ReviewForce control in object manipulation—A model for the study of sensorimotor control strategies
Section snippets
Force control in object manipulation – a model for the study of sensorimotor control strategies
The control of prehensile finger forces – referred to as grip forces and lift forces – when grasping and lifting an object is a well-established model to study sensorimotor and cognitive control processes of the human sensorimotor system (Flanagan et al., 2006, Wolpert and Flanagan, 2001). The simple task of grasping and lifting objects in the environment is orchestrated by a complex interplay between multiple sensorimotor systems to signal, analyze and process the mechanical interactions and
Predictive force control and trial-by-trial adaptation in the grip-lift task
Object manipulation tasks involve different phases of motor action in which objects are grasped, lifted/transported, make contact with other objects and are released. For the simple task of grasping and lifting an object, contact making between the fingertips and object surface, initiation of the lifting movement and termination of the lifting movement are all discrete and distinct sensory events. Each of these sensory events provides specific afferent (feedback) information related to the
Memories for predictive force scaling
In the early 1990s Gordon and co-workers demonstrated that adults store information related to object weight when grasping and lifting objects with one hand, and are able to use this information to scale both grip and lift forces during subsequent lifts with the opposite hand (Gordon et al., 1994). This effect is independent of hand sequence, e.g. weight-related information was equally transferred from the left to the right hemisphere and vice versa. Despite the fact that there was some loss of
Internal models
Prediction is an essential characteristic of the human motor system because of the time delays inherent in the sensorimotor system of the human body. The delay mainly results from conduction of the afferent signal, signal processing in the nervous system and transmission of the output to the muscles. In case of spinal mono-synaptic reflexes of arm muscles the delay is 20 ms (biceps brachii) (Hammond, 1954). If cortical or subcortical structures are involved the delay lengthens with longer
What is memorized: physical object properties or central sense of effort?
According to the internal model theory the human sensorimotor system establishes and maintains internal representations, e.g. internal models, of the dynamics of the own body and environmental objects. As detailed above grasping and lifting an environmental object in a precision grip necessitates sufficient scaling and timing of grip force according to the lift force exerted by the object to prevent slip (see Fig. 2). A memory of appropriate force scaling related to the mechanical object
The internal model theory revisited
There is recent evidence that the predictive programming in the grip-lift task operates independently for grip and lift force (Cole et al., 2008, Chang et al., 2008, Parikh and Cole, 2011, Quaney et al., 2003, Nowak et al., 2004a, Nowak et al., 2004b, Rabe et al., 2009). The object-specific force scaling based on central representations of both object and body dynamics (internal models) is obvious when grasping and lifting known objects (Gordon et al., 1993). Object identification due to visual
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Cited by (44)
Measuring complexity of muscle force control: Theoretical principles and clinical relevance in musculoskeletal research and practice
2023, Musculoskeletal Science and PracticeAge- and task-dependent effects of cerebellar tDCS on manual dexterity and motor learning–A preliminary study
2022, Neurophysiologie CliniqueCitation Excerpt :The cerebellum has been shown to be involved in finger force control tasks [32] as well as in finger (effector) selection [7]. Regarding force control, the cerebellum is directly involved in control of timing and real-time error-based signal processing and adaptation [24] as well as in prediction of force [32]. The role of the cerebellum in effector selection is less clear-cut: evidence for a direct role is lacking in human fMRI studies [15,22,23], in line with recordings in non-human primates [30].
Never too little: Grip and lift forces following probabilistic weight cues in patients with writer's cramp
2021, Clinical NeurophysiologyCitation Excerpt :When we grasp and lift familiar objects, we prepare the grip and lifting (load) forces according to the expected load (Nowak et al., 2013).
A review of the neurobiomechanical processes underlying secure gripping in object manipulation
2021, Neuroscience and Biobehavioral ReviewsCitation Excerpt :In this regard, we aim to provide an overarching account of the biophysical, biomechanical, and biological sensory-related aspects of precision gripping during manipulation. To date, research has tended to focus on a specific movement parameter or biological characteristic in grasping behaviour; for example, to examine the role of skin wetness on manual function (Filingeri and Ackerley, 2017), force control (Nowak et al., 2013), the molecular basis of touch (Moehring et al., 2018), frictional properties at the finger-object interface (Derler and Gerhardt, 2012; Tomlinson et al., 2007), functional properties of cutaneous mechanoreceptors in touch (Roudaut et al., 2012), coding of sensory-tactile afferents/signals (Johansson and Flanagan, 2009), or tactile sensing technology (Chen et al., 2018; Kappassov et al., 2015; Tiwana et al., 2012). Therefore, we will integrate current research findings from across disciplines relating to general movement parameters (e.g., hand position, velocity), finger characteristics (e.g., size/orientation, fingerprint ridges), skin characteristics (e.g., elasticity, moisture/absorption, stretch), mechanosensation (e.g., receptor/afferent signals) and parameters at the finger-object interface (e.g., adjustment of force, presence of friction, tension, deformation) to comprehensively examine the role of biophysical/mechanical, sensory mechanisms underlying secure gripping during object manipulation.
Bidirectional brain-computer interfaces
2020, Handbook of Clinical NeurologyParkinsonian patients do not utilize probabilistic advance information in a grip-lift task
2019, Parkinsonism and Related Disorders