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RESEARCH REPORTS

Hand-Arm Bimanual Intensive Therapy Improves Prefrontal Cortex Activation in Children With Hemiplegic Cerebral Palsy

Surkar, Swati M. PT, PhD; Hoffman, Rashelle M. PT, DPT; Willett, Sandra PT, PCS, MS; Flegle, Janice OTRL; Harbourne, Regina PT, PCS, PhD; Kurz, Max J. PhD

Author Information
doi: 10.1097/PEP.0000000000000486

INTRODUCTION

Action planning is the ability to anticipate forthcoming perceptual-motor demands and is crucial for the development of skilled movements.1 Various activities of daily living, such as manipulating objects, dressing and undressing, and tying shoe laces, require planning, online monitoring, and control of the goal-directed actions.2 Thus, cognitive, sensorimotor, and visuomotor integration are necessary for action planning. Recent studies have shown that children with hemiplegic cerebral palsy (HCP) may have deficiencies in their ability to plan motor actions.3–5 Consequently, these action-planning deficits may restrict the child's participation in educational, leisure, and vocational roles.3 While these observations may be accurate, therapeutic interventions for children with HCP often do not directly focus on theses action-planning deficiencies.6

Constraint-induced movement therapy and hand-arm bimanual intensive therapy (HABIT) are successful therapeutic approaches used to improve the motor actions of children with HCP.7 These approaches have been effective in improving the affected hand/arm function and bimanual coordination. The cortical changes related to these therapeutic improvements are associated with reorganization of the sensorimotor cortex topology, an increase in white matter volume, and maintenance of the integrity of the corticospinal fiber tract.8,9 Despite these promising results, these studies have largely overlooked the potential cortical changes associated with the action-planning problems noted in children with HCP.

The prefrontal cortex (PFC) plays a critical role in planning and monitoring of motor actions.1 This notion is based on the outcomes of numerous neuroimaging studies that have demonstrated concurrent activation within the PFC, the dorsolateral prefrontal cortex (DLPFC), and the ventrolateral prefrontal cortex (VLPFC) while performing motor actions.10–13 Few neuroimaging studies have evaluated the activity within these cortical regions, as children with HCP plan their motor actions.4,14,15 Furthermore, no studies have evaluated whether the activity within the PFC changes after physical therapy. Addressing this knowledge gap will strengthen our understanding of how the current physical therapy trends ignite beneficial changes in the cortical areas that are involved in the action planning of motor tasks.

The primary purpose of this novel exploratory investigation was to determine the changes in PFC activation following HABIT using functional near-infrared spectroscopy (fNIRS) neuroimaging. Our rationale in using HABIT was that the intensive practice of bimanual tasks would enhance the action planning of children with HCP. We hypothesized the improved action planning would be reflected through altered PFC activation during a goal-directed motor action.

METHODS

This is a quasiexperimental study.

Participants

Nine children with HCP (ages 4.8 ± 0.9 years; 4 males) were included in this investigation. An additional 15 age-matched children who were developing typically (ages 5.9 ± 1.2 years; 8 males) served as a comparison group. Further details of the participating children with HCP are provided in the Table. We excluded children with frontal cortex lesions, cognitive impairments, visual deficits, musculoskeletal deformity of the hand and arm that restrict motor performance, and arm weakness due to other neurological impairments such as brachial plexus injuries. The preferred handedness for all children was determined using Edinburgh handedness inventory, and parent reports.16 All of children who were developing typically were right handed. Furthermore, the time frame for the assessment of the children who were developing typically was the same as the pre-HABIT assessments of children with HCP.

TABLE - Demographic Details of Participantsa
HCP TD
HCP Gender Age, y Side of Hemiplegia MACS Level AHA Score Diagnosis TD Gender Age, y
HCP 1 Male 4.5 Left V 7 Perinatal stroke TD 1 Male 6.7
HCP 2 Male 4.6 Right II 85 Perinatal stroke TD 2 Female 6.6
HCP 3 Male 5.3 Right IV 12 Perinatal stroke TD 3 Female 4.1
HCP 4 Female 6.1 Left III 59 Perinatal stroke TD 4 Male 6.6
HCP 5 Female 6.1 Left II 87 Perinatal stroke TD 5 Female 4.6
HCP 6 Female 3.1 Left III 52 PVL TD 6 Female 4.1
HCP 7 Female 4.1 Left III 58 Perinatal stroke TD 7 Male 6.5
HCP 8 Female 4.8 Right III 58 Perinatal stroke TD 8 Female 7.5
HCP 9 Male 5.0 Left III 62 Schizencephaly TD 9 Female 6.8
TD 10 Male 7.0
TD 11 Male 5.11
TD 12 Male 4.6
TD 13 Female 6.11
TD 14 Female 5.11
TD 15 Female 6.0
Abbreviations: AHA, Assisting Hand Assessment Score (logit units); HCP, hemiplegic cerebral palsy; MACS, Manual Ability Classification System; PVL, periventricular leukomalacia; TD, typically developing.
aAll children developing typically were right-hand dominant.

Procedure

HABIT Protocol. HABIT is a child-friendly, intensive intervention directed at improving bimanual coordination and function of the affected arm.17 Our rationale in administrating HABIT was that an enriching movement experience with intensive practice of bimanual tasks would form an effective motor plan. The intervention employed in this study included various age-appropriate fine and gross motor bimanual activities that were delivered in a play context (for details of the activities, see Supplemental Digital Content 1, available at: http://links.lww.com/PPT/A206). The HABIT summer camp used a 1:2 ratio of the child to interventionists, respectively. The interventionists were physical therapy students who were trained and supervised by licensed physical and occupational therapists. The interventionists guided and continuously monitored each child's activities under the supervision of 2 physical and occupational therapists on-site. Since the children in our study had different levels of hand function, we set individual therapy goals based on the Assisting Hand Assessment (AHA). The bimanual activities that were practiced emphasized different arm roles, such as stabilizer, manipulator, and active/passive assisting. The activities were made progressively more difficult; however, the interventionist graded the task demands so that the child was successful in completing the activity. Positive feedback and knowledge of performance were used to motivate and reinforce the prescribed movements. The therapy incorporated both whole- and part-task practice. The goal of whole-task practice was to improve the performance by manipulating the temporal and spatial components of the task. Part-task practice focused on improving speed of the task. For all activities, the interventionist emphasized completing each movement with the involved upper extremity to increase its use in bimanual activities. The training sessions also included functional training activities that were tailored to the child's and parent's therapeutic goals. The children also performed 1 hour of bimanual activities at home with their parents, and the parents kept daily logs, which were used to monitor compliance. Makeup sessions were conducted when a child was not able to participate during the scheduled camp time. Children practiced bimanual activities for 5 hours per day (4 hours on-site and 1 hour at home each day), 5 days per week, for 2 consecutive weeks. To maintain the fidelity of HABIT, physical and occupational therapists supervised the interventionists. Moreover, interventionists recorded all the activities that the child performed each day. After the HABIT session, we conducted a daily meeting to give feedback to the interventionists, to discuss the child's progress and therapy goals for the next session.

fNIRS Experimental Paradigm. The fNIRS experimental task consisted of a sequential shape-matching task that had 3 complexity levels: easy, moderate, and difficult. The easy condition had the same shape types, the moderate had 2 different shape types, and the difficult had multiple different shape types (Figure 1). The 3 complexity levels were based on intricacy of shape identification, accurate selection, manipulation, and type of grasp required to orientate the shape. Children were given 30 seconds to match the shapes by selecting an item and physically placing it accurately on a template. Typically, the children could not match all shapes in the provided period. However, in the rare instance, if the child matched all 12 shapes, the assessor removed the items from the template and the child continued matching the shapes on the same template until the 30 seconds of active period was over.

Fig. 1.
Fig. 1.:
Experimental task conditions. The shape template was presented to the child just before beginning the task. (A) Easy: the easy condition had the same shape types. (B) Moderate: the moderate condition had 2 different shape types. (C) Difficult: the difficult condition had multiple shape types that were different from each other. The children were asked to match the maximum number of shapes with the corresponding template for 30 seconds. The conditions were randomized and each task condition was repeated 4 times.

Each shape-matching condition was performed in a block paradigm consisting of a 30-second rest period when the child sat still, and a 30-second active period when the child matched shapes to the respective template. To avoid anticipation of the complexity levels, the conditions were randomized and each shape-matching condition was repeated 4 times. The children performed a total of 12 blocks of the shape-matching task (3 shape complexity conditions × 4 repetitions of each condition) for the full session. Children with HCP performed the task with the affected and unaffected arms, and children who were developing typically performed the task with the dominant and nondominant hands before and after the HABIT camp. We chose to evaluate both arms to explore the global nature of cognitive processes required for movement planning and control.

fNIRS Methodology and Analysis. fNIRS uses specific wavelengths of infrared light that penetrates the skull to approximate the absorption characteristics of oxygenated (OxyHb) and deoxygenated (DeOxyHb) hemoglobin within the underlying tissues.18 A greater concentration of OxyHb corresponds to a heightened amount of activity in the underlying neural tissues.18 For this experiment, we used a continuous-wave fNIRS system (fNIR Devices LLC, Potomac, Maryland) that used 2 different wavelengths (730 and 850 nm) to measure the concentration of OxyHb and DeoxyHb.19 The system was composed of a flexible head piece that contained a series of emitters and detectors that were positioned on the hemispheres of the frontal cortices according to the International 10-20 system (Figure 2). A modified Beer-Lambert equation was used to determine the changes in the OxyHb concentrations based on the optical density of the raw light intensity signals.20 The calculated OxyHb concentration waveforms were subsequently low-pass filtered with a finite impulse response filter that had an order of 20 and cutoff frequency of 0.1 Hz. This filter was implemented to attenuate the high-frequency noise, respiration, and cardiac cycle effects.21,22 The epochs of each trial were 60 seconds in duration (−30 to +30 seconds), with the presentation of the shape-matching task defined as 0.0 second. The OxyHb waveforms for each channel were corrected based on the average OxyHb seen in the baseline period (−25 to −5 seconds), and the 4 trials performed in each condition were subsequently averaged. For each shape-matching condition, the maximum OxyHb during the active period was calculated and averaged for the channels that overlaid the right and left PFC, respectively. OxyHb was chosen because it is a valid marker for regional brain activation, and is often more sensitive to neural changes than DeoxyHb.23

Fig. 2.
Fig. 2.:
Depiction of the placement of the fNIRS system on an exemplary child. The system consists of a flexible sensor pad that is positioned on the forehead based on the 10-20 system. The flexible sensor pad contains the emitters and photodetectors. This arrangement results in 2 measurement channels per hemisphere. fNIRS indicates functional near-infrared spectroscopy.

Behavioral Data Acquisition and Analysis. During the fNIRS data collections, the shape-matching task was video recorded to determine the number of shapes the child attempted to match, the number of errors in matching the shapes, and the child's reaction time (RT). A trained coder coded these variables using the exploratory sequential data analysis software, “Datavyu” (Datavyu: A Video Coding Tool, Databrary Project, New York University).

The children with HCP also completed the AHA before and after the HABIT camp. This assessment consisted of a standardized play session with toys requiring bimanual use of the arm to score the affected arm's function and bimanual coordination.24 Both groups performed the 9-hole peg test (NHPT) and the box and blocks test (BBT) to assess manual dexterity and speed.25,26

Outcome Measures

Primary.

  • 1. OxyHb. The average maximum OxyHb across respective channels was used to determine activation in the PFC.
  • 2. AHA score. AHA 5.0 is a reliable (in our study, interrater = 0.98, intrarater = 0.99) and valid outcome to assess the affected hand function and bimanual coordination, specifically in children with HCP.24 It has 20 items in 6 different categories of the arm use and with a rating scale of 1 to 4 points: 1 = does not use the arm, 4 = effective use of the arm. The AHA raw scores were converted into logit units (0-100) for the final analysis. A 5-point change in the AHA scale is considered clinically meaningful.27

Secondary.

  • 3. Task performance. Task performance was determined based on the number of accurately matched shapes. A correct match of the shape on the corresponding template, use of the testing arm, and accurate orientation of the shapes were considered as correctly placed shapes. A total number of shapes were quantified across each trial and the average performance across the 4 trials for each condition was the outcome variable.
  • 4. Task errors. Task errors were an average number of errors in matching the shapes across all trials. A wrong match and inaccurate orientation of the shapes were considered errors.
  • 5. RT. RT was determined as the amount of time needed to initiate hand movement after the shape-matching task was presented. RT for the first shape in each trial was assessed, and average RT across all trials was used for the final analysis.
  • 6. NHPT and BBT. The NHPT and the BBT are valid and reliable tests to assess manual dexterity.25,26 The NHPT is a time test and was scored by the number of seconds the child required to place 9 pegs in a pegboard and remove them with each hand. The reported interrater and test-retest reliability of the NHPT is 0.99 and 0.81, respectively.25 The score for the BBT was the number of cubes transferred from one compartment to the other in 1 minute. The interrater and test-retest reliability of the BBT has been reported as 0.99 and 0.85, respectively.26

Statistical Analysis

Separate analyses of variance (ANOVAs) (pre-/post-HABIT × hemisphere × unaffected/affected arm × shape matching condition) were used to analyze OxyHb after HABIT. Separate 2 × 2 mixed ANOVAs (pre-/post-HABIT × unaffected/affected arm) were used to analyze behavioral variables after HABIT. Paired t test assessed the pre- and post-HABIT changes in the AHA. Similarly, separate mixed-model ANOVAs (group × hemisphere × arm × shape-matching condition) were used to analyze the differences in the OxyHb between the children who were developing typically and the OxyHb values for children with HCP before and after HABIT. Separate 2 × 2 mixed ANOVAs (group × arm) were used to analyze differences in the behavioral variables of the children with HCP after HABIT and children who were developing typically. Statistical analyses were performed using SPSS (version 22.0; IBM Corporation, Armonk, New York). Results are presented as a mean ± standard error of the mean.

RESULTS

Patient Flow

Figure 3 depicts patient recruitment. We screened 32 children, of whom 10 participated in the 2 HABIT camps (July 2015: n = 6; July 2016: n = 4).

Fig. 3.
Fig. 3.:
Patients' flow diagram showing progress through the stages of the study, including flow of participants, withdrawals, and inclusion in analyses. A total of 32 individuals were screened via telephone/e-mail, and 16 of these were excluded for the following reasons: too old (n = 4), too young (n = 3), poor cognition (n = 3), diagnosis other than hemiplegia (n = 3), uncontrollable seizures (n = 2), and recent hemispherectomy surgery (n = 1). A total of 16 children met the study criteria and were invited to undergo physical screening; 2 parents chose not to undergo physical screening. Of the remaining 14 individuals, 4 could not participate due to time constraint (n = 2) and fear of physical stress to the child (n = 2). A total 10 children participated in the HABIT camp (6, first year/4, second year). All 10 children completed the 50 hours of HABIT. Out of these 10 children, 1 could not complete the post-HABIT behavioral assessments. Remaining 9 children completed the behavioral assessments. Out of these 9 children, 1 child did not comply with the fNIRS data collection. Therefore, fNIRS analysis consists of 8 children. Our final analysis contains behavioral data of 9 children and fNIRS data of 8 children. fNIRS indicates functional near-infrared spectroscopy; HABIT, hand-arm bimanual intensive therapy.

Treatment Characteristics

All children completed 50 hours of HABIT. Our treatment logs recorded that 94.6% of the time the children were engaged in bimanual activities. On average, they spent 74.2% of time in whole-task practice, 10.2% in part-task practice, and 12% in functional training. All the children had good compliance (9.8 ± 0.33 hours) for the home exercise program. There were no adverse events reported during the course of either HABIT camp. Supplemental Digital Content 2 (available at: http://links.lww.com/PPT/A207) provides the individual outcome measures for the children with HCP and children who were developing typically.

fNIRS

Pre-HABIT and Developing Typically. There was a significant group main effect (P = .001), with the children with HCP having greater OxyHb before HABIT than the children who were developing typically (Figure 4). There was a significant (P = .001) group × arm interaction. There was a significant difference with post hoc analysis (P = .001) in OxyHb between the affected arm (0.46 ± 0.03 μmol) of children with HCP and the nondominant arm (0.20 ± 0.02 μmol) of children who were developing typically. There was a significant difference (P = .02) in OxyHb between the unaffected arm of children with HCP (0.26 ± 0.03 μmol) and the dominant arm of children who were developing typically (0.14 ± 0.02 μmol).

Fig. 4.
Fig. 4.:
Comparison of maximum OxyHb between pre-, post-HABIT, and control group. HABIT indicates hand-arm bimanual intensive therapy; OxyHb, oxygenated hemoglobin.

Pre- and Post-HABIT. There was a significant pre/post main effect (P = .001), with children with HCP having lower OxyHb after HABIT (Figure 4). There was a significant-arm main effect (P = .002), with greater OxyHb when children with HCP performed the task with the affected (0.33 ± 0.02 μmol) than the unaffected arm (0.22 ± 0.02 μmol). There was a significant group × arm interaction (P = .003). There was a reduction in OxyHb after HABIT when children performed the task with the affected arm (pre-/post-HABIT = 0.47 ± 0.03 μmol; 0.21 ± 0.03 μmol, P = .002).

Post-HABIT and Developing Typically. Remarkably, we found no significant main effects or interactions when comparing the OxyHb for the children with HCP and the children who were developing typically after HABIT (P > .05).

AHA

There was significant improvement in AHA score (pre = 54.66 ± 9.3; post = 64.22 ± 9.7; P = .001) after HABIT.

Number of Shapes Attempted

Pre- and Post-HABIT. There was a significant pre/post main effect (P = .01), with the children with HCP attempting to match 21% more shapes after HABIT (pre: 4.3 ± 0.4; post: 5.2 ± 0.3 shapes). There was a significant-condition main effect (P = .001). Post hoc analyses indicated that children with HCP attempted to match a greater number of shapes in easy (6.17 ± 0.33 shapes; P = .01) than moderate (4.38 difficult ± 0.33 shapes; P = .01) and difficult shape-matching conditions (3.71 ± 0.33 shapes; P = .01). There was a significant arm main effect (P = .001), with the affected (4.1 ± 0.28 shapes) arm matching 24% fewer number of shapes than the unaffected arm (5.4 ± 0.31 shapes).

Post-HABIT and Developing Typically. There was a significant group main effect (P = .001), with children with HCP (5.23 ± 0.30 shapes) attempting to match 35% fewer shapes than children who were developing typically (8.03 ± 0.25 shapes). There was a significant-condition main effect (P = .001). Post hoc analysis indicated that overall the children attempted to match more shapes in easy (8.7 ± 0.38 shapes) than moderate (6.77 ± 0.33 shapes) and difficult (5.4 ± 0.29 shapes; P = 0.001) shape-matching conditions.

Shape-Matching Errors

Pre- and Post-HABIT. There was a significant pre/post main effect (P = .002), with a 47.7% reduction in shape-matching errors after HABIT (pre = 4.88 ± 0.61; post = 2.55 ± 0.42). There was a significant arm main effect (P = .006), with a higher number of errors performed in the affected arm (4.47 ± 0.47) than in the unaffected arm (2.72 ± 0.47).

Post-HABIT and Developing Typically. There was a significant group main effect (P = .006), with the children with HCP performing 82% more errors (2.55 ± 0.42) than the children who were developing typically (1.40 ± 0.21).

RT

Pre- and Post-HABIT. There was a significant pre/post main effect (P = .006), with a 39.5% reduction in RT after HABIT (pre = 2.23 ± 0.29 seconds; post = 1.35 ± 0.17 seconds). There was a significant arm main effect (P = .003), indicating that the affected arm had a slower RT (affected = 2.27 ± 0.29 seconds; unaffected = 1.32 ± 0.15 seconds).

Post-HABIT and Developing Typically. There was a significant group main effect (P = .002), with 32.6% longer RT in children with HCP (1.35 ± 0.17 seconds) than children who were developing typically (0.91 ± 0.05 seconds). There was a significant group × arm interaction (P = .05). Post hoc analysis (P = .007) indicated that the RT of the affected arm of the children with HCP was slower (1.68 ± 0.26 seconds) than the performance of the nondominant arm of the children who were developing typically (0.97 ± 0.1 seconds). There was no significant difference (P=0.1) between the unaffected arm of children with HCP (1.02 ± 0.13 seconds) and the dominant arm of children who were developing typically (0.85 ± 0.04 seconds).

NHPT

Pre- and Post-HABIT. There was no pre/post main effect (P = .1; pre = 112.86 ± 11.41 seconds; post = 86.50 ± 11.41 seconds). However, there was a significant arm main effect, indicating that the children with HCP took longer to complete the NHPT with the affected arm (affected =130.64 ± 12.10 seconds; unaffected arm = 68.72 ± 10.67 seconds; P = .001).

Post-HABIT and Developing Typically. There was a group main effect (P = .001) indicating the children with HCP (86.50 ± 11.41 seconds) took longer to complete the NHPT than the children who were developing typically (41.03 ± 4.37 seconds). There was a significant group × arm interaction (P = .001). Post hoc analysis indicated a significant difference (P = .001) in NHPT time between the nondominant arm of children who were developing typically (39.46 ± 2.88 seconds) and the affected arm of children with HCP (110.0 ± 17.92 seconds). Similarly, there was a significant difference (P = .02) between the dominant arm of children who were developing typically (42.60 ± 2.62 seconds) and the unaffected arm of children with HCP (63.0 ± 10.10 seconds).

BBT

Pre- and Post-HABIT. The pre/post main effect was not significant (P = .5; pre: 14.8 ± 2.4 blocks; post: 17.1 ± 2.4 blocks). However, there was a significant arm main effect (P = .01), with 43.5% fewer number of blocks moved with the affected (11.55 ± 2.01 blocks) than with the unaffected arm (20.44 ± 2.47 blocks).

Post-HABIT and Developing Typically. There was a significant group main effect (P = .001), with 48.2% fewer blocks moved by children with HCP (17.11 ± 2.46 blocks) than by children who were developing typically (33.03 ± 1.27 blocks).

DISCUSSION

The results of this investigation suggest that HABIT has the potential to improve the activity of PFC while children with HCP perform the action planning of a shape-matching motor task. Notably, the decrease in PFC activation paralleled the overall improvements seen in the bimanual coordination and motor function of the affected arm. Altogether these preliminary results suggest that HABIT has the potential to improve not only the motor actions of children with HCP but also the action-planning capabilities.

The reduction in PFC activation after HABIT implies the children had an improvement in the allocation of attentional resources for simultaneously processing the cognitive (attention, memory, and information processing) and motor demands. The PFC plays a crucial role in modulating attentional demands of new motor tasks28 and enhances activation during motor tasks that demand attention.12 We suggest that the attenuation of the PFC activation may be associated with (1) reduction in attention to the motor task, which could be due to the practice-related “automaticity” of the motor tasks after the HABIT intervention29; (2) improvement in the functional cost of sharing cognitive and motor resources; and/or (3) increased neuronal efficiency of the neuronal circuits required for modulating the planning and control of goal-directed actions. These possible explanations corroborate with prior fMRI study that demonstrated similar attenuation in PFC activation following the practice of motor tasks.30

Our results also demonstrated improvement in bimanual coordination, manual dexterity, RT, a greater number of attempts to match shapes, and fewer shape-matching errors after HABIT. These results support that the children learned to better plan and execute their motor actions. Notably, the AHA scores exceeded the minimal clinically important difference of 5 units.27 Altogether, these promising behavioral improvements are consistent with other HABIT studies.17 Furthermore, our results suggests that 50 hours of HABIT is efficacious for improving the bimanual coordination and hand function of young children with HCP.

Remarkably, the PFC activity for the children with HCP after HABIT was not different from what was seen in the children who were developing typically. This implies that the PFC activity of the children with HCP may have become typical after HABIT. Whether the improved cortical activity is related to the production of more efficient motor actions or cognitive processing is debatable. If the motor actions organized by the sensorimotor cortices became more fluid, it may have freed up resources for the concurrent cognitive processing. Alternatively, the cognitive processing alone may have improved since many of the HABIT tasks emphasized problem-solving. These alternative possibilities were not addressed in this study since the fNIRS optodes were positioned to only measure the PFC. In addition, we did not have electromyographic or kinesiological data to measure the performance of the musculoskeletal system.

One of the limitations of the present study is the lack of a control group that received either other forms of alternative intensive therapy or conventional therapy, which would have enhanced our understanding of changes in PFC activation specific to particular therapies. A control group would also have enhanced understanding of our claim that HABIT improves planning capacity in children with HCP and is specific to the HABIT intervention, or whether this improvement is secondary to motor skill acquisition. These limitations should be addressed in future studies directed at understanding the effects of interventions on improving action-planning deficits seen in children with HCP.

CONCLUSION

Fifty hours of HABIT appears to be a promising intervention for improving the action planning of young children with HCP. This is supported by the improved bimanual coordination and function of the affected arm after HABIT. Our fNIRS analysis suggests that these improvements might be partially driven by the enhanced neural efficiency of the PFC. Based on our results, we suggest that pediatric physical therapists consider the possibility that the impaired motor actions seen in children with HCP may be related to altered contribution of the PFC to the formulation of the action plan.

ACKNOWLEDGMENTS

We thank physical therapists Amy Beyersdorf, Susan Dickson-Matsunami, Brianne Walbrecht; occupational therapist, Mindy Oetter; and all volunteers for their contribution to the HABIT camp.

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Keywords:

action-planning; bimanual coordination; cognition; fNIRS; motor planning

© 2018 Academy of Pediatric Physical Therapy of the American Physical Therapy Association