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

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On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG. / Andersen, Lau M.; Pfeiffer, Christoph; Ruffieux, Silvia; Riaz, Bushra; Winkler, Dag; Schneiderman, Justin F.; Lundqvist, Daniel.

I: NeuroImage, Bind 221, 117157, 11.2020.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

Harvard

Andersen, LM, Pfeiffer, C, Ruffieux, S, Riaz, B, Winkler, D, Schneiderman, JF & Lundqvist, D 2020, 'On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG', NeuroImage, bind 221, 117157. https://doi.org/10.1016/j.neuroimage.2020.117157

APA

Andersen, L. M., Pfeiffer, C., Ruffieux, S., Riaz, B., Winkler, D., Schneiderman, J. F., & Lundqvist, D. (2020). On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG. NeuroImage, 221, [117157]. https://doi.org/10.1016/j.neuroimage.2020.117157

CBE

Andersen LM, Pfeiffer C, Ruffieux S, Riaz B, Winkler D, Schneiderman JF, Lundqvist D. 2020. On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG. NeuroImage. 221:Article 117157. https://doi.org/10.1016/j.neuroimage.2020.117157

MLA

Vancouver

Andersen LM, Pfeiffer C, Ruffieux S, Riaz B, Winkler D, Schneiderman JF o.a. On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG. NeuroImage. 2020 nov;221. 117157. https://doi.org/10.1016/j.neuroimage.2020.117157

Author

Andersen, Lau M. ; Pfeiffer, Christoph ; Ruffieux, Silvia ; Riaz, Bushra ; Winkler, Dag ; Schneiderman, Justin F. ; Lundqvist, Daniel. / On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG. I: NeuroImage. 2020 ; Bind 221.

Bibtex

@article{41ea087f4c07485db80234e3bc45e667,
title = "On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG",
abstract = "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. We compared the 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. We observed that on-scalp MEG provided better classification performance during an early post-stimulus period (10–20 ​ms). This corresponded to the electroencephalographic (EEG) component P16/N16 and was an unexpected observation as this component is usually not observed in conventional MEG. This finding shows that on-scalp MEG enables a richer registration of the cortical signal, indicating a sensitivity to what are potentially sources in the thalamo-cortical radiation. We 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 suggest that this absence of differences is due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We show how the current sensor coverage may have limited our chances to register the necessary between-phalange source field dissimilarities for fair hypothesis testing, an approach we otherwise believe to be useful for future benchmarking measurements.",
author = "Andersen, {Lau M.} and Christoph Pfeiffer and Silvia Ruffieux and Bushra Riaz and Dag Winkler and Schneiderman, {Justin F.} and Daniel Lundqvist",
year = "2020",
month = nov,
doi = "10.1016/j.neuroimage.2020.117157",
language = "English",
volume = "221",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG

AU - Andersen, Lau M.

AU - Pfeiffer, Christoph

AU - Ruffieux, Silvia

AU - Riaz, Bushra

AU - Winkler, Dag

AU - Schneiderman, Justin F.

AU - Lundqvist, Daniel

PY - 2020/11

Y1 - 2020/11

N2 - 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. We compared the 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. We observed that on-scalp MEG provided better classification performance during an early post-stimulus period (10–20 ​ms). This corresponded to the electroencephalographic (EEG) component P16/N16 and was an unexpected observation as this component is usually not observed in conventional MEG. This finding shows that on-scalp MEG enables a richer registration of the cortical signal, indicating a sensitivity to what are potentially sources in the thalamo-cortical radiation. We 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 suggest that this absence of differences is due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We show how the current sensor coverage may have limited our chances to register the necessary between-phalange source field dissimilarities for fair hypothesis testing, an approach we otherwise believe to be useful for future benchmarking measurements.

AB - 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. We compared the 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. We observed that on-scalp MEG provided better classification performance during an early post-stimulus period (10–20 ​ms). This corresponded to the electroencephalographic (EEG) component P16/N16 and was an unexpected observation as this component is usually not observed in conventional MEG. This finding shows that on-scalp MEG enables a richer registration of the cortical signal, indicating a sensitivity to what are potentially sources in the thalamo-cortical radiation. We 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 suggest that this absence of differences is due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We show how the current sensor coverage may have limited our chances to register the necessary between-phalange source field dissimilarities for fair hypothesis testing, an approach we otherwise believe to be useful for future benchmarking measurements.

UR - http://www.scopus.com/inward/record.url?scp=85088784919&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2020.117157

DO - 10.1016/j.neuroimage.2020.117157

M3 - Journal article

C2 - 32659354

AN - SCOPUS:85088784919

VL - 221

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

M1 - 117157

ER -