Visual information following object grasp supports digit position variability and swift anticipatory force control.

Anticipatory force control underlying dexterous manipulation has historically been understood to rely on visual object properties and on sensorimotor memories associated with previous experiences with similar objects. However, it is becoming increasingly recognized that anticipatory force control also relies on how an object is grasped. Experiments that allow unconstrained grasp contact points when preventing tilting an object with an off-centered mass show trial-to-trial variations in digit position and subsequent scaling of lift forces, all before feedback of object properties becomes available. Here, we manipulated the availability of visual information before reach onset and after grasp contact (with no vision during the reach) to determine the contribution and timing of visual information processing to the scaling of fingertip forces during dexterous manipulation at flexible contact points. Results showed that anticipatory force control was similarly successful, quantified as an appropriate compensatory torque at lift onset that counters the external torque of an object with a left and right center of mass, irrespective of the timing and availability of visual information. However, the way in which anticipatory force control was achieved varied depending on the availability of visual information. Visual information following grasp contact was associated with greater use of an asymmetric thumb and index finger grasp configuration to generate a compensatory torque and digit position variability, together with faster fingertip force scaling and sensorimotor learning. This result supports the hypothesis that visual information at a critical and functionally relevant time point following grasp contact supports variable and swift digit-based force control for dexterous object manipulation.NEW & NOTEWORTHY Humans excel in dexterous object manipulation by precisely coordinating grasp points and fingertip forces, highlighted in scenarios requiring countering object torques in advance, e.g., lifting a teacup without spilling will demand a unique digit force pattern based on the grip configuration at lift onset. Here, we show that visual information following grasp contact, a critical and functionally relevant time point, supports digit position variability and swift anticipatory force control to achieve a dexterous motor goal.

Complementary contribution of the medial and lateral human parietal cortex to grasping: a repetitive TMS study.

The dexterous control of our grasping actions relies on the cooperative activation of many brain areas. In the parietal lobe, 2 grasp-related areas collaborate to orchestrate an accurate grasping action: dorsolateral area AIP and dorsomedial area V6A. Single-cell recordings in monkeys and fMRI studies in humans have suggested that both these areas specify grip aperture and wrist orientation, but encode these grasping parameters differently, depending on the context. To elucidate the causal role of phAIP and hV6A, we stimulated these areas, while participants were performing grasping actions (unperturbed grasping). rTMS over phAIP impaired the wrist orientation process, whereas stimulation over hV6A impaired grip aperture encoding. In a small percentage of trials, an unexpected reprogramming of grip aperture or wrist orientation was required (perturbed grasping). In these cases, rTMS over hV6A or over phAIP impaired reprogramming of both grip aperture and wrist orientation. These results represent the first direct demonstration of a different encoding of grasping parameters by 2 grasp-related parietal areas.

The effects of explicit and implicit information on modulation of corticospinal excitability during hand-object interactions.

Fingertip force scaling during hand-object interactions typically relies on visual information about the object and sensorimotor memories from previous object interactions. Here, we investigated whether contextual information, that is not explicitly linked to the intrinsic object properties (e.g., size or weight) but that is informative for motor control requirements, can mediate force scaling. For this, we relied on two separate behavioral tasks during which we applied transcranial magnetic stimulation (TMS) to probe corticospinal excitability (CSE), as a window onto the primary motor cortex role in controlling fingertip forces. In experiment 1, participants performed a force tracking task, where we manipulated available implicit and explicit visual information. That is, either the force target was fully visible, or only the force error was displayed as a deviation from a horizontal line. We found that participants' performance was better when the force target was fully visible, i.e., when they had explicit access to predictive information. However, we did not find differences in CSE modulation based on the type of visual information. On the other hand, CSE was modulated by the change in muscle contraction, i.e., contraction vs. relaxation and fast vs. slow changes. In sum, these findings indicate that CSE only reflects the ongoing motor command. In experiment 2, other participants performed a sequential object lifting task of visually identical objects that were differently weighted, in a seemingly random order. Within this task, we hid short series of incrementally increasing object weights. This allowed us to investigate whether participants would scale their forces for specific object weights based on the previously lifted object (i.e., sensorimotor effect) or based on the implicit information about the hidden series of incrementally increasing weights (i.e., extrapolation beyond sensorimotor effects). Results showed that participants did not extrapolate fingertip forces based on the hidden series but scaled their forces solely on the previously lifted object. Unsurprisingly, CSE was not modulated differently when lifting series of random weights versus series of increasing weights. Altogether, these results in two different grasping tasks suggest that CSE encodes ongoing motor components but not sensorimotor cues that are hidden within contextual information.

Neural effects of continuous theta-burst stimulation in macaque parietal neurons.

Theta-burst transcranial magnetic stimulation (TBS) has become a standard non-invasive technique to induce offline changes in cortical excitability in human volunteers. Yet, TBS suffers from a high variability across subjects. A better knowledge about how TBS affects neural activity in vivo could uncover its mechanisms of action and ultimately allow its mainstream use in basic science and clinical applications. To address this issue, we applied continuous TBS (cTBS, 300 pulses) in awake behaving rhesus monkeys and quantified its after-effects on neuronal activity. Overall, we observed a pronounced, long-lasting, and highly reproducible reduction in neuronal excitability after cTBS in individual parietal neurons, with some neurons also exhibiting periods of hyperexcitability during the recovery phase. These results provide the first experimental evidence of the effects of cTBS on single neurons in awake behaving monkeys, shedding new light on the reasons underlying cTBS variability.

Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper.

Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentials in cortical neurons. The spatial relationship between the locally induced electric field and the stimulated neurons determines axonal depolarization. The induced electric field is influenced by the conductive properties of the tissue compartments and is strongest in the superficial parts of the targeted cortical gyri and underlying white matter. TMS likely targets axons of both excitatory and inhibitory neurons. The propensity of individual axons to fire an action potential in response to TMS depends on their geometry, myelination and spatial relation to the imposed electric field and the physiological state of the neuron. The latter is determined by its transsynaptic dendritic and somatic inputs, intrinsic membrane potential and firing rate. Modeling work suggests that the primary target of TMS is axonal terminals in the crown top and lip regions of cortical gyri. The induced electric field may additionally excite bends of myelinated axons in the juxtacortical white matter below the gyral crown. Neuronal excitation spreads ortho- and antidromically along the stimulated axons and causes secondary excitation of connected neuronal populations within local intracortical microcircuits in the target area. Axonal and transsynaptic spread of excitation also occurs along cortico-cortical and cortico-subcortical connections, impacting on neuronal activity in the targeted network. Both local and remote neural excitation depend critically on the functional state of the stimulated target area and network. TMS also causes substantial direct co-stimulation of the peripheral nervous system. Peripheral co-excitation propagates centrally in auditory and somatosensory networks, but also produces brain responses in other networks subserving multisensory integration, orienting or arousal. The complexity of the response to TMS warrants cautious interpretation of its physiological and behavioural consequences, and a deeper understanding of the mechanistic underpinnings of TMS will be critical for advancing it as a scientific and therapeutic tool.

The effects of TMS over the anterior intraparietal area on anticipatory fingertip force scaling and the size-weight illusion.

When lifting an object skillfully, fingertip forces need to be carefully scaled to the object's weight, which can be inferred from its apparent size and material. This anticipatory force scaling ensures smooth and efficient lifting movements. However, even with accurate motor plans, weight perception can still be biased. In the size-weight illusion, objects of different size but equal weight are perceived to differ in heaviness, with the small object perceived to be heavier than the large object. The neural underpinnings of anticipatory force scaling to object size and the size-weight illusion are largely unknown. In this study, we tested the role of anterior intraparietal cortex (aIPS) in predictive force scaling and the size-weight illusion, by applying continuous theta burst stimulation (cTBS) prior to participants lifting objects of different sizes. Participants received cTBS over aIPS, the primary motor cortex (control area), or Sham stimulation. We found no evidence that aIPS stimulation affected the size-weight illusion. Effects were, however, found on anticipatory force scaling, where grip force was less tuned to object size during initial lifts. These findings suggest that aIPS is not involved in the perception of object weight but plays a transient role in the sensorimotor predictions related to object size. NEW & NOTEWORTHY Skilled object manipulation requires forming anticipatory motor plans according to the object's properties. Here, we demonstrate the role of anterior intraparietal sulcus (aIPS) in anticipatory grip force scaling to object size, particularly during initial lifting experience. Interestingly, this role was not maintained after continued practice and was not related to perceptual judgments measured with the size-weight illusion.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus.

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation.

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Motor resonance is modulated by an object's weight distribution.

Transcranial magnetic stimulation (TMS) studies showed that corticospinal excitability (CSE) is modulated during observation of object lifting, an effect termed 'motor resonance'. Specifically, motor resonance is driven by movement features indicating object weight, such as object size or observed movement kinematics. We investigated in 16 humans (8 females) whether motor resonance is also modulated by an object's weight distribution. Participants were asked to lift an inverted T-shaped manipulandum with interchangeable center of mass after first observing an actor lift the same manipulandum. Participants and actor were instructed to minimize object roll and rely on constrained digit positioning during lifting. Constrained positioning was either collinear (i.e., fingertips on the same height) or noncollinear (i.e., fingertip on the heavy side higher than the one on the light side). The center of mass changed unpredictably before the actor's lifts and participants were explained that their weight distribution always matched the actor's one. Last, TMS was applied during both lift observation and planning of lift actions. Our results showed that CSE was similarly modulated during lift observation and planning: when participants observed or planned lifts in which the weight distribution was asymmetrically right-sided, CSE recorded from the thumb muscles was significantly increased compared to when the weight distribution was left-sided. During both lift observation and planning, this increase seemed to be primarily driven by the weight distribution and not specifically by the (observed) digit positioning or muscle contraction. In conclusion, our results indicate that complex intrinsic object properties such as weight distributions can modulate activation of the motor system during both observation and planning of lifting actions.

Behavioral effects of continuous theta-burst stimulation in macaque parietal cortex.

The neural mechanisms underlying the effects of continuous Theta-Burst Stimulation (cTBS) in humans are poorly understood. Animal studies can clarify the effects of cTBS on individual neurons, but behavioral evidence is necessary to demonstrate the validity of the animal model. We investigated the behavioral effect of cTBS applied over parietal cortex in rhesus monkeys performing a visually-guided grasping task with two differently sized objects, which required either a power grip or a pad-to-side grip. We used Fitts' law, predicting shorter grasping times (GT) for large compared to small objects, to investigate cTBS effects on two different grip types. cTBS induced long-lasting object-specific and dose-dependent changes in GT that remained present for up to two hours. High-intensity cTBS increased GTs for a power grip, but shortened GTs for a pad-to-side grip. Thus, high-intensity stimulation strongly reduced the natural GT difference between objects (i.e. the Fitts' law effect). In contrast, low-intensity cTBS induced the opposite effects on GT. Modifying the coil orientation from the standard 45-degree to a 30-degree angle induced opposite cTBS effects on GT. These findings represent behavioral evidence for the validity of the nonhuman primate model to study the neural underpinnings of non-invasive brain stimulation.

Lift observation conveys object weight distribution but partly enhances predictive lift planning.

Observation of object lifting allows updating of internal object representations for object weight, in turn enabling accurate scaling of fingertip forces when lifting the same object. Here, we investigated whether lift observation also enables updating of internal representations for an object's weight distribution. We asked participants to lift an inverted T-shaped manipulandum, of which the weight distribution could be changed, in turns with an actor. Participants were required to minimize object roll (i.e., "lift performance") during lifting and were allowed to place their fingertips at self-chosen locations. The center of mass changed unpredictably every third to sixth trial performed by the actor, and participants were informed that they would always lift the same weight distribution as the actor. Participants observed either erroneous (i.e., object rolling toward its heavy side) or skilled (i.e., minimized object roll) lifts. Lifting performance after observation was compared with lifts without prior observation and with lifts after active lifting, which provided haptic feedback about the weight distribution. Our results show that observing both skilled and erroneous lifts convey an object's weight distribution similar to active lifting, resulting in altered digit positioning strategies. However, minimizing object roll on novel weight distributions was only improved after observing error lifts and not after observing skilled lifts. In sum, these findings suggest that although observing motor errors and skilled motor performance enables updating of digit positioning strategy, only observing error lifts enables changes in predictive motor control when lifting objects with unexpected weight distributions.NEW & NOTEWORTHY Individuals are able to extract an object's size and weight by observing interactions with objects and subsequently integrate this information in their own motor repertoire. Here, we show that this ability extrapolates to weight distributions. Specifically, we highlighted that individuals can perceive an object's weight distribution during lift observation but can only partially embody this information when planning their own actions.

The role of the anterior intraparietal sulcus and the lateral occipital cortex in fingertip force scaling and weight perception during object lifting.

Skillful object lifting relies on scaling fingertip forces according to the object's weight. When no visual cues about weight are available, force planning relies on previous lifting experience. Recently, we showed that previously lifted objects also affect weight estimation, as objects are perceived to be lighter when lifted after heavy objects compared with after light ones. Here, we investigated the underlying neural mechanisms mediating these effects. We asked participants to lift objects and estimate their weight. Simultaneously, we applied transcranial magnetic stimulation (TMS) during the dynamic loading or static holding phase. Two subject groups received TMS over either the anterior intraparietal sulcus (aIPS) or the lateral occipital area (LO), known to be important nodes in object grasping and perception. We hypothesized that TMS over aIPS and LO during object lifting would alter force scaling and weight perception. Contrary to our hypothesis, we did not find effects of aIPS or LO stimulation on force planning or weight estimation caused by previous lifting experience. However, we found that TMS over both areas increased grip forces, but only when applied during dynamic loading, and decreased weight estimation, but only when applied during static holding, suggesting time-specific effects. Interestingly, our results also indicate that TMS over LO, but not aIPS, affected load force scaling specifically for heavy objects, which further indicates that load and grip forces might be controlled differently. These findings provide new insights on the interactions between brain networks mediating action and perception during object manipulation.NEW & NOTEWORTHY This article provides new insights into the neural mechanisms underlying object lifting and perception. Using transcranial magnetic stimulation during object lifting, we show that effects of previous experience on force scaling and weight perception are not mediated by the anterior intraparietal sulcus or the lateral occipital cortex (LO). In contrast, we highlight a unique role for LO in load force scaling, suggesting different brain processes for grip and load force scaling in object manipulation.

Sensorimotor Expectations Bias Motor Resonance during Observation of Object Lifting: The Causal Role of pSTS.

Transcranial magnetic stimulation studies have highlighted that corticospinal excitability is increased during observation of object lifting, an effect termed "motor resonance." This facilitation is driven by movement features indicative of object weight, such as object size or observed movement kinematics. Here, we investigated in 35 humans (23 females) how motor resonance is altered when the observer's weight expectations, based on visual information, do not match the actual object weight as revealed by the observed movement kinematics. Our results highlight that motor resonance is not robustly driven by object weight but easily masked by a suppressive mechanism reflecting the correctness of weight expectations. Subsequently, we investigated in 24 humans (14 females) whether this suppressive mechanism was driven by higher-order cortical areas. For this, we induced "virtual lesions" to either the posterior superior temporal sulcus (pSTS) or dorsolateral prefrontal cortex (DLPFC) before having participants perform the task. Importantly, virtual lesion of pSTS eradicated this suppressive mechanism and restored object weight-driven motor resonance. In addition, DLPFC virtual lesion eradicated any modulation of motor resonance. This indicates that motor resonance is heavily mediated by top-down inputs from both pSTS and DLPFC. Together, these findings shed new light on the theorized cortical network driving motor resonance. That is, our findings highlight that motor resonance is not only driven by the putative human mirror neuron network consisting of the primary motor and premotor cortices as well as the anterior intraparietal sulcus, but also by top-down input from pSTS and DLPFC.SIGNIFICANCE STATEMENT Observation of object lifting activates the observer's motor system in a weight-specific fashion: Corticospinal excitability is larger when observing lifts of heavy objects compared with light ones. Interestingly, here we demonstrate that this weight-driven modulation of corticospinal excitability is easily suppressed by the observer's expectations about object weight and that this suppression is mediated by the posterior superior temporal sulcus. Thus, our findings show that modulation of corticospinal excitability during observed object lifting is not robust but easily altered by top-down cognitive processes. Finally, our results also indicate how cortical inputs, originating remotely from motor pathways and processing action observation, overlap with bottom-up motor resonance effects.

Observation of Both Skilled and Erroneous Object Lifting Can Improve Predictive Force Scaling in the Observer.

Recent studies have highlighted that the observation of hand-object interactions can influence perceptual weight judgments made by an observer. Moreover, observing salient motor errors during object lifting allows individuals to update their internal sensorimotor representation about object weight. Embodying observed visuomotor cues for the planning of a motor command further enables individuals to accurately scale their fingertip forces when subsequently lifting the same object. However, it is still unknown whether the observation of a skilled lift is equally able to mediate predictive motor control in the observer. Here, we tested this hypothesis by asking participants to grasp and lift a manipulandum after observing an actor's lift. The object weight changed unpredictably (light or heavy) every fourth to sixth trial performed by the actor. Participants were informed that they would always lift the same weight as the actor and that, based on the experimental condition, they would have to observe skilled or erroneously performed lifts. Our results revealed that the observation of both skilled and erroneously performed lifts allows participants to update their internal sensorimotor object representation, in turn enabling them to predict force scaling accurately. These findings suggest that the observation of salient motor errors, as well as subtle features of skilled motor performance, are embodied in the observer's motor repertoire and can drive changes in predictive motor control.

Dynamic size-weight changes after object lifting reduce the size-weight illusion.

In the size-weight illusion, the smaller object from two equally weighted objects is typically judged as being heavier. One explanation is that the mismatch between the weight expectation based on object size and actual sensory feedback influences heaviness perception. In most studies, the size of an object is perceived before its weight. We investigated whether size changes would influence weight judgement if both would be perceived simultaneously. We used virtual reality to change the size and weight of an object after lifting and asked participants to judge whether the object became lighter or heavier. We found that simultaneous size-weight changes greatly reduced the size-weight illusion to perceptual biases below discrimination thresholds. In a control experiment in which we used a standard size-weight illusion protocol with sequential lifts of small and large objects in the same virtual reality setup, we found a larger, typical perceptual bias. These results show that the size-weight illusion is smaller when size and weight information is perceived simultaneously. This provides support for the prediction mismatch theory explaining the size-weight illusion. The comparison between perceived and expected weight during the lifting phase could be a critical brain mechanism for mediating the size-weight illusion.

Sensorimotor memory for object weight is based on previous experience during lifting, not holding.

To allow skilled object manipulation, the brain must generate a motor command specifically tailored to the object properties. For instance, in object lifting, the forces applied by the fingertips must be scaled to the object's weight. When lifting a series of objects, forces are usually scaled according to recent experience from previously lifted objects, an effect often referred to as sensorimotor memory. In this study, we investigated the specific time period during which stored information from previous object manipulation is used to mediate sensorimotor memory. More specifically, we examined whether sensorimotor memory was based on weight information obtained between object contact and lift completion (lifting phase) or during stable holding (holding phase). Participants lifted light and heavy objects in a randomised order in virtual reality that could increase or decrease in weight after the object was lifted and held in the air. In this way, we could distinguish whether the force planning in the next lift was scaled depending on weight information gathered from either the dynamic lifting or static holding period. We found that force planning was based on the previous object weight experienced during the lifting, but not holding, phase. This suggest that the lifting phase is a key time period for building up sensorimotor memory for planning future hand-object interactions.

Neural effects of transcranial magnetic stimulation at the single-cell level.

Transcranial magnetic stimulation (TMS) can non-invasively modulate neural activity in humans. Despite three decades of research, the spatial extent of the cortical area activated by TMS is still controversial. Moreover, how TMS interacts with task-related activity during motor behavior is unknown. Here, we applied single-pulse TMS over macaque parietal cortex while recording single-unit activity at various distances from the center of stimulation during grasping. The spatial extent of TMS-induced activation is remarkably restricted, affecting the spiking activity of single neurons in an area of cortex measuring less than 2 mm in diameter. In task-related neurons, TMS evokes a transient excitation followed by reduced activity, paralleled by a significantly longer grasping time. Furthermore, TMS-induced activity and task-related activity do not summate in single neurons. These results furnish crucial experimental evidence for the neural effects of TMS at the single-cell level and uncover the neural underpinnings of behavioral effects of TMS.

Sensorimotor uncertainty modulates corticospinal excitability during skilled object manipulation.

Sensorimotor memory built through previous hand-object interactions allows subjects to plan grasp forces. The memory-based mechanism is particularly effective when contact points on the object do not change across multiple manipulations, thus allowing subjects to generate the same forces in a feedforward fashion. However, allowing subjects to choose where to grasp an object causes trial-to-trial variability in fingertip positioning, suggesting a decreased ability to predict where the object will be grasped. In this scenario, subjects modulate forces on a trial-to-trial basis as a function of fingertip positioning. We suggested that this fingertip force-to-position modulation could be implemented by transforming feedback of digit placement into an accurate distribution of fingertip forces. Thus, decreasing certainty of fingertip position on an object would cause a shift from predominantly memory- to feedback-based force control mechanisms. To gain further insight into these sensorimotor transformation mechanisms, we asked subjects to grasp and lift an object with an asymmetrical center of mass while preventing it from tilting. To isolate the effect of digit placement uncertainty, we designed two experimental conditions that differed in terms of predictability of fingertip position but had similar average fingertip positioning and force distribution. We measured corticospinal excitability to probe possible changes in sensorimotor processing associated with digit placement uncertainty. We found a differential effect of sensorimotor uncertainty after but not before object contact. Our results suggest that sensorimotor integration is rapidly tuned after object contact based on different processing demands for memory versus feedback mechanisms underlying the control of manipulative forces. NEW & NOTEWORTHY The relative contribution of predictive and feedback mechanisms for scaling digit forces to position during dexterous manipulation depends on the predictability of where the object will be grasped. We found that corticospinal excitability shortly after contact was sensitive to digit position predictability. This supports the proposition that distinct sensorimotor integration processes are engaged, depending on the role of feedback about digit placement versus sensorimotor memory in controlling manipulative forces.

Visual delay affects force scaling and weight perception during object lifting in virtual reality.

Lifting an object requires precise scaling of fingertip forces based on a prediction of object weight. At object contact, a series of tactile and visual events arise that need to be rapidly processed online to fine-tune the planned motor commands for lifting the object. The brain mechanisms underlying multisensory integration serially at transient sensorimotor events, a general feature of actions requiring hand-object interactions, are not yet understood. In this study we tested the relative weighting between haptic and visual signals when they are integrated online into the motor command. We used a new virtual reality setup to desynchronize visual feedback from haptics, which allowed us to probe the relative contribution of haptics and vision in driving participants' movements when they grasped virtual objects simulated by two force-feedback robots. We found that visual delay changed the profile of fingertip force generation and led participants to perceive objects as heavier than when lifts were performed without visual delay. We further modeled the effect of vision on motor output by manipulating the extent to which delayed visual events could bias the force profile, which allowed us to determine the specific weighting the brain assigns to haptics and vision. Our results show for the first time how visuo-haptic integration is processed at discrete sensorimotor events for controlling object-lifting dynamics and further highlight the organization of multisensory signals online for controlling action and perception. NEW & NOTEWORTHY Dexterous hand movements require rapid integration of information from different senses, in particular touch and vision, at different key time points as movement unfolds. The relative weighting between vision and haptics for object manipulation is unknown. We used object lifting in virtual reality to desynchronize visual and haptic feedback and find out their relative weightings. Our findings shed light on how rapid multisensory integration is processed over a series of discrete sensorimotor control points.

Functional interaction between human dorsal premotor cortex and the ipsilateral primary motor cortex for grasp plans: a dual-site TMS study.

Recent findings suggest that the dorsal premotor cortex (PMd), a cortical area in the dorsomedial pathway, is involved in grasp control. It is unclear, however, whether human PMd transfers grasp-related information to the primary motor cortex hand area (M1HAND) during action preparation. The present study tested whether ipsilateral cortico-cortical connections between PMd and M1HAND in the left hemisphere are modulated during grasp preparation. Ten participants performed object-directed grasps and reaches with the right hand. Functional connectivity between left PMd and ipsilateral M1HAND was probed with dual-site transcranial magnetic stimulation. We found that PMd-M1HAND functional interactions were facilitated selectively for the muscles involved in the preparation of the upcoming grasps. The PMd-M1HAND interaction was facilitated for first dorsal interosseous muscle for both precision grip and whole-hand grasps and for abductor digiti minimi muscle for whole-hand grasps. We conclude that human dorsomedial PMd-M1HAND circuit encodes handgrip formation during grasp preparation.