"Ball Bouncing" Project (2003 – Present)

Acronym:  "Ball Bouncing"

Name: Learning to bounce a ball in a time-delayed virtual environment

Type: Fundamental

Funds: Doctoral Fellowship (Bourse doctorale, Ministère de l'Education Nationale de la Recherche et de Technologie)

key researchers: Antoine MORICE, Isabelle SIEGLER (Université Paris-Sud 11, Orsay, France), Benoit G. BARDY (Université Montpellier-1, Montpellier, France)

Collaborators: William H. Warren (University of Connecticut, providence, USA)


The project :

The task of rhythmically bouncing a ball on a racket provides a deceptively simple but conceptually rich model system that incorporates mechanical, and informational constraints, allowing us to investigate the dynamics of perception and action. Ball bouncing provides a case study for the general problem of how people learn stable behavioral solutions to everyday tasks as they interact with the physical environment, from manipulating tools and other objects to learning skills such as skiing or cycling. Within this framework we can address such questions as to what properties define a behavioral attractor, how agents capitalize on the physics of the world to organize behavior, whether behavior is passively stable or actively controlled, and how information is exploited in the process.

Theory and current research:

I seek to understand how humans interacting with a physical system discover a new attractor and use it to stabilize their behavior.

Ball bouncing layout

 The Ball Bouncing task layout. The upper right panel depict the experimental setup. Participant hold a physical tennis table racket and have to control the displacement left panel depict thof a virtual racket on the screen in order to perform regular bounce of a virtual ball. The upper left panel depict the content of the virtual scene. The virtual racket had to propel a virtual ball at a target height. The upper left pannel shows the dynamics of the virtual racket and ball positions signals over time. The target error is comptuted at each bounce. The lower right panel depict the first return map of the bouncing task at each trial, indicating how participant exploit the different active (light gray square) and passive dynamical passive regime (dark gray square) of the bouncing task (Schaal et al., 1996).

Past Experiments

Experiment #1 : Measuring delays and evaluating its consequences for human bouncing a ball in time-delayed virtual environemnts

How can we evaluate the spatio-temporal performance of virtual environments (VE) for research use? Here we show that end-to-end latency (ETEL) of VE can strongly damage users’ perceptual and perceptuo-motor behaviors and that it can be considered to be the key factor for evaluating face and functional fidelity of a VE. We used a virtual ball-bouncing task as a paradigmatic example. Ball bouncing is known to exhibit attractive and repelling states whose localization in the racket cycle is sufficiently thin to be changed by small variations of ETEL. We first present a simple test-bed to measure the intrinsic ETEL of research-related VE systems. We then report results of a psychophysical ball-bouncing experiment in which ETEL was manipulated. While face validity (i.e., subjective experience) was maintained with relatively high values, the results reveal that the perception-action behavior (performance) was damaged with smaller ETEL values. These results call for action-perception variables in order to test the fidelity of VE systems.



Experiment #2 :Dynamics of learning in time-delayed virtual environements

How do humans discover stable solutions to perceptual-motor tasks as they interact with the physical environment? We investigate this question using the task of rhythmically bouncing a ball on a racket, for which a passively stable solution is defined. Previously, it was shown that participants exploit this passive stability but can also actively stabilize bouncing under perceptual control. Using a virtual ball-bouncing display, we created new behavioral solutions for rhythmic bouncing by introducing a temporal delay (45˚ to 180˚) between the motion of the physical racket and that of the virtual racket. We then studied how participants searched for and realized a new solution. In all delay conditions, participants learned to maintain bouncing just outside the passively stable region, indicating a role for active stabilization. They recovered the approximate initial phase of ball impact in the virtual racket cycle (half-way through the upswing) by adjusting the impact phase with the physical racket. With short delays (45˚, 90˚), the impact phase quickly shifted later in the physical racket upswing. With long delays (135˚, 180˚), bouncing was destabilized and phase was widely visited before a new preferred phase gradually emerged, during the physical downswing. Destabilization was likely due to the loss of spatial symmetry between the ball and physical racket motion at impact. The results suggest that new behavioral solutions may be discovered and stabilized through broad irregular sampling of variable space rather than through a systematic search.


Key references (downloadable version in page Publications)

  1. Morice, A.H.P., Siegler I.A, Bardy, B.G. (2008) Action-perception patterns in virtual ball-bouncing: Combating system latency and tracking functional validity. Journal of Neuroscience Methods , 169, 255-266.
  2. Morice, A.H.P., Siegler I., Warren W., Bardy B. (2007) Learning new perception-action solutions in virtual ball bouncing. Experimental Brain Research, 181, 249-265.


"Ball Interception" Project (2007– present)

Acronym:  "Ball Interception"

Name: Modelling intercepting actions with control laws

Type: Fundamental

Funds: Doctoral Fellowship (Bourse de Doctorat pour Ingénieur du CNRS)

key researchers: Antoine MORICE (Aix-Marseille Université), Mathieu FRANCOIS, Gilles MONTAGNE (Aix-Marseille Université)

Collaborators: David M. JACOBS (Universidad Auonoma de Madrid, Spain), Reinoud BOOTSMA (Aix-Marseille Université), Jean BLOUIN (LNC, Marseille)


The project :

Interceptive tasks have deserved a special interest in my research, not only because many daily activities rely on the ability to intercept and/or to avoid moving objects (in sport, in driving, or while walking in a crowded street), but also because they can provide insights about the central control of actions characterized by severe spatial-temporal constraints. The theoretical core of the "interception" project aims thus at identifying general principles and informations used by agent to intercept targets.

Theory :

The perceptual-motor dialogue between the perceptual flow produced by displacements so as to produce online locomotor adjustments can be formalized through task-specific laws of control linking a movement parameter to a perceptual information (Warren, 1988, 2006). The underlying idea of such laws, which express the circularity of the relations between information and movement, is that some invariant properties in the perceptual flow specify the current state of the relationship linking an agent to his/her environment. Following this logic, several specific laws of control have been shown to account for the regulation behavior of participants performing interceptive tasks (Francois et al. ,2001; Morice et al., 2010; Bastin, 2008).

The first strategy that could be used for controlling self-displacements during interceptive tasks is known as the constant bearing angle (CBA) strategy. The CBA links the subjects’ acceleration to the rate of change in bearing angle (i.e., the angle subtended by the current position of the target and the direction of the subjects’ motion). Using the CBA strategy, the moving object will be intercepted if the observer cancels any change in the bearing angle by accelerating or decelerating accordingly.

CBA layout

The ball interception layout according to the Constant Bearing Angle Model (CBA). The upper left panel simulate the content of the visual scene experienced by participants. The upper left panel depict the overal set up. Participant walk on a treadmill that send on-line the current velocity of participants used by the host computer to render the visual scene through videoprojection. The lower left panel depict the time change of the relevent information (rate of change of the bearing angle). The lower right panel shows numerical simulation of the participant velocity provided by the CBA.



The second strategy that couyld be used for controlling self-displacements during interceptive tasks is known as the Required Velocity model (RV).

Setup :

We use a virtual reality set-up that can be customized with different effector (e.g., treadmill, digital/analog joystick) that send in real-time to a host computer acceleration or velocity signals used by the virtual engine to render a virtual scene onto a 2.3 m high x 3 m wide projection screen by a videoprojector. Different virtual scene can be setup, depending on the information support provided to agents to intercept balls.

Past Experiments :

Experiment #1 : Role of ball expansion for locomotor interception

The constant bearing angle (CBA) strategy is a prospective strategy that permits the interception of moving objects. The purpose of the present study is to test this strategy. Participants were asked to walk through a virtual environment and to change, if necessary, their walking speed so as to intercept approaching targets. The targets followed either a rectilinear or a curvilinear trajectory and target size was manipulated both within trials (target size was gradually changed during the trial in order to falsify expansion) and between trials (targets of different sizes were used). The curvature manipulation had a large effect on the kinematics of walking, which is in agreement with the CBA strategy. The target size manipulations also affected the kinematics of walking. Although these effects of target size are not predicted by the CBA strategy, quantitative comparisons of observed kinematics and the kinematics predicted by the CBA strategy showed good fits. Furthermore, predictions based on the CBA strategy were deemed superior to predictions based on a required velocity (VREQ) model. The role of target size and expansion in the prospective control of walking is discussed.




CBA vs RV model


Experiment #2 : Role of visual content of the environment during interception by walking

This study concerns the process by which agents select control laws. Participants adjusted their walking speed in a virtual environment in order to intercept approaching targets. Successful interception can be achieved with a constant bearing angle (CBA) strategy, which relies on prospective information, or with a modified required velocity (MRV) strategy, which also includes predictive information. We manipulated the curvature of the target paths and the display condition of these paths. The curvature manipulation had large effects on the walking kinematics when the target paths were not displayed (informationally poor display). In contrast, the walking kinematics were less affected by the curvature manipulation when the target paths were displayed (informationally rich display). This indicates that participants used an MRV strategy in the informationally rich display and a CBA strategy in the informationally poor display. Quantitative fits of the respective models confirm this information-driven switch between the use of a strategy that relies on prospective information and a strategy that includes predictive information. We conclude that agents are able of taking advantage of available information by selecting a suitable control law.

Experiment #3 : Influence of age in interceptive actions

In this experiment, we look at the use of sensory information in young and middle-aged participants using a locomotor-driven interceptive task. Both groups of participants were asked to produce forward displacements by manipulating a joystick and to regulate, if necessary, their displacement velocity so as to intercept approaching targets. We manipulated the richness of the visual environment so as to manipulate the sensory information available to regulate the displacement. We show that the displacements produced by the middle-aged participants were more nonlinear in comparison with young participants. The errors in the middle-aged group can be accounted for by a constant bearing angle (CBA) model that incorporates a decrease in the sensitivity of sensory detection with advancing age. The implications of this study to a better understanding of the mechanisms underlying the detection of the rate of change in bearing angle are discussed

ball Interception Age-related performances Bounded CBA model



Experiment #4 : Role of velocity perception for locomotor interception

While it has been shown that the Global Optic Flow Rate (GOFR) is used in the control of self-motion speed, this study examined its relevance in the control of interceptive actions while walking. We asked participants to intercept approaching targets by adjusting their walking speed in a virtual environment, and predicted that the influence of the GOFR depended on their interception strategy. Indeed, unlike the Constant Bearing Angle (CBA), the Modified Required Velocity (MRV) strategy relies on the perception of self-displacement speed. On the other hand, the CBA strategy involves specific speed adjustments depending on the curvature of the target's trajectory, whereas the MRV does not. We hypothesized that one strategy is selected among the two depending on the informational content of the environment. We thus manipulated the curvature and display of the target's trajectory, and the  relationship  between  physical  walking  speed  and  the  GOFR  (through  eye  height  manipulations).  Our  results  showed  that  when  the  target  trajectory  was  not  displayed,  walking  speed  profiles  were  affected  by  curvature manipulations. Otherwise, walking speed profiles were less affected by curvature manipulations and were affected by the GOFR manipulations. Taken together, these results show that the use of the GOFR for intercepting a moving target while walking depends on the informational content of the environment. Finally we discuss the complementary roles of these two perceptual-motor strategies.


Key references (downloadable version in page Publications)

  1. Morice, A.H.P.,Wallet, G., Montagne, G. (2014) Is perception of self-motion speed a necessary condition for intercepting a moving target on foot ? Neuroscience Letters. 566, 315-319, doi: 10.1016/j.neulet.2014.02.030
  2. Francois, M., Morice, A.H.P., Bootsma, R.J., & Montagne, G. (2011). Visual control of walking velocity.Neuroscience Research, 70, 214-219
  3. Francois, M., Morice, A.H.P., Blouin, J., & Montagne, G. (2011). Age-related decline in sensory processing for locomotion and interception.Neuroscience. 172, 366-378
  4. Morice, A.H.P.,Francois, M., Jacobs, D.M., & Montagne, G. (2010). Environmental constraints modify the way an interceptive action is controlled. Experimental Brain Research.,202:2,397-411
  5. Bastin, J., Jacobs, D.M., Morice, A.H.P., Craig, C., & Montagne, G. (2008). The role of expansion on the control of interceptive action. Experimental Brain Research, 191, 301-312.

Key references :