Mapping Function in the Human Brain with Magnetoencephalography, Anatomical Magnetic Resonance Imaging, and Functional Magnetic Resonance Imaging

George, John; Aine, Cheryl J.; Mosher, John C.; Schmidt, D.; Ranken, Doug; Schlitt, H. A.; Wood, Charles Cresson; Lewine, Jeffrey D.; Sanders, John C.; Belliveau, John W.

doi:10.1097/00004691-199509010-00002

Cited by 206 publications

(78 citation statements)

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“…Therefore, given the complexity of the investigated processes and the wide range of characteristics for the different imaging technologies, the use of multimodal approaches is gaining the interest of the scientific community [11], [12], [13], [14]. The underlying principle is that all neuroimaging techniques provide in vivo measures of brain function but each has its own set of assets and drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

Merzagora

İzzetoğlu

Polikar

et al. 2009

Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience

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Abstract. Although neuroimaging has greatly expanded our knowledge about the brain-behavior relation, combining multiple neuroimaging modalities with complementing strengths can overcome some limitations encountered when using a single modality. Valuable candidates for a multimodal approach are functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). fNIRS is an imaging technology that localizes hemodynamic changes within the cortex. However, hemodynamic activation is an intrinsically slow process. On the other hand, EEG has excellent time resolution by directly measuring the manifestation of the brain electrical activity at the scalp. Based on their complementary strengths, the integration of fNIRS and EEG may provide higher spatiotemporal resolution than either method alone. In this effort, we integrate fNIRS and EEG to evaluate the behavioral performance of six healthy adults in a working memory task. To this end, features extracted from fNIRS and EEG were used separately, as well as in combination, and their performances were compared against each other.

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Section: Introductionmentioning

confidence: 99%

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

Merzagora

İzzetoğlu

Polikar

et al. 2009

Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience

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“…Techniques such as electroencephalography (EEG) and magenetoencephalography (MEG) measure the electromagnetic fields produced during neuronal activation to map brain function (Darvas et al 2004;George et al 1995). Other techniques such as functional near-infrared spectroscopy (fNIRS) (Plichta et al 2006), functional magnetic resonance imaging (fMRI) (Matthews 2002), positron emission tomography (PET) (Turner and Jones 2003), single photon emission computed tomography (SPECT) (Wyper 1993), and functional transcranial Doppler sonography (fTCD) (Stroobant and Vingerhoets 2000) measure changes in blood flow or blood gas concentration as surrogates for changes in neuronal activation.…”

Section: Introductionmentioning

confidence: 99%

Functional Tissue Pulsatility Imaging of the Brain During Visual Stimulation

Kucewicz

Dunmire

Leotta

et al. 2007

Ultrasound in Medicine & Biology

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Functional tissue pulsatility imaging (fTPI) is a new ultrasonic technique being developed to map brain function by measuring changes in tissue pulsatility due to changes in blood flow with neuronal activation. The technique is based in principle on plethysmography, an older, non-ultrasound technology for measuring expansion of a whole limb or body part due to perfusion. Perfused tissue expands by a fraction of a percent early in each cardiac cycle when arterial inflow exceeds venous outflow and relaxes later in the cardiac cycle when venous drainage dominates. Tissue pulsatility imaging (TPI) uses tissue Doppler signal processing methods to measure this pulsatile "plethysmographic" signal from hundreds or thousands of sample volumes in an ultrasound image plane. A feasibility study was conducted to determine if TPI could be used to detect regional brain activation during a visual contrast-reversing checkerboard block paradigm study. During a study, ultrasound data were collected transcranially from the occipital lobe as a subject viewed alternating blocks of a reversing checkerboard (stimulus condition) and a static, gray screen (control condition). Multivariate Analysis of Variance (MANOVA) was used to identify sample volumes with significantly different pulsatility waveforms during the control and stimulus blocks. In 7 out 14 studies, consistent regions of activation were detected from tissue around the major vessels perfusing the visual cortex.

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“…The source volume consisted of 17,342 cortical volume elements (voxels) from the subject's anatomical MRI scan with the cortex segmented using tools developed in our laboratory and described elsewhere. [3,4] For the compact regions of activation which make up our model we used spheres of 1 crn radius such that any voxel within a sphere is considered to be part of the "active" region. We allowed no more than 4 regions with relative prior probability of 1..…”

Section: Pminmentioning

confidence: 99%

A Method for Locating Regions Containing Neural Activation at a Given Confidence Level from MEG Data

Schmidt

George

2000

Biomag 96

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Mapping Function in the Human Brain with Magnetoencephalography, Anatomical Magnetic Resonance Imaging, and Functional Magnetic Resonance Imaging

Cited by 206 publications

References 0 publications

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

Functional Tissue Pulsatility Imaging of the Brain During Visual Stimulation

A Method for Locating Regions Containing Neural Activation at a Given Confidence Level from MEG Data

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