zetter ◽  
Joonas Iivanainen ◽  
Matti Stenroos ◽  
Lauri Parkkonen
Keyword(s):  
Sensor Arrays ◽  
Cryogenic Cooling ◽  
Minimum Norm ◽  
Forward Modelling ◽  
Optically Pumped ◽  
Position Errors ◽  
Sensor Position ◽  
Different Types ◽  
Position And Orientation ◽  
The Brain

AbstractRecent advances in magnetic sensing has made on-scalp magnetoencephalography (MEG) possible. In particular, optically-pumped magnetometers (OPMs) have reached sensitivity levels that enable their use in MEG. In contrast to the SQUID sensors used in current MEG systems, OPMs do not require cryogenic cooling and can thus be placed within millimetres from the head, enabling the construction of sensor arrays that conform to the shape of an individual’s head. To properly estimate the location of neural sources within the brain, one must accurately know the position and orientation of sensors in relation to the head. With the adaptable on-scalp MEG sensor arrays, this coregistration becomes more challenging than in current SQUID-based MEG systems that use rigid sensor arrays.Here, we used simulations to quantify how accurately one needs to know the position and orientation of sensors in an on-scalp MEG system. The effects that different types of localisation errors have on forward modelling and source estimates obtained by minimum-norm estimation, dipole fitting, and beamforming are detailed.We found that sensor position errors generally have a larger effect than orientation errors and that these errors affect the localisation accuracy of superficial sources the most. To obtain similar or higher accuracy than with current SQUID-based MEG systems, RMS sensor position and orientation errors should be < 4 mm and < 10°, respectively.

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