Fourteen patients with idiopathic PD (mean ± SD age: 73.15 ± 4.16 years; 6 males and 8 females), and 17 healthy age-matched elderly (ELD) (mean ± SD age: 72.47 ± 5.20 years, 7 males and 10 females) participated in this study.

Patients were referred from the Department of Neurosciences of the University of Genoa by a movement disorders neurologist who made the diagnosis of idiopathic PD (according to the United Kingdom Parkinson’s Disease Society Brain Bank criteria). The mean score of the MDS—Unified Parkinson Disease Rating Scale, part III (Italian version) (24) was 28.86 ± 6.16 (± SD) and the Hoehn and Yahr stage (25) was 2.32 ± 0.25 (mean ± SD). The illness duration of patients was 7.76 ± 3.52 years (mean ± SD). All PD patients enrolled were under treatment with levodopa and/or dopamine agonists. The experiment took place during the “on” state (approximately 1 h after taking their anti-parkinsonian medications) for two reasons: (i) to avoid “off” tremor and bradykinesia, which could interfere with the aim of this experiment and (ii) because, unlike the effects on voluntary control, the ability to change postural responses has been shown not to improve with medication in PD patients (26, 27). Details of demographic and clinical characteristics of participants are provided in Table 1.

Exclusion criteria for both the healthy participants and subjects with PD were the following: (i) Mini-Mental Status Examination score <24 points (28), (ii) presence of pain, orthopedic lower limbs conditions, or other conditions limiting independent stance, and (iii) previous diagnosis of peripheral nerve disorders or other neurological conditions known to affect touch, proprioception, and/or motor control. In addition, PD patients with freezing of gait symptom and Hoehn and Yahr stage > 3 were excluded from the enrollment. All participants provided informed consent prior to testing. Experimental procedures were approved by the Ethical Committee of the University of Genoa and were carried out in agreement with legal requirements and international norms (Declaration of Helsinki, 1964).

The center of pressure (CoP) is the point of location of the vertical ground reaction force vector and posturographic measures were derived from forces exerted against the ground during upright standing. During the acquisition, force platform signals were sampled at 40 Hz, amplified, and converted from analog to digital form. CoP displacements were recorded for the entire presentation of each stimulus and data were filtered using a second-order low-pass Butterworth filter (cutoff frequency 10 Hz). Coordinates for the antero-posterior (A-P, y-axis) and medio-lateral (M-L, x-axis) positions of the CoP were computed for postural sway assessment.

The following postural parameters were computed for each condition (control pre, biological, control post): (i) the CoP-length calculated as the excursions along the two axes (A-P and M-L) in the horizontal plane and (ii) the area encompassed by A-P and M-L displacements (sway area, computed as the surface of the confidence ellipse containing 95% of the CoP sampled positions).

For the analysis of the time course of CoP excursions on the A-P and M-L axes, we divided each 12 s trial into 4 s time bins and then postural parameters were calculated for each bin; the results were averaged across trials for each subject. We considered Bin 1, Bin 2, and Bin 3 the time bins of the control task (white cross) preceding the biological stimulus, Bin 4, Bin 5, and Bin 6 the time bins of the biological stimulus and Bin 7, Bin 8, and Bin 9 the time bins of the control task (white cross) displayed immediately after the biological stimulus. Similar to previous works (29, 30), the immediate effect of the visual perturbation was investigated by comparing data obtained from the time bin prior to and immediately after the insertion (i.e., Bin 3 vs Bin 4) and by comparing data obtained from the time bin prior to and immediately after the removal (i.e., Bin 6 vs Bin 7) of the biological stimuli, whereas the time course of postural control was determined by comparing postural parameters across Bin 4–Bin 6. For sway area, the grand average of the mean value obtained in the five recordings lasting 12 s of each condition (control pre, biological, control post) was used.

Chi-square test was applied to assess gender differences between groups. Prior to the analysis, all variables were examined for normality (Shapiro–Wilk W test) and mean and SD were calculated. Differences between groups (PD and ELD) for age an education were assessed by the non-parametric Mann–Whitney test. For the analysis of CoP A-P and M-L excursions, a repeated measures (RM) analysis of variance (ANOVA) was used with Group (PD, ELD) as between-subjects factor and Bins (Bins 3, 4, 5, 6, 7) as within-subjects factor. For the sway area, a RM-ANOVA with Group (PD, ELD) as between-subjects factor and TASK (Control-PRE, Biological, Control-POST) as within-subjects factor was performed. Finally, in order to assess whether possible changes induced by the observation of biological stimuli relied on postural performance recorded in control condition (PRE), a Pearson’s correlation analysis was performed.

The pre-defined level of significance was set at p < 0.05, with Bonferroni pairwise comparisons used as post hoc tests where appropriate.

Significant changes induced by the insertion or removal of the biological stimulus in A-P excursions were seen only in PD group (Figure 1B). Precisely, RM-ANOVA showed a significant main effect of Bins (F_4,108 = 9.633; p < 0.001) and a significant Group × Bins interaction (F_4,108 = 5.237; p = 0.001). Post hoc analysis showed a significant insertion (Bins 3 vs 4: p < 0.001) and removal effect (Bins 6 vs 7; p < 0.001) only in PD participants, whereas no changes where seen in ELD subjects (insertion: Bins 3 vs 4: p = 0,448 and removal: Bins 6 vs 7 p = 0.445). Additionally, post hoc analysis revealed that the increase of A-P excursions observed in PD participants immediately after the insertion of the biological stimuli persisted up to the end of the stimuli (Bins 3 vs 5: p < 0.001; Bins 3 vs 6: p < 0.001). Finally, when differences between groups were investigated (Figure 1B), post hoc analysis showed significant differences only during the imbalance stimuli (PD vs ELD: Bin 4, p = 0.001; Bin 5, p = 0.007, Bin 6, p = 0.002), whereas only a trend was found when comparing groups during the control stimuli (PD vs ELD: Bin 3, p = 0.083; Bin 7, p = 0.066).

For M-L excursions (Figure 1C), a significant Group × Bins interaction (F_4,108 = 4.340; p = 0.003) was found, confirming that the observation of biological stimuli acted differently on the two groups. Indeed, post hoc analysis revealed that only in PD participants CoP excursions along M-L axis recorded in Bin 4 and Bin 6 were significantly larger than those recorded in Bin 3 and Bin 7, respectively (insertion Bins 3 vs 4: p = 0.031 and removal, Bins 6 vs 7: p = 0.028). No significant changes were detected in ELD subjects at the insertion (Bins 3 vs 4: p = 0.328) and at the removal (Bins 6 vs 7: p = 0.201) of biological stimuli. As for A-P excursions, data recorded across Bins 4–6 (Figure 1C, gray box) confirmed that the increase of M-L excursions in PD, lasted for the entire duration of biological tasks (Bins 3 vs 5: p < 0.024; Bins 3 vs 6: p < 0.010). Finally, post hoc analysis showed significant differences between the two groups (PD vs ELD: Bin 4, p < 0.001; Bin 5, p = 0.002, Bin 6, p < 0.001) during the imbalance stimuli only.

The mean value of the sway area for each group during the three stimulus conditions are depicted in Figure 2. RM-ANOVA showed a main effect of Group (F_2,54 = 27.49; p < 0.001) and a significant interaction Group × Task (F_2,54 = 6.99; p = 0.007). Post hoc analysis revealed significant changes in PD group (Control-1 vs Biological p = 0.005 and Biological vs Control-2 p = 0.031), whereas no changes were detected in ELD group (Control-1 vs Biological p = 0.245 and Biological vs Control-2 p = 0.531).

Linear relationships are shown in Figure 3. Postural parameters data recorded during all trials were averaged for Control-PRE (considered as baseline) and for Biological conditions, respectively, in each participant. Thus, the grand mean of A-P and M-L displacements and sway area data for Control-PRE and Biological conditions were used for running Pearson’s correlation analysis. Results showed that postural parameters recorded at the baseline (Control-PRE) significantly correlated with changes induced by imbalance stimuli in (i) A-P (r = 0.0908, p < 0.001; Figure 3A), (ii) M-L (r = 0.0951, p < 0.001, Figure 3B) displacements, and (iii) sway area (r = 0.616, p = 0.025; Figure 3C) only in patients with PD. Precisely, these relationships indicated that the larger were CoP excursions on the two axes and the area, recorded in the Control-PRE condition, the less was the ability to inhibit a visually induced postural perturbation.

Approximately 95% of participants (93% of PD and 94% of ELD) identified as a human stimulus the point-light video. Only, 1 out of 14 PD and 1 of 17 ELD subjects did not recognize that biological stimulus represented a human model, thus they were excluded from the study. As previously reported (7), also in our study, 100% of those subjects reported that the video was showing a subject in postural disequilibrium. Regarding perception of postural perturbation induced by biological stimuli, similarly to what observed by Tia et al. (7), around 40% of participants in both groups (6 out of 13 PD subjects and 6 out of 16 ELD subjects) reported having felt a slight increase of their body’s sway, with no difference between groups.

Chartrand and Bargh (11) defined the non-conscious mimicry of the postures, mannerisms, facial expressions, and other behaviors of one’s interaction partner, as the “chameleon effect.” Since then, most studies were focused on investigating mimicry during social interactions, showing that this spontaneous tendency of imitation plays an important role within social relationships, fosters liking between partners and increases empathy [for review, see Ref. (31)]. A large amount of neurophysiological and behavioral studies has revealed that the mere observation of actions leads to motor priming, triggers motor resonance processes that facilitate movement execution and induces a propensity to execute the observed actions (32–35). Precisely, the abovementioned tendency of imitation is automatic in that it occurs without will or awareness (12, 13, 36).

The discovery of mirror neurons system (MNS) in human cortex (37, 38) placed the neurophysiological bases for explaining the effects induced by action observation. Indeed, it has been shown that during the observation of actions executed by others, cortical areas congruent with those recruited during the execution of the observed action become automatically activated in the observer’s brain (39, 40). Further investigations revealed an involvement of the basal ganglia and cerebellum in action recognition and imitation processes, underlying that the mirror circuit does not work in isolation from subcortical structures (41–43). This might suggest that in PD patients, action observation abilities may be affected. However, neurophysiological data about the influence of PD pathology over the integrity of the MNS are still inconsistent. Reduced facilitation in action execution (44, 45), as well as reduced motor resonance (33), i.e., “the muscle-action specific facilitation of primary motor cortex during action observation,” and altered subthalamic activity during action observation have been reported in patients with PD (42, 46). In contrast, significant improvements of motor behaviors such as freezing of gait (47) or bradykinesia (48) and in disease severity (49) were also shown after one or repeated sessions of action observation.

Here, we found that the mere observation of point-light video displaying human imbalance elicited postural contagion, suggesting that imitation mechanisms through action observation are preserved in PD patients. Due to the complexity of this topic and differences among experimental designs used to explore imitation induced by action observation, we do not claim to have solved this issue. However, starting from recent evidences demonstrating that the recognition of biological motion triggers automatic imitation mechanisms in healthy (15, 17) and in neurological patients (50), we proved that through this protocol it is possible to induce motor contagion even in PD patients.

A recent EEG study investigated the cerebral dynamics of coding of postural control through action observation in healthy subjects (9). The authors demonstrated that while the observation of a person sustaining a quiet stance led primarily to the recruitment of temporal-parietal networks, the observation of a person in a condition of postural instability was coded in the central, but also in the parietal and temporal regions, slightly lateralized on the right hemisphere. Indeed, the superior temporal sulcus has been indicated by a large number of studies as the crucial node in the human MNS for detecting biological motion (51–54). Precisely, Martins et al. (9) described two specific cortical activity related to postural instability processing: a first activity recorded in the right temporoparietal regions (≈150 ms after the stimulus presentation) and a later activity (≈400 ms after the stimulus presentation) strictly lateralized in the occipital, temporal, parietal, and central electrodes of the right hemisphere. The authors proposed that the first activity might reflect the processing of the emotional load of the postural instability context associated to fear of falling, whereas the second activity indicates the right hemisphere as the “neural detector” for postural instability (55, 56).

Two hypotheses can be proposed to explain altered inhibition of postural imbalance induced by action observation in PD. The first is related to the possibility that in PD the neural structures responsible for the inhibition of imitative tendencies are malfunctioning, while the second takes into account an altered control of postural stabilization when cognitive load increases. Sensory deficits were unlikely to be responsible of postural contagion observed in PD patients. Indeed, participants’ reports about the ability to recognize as a human subject in postural disequilibrium the point-light video and about postural perturbation perception were similar between PD patients and healthy controls.

The control of automatic imitative tendencies has been extensively studied with neurophysiological and neuroimaging techniques. It has been shown that controlling imitative tendencies (i.e., avoiding unwanted imitation) occurs through the MNS modulation (57). Precisely, it was shown that motor resonance was greater during preparation to imitate than during preparation to counter-imitate a simple finger movement. These findings suggest the presence of some active inhibitory mechanisms required to control automatic imitation.

The candidate brain regions for controlling imitation have been indicated in the anterior medial prefrontal cortex and the right temporoparietal junction (TPJ). Indeed, lesions in these areas are associated with disruptive control of imitative tendencies (58, 59). Particularly, the right TPJ has been demonstrated to be involved in a specialized capacity to control automatic imitation of human agents (60), that is specific to self-other control (61), rather than to a universal process of conflict management. A recent resting-state fMRI study in PD (62) showed an altered functional integration, in terms of reduced node strength and betweenness centrality, in the dorsal anterior insula and TPJ nodes of the cingulo-opercular network. The authors discussed the disruptive functional integration of the TPJ node in the framework of the diverse functions carried out by this area, ranging from basic perception to social cognition. A paradoxical imitative facilitation has been demonstrated in PD subjects with voluntary self-initiation problems; for instance, difficulty in initiating gait after freezing, overcoming when another person or a cue drives the action (63) or difficulties in task-set maintenance reversed when there is a visual feedback or another person whose behavior they can imitate. The compromised TPJ function might also explain the lack of inhibition of imitation observed in the present study. Indeed, disrupting TPJ activity enhanced motor imitative ability, resulting in decreased control over imitation (64, 65).

However, this is only a tentative hypothesis since to address the neural basis of the control of imitative behavior during the observation of postural instability was beyond the scope of the present study and should be addressed in future studies.

For a long time, postural reactions have been considered to be automatically controlled; however, it has been demonstrated that postural control is highly influenced by the amount of attention invested in keeping stance (66), by previous knowledge of an upcoming postural perturbation (67), and by the surrounding emotional context (68, 69). Therefore, postural control is now considered as a complex cognitive-motor function. As an example, when subjects have to control their posture during the execution of a mental task they must inevitably manage and allocate their attention both to postural control and to the other task simultaneously (70).

Postural instability is one of the major problems for individuals with PD, it affects simple everyday activities, and it increases the risk of falls (18), especially when PD patients have to adapt to mutable circumstances or environments. Although in PD subjects, falls were previously identified as a result of a pure motor problem (i.e., balance and gait dysfunctions), it is now accepted that falls are also related to cognitive function deficits (i.e., executive dysfunction). This is supported by the fact that dual and multitasking performance is severely compromised in PD, causing interference with attentional mechanisms that normally allow people to compensate for their balance and gait disturbances (19, 71, 72).

Considering the instruction given here to the participants (i.e., to carefully observe the video trying to stay as still as possible), changes in postural control seen during the observation of the biological stimuli could suggest the impairment of a cognitive-motor task. This hypothesis is supported by previous studies concerning the effect of a cognitive load on postural control in PD patients (18, 20, 73). In particular, alteration of CoP excursions during the execution of a secondary task has been found in PD, suggesting that patients may prioritize the “cognitive” task (“carefully observe the video”) over the primary motor task (“to stay as still as possible”). Furthermore, even if previous studies demonstrated that consciously focusing on postural balance may affect postural control (74, 75), recently Sciadas et al. (76) showed that attempting to reduce postural sway did not lead to changes in postural control in individuals with PD, under single task condition. Conversely, changes in CoP displacement and increase in M-L velocity were observed with the addition of a cognitive task, suggesting again a difficulty in prioritizing activities to maintain postural stability as tasks become more challenging. Finally, it is worthy to note that the biological stimulus and the control stimulus presented different degree of complexity (human dynamic figure vs white cross). This difference could also exert a potential influence on the cognitive loads of the two tasks, even if the great part of the cognitive load of the experimental condition (“carefully observe the video while staying as still as possible”) lies in the dynamic aspects of the biological stimulus. However, in a future study, this issue could be partly solved by using similar stimuli in both the experimental and control conditions (e.g., human dynamic figure vs static human figure).