An involuntary stereotypical grasp tendency pervades voluntary dynamic multifinger manipulation

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Distinct adaptation processes underlie multidigit force coordination for dexterous manipulation

The human sensorimotor system can adapt to various changes in the environmental dynamics by updating motor commands to improve performance after repeated exposure to the same task. However, the characteristics and mechanisms of the adaptation process remain unknown for dexterous manipulation, a unique motor task in which the body physically interacts with the environment with multiple effectors, i.e., digits, in parallel. We addressed this gap by using robotic manipulanda to investigate the changes in the digit force coordination following mechanical perturbation of an object held by tripod grasps. As the participants gradually adapted to lifting the object under perturbations, we quantified two components of digit force coordination. One is the direction-specific manipulation moment that directly counteracts the perturbation, whereas the other one is the direction-independent internal moment that supports the stability and stiffness of the grasp. We found that trial-to-trial improvement of task performance was associated with increased manipulation moment and a gradual decrease of the internal moment. These two moments were characterized by different rates of adaptation. We also examined how these two force coordination components respond to changes in perturbation directions. Importantly, we found that the manipulation moment was sensitive to the extent of repetitive exposure to the previous context that has an opposite perturbation direction, whereas the internal moment did not. However, the internal moment was sensitive to whether the postchange perturbation direction was previously experienced. Our results reveal, for the first time, that two distinct processes underlie the adaptation of multidigit force coordination for dexterous manipulation.NEW & NOTEWORTHY Changes in digit force coordination in multidigit object manipulation were quantified with a novel experimental design in which human participants adapted to mechanical perturbations applied to the object. Our results show that the adaptation of digit force coordination can be characterized by two distinct components that operate at different timescales. We further show that these two components respond to changes in perturbation direction differently.

Unexpected complexity of everyday manual behaviors

How does the brain control an effector as complex and versatile as the hand? One possibility is that neural control is simplified by limiting the space of hand movements. Indeed, hand kinematics can be largely described within 8 to 10 dimensions. This oft replicated finding has been construed as evidence that hand postures are confined to this subspace. A prediction from this hypothesis is that dimensions outside of this subspace reflect noise. To address this question, we track the hand of human participants as they perform two tasks-grasping and signing in American Sign Language. We apply multiple dimension reduction techniques and replicate the finding that most postural variance falls within a reduced subspace. However, we show that dimensions outside of this subspace are highly structured and task dependent, suggesting they too are under volitional control. We propose that hand control occupies a higher dimensional space than previously considered.

Parkinson's Disease Exhibits Amplified Intermuscular Coherence During Dynamic Voluntary Action

Parkinson's disease (PD) is typically diagnosed and evaluated on the basis of overt motor dysfunction, however, subtle changes in the frequency spectrum of neural drive to muscles have been reported as well. During dynamic actions, coactive muscles of healthy adults often share a common source of 6-15 Hz (alpha-band) neural drive, creating synchronous alpha-band activity in their EMG signals. Individuals with PD commonly exhibit kinetic action tremor at similar frequencies, but the potential relationship between the intermuscular alpha-band neural drive seen in healthy adults and the action tremor associated with PD is not well-understood. A close relationship is most tenable during voluntary dynamic tasks where alpha-band neural drive is strongest in healthy adults, and where neural circuits affected by PD are most engaged. In this study, we characterized the frequency spectrum of EMG synchronization (intermuscular coherence) in 16 participants with PD and 15 age-matched controls during two dynamic motor tasks: (1) rotation of a dial between the thumb and index finger, and (2) dynamic scaling of isometric precision pinch force. These tasks produce different profiles of coherence between the first dorsal interosseous and abductor pollicis brevis muscles. We sought to determine if alpha-band intermuscular coherence would be amplified in participants with PD relative to controls, if such differences would be task-specific, and if they would correlate with symptom severity. We found that relative to controls, the PD group displayed amplified, but similarly task-dependent, coherence in the alpha-band. The magnitude of coherence during the rotation task correlated with overall symptom severity as per the UPDRS rating scale. Finally, we explored the potential for our coherence measures, with no additional information, to discriminate individuals with PD from controls. The area under the Receiver Operating Characteristic curve (AUC) indicated a clear separation between groups (AUC = 0.96), even though participants with PD were on their typical medication and displayed only mild-moderate symptoms. We conclude that a task-dependent, intermuscular neural drive within the alpha-band is amplified in PD. Its quantification via intermuscular coherence analysis may provide a useful tool for detecting the presence of PD, or assessing its progression.

Synergies in coordination: a comprehensive overview of neural, computational, and behavioral approaches

At face value, the term "synergy" provides a unifying concept within a fractured field that encompasses complementary neural, computational, and behavioral approaches. However, the term is not used synonymously by different researchers but has substantially different meanings depending on the research approach. With so many operational definitions for the one term, it becomes difficult to use as either a descriptive or explanatory concept, yet it remains pervasive and apparently indispensable. Here we provide a summary of different approaches that invoke synergies in a descriptive or explanatory context, summarizing progress, not within the one approach, but across the theoretical landscape. Bernstein's framework of flexible hierarchical control may provide a unifying framework here, since it can incorporate divergent ideas about synergies. In the current motor control literature, synergy may refer to conceptually different processes that could potentially operate in parallel, across different levels within the same hierarchical control scheme. There is evidence for the concurrent existence of synergies with different features, both "hard-wired" and "soft-wired," and task independent and task dependent. By providing a comprehensive overview of the multifaceted ideas about synergies, our goal is to move away from the compartmentalization and narrow the focus on one level and promote a broader perspective on the control and coordination of movement.

Feasibility Theory Reconciles and Informs Alternative Approaches to Neuromuscular Control

We present Feasibility Theory, a conceptual and computational framework to unify today's theories of neuromuscular control. We begin by describing how the musculoskeletal anatomy of the limb, the need to control individual tendons, and the physics of a motor task uniquely specify the family of all valid muscle activations that accomplish it (its ‘feasible activation space’). For our example of producing static force with a finger driven by seven muscles, computational geometry characterizes—in a complete way—the structure of feasible activation spaces as 3-dimensional polytopes embedded in 7-D. The feasible activation space for a given task is the landscape where all neuromuscular learning, control, and performance must occur. This approach unifies current theories of neuromuscular control because the structure of feasible activation spaces can be separately approximated as either low-dimensional basis functions (synergies), high-dimensional joint probability distributions (Bayesian priors), or fitness landscapes (to optimize cost functions).

Intermuscular coherence reflects functional coordination

Coherence analysis has the ability to identify the presence of common descending drive shared by motor unit pools and reveals its spectral properties. However, the link between spectral properties of shared neural drive and functional interactions among muscles remains unclear. We assessed shared neural drive between muscles of the thumb and index finger while participants executed two mechanically distinct precision pinch tasks, each requiring distinct functional coordination among muscles. We found that shared neural drive was systematically reduced or enhanced at specific frequencies of interest (~10 and ~40 Hz). While amplitude correlations between surface EMG signals also exhibited changes across tasks, only their coherence has strong physiological underpinnings indicative of neural binding. Our results support the use of intermuscular coherence as a tool to detect when coactivated muscles are members of a functional group or synergy of neural origin. Furthermore, our results demonstrate the advantages of considering neural binding at 10, ~20, and >30 Hz, as indicators of task-dependent neural coordination strategies.NEW & NOTEWORTHY It is often unclear whether correlated activity among muscles reflects their neural binding or simply reflects the constraints defining the task. Using the fact that high-frequency coherence between EMG signals (>6 Hz) is thought to reflect shared neural drive, we demonstrate that coherence analysis can reveal the neural origin of distinct muscle coordination patterns required by different tasks.

Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures

We used a musculoskeletal model to investigate the possible biomechanical and neural bases of using consistent muscle synergy patterns to produce functional motor outputs across different biomechanical conditions, which we define as generalizability. Experimental studies in cats demonstrate that the same muscle synergies are used during reactive postural responses at widely varying configurations, producing similarly-oriented endpoint force vectors with respect to the limb axis. However, whether generalizability across postures arises due to similar biomechanical properties or to neural selection of a particular muscle activation pattern has not been explicitly tested. Here, we used a detailed cat hindlimb model to explore the set of feasible muscle activation patterns that produce experimental synergy force vectors at a target posture, and tested their generalizability by applying them to different test postures. We used three methods to select candidate muscle activation patterns: (1) randomly-selected feasible muscle activation patterns, (2) optimal muscle activation patterns minimizing muscle effort at a given posture, and (3) generalizable muscle activation patterns that explicitly minimized deviations from experimentally-identified synergy force vectors across all postures. Generalizability was measured by the deviation between the simulated force direction of the candidate muscle activation pattern and the experimental synergy force vectors at the test postures. Force angle deviations were the greatest for the randomly selected feasible muscle activation patterns (e.g., >100°), intermediate for effort-wise optimal muscle activation patterns (e.g., ~20°), and smallest for generalizable muscle activation patterns (e.g., <5°). Generalizable muscle activation patterns were suboptimal in terms of effort, often exceeding 50% of the maximum possible effort (cf. ~5% in minimum-effort muscle activation patterns). The feasible muscle activation ranges of individual muscles associated with producing a specific synergy force vector was reduced by ~45% when generalizability requirements were imposed. Muscles recruited in the generalizable muscle activation patterns had less sensitive torque-producing characteristics to changes in postures. We conclude that generalization of function across postures does not arise from limb biomechanics or a single optimality criterion. Muscle synergies may reflect acquired motor solutions globally tuned for generalizability across biomechanical contexts, facilitating rapid motor adaptation.

Feasible muscle activation ranges based on inverse dynamics analyses of human walking

Although it is possible to produce the same movement using an infinite number of different muscle activation patterns owing to musculoskeletal redundancy, the degree to which observed variations in muscle activity can deviate from optimal solutions computed from biomechanical models is not known. Here, we examined the range of biomechanically permitted activation levels in individual muscles during human walking using a detailed musculoskeletal model and experimentally-measured kinetics and kinematics. Feasible muscle activation ranges define the minimum and maximum possible level of each muscle's activation that satisfy inverse dynamics joint torques assuming that all other muscles can vary their activation as needed. During walking, 73% of the muscles had feasible muscle activation ranges that were greater than 95% of the total muscle activation range over more than 95% of the gait cycle, indicating that, individually, most muscles could be fully active or fully inactive while still satisfying inverse dynamics joint torques. Moreover, the shapes of the feasible muscle activation ranges did not resemble previously-reported muscle activation patterns nor optimal solutions, i.e. static optimization and computed muscle control, that are based on the same biomechanical constraints. Our results demonstrate that joint torque requirements from standard inverse dynamics calculations are insufficient to define the activation of individual muscles during walking in healthy individuals. Identifying feasible muscle activation ranges may be an effective way to evaluate the impact of additional biomechanical and/or neural constraints on possible versus actual muscle activity in both normal and impaired movements.

Independent digit contributions to rotational manipulation in a three-digit pouring task requiring dynamic stability

Many activities of daily living involve multi-digit, voluntary rotational manipulations of grasped objects. Yet, only a few studies have focused on coordination of individual fingertip forces during such tasks. The objective of this study was to investigate individual digit contributions to a three-digit task in which an object was rotationally manipulated against gravity. Center of mass was varied through the use of containers shaped like a water bottle, pint glass, and cocktail glass, from which subjects poured fluid carefully into a nearby receptacle. The center of mass of the grasped object changed continuously as fluid was poured out. Self-selected digit placement and contributions of fingertip forces to rotational manipulation were dependent upon anticipated center of mass location associated with container shape. The thumb resisted the rotation of the top-heavy, cocktail glass container until 79 % of the pouring phase had elapsed, but actively assisted the rotation of the less challenging containers. More directly opposing the thumb, the index finger contributed more to grasp stability. The middle finger contributed more to rotation of the container for pouring. It was found that the thumb, index, and middle fingers acted in unison temporally, but contributed independently to the grip forces and stabilizing moments throughout the dynamic, rotational manipulation task.

Motor primitives--new data and future questions

Motor primitives allow integration across scales in the motor system and may link movement construction and circuit organization. This review examines support for primitives, and new data relating primitives to concrete circuit elements across species. Both kinematic motor primitives and muscle synergy/kinetic motor primitives are reviewed. Motor primitives allow a modular hierarchy that may be re-used by volitional systems in novel ways. They can provide a developmental bootstrap for ethologically important actions. Collections of primitives somewhat constrain motor acts, but at the same time sets of primitives facilitate the rapid construction of these constrained actions, and can allow use of simpler controls. Novel motor skill likely requires augmentation to transcend the constraints present in initial collections of low level motor primitives. The benefits and limitations of motor primitives and the recognized knowledge gaps and needs for future research are briefly discussed.

Workspace Shape and Characteristics for Human Two- and Three-Fingered Precision Manipulation

GOAL

To study precision manipulation, which involves repositioning an object in the fingertips and is used in everyday tasks such as writing and key insertion, and also for domain-specific tasks such as small scalpel cuts, using tweezers, and hand soldering.

METHODS

In this study, the range of positions (workspace) through which 19 participants manipulated a 3.3-4.1 cm-diameter object are measured with a magnetic tracker. Each participant performed two conditions: a two-finger thumb-index finger condition and a three-finger thumb-index-middle finger condition.

RESULTS

The observed workspaces, normalized to a 17.5 cm hand length, are small compared to free-finger trajectories; for the two-finger trials, 68% of points are within 1.05 cm of the centroid and 95% are within 2.31 cm, while the three-finger case shows a narrower distribution, with 68% of points within 0.94 cm of the centroid and 95% of points within 2.19 cm. The longest axis is a long thin arc in the proximal-palmar plane. Analysis of fingertip workspaces shows that the index fingertip workspace volume is the most linear predictor of object workspace (R(2) = 0.98).

CONCLUSION

Precision manipulation workspace size and shape is shown, along with how the fingers are used during the manipulation.

SIGNIFICANCE

The results have many applications, including normative data for rehabilitation, guidelines for ergonomic device design, and benchmarking prosthetic and robotic hands.

Spinal primitives and intra-spinal micro-stimulation (ISMS) based prostheses: a neurobiological perspective on the "known unknowns" in ISMS and future prospects

The current literature on Intra-Spinal Micro-Stimulation (ISMS) for motor prostheses is reviewed in light of neurobiological data on spinal organization, and a neurobiological perspective on output motor modularity, ISMS maps, stimulation combination effects, and stability. By comparing published data in these areas, the review identifies several gaps in current knowledge that are crucial to the development of effective intraspinal neuroprostheses. Gaps can be categorized into a lack of systematic and reproducible details of: (a) Topography and threshold for ISMS across the segmental motor system, the topography of autonomic recruitment by ISMS, and the coupling relations between these two types of outputs in practice. (b) Compositional rules for ISMS motor responses tested across the full range of the target spinal topographies. (c) Rules for ISMS effects' dependence on spinal cord state and neural dynamics during naturally elicited or ISMS triggered behaviors. (d) Plasticity of the compositional rules for ISMS motor responses, and understanding plasticity of ISMS topography in different spinal cord lesion states, disease states, and following rehabilitation. All these knowledge gaps to a greater or lesser extent require novel electrode technology in order to allow high density chronic recording and stimulation. The current lack of this technology may explain why these prominent gaps in the ISMS literature currently exist. It is also argued that given the "known unknowns" in the current ISMS literature, it may be prudent to adopt and develop control schemes that can manage the current results with simple superposition and winner-take-all interactions, but can also incorporate the possible plastic and stochastic dynamic interactions that may emerge in fuller analyses over longer terms, and which have already been noted in some simpler model systems.

Decoding of human hand actions to handle missing limbs in neuroprosthetics

The only way we can interact with the world is through movements, and our primary interactions are via the hands, thus any loss of hand function has immediate impact on our quality of life. However, to date it has not been systematically assessed how coordination in the hand's joints affects every day actions. This is important for two fundamental reasons. Firstly, to understand the representations and computations underlying motor control "in-the-wild" situations, and secondly to develop smarter controllers for prosthetic hands that have the same functionality as natural limbs. In this work we exploit the correlation structure of our hand and finger movements in daily-life. The novelty of our idea is that instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. We asked seven subjects to interact in 17 daily-life situations, and quantified behavior in a principled manner using CyberGlove body sensor networks that, after accurate calibration, track all major joints of the hand. Our key findings are: (1) We confirmed that hand control in daily-life tasks is very low-dimensional, with four to five dimensions being sufficient to explain 80-90% of the variability in the natural movement data. (2) We established a universally applicable measure of manipulative complexity that allowed us to measure and compare limb movements across tasks. We used Bayesian latent variable models to model the low-dimensional structure of finger joint angles in natural actions. (3) This allowed us to build a naïve classifier that within the first 1000 ms of action initiation (from a flat hand start configuration) predicted which of the 17 actions was going to be executed-enabling us to reliably predict the action intention from very short-time-scale initial data, further revealing the foreseeable nature of hand movements for control of neuroprosthetics and tele operation purposes. (4) Using the Expectation-Maximization algorithm on our latent variable model permitted us to reconstruct with high accuracy (<5-6° MAE) the movement trajectory of missing fingers by simply tracking the remaining fingers. Overall, our results suggest the hypothesis that specific hand actions are orchestrated by the brain in such a way that in the natural tasks of daily-life there is sufficient redundancy and predictability to be directly exploitable for neuroprosthetics.

Axon diameters and conduction velocities in the macaque pyramidal tract

Small axons far outnumber larger fibers in the corticospinal tract, but the function of these small axons remains poorly understood. This is because they are difficult to identify, and therefore their physiology remains obscure. To assess the extent of the mismatch between anatomic and physiological measures, we compared conduction time and velocity in a large number of macaque corticospinal neurons with the distribution of axon diameters at the level of the medullary pyramid, using both light and electron microscopy. At the electron microscopic level, a total of 4,172 axons were sampled from 2 adult male macaque monkeys. We confirmed that there were virtually no unmyelinated fibers in the pyramidal tract. About 14% of pyramidal tract axons had a diameter smaller than 0.50 μm (including myelin sheath), most of these remaining undetected using light microscopy, and 52% were smaller than 1 μm. In the electrophysiological study, we determined the distribution of antidromic latencies of pyramidal tract neurons, recorded in primary motor cortex, ventral premotor cortex, and supplementary motor area and identified by pyramidal tract stimulation (799 pyramidal tract neurons, 7 adult awake macaques) or orthodromically from corticospinal axons recorded at the mid-cervical spinal level (192 axons, 5 adult anesthetized macaques). The distribution of antidromic and orthodromic latencies of corticospinal neurons was strongly biased toward those with large, fast-conducting axons. Axons smaller than 3 μm and with a conduction velocity below 18 m/s were grossly underrepresented in our electrophysiological recordings, and those below 1 μm (6 m/s) were probably not represented at all. The identity, location, and function of the majority of corticospinal neurons with small, slowly conducting axons remains unknown.

Quantification of dexterity as the dynamical regulation of instabilities: comparisons across gender, age, and disease

Dexterous manipulation depends on using the fingertips to stabilize unstable objects. The Strength-Dexterity paradigm consists of asking subjects to compress a slender and compliant spring prone to buckling. The maximal level of compression [requiring low fingertip forces <300 grams force (gf)] quantifies the neural control capability to dynamically regulate fingertip force vectors and motions for a dynamic manipulation task. We found that finger dexterity is significantly affected by age (p = 0.017) and gender (p = 0.021) in 147 healthy individuals (66F, 81M, 20-88 years). We then measured finger dexterity in 42 hands of patients following treatment for osteoarthritis of the base of the thumb (CMC OA, 33F, 65.8 ± 9.7 years), and 31 hands from patients being treated for Parkinson's disease (PD, 6F, 10M, 67.68 ± 8.5 years). Importantly, we found no differences in finger compression force among patients or controls. However, we did find stronger age-related declines in performance in the patients with PD (slope -2.7 gf/year, p = 0.002) than in those with CMC OA (slope -1.4 gf/year, p = 0.015), than in controls (slope -0.86 gf/year). In addition, the temporal variability of forces during spring compression shows clearly different dynamics in the clinical populations compared to the controls (p < 0.001). Lastly, we compared dexterity across extremities. We found stronger age (p = 0.005) and gender (p = 0.002) effects of leg compression force in 188 healthy subjects who compressed a larger spring with the foot of an isolated leg (73F, 115M, 14-92 years). In 81 subjects who performed the tests with all four limbs separately, we found finger and leg compression force to be significantly correlated (females ρ = 0.529, p = 0.004; males ρ = 0.403, p = 0.003; 28F, 53M, 20-85 years), but surprisingly found no differences between dominant and non-dominant limbs. These results have important clinical implications, and suggest the existence - and compel the investigation - of systemic versus limb-specific mechanisms for dexterity.

Finger-thumb coupling contributes to exaggerated thumb flexion in stroke survivors

The purpose of this study was to investigate altered finger-thumb coupling in individuals with chronic hemiparesis poststroke. First, an external device stretched finger flexor muscles by passively rotating the metacarpophalangeal (MCP) joints. Subjects then performed isometric finger or thumb force generation. Forces/torques and electromyographic signals were recorded for both the thumb and finger muscles. Stroke survivors with moderate (n = 9) and severe (n = 9) chronic hand impairment participated, along with neurologically intact individuals (n = 9). Stroke survivors exhibited strong interactions between finger and thumb flexors. The stretch reflex evoked by stretch of the finger flexors of stroke survivors led to heteronymous reflex activity in the thumb, while attempts to produce isolated voluntary finger MCP flexion torque/thumb flexion force led to increased and undesired thumb force/finger MCP torque production poststroke with a striking asymmetry between voluntary flexion and extension. Coherence between the long finger and thumb flexors estimated using intermuscular electromyographic correlations, however, was small. Coactivation of thumb and finger flexor muscles was common in stroke survivors, whether activation was evoked by passive stretch or voluntary activation. The coupling appears to arise from subcortical or spinal sources. Flexor coupling between the thumb and fingers seems to contribute to undesired thumb flexor activity after stroke and may impact rehabilitation outcomes.

Spatio-temporal analysis reveals active control of both task-relevant and task-irrelevant variables

The Uncontrolled Manifold (UCM) hypothesis and Minimal Intervention principle propose that the observed differential variability across task relevant (i.e., task goals) vs. irrelevant (i.e., in the null space of those goals) variables is evidence of a separation of task variables for efficient neural control, ranked by their respective variabilities (sometimes referred to as hierarchy of control). Support for this comes from spatial domain analyses (i.e., structure of) of kinematic, kinetic, and EMG variability. While proponents admit the possibility of preferential as opposed to strictly uncontrolled variables, such distinctions have only begun to be quantified or considered in the temporal domain when inferring control action. Here we extend the study of task variability during tripod static grasp to the temporal domain by applying diffusion analysis. We show that both task-relevant and task-irrelevant parameters show corrective action at some time scales; and conversely, that task-relevant parameters do not show corrective action at other time scales. That is, the spatial fluctuations of fingertip forces show, as expected, greater ranges of variability in task-irrelevant variables (>98% associated with changes in total grasp force; vs. only <2% in task-relevant changes associated with acceleration of the object). But at some time scales, however, temporal fluctuations of task-irrelevant variables exhibit negative correlations clearly indicative of corrective action (scaling exponents <0.5); and temporal fluctuations of task-relevant variables exhibit neutral and positive correlations clearly indicative of absence of corrective action (scaling exponents ≥0.5). In agreement with recent work in other behavioral contexts, these results propose we revise our understanding of variability vis-á-vis task relevance by considering both spatial and temporal features of all task variables when inferring control action and understanding how the CNS confronts task redundancy. Instead of a dichotomy of presence vs. absence of control, we should speak of a continuum of weaker to stronger—and potentially different—control strategies in specific spatiotemporal domains, indicated here by the magnitude of deviation from the 0.5 scaling exponent. Moreover, these results are counter examples to the UCM hypothesis and the Minimal Intervention principle, and the similar nature of control actions across time scales in both task-relevant and task-irrelevant spaces points to a level of modularity not previously recognized.