MEG Studies on the Connectivity of Brain Networks in Children

Johnson, Blake W.; He, Wei

doi:10.1007/978-3-030-00087-5_82

Cited by 4 publications

(5 citation statements)

References 128 publications

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Section: Methodsmentioning

confidence: 99%

“…Participants also performed manual button presses on a fibre optic response pad (Current Designs, Philadelphia) with the index finger of their dominant hand at a self-paced rate of about 1 per 2 seconds for 180 sec (see Figure 1B) (Cheyne et al, 2008;Cheyne et al, 2014;De Nil et al, 2021;Johnson & He, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…For the manual nonspeech task, participants performed self-paced button presses at a rate of about 1/ 2 seconds on a fibre optic response pad (Current Designs, Philadelphia) for 180sec (see Figure 1B). (Cheyne et al, 2008;Cheyne et al, 2014;De Nil et al, 2021;Johnson & He, 2019). Instructions were displayed for about 30s followed by a fixation cross, during which participants performed self-paced button pressed with the index finger of their dominant (right) hand at a rate of about 1 per 2 seconds for a total of about 90 trials.…”

Section: Participantsmentioning

confidence: 99%

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Decoding kinematic information from beta-band motor rhythms of speech motor cortex: A methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Anastasopoulou¹,

Cheyne²,

Lieshout³

et al. 2023

Preprint

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Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK; Alves et al., 2016), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements (Anastasopoulou et al., 2022). Data were collected from two healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances /ipa/ and /api/, produced at normal and faster rates (Anastasopoulou et al., 2022; Van Lieshout, 2007). The results show that (1) beta band (13-30 Hz) neuromotor oscillations are present and can be readily separated by filtering from the high frequency MASK coil fields; (2) primary speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere from the beta band signals; and (3) kinematic parameters of speech movements can be mapped on to neuromagnetic brain signals using multivariate pattern analytic techniques. These results show that MASK provides the capability, for the first time, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the brain recordings and in temporal and spatial co-register with the brain data. The co-registered MASK data dramatically improves the precision and inferential power of MEG measures of speech-related brain activity compared to previous methodological approaches. This new capability for measuring and characterising speech movement parameters, and the brain activities that control them, within the same experimental setup, paves the way for innovative cross-disciplinary studies of neuromotor control of human speech production, speech development, and speech motor disorders.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

See 1 more Smart Citation

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: A methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Anastasopoulou¹,

Cheyne²,

Lieshout³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Participants also performed manual button presses on a fibre optic response pad (Current Designs, Philadelphia) with the index finger of their dominant hand at a self-paced rate of about 1 per 2 s for 180 s (see Figure 1B) (Cheyne, 2008;Cheyne et al, 2014;Johnson and He, 2019;De Nil et al, 2021).…”

Section: Experimental Protocolmentioning

confidence: 99%

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Anastasopoulou,

Cheyne,

van Lieshout

et al. 2024

Front. Hum. Neurosci.

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IntroductionArticulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies.MethodsHere we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements. Data were collected from 10 healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances/ipa/ and /api/, produced at normal and faster rates.ResultsThe results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8–12 Hz) and beta band (13–30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques.DiscussionThese results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.

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“…In addition, MEG provides a better spatial resolution than EEG, being less susceptible to the spatial distortions in recorded brain activity caused by interactions between the signal and tissue layers with variable electric conductivity surrounding the brain 30 . Resting-state MEG recordings can be used to infer functional networks 31, 32 , in a similar way as fMRI in AE 16 . MEG has been widely used in paediatric epilepsy to predict cognitive outcomes 33 and has the same advantages as EEG, i.e.…”

Section: Introductionmentioning

confidence: 99%

Linking brain networks to cognition with magnetoencephalography in paediatric autoimmune encephalitis

Billaud,

Wood,

Griffiths-King

et al. 2024

Preprint

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Paediatric autoimmune encephalitis (e.g., acute disseminated encephalomyelitis, N-methyl-D-aspartate receptor antibody encephalitis) is an inflammatory brain disease that causes cognitive deficits, psychiatric symptoms, seizures, MRI, and EEG abnormalities. Patients can continue to experience residual cognitive difficulties months to years after the acute illness. Magnetoencephalography (MEG) can examine neural changes in the absence of frank structural abnormalities and may help identify factors predicting children at risk of long-term cognitive deficits. We predicted that theta and delta brain functional connectivity networks would be associated with processing speed and working memory in children with autoimmune encephalitis. Participants were children diagnosed with autoimmune encephalitis at least 18 months before testing and typically developing children. All completed MEG recording (Elekta Neuromag Triux) at rest, eyes open with a fixation cross during six minutes; T1 MRI scans; and cognitive evaluation using the primary subtests of the Weschler Intelligence Scale for Children, fifth edition. Brain connectivity, specifically in delta and theta brain activity, was estimated with amplitude envelope correlation, and network efficiency was measured using graph measures (global efficiency, local efficiency, modularity). The measures were compared across the two groups with permutation correction for multiple thresholds. Finally, statistical associations with processing speed and working memory scores were tested in the autoimmune encephalitis group. Age and sex-matched cohorts of 12 children with AE (11.2+/-3.5y, IQR 9y; 5M:7F) and 12 typically developing controls (10.6+/-3.2y, IQR 7y; 8M:4F) participated in this study. On average, children with autoimmune encephalitis did not differ from controls in working memory (t(21)= 1.449; p = .162; d = 0.605) but had a significantly lower processing speed (t(21) = 2.463; p = .023; Cohens d = 1.028). The groups did not differ in theta network topology measures but the autoimmune encephalitis group had a significantly lower delta local efficiency across all thresholds tested (d = -1.60 at network threshold 14%). Theta modularity was associated with lower working memory (β = -.781; t(8) = -2.588, p = .032) but this effect did not survive correction for multiple comparisons (p(corr) = .224). No other graph measure was significantly associated with psychometric scores in the autoimmune encephalitis group. MEG was able to capture network alterations in paediatric autoimmune encephalitis patients, specifically in the topological organisation of delta brain activity. This preliminary study demonstrates that MEG is an appropriate tool for assessing children with autoimmune encephalitis; future studies should focus on confirming which functional networks can predict cognitive performance.

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MEG Studies on the Connectivity of Brain Networks in Children

Cited by 4 publications

References 128 publications

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: A methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: A methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography

Linking brain networks to cognition with magnetoencephalography in paediatric autoimmune encephalitis

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