Evaluation of external vs. internal focus of attention in Parkinson's disease: A systematic review and meta-analysis during on and off medication states

Eligibility criteria

The studies needed to assign participants to different intervention groups to allow for a comparison. This could be an intervention group and a control group or multiple different intervention groups. Studies based on a crossover design were also included. The following eligibility criteria for articles were defined:

Population: Individuals with PD or a parkinsonian disorder were included. The stage of the disease reported in Hoehn & Yahr stages (H&Y) (Hoehn & Yahr, 1967) was not an excluding factor, and no variation of the disease was excluded.

Interventions: Instruction of at least one attentional focus during acquisition of a motor task. Multiple attentional foci could be compared within the same study. This could involve either internal or external attentional focus. Other attentional foci were also eligible.

Comparison: Included studies needed to have a control group. This group could be instructed with a different attentional focus, receive no attentional instructions, or undergo usual treatment.

Outcomes: The effect of the attentional focus had to be measured on at least one of the following outcomes: balance, gait or the motor symptom severity. The medication status during the intervention and measurement had to be specified (ON, OFF, or normal). For ON and OFF states, the duration since the last medication intake had to be specified.

Search strategy

The search strategy was constructed using two search concepts (i.e. population and intervention). Multiple search terms for the population concept ‘Parkinson’s disease’ and the intervention concept ‘attentional focus’ were first combined using the Boolean operator ‘OR’. In the next step, both concepts were combined using the operator ‘AND’.

The search was conducted in four electronic databases (MEDLINE (OVID), Cochrane CENTRAL, Embase, and CINAHL Ultimate). For each database specific subject headings were added to the search terms if available. The design of the search string is presented in Table 1.

Selection process

The selection process was divided into three phases. For each phase, the eligibility criteria were applied to decide on the inclusion of studies. All search results from each database were collated using RAYYAN software (RRID:SCR_017584) (Ouzzani et al., 2016) https://www.rayyan.com. First, duplicates were automatically removed using Rayyan’s deduplication functionality. Second, titles and abstracts were screened independently by GC and MK. Third, GC and MK independently reviewed the full texts of the studies that could potentially be included. In case of disagreements a third reviewer was used to solve the conflicts (KMS).

Data extraction

Data extraction was jointly performed by two reviewers, GC and MK. If data was only available in graphical form the WebPlotDigitizer (RRID:SCR_013996) (Rohatgi, 2017) was used to extract numerical data. We extracted data related to outcomes and outcome measures as well as demographic and clinical data.

Outcomes and outcome measures

The primary outcome in this review was “balance”, defined as the action of maintaining, achieving, or restoring a state of balance during posture or activity (Pollock et al., 2000). Outcome measures for this outcome included balance parameters like sway or balance tests (e.g. the Berg Balance Scale (BBS) or the Sensory Organization Test). When multiple outcome measures were present in a study, the most frequently used among included studies was selected. In cases of equal frequency, the BBS was prioritised due to its strong psychometric properties and widespread validation in people with Parkinson’s disease (Winser et al., 2019). The second outcome gait was defined as follows: Non-pathological gait is defined as a series of rhythmic, systematic, and coordinated movements of the limbs and trunk that result in the advancement of the body’s centre of gravity (Winter, 1987). Potential eligible outcome measures included gait parameters (e.g. walking speed, step variability, or symmetry) or gait tests like the Timed Up and Go (TUG). When multiple measures were present in a study, the most frequently used among included studies was selected.

The third outcome in this review was motor symptom severity. This included the expression of major motor symptoms related to PD, such as performing daily motor tasks, speech, facial expressions, muscle rigidity, or resting tremors (Goetz et al., 2008). Eligible outcome measures were the third part of the Unified Parkinson’s Disease Rating Scale (UPDRS-III) or its modified version (Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-III)). When multiple measures were present in a study, the most frequently used among included studies was selected. Across all outcome domains, when no clearly established gold-standard measure existed, frequency of reporting served as the sole criterion for selection.

Given the well-established influence of dopaminergic medication on motor symptoms in Parkinson’s disease, data were analysed separately for ON and OFF medication states. Participants who maintained their usual medication regimen were considered to be in the ON state, typically marked by improved mobility, while the OFF state reflects a return of motor symptoms and reduced functional capacity (Chou et al., 2018). Differentiating these states was clinically important, as attentional focus strategies may yield different outcomes depending on medication status. Moreover, recent translational research highlights that underlying neural mechanisms (such as impaired synaptic plasticity and circuit dysfunction) vary with dopaminergic availability (Rai et al., 2024). Separate analyses therefore allowed for a more accurate assessment of how attentional focus interacts with medication-related motor fluctuations, which is critical for tailoring rehabilitation strategies in clinical settings.

Study endpoints

Outcome data was extracted as close to the end of the intervention as possible. Some studies measured the effect of an attentional focus following a training program, in which case the measurement closest to the end of the training program was used. When studies reported outcomes in both medication states (i.e. ON and OFF state), measurements were taken as close to the end of the intervention on different days corresponding to different medications days.

Measurement and intervention conditions: Measurement conditions could vary between studies. If there was a choice among several conditions, such as measuring balance on a stable or unstable surface, the condition most frequently applied in all studies was used. For medication state, if subjects were instructed to maintain their usual medication, measurements were considered in a “normal” medication state and analysed together with the other data in ON state.

Assessment of methodological quality

Risk of Bias was evaluated with the newly developed ROBUST-RCT tool. This tool addresses limitations in existing risk of bias assessment instruments and provides a structured approach for assessing bias in randomised controlled trials (Wang et al., 2025). Risk of bias was evaluated for the primary outcome balance. If a study did not report on this outcome, we based the rating on the outcome gait and if still not reported we based the rating on the outcome motor symptom severity.

Synthesis methods

The statistical analysis followed the guidelines of the Cochrane Handbook for Systematic Reviews of Interventions (Deeks et al., 2019). The effectiveness of an attentional focus was analysed for the outcomes balance, gait, and severity of motor symptoms in ON/normal and OFF states. Meta-analyses were conducted using Review Manager 5.4 software (RRID:SCR_003581). For each outcome, means, standard deviations, and the number of participants were used for the meta-analyses. If standard deviations were not available, they were calculated from other available variability measures using Review Manager’s calculator. An inverse variance model with random effects was used (DerSimonian & Laird, 1986). Efficacy was evaluated using standardized mean differences (SMD) and 95% confidence intervals (CI), allowing us to compare effect sizes across studies that used different scales to assess similar outcomes. The SMD expresses the intervention effect in units of standard deviation, which standardises the results and enables meaningful aggregation of data from studies using different measurement instruments (Deeks et al., 2019).

Effect sizes were classified based on Cohen’s (2016) guideline, with categories set at 0.2 for a small effect, 0.5 for a moderate effect, and 0.8 for a large effect. Statistical heterogeneity was evaluated using the I² statistic, categorised as follows: 0% - 40% (potentially unimportant), 30% - 60% (moderate), 50% - 90% (substantial), and 75% - 100% (considerable) (Deeks et al., 2019). Funnel plots were employed to examine the potential for reporting bias.

Study selection

A total of 726 records were identified from the four databases. After excluding duplicates, 558 records were screened based on their titles and abstracts. We excluded 543 records excluded in this process. Of the remaining 15 publications, the full texts of 14 studies were retrieved. The study not retrieved was a conference paper. Despite contacting the author, no response could be obtained. After examining the full texts according to the inclusion criteria, five studies were excluded for the following reasons: in one study, the intervention was not compliant; three manuscripts did not meet the comparison criteria; and one work was excluded because it did not measure the desired outcomes. In the end, nine studies were selected for this research. The selection process is illustrated in Figure 1 with a flow diagram.

Figure 1. Flow chart of the study selection process.

Study characteristics

The main characteristics of the included studies are presented in Table 2. The nine selected studies included four randomised controlled trials (RCTs) and five crossover studies. Chen et al. (2023), Beck et al. (2018, 2020), and Landers et al. (2016) are randomised controlled trials. Landers et al. (2005), Beck and Almeida (2017), Wulf et al. (2009), Martin et al. (2023) and Jazaeri et al. (2018) are crossover studies. A total of 240 subjects were included for analysis. The stage of the disease was given by the Hoehn & Yahr stages, (Hoehn and Yahr (II-III)) and the disease duration by the average number of years (6.52 years). In five studies, the intervention was conducted in a single session (Beck & Almeida, 2017; Jazaeri et al., 2018; Landers et al., 2005; Martin et al., 2023; Wulf et al., 2009). In the other four studies, training programmes with specific attentional foci for each group were analysed (Beck et al., 2018, 2020; Chen et al., 2023; Landers et al., 2016). The medication status during specific interventions is shown in the column corresponding to each endpoint. In three studies, outcomes were measured in both medication states (Beck et al., 2018, 2020; Chen et al., 2023).

Methodological quality

The evaluation of the methodological quality of the included studies showed that the studies by Landers et al. (2016), with two items rated as having probable or definite risk of bias, and Chen et al. (2023), with three such items, had the lowest overall risk of bias among all selected studies. The studies by Landers et al. (2005) and Beck et al. (2017) had the lowest methodological quality, with each having five items rated as having a definitive or probable risk of bias. The criterion of sequence generation presented a risk of bias only in the Landers et al. (2005) study. All studies demonstrated a risk of bias related to the blinding of healthcare providers. However, the study by Landers et al. (2016) was the only one to report participant blinding, suggesting a probable low risk of bias for this criterion. The risk of bias assessment was based on the outcome ‘balance’ for all studies, except for Beck et al. (2018), which focused on ‘gait’, and Beck et al. (2020), which focused on ‘motor symptoms’. The assessment of methodological quality is shown in Figure 2.

Figure 2. Methodological quality of included studies.

NB. DH (Definitely High), DL (Definitely Low), HA-PD (High anxiety Parkinson’s disease), LA-PD (Low anxiety Parkinson’s disease), PH (Probably High), PL (Probably Low).

Results of the syntheses

In the following section, we present the syntheses for the outcomes: balance, gait, and motor symptoms. For each outcome, the analyses are reported separately based on the medication status of the participants (On/normal and OFF).

Balance

For the assessment of an attentional focus on balance in the ON/normal state, six studies could be included for the EFA-IFA comparison ( Figure 3). The EFA group comprised 93 subjects, while the IFA analysis included 94 subjects. Four studies involved single-session interventions (Beck & Almeida, 2017; Landers et al., 2005; Martin et al., 2023; Wulf et al., 2009) and the other two studies involved a training programme: 6 weeks with 12 sessions (Chen et al., 2023) and 4 weeks with 12 sessions (Landers et al., 2016). Three different balance outcome measures were used within this metanalysis. Body sway was assessed in three studies (Beck & Almeida, 2017; Martin et al., 2023; Wulf et al., 2009). Two studies assessed sway on an unstable surface (Beck & Almeida, 2017; Wulf et al., 2009). One study measured sway on a stable surface after sit-to-stand (Martin et al., 2023). The Berg Balance Scale (BBS) was used in two studies (Chen et al., 2023; Landers et al., 2016). The fourth condition of the Sensory Organization Test was used in one study (Landers et al., 2005). The meta-analysis showed no effect in favour of an attentional focus (SMD = 0.00; 95% CI between -0.46 and 0.46). Statistical heterogeneity was moderate (I² = 58%).

Figure 3. Forest plot comparing EFA versus IFA on balance for both ON/normal and OFF medication statuses.

NB. EFA (external focus of attention), IFA (Internal focus of attention).

For the analysis of balance during an OFF-medication status, four studies were included ( Figure 3). Both groups (EFA and IFA) consisted of 51 participants each. Two studies reported single-session interventions (Beck & Almeida, 2017; Jazaeri et al., 2018) and one used a training programme (Chen et al., 2023). Two balance outcome measure were employed. Body sway was assessed in two studies (Beck & Almeida, 2017; Jazaeri et al., 2018). Both sway assessments were performed on an unstable surface.

The BBS was used in one study (Chen et al., 2023). The meta-analysis showed no effect in favour of an attentional focus (SMD = 0.15; 95% CI between -0.24 and 0.54). Heterogeneity was not important (I² = 0%).

Gait

Concerning the evaluation of an attentional focus on gait in the ON/normal drug state, three studies could be included for the EFA versus IFA comparison ( Figure 4). The EFA group comprised 44 and the IFA group 46 participants. All three studies were interventions with a training programme (Beck et al., 2018; Chen et al., 2023; Landers et al., 2016). Two different gait outcome measures were used for the metanalysis. Walking speed was assessed in two studies (Beck et al., 2018; Landers et al., 2016). One measured walking speed in cm/s (Beck et al., 2018). The other study measured speed in m/s (Landers et al., 2016). The Timed Up and Go test was used in one study (Chen et al., 2023). The meta-analysis showed no effect in favour of an attentional focus (SMD = 0.11; 95% CI between -0.30 and 0.53). Heterogeneity was not important (I² = 0%).

Figure 4. Forest plot comparing EFA versus IFA on gait for both ON/normal and OFF medication statuses.

NB. EFA (external focus of attention), IFA (Internal focus of attention).

For the analysis of gait in the OFF-medication state, only the Chen et al. (2023) study was included for the EFA versus IFA comparison ( Figure 4). Both groups consisted of 15 participants. This study involved a training programme (6 weeks with 12 sessions). The Timed Up and Go (TUG) was used to measure walking. The meta-analysis showed no effect in favour of an attentional focus (SMD = 0.16; 95% CI between -0.56 and 0.88).

Severity of motor symptoms

Concerning the evaluation of an attentional focus on the severity of motor symptoms in the ON/normal drug state, three studies could be included for the EFA versus IFA comparison ( Figure 5). These were the studies by Beck et al. (2018, 2020) and Chen et al. (2023). All three studies were training programmes (duration: 11 weeks with 33 sessions for the Beck et al. studies and 6 weeks with 12 sessions for the Chen et al. study). The EFA analysis involved 51 participants, while the IFA analysis involved 53 participants. Two outcome measures were used to assess the severity of motor symptoms in the metanalysis. The Beck et al. (2018, 2020) studies used the third part of the Unified Parkinson’s Disease Rating Scale (UPDRS-III. Chen et al. (2023) used the third part of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-III). The meta-analysis showed no effect in favour of an attentional focus (SMD = -0.16; 95% CI between -0.55 and 0.22). Heterogeneity was not important (I² = 0%).

Figure 5. Forest plot comparing EFA versus IFA on severity of motor symptoms for both ON/normal and OFF medication statuses.

NB. EFA (external focus of attention), IFA (Internal focus of attention).

For the severity of motor symptoms in the OFF state, three studies could be included for the EFA versus IFA comparison ( Figure 5) (Beck et al., 2018, 2020; Chen et al., 2023). The EFA group comprised of 51 and the IFA group of 53 participants. In all three studies, a training programme was implemented, utilising the same two outcome measures as in the ON state analysis. The meta-analysis showed no effect in favour of an attentional focus (SMD = -0.15; 95% CI between -0.53 and 0.24). Heterogeneity was not important (I² = 0%).

Reporting bias

The presence of a possible reporting bias was analysed for the EFA versus IFA comparison for balance was analysed with a funnel plot ( Figure 6). We could not identify a reporting bias, but this may be caused by the limited number of included studies.

Figure 6. Funnel plot EFA versus IFA for balance.

NB. EFA (external focus of attention), IFA (Internal focus of attention), The negative area of the graph corresponds to the effect in favour of an EFA. The positive area of the graph corresponds to the effect in favour of an IFA.

Sensitivity analyses

We explored the influence of the factors: duration of the interventions, disease duration, stage of the disease and methodological quality in more depth to identify whether they could have masked a potential effect on the primary outcome balance.

Sensitivity analysis – duration of the intervention

Within this analysis, we excluded studies with single-session interventions on the outcome balance. Only studies going over a longer duration were retained. For the ON/normal medication condition two studies remained within the analysis (Chen et al., 2023; Landers et al., 2016) reporting on 51 PwPD. Effectiveness was in favour of IFA (SMD: 0.22; 95% CI: -0.33 to 0.77). Heterogeneity was low with an I2 value of 0%. For the OFF condition only the study of Chen et al. (2023) remained. Effectiveness was in favour of IFA (SMD: 0.24; 95% CI: -0.48 to 0.96).

Sensitivity analysis – disease duration

Within this analysis, we excluded studies with a mean disease duration of less than 6 years on the outcome balance. Under the ON/normal medication condition, three studies (Beck et al., 2017; Chen et al., 2023; Landers et al., 2005) were included, comprising a total of 112 PwPD. The analysis indicated a small effect in favour of IFA, with a SMD of 0.22 and a 95% confidence interval ranging from –0.28 to 0.72. Heterogeneity was moderate, with an I² value of 43%. For the OFF condition, two studies remained within the analysis (Beck et al., 2017; Chen et al., 2023) with a total of 68 PwPD. Effectiveness was in favour of IFA (SMD: 0.31; 95% CI: -017 to 0.79) with an I² value of 0%.

Sensitivity analysis – stage of disease

Further exploration on the potential influence of the variable stage of the disease (i.e. the H&Y stage) was not possible, because all studies reported on PwPD with H&Y stages between 2 and 3 or did not report this variable at all.

Sensitivity analysis – methodological quality

With this analysis we explored whether the rated methodological quality of the included studies could have influenced the primary outcome balance. We excluded the studies with the highest amount of definitive or probable risk of bias ratings (i.e. Landers et al., 2005; Beck et al., 2017). Under the ON/normal condition four studies remained within the analysis (Chen et al., 2023; Landers et al., 2016; Martin et al., 2023; Wulf et al., 2009). The analysed effect size shifted slightly in favour of the EFA group. However, the magnitude did not reach the threshold for a small effect (SMD = -0.11; 95% CI: -0.75 to 0.54), indicating a statistically non-significant and clinically negligible difference. Heterogeneity was moderate (I² = 63%). For the Off condition, the effect size was negligible (SMD = 0.03; 95% CI: -0.46 to 0.52), indicating no meaningful difference between groups and a statistically non-significant result.

Limitations

A limitation of this systematic review was that we included studies with different acquisition periods. We included both studies with a single training session and studies using a training period over several weeks. It is difficult to exclude a carry-over effect in the studies with a single training session. These studies used a crossover design. Participants received a training intervention with an EFA and IFA during the training period. Performance measured with a post-acquisition test might be biased because participants may have used a different attentional focus than what was intended by the test instructions. The wash-out period between the two interventions was generally very brief and never reached a duration where interference from the instructions could be ruled out. This risk of bias is not present in studies using only a single focus of attention during the acquisition phase.

Another limitation could be related to the dopaminergic state during the measurements in the study by Landers et al. (2005). The subjects in this study were instructed to maintain their usual medication regimen the day before and the day of the measurements. We assumed that the subjects were taking dopaminergic medications. The medication state was considered “normal” during these measurements. Unlike other studies that required about an hour of waiting after taking the medication for ON measurements, it is not possible to know the precise dopaminergic state of the subjects in the study by Landers et al. (2005).

The differences in duration and frequency of the training programs are another limitation. Indeed, the influence of the duration of a programme based on a specific attentional focus could be observed in the analysis of motor symptom severity (i.e. a longer training period causes a longer exposure to a certain attentional focus, which might increase the effectiveness of this focus). The studies by Beck et al. (2018, 2020) implemented a program of 33 sessions over 11 weeks (three sessions per week). The study by Chen et al. (2023) is based on a programme approximately half as long, lasting six weeks with a total of 12 sessions (two sessions per week). The two studies by Beck et al. (2018, 2020) suggest that the benefits of an EFA on the severity of motor symptoms may emerge from a certain frequency of training over a longer duration.

Another limitation of this study was that the confidence intervals are wide, and precision was low for most of the analyses. In order to identify possible sources of imprecision we analysed the influence of the clinical variables: duration of the intervention, disease duration and stage of the disease on the primary outcome balance with separate sub-group analyses.

We explored the influence of the duration of the intervention with a sensitivity analysis on the primary outcome balance. Within this analysis single session interventions were excluded. Analysis of the longer duration interventions indicated that an IFA was more effective for balance for ON/normal medication with a small effect size. A similar finding was seen for the OFF condition. Although both analyses had high uncertainty with large confidence intervals. This also indicates that an EFA might be more effective for single session interventions.

The hypothesis that individuals with Parkinson’s disease (PwPD) at different stages of disease duration might benefit from different types of attentional focus was also examined through a subgroup analysis. Within this analysis we found that PwPD with a disease duration of more than 6 years seemed to benefit more from an IFA when compared to the full-analysis with all studies. However, the effect remained small with a large confidence interval.

We tried to confirm these results with a sensitivity analysis of the variable stage of the disease (i.e. measured with the H&Y stage) but as all studies reported on the H&Y stages 2-3 a subgroup analysis was not possible.

The influence of the methodological quality of the included studies on the primary outcome was also explored through a subgroup analysis. In this analysis, we excluded the studies with the highest risk of bias rating on the ROBUST-RCT assessment. Effect estimates for both analyses (i.e. ON and OFF medication status) were imprecise, with large confidence intervals that were compatible with effect estimates favouring each group. Therefore, we could not establish an influence of the risk of bias rating on the effect estimates.

The results of the sensitivity analyses are exploratory. Given the small sample sizes and the limited number of included studies we were not able to investigate these variables in more detail using meta-regression.

A further limitation is that the meta-analysis of the balance outcome during the ON state showed a moderate heterogeneity. This was probably caused by a single study showing a large effect in favour of the EFA condition (Wulf et al., 2009). To identify potential reasons, we analysed several factors, including the number of participants, stage of the disease, age, order of focus testing, verbal instructions given to participants, and intervention conditions. After investigating these clinical data, we were unable to identify any differences that might explain this disparity compared with the other studies. More specifically, the study did not involve a longer training duration and comprised only a single session. Participants were considered in the ON state, the average age was 71 years, and the disease stage involved H&Y stages II and III.

Another limitation was the relatively small combined sample size of only 228 participants across all studies, which may compromise the statistical power of the findings.

Implications

Although the results of this work do not show superiority of a specific attentional focus in PwPD, it is important to note that they only concern the three analysed outcomes (i.e. balance, gait and motor symptom severity)

Regarding clinical implications, it is important for rehabilitation specialists to observe the patient’s attentional preferences in order to adapt the attention according to their needs. These may vary depending on the progression of the pathology as well as the biopsychosocial factors that are different for each PwPD. Indeed, some studies demonstrate the superiority of an EFA on balance in anxious PwPD or those with a history of falls (Jazaeri et al., 2018; Landers et al., 2005). Therefore, we believe that a patient-centred approach where strategies are developed considering the medication status, the duration of the interventions and in collaboration with the person’s preferences and their environment is essential given the current state of evidence. A patient-centred approach is further supported by the heterogeneity observed in the included studies. Despite the absence of significant group-level effects in the meta-analyses, individual studies reported varying responses to attentional focus strategies, suggesting that some PwPD may benefit more from one approach than another. For instance, Beck and Almeida (2017) found better balance outcomes with an internal focus in the OFF state, while Landers et al. (2005) and Wulf et al. (2009) reported benefits of an external focus in ON states. These inconsistencies may reflect underlying differences in disease stage, anxiety levels, or attentional preferences (i.e. factors that are not captured in group-level analyses but are critical in clinical practice).

This patient-centred approach is supported by expert opinion, such as that expressed by Okun (2017), who emphasises that due to the complexity and fluctuating nature of Parkinson’s disease, treatment should be tailored to individual patient needs. Other sources, such as Khanna and Jones (2023), argue that the wide range of distinct patient phenotypes (i.e. characterized by varying combinations of motor and non-motor symptoms) necessitates a personalised treatment approach in PwPD.

Clinically, this suggests that rehabilitation professionals should assess and incorporate individual attentional preferences, medication status, and psychosocial factors when designing interventions. Future RCTs should consider stratifying participants based on these variables or employing adaptive trial designs to better capture individual responsiveness. Moreover, exploring alternative attentional strategies (e.g., holistic or switching focus) and integrating neuroimaging to understand underlying mechanisms could further refine personalized interventions.

Further research is needed, specifically randomized controlled studies, to investigate the effectiveness of different attentional foci in larger sample sizes of PwPD undergoing similar rehabilitative interventions.

Furthermore, it would be interesting to investigate certain profiles of the disease separately. The choice of one attentional focus over another could be particularly useful in the stages of the disease where PwPD are still mobile. In these phases, it is important to maintain independence and safety during daily activities. In addition, recent research has demonstrated that other types of attentional focus, such as a holistic focus or a switching focus of attention, have shown promising results in supporting healthy individuals acquire sport-related motor skills (Abedanzadeh et al., 2022; Favre-Bulle et al., 2024). The effectiveness in of these principle in PwPD should be investigated in future studies.

Lastly, further neuroimaging studies could be dedicated to understanding the impact of medications on the engagement of brain areas and networks associated with different attentional foci in PwPD.