Children with cerebral palsy have uncharacteristic somatosensory cortical oscillations after stimulation of the hand mechanoreceptors

Kurz, Max J.; Becker, Katherine M.; Heinrichs‐Graham, Elizabeth; Wilson, Tony W.

doi:10.1016/j.neuroscience.2015.07.072

Cited by 37 publications

(38 citation statements)

References 47 publications

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“…130 A related study of particular interest showed that theta-alpha synchronization in the somatosensory cortices was normal in children with CP following tactile stimulation of the hand. 131 Since the children in this study did not have upper extremity impairments, these findings may suggest that theta-alpha synchronization is selectively disturbed in CP and is only abnormal in neural regions that serve severely impaired limbs.…”

Section: Cerebral Palsy (Cp)mentioning

confidence: 71%

Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology

Wilson

Heinrichs‐Graham

Proskovec

et al. 2016

Translational Research

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Magnetoencephalography (MEG) is a noninvasive, silent, and totally-passive neurophysiological imaging method with excellent temporal resolution (∼1 ms) and good spatial precision (∼3-5 mm). In a typical experiment, MEG data are acquired while healthy controls and/or patients with neurologic or psychiatric disorders perform a specific cognitive task and/or receive sensory stimulation. The resulting data are generally analyzed using standard electrophysiological methods, coupled with advanced image reconstruction algorithms. To date, the total number of MEG instruments and associated users is significantly smaller than comparable human neuroimaging techniques, although this is likely to change in the near future with advances in the technology. Despite this small base, MEG research has made a significant impact on several areas of translational neuroscience, largely through its unique capacity to quantify the oscillatory dynamics of activated brain circuits in humans. This review focuses on the clinical areas where MEG imaging has arguably had the greatest impact, in regard to the identification of aberrant neural dynamics at the regional and/or network-level, monitoring of disease progression, determining how efficacious pharmacological and behavioral interventions modulate neural systems, and the development of neural markers of disease. Specifically, this review covers recent advances in understanding the abnormal neural oscillatory dynamics that underlie Parkinson's disease, autism spectrum disorders, HIV-associated neurocognitive disorders, cerebral palsy, attention-deficit/hyperactivity disorder, cognitive aging, and posttraumatic stress disorder. MEG imaging has had a major impact on how clinical neuroscientists understand the brain basis of these disorders, and its translational influence is rapidly expanding with new discoveries and applications emerging continuously.

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Section: Cerebral Palsy (Cp)mentioning

confidence: 71%

Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology

Wilson

Heinrichs‐Graham

Proskovec

et al. 2016

Translational Research

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“…Using time-frequency analysis, we tested whether the reactivity of the ongoing S1 activity in children with HCP differs between the LA and MA hemisphere or in comparison with TD children. Very few studies have examined the sensorimotor oscillatory responses to tactile or electrical stimuli of the upper limbs in children with CP ( Guo et al, 2012 , Pihko et al, 2014 , Kurz et al, 2015a , Kurz et al, 2015b ). Except Guo et al (2012) , prior studies have focused their attention on lower frequency bands (i.e., alpha and beta), which are traditionally considered to be closely tied to the activation of sensory ( van Ede et al, 2011 ) and/or motor cortex ( Perry et al, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

“…These studies performed statistics either in the frequency or the time-frequency domain for predefined bands of interest (i.e. from 70 to 200 Hz for gamma in Guo et al, 2012 ; 6–14 Hz for alpha and 12–27 Hz for beta in Pihko et al, 2014 ; and 4–14 Hz for theta-alpha and 18–34 Hz for beta in Kurz et al, 2015a , Kurz et al, 2015b ). Here, we performed statistics in the entire spectrum from 1 to 100 Hz without a priori assumptions.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, the magnitude of the somatosensory cortical activity was found to be related to the mobility and strength impairments seen in children with CP ( Kurz et al, 2015b ). Few previous MEG studies also reported changes in the oscillatory activity of CP in response to the application of peripheral somatosensations ( Guo et al, 2012 , Pihko et al, 2014 , Kurz et al, 2014 , Kurz et al, 2015a , Kurz et al, 2015b ; Becker, et al 2015). Except Guo et al (2012) and Kurz et al (2017), these studies focused their attention on lower frequency bands (i.e., alpha and beta), which are traditionally considered to be closely tied to the activation of the sensory cortex ( van Ede et al, 2011 ).…”

Section: Introductionmentioning

confidence: 94%

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Reorganization of the somatosensory cortex in hemiplegic cerebral palsy associated with impaired sensory tracts

Papadelis

Butler

Rubenstein

et al. 2018

NeuroImage: Clinical

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Functional neuroimaging studies argue that sensory deficits in hemiplegic cerebral palsy (HCP) are related to deviant somatosensory processing in the ipsilesional primary somatosensory cortex (S1). A separate body of structural neuroimaging literature argues that these deficits are due to structural damage of the ascending sensory tracts (AST). The relationship between the functional and structural integrity of the somatosensory system and the sensory performance is largely unknown in HCP. To address this relationship, we combined findings from magnetoencephalography (MEG) and probabilistic diffusion tractography (PDT) in 10 children with HCP and 13 typically developing (TD) children. With MEG, we mapped the functionally active regions in the contralateral S1 during tactile stimulation of the thumb, middle, and little fingers of both hands. Using these MEG-defined functional active regions as regions of interest for PDT, we estimated the diffusion parameters of the AST. Somatosensory function was assessed via two-point discrimination tests. Our MEG data showed: (i) an abnormal somatotopic organization in all children with HCP in either one or both of their hemispheres; (ii) longer Euclidean distances between the digit maps in the S1 of children with HCP compared to TD children; (iii) suppressed gamma responses at early latencies for both hemispheres of children with HCP; and (iv) a positive correlation between the Euclidean distances and the sensory tests for the more affected hemisphere of children with HCP. Our MEG-guided PDT data showed: (i) higher mean and radian diffusivity of the AST in children with HCP; (ii) a positive correlation between the axial diffusivity of the AST with the sensory tests for the more affected hemisphere; and (iii) a negative correlation between the gamma power change and the AD of the AST for the MA hemisphere. Our findings associate for the first time bilateral cortical functional reorganization in the S1 of HCP children with abnormalities in the structural integrity of the AST, and correlate these abnormalities with behaviorally-assessed sensory deficits.

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“…We suspect that this developmental change will be partially linked with the maturation of the fiber tracts that serve the cortical areas identified in this investigation. Understanding this potential link is critical for advancing translational studies of the sensorimotor system in patients with developmental disabilities (e.g., Kurz et al 2014b, 2015a, b; Wilson et al 2016), and should be considered high priority for clinical studies of motor control.…”

Section: Discussionmentioning

confidence: 99%

Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task

et al. 2016

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There is currently a void in the scientific literature on the cortical beta oscillatory activity that is associated with the production of leg motor actions. In addition, we have limited data on how these cortical oscillations may progressively change as a function of development. This study began to fill this vast knowledge gap by using high-density magnetoencephalography to quantify the beta cortical oscillatory activity over a cross-section of typically developing children as they performed an isometric knee target matching task. Advanced beamforming methods were used to identify the spatiotemporal changes in beta oscillatory activity during the motor planning and motor action time frames. Our results showed that a widespread beta event-related desynchronization (ERD) was present across the pre/postcentral gyri, supplementary motor area, and the parietal cortices during the motor planning stage. The strength of this beta ERD sharply diminished across this fronto-parietal network as the children initiated the isometric force needed to match the target. Rank order correlations indicated that the older children were more likely to initiate their force production sooner, took less time to match the targets, and tended to have a weaker beta ERD during the motor planning stage. Lastly, we determined that there was a relationship between the child’s age and the strength of the beta ERD within the parietal cortices during isometric force production. Altogether our results suggest that there are notable maturational changes during childhood and adolescence in beta cortical oscillatory activity that are associated with the planning and execution of leg motor actions.

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Children with cerebral palsy have uncharacteristic somatosensory cortical oscillations after stimulation of the hand mechanoreceptors

Cited by 37 publications

References 47 publications

Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology

Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology

Reorganization of the somatosensory cortex in hemiplegic cerebral palsy associated with impaired sensory tracts

Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task

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