Personalized rehabilitation approach for reaching movement using reinforcement learning.

Musculoskeletal disorders challenge significantly the performance of many daily life activities, thus impacting the quality of life. The efficiency of the traditional physical therapy programs is limited by ecological parameters such as intervention duration and frequency, number of caregivers, geographic accessibility, as well as by subjective factors such as patient's motivation and perseverance in training. The implementation of VR rehabilitation systems may address these limitations, but the technology still needs to be improved and clinically validated. Furthermore, current applications generally lack flexibility and personalization. A VR rehabilitation game simulation is developed, which focuses on the upper-limb movement of reaching, an essential movement involved in numerous daily life activities. Its novelty consists in the integration of a machine learning algorithm, enabling highly adaptive and patient-customized therapeutic intervention. An immersive VR system for the rehabilitation of reaching movement using a bubble popping game is proposed. In the virtual space, the patient is presented with bubbles appearing at different locations and is asked to reach the bubble with the injured limb and pop it. The implementation of a Q-learning algorithm enables the game to adjust the location of the next bubble according to the performance of the patient, represented by his kinematic characteristics. Two test cases simulate the performance of the patient during a training program of 10 days/sessions, in order to validate the effectiveness of the algorithm, demonstrated by the spatial and temporal distribution of the bubbles in each evolving scenario. The results show that the algorithm learns the patient's capabilities and successfully adapts to them, following the reward policy dictated by the therapist; moreover, the algorithm is highly responsive to kinematic features' variation, while demanding a reasonable number of iterations. A novel approach for upper limb rehabilitation is presented, making use of immersive VR and reinforcement learning. The simulation suggests that the algorithm offers adaptive capabilities and high flexibility, needed in the comprehensive personalization of a rehabilitation process. Future work will demonstrate the concept in clinical trials.

New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies.

Despite the growing body of functional near-infrared spectroscopy (fNIRS) hyperscanning studies, the assessment of coupling between two neural signals using wavelet transform coherence (WTC) seems to ignore the directionality of the interaction. The field is currently lacking a framework that allows researchers to determine whether a high coherence value obtained using a WTC function reflects in-phase synchronization (i.e., neural activation is seen in both members of the dyad at the same time), lagged synchronization (i.e., neural activation is seen in one member of the dyad prior to the other member), or anti-phase synchronization (i.e., neural activation is increased in one member of the dyad and decreased in the other). To address this need, a complementary and more sensitive approach for analyzing the phase coherence of two neural signals is proposed in this work. The toolbox allows investigators to estimate the coupling directionality by classifying the phase angle values obtained using traditional WTC into in-phase synchronization, lagged synchronization, and anti-phase synchronization. The toolbox also allows researchers to assess how the dynamics of interactions develop and change throughout the task. Using this novel WTC approach and the toolbox will advance our understanding of complex social interactions through their uses in fNIRS hyperscanning studies.

Classifying interpersonal synchronization states using a data-driven approach: implications for social interaction understanding.

This study presents a data-driven approach to identifying interpersonal motor synchrony states by analyzing hand movements captured from a 3D depth camera. Utilizing a single frame from the experiment, an XGBoost machine learning model was employed to differentiate between spontaneous and intentional synchrony modes with nearly [Formula: see text] accuracy. Our findings demonstrate a consistent pattern across subjects, revealing that movement velocity tends to be slower in synchrony modes. These insights support the notion that the relationship between velocity and synchrony is influenced by the cognitive load required for the task, with slower movements leading to higher synchrony in tasks demanding higher cognitive load. This work not only contributes to the limited literature on algorithms for identifying interpersonal synchrony but also has potential implications for developing new metrics to assess real-time human social interactions, understanding social interaction, and diagnosing and developing treatment strategies for social deficits associated with conditions such as Autism Spectrum Disorder.

The Potential Role of Dopamine in Mediating Motor Function and Interpersonal Synchrony.

Motor functions in general and motor planning in particular are crucial for our ability to synchronize our movements with those of others. To date, these co-occurring functions have been studied separately, and as yet it is unclear whether they share a common biological mechanism. Here, we synthesize disparate recent findings on motor functioning and interpersonal synchrony and propose that these two functions share a common neurobiological mechanism and adhere to the same principles of predictive coding. Critically, we describe the pivotal role of the dopaminergic system in modulating these two distinct functions. We present attention deficit hyperactivity disorder (ADHD) as an example of a disorder that involves the dopaminergic system and describe deficits in motor and interpersonal synchrony. Finally, we suggest possible directions for future studies emphasizing the role of dopamine modulation as a link between social and motor functioning.

Attachment and task persistence: attachment orientations, perception of teacher's responsiveness, and adolescents' persistence in academic tasks.

The goal of the two studies reported here was to examine the contribution of adolescents' attachment orientations (anxiety, avoidance) and their perception of teacher's responsiveness to persistence in academic tasks. In Study 1 (N = 160), we assessed self-reports of persistence in schoolwork. In Study 2 (N = 240), we manipulated the symbolic presence of participants' teacher (teacher priming) and assessed their actual persistence in a cognitive task. Across the two studies, attachment anxiety was associated with decreased persistence, and the perception of teacher as a responsive figure contributed to heightened persistence and buffered the detrimental effects of attachment anxiety. Study 2's findings also showed that the beneficial effects of perceived teacher's responsiveness on actual task persistence were found only when the teacher was made contextually salient but not when the teacher was not salient. We discussed the dispositional and contextual sources of attachment security that contribute to task persistence.

Brief Report: Classification of Autistic Traits According to Brain Activity Recoded by fNIRS Using ε-Complexity Coefficients.

Individuals with ASD have been shown to have different pattern of functional connectivity. In this study, brain activity of participants with many and few autistic traits, was recorded using an fNIRS device, as participants preformed an interpersonal synchronization task. This type of task involves synchronization and functional connectivity of different brain regions. A novel method for assessing signal complexity, using ε-complexity coefficients, applied for the first i.e. on fNIRS recording, was used to classify brain recording of participants with many/few autistic traits. Successful classification was achieved implying that this method may be useful for classification of fNIRS recordings and that there is a difference in brain activity between participants with low and high autistic traits as they perform an interpersonal synchronization task.

Impairments of interpersonal synchrony evident in attention deficit hyperactivity disorder (ADHD).

In addition to well-known attention deficiencies, attention deficit hyperactivity disorder (ADHD) is accompanied by deficiencies in social cognition. Both intentional and spontaneous interpersonal synchrony have been found to be an essential part of successful human interaction. Here, we used a novel paradigm to assess intentional and spontaneous interpersonal synchrony in adults with and without ADHD. Our data indicate that intentional interpersonal synchrony is reduced in ADHD, whereas spontaneous interpersonal synchrony remains intact. These results suggest that a dysfunctional pattern of interpersonal synchrony may account for interpersonal difficulties in ADHD.

How Long Is Too Long: An Individual Time-Window for Motor Planning.

Human motor response time (RT) is determined by the matureness of the preceding neural motor planning process. In the current study, we characterize the temporal boundaries required for the motor planning process, and its impact on the overall motor RT. In particular, we contrasted short and long planning times by measuring the resulting differences in motor RTs, in an attempt to find whether an optimal planning time for minimal RT exists. Using a "Timed Response" paradigm, we presented participants with varying planning intervals prior to a requested motor response and studied their effect on the timing of initiation of the following movement. We found that, as expected, reaction time shortens as more planning time is provided, yet only until reaching a minimal RT, after which additional planning time increases the motor RT, thus creating a U-shaped behavioral function. Furthermore, since the minimal RT was found to be an individual characteristic, we suggest that there is an individual time window for motor planning.

Author Correction: Evidence for deficient motor planning in ADHD.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Components of Motor Deficiencies in ADHD and Possible Interventions.

There is a growing body of evidence pointing at several types of motor abnormalities found in attention-deficit/hyperactivity disorder (ADHD). In this article we review findings stemming from different paradigms, and suggest an interweaving approach to the different stages involved in the motor regulation process. We start by reviewing various aspects of motor abnormalities found in ADHD and related brain mechanisms. Then, we classify reported motor impairments associated with ADHD, into four classes of motor stages: Attention to the task, motion preparation, motion execution and motion monitoring. Motor abnormalities and corresponding neural activations are analyzed in the context of each of the four identified motor patterns, along with the interactions among them and with other systems. Given the specifications and models of the role of the four motor impairments in ADHD, we ask what treatments correspond to the identified motor impairments. We analyze therapeutic interventions targeting motor difficulties most commonly experienced among individuals with ADHD; first, Neurofeedback training and EMG-biofeedback. As some of the identified components of attention, planning and monitoring have been shown to be linked to abnormal oscillation patterns in the brain, we examine neurofeedback interventions aimed to address these types of oscillations: Theta/beta frequency training and SCP neurofeedback targeted at elevating the CNV component. Additionally we discuss EMG-Biofeedback interventions targeted at feedback on motor activity. Further we review physical activity and motor interventions aimed at improving motor difficulties, associated with ADHD. These kinds of interventions are shown to be helpful not only in aspects of physical ability, but also in enhancing cognition and executive functioning.

Evidence for deficient motor planning in ADHD.

We compare motor planning mechanisms of ADHD and control subjects based on their effect on later observed kinematic characteristics. We monitor hand movement following planning conditions that differ in preparation time, and evaluate the differences across conditions and participants with/without ADHD. Our findings show that when there is sufficient planning time, people without ADHD seem to have a motor plan ready, and immediately initiate a planned movement after a 'GO' cue, with a bell shaped velocity profile. When planning time is not sufficient, they start the movement in a delayed time, possibly indicating that they needed to complete a movement plan. However, people with ADHD, did not start movement immediately after the cue, even when provided with a long preparation time, possibly indicating that even for this planning interval they did not have a motion plan ready. The movement was not only delayed, its velocity profile was not bell shaped and had several peaks. We further found differences between control and ADHD participants in the velocity profile, variability and jitter of movements. Our results suggest that ADHD motion characteristics, are associated with an immature motor plan. Based on the results we propose a paradigm to evaluate deficiencies in motor planning.

Recognition of the semantics and kinematics of gestures: Neural responses to "what" and "how"?

The extensive use of gestures for human-human communication, independently of culture and language, suggests an underlying universal neural mechanism for gesture recognition. The mirror neuron system (MNS) is known to respond to observed human actions, and overlaps with self-action. The minimal cues needed for activation of the MNS for gesture recognition, facial expressions and bodily dynamics, is not yet defined. Using LED-point representations of gestures, we compared two types of brain activations: 1) in response to human recognizable vs non-recognizable motion and 2) in response to human vs non-human motion. Our preliminary results show that parts of the MNS respond only to human kinematics, and not to nonhuman kinematics, suggesting that the brain has a mechanism of discriminating human from nonhuman motion, even if the pattern of motion is meaningless, but still follows biological motion patterns. This implies that mechanisms of learning-mimicking, empathy and emotional communication, are possibly constrained by biological motion patterns. We then suggest a two-tier-model of human-bodily-communication: (1) recognition of human biological kinematics; (2) recognition of meaning. Implications are both theoretical (understanding the underlying mechanism for action recognition) and applicative (in digital graphical social representations, motion should be reasonably biological to generate the same emotional and mimicking automatic mechanisms as in face-to-face social interactions).