does the central nervous system learn to plan bimanual - visual feedback

8/12/2019 Does the Central Nervous System Learn to Plan Bimanual - Visual Feedback

1/16

Does the Central Nervous System learn to plan bimanual

movements based on its expectation of availability

of visual feedback?

Divya Srinivasan a,b,, Bernard J. Martin a

a Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor 48109, Michigan, USAb Centre for Musculo-Skeletal Research, University of Gavle, 80176 Gavle, Sweden

a r t i c l e i n f o

Article history:

Available online 27 June 2012

PsycInfo classification:

2330

Keywords:

Eye-hand coordination

Repetitive bimanual movements

Learning

Gaze strategies

Visual feedback

Left-right asymmetry

a b s t r a c t

The correlation between gaze strategy and kinematics of bimanual

movements was assessed using repetitive bimanual object trans-

fers as an experimental paradigm. The hypothesis was that visual

demand in such tasks is a critical bottleneck in determining biman-

ual coordination. Kinematics and eye movements were compared

before and after practice of this repetitive task. New eye-hand coor-

dination strategies emerged with practice. Also, with practice a sys-

tematic prioritization of the left hand movement to be primary and

the right hand movement to be secondary emerged. This choice

implied that the left hand movement kinematics was similar to that

of the unimanual left hand movements, whereas the performance

of the right hand task was contingent on successful completion of

the primary task. This was revealed by anticipatory adjustments

of the right hand kinematics (right-hand peak velocity ranged from

10070% of the left-hand, and the scaling was dependent on task

conditions and the corresponding eye-hand coordination strategies

used). We used this evidence to argue that the CNS, aware of aninherent asymmetry between the two hand systems, learns to

anticipate the need and availability of visual feedback for successful

task completion, and uses this knowledge to optimize movement

coordination, specifically such that the right-hand control was

modulated to take visual constraints into account.

2012 Elsevier B.V. All rights reserved.

0167-9457/$ - see front matter 2012 Elsevier B.V. All rights reserved.

http://dx.doi.org/10.1016/j.humov.2012.02.011

Corresponding author at: Center for Musculo-Skeletal Research, University of Gavle, 801 76 Gavle, Sweden. Tel.: +46 026 64

8623.

E-mail address: [email protected](D. Srinivasan).

Human Movement Science 31 (2012) 14091424

Contents lists available at SciVerse ScienceDirect

Human Movement Science

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / h u m o v
http://dx.doi.org/10.1016/j.humov.2012.02.011mailto:[email protected]://dx.doi.org/10.1016/j.humov.2012.02.011http://www.sciencedirect.com/science/journal/01679457http://www.elsevier.com/locate/humovhttp://www.elsevier.com/locate/humovhttp://www.sciencedirect.com/science/journal/01679457http://dx.doi.org/10.1016/j.humov.2012.02.011mailto:[email protected]://dx.doi.org/10.1016/j.humov.2012.02.011


2/16


3/16

Since we observed a bias in gaze direction, predominantly towards the left (non-dominant) hand

target in 90% of bimanual movements to symmetric task conditions in an earlier study (Srinivasan

& Martin, 2010), we may assume that there is an asymmetry between the left and right hand systems

in the utilization of feedback information and this difference in the functioning of the two hand sys-

tems may also be a factor affecting the CNSs motor planning process.

A good way to test such a hypothesis would be to elicit multiple task-specific eye movement

behaviors, and observe the acceleration phases of movements in each case to find evidence of differ-

ences in motor planning. If the acceleration phases of movements are the same in all these cases, then

this would imply that motor planning is similar in each case and task-specific differences in coordina-

tion arise only in the motor execution stages.

Contradictory findings in different experimental contexts and thus the difficulty in answering these

questions unequivocally in earlier investigations could largely stem from the fact that in a bimanual

task, the sensorimotor system has to deal with multiple task constraints, both in terms of motor plan-

ning and execution. This implies that the system might need time to learn a good/optimal motor

Fig. 1. Four different gaze strategies as a function of task condition. Black lines indicate left hand movements and white lines

indicate right hand movements; solid lines indicate hand movements performed when gaze is directed to that corresponding

target; dotted lines indicate hand movements performed when gaze is directed to the other target.

D. Srinivasan, B.J. Martin / Human Movement Science 31 (2012) 14091424 1411


4/16

control strategy. Hence, the participants performed the experimental session after a practice session of

100 trials of randomized unimanual and bimanual task conditions. And the coordination strategies

used in the learning phases of behavior, before a stable pattern has been settled upon, were analyzed

using the trials in the practice session.

Did the participants exhibit the advanced patterns of kinematics and eye movements from the very

onset of the tasks, or did they learn these patterns with time in this specific experimental setup? Also,

movement characteristics that have specifically emerged with practice can be reasonably assumed to

present an advantage from the perspective of task performance/cost to the motor-cognitive system. So

studying how patterns of visuomotor coordination in bimanual movements change with practice

might help in further validating the results of the hypothesis tests presented above i.e., whether mo-

tor planning processes in bimanual movements are indeed affected by visual feedback constraints, or

if task specific differences in coordination arise spontaneously during motor execution. This was

tested by comparing the kinematics and eye movement patterns of bimanual trials in the first 30%

of the practice session, with trials in the last 30% of the same practice session and trials in the exper-

imental session.

In a recent study we varied task factors in bimanual reaching tasks and observed the successful

manipulation of gaze strategy as a function of task condition. Participants performed a set of bimanualtasks in which they moved a pair of objects, one with each hand, from their respective initial locations

to corresponding target locations. Object size, target tolerance and inter-target distance were varied.

Four different gaze strategies (terminal, intermittent, predictive and selective) were observed as a

function of task conditions (Srinivasan & Martin, 2010,Fig. 1). The temporal coordination of terminal

phases of hand movements also co-varied with the specific gaze strategy used in each condition. Fur-

ther, the left hand task was systematically prioritized such that gaze was directed to the left target

first, and subsequently the left hand movement was completed first in more than 90% of all the ob-

served bimanual trials.

Part I of the current study analyzes the effects of the elicited gaze strategies on kinematics of both

hand movements in the same set of bimanual trials. In order to understand the relative effects of con-

current task performance and associated sensorimotor control on each hands kinematics, participantsalso performed unimanual trials with their right and left hands to similar target locations. Movement

kinematics of the left and right hands were compared between unimanual and bimanual situations for

similar task conditions. Part II of the study is a comparison of the hand kinematics and eye-movement

behaviors before practice and after practice.

2. Methods

Six right-handed individuals, four male and two female, aged 2030 years, participated in this

experiment as volunteers. All participants were naive to the purpose of the experiment, and had no

prior experience in the specific tasks. They had normal vision and were free from neurological and

musculo-skeletal disorders. The experiment was approved by the Institutional Review Board of the

University of Michigan and all participants signed an informed consent form.

2.1. Experimental setup

The experimental taskconsisted of transferringobjects from specified initial positions to target loca-

tions. Unimanual transfers with the right and left hands, and bimanual transfers of a pair of identical

objects, one in each hand, were performed. For unimanual trials, object size and target tolerance were

chosen as the task variables to be manipulated. Two pairs of light weight cylindrical objects, of height

120 mm, and diameters 8 mm (obj 1) and 44 mm (obj 2) were used in the study. The weights of the ob-

jects were8 g and60 g, respectively.Thetargetdiameterwas definedwithrespecttotheobjectdiameter,using a target tolerance criterion. For each object, the following two target tolerances were defined:

1. Target diameter = object diameter + 0 mm (tol1)

2. Target diameter = object diameter + 45 mm (tol2)

1412 D. Srinivasan, B.J. Martin / Human Movement Science 31 (2012) 14091424


5/16

The object-to-target distance was set at 400 mm for all trials. In bimanual trials, apart from object

size and target tolerance, inter-target distance, defined as the distance between the two closest points

on the target circles, was also varied, and set at either 30 or 200 mm (Fig. 2). The initial object and final

target locations were displayed as images on a 5200 flat-screen TV placed horizontally at elbow height.

Participants were seated in front of the TV such that the screen centerline was aligned with their mid-

sagittal plane. An eight-camera Qualisys motion capture system was used to record kinematic data

sampled at 60 Hz. Eye movements were recorded simultaneously using a head mounted eye tracking

system (ASL Eye Trac 6.0). Equipment calibration and data collection procedures have been described

in detail inSrinivasan and Martin (2010).

2.2. Procedure

In unimanual trials, subjects were instructed to move objects on to specified target locations with

either their right or left hand, depending on the trial type. In bimanual trials, subjects were instructed

to move a pair of objects, one with their left and the other with their right hand, from their respective

initial positions to specified target locations. The left hand always picked the object on the left and

moved it to the left target location, and vice versa for the right, i.e., the task did not require any cross-

ing over of the two hands. No explicit instruction was provided to the participants about the expected

sequence of movements or movement speed (see Srinivasan and Martin (2010)for details).

Each condition was repeated thrice during the experiment trials. All conditions were randomized

and inter-trial intervals lasted approximately 15 s. If the accuracy constraints were not met in any

of the trials, those corresponding trials were repeated at the end of the experiment. For trials in which

the target size was larger than the object size, the objects had to only be placed within the limits of the

target area and did not have to be centered. The participants were not allowed to make corrections

after the object made contact with the surface.

Since pilot studies indicated the development of consistent eye-hand coordination strategies with

learning, experimental data collection was initiated after 100 practice/learning trials. These 100 trials

were composed of a randomized order of bimanual trials and unimanual movements of both the left

and right hands in similar task conditions.

2.3. Data analysis

The three dimensional data from the motion capture system were filtered using a second-order,

low-pass Butterworth filter with a cut-off frequency of 6 Hz. Kinematic data from the markers placedon the wrists were used to calculate the onset and end times of movements. The algorithms for com-

puting movement kinematics and gaze-data parameters are described in Srinivasan and Martin

(2010). In bimanual trials, the hand moving to the target fixated first is defined as the primary hand,

and the other hand is referred to as the secondary hand.

Fig. 2. Experimental setup showing the object and target locations on LCD screen (D denotes inter-target distance, LH and RH

denote the left hand and right hand, respectively).



6/16

2.3.1. Part I Experimental session

As indicated in the Introduction, all subsequent analyses on bimanual movements were performed

only on those trials in which the left hand was the primary hand (90% of all bimanual trials). The time

to peak velocity (Tpv) was computed for each hand movement in unimanual and bimanual trials as

the time from movement onset up to the instant when the magnitude of the wrist tangential velocity

profile (speed) reached the highest peak. Similarly, the magnitude of peak tangential velocity of the

wrist (PV) was also computed for each hand in both unimanual and bimanual situations. Since the left

hand was the primary hand in the bimanual trials, the kinematic parameters of left hand movements

in unimanual and bimanual conditions were compared. Further, since the performance of the second-

ary hand relative to the primary hand was of interest, the ratio of peak velocities of the two hands

(PVsecondary hand/PVprimary hand) was computed and expressed as fractional peak velocity (FPV). The ef-

fect of each task condition and gaze strategy on FPV was analyzed.

2.3.2. Part II Comparison of experimental bimanual trials with practice bimanual trials

The practice session of 100 trials was split into two sections for comparison with the experimental

trials: The first 30% of the practice session (trials 130) and the last 30% of the practice session (trials70100). For each session, the magnitude of peak tangential velocity of the wrist (PV) and the time to

peak velocity (Tpv) for both hands and FPV values were computed in each bimanual trial. The absolute

differences in movement onsets, time-to-peak velocity and movement durations between the left and

right hands (|OLR|, |TPVLR|, |MTLR| respectively), gaze strategies used and task prioritizations into

primary-secondary hand tasks were determined using procedures outlined inSrinivasan and Martin

(2010). The average values of |MTL-R| and FPV were compared between the initial practice session (first

30% of practice trials), the final practice session (last 30% of practice trials) and the experimental

session.

3. Results

3.1. Part I Experimental session

3.1.1. Peak velocity

In both unimanual and bimanual trials, the time to peak velocity was similar for both hands, irre-

spective of differences in task condition, whether right/left hand was used and whether in unimanual

or bimanual condition.

3.1.2. Magnitude of peak velocity

In unimanual movements, neither hand peak velocity (within hand) was significantly influenced by

task conditions (object size, target tolerance); however, the peak velocity of the right hand was signif-icantly greater than that of the left hand (Table 1).Fig. 3shows the average peak velocity of the right

and left hand movements for each subject, collapsed across all task conditions. Fig. 4 shows the typical

peak velocities of the primary (left) and secondary (right) hands of one subject, observed in bimanual

conditions. The peak velocity of the primary (left) hand was not significantly influenced by task con-

ditions (p> .5). However, as seen in Fig. 4, the secondary (right) hand peak velocity varied significantly

with target tolerance and inter-target distance (Table 1).

The average peak velocity of the left hand, collapsed across all task conditions was not significantly

different between unimanual and bimanual situations (p= .37, Students t-test). However, the average

peak velocity of the right hand, collapsed across conditions was significantly lower than in unimanual

movements (p= .003, Studentst-test).

The left hand peak velocity did not vary significantly between the different bimanual trials,whereas the right hands peak velocity varied with task condition. Since the coupling between the

right and left hand peak velocities is of primary interest, this was quantified by FPV. Table 2shows

the classification of eye-hand coordination strategies according to task parameters (Fig. 1), and the

mean values of FPV, grouped according to task condition and eye-hand coordination strategies.



7/16

3.1.3. FPV and gaze strategy

FPV and gaze strategy varied with task difficulty in bimanual tasks. The terminal gaze strategy was

observed mainly when target tolerance was small (rows 13 ofTable 2). In conditions exhibiting this

gaze strategy, gaze transition from the primary to secondary target occurred after completion of theprimary hand movement (Fig. 1). In this case, the right hand peak velocity was lesser than that of

the left hand, as indicated by FPV < 1 in rows (1a), (2b) and (3a) ofTable 2. Even within the terminal

gaze strategy, FPV decreased further with increase in inter-target distance, as indicated by the com-

parison of FPV in rows (1a) and (3a).

Table 1

Repeated Measures ANOVA for effect of task conditions on Hand peak velocity (PV).

(a): In unimanual movement condition:

General linear models (a = .05) PVunimanual

Factor DOF Fstat Pvalue

Object size 1 NS

Target tolerance 1 NS

Hand (Left/Right) 1 13.25


8/16

The intermittent gaze strategy was predominantly observed in cases where the object size was

large, but target tolerance and the inter-target distance were small (second row ofTable 2). In these

conditions, both hand movements terminated simultaneously despite a restrictively small target tol-

erance. This is probably enabled by the multiple gaze transitions that occurred between the primaryand secondary targets during the course of the bimanual movements (Fig. 1). In this case, FPV 1:

both hand movements exhibited similar peak velocities.

The selective and predictive gaze strategies were observed when the target tolerance was large.

While the selective gaze behavior was observed predominantly when the inter-target distance was

small (fourth row of Table 2), predictive gaze behavior was observed when inter-target distance

was large (fifth row ofTable 2). In the selective strategy, both movements were completed while gaze

remained on the primary target, and no gaze transition to secondary target occurred ( Fig. 1). In the

predictive strategy, a gaze transition from the primary to the secondary target occurred, but occurred

before completion of the primary movement (Fig. 1). Both hand movements exhibited similar peak

velocities (FPV 1) in both the selective and predictive strategies.

Although gaze movements, FPV and placement strategy seemed to vary with task condition, com-parison of the (a) and (b) subsections of rows (1) (2) and (3) in Table 2 indicated that while gaze strat-

egy varied significantly with task condition, both placement strategy and FPV co-varied with gaze

strategy rather than with the different task conditions. Gaze strategy had a significant effect on

FPV, F(3, 58.5) = 3.14, p= .03 Welchs ANOVA. Games-Howell post hoc test comparisons indicated

Fig. 4. Typical peak velocities of primary/left (P) and secondary/right (S) hands during different bimanual tasks performed by

one subject.

Table 2

Mean Fractional Peak velocities, classified according to gaze strategy and task condition.

object size

low: 8 mm;

high:

44 mm

target

tolerance

low: 0 mm;

high: 45 mm

inter-target

distance low:

30 mm; high:

200 mm

placement

strategy

gaze

strategy

% of trials in task

condition

exhibiting each

gaze strategy

mean FPV Row

No.

low low low sequential terminal 95.8% 0.81 0.05 1a

simultaneous intermittent 4.2% 0.95 0.02 1b

high low low simultaneous intermittent 82.4% 0.96 0.05 2a

sequential terminal 17.6% 0.8 0.026 2b

low high low low high high sequential terminal 98.6% 0.75 0.041 3a

simultaneous intermittent 1.4% 0.96 0 .024 3b

low high high high low low simultaneous selective 86.8% 0.98 0.021 4a

simultaneous predictive 13.2% 0.97 0.019 4b

low high high high high high simultaneous predictive 96.2% 0.96 0.033 5a

simultaneous intermittent 3.8% 0.97 0 .013 5b



9/16

that the FPV was significantly lower for trials corresponding to terminal gaze strategy than those trials

corresponding to intermittent, predictive and selective gaze strategies (p= .023, .027, .011 respec-

tively), as illustrated inFig. 5. FPV was not significantly different between the intermittent, selective

and predictive gaze strategies (p> .5).

3.2. Part II Comparison of practice bimanual trials with experimental bimanual trials

The initial practice trials (130) were compared with the final practice trials (70100) in terms of

movement kinematics, leftright hand task prioritizations, movement times and gaze strategies.

The final practice session trials were similar to the experimental session in all respects movement

patterns, times, eye movements and coordination strategies.

3.2.1. Initial practice session (practice trials 130).

1. Similar to the later practice and experimental trials, both hand movements were initiated simulta-

neously and reached peak velocity at about the same time, irrespective of task condition. Sample

movement velocity profiles of the two hands in a practice trial in this session are shown in

Fig. 6. |MTLR

| varied significantly with task factors (shown in Fig. 7). The patterns of variation of

|MTLR| with task conditions were also similar to the reported effects in the experimental session

inSrinivasan and Martin (2010).

2. However, only two gaze patterns terminal (in 66% of bimanual trials during initial practice) and

intermittent (in the remaining 34%) were observed. Terminal strategy corresponded to sequential

movement termination and intermittent strategy corresponded to simultaneous movement

termination.

3. Based on the order of gaze fixation and movement termination sequences, the left hand was the

primary hand in61% and the right hand was the primary in 39% of these practice trials. This order

of prioritization between the left and right task executions did not vary in any systematic manner

as a function of task factors.

4. The magnitudes of peak velocity (PV) of neither hand varied with task condition: Although the

choice of the primary task/hand did not vary consistently with task condition or between subjects,

if the right hand target was the first target to be fixated, the PVs of both hands were similar to the

unimanual right hand PV i.e FPV = 1. Similarly, when the left hand was primary, both hand peak

velocities were similar to the left hand unimanual condition with FPV = 1.

Fig. 5. Variation of Fractional Peak Velocity (FPV) with gaze strategy (* indicates significance).



10/16

Fig. 6. Typical tangential velocity profiles of both hands in a bimanual practice trial of type low object size, low target tolerance

and low inter-target distance.

Fig. 7. Gaze strategies, terminal coordination patterns of hand movements, and fractional peak velocities observed in bimanual

tasks in trials 130 of practice session. Bars represent the percentage of trials in each task condition in which a particular gaze

strategy was observed: Term = Terminal, Inter = Intermittent; FPV (d) = (PVsec hand/PVpri hand) and |MTLR| (N) = absolute

difference in movement times between the left and right hand movements.



11/16

5. Fig. 7presents the breakdown of gaze strategy, FPV and |MTLR| according to each task condition.

6. Comparison of the mean FPV and |MTLR| in different task conditions between the experimental

session and the initial practice session indicated that:

a. When target tolerance was high, mean FPV and |MTL-R| were not significantly different between

the initial practice and experimental sessions (p= .17,p = .36,t-test). But different gaze strate-

gies were used for the same task conditions between the two sessions (only intermittent in the

initial practice, but gaze strategies such as predictive and selective were observed in the exper-

imental session).

b. When the target tolerance was low, similar gaze strategies were used in both the initial practice

trials and the experimental trials (terminal and intermittent). However, in those trials in which

the terminal gaze strategy was used, mean FPV was significantly higher in the practice session

than in the experimental session (p= .014, t-test) and |MTLR| was significantly higher in the

practice session than in the experimental session (p= .031, t-test).

3.2.2. Comparison of bimanual movement time (MT) between practice and experimental sessions

Fig. 8shows the mean overall bimanual movement time (and each hand movement time) for trials

associated with theterminal gaze strategy, (i.e., those corresponding to low target tolerance), in initialpractice (trials 130), final practice (trials 70100) and experimental test, respectively:

1. There were no significant differences in either hand movement duration between final practice

(trials 70100) and the experimental session when the terminal gaze strategy was used (see two

left columns inFig. 8,p= .19,t-test).

2. During initial practice (trials 130), the left hand was not systematically chosen as the primary

hand. So the trials were split into two groups (right two columns in Fig. 8), based on which hand

was used as the primary hand, and average MTs of both groups are shown in Fig. 8.

3. Irrespective of which hand was the primary hand, the overall bimanual movement time was sig-

nificantly longer during initial practice than during final practice (p= .015, t-test) or during the

experimental session (p= .008,t-test).

Fig. 8. Bimanual movement times in initial and final practice sessions, compared to experimental session: D Secondary

hand MT = Additional time taken for completion of secondary hand movement, after primary hand movement is completed;

only trials corresponding to low target tolerance and hence terminal gaze strategy, are included in mean MT computations

presented in this figure.



12/16

4. When the left hand was used as the primary hand, primary hand movement time was not different

between any of the sessions compared. However, |MTLR|, i.e., the additional time required by the

right hand to complete the task after the left hand task was completed, was significantly greater in

the initial practice than in the final practice and test trials (p= .017,p = .013, t-test).

5. When the right hand was the primary hand during the initial practice session, although the pri-

mary hand movement time seems shorter than in all the other three cases (Fig. 8), overall bimanual

movement time was the longest.

When target tolerance was high, overall bimanual movement times as well as the temporal phase lag

between the left and right hand movements (|MTL-R|) were not significantly different between any of

the sessions compared, irrespective of what gaze strategy was used.

4. Discussion

Three main results were observed when comparing bimanual trials before and after training:

1. A systematic left-hand task prioritization emerged with training.

2. Two new gaze strategies appeared with training, selective and predictive.

3. A task dependent scaling of the secondary hand peak velocity, and a corresponding shortening of

movement time of the bimanual task were observed.

4.1. Leftright prioritization of bimanual tasks before and after training

When comparing the initial practice trials in which the right hand was primary to the experimental

trials in which the left hand was primary, the following results were noted: Even though the primary

hand movement time was reduced when the right hand was primary than when the left hand was pri-

mary (Fig. 10), the overall bimanual movement time was higher for the right-primary, left-secondarycases when compared to the left-primary, right-secondary cases. This suggests that the left hand per-

forming the secondary task increased the additional time required to perform the secondary task after

the primary task was completed, and the overall bimanual times were higher.

A preference for a left-target fixation in bimanual movements has previously been reported by Riek

et al. (2003)and a consequent reduction in temporal phase lags between the two hand movements

when the left hand target was preferentially foveated has been observed in other studies ( Pellegrini,

Andrade, & Teixeira, 2004; Swinnen, Verschueren, & Dounskaia, 1996). Thus the consistent prioritiza-

tion of the non-dominant hand over the other hand indicates a natural tendency driven by intrinsic

differences between the two hand systems. The systematic emergence of this strategy with practice

indicates that the CNS may be adjusting movement control strategies based on an awareness of this

asymmetry in order to make the best use of it.This implies that, in the context of bimanual tasks, the movement of thenon-dominant hand must be

visually guided while the concurrent movement of the right/dominant hand can be initiated without

the corresponding target being fixated. This may be in agreement with the dynamic dominance hypoth-

esis, which proposes that the left hemisphere is specialized in movement trajectory control while the

right hemisphere is specialized in position control (Sainburg, 2002, 2005); hence visual information

and guidance may be more important for the left than right hand since position control is primarily dri-

ven by feedback while trajectorycontrol is less dependent on continuousfeedback. Alternatively, it may

be related to differences in skill between the left and right hand, i.e., the left hand is more likely to

make errors and thus more control is exerted for that hand (White & Diedrichsen, 2010).

4.2. Gaze strategies

In the initial practice trials, only the terminal and intermittent gaze strategies were observed,

whereas four different gaze strategies terminal, intermittent, predictive and selective were ob-

served in the later experimental trials. With learning, in movements to targets of high tolerance,



13/16

the intermittent gaze strategy was replaced by predictive and selective gaze strategies. This indicates

that the intermittent gaze strategy might be the most preferred, default eye-movement pattern in a

hitherto unknown/new environment, when performing tasks with multiple constraints. In the absence

of knowledge, anticipatory planning and thus programming of movement sequences might be neither

efficient nor accurate; hence, bimanual movements are controlled by an online process using visual

sampling to allow feedback adjustments as illustrated by models concerning tracking performances

based on different control modes as a function of skill (Neilson, Neilson, & ODwyer, 1988).

However, with training, the number of gaze transitions between the two targets required to suc-

cessfully complete both hand-tasks decreased. It has been suggested that the cerebellums capacity

for adaptive learning to new task paradigms or external perturbations in visuomotor tasks might rely

on sensory (i.e., visual) prediction errors, i.e., mismatch between predicted and actual sensory out-

come of motor commands (Tseng, Diedrichsen, Krakauer, Shadmehr, & Bastian, 2007). In the compu-

tational modeling framework, this adaptation is analogous to an adaptation of the internal forward

model controlling the hand movement, which predicts the sensory outcome based on an efference

copy of a motor command (Tseng et al., 2007; Wolpert, Miall, & Kawato, 1998). These hypotheses

may be extended in the current context to suggest that in bimanual movements to targets of high tol-

erance, once both movements are initiated, the CNS learns that after visually guiding the primarymovement for a certain amount of time, the predictions of the internal forward model become reliable

enough to guide the primary hand movement to successful completion. Hence gaze does not shift back

and forth between the two targets (intermittent gaze strategy) after training. The use of a predictive

gaze strategy in which gaze leaves the primary target before completion of the primary hand move-

ment strongly supports this perspective. This pre-emptive transition of gaze to the secondary hand

movement allows both hand movements to be completed synchronously (unlike sequential move-

ment execution in the terminal gaze strategy). Thus a decrease in number of gaze transitions between

targets in the predictive and selective gaze strategies (when compared to the intermittent strategy)

imply that these are sophisticated strategies for acquiring the required visual information for move-

ment completion. These strategies may represent an efficient way of obtaining the required visual

information with lesser cost/effort to the eyes/head system.

4.3. Task-dependent scaling of secondary hand velocity

Post training, gaze strategies varied significantly with task conditions in bimanual tasks and the

correlation between task conditions and gaze strategy was consistent across all subjects. The eye-

movement behavior was found to drive the pattern of temporal coupling between the terminal phases

of the two hand movements (Srinivasan & Martin, 2010). The tabulation of FPV values according to

both task condition and gaze strategy (Table 2) showed that the peak velocity of the secondary hand

varied significantly with gaze strategy.

In those trials exhibiting terminal gaze strategy, movement duration was significantly greater for

the secondary hand than the primary hand (Fig. 1). Correspondingly, FPV was less than 1 in trials usingthe terminal gaze strategy, indicating that the peak velocity was consistently lower for the secondary

than the primary hand. Within the trials exhibiting terminal gaze strategy, the difference in move-

ment duration of the primary and secondary hands increased with increasing inter-target distance.

FPV decreased with increase in inter-target distance. In other words, as the inter-target distance in-

creases, the secondary hands PV is further reduced with respect to the primary hand PV and corre-

spondingly, the secondary hand movement takes longer to terminate after completion of the

primary hand movement. However, in the predictive and selective gaze strategies associated with less

demanding task constraints in terms of target-accuracy, both hand movements terminated simulta-

neously (Fig. 1) and both hands exhibited similar peak velocities.

Hence, the secondary hand peak velocity seems to be anticipatorily scaled based on task diffi-

culty, and more specifically, gaze strategy. Since Tpvs are similar for both hands, a reduced peak veloc-ity implies that the secondary hand covers a shorter distance to target. The object of scaling the

secondary hand movement velocity with respect to the velocity of the primary hand movement might

be to position the secondary hand farther away from its target by the time gaze becomes available for

completion of its terminal phase. This might be a good strategy to execute both hand movements such



14/16


15/16

durations of the self-paced bimanual movements using the terminal gaze strategy, and more efficient

eye-movement patterns in cases in which movement durations were already optimal.

Thus, the task reorganization emerging with practice, with attributes such as prioritizing feedback

resources to guide the non-dominant hand movement, temporally synchronized acceleration phases

of hand movements, anticipatory scaling of peak velocities (leading to reduced number of movement

sub-phases) and reduction in number of gaze transitions, seems to contribute to reducing both move-

ment programming and execution costs.

Previous studies (Jackson et al., 1999; Kelso, Putnam, & Goodman, 1983) have suggested that the

dominant hand may exhibit reduced velocities in order to maintain rigid temporal synchrony of sym-

metric/asymmetric bimanual tasks and have used this result to argue in favor of a functional coupling

between the two limb movements. Our results are in agreement with the hypothesis of a pro-

grammed coupling between the two hand systems allowing both hands to move simultaneously

the high consistency of one hands peak velocity being fixed and FPV varying as a function of task fac-

tors across different subjects suggests that such scaling might be intentionally programmed by the

central nervous system.

The rigid temporal coupling of the acceleration phases suggests that there might be a tendency to

activate homologous groups of muscles with a unique timing control (Kelso et al., 1983; Swinnenet al., 1998). But task-dependent disruption in temporal synchrony in the terminal phases of move-

ments indicates that feedback constraints may be the bottleneck in maintaining the initiated syn-

chrony. The same feedback constraints might also drive the CNS to program movements in such a

way that one task/hand is prioritized prior to movement initiation. After deciding to prioritize one

hand task, the next decision may be to determine the qualitative eye-hand coordination strategy

and the coupling/scaling parameter as a function of the systems expectations of visual feedback (de-

mand/availability).

Thus, while temporal synchronization of kinematic landmarks (movement initiation, instant of

peak velocity) of both movements is initiated by programming simultaneous activation of homolo-

gous groups of muscles, the secondary movement might be modulated in amplitude (muscle activa-

tion strength), depending on expected constraints on visual feedback caused by execution of theprimary movement. Hence, the same program, with the exception of a difference in the velocity

parameter driven by anticipation of the visual constraint, may be executed to control both hands

simultaneously during the acceleration phase.

This hypothesis that bimanual movement characteristics are modified based on the expectations of

visual feedback availability is in accordance withJakobson and Goodale (1991)that kinematic move-

ment variables are affected by visually-based estimates of object size and movement distance.

4.6. Conclusion

The present results show that bimanual movements may be planned based on an expectation of the

availability, and need for, visual feedback in each task. This is accomplished by prioritizing the execu-tion of the left hand movement first, and by controlling the concurrent right hand movement differ-

ently based on task parameters and resultant gaze patterns. The initial absence of this behavior before

practice enabled us to compare movement times and kinematics in movements with and without

these two major characteristics: goal-prioritization and anticipatory scaling of peak velocities. Our re-

sults show that these characteristics result in reduced hand-movement times/phases, and reduced

number of gaze transitions between the two targets, suggesting that such anticipatory adjustments

in motor planning are clearly advantageous for task execution, and that there is an intrinsic tendency

towards optimization without any specific instructions.

4.7. Limitations

Despite these complex visuomotor coordination patterns offering a new and interesting insight

into probable planning and execution processes, these complex patterns of coordination were elicited

after practice sessions in a very specific task design in a controlled laboratory environment. So further

studies are needed to understand how generalizable these findings are, to action-perception coupling,



16/16

in terms of retention and transferability: if and for how long these coordination patterns are retained

and whether they are transferable between different tasks.

Acknowledgments

The authors wish to thank the University of Michigans HUMOSIM consortium for their intellectual

and material support of this research.

References

Balakrishnan, R., & Hinckley, K. (2002).Symmetric bimanual interaction. ACM CHI Conference, CHI Letters, 2, 3340. New York:ACM.

Bingham, G. P., Hughes, K., & Mon-Williams, M. (2008). The coordination patterns observed when two hands reach-to-grasp

separate objects.Experimental Brain Research, 184, 283293.Bruyn, J. L., & Mason, A. H. (2009). Temporal coordination during bimanual reach-to-grasp movements: The role of vision.

Quarterly Journal of Experimental Psychology, 62, 13281342.Cohen, R. G., Biddle, J. C., & Rosenbaum, D. A. (2010). Manual obstacle avoidance takes into account visual uncertainty, motor

noise, and biomechanical costs. Experimental Brain Research, 201(3), 587592.

Diedrichsen, J., Nambisan, R., Kennerley, S. W., & Ivry, R. B. (2004). Independent on-line control of the two hands duringbimanual reaching. European Journal of Neuroscience, 19, 16431652.

Jackson, G. M., Jackson, S. R., & Kritikos, A. (1999). Attention for action: Coordinating bimanual reach-to-grasp movements.

British Journal of Psychology, 90, 247270.Jakobson, L. S., & Goodale, M. A. (1991). Factors affecting higher-order movement planning: A kinematic analysis of human

prehension. Experimental Brain Research, 86, 199208.Kelso, J. A. S., Putnam, C. A., & Goodman, D. (1983). On the space-time structure of human interlimb coordination. Quarterly

Journal of Experimental Psychology: Section A Human Experimental Psychology, 35, 347375.Marteniuk, R. G., MacKenzie, C. L., & Baba, D. M. (1984). Bimanual movement control: Information processing and interaction

effects. Quarterly Journal of Experimental Psychology: Section A Human Experimental Psychology, 36, 335365.Marteniuk, R. G., & MacKenzie, C. L. (1980). A preliminary theory of two-handed coordinated control. In G. E. Stelmach & J.

Requin (Eds.), Tutorials in motor behavior(pp. 185197). Amsterdam: North-Holland.Mason, A. H., & Bruyn, J. L. (2009). Manual asymmetries in bimanual prehension tasks: Manipulation of object size and object

distance. Human Movement Science, 28, 4873.Moisello, C., Crupi, D., Tunik, E., Quartarone, A., Bove, M., Tononi, G., et al (2009). The serial reaction time task revisited: A study

on motor sequence learning with an arm-reaching task. Experimental Brain Research, 194, 143155.Neilson, P. D., Neilson, M. D., & ODwyer, N. J. (1988). Internal models and intermittency: A theoretical account of human

tracking behavior.Biological Cybernetics, 58, 101112.Pellegrini, A. M., Andrade, E. C., & Teixeira, L. A. (2004). Attending to the non-preferred hand improves bimanual coordination in

children. Human Movement Science, 23, 447460.Riek, S., Tresilian, J. R., Mon-Williams, M., Coppard, V. L., & Carson, R. G. (2003). Bimanual aiming and overt attention: One law

for two hands. Experimental Brain Research, 153, 5975.Sainburg, R. L. (2002). Evidence for a dynamic-dominance hypothesis of handedness.Experimental Brain Research, 142, 241258.Sainburg, R. L. (2005). Handedness: Differential specializations for control of trajectory and position. Exercise and Sport Science

Reviews, 33, 206213.Spijkers, W., & Heuer, H. (1995). Structural constraints on the performance of symmetrical bimanual movements with different

amplitudes. Quarterly Journal of Experimental Psychology. Section A, 48, 716740.Spijkers, W., & Heuer, H. (2004). Behavioural principles of interlimb coordination. In S. P. Swinnen & J. Duysens (Eds.), Neuro-

behavioral determinants of interlimb coordination: A multidisciplinary approach (pp. 223258). Boston: Kluwer Academic.

Srinivasan, D., & Martin, B. J. (2010). Eye-hand coordination of symmetric bimanual reaching tasks: Temporal aspects.Experimental Brain Research, 203, 391405.

Swinnen, S. P., Jardin, K., Verschueren, S., Meulenbroek, R., Franz, L., Dounskaia, N., et al (1998). Exploring interlimb constraints

during bimanual graphic performance. effects of muscle grouping and direction. Behavioral and Brain Research, 90, 7987.Swinnen, S. P., Verschueren, S. M. P., & Dounskaia, N. (1996). Is motor pathology associated with setting new CNS priorities or

with increased difficulty in overcoming or suppressing preexisting CNS priorities? Behavioral and Brain Sciences, 19, 8788.Tseng, Y. W., Diedrichsen, J., Krakauer, J. W., Shadmehr, R., & Bastian, A. J. (2007). Sensory prediction errors drive cerebellum-

dependent adaptation of reaching. Journal of Neurophysiology, 98, 5462.White, O., & Diedrichsen, J. (2010). Responsibility assignment in redundant systems. Current Biology, 20, 12901295.Wolpert, D. M., Miall, R. C., & Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Science, 2, 338347.


does the central nervous system learn to plan bimanual - visual feedback

Documents