An open-access database of video stimuli for action observation research in neuroimaging settings: psychometric evaluation and motion characterization.

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss' Kappa = 0.702), establishing excellent validity and reliability. Videos' exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos' timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework (https://osf.io/zexc4/).

Simplified Virtual Reality System Can Be Used to Evaluate the Temporal Discrimination Ability in Softball Batting as in the Real Environment.

Recently, virtual reality (VR) technology has developed rapidly and has increasingly come to be used in the sports field. VR technology ranges from large, highly immersive devices to simple devices such as smartphones, and the respective usefulness and shortcomings of different device types have been debated. Simple devices have advantages such as portability, but also provide only a weak sense of realism. It is important to understand the purpose and extent to which VR technologies can be used. Our purpose in this study was to briefly measure one of the cognitive-motor abilities used in softball batting: temporal discrimination ability in swing onset when a batter faces two types of balls thrown at different speeds. We investigated whether a simplified head-mounted display (HMD) system can evaluate such cognitive-motor ability to the same extent as in a real environment. Ten elite female softball batters swung at fastballs and slowballs randomly thrown by the same pitcher in both real and 3D VR environments, with the same range of trajectories. We then compared the temporal discrimination ability of swing onset analyzed by video analysis between environments. We found that the discrimination ability in VR is almost the same as in reality. In addition, questionnaire items on the VR system related to user experience and cybersickness showed overall promising responses. However, we also found that the system had some issues that need to be considered, such as leading to early swing onset and large variability in it. We discussed the usefulness and limitations of the VR system by combining the results for swing onset with the questionnaire responses. By understanding the characteristics of VR technology and using it as an efficient evaluation and training of players, the sports field can make significant progress.

Behavioral Measures in a Cognitive-Motor Batting Task Explain Real Game Performance of Top Athletes.

Excellent athletic performance in baseball and softball batting is achieved through the momentary cognitive-motor processes. However, in previous studies, cognitive and motor processes are investigated separately. In this study, we focused on the difference in the time of swing onset (a delta onset) during a batting task where 17 elite female softball batters hit balls randomly thrown at two different speeds by pitchers. The delta onset included both cognitive and motor processes because the batters needed to anticipate the ball speed and discriminate their swing motion according to the time-to-contact. Then, we investigated the relationship between the delta onset and the batting outcomes of the batting task, and the relationship between the experimental outcomes and actual batting performance (batting average) over a season. We used path analysis to clarify the structure of the cognitive-motor processes and consequent performance. We found that the batters who had a larger delta onset attained superior batting outcomes (i.e., higher exit velocity and lower miss ratio) in the batting task, and these experimental outcomes explained 67% of the batting average in real games. On the other hand, the cognitive scores (judgement accuracy and rapidity) obtained from a button pressing task, where batters responded to a ball by pressing a button instead of actually swinging, explained only 34% of the batting average. Therefore, our model quantitatively describes the key cognitive-motor structure for athletes and can partially predict a batter's performance in real games. These findings suggest that it is important to employ both cognitive and motor processes in performing tasks, such as this batting task, to properly evaluate a batter's actual ability.

The 2017 and 2018 Iranian Brain-Computer Interface Competitions.

This article summarizes the first and second Iranian brain-computer interface competitions held in 2017 and 2018 by the National Brain Mapping Lab. Two 64-channel electroencephalography (EEG) datasets were contributed, including motor imagery as well as motor execution by three limbs. The competitors were asked to classify the type of motor imagination or execution based on EEG signals in the first competition and the type of executed motion as well as the movement onset in the second competition. Here, we provide an overview of the datasets, the tasks, the evaluation criteria, and the methods proposed by the top-ranked teams. We also report the results achieved with the submitted algorithms and discuss the organizational strategies for future campaigns.

Impaired anticipatory vision and visuomotor coordination affects action planning and execution in children with hemiplegic cerebral palsy.

BACKGROUND: Action-planning and execution deficits in children with hemiplegic cerebral palsy (HCP) are potentially due to deficits in the integration of sensory information, such as vision, with motor output. AIMS: To determine differences in anticipatory visual patterns in children with HCP compared to typically developing (TD) children, and to assess visuomotor coordination in children with HCP. METHODS AND PROCEDURES: We included 13 children with HCP (Age = 6.8 + 2.9 yrs) and 15 TD children (Age = 5.8 + 1.1 yrs). The experimental task used in this study is a valid action-planning task, which consisted of initially reaching and grasping an object placed at a fixed position, followed by placing the object in a random target position. Visual patterns were recorded using a head-mounted eye-tracker system and arm movements were recorded using motion capture (120 Hz). OUTCOMES AND RESULTS: Children with HCP had delayed anticipatory gaze time and longer latency than TD children during the planning and execution phases. Children with HCP also had a higher frequency of gaze shifts, longer reaction times (RT) and movement times (MT) than TD children. CONCLUSIONS AND IMPLICATIONS: Children with HCP may have deficits in anticipatory vision, which potentially affected planning and executing a goal-directed action. Therapeutic interventions focusing on improving visuomotor coordination may improve the motor performance in children with HCP.

Effects of visual display terminal works on cervical movement pattern in patients with neck pain.

[Purpose] This study examined changes in the onset of neck movement in young adults with and without mild neck pain (MNP) during visual display terminal (VDT) work. [Subjects] Ten control subjects and 10 subjects with MNP who were VDT workers were recruited. The upper (UC) and lower cervical (LC) spine angles in the sagittal plane were collected using an ultrasound-based motion analysis system during VDT work for 5 min. [Results] The MNP group had faster movement initiation in the UC and LC compared with the control group during VDT work. [Conclusion] These findings suggest that young adults with MNP should be cautious when performing VDT work while sitting.

Decoding onset and direction of movements using Electrocorticographic (ECoG) signals in humans.

Communication of intent usually requires motor function. This requirement can be limiting when a person is engaged in a task, or prohibitive for some people suffering from neuromuscular disorders. Determining a person's intent, e.g., where and when to move, from brain signals rather than from muscles would have important applications in clinical or other domains. For example, detection of the onset and direction of intended movements may provide the basis for restoration of simple grasping function in people with chronic stroke, or could be used to optimize a user's interaction with the surrounding environment. Detecting the onset and direction of actual movements are a first step in this direction. In this study, we demonstrate that we can detect the onset of intended movements and their direction using electrocorticographic (ECoG) signals recorded from the surface of the cortex in humans. We also demonstrate in a simulation that the information encoded in ECoG about these movements may improve performance in a targeting task. In summary, the results in this paper suggest that detection of intended movement is possible, and may serve useful functions.

Reaching movement onset- and end-related characteristics of EEG spectral power modulations.

The spectral power of intracranial field potentials shows movement-related modulations during reaching movements to different target positions that in frequencies up to the high-γ range (approximately 50 to above 200 Hz) can be reliably used for single-trial inference of movement parameters. However, identifying spectral power modulations suitable for single-trial analysis for non-invasive approaches remains a challenge. We recorded non-invasive electroencephalography (EEG) during a self-paced center-out and center-in arm movement task, resulting in eight reaching movement classes (four center-out, four center-in). We found distinct slow (≤5 Hz), µ (7.5-10 Hz), ß (12.5-25 Hz), low-γ (approximately 27.5-50 Hz), and high-γ (above 50 Hz) movement onset- and end-related responses. Movement class-specific spectral power modulations were restricted to the ß band at approximately 1 s after movement end and could be explained by the sensitivity of this response to different static, post-movement electromyography (EMG) levels. Based on the ß band, significant single-trial inference of reaching movement endpoints was possible. The findings of the present study support the idea that single-trial decoding of different reaching movements from non-invasive EEG spectral power modulations is possible, but also suggest that the informative time window is after movement end and that the informative frequency range is restricted to the ß band.

A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile.

Motor control neuroscientists measure limb trajectories and extract the onset of the movement for a variety of purposes. Such trajectories are often aligned relative to the onset of individual movement before the features of that movement are extracted and their properties are inspected. Onset detection is performed either manually or automatically, typically by selecting a velocity threshold. Here, we present a simple onset detection algorithm that is more accurate than the conventional velocity threshold technique. The proposed method is based on a simple regression and follows the minimum acceleration with constraints model, in which the initial phase of the bell-shaped movement is modeled by a cubic power of the time. We demonstrate the performance of the suggested method and compare it to the velocity threshold technique and to manual onset detection by a group of motor control experts. The database for this comparison consists of simulated minimum jerk trajectories and recorded reaching movements.