Abstract
Previous research has shown that Parkinson’s disease (PD) patients can increase the speed of their movement when catching a moving ball compared to when reaching for a static ball (Majsak et al., 1998). A recent model proposed by Redgrave et al. (2010) explains this phenomenon with regards to the dichotomic organization of motor loops in the basal ganglia circuitry and the role of sensory micro-circuitries in the control of goal-directed actions.
According to this model, external visual information that is relevant to the required movement can induce a switch from a habitual control of movement towards an externally-paced, goal- directed form of guidance, resulting in augmented motor performance (Bieńkiewicz et al., 2013). In the current study, we investigated whether continuous acoustic information generated by an object in motion can enhance motor performance in an arm reaching task in a similar way to that observed in the studies of Majsak et al. (1998, 2008). In addition, we explored whether the kinematic aspects of the movement are regulated in accordance with time to arrival information generated by the ball’s motion as it reaches the catching zone. A group of 7 idiopathic PD (6 male, 1 female) patients performed a ball catching task where the acceleration (and hence ball velocity) was manipulated by adjusting the angle of the ramp.
The type of sensory information (visual and/or auditory) specifying the ball’s arrival at the
catching zone was also manipulated. Our results showed that patients with PD demonstrate
improved motor performance when reaching for a ball in motion, compared to when
stationary. We observed how PD patients can adjust their movement kinematics in accordance
with the speed of a moving target, even if vision of the target is occluded and patients have to
rely solely on auditory information. We demonstrate that the availability of dynamic temporal
information is crucial for eliciting motor improvements in PD. Furthermore, these effects
appear independent from the sensory modality through-which the information is conveyed.
Balls to the wall: How acoustic information from a ball in motion guides interceptive movement in people with Parkinson’s disease.
Marta M. N. Bieńkiewicz
a, William R. Young
b, and Cathy M. Craig
ca
Lehrstuhl für Bewegungswissenschaft, Technische Universität München, Georg-Brauchle- Ring 60-62, München, Deutschland
b
Centre for Sports Medicine and Human Performance, Brunel University, UB83PH, UK
c
School of Psychology, Queen’s University Belfast, Belfast, UK
Correspondence concerning this paper should be addressed to Marta M. Bieńkiewicz, Lehrstuhl für Bewegungswissenschaft, Technische Universität München, Georg-Brauchle- Ring 60-62, München, Deutschland
E-mail:
marta.bienkiewicz@tum.deTelephone: +49 (0) 89 289 24 510
Keywords: Parkinson's disease; paradoxical kinesia; ball catching; time to contact;
ecological sound.
Acknowledgments
The authors would like to thank: Ms. Sarah Mason and Dr. David Craig from Belfast City
Hospital for providing medical assessment of the patients. This research was funded by the
European Research Council TEMPUS_G project (210007 StIG).
1.1 Introduction.
One of the hallmarks of Parkinson’s disease (PD) is a global deterioration in motor function
that predominantly affects movement speed (bradykinesia). Patients progressively lose their
natural pace and smoothness of movements, leading to global slowness and a decreased range
of motion (hypokinesia) (Parkinson, 2002). In 1998, Majsak et al. showed that kinematic
parameters of movement were enhanced in PD patients when reaching for a ball in motion
(rolling down a ramp) compared to conditions where they reached as fast as they could for a
motionless ball at the same reaching distance. This phenomenon, commonly referred to as
paradoxical kinesia, defines the ability of PD patients to move as fast as age matched controls
under specific circumstances (Asmus et al., 2008). There are several anecdotal and scientific
accounts of paradoxical kinesia in PD patients when performing various goal-directed acts
that recognize the contribution of visual and proprioceptive information in enhancing
movement performance. For example, a study by Snijders, & Bloem (2010) showed that a
patient was able to freely ride a bicycle, despite being affected by severe symptoms of
bradykinesia which caused falls, motor blocks and festination during self-paced gait. In this
case study, the preserved ability to cycle was attributed to the extrinsic pacing cue imposed by
rotating pedals (Snijders, & Bloem, 2010). Other examples include that of a patient at an
advanced stage of the disease that was able to overcome freezing and shuffling gait by kicking
a ball attached to a string (Asmus et al., 2008) and even of a patient being able to run to save
his grandson from an approaching car (Daroff, 2008). Whilst all of these examples are
pertinent, none of them recognise the contribution of continuous acoustic information in
inducing paradoxical kinesia. A recent study by Young et al. (2014) identified improvement
in gait function in PD subjects when cued with environmental sounds representing a stepping
action. However, this study showed how cues can serve to promote changes in movement
amplitude, rather than increased movement speed. Previous studies have investigated the use
of intermittent auditory cues, demarcating temporal goals for movement based on an isochronous metronome. Both gait parameters, turning ability and upper limb movements were enhanced when paced with an intermittent beat (Suteerawattananon et al. 2004; Wegen et al,. 2006; Willems et al., 2007; Vercruysse et al., 2012).
A seminal proposal by Redgrave et al. (2010), based on rodent models of PD, shed new light on understanding PD symptoms and the role of sensory guidance in ‘overcoming’
bradykinesia. Redgrave et al. (2010) has posited a dichotomy in neural organisation of sub- cortical motor pathways. In this seminal model it is suggested that the depletion of dopamine in PD primarily affects the habitual system of control, but initially spares the goal-directed circuitries. In the healthy brain, habitual motor loops are responsible for facilitation of well- learnt movements and endogenous pacing of actions (direct striatonigral pathway) (Torres et al., 2011). Habitual actions often put low load on the conscious level of control – like walking, driving a car or making a cup of tea in the morning. Positron emission tomography (Morrish et al., 1995) and post-mortem studies (Kish et al., 1988) suggest that major dopamine loss in PD takes place in the heart of the habitual circuitry – the caudal putamen.
The erratic excitatory output from this striatonigral pathway leads to behaviourally observable
PD symptoms by creating noise in the whole motor circuitry. The goal-directed motor loops,
which are intertwined with sensory, cortical and limbic inputs can, in specific conditions,
overtake the functionality of habitual movement control. The presence of movement relevant
sensory input attenuates the erratic oscillations from the habitual loop resulting in an
enhancement in global motor control (Redgrave et al., 2010). The goal-directed circuitry is
based on more indirect connections (relays to the external globus pallidus and the subthalamic
nucleus) and consumes our attention during conscious and deliberate monitoring of motor
actions. The model assumes that environmental sensory information can switch motor control
pathways from intrinsic to extrinsic and allow patients to co-ordinate movements with respect
to an external cue (e.g. an object in motion). A preserved ability to perform externally driven movements in PD subjects was also posited by Torres et al. (2011). Furthermore, a recent study by Bieńkiewicz et al. (2013) demonstrated that the key to understanding how the external information translates into motor improvement lies in the coupling between perceptual information and the ensuing action. PD patients were asked to manually follow a LED light display conveying the spatio-temporal pattern of the movement of a healthy young adult. They were able to adjust the speed of their movement to match the dynamics of the visual information displayed via a single point travelling light. As such, in circumstances where PD patients observe visual information that specifies kinematic properties that exceed their own self-paced capabilities, they are still able to follow the external cue, resulting in an enhanced motor output. The remaining question is whether other sensory modalities, such as audition, are sufficient to drive the goal-directed motor pathways in PD allowing for the adaptation of movement.
Although vision is the most intuitive sensory modality that allows us to interact with the environment and regulate our movements, perception research suggests that visual, auditory and haptic information are argued to be partially interchangeable in terms of their contribution to motor planning or perception of spatiotemporal events (Goodale, & Humphrey, 1998;
Zahariev, & MacKenzie, 2007). For instance, it has been shown that healthy adults are capable of identifying both the size and shape of an object dropped on a surface by using only auditory feedback of the event and in the absence of any additional visual information or previous knowledge about the object (Lakatos et al., 1997; Grassi, 2005; Houben et al., 2005).
In a similar study, young healthy adults were able to adjust their grip aperture to the size of an
object, solely on the basis of the sound it produced when dropped on the table (Sedda et al.,
2011). Indeed, authors demonstrated that, in this context, the weight of auditory information
in motor planning is almost equal to that of the visual channel (0.46 to 0.54 respectively,
Sedda et al. 2011). Olfaction can also contribute to appropriate adaptations in the size of grip aperture – for instance the smell of a particular fruit can regulate prehension in the absence of any visual information (Tubaldi et al., 2008). This cross modality of the perceptual guidance of action enables our motor system to steer the interaction with the environment and fine-tune our movements.
In 1966, JJ Gibson proposed that the environment is built of structured arrays of sensory information that we can perceive. When gauging our own spatial position relative to that of a moving target we use the changing sensory array to inform us about the arrival time, or time- to-contact (TTC) (Lee, 1998). For instance, as an object approaches an observer the manner in which the gap between the object and the observer changes over time will inform the observer about the time to arrival at a given location. This type of information in both the visual and auditory domains is often termed ‘looming’. Natural sounds often contain looming information – such as the sound made when filling a glass of water. In a vessel-filling experiment Cabe and Pittenger (2000) demonstrated how healthy adults and people who are visually impaired can, in the absence of any visual information, use changes in the acoustic array to judge the time when the vessel would be filled. The sound frequencies created by the splashing of water as the vessel fills and the distance between the fill level and the vessel opening was shown to generate a robust continuous array of information than can be used by humans to make perceptual judgements and adapt their movement.
The ability to use visual information to guide both spatial and temporal components of
movement appears to be preserved in PD despite global motor dysfunction (Bienkiewicz et
al., 2013). By examining whether sensory modalities other than vision can be used to induce
paradoxical kinesia in people suffering from PD, new insights for developing novel
rehabilitation approaches can be established. To take this approach further, we adapted the
ball rolling task described by Majsak et al. (1998). In our task, we asked participants to time
the movement of their hand to stop the ball in the catching zone as the ball arrived. In this experiment we wanted to explore whether there is an improvement in motor control in individuals with PD when catching a ball they could either see or hear rolling down the ramp.
By employing a kinematic analysis of the movement we wanted to see how the information (auditory or visual) specifying the motion of a rolling ball influenced the way the participants moved to intercept the ball (interception conditions) and compare this to when they reached for a static ball placed at the same distance (self-paced condition). Furthermore, we investigated how the ball speed influenced movement regulation by measuring success rates, peak velocities, movement symmetry (normalised time to reach peak velocity) and initiation times for each sensory condition (auditory vs. visual) and for each sensory condition compared to the self-paced condition. We predict that participants will be able to modulate their movements in accordance with changes in TTC information, irrespective of sensory modality, and move faster as required in the interception conditions to stop the moving ball compared to the self-paced conditions where the ball is stationary.
2 Method
2.1 Participants
Seven right-handed participants with idiopathic PD (6 males, 1 female) participated in the study. All participants had normal or corrected to normal vision and reported no hearing difficulties. Ethical approval for the study was granted by the Office of Research Ethics Committees, Northern Ireland. Written informed consent was obtained from all participants.
2.2 Medical assessment of participants
All participants were tested in the morning or early afternoon depending on their optimal
functioning and mobility levels during the day (ON state). There was no change in their
medication schedule. All procedures were carried out in the Perception and Action Laboratory
at Queen’s University of Belfast. Before the experiment began, the medical condition of each patient was assessed by a qualified PD nurse. The assessment included the Hoehn and Yahr (H&Y) scale (Hoehn & Yahr, 1967), The Unified Parkinson’s Disease Rating Scale (MDS- UPDRS) (Goetz et al, 2007), the Objective Dyskinesia Rating Scale (Goetz et al., 2008) and The Mini-Mental State Examination (MMSE) (Folstein et al., 1995). The severity of PD used in the inferential statistical analysis was based on the H&Y rating. The medical condition of participants is summarised in Table 1. In addition, hand dominance was assessed using the Edinburgh Handedness Inventory (Oldfield, 1971).
<insert Table 1 about here>
2.3 Apparatus
A metal ramp (50cm long x 5 cm wide) was covered with coarse sandpaper (Naylors, grade 3, GB606, 36 grit) with one end attached to a clamp stand and the other end resting on the table top. A 3cm
2target was taped flush with the table surface at a distance of 3cm from the bottom of the ramp. The horizontal plane of the ramp was aligned with the desk edge at a distance of 35 cm (see Fig. 1a).
<insert Figure 1 about here>
The height of the clamp was regulated to create two different ramp height (and ball speed) conditions: 1) low (14cm), and 2) high (21cm). The distances indicate the height of the clamp above the table’s surface and created two ramp angles, giving rise to two conditions of differing ball speed and TTC (see Fig. 1b). The duration of the ball roll was calculated as the difference in time between the initiation of the ball roll and the ball arriving at the target.
We manipulated the sensory information available to the participant so that the
participant could see (vision only), hear (auditory only), or see and hear (vision and auditory)
the ball rolling down the ramp. Two condenser microphones (Rode NT1A) were placed 15cm
above each end of the ramp. Sound was delivered to participants through headphones (Sennheiser, HD 201, specification: 24 Ω, 21 - 18000 Hz, 108 dB). In the vision only condition low-level white noise was played through the headphones to mask the sound of the ball rolling down the ramp. During the audio only trials a white screen was mounted on the desk surface so that the participant could see the target at the end of the ramp, but not the ramp itself nor the experimenter releasing the ball (see Fig. 2).
<insert Figure 2 about here>
Participants wore an open glove with a fitted metal disc attached to prevent participants from grasping the ball. This disc was placed directly under the palm of the hand with its outer rim extended to the proximal interphalangeal joints. Using a disc to ‘trap’ the ball meant that any failure to catch the ball was due to poor spatio-temporal control of the hand movement and not due to a poor grasping action. Three reflective motion capture markers were fixed to the top of the glove worn by participants and positioned on the ulnar and radial sides of the wrist joint, and centrally on the top of the hand. The ball used in the study was a squash ball (40.5 mm diameter) covered in reflective tape. Motion of the ball and hand were recorded using 6 Oqus Qualisys Motion Capture cameras sampling at 200Hz.
Additionally the experiment was recorded with a video camera positioned so as to record both the movement of the ball, the height of the ramp and the participant so that success could be determined for each trial.
Two ramp heights and 3 sensory modality conditions gave rise to 6 sub-conditions.
Each sensory condition comprised of 16 randomised trials (8 trials per each ramp height sub-
condition). In addition to the ball roll conditions, patients were asked to perform 8 trials where
they reached as fast as they could for a static ball placed in the ball arrival target zone,
demanding a reaching action of the same amplitude as that used in the other 6 interceptive sub-conditions. The order of conditions was randomised using a Latin Square design.
2.4 Procedure
Participants were seated comfortably in front of a desk (see Fig. 2). After receiving oral instructions of what was involved in the experiment, the task was clearly demonstrated by the experimenter. Participants were given time to familiarise themselves with the setup and put themselves in a comfortable position. Subjects were instructed to trap the moving or static ball under the disc attached to their hand. Participants were told that in some blocks of trials they would not be able to see the ball, but they would hear the sound of the ball rolling down the ramp. Similarly, in the vision only condition they would not hear the ball, but they would have full vision of the ball and ramp. In some blocks they would both see and hear the ball rolling down the ramp. Participants completed 2 practice trials in each sub-condition at the start of each session.
At the start of each trial every participant was reminded to place their hand at the starting position on the table. To ensure consistency of the ball roll across trials – the researcher released the ball from the same point at the top of the ramp. Participants were asked to trap the ball as it rolled over the target zone. Kinematic data from these trials were analysed and used as to assess movement performance for each participant in each trial.
2.5 Data processing
Kinematic data representing the movement of the hand and ball were filtered using a second order low-pass Butterworth filter at a frequency of 8Hz using a MATLAB script (The Mathworks Inc. 2009) from which velocity and acceleration profiles for each were calculated.
To assess the level of temporal control displayed by participants five different measures were
selected: i) success rate (percentage of successful ball traps), ii) peak velocity of the
participant’s hand movement, iii) temporal error (time difference between the hand’s arrival at the target zone and the ball crossing the target zone), iv) time to peak velocity of the participant’s hand movement following initiation, and v) movement initiation time (time difference between the onset of the ball movement and the movement of participant). In addition we compared movement symmetry between the self-paced trials and sensory guided conditions to investigate the global organisation of the movement.
We classified a trial as successful when participants managed to ‘trap’ and stop the ball under the disc of their glove. For each trial the initiation of hand movement was defined as the first frame when hand velocity exceeded 2% of peak hand velocity (y axis). The termination of hand movement was defined as the first frame when hand velocity fell below this 2% threshold. Likewise, the initiation of the ball roll was also defined as the first frame where the ball velocity superseded 2% of its peak velocity (z axis) for that trial. For statistical analysis, mean values for each of the dependent variables were calculated for each of the experimental sub-conditions, for all trials regardless of the success in intercepting the ball. All data were included in the data set. To further explore the interaction between the temporal information generated by the ball’s motion and the participant’s movement, we took the time of peak velocity of the hand movement and normalised this time point with respect to the overall duration of the hand movement for each trial (ratio of the time point of peak velocity with respect to total hand movement duration). All data were then analysed using a 3 x 2 (sensory conditions x ramp height) Repeated Measures ANOVA and Bonferroni-corrected post hoc comparisons.
2.6 Healthy adults’ validation
The experimental setup was validated on a group of 10 young, right-handed healthy
adults (mean age 24 ± 5.7 years). All participants had normal or corrected to normal vision
and reported no hearing difficulties. The procedure was the same as that described above.
Ethical approval was granted by The Office for Research Ethics Committees Northern Ireland and written consent was obtained from all participants. For the vision condition participants had a high success rate of 98% for the 21 cm ramp height and 100% for the 14 cm ramp height (group mean). In the audio only condition, success rates were still high but lower than the vision only conditions at 72% and 66% for the 21cm and 14cm ramp heights respectively.
There was a significant main effect of sensory modality on the percentage of successful interceptions (F(2,18) = 51.256, p<0.001). Post hoc comparisons showed that the percentage of successful catches was significantly lower during the audio only trials, compared to vision only. There was no main effect of ramp height (ball speed) on the percentage of interception success. Similarly, there were no main effects of sensory modality on movement duration or peak velocity (Movement Duration: Audio+Vision (M=496 ± 122 ms), Vision (M=488 ± 130 ms), Audio (M= 477 ± 88 ms); Peak Velocity: Audio+Vision (M=1757± 388 mm/s), Vision (M=1866±491 mm/s), Audio (M=1990±464 mm/s)). However, results showed a significant main effect of ramp height on movement duration [(F(2,18) = 24.021, p<0.00; M=453 ± 95ms (14cm); M= 416 ± 77 (21cm)] and peak velocity [(F(2,18) = 24.681, p<0.001; M=1938 ± 462 mm/s (14cm); M= 2232± 479 mm/s (21cm)] with participants moving significantly faster when the time to arrival of the ball was shorter In other words, the two different ramp height conditions generated two different and consistent movement responses in terms of movement speed, with peak velocity being greater for faster ball rolls. This validation experiment showed that healthy young adults adapted their movement kinematics in response to changes in ball motion regardless of whether the information about TTC was visual, auditory, or both.
In addition, we confirmed that healthy adults are able to intercept a moving ball with sound
alone, albeit with significantly reduced success rates compared to conditions where vision was
available. These results from a group of young healthy adults show that interceptive actions
can be adapted in accordance with changes in auditory and/or visual information. Following this validation, the same set-up was used with a group of PD participants whose results are presented in the next section.
3 Results
3.1 Success rates
All of the PD participants, with the exception of one (P7), scored a 100% success rate when trapping the rolling ball in the 14cm ramp height vision and audio condition.
Performance deteriorated slightly for the faster ball roll condition (ramp height 21cm;
M=85%; range 75-100%). Although performance remained equally high for the vision only and the audio only conditions (see Table 2), two of the participants at the most advanced stage of the disease had the lowest success rates for the audio only conditions (0-33%). However, neither the sensory condition nor the H&Y rating score had a significant effect on the success rate in the task (p>0.05). The height of the ramp had a significant main effect on the success rates (Wilk’s Lambda=0.407, F(1,6) = 8.75, p=0.025, η2=0.7). If participants failed to ‘trap’
the ball in all cases it was because they reached the target zone too late (positive temporal error, M=242 ± 0.07 ms). The sensory condition did not have an effect on the magnitude of the temporal error (p>0.05). Table 2 presents a summary of the success rates across participants.
3.2 Initiation time
To understand how participants started adjusting their movement with respect to the
information presented in the environment, we looked at the initiation times of the arm
movement in all six sub conditions (see Fig. 3). In the patient sample we found a significant
main effect of the ramp height on movement initiation times (Wilk’s Lambda=0.138, F(1,6) =
37.42, p=0.001, η2=0.86) with participants moving earlier in the faster ball roll condition (21cm ramp height).
<insert Figure 3 about here>
Interestingly, there was no main effect of sensory condition on the movement initiation times (p>0.05). This suggests that PD participants were able to successfully adapt the movement initiation time to TTC information irrespective of the sensory modality in which the ball rolling event was presented. This interesting finding suggests that paradoxical kinesia can be induced by both visual and auditory information and affect not only the execution part of the movement, but also movement preparation. In other words, the changing pattern of sensory information specifying when a moving object will arrive at a target zone is a critical factor for inducing paradoxical kinesia irrespective of modality.
3.3 Peak velocity
<insert Figure 4 about here>
Figure 4 shows how the means of the peak velocity of the hand movement differ for
the different ramp heights and from the self-paced action condition. An analysis of these
results show a significant main effect of ramp height on peak velocity across all sensory
conditions (F(1,6)=12.57, Wilk’s Lambda=0.32, p=0.012, η2=0.67). As expected,
participants moved faster when the ball rolled down the steeper ramp. Interestingly, there
were no significant differences between the sensory conditions (audio only, vision only, audio
and vision) nor was there any significant interaction between height and sensory condition
(p>0.05).
The second aim was to verify whether coupling movement to the temporal dynamics of an unfolding event (ball roll) would enhance the velocity profile of the movement compared to what was observed when performing a self-paced movement (i.e. reaching for a static ball). The results show that a higher peak velocity for the reaching movement was observed when catching a moving ball than when participants were reaching for a static ball placed at the same reaching distance. As such, participants were able to successfully speed up their movement to successfully perform the task. A paired sample t-test showed that peak velocity of the movement for both ramp height conditions was significantly greater than the self-paced condition (high ramp condition: t(6)=4.14, p=0.006 (M= 1158.2, M= 590.6); low ramp condition (t(6)=3.0, p=0.02 (M=954.4, M= 590.6) (see Figure 5 and Table 3 for an overview).
<insert Figure 5 around here>
In addition, we found no effect of ramp height or sensory condition on the normalised time to reach peak velocity of the movement (p>0.05) or differences with the self-paced movement trials (p>0.05).
4 Discussion of the experimental findings
4.1 Main findings
Using a ball catching paradigm we have demonstrated a preserved ability in PD
patients to successfully intercept a moving object. Results show that in PD patients kinematic
properties of the reaching movement are adapted to the speed of the moving ball (determined
by ramp height). In spite of the reaching distance being kept constant across trials, variables
such as initiation time and peak velocity were significantly modulated as a function of ball
speed across all three sensory conditions. The faster the ball moved, the faster patients
initiated and executed their reaching movements. All participants demonstrated a significant
improvement in movement kinematics when trapping a moving ball (21cm and 14cm ramp height) compared to reaching for a stationary ball. Patients demonstrated a high level of successful interceptions within the 71%-100% range for the vision only and vision and audio conditions. Remarkably, when solely relying on auditory information participants were still able to intercept the ball on approximately 66% of the trials.
4.2 Interpretation of findings
These findings support the results of previous research that has investigated paradoxical kinesia in PD using a ball roll task (Majsak et al., 1998, 2008). Firstly, we have demonstrated that participants are able to successfully intercept the ball if the need for catching and grip control is eliminated. Majsak et al. (2008) proposed that the poor kinematics observed in the reach-to-grasp movement in self-paced action were due to poor prehension.
However this approach does not fully account for the nature of paradoxical kinesia and the global range of actions that are stigmatised with bradykinesia, such as turning or walking that do not require fine-motor control per se. By using a metal disc attached to the hand to trap the ball we observed a preserved ability in PD subjects to intercept the moving object when the prehension component was eliminated. These findings are supported by the results of a similar study by Ballanger et al. (2006). Furthermore, we demonstrate that the temporal dynamics imposed by an unfolding external event play an important role in decreasing levels of bradykinesia and improving motor performance. The temporal constraints of the task (Majsak et al., 2008; Ballanger et al. 2008; 2006) were previously demonstrated to contribute to motor urgency and facilitation of the movement in PD. However, we propose that the
‘coupling’ of the motor action to an ongoing and dynamic sensory event may reflect different
neural and functional processes, such as those proposed by Redgrave et al. (2010). In our
study paradoxical kinesia was induced through the modulation of sensory TTC information
(both visual and auditory) that specifies how the ball is moving with respect to a target. We
propose that it is the patterning of information that specifies the dynamics of the sensory event that is picked up and used by the brain to guide subsequent action in a goal-directed fashion.
In other words, we propose that, whilst motor urgency may be responsible for facilitated motor performance (Ballanger et al., 2006), such improvements in motor output can also be scaled in accordance with changes in ongoing dynamic information, be it auditory, visual, or both (see Fig.4). Similar finding in PD patients was previously reported by Schenk et al.
(2003) in a study linking the improvement of kinematic parameters of reaching movements to the speed of an external moving cue.
There is an interesting distinction to be made between the previous findings demonstrating the facilitating influence of perceived temporal urgency (Ballanger et al., 2006) and the ‘coupling’ of motor output to ongoing dynamic information described in the current results. In the study described by Ballanger and colleagues (2006), the temporal constraints of the task were pre-defined in each trial using an intermittent auditory stimulus. Therefore, these trials incorporated feed-forward aspects of motor planning and execution, as participants used the beeps preceding ball release to plan and initiate the timing of their subsequent action.
However, in the current study participants were unaware of the temporal dynamics of the
imminent task, thus placing an emphasis on online movement control. It would be interesting
to determine if similar benefits to motor performance shown here are also evident in a reactive
task under conditions where continuous sensory information is occluded (i.e., provide a
comparable temporal urgency condition). It is, however, difficult to occlude portions of
continuous sensory information and still specify the temporal constraints of a fast, discrete
and reactive task (such as ours) without providing some prospective information that permits
anticipatory (feed forward) movement control. We suggest that future research should
determine if continuous dynamic information is necessary to drive motor facilitation in PD
independently of the perceived temporal urgency. If this proves difficult to ascertain in
reactive and discrete tasks, it may be more suitable to look at cyclical tasks, such as gait, where one could observe the effects of occluding portions of sensory information on motor output (e.g., look at movement variability) with the assurance that TTC information is directly specified by the task cadence.
A recent study by Young et al., 2014 demonstrated that although temporal urgency imposed by a metronome may produce certain benefits (i.e. reduced temporal variability) during walking in PD patients, it was burdened with higher spatial variability compared to when PD patients used continuous auditory cues such as sonified footsteps of a healthy adult walking on a gravel path. This suggests that continuous dynamic information is required to maximize motor enhancements in PD patients, and that intermittent TTC information may lead to disrupted motor output as it is likely to place additional demands on circuitry associated with habitual control in the basal ganglia (according to the predictions made by Redgrave et al., 2010).
These findings, in conjunction with the current results, support the suggestion that
providing continuous extrinsic, task-relevant information to the goal-directed control system
can serve to exploit elements of the motor control system that are, theoretically, relatively
preserved and effectively bypass the effected areas. On the neurophysiological level this
could be referred to as the moderation of erratic brain oscillations produced by compromised
motor loops (Williams et al., 2003). More specifically, this can be measured as erratic
oscillations in the subthalamic area (Weinberger et al., 2009; Eusebio, & Brown, 2009). Local
Field Potential recordings show that in the subthalamic nucleus in PD there is an irregular
pattern of oscillations at the beta frequency of 13-35 Hz, ranging from the low beta band to
the high beta band (Kühn et al., 2005). Therefore the facilitatory output from habitual loops to
the motor system is too weak and imbalanced with strong inhibitory excitation from the goal-
directed loop. Previous research has demonstrated that beta oscillations in the subthalamic
nucleus can be partially suppressed with the availability of spatial cues (Williams et al., 2003). It was demonstrated that predictive cues that improve reaction time performance in Parkinson’s disease patients are coupled to the suppression of the pathological frequency in the ~20Hz band (the range linked to bradykinesia). The informative load in the cues was found to linearly modulate the level of suppression of erratic oscillation. Therefore, an additional sensory input to the basal ganglia system balances out the erratic signal of the habitual circuitry with enhanced output from the goal-directed system (Redgrave, 2010). In the scenario where temporal urgency is imposed, although not tested in this study, we refer to the study of Ballanger et al. (2008) who showed the critical role of the cerebellum in the facilitation of movement.
It should also be stressed that PD patients might react differently to healthy adults who are exposed to the same continuous temporal stimuli. For instance, attention was also identified as a crucial element for extracting sensory information in PD (Lewis et al., 2000;
Suteerawattananon et al., 2004). In our limited sample, patients at the most advanced stage of
the disease struggled with successful interception in the audio only condition. The severity of
PD in those participants might also result in a difficulty with sustaining attention and
therefore attending to temporal information available from dynamic auditory cues (i.e. the
sonified ball roll motion) or disruptions in sensory processing caused by a dopamine
breakdown in the neural pathways (Mosimann et al., 2004). In addition, velocity perception is
reported to be linked to the computational resources of the cerebellum, as supported by the
many studies using single-unit recordings in monkeys and patients with cerebellar lesions
(Ivry, & Diener, 1991, Ilg, & Thier, 2008). For example, in a study by Suzuki and Keller
(1988), three macaque monkeys were trained to fixate on a LED and track a moving spot with
their head position fixed (smooth eye pursuit). After subtracting the influence of the monkey’s
own head and eye movements, there was a correspondence between the speed of the moving
object and the activation pattern in the cells localised in the cerebellar vermis VI and VII (supplied by the retinal image signal). It has been suggested that the Purkinje cells localised in this area are responsible for coding target velocity moving in the space (Suzuki, & Keller, 1988). Evidence for cerebellar function in velocity perception is complimented by a study by Ivry and Diener (1991) who investigated the ability of patients with cerebellar lesions to discriminate velocity. Twenty patients were recruited with cerebellar damage (due to atrophy, tumour, stroke or autoimmune reaction) that was localised in the hemispheres and posterior vermis. Participants were asked to discriminate (faster/slower) the velocity of the stimuli (moving dot or LEDs) presented in succession. Unlike healthy controls or participants with alcohol dependence (cerebellar controls with lesions in the anterior lobe of the cerebellum) cerebellar patients demonstrated a deficit in velocity discrimination. This inability was isolated from preserved accurate judgements of the position of the stimuli and adequate eye movements. This suggests that the neocerebellum, cerebellar hemispheres and posterior vermis (analogue to the findings in macaques), is involved in velocity perception. Ivry and Diener (1991) speculated that since the cerebellum is well-recognised as the brain’s centre for computation and timing, it certainly is involved in the temporal processing of stimuli.
However, to our knowledge, no evidence exists regarding compromised cerebellar functions in people with Parkinson’s disease.
This study, despite the limited sample of patients, has implications for neuro-
rehabilitation. We propose that the use of continuous displays, based on event-based
feedback, or looming signals is a powerful approach to improving mobility in patients. In
many aspects, such as portability, low-equipment costs, the use of auditory displays might
prove advantageous over the use of visual cues (Rodger et al., 2013; Young et al., 2014). In
light of the findings from Ridgel et al. (2008), increasing the pace of the movement in PD
patients, as a therapeutic intervention might bring potential long-term neuro-protective
benefits. Studies incorporating the use of tandem bicycles have demonstrated that exercising at the forced pace of a healthy adult, can improve the global motor function by 35% as measured by the UPDRS. This effect can be explained by stimulation of dopamine secretion due to the increased pace of the movement. Using auditory displays could impose higher exercise rates; therefore creating a new cueing method that could be useful for the neuro- rehabilitation of PD patients. Acoustic based pacing could also be incorporated into the stationary bike training intervention or treadmill walking to improve global motor function.
4.3 Conclusions
In this study we have demonstrated that the perception of continuous temporal information generated by a naturally occurring event can regulate the execution of movements in PD participants. The degree of enhancement of the motor control was linked to the temporal and spatial dynamic characteristics of the moving ball irrespective of the sensory channel involved. All participants demonstrated an increase in terms of the speed of their movements when catching a moving ball compared to a self-paced reaching movement towards a static ball placed at the same distance. Importantly, we found a preserved ability to successfully intercept the ball. In accordance with model proposed by Redgrave et al. (2010), we suggest that sensory information can modulate the excitatory output to the motor system from basal ganglia pathways, leading to an improvement in the overall control of movement.
This work proposes a new approach for the neuro-rehabilitation of PD, providing a rationale
for using event-based or looming auditory displays to cue movement.
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