Nadia Dominici | Vrije Universiteit Amsterdam (original) (raw)
Papers by Nadia Dominici
The Journal of Experimental Biology, Oct 1, 2004
Journal of Neurophysiology, Apr 1, 2007
Journal of Neurophysiology, Mar 1, 2009
Gait & Posture, Jun 1, 2005
Applied sciences, Mar 14, 2020
Developmental Medicine & Child Neurology, Oct 6, 2021
Journal of Neurophysiology, Jul 1, 2005
The Journal of Neuroscience, Oct 10, 2007
Gait & Posture, Jun 1, 2005
European Journal of Applied Physiology, Jan 13, 2021
Journal of Neural Engineering, Sep 2, 2015
OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been inter... more OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. APPROACH Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. MAIN RESULTS We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. SIGNIFICANCE Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds, are likely to provide more robust control strategies for the design of such neuroprostheses.
Journal of Neurophysiology, Dec 1, 2010
Journal of Neurophysiology, Feb 1, 2010
Frontiers in Network Physiology, Mar 24, 2022
Muscle synergy assessments are often employed to evaluate the modular organization of the spinal ... more Muscle synergy assessments are often employed to evaluate the modular organization of the spinal cord during a locomotion task. While they provide valuable insights into the pattern formation of the a-motoneurons at the spinal cord, by construction they cannot capture control from supra-spinal layers. We examined how locomotor muscle synergies are represented in the sensorimotor cortex, with particular focus on the cortico-synergy coherence as a measure of coupling along the cortico-spinal tract. Non-negative matrix factorization served to decompose multivariate electromyographic signals into muscle synergies. Their representations were localized in the cortex using coherence-based beamforming. Overall, the cortico-synergy coherence was maximal in sensorimotor areas especially in the beta-frequency band. However, only for the synergies timed to heel strike, that are related to the double support phases, the coherence was significant. These coherences were closely related to the timing of the activation patterns of the synergies, suggesting sensorimotor cortex to be strongly involved in emergence and control of these synergies.
Progress in Brain Research, 2020
In this chapter, we explore the use of motion tracking methodology in developmental research. Wit... more In this chapter, we explore the use of motion tracking methodology in developmental research. With motion tracking, also called motion capture, human movements can be precisely recorded and analyzed. Motion tracking provides developmental researchers with objective measurements of motor and (socio-)cognitive development. It can further be used to create carefully-controlled stimuli videos and can offer means of measuring development outside of the lab. We discuss three types of motion tracking that lend themselves to developmental applications. First, marker-based systems track optical or electromagnetic markers or sensors placed on the body and offer high accuracy measurements. Second, markerless methods entail image processing of videos to track the movement of bodies without participants being hindered by physical markers. Third, inertial motion tracking measures three-dimensional movements and can be used in a variety of settings. The chapter concludes by examining three example topics from developmental literature in which motion tracking applications have contributed to our understanding of human development.
Frontiers in Physiology, Sep 27, 2019
The Journal of Experimental Biology, Oct 1, 2004
Journal of Neurophysiology, Apr 1, 2007
Journal of Neurophysiology, Mar 1, 2009
Gait & Posture, Jun 1, 2005
Applied sciences, Mar 14, 2020
Developmental Medicine & Child Neurology, Oct 6, 2021
Journal of Neurophysiology, Jul 1, 2005
The Journal of Neuroscience, Oct 10, 2007
Gait & Posture, Jun 1, 2005
European Journal of Applied Physiology, Jan 13, 2021
Journal of Neural Engineering, Sep 2, 2015
OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been inter... more OBJECTIVE Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. APPROACH Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. MAIN RESULTS We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. SIGNIFICANCE Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds, are likely to provide more robust control strategies for the design of such neuroprostheses.
Journal of Neurophysiology, Dec 1, 2010
Journal of Neurophysiology, Feb 1, 2010
Frontiers in Network Physiology, Mar 24, 2022
Muscle synergy assessments are often employed to evaluate the modular organization of the spinal ... more Muscle synergy assessments are often employed to evaluate the modular organization of the spinal cord during a locomotion task. While they provide valuable insights into the pattern formation of the a-motoneurons at the spinal cord, by construction they cannot capture control from supra-spinal layers. We examined how locomotor muscle synergies are represented in the sensorimotor cortex, with particular focus on the cortico-synergy coherence as a measure of coupling along the cortico-spinal tract. Non-negative matrix factorization served to decompose multivariate electromyographic signals into muscle synergies. Their representations were localized in the cortex using coherence-based beamforming. Overall, the cortico-synergy coherence was maximal in sensorimotor areas especially in the beta-frequency band. However, only for the synergies timed to heel strike, that are related to the double support phases, the coherence was significant. These coherences were closely related to the timing of the activation patterns of the synergies, suggesting sensorimotor cortex to be strongly involved in emergence and control of these synergies.
Progress in Brain Research, 2020
In this chapter, we explore the use of motion tracking methodology in developmental research. Wit... more In this chapter, we explore the use of motion tracking methodology in developmental research. With motion tracking, also called motion capture, human movements can be precisely recorded and analyzed. Motion tracking provides developmental researchers with objective measurements of motor and (socio-)cognitive development. It can further be used to create carefully-controlled stimuli videos and can offer means of measuring development outside of the lab. We discuss three types of motion tracking that lend themselves to developmental applications. First, marker-based systems track optical or electromagnetic markers or sensors placed on the body and offer high accuracy measurements. Second, markerless methods entail image processing of videos to track the movement of bodies without participants being hindered by physical markers. Third, inertial motion tracking measures three-dimensional movements and can be used in a variety of settings. The chapter concludes by examining three example topics from developmental literature in which motion tracking applications have contributed to our understanding of human development.
Frontiers in Physiology, Sep 27, 2019