In den letzte Jahrzehnten wurde viel daran geforscht zu entschlüsseln wie das Gehirn Greifbewegungen koordiniert. Das anteriore intraparietale Areal (AIP), das Hand Areal des ventralen premotorischen Kortex (F5), und das Hand Areal des primären motorischen Kortex (M1) wurden als essentielle kortikale Arealen für die Kontrolle der Hand identifiziert. Nichtsdestotrotz ist deutlich weniger darüber bekannt wie die Neuronen dieser Areale einen weiteren essentielle Parameter von Greifbewegungen kodieren: Greifkraft. Insbesondere die Rolle der tertiären, kortikalen Areale AIP und F5 in diesen Prozess ist bisher unklar. Die hier durchgeführte Studie befasst sich mit der Wissenslücke über die neuronale Kodierung von Greifkraft Planung und Steuerung in diesen Arealen. Um dies zu erreichen, haben wir zwei Makaken (Macaca mulatta) trainiert eine verzögerte Greifaufgabe auszuführen mit zwei Grifftypen (ein Griff mit der ganzen Hand oder ein Präzisionsgriff) und mit drei verschiedene Kraftniveaus (0-12 N). Während die Affen die Aufgabe ausführten, haben wir die Aktivität von “single-units“ (einzelnen Neuronen) und “multi-units“ (Gruppen von mehreren Neuronen) in den Arealen AIP, F5 und M1 aufgenommen. Wir berechneten den Prozentsatz von Grifftyp modulierten und Griffkraft modulierten “units“ (cluster-based permutation test) und berechneten wie viel Varianz in der Population von “units“ durch Grifftyp und Kraft erklärbar ist, separat für jedes Gehirn Areal mit einer modernen Dimensionalitätsreduktionsanalyse (demixed principal component analysis). 18 Wir zeigen hier zum ersten Mal die Modulation von einzelnen AIP Neuronen durch Greifkraft. Weiterhin bestätigen und erweitern wir hier vorherige Ergebnisse, welche solche neuronale Modulationen bereits in F5 und M1 gezeigt haben. Überaschenderweise war der Prozentsatz von “units“ welche durch Griffkraft moduliert werden, in AIP und F5 nicht wesentlich kleiner als in M1 und ähnlich zu dem Prozentsatz an Grifftyp modulierte Neuronen. Der Anteil an erklärte Varianz in F5 durch Greifkraft war nahezu so groß, wie der Anteil erklärt durch Grifftyp. In AIP und M1 war klar mehr Varianz durch Grifftyp erklärt als durch Kraft, aber der Anteil an erklärte Varianz beider Arealen war ausreichend, um zuverlässig Kraftbedingung zu dekodieren. Wir fanden ebenfalls eine starke neuronale Modulation für Griffkraftbedingungen vor der Bewegungsinitiierung in F5, was wahrscheinlich eine Rolle dieses Areals in der Greifkraftplanung repräsentiert. In AIP war Greifkraftplanungsaktivität nur in einen der beiden Affen vorhanden und wie erwartet nicht präsent in M1 (gemessen nur in einen Affen). Letztendlich, obwohl Greifkraftmodulation in einigen Fällen durch Grifftypmodulation beeinflusst war, war nur ein kleiner Anteil der Populationsvarianz, in den jeweiligen Arealen, durch interaktive Modulation erklärt. Information über Greifkraft können somit folglich separat vom Grifftyp extrahiert werden. Diese Ergebnisse legen eine wichtige Rolle von AIP und F5 bei der Greifkraftkontrolle, neben M1, nah. F5 ist mit hoher Wahrscheinlichkeit auch bei der Planung von Greifkraft involviert, während die Rolle von AIP und M1 geringer ist in diesem Prozess. Letztendlich, da Grifftyp- und Kraftinformation separat extrahierbar sind, zeigen diese Ergebnisse, dass Greifkraft vermutlich unabhängig von Grifftyp, im kortikalen Greifnetzwerk kodiert ist. / In de laatste decennia is er veel onderzoek gedaan om te interpreteren hoe de hersenen grijpbewegingen besturen. Het anterieure intra pariëtale gebied (AIP), het handgebied van de ventrale premotorische schors (F5) en het handgebied van de primaire motorische schors (M1) zijn geïdentificeerd als essentiële gebieden van de hersenschors die de vorm van de hand besturen. Maar er is veel minder bekend over hoe de hersenen een andere parameter van grijpbewegingen bestuurt: grijpkracht. Vooral de rol in dit proces van AIP en F5, gebieden van hogere orde, is nog nagenoeg onbekend. Deze studie richt zich op het gebrek aan kennis over de neurale codering van het plannen en besturen van grijpkracht. Om dit te bereiken, hebben we twee makaken (Macaca mulatta) getraind om een vertraagde grijptaak uit te voeren met twee grepen van de hand (een grip met de hele hand of een precisie grip) en met drie verschillende krachtniveaus (0-12 N). Terwijl de apen de taak uitvoerden, maten we de activiteit van single-units (individuele neuronen) en multiunits (collectie van enkele neuronen) in de gebieden AIP, F5 en M1. We berekenden het percentage van units die hun activiteit moduleerden op basis van grip vorm of kracht met een moderne statistieke test (cluster-based permutation test) en we berekenden de hoeveelheid variantie die werd verklaard door de grip vorm en kracht door de populatie van units van elk hersengebied met een moderne dimensie vermindering techniek (demixed principal component analysis). We laten hier voor het eerst zien dat individuele neuronen van AIP hun activiteit moduleren op basis van grijpkracht. Verder bevestigen we dat neuronen van F5 en M1 20 dergelijke modulaties vertonen en breiden we de kennis hierover uit. Verassend genoeg was het percentage units dat reageert op het besturen van grijpkracht in AIP en F5 niet veel lager dan in M1 en ongeveer gelijk aan de hoeveelheid units dat reageert op grip vorm. De hoeveelheid variantie die werd verklaard door grijpkracht in F5 was bijna net zo hoog als wat werd verklaard door grip vorm. In AIP en M1 verklaarde grip vorm duidelijk meer variantie dan grijpkracht, maar ook in deze gebieden was de hoeveelheid variantie dat grijpkracht verklaarde hoog genoeg om de kracht conditie te decoderen. We vonden ook een sterke neurale modulatie voor grijpkracht condities in F5 voordat de arm bewoog, wat mogelijk een rol voor dit gebied representeert in het plannen van grijpkracht. In AIP was activiteit voor het plannen van grijpkracht alleen in één van beide apen gevonden en zoals verwacht was het niet gevonden in M1 (onderzocht in één aap). Tenslotte vonden we dat, hoewel modulatie voor kracht werd beïnvloedt door grip vorm in sommige eenheden, slechts een kleine fractie van de variantie van de neurale populatie van elk hersengebied een gemixte selectiviteit voor grip vorm en kracht had. Informatie over grijpkracht kon daarom onafhankelijk van grip vorm worden geëxtraheerd. Deze bevindingen suggereren een belangrijke rol voor AIP en F5 in het besturen van grijpkracht, samen met M1. F5 is waarschijnlijk ook betrokken met het plannen van grijpkracht, terwijl AIP en M1 waarschijnlijk een kleinere rol hebben in dit proces. Tenslotte, omdat informatie over grip vorm en grijpkracht onafhankelijk konden worden geëxtraheerd, laten deze resultaten zien dat grijpkracht vermoedelijk onafhankelijk van hand vorm is gecodeerd in het grijpnetwerk van de hersenschors.

La stimulation électrique fonctionnelle (FES) est présente depuis des décennies dans les centres de rééducation. Le principe de cette technique est de créer une dépolarisation de la membrane (potentiel d’action) des cellules excitables (axones ou myocytes) entrainant une contraction musculaire. Employée dans la plupart des cas pour le renforcement musculaire et la prévention des atrophies musculaires faisant suite à une lésion de la moelle épinière, la FES peut également être utilisée pour diminuer la spasticité et restaurer des mouvements des membres. Ainsi, certains dispositifs (neuroprothèses) utilisant la FES sont utilisés depuis plus de 25 ans, pour permettre à certains patients atteints de paralysies des membres supérieurs de pouvoir effectuer des préhensions. Les patients gagnent alors en autonomie dans les activités de la vie quotidienne ce qui limite leurs recours aux aides humaines. Cependant, bien que ce type de neuroprothèse se présente comme l’une des techniques les plus prometteuses pour le rétablissement de la fonction de préhension chez des sujets atteints d’une lésion de la moelle épinière, son utilisation reste limitée. En effet, les dispositifs de stimulation externe provoque des mouvements peu précis et les modes de pilote de cette stimulation, peu ergonomiques, ne sont pas accessibles à la plupart des patients lésés médullaires. Ces difficultés sont atténuées lorsque la stimulation est implantée et le mode de contrôle adapté à la pathologie. Parmi les dispositifs implantées, tous utilisent la stimulation des points moteurs pour rétablir des mouvements de main ce qui nécessite l’implantation de nombreuses électrodes et donc une opération chirurgicale lourde. Des complications liées aux matériels implantés peuvent apparaître au cours du temps. Ce travail de thèse propose une approche originale basée sur (i) la stimulation sélective nerveuse (à l’aide d’une électrode gouttière multi contact) pour rétablir des mouvements de préhension chez des patients tétraplégiques et (ii) l’utilisation de signaux émanant de muscles supra lésionnels pour le contrôle de cette stimulation. Des expérimentations humaines et animales réalisées en conditions aiguës ont démontré la faisabilité de notre approche. Ainsi, la stimulation du nerf sciatique par notre électrode gouttière a permis d’activer sélectivement plusieurs muscles antagonistes chez les 5 animaux de l’étude inclus dans l’étude. Une sélectivité intra fasciculaire est retrouvée chez 3 des 5 animaux. La stimulation du nerf médian chez un patient tétraplégique a permis d’activer sélectivement les muscles palmaris longuset flexor carpi radialis. Concernant le contrôle de la neuroprothèse, nous avons mis en évidence chez les 5 sujets tétraplégiques ayant participé aux expérimentations, une combinaison de muscles pouvant être utilisée pour piloter facilement un dispositif. Des contractions continues ou gradées de ces muscles peuvent être maintenues et ce, sans aucun apprentissage ou entrainement préalable. Les modalités de contrôle et les muscles préférentiels sont patient-dépendant. / Functional electrical stimulation (FES) is used for decades in rehabilitation centers. The principle of this technique is to create a membrane depolarization (action potential) of excitable cells (myocytes or axons) to cause a muscle contraction. Used in most cases for muscle strengthening and prevention of muscle atrophy following a spinal cord injury, FES can also be used to reduce spasticity and restore limb movement. For example, some devices (neuroprostheses) using FES are used for over 25 years, to allow some patients with paralysis of the upper limbs to perform hand movements. Patients then becoming more independent in activities of daily living which limits their use of human aid. However, although this type of neuroprosthesis stands as one of the most promising techniques for the recovery of the gripping function in subjects with spinal cord injury, its use is limited. Indeed, external stimulation devices cause imprecise movements and modes of control modes, not very ergonomic, are not accessible to most spinal cord injured patients. These difficulties are alleviated when the stimulation is implanted and control mode adapted to the pathology. Among the implanted devices all use the stimulation of motor pointsto restore hand movements which requires the implantation of many electrodes and therefore a major surgery. Complications related to the implanted materials can occur over time. This thesis proposes an original approach based on (i) selective nerve stimulation (using a multi contact cuff electrode) to restore gripping motion in tetraplegic patients and (ii) use of signals from supra lesional muscles to control this stimulation. Human and animal experimentations performed in acute conditions have demonstrated the feasibility of our approach. Thus, stimulation of the sciatic nerve by our cuff electrode allowed to selectively activate several antagonistic muscles in the 5 animals included in the study. Intra fascicular selectivity was found in 3 of 5 animals. The stimulation of the median nerve of a tetraplegic patient allowed to selectively activate the palmaris longus and flexor carpi radialis muscles. For the control of neuroprosthesis we demonstrated in the 5 tetraplegics subjects who participated in the experiments, a combination of muscles that can be used to easily control a device. Continuous or graded contractions of these muscles can be maintained, without any prior learning or training. The control modalities and preferential muscles are patient-dependent.

Wearable assistive robotics have the potential to address an unmet medical need of reducing disability in individuals with chronic hand impairments due to neurological trauma. Despite myriad prior works, few patients have seen the benefits of such devices. Following application experience with tendon-actuated soft robotic gloves and a collaborator's orthosis with novel flat-spring actuators, we identified two common assumptions regarding hand orthosis design. The first was reliance on incomplete studies of grasping forces during activities of daily living as a basis for design criteria, leading to poor optimization. The second was a neglect of increases in muscle tone following neurological trauma, rendering most devices non-applicable to a large subset of the population. To address these gaps, we measured joint torques during activities of daily living with able-bodied subjects using dexterity representative of orthosis-aided motion. Next, we measured assistive torques needed to extend the fingers of individuals with increased flexor tone following TBI. Finally, we applied this knowledge to design a cable actuated orthosis for assisting finger extension, providing a basis for future work focused on an under-represented subgroup of patients.

While robots are extensively used in factories, our industry hasn't yet been able to prepare them for working in human environments - for instance in houses or in human-operated factories. The main obstacle to these applications lies in the amplitude of the uncertainty inherent to the environments humans are used to work in, and in the difficulty in programming robots to cope with it. For instance, in robot-oriented environments, robots can expect to find specific tools and objects in specific places. In a human environment, obstacles may force one to find a new way of holding a tool, and new objects appear continuously and need to be dealt with. As it proves difficult to build into robots the knowledge necessary for coping with uncertain environments, the robotics community is turning to the development of agents that acquire this knowledge progressively and that adapt to unexpected events. This thesis studies the problem of vision-based robotic grasping in uncertain environments. We aim to create an autonomous agent that develops grasping skills from experience, by interacting with objects and with other agents. To this end, we present a 3D object model for autonomous, visuomotor interaction. The model represents grasping strategies along with visual features that predict their applicability. It provides a robot with the ability to compute grasp parameters from visual observations. The agent acquires models interactively by manipulating objects, possibly imitating a teacher. With time, it becomes increasingly efficient at inferring grasps from visual evidence. This behavior relies on (1) a grasp model representing relative object-gripper configurations and their feasibility, and (2) a model of visual object structure, which aligns the grasp model to arbitrary object poses (3D positions and orientations). The visual model represents object edges or object faces in 3D by probabilistically encoding the spatial distribution of small segments of object edges or the distribution of small patches of object surface. A model is learned from a few segmented 3D scans or stereo images of an object. Monte Carlo simulation provides robust estimates of the object's 3D position and orientation in cluttered scenes. The grasp model represents the likelihood of success of relative object-gripper configurations. Initial models are acquired from visual cues or by observing a teacher. Models are then refined autonomously by ``playing' with objects and observing the effects of exploratory grasps. After the robot has learned a few object models, learning becomes a combination of cross-object generalization and interactive experience: grasping strategies are generalized across objects that share similar visual substructures; they are then adapted to new objects through autonomous exploration. The applicability of our model is supported by numerous examples of pose estimates in cluttered scenes, and by a robot platform that shows increasing grasping capabilities as it explores its environment.

‘Sensorimotor transformations’ are processes whereby sensory information is used to generate motor commands. One example is the ‘visuomotor map’ that transforms visual information about objects to motor commands that activates various muscles during grasping movements. In the first study we quantified the relative impact (or ‘weighting’) of visual and haptic information on the sensorimotor transformation and investigated the principles that regulates the weighting process. To do this, we let subjects perform a task in which the object seen (visual object) and the object grasped (haptic object) were physically never the same. When the haptic object became larger or smaller than the visual object, subjects in the following trials automatically adapted their maximum grip aperture (MGA) when reaching for the object. The adaptation process was quicker and relied more on haptic information when the haptic objects increased in size than when they decreased in size. As such, sensory weighting is molded to avoid prehension error. In the second study we investigated the degree to which the visuomotor map could be modified. Normally, the relationship between the visual size of the object (VO) and the MGA can be expressed as a linear relationship, where MGA = a + b * VO. Our results demonstrate that subjects inter- and extrapolate in the visuomotor map (that is, they are reluctant to abandon the linear relationship) and that the offset (a) but not the slope (b) can be modified. In the third study, we investigated how a ‘new’ sensorimotor transformation can be established and modified. We therefore replaced the normal input of visual information about object size with auditory information, where the size of the object was log-linearly related to the frequency of a tone. Learning of an audiomotor map consisted of three distinct phases: during the first stage (~10-15 trials) there were no overt signs of learning. During the second stage there was a period of fast learning where the MGA became scaled to the size of the object until the third stage where the slope was constant. The purpose of the fourth study was to investigate the sensory basis for the aperture adaptation process. To do that, the forces acting between the fingertips and the object was measured as the subjects adapted. Our results indicate that information about when the fingers contacts the object, that is, the ‘timing’ of contact, is likely to be used by the CNS to encode an unexpected object size. Since injuries and disease can affect the sensorimotor transformations that controls the hand, knowledge about how these processes are established and modified may be used to develop techniques for sensory substitution and other rehabilitation strategies.

This thesis presents two studies that investigate how vision is used to control rapid, compensatory reach-to-grasp reactions. Compensatory grasping reactions were evoked in healthy young adults via unpredictable translations of large platforms on which the subjects stood or walked. The first study tracked natural gaze behaviour during responses to unexpected balance perturbations. It provided evidence that, unlike with voluntary movements, the eyes do not lead the hand during balance recovery – subjects relied on ‘stored’ information from central vision, continuously-available peripheral vision, or a combination of these sources to guide the hand. The second study investigated the efficacy of reliance on peripheral vision to guide rapid reach-to-grasp balance-recovery reactions. Peripheral vision was found to guide reach-to-grasp responses with sufficient accuracy to achieve a functional grasp of a relatively small handhold; however, peripherally-guided movements were slower when the handhold was in the extreme periphery.

This thesis presents two studies that investigate how vision is used to control rapid, compensatory reach-to-grasp reactions. Compensatory grasping reactions were evoked in healthy young adults via unpredictable translations of large platforms on which the subjects stood or walked. The first study tracked natural gaze behaviour during responses to unexpected balance perturbations. It provided evidence that, unlike with voluntary movements, the eyes do not lead the hand during balance recovery – subjects relied on ‘stored’ information from central vision, continuously-available peripheral vision, or a combination of these sources to guide the hand. The second study investigated the efficacy of reliance on peripheral vision to guide rapid reach-to-grasp balance-recovery reactions. Peripheral vision was found to guide reach-to-grasp responses with sufficient accuracy to achieve a functional grasp of a relatively small handhold; however, peripherally-guided movements were slower when the handhold was in the extreme periphery.

This thesis focuses on the definition of a task for the determination, tracking and execution of a grasp on an unknown object. In particular, it is considered the case in which the object is ideally planar and the grasp has to be executed with a two-fingered, parallel-jaw gripper using vision as the source of sensor data. For the specification of this task, an architecture is defined that is based on three basic components -virtual sensors, filters, and actuators-, which can be connected to define a control loop. Each step in this task is analyzed separately, considering several options in some cases.Some of the main contributions of this thesis include: (1) the use of a modular approach to the specification of a control task that provides a basic framework for supporting the concept of behavior; (2) the analysis of several strategies for obtaining a compact representation of the contour of an object; (3) the development of a method for the evaluation and search of a grasp on a planar object for a two-fingered gripper; (4) the specification of different representations of a grasp and the analysis of their use for tracking the grasp between different views of an object; (5) the specification of algorithms for the tracking of a grasp along the views of an object obtained from a sequence of single images and a sequence of stereo images; (6) the definition of parametrized models of the target position of the grasp points and of the feasibility of this target grasp, and of an off-line procedure for the computation of some of the reference values required by this model; and (7) the definition and analysis of a visual servoing control scheme to guide the gripper of a robot arm towards an unknown object using the grasp points computed for that object as control features.

In this dissertation, three experiments were conducted that examined the influence of task demands on manual asymmetries for the performance of reaching movements to tools. In all three experiments, the difference between the hands (in terms of preference for Experiment 1 and performance for Experiments 2 and 3) was studied in response to varying task demands for grasping movements to tools. In the first experiment, 82 right-handed and 60 left-handed university students performed reaching movements to tools and dowels at five positions within working space. Differences in the reaching patterns of the left and right hands to the tools and dowels were examined, as well as the effect of task demands (lift, use) and type of object (tool, dowel) on the reaching patterns. Dowels were used in order to examine if participants would treat a neutral object as if it were a tool in terms of their reaching patterns in working space. Results confirmed and extended prior research on the influence of task demands on reaching patterns within working space. Overall, there were more similarities in the general reaching patterns of left- and right-handed participants than differences. However key differences between the handedness groups emerged in the treatment of the dowel and the frequency of switches (reaching to lift the object with the non-preferred hand and transferring it to the preferred hand to use). Results also showed that tools enjoy a privileged association with the preferred hand, and that the intent of the movement has a very real goal on movement planning. The first experiment examined patterns of hand use across working space in response to differing task demands. In the next experiments performance differences between the hands in terms of movement planning and initiation were examined through the use of reaction time and movement time. In these experiments, reaction time represented the time from the presentation of a go signal to when the participant first lifted their hand, and movement time was the time between lifting the hand to lifting a tool off a sensor. Movement time represented the time to pick up the tool, and did not include the time to use the tool to perform a particular task and complete the reaching movement. In the second experiment, reaction time and movement time to tools placed at the midline position were examined under varying degrees of advance information using a precue paradigm. Three precue conditions were used which presented advance information on the hand to use to perform the movement (left or right) and/or the task (lift, use, or pantomime) to be performed: (1) both hand and task were cued in advance (Both precue); (2) task only was cued in advance (Task precue); and (3) neither hand nor task were cued in advance (No precue). Twenty-four right-handed university students performed reaching movements to tools under the three different precue conditions. The results of Experiment 2 showed that reaction time was sensitive to the amount of advance information presented in the precue. For reaction time manual asymmetries were observed in one condition only – a right hand advantage was present in the No precue condition. In contrast manual asymmetries in favor of the right hand were clearly observed with the movement time results. Experiment 2 was the first experiment reported in the literature to systematically examine reaction time for reaching and grasping movements to tools. In order to further explore these results, in Experiment 3 a fourth precue condition (in which the hand to be used was cued in advance; the Hand precue) was added to the precue paradigm used in Experiment 2. An additional variable called replacement time, which represented the time spent interacting with the tool, was also examined. Forty-two right-handed university students participated in Experiment 3. The results of Experiment 3 largely replicated the findings of Experiment 2, and indicated that both the amount and type of precue information had an effect on reaction time. The addition of the Hand precue condition suggested that having advance knowledge of the hand to be used to perform the task was of greater importance for movement planning than was advance knowledge of the task to be performed. Regarding the movement time results, Experiment 3 was one of the first experiments to show the influence of task demands on the magnitude of manual asymmetries. The lack of differences between the hands for the replacement time results also suggested that the initial execution of the movement (represented by movement time) was most sensitive to manual asymmetries. Overall, these experiments provided further insight into manual asymmetries for the performance of reaching movements, and illustrated how simple manipulations of task demands led to differences between the hands in measures of both preference and performance when interacting with tools.

In this dissertation, three experiments were conducted that examined the influence of task demands on manual asymmetries for the performance of reaching movements to tools. In all three experiments, the difference between the hands (in terms of preference for Experiment 1 and performance for Experiments 2 and 3) was studied in response to varying task demands for grasping movements to tools. In the first experiment, 82 right-handed and 60 left-handed university students performed reaching movements to tools and dowels at five positions within working space. Differences in the reaching patterns of the left and right hands to the tools and dowels were examined, as well as the effect of task demands (lift, use) and type of object (tool, dowel) on the reaching patterns. Dowels were used in order to examine if participants would treat a neutral object as if it were a tool in terms of their reaching patterns in working space. Results confirmed and extended prior research on the influence of task demands on reaching patterns within working space. Overall, there were more similarities in the general reaching patterns of left- and right-handed participants than differences. However key differences between the handedness groups emerged in the treatment of the dowel and the frequency of switches (reaching to lift the object with the non-preferred hand and transferring it to the preferred hand to use). Results also showed that tools enjoy a privileged association with the preferred hand, and that the intent of the movement has a very real goal on movement planning. The first experiment examined patterns of hand use across working space in response to differing task demands. In the next experiments performance differences between the hands in terms of movement planning and initiation were examined through the use of reaction time and movement time. In these experiments, reaction time represented the time from the presentation of a go signal to when the participant first lifted their hand, and movement time was the time between lifting the hand to lifting a tool off a sensor. Movement time represented the time to pick up the tool, and did not include the time to use the tool to perform a particular task and complete the reaching movement. In the second experiment, reaction time and movement time to tools placed at the midline position were examined under varying degrees of advance information using a precue paradigm. Three precue conditions were used which presented advance information on the hand to use to perform the movement (left or right) and/or the task (lift, use, or pantomime) to be performed: (1) both hand and task were cued in advance (Both precue); (2) task only was cued in advance (Task precue); and (3) neither hand nor task were cued in advance (No precue). Twenty-four right-handed university students performed reaching movements to tools under the three different precue conditions. The results of Experiment 2 showed that reaction time was sensitive to the amount of advance information presented in the precue. For reaction time manual asymmetries were observed in one condition only – a right hand advantage was present in the No precue condition. In contrast manual asymmetries in favor of the right hand were clearly observed with the movement time results. Experiment 2 was the first experiment reported in the literature to systematically examine reaction time for reaching and grasping movements to tools. In order to further explore these results, in Experiment 3 a fourth precue condition (in which the hand to be used was cued in advance; the Hand precue) was added to the precue paradigm used in Experiment 2. An additional variable called replacement time, which represented the time spent interacting with the tool, was also examined. Forty-two right-handed university students participated in Experiment 3. The results of Experiment 3 largely replicated the findings of Experiment 2, and indicated that both the amount and type of precue information had an effect on reaction time. The addition of the Hand precue condition suggested that having advance knowledge of the hand to be used to perform the task was of greater importance for movement planning than was advance knowledge of the task to be performed. Regarding the movement time results, Experiment 3 was one of the first experiments to show the influence of task demands on the magnitude of manual asymmetries. The lack of differences between the hands for the replacement time results also suggested that the initial execution of the movement (represented by movement time) was most sensitive to manual asymmetries. Overall, these experiments provided further insight into manual asymmetries for the performance of reaching movements, and illustrated how simple manipulations of task demands led to differences between the hands in measures of both preference and performance when interacting with tools.