Periodic Reporting for period 1 - POSTURENET (Postural networks: linking cognitive and motor control across the lifespan)
Período documentado: 2020-09-01 hasta 2022-08-31
This aim of the project was to investigate the role of neural synchronization in postural control and to investigate how the neural coordination involved in postural control changes across the lifespan. To this end, a new network approach was developed to investigate human postural control and how neural coordination breaks down with ageing.
The ageing population in Europe will have a major impact on economy and well-being, resulting in an increase in motor impairments and movement-related disorders. It is estimated that every year within the EU 3.8 million older people attend emergency departments with a fall-related injury and 35,000 die as a consequence of falls. Although many factors influencing fall risk have been identified, e.g. muscle loss and impaired sensation, little remains known about changes in neural coordination of posture across the lifespan.
In this project, muscle network analysis is proposed as a novel approach to assess postural control across the lifespan. The aims of the project are to:
• Investigate the mechanisms underlying postural networks and determine the role of cortical sensorimotor cortices
• Investigate the functional role of postural networks and assess how executive control modulates the coordination between muscles
• Investigate how postural networks changes across the lifespan to gain new insights into the motor impairments observed with normal ageing
The overall objective of the project is to evaluate the age-related changes in postural control that can be revealed by this new network approach. The outcomes of this fellowship may provide new markers of physiological changes that predict fall risk and identify potential targets of interventions to reduce falls.
The ageing population in Europe will have a major impact on economy and well-being, resulting in an increase in motor impairments and movement-related disorders. It is estimated that every year within the EU 3.8 million older people attend emergency departments with a fall-related injury and 35,000 die as a consequence of falls. Although many factors influencing fall risk have been identified, e.g. muscle loss and impaired sensation, little remains known about changes in neural coordination of posture across the lifespan.
In this project, muscle network analysis is proposed as a novel approach to assess postural control across the lifespan. The aims of the project are to:
• Investigate the mechanisms underlying postural networks and determine the role of cortical sensorimotor cortices
• Investigate the functional role of postural networks and assess how executive control modulates the coordination between muscles
• Investigate how postural networks changes across the lifespan to gain new insights into the motor impairments observed with normal ageing
The overall objective of the project is to evaluate the age-related changes in postural control that can be revealed by this new network approach. The outcomes of this fellowship may provide new markers of physiological changes that predict fall risk and identify potential targets of interventions to reduce falls.
We developed a new research environment for mobile brain-body imaging at Maastricht University by integrate equipment for acquiring mobile electrophysiological data (EEG and EMG) with equipment for movement kinematics (Vicon 3D motion system). This research facility was used to acquire all data for this project and was also used by other researchers for related projects on postural control. For the current project this facility was used to investigate postural control across this lifespan and it will also be used to investigate movement disorders such as Parkinson’s Disease in follow-up studies that are being planned.
A multimodal data set was acquired combining 64-channel mobile EEG, 32-channel EMG from the major muscle groups involved in postural control and 3D kinematics. Data was acquired during different postural tasks (quiet standing, sit-to-stand, a choice stepping task) from 24 younger (20-26 years) healthy participants and 25 older (65-81 years) healthy participants. De-identified data will be shared on a public data repository (Zenodo).
Kinematic analysis of the choice stepping task confirmed the hypotheses on a behavioural level: reaction time is slower in older participants and slower if the likelihood of a go-cue is lower, and this difference is larger for older participants. The first analyses of intermuscular coherence during high and low conscious movement processing have been published and we currently preparing a manuscript reporting muscle network analysis of the sit-to-stand experiment. A manuscript reporting the differences in brain-muscle networks in older participants is planned for early 2023.
A postdoctoral researcher, a visiting PhD student and several Master students were trained in acquiring and analysing postural brain-muscle networks. They were also involved in the acquisition of research data for this project. The analysis pipeline for estimating brain-muscle networks from mobile EEG and EMG data will be shared on a public repository.
A multimodal data set was acquired combining 64-channel mobile EEG, 32-channel EMG from the major muscle groups involved in postural control and 3D kinematics. Data was acquired during different postural tasks (quiet standing, sit-to-stand, a choice stepping task) from 24 younger (20-26 years) healthy participants and 25 older (65-81 years) healthy participants. De-identified data will be shared on a public data repository (Zenodo).
Kinematic analysis of the choice stepping task confirmed the hypotheses on a behavioural level: reaction time is slower in older participants and slower if the likelihood of a go-cue is lower, and this difference is larger for older participants. The first analyses of intermuscular coherence during high and low conscious movement processing have been published and we currently preparing a manuscript reporting muscle network analysis of the sit-to-stand experiment. A manuscript reporting the differences in brain-muscle networks in older participants is planned for early 2023.
A postdoctoral researcher, a visiting PhD student and several Master students were trained in acquiring and analysing postural brain-muscle networks. They were also involved in the acquisition of research data for this project. The analysis pipeline for estimating brain-muscle networks from mobile EEG and EMG data will be shared on a public repository.
The project has generated a unique dataset acquiring state-of-the-art mobile brain-body imaging data during new experimental protocols to assess the cortical control of posture in healthy younger and older participants. The behavioural data has shown that the choice stepping task that was developed was successful in revealing age-related changes in cognitive control of posture. The first analyses of intermuscular coherence confirmed the quality of the electrophysiology data that was acquired and the ability to reliability estimate brain-muscle networks from this dataset. We are therefore confident that further analyses that are currently being conducted will reveal how postural networks changes across the lifespan and gain new insights into the motor impairments observed with normal ageing.
This would demonstrate the feasibility of brain-muscle network analysis to gain new insights into the cognitive control of posture. The expertise and research facilities developed in this project can be used to address questions from clinical practice. For example, we are currently planning follow-up studies to assess the effects of neuromodulation interventions for Parkinson’s Disease (i.e. deep-brain stimulation and spinal cord stimulation) on the neural control of gait. As such, the project was a major step in bringing the muscle network paradigm to full fruition and establish it as a principled approach to investigate the neural basis of motor coordination in health and disease
This would demonstrate the feasibility of brain-muscle network analysis to gain new insights into the cognitive control of posture. The expertise and research facilities developed in this project can be used to address questions from clinical practice. For example, we are currently planning follow-up studies to assess the effects of neuromodulation interventions for Parkinson’s Disease (i.e. deep-brain stimulation and spinal cord stimulation) on the neural control of gait. As such, the project was a major step in bringing the muscle network paradigm to full fruition and establish it as a principled approach to investigate the neural basis of motor coordination in health and disease