MEG and Multimodal Integration

Ahlfors, Seppo P.

doi:10.1007/978-3-030-00087-5_7

Cited by 2 publications

(1 citation statement)

References 143 publications

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“…Major contributions to the primary currents come from postsynaptic dendritic currents in cortical pyramidal cells. The spatial sensitivity patterns to the primary currents are different for MEG and EEG, which allows MEG and EEG to provide complementary information about the same type of sources [279]. Clinically, MEG combined with EEG and structural MRI has been maturely applied to the localization of focal epilepsy, providing a powerful tool for the treatment and diagnosis of neurological diseases [280].…”

Section: In Vivo Electrophysiological Recording In Brain Mappingmentioning

confidence: 99%

Structural and functional imaging of brains

Liu

Zhu²,

Zhang³

et al. 2022

Sci. China Chem.

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Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.

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Section: In Vivo Electrophysiological Recording In Brain Mappingmentioning

confidence: 99%

Structural and functional imaging of brains

Liu

Zhu²,

Zhang³

et al. 2022

Sci. China Chem.

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Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum

et al. 2022

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Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG). Specifically, source estimation results showed differences between AS and neurotypically developing (NTD) subjects in the brain response to 25-Hz vibrotactile stimulation of the right fingertips, with lower inter-trial coherence (ITC) observed in the AS group. Here, we examined whether these group differences can be detected without source estimation using scalp electroencephalography (EEG), which is more commonly available in clinical settings than MEG, and therefore offers a greater potential for clinical translation. To that end, we recorded simultaneous whole-head MEG and EEG in 14 AS and 10 NTD subjects (age 15–28 years) using the same vibrotactile paradigm. Based on the scalp topographies, small sets of left hemisphere MEG and EEG sensors showing the maximum overall ITC were selected for group comparisons. Significant differences between the AS and NTD groups in ITC at 25 Hz as well as at 50 Hz were recorded in both MEG and EEG sensor data. For each measure, the mean ITC was lower in the AS than in the NTD group. EEG ITC values correlated with behaviorally assessed somatosensory sensation avoiding scores. The results show that information about ITC from MEG and EEG signals have substantial overlap, and thus EEG sensor-based ITC measures of the AS somatosensory processing biomarker previously identified using source localized MEG data have a potential to be developed into clinical use in AS, thanks to the higher accessibility to EEG in clinical settings.

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MEG and Multimodal Integration

Cited by 2 publications

References 143 publications

Structural and functional imaging of brains

Structural and functional imaging of brains

Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum

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