Stretch Evoked Potentials in Healthy Subjects and After Stroke: A Potential Measure for Proprioceptive Sensorimotor Function

Campfens, S.F.; Meskers, Carel G.M.; Schouten, Alfred C.; Putten, Michel Johannes Antonius Maria van; Kooij, Herman van der

doi:10.1109/tnsre.2015.2388692

Cited by 14 publications

(17 citation statements)

References 38 publications

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“…Examples of an even nonlinear function are y(u)=u 2 , y(u)=u 4 and y(u)=abs(u). Seiss et al [32] and Campfens, et al [33] showed that a stretch of respectively the finger and wrist resulted in a similar ERP for both flexion and extension direction, which also indicates an even nonlinear relation.…”

Section: A Quantification Of the Nonlinear Contributionsmentioning

confidence: 95%

Quantifying Nonlinear Contributions to Cortical Responses Evoked by Continuous Wrist Manipulation

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Solis‐Escalante

Vardy

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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Abstract-Cortical responses to continuous stimuli as recorded using either magneto-or electroencephalography (EEG) have shown power at harmonics of the stimulated frequency, indicating nonlinear behavior. Even though the selection of analysis techniques depends on the linearity of the system under study, the importance of nonlinear contributions to cortical responses has not been formally addressed. The goal of this paper is to quantify the nonlinear contributions to the cortical response obtained from continuous sensory stimulation. EEG was used to record the cortical response evoked by continuous movement of the wrist joint of healthy subjects applied with a robotic manipulator. Multisine stimulus signals (i.e. the sum of several sinusoids) elicit a periodic cortical response and allow to assess the nonlinear contributions to the response. Wrist dynamics (relation between joint angle and torque) were successfully linearized, explaining 99% of the response. In contrast, the cortical response revealed a highly nonlinear relation; where most power (~80%) occurred at nonstimulated frequencies. Moreover, only 10% of the response could be explained using a nonparametric linear model. These results indicate that the recorded evoked cortical responses are governed by nonlinearities and that linear methods do not suffice when describing the relation between mechanical stimulus and cortical response.

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Section: A Quantification Of the Nonlinear Contributionsmentioning

confidence: 95%

Quantifying Nonlinear Contributions to Cortical Responses Evoked by Continuous Wrist Manipulation

Vlaar

Solis‐Escalante

Vardy

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…In the central nervous system, cortical responses to muscle stretch have been investigated by previous studies using the event-related potential (ERP) (Abbruzzese et al, 1985 ; Campfens et al, 2015 ). The latencies and topographies of the stretch-evoked ERP reflect the time courses of cortical activity and most active areas in response to the muscle stretch.…”

Section: Introductionmentioning

confidence: 99%

“…The latencies and topographies of the stretch-evoked ERP reflect the time courses of cortical activity and most active areas in response to the muscle stretch. Both early (<100 ms post-perturbation onset) and late (>100 ms) ERP components were reported around the contralateral motor cortex (Campfens et al, 2015 ). Considering the efferent motor conduction delay (~20 ms), the early cortical response is thought to related to the rapid transcortical muscle reaction to the perturbation (<~120 ms) while the late cortical response may be related to the slow transcortical muscle reaction (>~120 ms) (MacKinnon et al, 2000 ; Pruszynski and Scott, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Causal Modeling of the Cortical Responses to Wrist Perturbations

2017

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Mechanical perturbations applied to the wrist joint typically evoke a stereotypical sequence of cortical and muscle responses. The early cortical responses (<100 ms) are thought be involved in the “rapid” transcortical reaction to the perturbation while the late cortical responses (>100 ms) are related to the “slow” transcortical reaction. Although previous studies indicated that both responses involve the primary motor cortex, it remains unclear if both responses are engaged by the same effective connectivity in the cortical network. To answer this question, we investigated the effective connectivity cortical network after a “ramp-and-hold” mechanical perturbation, in both the early (<100 ms) and late (>100 ms) periods, using dynamic causal modeling. Ramp-and-hold perturbations were applied to the wrist joint while the subject maintained an isometric wrist flexion. Cortical activity was recorded using a 128-channel electroencephalogram (EEG). We investigated how the perturbation modulated the effective connectivity for the early and late periods. Bayesian model comparisons suggested that different effective connectivity networks are engaged in these two periods. For the early period, we found that only a few cortico-cortical connections were modulated, while more complicated connectivity was identified in the cortical network during the late period with multiple modulated cortico-cortical connections. The limited early cortical network likely allows for a rapid muscle response without involving high-level cognitive processes, while the complexity of the late network may facilitate coordinated responses.

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“…Combining peripheral perturbations with neurophysiological measurements like Electro Encephalography (EEG) yields properties of the sensor-controller-motor loop in more detail. Assessing cortical responses to fast muscle stretches yields stretch Evoked Potentials (strEP) that may serve as a measure of cortical sensorimotor activation in response to proprioceptive input (Campfens et al, 2015a ). Afferent sensory pathway information transfer and processing can be assessed by calculation of the coherence between cortical activity and a peripheral position perturbation (position-cortical coherence, PCC; Campfens et al, 2015b ).…”

Section: Control and Plant Interactionmentioning

confidence: 99%

“…Afferent sensory pathway information transfer and processing can be assessed by calculation of the coherence between cortical activity and a peripheral position perturbation (position-cortical coherence, PCC; Campfens et al, 2015b ). Aforementioned measures are disturbed in stroke patients and may be used to detect integrity of afferent and efferent pathways separately and propagation of signals over the cortex (Campfens et al, 2015a , b ). High density EEG may further reveal cortical involvement and its location in motor tasks (Yao and Dewald, 2005a ; Yao et al, 2005b ).…”

Section: Control and Plant Interactionmentioning

confidence: 99%

NeuroControl of movement: system identification approach for clinical benefit

Meskers

Groot

Vlugt

et al. 2015

Front. Integr. Neurosci.

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Progress in diagnosis and treatment of movement disorders after neurological diseases like stroke, cerebral palsy (CP), dystonia and at old age requires understanding of the altered capacity to adequately respond to physical obstacles in the environment. With posture and movement disorders, the control of muscles is hampered, resulting in aberrant force generation and improper impedance regulation. Understanding of this improper regulation not only requires the understanding of the role of the neural controller, but also attention for: (1) the interaction between the neural controller and the “plant”, comprising the biomechanical properties of the musculaskeletal system including the viscoelastic properties of the contractile (muscle) and non-contractile (connective) tissues: neuromechanics; and (2) the closed loop nature of neural controller and biomechanical system in which cause and effect interact and are hence difficult to separate. Properties of the neural controller and the biomechanical system need to be addressed synchronously by the combination of haptic robotics, (closed loop) system identification (SI), and neuro-mechanical modeling. In this paper, we argue that assessment of neuromechanics in response to well defined environmental conditions and tasks may provide for key parameters to understand posture and movement disorders in neurological diseases and for biomarkers to increase accuracy of prediction models for functional outcome and effects of intervention.

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Stretch Evoked Potentials in Healthy Subjects and After Stroke: A Potential Measure for Proprioceptive Sensorimotor Function

Cited by 14 publications

References 38 publications

Quantifying Nonlinear Contributions to Cortical Responses Evoked by Continuous Wrist Manipulation

Quantifying Nonlinear Contributions to Cortical Responses Evoked by Continuous Wrist Manipulation

Dynamic Causal Modeling of the Cortical Responses to Wrist Perturbations

NeuroControl of movement: system identification approach for clinical benefit

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