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A kinematic analysis of manual aiming control on euthymic bipolar disorder
Psychiatry Research 208 (2013) 140–144
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A kinematic analysis of manual aiming control on euthymic bipolar disorder Guilherme M. Lage a,n, Leandro F. Malloy-Diniz b, Fernando S. Neves b, Lı´via G. Gallo a, Alexandre S. Valentini a, Humberto Corrˆea b a
~ Fı´sica da Universidade FUMEC, Rua Cobre 200, Bairro Cruzeiro, 30310-190, Faculdade de Ciˆencias Humanas, Sociais e da Departamento de Educac- ao ´ de, Belo Horizonte, Minas Gerais, Brazil Sau b ´ de mental, Universidade Federal de Minas Gerais, Faculdade de Medicina, Avenida Alfredo Balena, 190, sala 240, Santa Efigˆenia, Departamento de Sau 30130-100, Belo Horizonte, Minas Gerais, Brazil
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 April 2012 Received in revised form 8 August 2012 Accepted 25 September 2012
Motor deficits in tasks that require force steadiness or scaling of movement velocity have been found in bipolar disorder (BD). A potential explanation for these results is the abnormal functioning of the frontostriatal circuitry. We designed this study to investigate the possible impairments in a manual aiming task. Participants comprised 15 euthymic BD patients and 15 healthy controls, who performed 100 trials of a goal-directed manual movement with a non-inking pen on a digitizing tablet. Four different conditions of execution were required. The control condition appeared on the computer screen in 70% of the trials, and the other three conditions, (a) distractor, (b) inhibition of response and (c) higher index of difficulty, each appeared in 10% of the trials. Compared to the controls, the BD patients were less fluent in their movements, relied more heavily on visual feedback to control their manual movements and presented a lower spatial accuracy. We found that motor deficits in euthymic BD were observed in the kinematic analysis of manual aiming. Our findings are consistent with the hypothesis of abnormal functioning of the frontostriatal circuitry in euthymic BD. & 2012 Elsevier Ireland Ltd. All rights reserved.
Keywords: Movement disorders Psychomotor performance Dyskinesias Basal ganglia Bipolar disorder
1. Introduction Motor deficits are an important phenomenological facet observed in many psychiatric illnesses, including bipolar disorder (BD). A potential explanation of the disabilities found in the control of voluntary movements in BD patients is the abnormal functioning of brain circuitry involving the basal ganglia (Lohr and Caligiuri, 2006; Lee et al., 2008). For instance, increased activation of both the left and right striatum (caudate and putamen) has been observed (Marchand et al., 2007). Anatomical abnormalities (Noga et al., 2001; DelBello et al., 2004) are exemplified by the enlargement of the caudate and putamen in bipolar patients when compared to healthy subjects (Aylward et al., 1994; DelBello et al., 2004). The cortical areas interconnected with the striatum, such as the dorsolateral prefrontal cortex, cingulate cortex, primary motor cortex and somatosensory cortex, also show increased activation indicating abnormal function in the frontostriatal circuitry (Marchand et al., 2007). Taking into account that disturbances in the brain circuitry involving the basal ganglia have an important effect on motor control in BD (Lohr and Caligiuri, 2006), it is expected that BD patients have some of the motor impairments n
Corresponding author. Tel.: þ55 31 32283000. E-mail address: [email protected] (G.M. Lage). 0165-1781/$ - see front matter & 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2012.09.046
found in patients with basal ganglia disorders, such as those with Parkinson’s and Huntington’s diseases. There is some evidence in the literature that supports this assumption, demonstrating that BD patients, for example, exhibit poorer performance in tasks that require force steadiness or scaling of movement velocity to different distances (Lohr and Caligiuri, 2006). Although previous studies have specifically investigated motor abnormalities in BD (Heninger and Kirstein, 1977; Klein et al., 1992; Lohr and Caligiuri, 2006; Martino et al., 2008), there is very little research on this topic. For example, to our knowledge, no studies have examined goal-directed manual aiming movements in BD using a kinematical analysis. The manual aiming movements performed with visual feedback include an initial impulse component that roughly approaches the target by an open-loop control and a final homing component under a closed-loop control, with visually guided adjustments in the last portion of the movement (Woodworth, 1899). A common kinematic marker used to distinguish between the two components of the movement is peak velocity. The time interval preceding the peak velocity, the initial impulse, reflects the preprogrammed characteristics of the movement. After the peak velocity is initiated, an error correction phase or final homing component occurs (Khan et al., 2006). We designed this study to evaluate motor impairments in manual aiming in euthymic BD patients. Although euthymia is
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characterized by the absence of significant clinical symptoms, neuropsychological impairments, such as inhibitory control, are frequently observed in euthymic patients (Kaladjian et al., 2009). Motor impairments, for example, in the sequencing of complex movements, have also been observed in euthymic patients (Negash et al., 2004). Therefore, it is possible that motor impairments in aiming movements are also present in these patients. We hypothesized that compared to healthy control subjects bipolar patients would present slower movements, lower peak velocities and a greater dysfluency of movements. This assumption is based on the view that these measures of motor performance are affected by the abnormal functioning of brain circuitry involving the basal ganglia (Tucha et al., 2006). In addition, we aimed to investigate whether these abnormalities were influenced by different sensory–motor components of the task. Thus, we investigated the motor control of euthymic BD patients in their ability (1) to resist distraction and stay on task, (2) to inhibit a prepotent response, and (3) to adapt to a higher spatial and temporal demand of the task.
2. Material and methods 2.1. Subjects Fifteen euthymic BD patients (12 women and 3 men; mean age ¼40.6 7 11.7 years; 11.7 73.2 years of formal education) were recruited from the Nu´cleo de Transtornos Afetivos (Center for Affective Disorders) from the Psychiatric Service of the Hospital das Clı´nicas, Universidade Federal de Minas Gerais. The inclusion criteria included a BD diagnosis according to the DSM-IV and was determined using a structured interview (Mini International Neuropsychiatric Interview (MINI) Plus). The patients were diagnosed as euthymic at the time of the neuropsychological assessment. The Brazilian version of the Beck Depression Inventory (BDI) (Gorestein and Andrade, 1988) and the Young Mania Rating Scale (YMRS) (Vilela et al., 2005) were used. The subjects were classified as euthymic if they had both a BDI score lower than 12 points and a YMRS score lower than 13. An additional inclusion criterion was a score lower than 0.65 on the Simpson and Angus Scale (Janno et al., 2005), which was used for the assessment of neuropleptic-induced Parkinsonism symptoms. Fourteen bipolar subjects were taking psychiatric medication at the time of the assessment. The most common medications were antidepressants (n¼ 8), anticonvulsive mood stabilizers (n¼ 8), second-generation antipsychotics (n¼ 2), lithium (n¼4) and anxiolitics (n¼ 5). The control group consisted of 15 subjects (12 women and 3 men; mean age¼ 36.1 79.9 years; 12.9 7 2 years of formal education) recruited from the community. No subject had any history of an Axis 1 psychiatric illness according to the DSM-IV criteria, as assessed by the MINI-Plus. In both of the groups, all of the participants were right-handed (mean laterality quotient¼ 85.3; Edinburgh Handedness Inventory; Oldfield, 1971) and had normal or corrected-to-normal visual acuity in both of their eyes. A local ethics committee approved of all of the procedures, and the subjects signed an informed consent form after receiving a full explanation of the study. 2.2. Apparatus The manual aiming movements were quantified using a commercial digitizing tablet and the MovAlyzeR software (NeuroScript, LLC; Tempe, AZ, USA). We used a non-inking pen with a Wacom Intuos 3 digitizing tablet (30.4 cm 30.4 cm, RMS accuracy 0.01 cm). The sampling rate was 200 Hz. The tablet was attached to an MS Windows laptop computer (15.400 diagonal widescreen) running the MovAlyzeR software. The distance traveled by the non-inking pen on the tablet was proportional to the distance traveled by the cursor on the computer screen. 2.3. Assessment The evaluations of symptoms of depression, mania and neuropleptic-induced Parkinsonism were conducted on the day of the motor performance evaluation. The motor task used by Lage et al. (2012) was applied. The motor task consisted of the execution of a goal-directed manual movement with a non-inking pen on a digitizing tablet. The participants were comfortably seated in a chair in front of the digitizing tablet, on which they were required to make fast and accurate strokes with the pen from the home position to the target. These strokes were displayed in real time on the laptop monitor. A continuous red trace of the pen movement was
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displayed in real time, indicating to the performer the trajectory of his/her stroke. The trial started with a presentation of both the home position and a filled-in green circle target to be pointed to (the pre-cue) on the monitor. The participant placed the cursor on the home position during this pre-cue period. Then, the green target disappeared from the screen, and in a random interval ranging from 2 to 3 s, the target turned into an imperative stimulus that would instruct the patient to ‘‘go’’; at this point, the recording of the trial began. The participant was instructed to complete the movement to the target as quickly and as accurately as possible. This was the control condition that appeared in 70% of the trials. The other three conditions each appeared in only 10% of the trials. In the distractor condition, a filled-in yellow circle appeared instead of the green target (stimulus of the control condition). The goal of the distractor condition was identical to the control condition; the unique difference was the stimulus color. In the inhibition of response condition, a filled-in red circle appeared instead of the green target (stimulus of the control condition) indicating ‘‘stop’’. Under this condition, the participant was instructed to not move the pen. The last condition was the higher index of difficulty condition. In the higher index of difficulty condition, a filled-in green circle appeared similarly to the stimulus of the control condition. However, the size and the position of the green target were changed compared to the control condition. The goal of executing the movement to the target as quickly and as accurately as possible was still the same. The participant was informed that the endpoint of the continuous red trace should achieve, at least, the margins of the target. In the control, distractor and inhibition of response conditions, the target (1 cm in diameter) was presented at the same distance (19 cm center-to-center) and angle (451 from the upper right of the screen) from the home position, resulting in an index of difficulty of 5.2 bits (Fitts, 1954). In the higher index of difficulty condition, the target presented had a smaller diameter (0.5 cm) and a longer distance (20 cm center-to-center) from the home position, as well as an angle of 351 from the upper right of the screen. The index of difficulty for this condition was 6.3 bits. The values of these indexes of difficulty were previously defined by Couto et al. (2010) and Lage et al. (2012) and calculated using the following formula: Log2 ð2A=WÞ, where A is the amplitude of the movement and W is the target width.
2.4. Data reduction and dependent variables The pen movements were low-pass-filtered at 12 Hz using a Fast Fourier Transform (FFT) and were differentiated to yield estimates of the velocity and acceleration curves. A stroke was segmented into primary and secondary submovements by the first negative-to-positive zero crossing after the absolute peak velocity in the acceleration profile. The primary submovement refers to the initial part of the movement, the preprogrammed phase, and the secondary submovement refers to the online controlled phase (Lage et al., 2012). The performance measures examined were as follows: (1) reaction time, (2) movement time, (3) scores of incorrect hits to the target (0 if hit and 1 if missed) and (4) scores of response inhibition errors (0 if ‘‘stop’’ and 1 if ‘‘go’’). The reaction time was the time in seconds from the beginning of the imperative stimulus (the recording started with the presentation of the imperative stimulus) until the beginning of the stroke (beginning of the segmentation point). The beginning and the end of the movement time were the first and last sample, respectively, where the absolute vertical velocity exceeded or fell below 5% of the absolute peak velocity and reached the instrument noise level. The number of incorrect hits was used to evaluate the spatial accuracy. An incorrect hit was detected when the movement endpoint did not achieve, at least, the diameter margins defined from the center of the target (1 cm in both control and distractor conditions and 0.5 cm in the higher index of difficulty condition). The error of response inhibition occurred when a red target appeared and the movement was registered (Lage et al., 2012). The kinematic measures analyzed were as follows: (1) peak velocity, (2) relative time to peak velocity, (3) normalized jerk averaged (a measure of smoothness, fluency) and (4) number of discontinuities in the acceleration of the secondary submovement. The duration of the primary submovement and peak velocity were measures related to the preprogramming part of the movement (Khan et al., 2006). The primary submovement was considered from the movement onset to the first negative-to-positive point (or second zero-crossing) of the acceleration profile after the peak velocity (Caligiuri et al., 2010). The secondary submovement(s) are subsequent zero-crossings in the acceleration profile. Thus, the number of discontinuities in the acceleration of the secondary submovement reflect online modification to the movement trajectory based on sensory or feed-forward information regarding the movement error (Mieschke et al., 2001). The relative time to peak velocity measure reflects the type of strategy involved in the planning and execution of the movements. A high relative time to peak velocity indicates an efficient strategy of the motor system, in which a long initial impulse home, nearest to the target, reduces time and energy expenditures involved in the corrective process. The aiming smoothness was quantified by calculating the normalized jerk averaged per stroke. The normalized jerk is unitless because it is normalized for the stroke duration and
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the length. It was calculated using the following formula (Teulings et al., 1997): Oð0:5S2 ðjerkðtÞÞ5 duration=2 lengthÞ: The estimation of handwriting performance and kinematic variables was conducted automatically by the MovAlyzeR software (Saltuklaroglu et al., 2009).
2.5. Analysis The means were based on 10 trials for the distractor, inhibition of response and higher index of difficulty conditions and were calculated for all of the dependent measures. For the control condition, the means were based on 70 trials and were calculated for all of the measures (Lage et al., 2012). The ShapiroWilk’s W test revealed that in the control condition, the movement time, peak velocity and relative time to peak velocity violated the assumption of a normal distribution. In the distractor condition, the movement time and relative time to peak velocity violated the assumption of a normal distribution. In the higher index of difficulty condition, the movement time, peak velocity, relative time to peak velocity and normalized jerk violated the assumption of a normal distribution. A logarithmic transformation (log 10) and a square root transformation were performed for all of the data that violated the assumption of a normal distribution. In all of the conditions of execution, the movement time data were normalized by the logarithmic transformation. Other dependent variables were not normalized. Therefore, Student’s t-tests were used to analyze the normally distributed data and Mann–Whitney U tests were used for the non-normally distributed data. Chi-squared tests were conducted to analyze the nominal data: (a) scores of incorrect hits to the target and (b) scores of the response inhibition errors. A significant difference at level of 0.05 was adopted for all of the statistical analyses. The effect size was calculated using Cohen’s formula (Cohen, 1988) in the parametric analyses and Cliff’s d formula (Cliff, 1993) in the non-parametric analyses.
3.2. Distractor condition The analysis of the data indicated that the BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.33, po0.001), higher levels of the normalized jerk averaged [t(28)¼3.26, po0.001] and number of incorrect hits (w2 ¼12.2, po0.001) when compared to the control subjects. All the other comparisons were not significant (Table 2).
3.3. Higher index of difficulty condition The analysis of the data indicated that the BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.25, po0.01), higher levels of the normalized jerk averaged (Z¼3.17, po0.01) and number of incorrect hits (w2 ¼7.4, po0.01) when compared to the control subjects. All of the other comparisons were not significant (Table 3). The measures of movement time and the number of discontinuities in the acceleration of the secondary submovement presented a marginal difference (p¼ 0.07 for each measure).
3.4. Response inhibition error The analysis of the data indicated a tendency of BD patients to present a higher number of errors in the response inhibition (n ¼57) than the control participants (n¼39) (w2 ¼3.3, p¼0.06). The effect size calculated was 0.24.
3. Results The Mann–Whitney U test did not indicate a significant difference for age (Z¼1.16, p¼0.24) and years of formal education (Z¼ 1.61, p¼0.10). 3.1. Control condition The analysis of the data indicated that BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.50, po0.001), (2) higher levels of normalized jerk averaged [t(28)¼3.15, po0.01] and number of incorrect hits (w2 ¼60.3, po0.001) when compared to the control subjects. All the other comparisons were not significant (Table 1). With regard to our initial hypotheses, bipolar patients presented greater dysfluency of movements, but did not present slower movements and lower levels of peak velocities.
Table 1 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the control condition; the results of the Student’s t-tests, Mann–Whitney U tests and Chi-squared test; and the effect size results. Measure
Groups
Value
p
Effect size
3.5. Analysis without the unmedicated patient Despite evidence indicating that motor impairment in BD is independent of pharmacotherapy (Lohr and Caligiuri, 2006) and although we adopted an inclusion criterion to avoid the analysis of patients with neuropleptic-induced parkinsonism symptoms, we reanalyzed our data without the unmedicated patient to observe if medication was an influencing factor. Thus, we conducted again all statistical analysis, exactly as described in Section 2, but without the unmedicated patient. The results, in terms of significant differences, were exactly the same for: (a) age, (b) years of education and (c) motor performance, that is, the analysis with an unmedicated patient did not affect the results.
Table 2 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the distractor condition; the results of the Student’s t-tests, Mann–Whitney U tests and Chi-squared test; and the effect size results. Measure
Bipolar disorder Control RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND a
0.446 70.07 1.26 70.17a 439b 24.75 75.34 31.8 78 151.05 756.8 3.29 70.88
0.473 70.10 1.13 70.24a 237b 27.29 7 13.01 54.1 716 967 36.42 2.84 70.64
t ¼ 0.80 t ¼1.66 w2 ¼ 60.3 Z¼ 0.06 Z¼ 3.50 t ¼3.15 t ¼1.58
n.s. n.s. po 0.001 n.s. po 0.001 po 0.01 n.s.
0.31 0.62 0.54 0.01 0.75 1.15 0.58
The data not transformed by the square root transformation. Total frequency of errors; RT ¼ reaction time; MT¼ movement time; IH¼ incorrect hits; PV ¼peak velocity; RTPV¼ relative time to achieve peak velocity; NJA ¼normalized jerk averaged; ND¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼ not significant. b
RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND a
Groups Bipolar disorder
Control
0.441 7 06 1.25 7 21a 64b 24.83 7 5.70 31.8 7 9 163.597 74.2 3.40 7 1.00
0.458 7 0.11 1.15 7 24a 30b 26.71 7 13.03 54.4 7 18 93.06 7 38.5 2.92 7 0.87
Value
p
Effect size
t¼ 0.66 t¼ 1.15 w2 ¼ 12.2 t¼ 0.43 Z¼ 3.33 t¼ 3.26 t¼ 1.40
n.s. n.s. po 001 n.s. po 001 po 001 n.s.
0.19 0.44 0.57 0.90 1.58 1.19 0.51
The data not transformed by the square root transformation. The total frequency of errors; RT¼ reaction time; MT¼ movement time; IH¼ incorrect hits; PV ¼ peak velocity; RTPV¼ relative time to achieve peak velocity; NJA ¼normalized jerk averaged; ND ¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼ not significant. b
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Table 3 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the higher index of difficulty condition; the results of Student’s t-tests, Mann-Whitney U tests and Chi-squared test; and the effect size results. Measure
Groups
Value
p
Effect size
t¼ 0.83 t¼ 1.84 w2 ¼ 7.4 Z¼ 0.26 Z¼ 3.25 Z¼ 3.17 t¼ 1.87
n.s. n.s. p o 0.01 n.s. p o 0.001 p o 0.01 n.s.
0.32 0.64 0.55 0.06 1.59 0.68 0.69
Bipolar disorder Control RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND
0.432 7 0.09 1.26 7 0.19a 110b 26.11 7 5.55 31.4 7 11 149.54 779.4 3.33 7 0.95
0.461 70.09 1.12 70.25a 73b 28.74 7 14.92 56.2 719 85.12 7 33.1 2.70 70.86
a
The data not transformed by the square root transformation; The total frequency of the errors; RT¼ reaction time; MT ¼movement time; IH¼ incorrect hits; PV ¼peak velocity; RTPV ¼relative time to achieve peak velocity; NJA ¼ normalized jerk averaged; ND¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼not significant. b
4. Discussion We examined manual aiming control in euthymic BD patients and hypothesized that BD patients would present slower movements, fewer peak velocity and greater normalized jerk averaged (dysfluency) measures than the healthy subjects. Our hypothesis was partially confirmed because BD patients only presented more dysfluent movements than the healthy controls. In addition, we found that the BD patients spent less time achieving the peak velocity and were less accurate than the controls. The dysfluency in movement indicates an abnormal function of the brain circuitry involving the basal ganglia (Tucha et al., 2006). A decreased smoothness in the manual movements has been observed in patients with Parkinson’s (Teulings et al., 1997) and Huntington’s diseases (Lemay et al., 2008). Our main results showed that the BD patients were also less fluent in their fast aiming movements than the control individuals. This deficit was found independently of the sensory–motor demand of the task, that is, in all of the conditions of execution. This type of deficit appears to be the effect of the disproportionate accelerations and decelerations of independent muscle systems (Teulings et al., 1997). In contrast to studies that investigated motor control in neurological diseases, the normalized jerk averaged measure has not been frequently used as a dependent variable in psychiatric studies. To our knowledge, this is the first study to observe increased values of this kinematic variable in BD patients. Increased movement time and a decreased peak velocity reflect slowness of movement or bradykinesia, whereas increased normalized jerk averaged scores and a number of acceleration peaks are indicative of dysfluent movements or dyskinesia (Caligiuri et al., 2010). In euthymic patients, motor deficits in aiming appear to be more related to dyskinesia because our results did not show differences in motor performance, as measured by the movement time and peak velocity. We found only a marginal difference in the movement time (p¼0.07) in the higher index of difficulty condition, but regardless of condition of execution, euthymic BD patients were not slower in their movements than the control participants. A pattern of the results similar to the measure of movement time was also found in number of discontinuities in the acceleration of the secondary submovement. We found only a marginal difference (p¼0.07) in the higher index of difficulty condition. In all conditions of execution there was no difference between BD patients and healthy participants. We would expect significant difference between
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groups in the higher index of difficulty condition. Mavrogiorgou et al. (2001), for example, found differences in the quality of the manual motor control between obsessive-compulsive disorder (OCD) patients and controls only in the tasks that required more involvement of the motor system. While Mavrogiorgou et al. (2001) used a simple continuous circle-drawing task and three more complex handwriting tasks, we used a discrete aiming task with different sensory–motor requirements. Future studies should investigate how the characteristics of the tasks interfere in the quality of motor performance in euthymic BD patients. Another important finding from our study was the lower relative time to achieve peak velocity, as demonstrated by the BD patients in all of the conditions of execution. These results showed differences in the planning and execution of the aiming movements when compared to the controls. The time interval preceding the peak velocity, which is the initial impulse, reflects the preprogrammed characteristics of the movement. After the peak velocity was achieved, an error correction phase or final homing component occurs (Khan et al., 2006). The lower duration of the initial impulse, as demonstrated by the BD patients, was reflective of a motor control strategy that was based more on a closed-loop control, that is, a type of control that relies more on visual feedback to produce online corrections. In contrast, the healthy subjects preprogrammed their movements to achieve a longer initial impulse to home, nearest to the target, resulting in minimum error correction. The OCD patients also presented manual movements that were more based on closed-loop control (Mavrogiorgou et al., 2001), indicating that some motor deficits were very similar in psychiatric illnesses that exhibited abnormal function of circuitry involving the basal ganglia (Lohr and Caligiuri, 2006; Mavrogiorgou et al., 2001). Although the BD patients showed longer times in the error correction phase, they presented a higher frequency of incorrect hits to the target than the controls in all of the conditions of execution. It is possible that the low quality of accuracy is not only a consequence of the error correction phase but also of the preprogrammed phase. For instance, Lohr and Caligiuri (2006) found that BD patients exhibited deficits related to velocity scaling in a manual task that involves an open-loop control, that is, a movement that is reliant on the motor commands that have been previously programmed. Further studies are required to address this question. An overall analysis of these results indicates that the BD patients (a) did not present specific deficits related to the distraction because no specific differences were found between the groups in the distractor condition, (b) tended to present deficits in the inhibition of a prepotent response and (c) tended to present specific deficits when a higher spatial and temporal condition was required. In conclusion, these findings indicate that motor deficits in euthymic BD patients can be observed in the kinematic analysis of manual aiming. Our main finding was the impairment in the movement fluency, which suggests abnormal functioning of the frontostriatal circuitry. The study of the manual aiming movements is functionally relevant, as numerous daily activities require the planning and execution of this type of movement. Further studies are necessary to investigate the effects of motor dysfunction in aiming movements that are performed daily and to determine whether the detection and monitoring of these motor deficits could be useful in a clinical setting.
Acknowledgment Support was provided by the Programa de Institutos Nacionais de Ciˆencia e Tecnologia (CNPq, MCT and FAPEMIG). We acknowledge the volunteers for their readiness to participate in our study.
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A kinematic analysis of manual aiming control on euthymic bipolar disorder Guilherme M. Lage a,n, Leandro F. Malloy-Diniz b, Fernando S. Neves b, Lı´via G. Gallo a, Alexandre S. Valentini a, Humberto Corrˆea b a
~ Fı´sica da Universidade FUMEC, Rua Cobre 200, Bairro Cruzeiro, 30310-190, Faculdade de Ciˆencias Humanas, Sociais e da Departamento de Educac- ao ´ de, Belo Horizonte, Minas Gerais, Brazil Sau b ´ de mental, Universidade Federal de Minas Gerais, Faculdade de Medicina, Avenida Alfredo Balena, 190, sala 240, Santa Efigˆenia, Departamento de Sau 30130-100, Belo Horizonte, Minas Gerais, Brazil
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 April 2012 Received in revised form 8 August 2012 Accepted 25 September 2012
Motor deficits in tasks that require force steadiness or scaling of movement velocity have been found in bipolar disorder (BD). A potential explanation for these results is the abnormal functioning of the frontostriatal circuitry. We designed this study to investigate the possible impairments in a manual aiming task. Participants comprised 15 euthymic BD patients and 15 healthy controls, who performed 100 trials of a goal-directed manual movement with a non-inking pen on a digitizing tablet. Four different conditions of execution were required. The control condition appeared on the computer screen in 70% of the trials, and the other three conditions, (a) distractor, (b) inhibition of response and (c) higher index of difficulty, each appeared in 10% of the trials. Compared to the controls, the BD patients were less fluent in their movements, relied more heavily on visual feedback to control their manual movements and presented a lower spatial accuracy. We found that motor deficits in euthymic BD were observed in the kinematic analysis of manual aiming. Our findings are consistent with the hypothesis of abnormal functioning of the frontostriatal circuitry in euthymic BD. & 2012 Elsevier Ireland Ltd. All rights reserved.
Keywords: Movement disorders Psychomotor performance Dyskinesias Basal ganglia Bipolar disorder
1. Introduction Motor deficits are an important phenomenological facet observed in many psychiatric illnesses, including bipolar disorder (BD). A potential explanation of the disabilities found in the control of voluntary movements in BD patients is the abnormal functioning of brain circuitry involving the basal ganglia (Lohr and Caligiuri, 2006; Lee et al., 2008). For instance, increased activation of both the left and right striatum (caudate and putamen) has been observed (Marchand et al., 2007). Anatomical abnormalities (Noga et al., 2001; DelBello et al., 2004) are exemplified by the enlargement of the caudate and putamen in bipolar patients when compared to healthy subjects (Aylward et al., 1994; DelBello et al., 2004). The cortical areas interconnected with the striatum, such as the dorsolateral prefrontal cortex, cingulate cortex, primary motor cortex and somatosensory cortex, also show increased activation indicating abnormal function in the frontostriatal circuitry (Marchand et al., 2007). Taking into account that disturbances in the brain circuitry involving the basal ganglia have an important effect on motor control in BD (Lohr and Caligiuri, 2006), it is expected that BD patients have some of the motor impairments n
Corresponding author. Tel.: þ55 31 32283000. E-mail address: [email protected] (G.M. Lage). 0165-1781/$ - see front matter & 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2012.09.046
found in patients with basal ganglia disorders, such as those with Parkinson’s and Huntington’s diseases. There is some evidence in the literature that supports this assumption, demonstrating that BD patients, for example, exhibit poorer performance in tasks that require force steadiness or scaling of movement velocity to different distances (Lohr and Caligiuri, 2006). Although previous studies have specifically investigated motor abnormalities in BD (Heninger and Kirstein, 1977; Klein et al., 1992; Lohr and Caligiuri, 2006; Martino et al., 2008), there is very little research on this topic. For example, to our knowledge, no studies have examined goal-directed manual aiming movements in BD using a kinematical analysis. The manual aiming movements performed with visual feedback include an initial impulse component that roughly approaches the target by an open-loop control and a final homing component under a closed-loop control, with visually guided adjustments in the last portion of the movement (Woodworth, 1899). A common kinematic marker used to distinguish between the two components of the movement is peak velocity. The time interval preceding the peak velocity, the initial impulse, reflects the preprogrammed characteristics of the movement. After the peak velocity is initiated, an error correction phase or final homing component occurs (Khan et al., 2006). We designed this study to evaluate motor impairments in manual aiming in euthymic BD patients. Although euthymia is
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characterized by the absence of significant clinical symptoms, neuropsychological impairments, such as inhibitory control, are frequently observed in euthymic patients (Kaladjian et al., 2009). Motor impairments, for example, in the sequencing of complex movements, have also been observed in euthymic patients (Negash et al., 2004). Therefore, it is possible that motor impairments in aiming movements are also present in these patients. We hypothesized that compared to healthy control subjects bipolar patients would present slower movements, lower peak velocities and a greater dysfluency of movements. This assumption is based on the view that these measures of motor performance are affected by the abnormal functioning of brain circuitry involving the basal ganglia (Tucha et al., 2006). In addition, we aimed to investigate whether these abnormalities were influenced by different sensory–motor components of the task. Thus, we investigated the motor control of euthymic BD patients in their ability (1) to resist distraction and stay on task, (2) to inhibit a prepotent response, and (3) to adapt to a higher spatial and temporal demand of the task.
2. Material and methods 2.1. Subjects Fifteen euthymic BD patients (12 women and 3 men; mean age ¼40.6 7 11.7 years; 11.7 73.2 years of formal education) were recruited from the Nu´cleo de Transtornos Afetivos (Center for Affective Disorders) from the Psychiatric Service of the Hospital das Clı´nicas, Universidade Federal de Minas Gerais. The inclusion criteria included a BD diagnosis according to the DSM-IV and was determined using a structured interview (Mini International Neuropsychiatric Interview (MINI) Plus). The patients were diagnosed as euthymic at the time of the neuropsychological assessment. The Brazilian version of the Beck Depression Inventory (BDI) (Gorestein and Andrade, 1988) and the Young Mania Rating Scale (YMRS) (Vilela et al., 2005) were used. The subjects were classified as euthymic if they had both a BDI score lower than 12 points and a YMRS score lower than 13. An additional inclusion criterion was a score lower than 0.65 on the Simpson and Angus Scale (Janno et al., 2005), which was used for the assessment of neuropleptic-induced Parkinsonism symptoms. Fourteen bipolar subjects were taking psychiatric medication at the time of the assessment. The most common medications were antidepressants (n¼ 8), anticonvulsive mood stabilizers (n¼ 8), second-generation antipsychotics (n¼ 2), lithium (n¼4) and anxiolitics (n¼ 5). The control group consisted of 15 subjects (12 women and 3 men; mean age¼ 36.1 79.9 years; 12.9 7 2 years of formal education) recruited from the community. No subject had any history of an Axis 1 psychiatric illness according to the DSM-IV criteria, as assessed by the MINI-Plus. In both of the groups, all of the participants were right-handed (mean laterality quotient¼ 85.3; Edinburgh Handedness Inventory; Oldfield, 1971) and had normal or corrected-to-normal visual acuity in both of their eyes. A local ethics committee approved of all of the procedures, and the subjects signed an informed consent form after receiving a full explanation of the study. 2.2. Apparatus The manual aiming movements were quantified using a commercial digitizing tablet and the MovAlyzeR software (NeuroScript, LLC; Tempe, AZ, USA). We used a non-inking pen with a Wacom Intuos 3 digitizing tablet (30.4 cm 30.4 cm, RMS accuracy 0.01 cm). The sampling rate was 200 Hz. The tablet was attached to an MS Windows laptop computer (15.400 diagonal widescreen) running the MovAlyzeR software. The distance traveled by the non-inking pen on the tablet was proportional to the distance traveled by the cursor on the computer screen. 2.3. Assessment The evaluations of symptoms of depression, mania and neuropleptic-induced Parkinsonism were conducted on the day of the motor performance evaluation. The motor task used by Lage et al. (2012) was applied. The motor task consisted of the execution of a goal-directed manual movement with a non-inking pen on a digitizing tablet. The participants were comfortably seated in a chair in front of the digitizing tablet, on which they were required to make fast and accurate strokes with the pen from the home position to the target. These strokes were displayed in real time on the laptop monitor. A continuous red trace of the pen movement was
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displayed in real time, indicating to the performer the trajectory of his/her stroke. The trial started with a presentation of both the home position and a filled-in green circle target to be pointed to (the pre-cue) on the monitor. The participant placed the cursor on the home position during this pre-cue period. Then, the green target disappeared from the screen, and in a random interval ranging from 2 to 3 s, the target turned into an imperative stimulus that would instruct the patient to ‘‘go’’; at this point, the recording of the trial began. The participant was instructed to complete the movement to the target as quickly and as accurately as possible. This was the control condition that appeared in 70% of the trials. The other three conditions each appeared in only 10% of the trials. In the distractor condition, a filled-in yellow circle appeared instead of the green target (stimulus of the control condition). The goal of the distractor condition was identical to the control condition; the unique difference was the stimulus color. In the inhibition of response condition, a filled-in red circle appeared instead of the green target (stimulus of the control condition) indicating ‘‘stop’’. Under this condition, the participant was instructed to not move the pen. The last condition was the higher index of difficulty condition. In the higher index of difficulty condition, a filled-in green circle appeared similarly to the stimulus of the control condition. However, the size and the position of the green target were changed compared to the control condition. The goal of executing the movement to the target as quickly and as accurately as possible was still the same. The participant was informed that the endpoint of the continuous red trace should achieve, at least, the margins of the target. In the control, distractor and inhibition of response conditions, the target (1 cm in diameter) was presented at the same distance (19 cm center-to-center) and angle (451 from the upper right of the screen) from the home position, resulting in an index of difficulty of 5.2 bits (Fitts, 1954). In the higher index of difficulty condition, the target presented had a smaller diameter (0.5 cm) and a longer distance (20 cm center-to-center) from the home position, as well as an angle of 351 from the upper right of the screen. The index of difficulty for this condition was 6.3 bits. The values of these indexes of difficulty were previously defined by Couto et al. (2010) and Lage et al. (2012) and calculated using the following formula: Log2 ð2A=WÞ, where A is the amplitude of the movement and W is the target width.
2.4. Data reduction and dependent variables The pen movements were low-pass-filtered at 12 Hz using a Fast Fourier Transform (FFT) and were differentiated to yield estimates of the velocity and acceleration curves. A stroke was segmented into primary and secondary submovements by the first negative-to-positive zero crossing after the absolute peak velocity in the acceleration profile. The primary submovement refers to the initial part of the movement, the preprogrammed phase, and the secondary submovement refers to the online controlled phase (Lage et al., 2012). The performance measures examined were as follows: (1) reaction time, (2) movement time, (3) scores of incorrect hits to the target (0 if hit and 1 if missed) and (4) scores of response inhibition errors (0 if ‘‘stop’’ and 1 if ‘‘go’’). The reaction time was the time in seconds from the beginning of the imperative stimulus (the recording started with the presentation of the imperative stimulus) until the beginning of the stroke (beginning of the segmentation point). The beginning and the end of the movement time were the first and last sample, respectively, where the absolute vertical velocity exceeded or fell below 5% of the absolute peak velocity and reached the instrument noise level. The number of incorrect hits was used to evaluate the spatial accuracy. An incorrect hit was detected when the movement endpoint did not achieve, at least, the diameter margins defined from the center of the target (1 cm in both control and distractor conditions and 0.5 cm in the higher index of difficulty condition). The error of response inhibition occurred when a red target appeared and the movement was registered (Lage et al., 2012). The kinematic measures analyzed were as follows: (1) peak velocity, (2) relative time to peak velocity, (3) normalized jerk averaged (a measure of smoothness, fluency) and (4) number of discontinuities in the acceleration of the secondary submovement. The duration of the primary submovement and peak velocity were measures related to the preprogramming part of the movement (Khan et al., 2006). The primary submovement was considered from the movement onset to the first negative-to-positive point (or second zero-crossing) of the acceleration profile after the peak velocity (Caligiuri et al., 2010). The secondary submovement(s) are subsequent zero-crossings in the acceleration profile. Thus, the number of discontinuities in the acceleration of the secondary submovement reflect online modification to the movement trajectory based on sensory or feed-forward information regarding the movement error (Mieschke et al., 2001). The relative time to peak velocity measure reflects the type of strategy involved in the planning and execution of the movements. A high relative time to peak velocity indicates an efficient strategy of the motor system, in which a long initial impulse home, nearest to the target, reduces time and energy expenditures involved in the corrective process. The aiming smoothness was quantified by calculating the normalized jerk averaged per stroke. The normalized jerk is unitless because it is normalized for the stroke duration and
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the length. It was calculated using the following formula (Teulings et al., 1997): Oð0:5S2 ðjerkðtÞÞ5 duration=2 lengthÞ: The estimation of handwriting performance and kinematic variables was conducted automatically by the MovAlyzeR software (Saltuklaroglu et al., 2009).
2.5. Analysis The means were based on 10 trials for the distractor, inhibition of response and higher index of difficulty conditions and were calculated for all of the dependent measures. For the control condition, the means were based on 70 trials and were calculated for all of the measures (Lage et al., 2012). The ShapiroWilk’s W test revealed that in the control condition, the movement time, peak velocity and relative time to peak velocity violated the assumption of a normal distribution. In the distractor condition, the movement time and relative time to peak velocity violated the assumption of a normal distribution. In the higher index of difficulty condition, the movement time, peak velocity, relative time to peak velocity and normalized jerk violated the assumption of a normal distribution. A logarithmic transformation (log 10) and a square root transformation were performed for all of the data that violated the assumption of a normal distribution. In all of the conditions of execution, the movement time data were normalized by the logarithmic transformation. Other dependent variables were not normalized. Therefore, Student’s t-tests were used to analyze the normally distributed data and Mann–Whitney U tests were used for the non-normally distributed data. Chi-squared tests were conducted to analyze the nominal data: (a) scores of incorrect hits to the target and (b) scores of the response inhibition errors. A significant difference at level of 0.05 was adopted for all of the statistical analyses. The effect size was calculated using Cohen’s formula (Cohen, 1988) in the parametric analyses and Cliff’s d formula (Cliff, 1993) in the non-parametric analyses.
3.2. Distractor condition The analysis of the data indicated that the BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.33, po0.001), higher levels of the normalized jerk averaged [t(28)¼3.26, po0.001] and number of incorrect hits (w2 ¼12.2, po0.001) when compared to the control subjects. All the other comparisons were not significant (Table 2).
3.3. Higher index of difficulty condition The analysis of the data indicated that the BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.25, po0.01), higher levels of the normalized jerk averaged (Z¼3.17, po0.01) and number of incorrect hits (w2 ¼7.4, po0.01) when compared to the control subjects. All of the other comparisons were not significant (Table 3). The measures of movement time and the number of discontinuities in the acceleration of the secondary submovement presented a marginal difference (p¼ 0.07 for each measure).
3.4. Response inhibition error The analysis of the data indicated a tendency of BD patients to present a higher number of errors in the response inhibition (n ¼57) than the control participants (n¼39) (w2 ¼3.3, p¼0.06). The effect size calculated was 0.24.
3. Results The Mann–Whitney U test did not indicate a significant difference for age (Z¼1.16, p¼0.24) and years of formal education (Z¼ 1.61, p¼0.10). 3.1. Control condition The analysis of the data indicated that BD patients presented (1) lower relative time to achieve peak velocity (Z¼ 3.50, po0.001), (2) higher levels of normalized jerk averaged [t(28)¼3.15, po0.01] and number of incorrect hits (w2 ¼60.3, po0.001) when compared to the control subjects. All the other comparisons were not significant (Table 1). With regard to our initial hypotheses, bipolar patients presented greater dysfluency of movements, but did not present slower movements and lower levels of peak velocities.
Table 1 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the control condition; the results of the Student’s t-tests, Mann–Whitney U tests and Chi-squared test; and the effect size results. Measure
Groups
Value
p
Effect size
3.5. Analysis without the unmedicated patient Despite evidence indicating that motor impairment in BD is independent of pharmacotherapy (Lohr and Caligiuri, 2006) and although we adopted an inclusion criterion to avoid the analysis of patients with neuropleptic-induced parkinsonism symptoms, we reanalyzed our data without the unmedicated patient to observe if medication was an influencing factor. Thus, we conducted again all statistical analysis, exactly as described in Section 2, but without the unmedicated patient. The results, in terms of significant differences, were exactly the same for: (a) age, (b) years of education and (c) motor performance, that is, the analysis with an unmedicated patient did not affect the results.
Table 2 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the distractor condition; the results of the Student’s t-tests, Mann–Whitney U tests and Chi-squared test; and the effect size results. Measure
Bipolar disorder Control RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND a
0.446 70.07 1.26 70.17a 439b 24.75 75.34 31.8 78 151.05 756.8 3.29 70.88
0.473 70.10 1.13 70.24a 237b 27.29 7 13.01 54.1 716 967 36.42 2.84 70.64
t ¼ 0.80 t ¼1.66 w2 ¼ 60.3 Z¼ 0.06 Z¼ 3.50 t ¼3.15 t ¼1.58
n.s. n.s. po 0.001 n.s. po 0.001 po 0.01 n.s.
0.31 0.62 0.54 0.01 0.75 1.15 0.58
The data not transformed by the square root transformation. Total frequency of errors; RT ¼ reaction time; MT¼ movement time; IH¼ incorrect hits; PV ¼peak velocity; RTPV¼ relative time to achieve peak velocity; NJA ¼normalized jerk averaged; ND¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼ not significant. b
RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND a
Groups Bipolar disorder
Control
0.441 7 06 1.25 7 21a 64b 24.83 7 5.70 31.8 7 9 163.597 74.2 3.40 7 1.00
0.458 7 0.11 1.15 7 24a 30b 26.71 7 13.03 54.4 7 18 93.06 7 38.5 2.92 7 0.87
Value
p
Effect size
t¼ 0.66 t¼ 1.15 w2 ¼ 12.2 t¼ 0.43 Z¼ 3.33 t¼ 3.26 t¼ 1.40
n.s. n.s. po 001 n.s. po 001 po 001 n.s.
0.19 0.44 0.57 0.90 1.58 1.19 0.51
The data not transformed by the square root transformation. The total frequency of errors; RT¼ reaction time; MT¼ movement time; IH¼ incorrect hits; PV ¼ peak velocity; RTPV¼ relative time to achieve peak velocity; NJA ¼normalized jerk averaged; ND ¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼ not significant. b
G.M. Lage et al. / Psychiatry Research 208 (2013) 140–144
Table 3 The means and standard deviations of the bipolar disorder and control groups on the dependent measures obtained in the higher index of difficulty condition; the results of Student’s t-tests, Mann-Whitney U tests and Chi-squared test; and the effect size results. Measure
Groups
Value
p
Effect size
t¼ 0.83 t¼ 1.84 w2 ¼ 7.4 Z¼ 0.26 Z¼ 3.25 Z¼ 3.17 t¼ 1.87
n.s. n.s. p o 0.01 n.s. p o 0.001 p o 0.01 n.s.
0.32 0.64 0.55 0.06 1.59 0.68 0.69
Bipolar disorder Control RT (s) MT (s) IH (%) PV (cm/s) RTPV (%) NJA ND
0.432 7 0.09 1.26 7 0.19a 110b 26.11 7 5.55 31.4 7 11 149.54 779.4 3.33 7 0.95
0.461 70.09 1.12 70.25a 73b 28.74 7 14.92 56.2 719 85.12 7 33.1 2.70 70.86
a
The data not transformed by the square root transformation; The total frequency of the errors; RT¼ reaction time; MT ¼movement time; IH¼ incorrect hits; PV ¼peak velocity; RTPV ¼relative time to achieve peak velocity; NJA ¼ normalized jerk averaged; ND¼ number of discontinuities in the acceleration of the secondary submovement; n.s. ¼not significant. b
4. Discussion We examined manual aiming control in euthymic BD patients and hypothesized that BD patients would present slower movements, fewer peak velocity and greater normalized jerk averaged (dysfluency) measures than the healthy subjects. Our hypothesis was partially confirmed because BD patients only presented more dysfluent movements than the healthy controls. In addition, we found that the BD patients spent less time achieving the peak velocity and were less accurate than the controls. The dysfluency in movement indicates an abnormal function of the brain circuitry involving the basal ganglia (Tucha et al., 2006). A decreased smoothness in the manual movements has been observed in patients with Parkinson’s (Teulings et al., 1997) and Huntington’s diseases (Lemay et al., 2008). Our main results showed that the BD patients were also less fluent in their fast aiming movements than the control individuals. This deficit was found independently of the sensory–motor demand of the task, that is, in all of the conditions of execution. This type of deficit appears to be the effect of the disproportionate accelerations and decelerations of independent muscle systems (Teulings et al., 1997). In contrast to studies that investigated motor control in neurological diseases, the normalized jerk averaged measure has not been frequently used as a dependent variable in psychiatric studies. To our knowledge, this is the first study to observe increased values of this kinematic variable in BD patients. Increased movement time and a decreased peak velocity reflect slowness of movement or bradykinesia, whereas increased normalized jerk averaged scores and a number of acceleration peaks are indicative of dysfluent movements or dyskinesia (Caligiuri et al., 2010). In euthymic patients, motor deficits in aiming appear to be more related to dyskinesia because our results did not show differences in motor performance, as measured by the movement time and peak velocity. We found only a marginal difference in the movement time (p¼0.07) in the higher index of difficulty condition, but regardless of condition of execution, euthymic BD patients were not slower in their movements than the control participants. A pattern of the results similar to the measure of movement time was also found in number of discontinuities in the acceleration of the secondary submovement. We found only a marginal difference (p¼0.07) in the higher index of difficulty condition. In all conditions of execution there was no difference between BD patients and healthy participants. We would expect significant difference between
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groups in the higher index of difficulty condition. Mavrogiorgou et al. (2001), for example, found differences in the quality of the manual motor control between obsessive-compulsive disorder (OCD) patients and controls only in the tasks that required more involvement of the motor system. While Mavrogiorgou et al. (2001) used a simple continuous circle-drawing task and three more complex handwriting tasks, we used a discrete aiming task with different sensory–motor requirements. Future studies should investigate how the characteristics of the tasks interfere in the quality of motor performance in euthymic BD patients. Another important finding from our study was the lower relative time to achieve peak velocity, as demonstrated by the BD patients in all of the conditions of execution. These results showed differences in the planning and execution of the aiming movements when compared to the controls. The time interval preceding the peak velocity, which is the initial impulse, reflects the preprogrammed characteristics of the movement. After the peak velocity was achieved, an error correction phase or final homing component occurs (Khan et al., 2006). The lower duration of the initial impulse, as demonstrated by the BD patients, was reflective of a motor control strategy that was based more on a closed-loop control, that is, a type of control that relies more on visual feedback to produce online corrections. In contrast, the healthy subjects preprogrammed their movements to achieve a longer initial impulse to home, nearest to the target, resulting in minimum error correction. The OCD patients also presented manual movements that were more based on closed-loop control (Mavrogiorgou et al., 2001), indicating that some motor deficits were very similar in psychiatric illnesses that exhibited abnormal function of circuitry involving the basal ganglia (Lohr and Caligiuri, 2006; Mavrogiorgou et al., 2001). Although the BD patients showed longer times in the error correction phase, they presented a higher frequency of incorrect hits to the target than the controls in all of the conditions of execution. It is possible that the low quality of accuracy is not only a consequence of the error correction phase but also of the preprogrammed phase. For instance, Lohr and Caligiuri (2006) found that BD patients exhibited deficits related to velocity scaling in a manual task that involves an open-loop control, that is, a movement that is reliant on the motor commands that have been previously programmed. Further studies are required to address this question. An overall analysis of these results indicates that the BD patients (a) did not present specific deficits related to the distraction because no specific differences were found between the groups in the distractor condition, (b) tended to present deficits in the inhibition of a prepotent response and (c) tended to present specific deficits when a higher spatial and temporal condition was required. In conclusion, these findings indicate that motor deficits in euthymic BD patients can be observed in the kinematic analysis of manual aiming. Our main finding was the impairment in the movement fluency, which suggests abnormal functioning of the frontostriatal circuitry. The study of the manual aiming movements is functionally relevant, as numerous daily activities require the planning and execution of this type of movement. Further studies are necessary to investigate the effects of motor dysfunction in aiming movements that are performed daily and to determine whether the detection and monitoring of these motor deficits could be useful in a clinical setting.
Acknowledgment Support was provided by the Programa de Institutos Nacionais de Ciˆencia e Tecnologia (CNPq, MCT and FAPEMIG). We acknowledge the volunteers for their readiness to participate in our study.
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