Fifteen right-handed non-demented patients (10 males) with IPD, aged 49–80 years (M = 67.2, SD = 7.5) participated in the study (see Table 1). Scores of the Unified Parkinson’s Disease Rating Scale (UPDRS) and staging according to Hoehn and Yahr (H&Y) were assessed by an experienced neurologist (H.O.). Patients did not discontinue medication, and the levodopa equivalent daily dose was on average 363 mg. They were clinically assessed at the Clinic for Cognitive Neurology at the University Hospital in Leipzig, Germany. Patients showed moderate symptoms of IPD, with an average H&Y stage of 2 (SD = 0.7) and a UPDRS of 37.7 (SD = 18.8). Inclusion criteria were low scores (<5; M = 1.29) on the Geriatric Depression Scale (Yesavage et al., 1982), absence of a hearing impairment, absence of musical training as assessed by a customized questionnaire for musical aptitudes. Additional neuropsychological testing included the Token-test (De Renzi and Vignolo, 1962), the consortium to establish a registry for Alzheimer’s disease (CERAD) (Welsh et al., 1994) and the Parkinson neuropsychometric dementia assessment (PANDA) (Kalbe et al., 2008). No other severe neurological or psychiatric illness was reported. Twenty (10 males) right-handed healthy adults, who matched the patients in age (M = 66.4, SD = 7.8) and education (M = 14.4 years; SD = 3.0) formed the control group. Healthy controls had no history of neurological or psychiatric disorders, showed no hearing impairments and did not actively practice music. All participants, recruited via the database of the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, gave informed consent and were remunerated for their participation. The study was approved by the Ethics Committee of the University of Leipzig, Germany.

IPD patients took part in an auditory cuing training program. A 2-day assessment of perceptual and movement kinematics was administered before, after, and 1 month following the intervention. Controls were assessed only once. IPD patients were tested while they were in an ON-state. Details about the training program and the evaluation of perceptual and motor timing are provided in detail below.

The training sessions took place at the Day Clinic for Cognitive Neurology at the University of Leipzig. Patients were asked to walk while following a familiar German folk song. No explicit instructions to synchronize their footsteps to the beat of music were provided. The song was played without lyrics and the beat of the song was emphasized with a superimposed salient high-pitch bell sound. The beat rate of the auditory stimulus was set to ±10% of a patient’s spontaneous walking cadence as assessed prior to the first training session. The chosen beat rate [i.e., +10% (n = 8) or −10% (n = 7)] was the one which led to the longest step length as assessed in prior testing (Willems et al., 2006). Patients underwent three training sessions per week for 1 month. Medication was kept constant over the whole course of the study. Stimuli were delivered via a portable MP3-player (Sansa-Clip) and headphones (Sansa-Clip earbuds). Each training session lasted 30 min and consisted of three phases. In the first phase (10 min) the patient walked to the auditory rhythmic stimulus for 8 min. The stimulus was then stopped while the patient continued walking for 2 min at the same speed. In the second phase (10 min), the patient performed stop-and-go trials, in which the auditory stimulus was played for 30 s. At the end of the stimulus presentation, the patient stopped walking and restarted at the onset of the next stimulus presentation. During the last 2 min, the patient repeated the stop-and-go trials without the stimulus. The third phase (10 min) was the same as phase 1.

Patients and controls were submitted to the BAASTA, which consists of a series of perceptual timing and motor timing tasks sketched out below. The test battery was administered over 2 days.

The first three tasks (duration discrimination, anisochrony detection with tones, and anisochrony detection with music) allow estimating thresholds of duration discrimination of two tones and to detect an interval embedded in an isochronous sequence of tones or in a musical excerpt. Thresholds are estimated using a maximum-likelihood adaptive procedure (MLP) (Green, 1993) implemented in the MLP toolbox (Grassi and Soranzo, 2009) in MATLAB. Participants performed 3 blocks of 16 trials each. In each trial, the stimulus difference was changed adaptively depending on the participants’ response. Thresholds corresponded to the midpoint of the psychometric curve defined as a probability of 63.1% of correct detection (Grassi and Soranzo, 2009). Stimuli were delivered via headphones (Sennheiser HD201) at a comfortable sound pressure level. A response was provided verbally by participants and entered by the experimenter via a computer keyboard. The tasks were preceded by four practice trials with feedback.

The goal of this test is to measure the ability to discriminate two subsequent durations. The participants are presented with pairs of pure tones (frequency = 1 kHz; interval between tones = 600 ms). The first tone lasts 600 ms (standard duration) while the second tone (comparison) varies between 600 and 1000 ms. The duration of the second tone is controlled by the MLP algorithm. Participants’ task is to note if the second tone lasts “longer” than the first or has the “same” duration.

This test assesses the sensitivity to time shifts (i.e., anisochrony) in a sequence of isochronous stimuli (Hyde and Peretz, 2003; Sowinski and Dalla Bella, 2013). Participants listen to sequences of five tones (tone frequency = 1047 Hz, duration = 150 ms). Isochronous sequences have a constant inter-onset-interval (IOI) while in non-isochronous sequences the fourth tone occurs earlier than expected based on the IOI of the preceding tones. This displacement results in reciprocal time shifts between tones 3/4 (shortened) and 4/5 (lengthened). The standard IOI is 600 ms. The magnitude of the local shift, up to 30% of the IOI (180 ms), is controlled by the MLP algorithm. After each sequence, participants are asked to judge whether the sequence was “regular” or “irregular.”

The purpose of the third task is to assess participants’ ability to detect a time shift (i.e., deviant beat) in a short musical excerpt (Sowinski and Dalla Bella, 2013). In each trial, a computer-generated musical excerpt is presented to participants. The excerpt is a two-bar fragment (i.e., eight quarter notes overall) taken from Bach’s “Badinerie” orchestral suite for flute BWV 1067, played with a piano timbre at a tempo of 100 beats/min (IOI = 600 ms; beat = quarter note). The IOI between musical beats is not manipulated in a regular sequence, while a local time shift (as in the previous task) is introduced at the onset of the fifth beat in an irregular sequence. The standard IOI between musical beats is 600 ms. The magnitude of the time shift, up to 30% (180 ms) of the IOI between musical beats, is controlled by the MLP algorithm. Participants’ task is to judge whether the sequence was “regular” or “irregular.”

This task examines sensitivity to the beat conveyed by a musical stimulus. The task is an adapted version of the beat alignment task (Iversen and Patel, 2008; Fujii and Schlaug, 2013). Participants are presented with four musical excerpts including a salient beat structure. Two are fragments from Bach’s “Badinerie” and two from Rossini’s “William Tell Overture.” Each excerpt includes 20 beats (beat = quarter note). An isochronous sequence with a triangle timbre is superimposed on the music starting on the seventh beat. The isochronous sequence is either aligned to the musical beat or unaligned. In the latter case either relative phase is changed (with the tones preceding or following the beats by 33% of the IOI between beats, while keeping the same tempo of the musical stimulus), or period (with the tones being presented at a slower or faster rate by 10% of the quarter note duration). The 4 musical excerpts are presented at 3 different tempi (IOIs of 450, 600, and 750 ms, respectively), for a total of 24 beat-aligned trials and 48 beat-unaligned trials (72 trials overall). After each excerpt, participants are asked whether the isochronous sounds are aligned to the musical beat (perception of a regular pulse evoked by music).

Motor timing is assessed by hand tapping (Aschersleben, 2002; Repp, 2005). Participants are instructed to tap as regularly as possible with their right hand either without stimulation (unpaced tapping) or in the presence of a rhythmic auditory stimulus (paced tapping). Tapping is recorded via a Roland SPD-6 MIDI percussion pad controlled by MAX-MSP software (version 5.1). Stimuli are delivered over headphones (Sennheiser HD201) at a comfortable sound pressure level. No auditory feedback is provided during tapping. The tasks are preceded by practice trials.

The aim of this task is to assess the tapping rate and variability in the absence of a pacing stimulus. Participants are instructed to tap regularly at a comfortable rate for 60 s, while maintaining tapping rate as constant as possible. The same task is realized also with the left hand. Unpaced tapping tasks are repeated once more at the end of all the motor timing tasks of the BAASTA.

This task assesses sensorimotor synchronization with isochronous sequences of tones. Participants are instructed to synchronize their taps to an isochronous sequence of 60 piano tones (tone frequency = 1319 Hz). The sequence is presented at three IOIs: 600, 450, and 750 ms. Each tapping trial at a given tempo is repeated twice.

In this task, the ability to synchronize to the beat of a musical stimulus is tested. Participants synchronize their taps to the beat of a well-formed musical excerpt from Bach’s “Badinerie” and from Rossini’s “William Tell Overture” (quarter note IOI = 600 ms), each including 64 beats. The tapping trial for each musical excerpt is repeated twice.

The purpose of this test is to assess motor timing when participants continued tapping at a given rate after prior synchronization with an isochronous sequence (Wing and Kristofferson, 1973a,b; O’Boyle et al., 1996). Participants synchronize to a series of 10 piano tones presented isochronously at 3 tempi (600, 450, or 750 ms) and are instructed to continue tapping at the same rate (continuation phase) for a duration corresponding to 30 IOIs in the absence of a pacing stimulus. The end of the trial is indicated by a low-pitch tone. Each tapping trial at a given tempo is repeated twice.

This final test examines the ability to adapt to tempo change in a synchronization–continuation task, using an adaptive tapping task (Schwartze et al., 2011). Series of 10 tones are presented to participants. The first six tones of the sequences have an IOI of 600 ms, while the remaining four tones either maintain the same IOI or, in 67% of the trials, show a slower tempo (with a final IOI of 630 or 670 ms) or a faster tempo (with a final IOI of 570 or 525 ms). Participants are instructed to synchronize to the initial tempo, to adapt to the tempo change, and to continue tapping at the new tempo after the presentation of the last tone for a duration corresponding to 10 IOIs. At the end of each trial, participants are asked whether they perceived acceleration, deceleration, or no tempo change in the sequence. There are 10 blocks with 6 trials per block (4 with tempo change, 2 without), presented in random order.

Gait kinematics in the absence of auditory cues was assessed with a Vicon MX Motion Capture System during the second day of testing. Sixteen passive reflective markers (14 mm) were attached to participants’ lower body (four on the hip, three on each leg and foot, respectively) in accordance with the Conventional Gait Model (Baker, 2006). Participants were asked to walk for 1 min at their spontaneous walking speed. The trial was repeated twice. The performance was recorded using Vicon Nexus Software.

When walking at comfortable speed in the absence of an external cue, patients showed lower stride length (M = 980.4 mm) as compared to controls (M = 1152.3 mm) (U = 76, p < 0.01). Cueing training increased stride length (M = 1037.0 mm at post-test; W  = −70, p < 0.05) and this benefit was maintained 1 month after the training had ended (M = 1028.9 mm; W  = −78, p < 0.05).

Before submitting data to the following analyses, trials were screened for outliers (e.g., for perceptual tasks, blocks with a higher false alarm rate higher than 30%; for motor tasks, taps with ITI deviating by more than three times the interquartile range from the median). A low number of outliers was found in both patients and controls. Overall in the perceptual tasks, 3.3% of the trials were rejected for patients and 3.8% for controls. In the motor tasks, <1% of taps were discarded for both patients and controls.

The effect of training on perceptual and motor timing abilities was examined for the tasks of the BAASTA where patients showed impaired performance relative to controls pre-training. The mean results obtained in these tasks are shown in Figure 1 (perceptual tasks), and Figure 2 (motor tasks). Patients showed higher thresholds than controls (U = 75.5, p < 0.05) in the duration discrimination task before the training. Patients improved following the training, an effect that was not confirmed post-training but in the follow-up evaluation (W  = 66.0, p < 0.05). One month following the intervention, the difference between patients’ and controls’ discrimination thresholds was no longer significant. Patients displayed worse detection of anisochronies in musical stimuli than controls (U = 87.5, p < 0.05); yet, training did not improve patients’ performance in this task. Finally, in the BAT, patients had more difficulties in detecting misaligned beats before intervention when compared to controls (U = 74.5, p < 0.05). This difference was present for tempi with inter-beat-intervals of 600 and 750 ms (U = 84.5, p < 0.05 and U = 68.0, p < 0.05, respectively). No difference between patients (M = 11.8, SEM = 0.8) and controls (M = 12.9, SEM = 0.9) was found at the fastest tempo (450 ms). The detection of misaligned beats generally improved when tested at follow-up. The difference pre-/post-training just failed to reach significance (W  = −49.0, p = 0.07). This effect of training was mostly driven by patients’ performance at the average tempo (W  = −37.0, p < 0.05). Patients’ performance at the follow-up testing did not significantly differ from that of controls.

In the unpaced tapping tasks patients did not differ from controls before the training, in terms of accuracy (IPD: M = 580.4, SEM = 78.5; controls: M = 600.3, SEM = 63.9) and variability (IPD: M = 0.05, SEM = 0.08; controls: M = 0.05, SEM = 0.004). In paced tapping tasks, patients tended to be less accurate than controls when synchronizing with an isochronous sequence, a difference showing a statistical trend (at 450 ms, U = 102.0, p = 0.06; at 750 ms, U = 102.5, p = 0.06). The effect of the training was mostly visible in the follow-up session. Training led to increased synchronization accuracy with the isochronous sequences at the fastest tempo (450 ms) as confirmed by a statistical trend (W  = 50, p = 0.08). A significant increase of synchronization accuracy was found in the follow-up session (at 750 ms; W  = 72.0, p < 0.05). Patients’ performance in the follow-up evaluation did not statistically differ from that of controls. Patients and controls did not differ in terms of synchronization variability before the training (on average, IPD: M = 0.6, SEM = 0.1; controls: M = 0.6, SEM = 0.06). Patients and controls did not differ in terms of synchronization accuracy (on average, IPD: M = 7.3, SEM = 1.4; controls: M = 6.9, SEM = 0.8) and variability (on average, IPD: M = 0.8, SEM = 0.2; controls: M = 0.7, SEM = 0.08) when they synchronized with music.

In the synchronization–continuation task, patients tested prior to training were less accurate than controls only at the fastest tempo (450 ms, U = 78.0, p < 0.01). However, the two groups did not differ in terms of variability across all tempi (average variability, IPD: M = 0.03, SEM = 0.003; controls: M = 0.03, SEM = 0.002). Training had no effect on this task. Similar results were obtained in the adaptive tapping task. Before the training, patients exhibited lower accuracy than controls at the fastest tempi in the continuation phase (at 570 ms, U = 100.0, p < 0.05, and at 525 ms, U = 94.0, p < 0.05). Moreover, patients performed worse in detecting tempo changes at 600 ms (U = 99.5, p < 0.05). Both groups displayed similar tapping variability (on average, IPD: M = 0.05, SEM = 0.007; Controls: M = 0.05, SEM = 0.005), and comparable adaptation indexes (on average, IPD: M = 1.5, SEM = 0.2; Controls: M = 1.4, SEM = 0.1). Training was effective only in improving the detection of tempo changes, an effect visible when comparing pre-intervention to follow-up (W  = −43, p < 0.05). Patients’ perception in the follow-up session did not significantly differ from the performance of healthy controls.

Further analyses targeted the benefits of training on perceptual and motor timing at the individual level. Table 2 shows the individual performance of the 15 IPD patients on the BAASTA tasks showing significant effects at the group level. z-Scores for each testing session relative to the performance of controls are reported. Significant results are highlighted by the gray shading. Notably there are important individual differences in patients. After the training, some of them performed comparably to age-matched controls (n = 4), others showed improvement in perceptual/motor timing (n = 8) while the remaining did not respond to the training (n = 3). The percent of patients showing perceptual, motor, or perceptual and motor deficits at the three times of testing are summarized in Table 3. Perceptual or motor timing impairment is defined here based on the tasks included in Table 2. As can be seen, 73% of the patients displayed some form of timing impairment before the training. Post-intervention, poor timing abilities were found in 67% of the patients, while in the follow-up evaluation, only 40% of the patients still showed impaired timing.

In summary, training successfully yielded improvements in gait kinematics, which were still present in follow-up tests 1 month after the training ended. Prior to training patients performed worse in several tests of the BAASTA. Training improved performance in three perceptual and two motor tasks at the group level. However, there were important individual differences: four patients were unimpaired at the training onset, eight patients improved their performance with training, while three did not respond to the intervention.