Functional source separation applied to induced visual gamma activity

Giulia Barbati, Camillo Porcaro, Avgis Hadjipapas, Peyman Adjamian, Vittorio Pizzella, Gian Luca Romani, Stefano Seri, Franca Tecchio, Gareth R. Barnes

Research output: Contribution to journalArticle

Abstract

Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20-70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data.
LanguageEnglish
Pages131-141
Number of pages11
JournalHuman Brain Mapping
Volume29
Issue number2
DOIs
Publication statusPublished - Feb 2008

Fingerprint

Passive Cutaneous Anaphylaxis
Magnetometry
Visual Cortex
Principal Component Analysis
Head
hydroquinone

Keywords

  • functional source separation
  • blind source separation
  • synthetic aperture magnetometry
  • magnetoencephalography
  • induced gamma activity

Cite this

Barbati, G., Porcaro, C., Hadjipapas, A., Adjamian, P., Pizzella, V., Romani, G. L., ... Barnes, G. R. (2008). Functional source separation applied to induced visual gamma activity. Human Brain Mapping, 29(2), 131-141. https://doi.org/10.1002/hbm.20375
Barbati, Giulia ; Porcaro, Camillo ; Hadjipapas, Avgis ; Adjamian, Peyman ; Pizzella, Vittorio ; Romani, Gian Luca ; Seri, Stefano ; Tecchio, Franca ; Barnes, Gareth R. / Functional source separation applied to induced visual gamma activity. In: Human Brain Mapping. 2008 ; Vol. 29, No. 2. pp. 131-141.
@article{018a94d29b6b40a78a2da28d5bbf22d9,
title = "Functional source separation applied to induced visual gamma activity",
abstract = "Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20-70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data.",
keywords = "functional source separation, blind source separation, synthetic aperture magnetometry, magnetoencephalography, induced gamma activity",
author = "Giulia Barbati and Camillo Porcaro and Avgis Hadjipapas and Peyman Adjamian and Vittorio Pizzella and Romani, {Gian Luca} and Stefano Seri and Franca Tecchio and Barnes, {Gareth R.}",
year = "2008",
month = "2",
doi = "10.1002/hbm.20375",
language = "English",
volume = "29",
pages = "131--141",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley",
number = "2",

}

Barbati, G, Porcaro, C, Hadjipapas, A, Adjamian, P, Pizzella, V, Romani, GL, Seri, S, Tecchio, F & Barnes, GR 2008, 'Functional source separation applied to induced visual gamma activity' Human Brain Mapping, vol. 29, no. 2, pp. 131-141. https://doi.org/10.1002/hbm.20375

Functional source separation applied to induced visual gamma activity. / Barbati, Giulia; Porcaro, Camillo; Hadjipapas, Avgis; Adjamian, Peyman; Pizzella, Vittorio; Romani, Gian Luca; Seri, Stefano; Tecchio, Franca; Barnes, Gareth R.

In: Human Brain Mapping, Vol. 29, No. 2, 02.2008, p. 131-141.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Functional source separation applied to induced visual gamma activity

AU - Barbati, Giulia

AU - Porcaro, Camillo

AU - Hadjipapas, Avgis

AU - Adjamian, Peyman

AU - Pizzella, Vittorio

AU - Romani, Gian Luca

AU - Seri, Stefano

AU - Tecchio, Franca

AU - Barnes, Gareth R.

PY - 2008/2

Y1 - 2008/2

N2 - Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20-70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data.

AB - Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20-70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data.

KW - functional source separation

KW - blind source separation

KW - synthetic aperture magnetometry

KW - magnetoencephalography

KW - induced gamma activity

UR - http://www.scopus.com/inward/record.url?scp=39749127082&partnerID=8YFLogxK

UR - http://onlinelibrary.wiley.com/doi/10.1002/hbm.20375/full

U2 - 10.1002/hbm.20375

DO - 10.1002/hbm.20375

M3 - Article

VL - 29

SP - 131

EP - 141

JO - Human Brain Mapping

T2 - Human Brain Mapping

JF - Human Brain Mapping

SN - 1065-9471

IS - 2

ER -

Barbati G, Porcaro C, Hadjipapas A, Adjamian P, Pizzella V, Romani GL et al. Functional source separation applied to induced visual gamma activity. Human Brain Mapping. 2008 Feb;29(2):131-141. https://doi.org/10.1002/hbm.20375