Alexandria McPherson

All Publications

• Noise Optimization of Basic Signal Component Extraction for Cryogenic and On-Scalp Magnetoencephalography (MEG). bioRxiv : the preprint server for biology McPherson, A., Sanchirico, S., Xu, A., Larson, E., Kaestner, M., Turner, W., Gwilliams, L., Taulu, S. 2026

  Abstract

  Magnetoencephalography (MEG) measures human neural activity non-invasively with spatio-temporal precision, and has been foundational in enabling impactful discoveries in cognitive neuroscience. New on-scalp MEG sensor technologies, such as OPM-MEG, offer the opportunity to capture more information about the neuronal magnetic fields with higher sensitivity to more complex, higher order spatial components, leading to improved source localization. The accuracy of MEG and OPM-MEG source localization relies on data preprocessing techniques to isolate the neuronal fields from other magnetic and biomagnetic sources through signal space separation, rejection, and suppression methods. Current preprocessing methods risk rejecting brain signals of interest, or can spread sensor noise artifacts unknowingly. Here we propose a novel preprocessing method for MEG, and test the extent to which it overcomes limitations of prior methods. Specifically, we derive, apply, and assess a novel signal space separation (SSS) method with Foster's inverse, a weighted matrix inversion protocol that can utilize information about the MEG sensor noise and artifacts to reconstruct neuronal activity. With simulations, phantom head cryogenic MEG recordings, and subject recordings with two OPM-MEG systems, we show that Foster's inverse with SSS offers a more robust and stable reconstruction of the neuronal magnetic fields, especially in the face of sensor noise and artifacts. As the field of cognitive neuroscience continues to embrace MEG and OPM-MEG, Foster's inverse with SSS offers a robust and powerful data preprocessing technique for reducing noise and improving source localization of the underlying neuronal currents.

  View details for DOI 10.64898/2026.07.21.739883

  View details for PubMedID 42539285

  View details for PubMedCentralID PMC13419842

• Refined signal space separation methods for on-scalp MEG systems. Physics in medicine and biology McPherson, A., Fahmy, I., Larson, E., Yeo, W., Holmes, N., Taulu, S. 2025; 70 (13)

  Abstract

  Objective.The reliability of biomagnetic measurements is improved by data processing techniques like the signal space separation (SSS) method, which transforms multichannel signals into device-independent channels with separate components for internal biomagnetic and external interference signals based on sensor geometry. Newer on-scalp sensors, such as optically-pumped magnetometers (OPMs), have recently been deployed in magnetoencephalography (MEG) systems, bringing a need for refined SSS variants to capture the potentially improved spatial resolution provided by the on-scalp sensors. Standard single-origin SSS may fail to capture the full brain-space when the sensors are on scalp. In this paper, we propose potential solutions to this problem including novel multi-origin SSS (mSSS). With multiple optimized origins and radii used together, the basis can span the brain-space without encroaching on the sensor space. Other adaptations to SSS include vector spheroidal harmonics, which create signal space expansions using ellipsoidal geometry to model the brain-space. This adaptation is further modified to combine an interior spheroidal with exterior single-SSS.Approach.Focusing on two-origin mSSS, the spheroidal constructions and the single-origin SSS are investigated with simulated data from an internal current dipole source coupled with an external interference signal with geometry from the 432-channel Kernel Flux OPM system, the 306-channel MEGIN/Elekta Neuromag SQUID system, and the 192-Channel Triaxial QuSpin OPM system. Finally, each variant is used to process collected data including auditory evoked data measured at the University of Washington with the Kernel Flux OPM system, previously recorded empty-room data collected in a lightly-shielded magnetically shielded room with 192-channel third generation triaxial QuSpin Zero Field Magnetometers, and publicly available single-subject audiovisual data collected with an 86-Channel dual-axis QuSpin OPM system at the University College London.Main results.The mSSS method has comparable or better stability to the SSS method in all sensor geometries and reconstructs interior simulated signals while successfully suppressing exterior interference, and performs better in simulated cases with variably placed on-scalp MEG systems. Additionally, results with Kernel and QuSpin data show the mSSS basis provides a lower noise floor than other SSS variants and had the best performance with on-scalp systems, even with low-channel-count OPM systems.Significance.With on-scalp MEG systems becoming more widely available, the MEG community needs updated data analysis techniques. mSSS is a straightforward and robust modification to the SSS method which functions for novel on-scalp sensor systems without needing drastic modification to the underlying mathematical method.

  View details for DOI 10.1088/1361-6560/ade6ba

  View details for PubMedID 40541227

• Excess carrier concentration in silicon devices and wafers: How bulk properties are expected to accelerate light and elevated temperature degradation MRS ADVANCES McPherson, A. N., Karas, J. F., Young, D. L., Repins, I. L. 2022; 7 (21): 438-443

  View details for DOI 10.1557/s43580-022-00222-5

  View details for Web of Science ID 000752208600004