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Physiological Reviews Apr 2017Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish... (Review)
Review
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are ) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and ) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.
Topics: Brain; Brain-Computer Interfaces; Feedback, Sensory; Humans; Movement; Neurological Rehabilitation
PubMed: 28275048
DOI: 10.1152/physrev.00027.2016 -
Neuron Oct 2022A defining feature of early infancy is the immense neural plasticity that enables animals to develop a brain that is functionally integrated with a growing body. Early... (Review)
Review
A defining feature of early infancy is the immense neural plasticity that enables animals to develop a brain that is functionally integrated with a growing body. Early infancy is also defined as a period dominated by sleep. Here, we describe three conceptual frameworks that vary in terms of whether and how they incorporate sleep as a factor in the activity-dependent development of sensory and sensorimotor systems. The most widely accepted framework is exemplified by the visual system where retinal waves seemingly occur independent of sleep-wake states. An alternative framework is exemplified by the sensorimotor system where sensory feedback from sleep-specific movements activates the brain. We prefer a third framework that encompasses the first two but also captures the diverse ways in which sleep modulates activity-dependent development throughout the nervous system. Appreciation of the third framework will spur progress toward a more comprehensive and cohesive understanding of both typical and atypical neurodevelopment.
Topics: Animals; Sleep; Brain; Feedback, Sensory
PubMed: 36084653
DOI: 10.1016/j.neuron.2022.08.005 -
The European Journal of Neuroscience Nov 2022The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of... (Review)
Review
The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of the nervous sensory pathway can be adopted to restore the artificial sense of touch and proprioception in people suffering from sensory-motor disorders. The modulation of the neural stimulation parameters has a direct effect on the electrically induced sensations, both when targeting the somatosensory cortex and the peripheral somatic nerves. The properties of the artificial sensations perceived, as their location, quality and intensity are strongly dependent on the direct modulation of pulse width, amplitude and frequency of the neural stimulation. Different sensory encoding schemes have been tested in patients showing distinct effects and outcomes according to their impact on the neural activation. Here, I reported the most adopted neural stimulation strategies to artificially encode somatosensation into the peripheral nervous system. The real-time implementation of these strategies in bionic devices is crucial to exploit the artificial sensory feedback in prosthetics. Thus, neural stimulation becomes a tool to directly communicate with the human nervous system. Given the importance of adding artificial sensory information to neuroprosthetic devices to improve their control and functionality, the choice of an optimal neural stimulation paradigm could increase the impact of prosthetic devices on the quality of life of people with sensorimotor disabilities.
Topics: Humans; Quality of Life; Touch Perception; Touch; Artificial Limbs; Feedback, Sensory; Electric Stimulation
PubMed: 36097134
DOI: 10.1111/ejn.15822 -
Proceedings of the National Academy of... Jul 2022Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to...
Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.
Topics: Adaptation, Physiological; Feedback, Sensory; Humans; Learning; Movement; Psychomotor Performance
PubMed: 35858450
DOI: 10.1073/pnas.2204379119 -
Journal of Vision Aug 2019Prediction allows humans and other animals to prepare for future interactions with their environment. This is important in our dynamically changing world that requires... (Review)
Review
Prediction allows humans and other animals to prepare for future interactions with their environment. This is important in our dynamically changing world that requires fast and accurate reactions to external events. Knowing when and where an event is likely to occur allows us to plan eye, hand, and body movements that are suitable for the circumstances. Predicting the sensory consequences of such movements helps to differentiate between self-produced and externally generated movements. In this review, we provide a selective overview of experimental studies on predictive mechanisms in human vision for action. We present classic paradigms and novel approaches investigating mechanisms that underlie the prediction of events guiding eye and hand movements.
Topics: Feedback, Sensory; Goals; Humans; Movement; Psychomotor Performance; Vision, Ocular
PubMed: 31434106
DOI: 10.1167/19.9.10 -
Neuron Sep 2018Heindorf et al. (2018) report that motor cortex plays a key role in behavioral tasks that rely on continuous sensory feedback. They propose a layer-based circuit that...
Heindorf et al. (2018) report that motor cortex plays a key role in behavioral tasks that rely on continuous sensory feedback. They propose a layer-based circuit that might be of particular importance when coping with unexpected perturbations in dynamic environments.
Topics: Animals; Feedback, Sensory; Mice; Motor Cortex
PubMed: 30189206
DOI: 10.1016/j.neuron.2018.08.024 -
Experimental Brain Research Aug 2023Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities...
Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities of daily living and involves integrating sensory signals. During this sensory integration, the central nervous system deals with the uncertainty of sensory signals. When handling compliant objects, force and position are related. Interactions with stiff objects result in reduced position changes and increased force changes compared to compliant objects. Literature has shown sensory integration of force and position at the shoulder. Nevertheless, differences in sensory requirements between proximal and distal joints may lead to different proprioceptive representations, hence findings at proximal joints cannot be directly transferred to distal joints, such as the digits. Here, we investigate the sensory integration of force and position during pinching. A haptic manipulator rendered a virtual spring with adjustable stiffness between the index finger and the thumb. Participants had to blindly reproduce a force against the spring. In both visual reference trials and blind reproduction trials, the relation between pinch force and spring compression was constant. However, by covertly changing the spring characteristics in catch trials into an adjusted force-position relation, the participants' weighting of force and position could be revealed. In agreement with previous studies on the shoulder, participants relied more on force sense in trials with higher stiffness. This study demonstrated stiffness-dependent sensory integration of force and position feedback during pinching.
Topics: Humans; Feedback; Activities of Daily Living; Fingers; Proprioception; Feedback, Sensory
PubMed: 37382669
DOI: 10.1007/s00221-023-06654-1 -
Journal of Speech, Language, and... Aug 2019Purpose While the speech motor system is sensitive to feedback perturbations, sensory feedback does not seem to be critical to speech motor production. How the speech... (Review)
Review
Purpose While the speech motor system is sensitive to feedback perturbations, sensory feedback does not seem to be critical to speech motor production. How the speech motor system is able to be so flexible in its use of sensory feedback remains an open question. Method We draw on evidence from a variety of disciplines to summarize current understanding of the sensory systems' role in speech motor control, including both online control and motor learning. We focus particularly on computational models of speech motor control that incorporate sensory feedback, as these models provide clear encapsulations of different theories of sensory systems' function in speech production. These computational models include the well-established directions into velocities of articulators model and computational models that we have been developing in our labs based on the domain-general theory of state feedback control (feedback aware control of tasks in speech model). Results After establishing the architecture of the models, we show that both the directions into velocities of articulators and state feedback control/feedback aware control of tasks models can replicate key behaviors related to sensory feedback in the speech motor system. Although the models agree on many points, the underlying architecture of the 2 models differs in a few key ways, leading to different predictions in certain areas. We cover key disagreements between the models to show the limits of our current understanding and point toward areas where future experimental studies can resolve these questions. Conclusions Understanding the role of sensory information in the speech motor system is critical to understanding speech motor production and sensorimotor learning in healthy speakers as well as in disordered populations. Computational models, with their concrete implementations and testable predictions, are an important tool to understand this process. Comparison of different models can highlight areas of agreement and disagreement in the field and point toward future experiments to resolve important outstanding questions about the speech motor control system.
Topics: Feedback, Sensory; Humans; Learning; Models, Theoretical; Speech
PubMed: 31465712
DOI: 10.1044/2019_JSLHR-S-CSMC7-18-0127 -
ELife Dec 2021Investigating how an artificial network of neurons controls a simulated arm suggests that rotational patterns of activity in the motor cortex may rely on sensory...
Investigating how an artificial network of neurons controls a simulated arm suggests that rotational patterns of activity in the motor cortex may rely on sensory feedback from the moving limb.
Topics: Feedback, Sensory; Motor Cortex; Neurons
PubMed: 34932466
DOI: 10.7554/eLife.75469 -
Physiological Reviews Apr 2022Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the... (Review)
Review
Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.
Topics: Animals; Bionics; Brain; Brain-Computer Interfaces; Feedback, Sensory; Hand; Humans; Movement; Touch Perception
PubMed: 34541898
DOI: 10.1152/physrev.00034.2020