A paradigm for emulating the early learning stage of handwriting: Performance comparison between healthy controls and Parkinson’s disease patients in drawing loop shapes

Highlights

• We present a new paradigm for simulating the early learning stage of stroke sequences.

• Subjects were asked to draw the same shape using familiar and unfamiliar motor plans.

• We show that the paradigm elicits non-automated movements in healthy subjects.

• Healthy controls using unfamiliar motor plans show performance similar to PD patients.

• Results suggest that the fine tuning of motor parameters is impaired in PD patients.

Abstract

We present a novel paradigm, aimed at emulating the early stage of handwriting learning in proficient writers, by asking them to produce a familiar shape through a novel (unfamiliar) motor plan. Handwriting of beginner writers is characterized by slower movements, reduced spatial precision, lower fluency and reduced force regulation compared to those observed in the handwriting production of proficient writers. Features observed in the ink trace obtained with the novel motor plan and performance comparison of the handwriting obtained by familiar and unfamiliar motor plan suggest that the proposed paradigm is able to elicit non-automated movements in proficient writers.

As that produced by beginner writers, handwriting of Parkinson’s disease (PD) patients is characterized by lack of fluency, slowness and abrupt changes of direction. Furthermore, PD patients show impaired performance in learning novel motor behaviors, as well as in executing motor behaviors acquired before the onset of the disease. We used the proposed paradigm for comparing the performance achieved by healthy controls in writing a familiar shape through a novel motor plan with those obtained by PD patients performing a well-known motor plan for drawing the same shape. Our analysis points out some similarities between performance obtained by healthy controls and those obtained by PD patients, sustaining the hypothesis that the fine tuning of the motor plan parameters involved in the handwriting production is impaired by PD.

Introduction

Handwriting involves complex movements that can be seen as a composition of elementary movements, each corresponding to an elementary shape or stroke (Plamondon & Maarse, 1989). Studies on motor control (Kawato, 1999) suggested that an elementary movement is performed through a process of sensorimotor transformation (involving the activation and cooperation of several brain areas) in which the location of the target to reach, encoded in trajectory coordinates, is converted into information (the motor plan) suitable for the motor system. This process characterizes the first stage of learning, which is computational demanding and slower, since it relies on the visuo-proprioceptive feedback, which allows humans to correct, trial by trial, the trajectory and motor plan. As learning proceeds, the information provided by the visuo-proprioceptive feedback is exploited in the following trials for a more efficient execution of the task, leading to a coordination and control solution more accurate in terms of the motor production (so that the actual trajectory corresponds to the desired one), and more economical in terms of the metabolic energy expenditure (Sparrow & Newell, 1998). Lashley (1930) and Hebb (1949) observed that movements learned with one extremity could be executed by different effectors (this phenomenon is known as “motor equivalence”), and Raibert (1977) and Wing (2000) showed that writing movements learned through the dominant hand could be executed by using different body parts (such as the non-dominant hand, the mouth and the foot). They observed that, despite subjects had no previous experience writing with any of the other effectors and even though the movements were not smooth, the writing production followed the same trajectory in all conditions. Taken together, these studies suggest that the sequence of movements composing a motor task is stored in the brain in two ways: in an abstract form (effector independent) related to the spatial sequence of points representing the trajectory plan, and as a sequence of motor commands (effector-dependent) directed to obtain particular muscular contractions and articulatory movements. It has been shown that when the untrained hand is used to perform a given sequence, learned with long-term practice with the other hand, performance is poorer, but this is not true for a newly learned sequence (Rand, Hikosaka, Miyachi, Lu, & Miyashita, 1998), supporting the hypothesis that early in learning the execution of the motor task is more based upon the trajectory plan (effector independent), whereas late in learning upon the sequence of motor commands (effector-dependent). Accordingly, we suggested (Senatore & Marcelli, 2012) that handwriting learning follows two distinct phases, in which two different processes take place. Early in learning, handwriting is acquired as a sequence of spatial coordinates (target points) converted into motor commands; as learning proceeds and the sequence of motor commands is acquired, it comes to be executed as a single behavior, and is performed automatically, with no need of the sensorimotor transformation and the info provided by the visuo-proprioceptive feedback. Consequently, with training, the simple point-to-point movements become continuous, curved and smoother. Indeed, during the first phase of handwriting learning the elementary strokes are drawn one after the other, are quite straight and aimed at reaching a sequence of points. Further support to this view has been provided by the neural model proposed by Grossberg and Paine (that incorporates both the role of basal ganglia and cerebellum), which has shown that handwriting movements are initially straight and guided by the visual feedback, while are guided by memory and become smooth and continuous after learning (Grossberg & Paine, 2000).

Handwriting production of beginner writers is characterized by slower movements, reduced spatial precision, lower fluency and reduced force regulation compared to those observed in the handwriting production of proficient writers (Graham and Weintraub, 1996, Rosenblum et al., 2003, Smits-Engelsman et al., 2001, Wann, 1987). Moreover, it has been shown that conscious control of movements, which characterizes the early learning stage of handwriting, causes the reduction of fluency in handwriting (Tucha, Paul, & Lange, 2001). As the writer becomes familiar with a given sequence of strokes, the group of strokes is “embedded” into a single sequence, which is drawn without any feedback, as it was an “elementary” writing movement. Skilled writers know how long it takes to draw a stroke and where it will finish, so that the next stroke can be initiated before the current one is completed, movements becomes more automated and fluency emerges from the time superimposition of strokes (Plamondon & Maarse, 1989). According to these findings and observations, the execution of a novel sequence of handwriting movements for obtaining a specific trajectory should be characterized by novel target points (or, more in general, different target points) and reduced motor performance compared to the known handwriting movements commonly performed for drawing the same trajectory.

It has been shown that cortical and subcortical structures, including the basal ganglia, cerebellum, and cortical regions, are critical in different stages and aspects in the acquisition and/or retention of motor behaviors (Doya, 2000, Doyon et al., 2009). Parkinson’s disease (PD) is characterized by the dysfunction of the basal ganglia, caused by the loss of dopaminergic neurons. Such dysfunction, eventually, impairs the initial learning (Doyon and Ungerleider, 2002, Krebs et al., 2001, Packard and Knowlton, 2002). It has also been shown that reduced amount of dopamine, the neurotransmitter that modulates basal ganglia activity, correlates with reduced performance in the acquisition and expression of a behavior during the initial stage of learning (Horvitz et al., 2007, Smith-Roe and Kelley, 2000).

In previous work (Senatore & Marcelli, 2012) we designed a neural network model incorporating the key biological features of basal ganglia, cerebellum and their cortical interactions. Looking at the neural network behavior, we found that early in learning task performance is more dependent on the interactions between the cortex and the basal ganglia, whereas, after long-term training, task performance is more dependent on the cortex-cerebellar interactions. Other studies showed that basal ganglia are more activated in the execution of internally-driven movements (Debaere et al., 2003, Jenkins et al., 2000), whereas increased activation of the cerebellum was observed in the execution of externally driven movements (Debaere et al., 2003, Jueptner and Weiller, 1998). Furthermore, it has been shown that motor learning in PD patients benefits from the use of external cues (reference points for the execution of the task) or augmented feedback (knowledge about the results of the executed movement) (Nackaerts et al., 2013). All together, these studies support the view that basal ganglia are involved in the early phase of learning, which is mainly focused in the acquisition of the sequence of target points (the trajectory plan) and is based on the visuo-proprioceptive feedback. However, the study of Swett, Contreras-Vidal, Birn, and Braun (2010) reported that a novel sequence of movements is initially mapped to form an internal representation of the sequence that is progressively encoded and refined subcortically (in the basal ganglia and in the cerebellum) as performance improves (Swett et al., 2010), providing some evidence that the basal ganglia are also involved in the late stage of learning, in which fine tuning of motor plan parameters is achieved.

Several studies observed that, similar to beginner writers, handwriting of PD patients is characterized by lack of fluency, slowness, abrupt changes of direction and micrographia (Flash et al., 1992, Marsden, 1989, McLennan et al., 1972, Sheridan et al., 1987, Teulings and Stelmach, 1991, Van Gemmert et al., 1999). PD deficits have been ascribed to patients’ impaired ability in controlling movement speed and amplitude (Broderick et al., 2009, Teulings and Stelmach, 1991, Van Gemmert et al., 1999), coordinating fingers and wrist movements (Teulings et al., 1997, Van Gemmert et al., 2003), and modulating force-production (Stelmach et al., 1989, Stelmach and Worringham, 1988). An interesting question, which is still unanswered, is whether these observed impairments are closely related and could be ascribed to the same underlying deficit.

We hypothesize that reduced performance achieved by PD patients in executing both novel tasks and previously acquired task could be due to an impaired fine tuning of the motor plan parameters involved in the handwriting production. In line with this hypothesis, we expected that PD patients perform handwriting as they got stuck on the early stages of the learning process, in which fine tuning of the motor plan is not still acquired, and that their performance remains poor, due to their impaired learning abilities. Consequently, we expect to find some similarities between the performance achieved by healthy controls in executing novel handwriting movements and those measured in handwriting movements produced by PD patients.

Therefore, the goal of the proposed work is twofold. We present a novel experimental paradigm, and provide evidence that through its use we were able to elicit non-automated movements in healthy subjects, and therefore emulate the early learning stage of a stroke sequence. Furthermore, with the aim of evaluating our hypothesis, we exploited the proposed paradigm, and compared the kinematic features of the handwriting traces produced by the healthy controls using skilled and unskilled movements to those produced by the PD patients.

The investigation of the deficits underlying poor performance characterizing handwriting movements of PD patients can provide insights for the development of novel rehabilitation strategies that could be combined with the pharmacological treatments.