Optimal time lags from causal prediction model help stratify and forecast nervous system pathology

Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing question thus is how to automatically stratify a given random cohort of the population, such that treatment can be better tailored to each cluster’s symptoms, and severity of any given group forecasted to provide neuroprotective therapies. In this work we introduce new methods to automatically stratify a random cohort of the population composed of healthy controls of different ages and patients with different disorders of the nervous systems. Using a simple walking task and measuring micro-fluctuations in their biorhythmic motions, we combine non-linear causal network connectivity analyses in the temporal and frequency domains with stochastic mapping. The methods define a new type of internal motor timings. These are amenable to create personalized clinical interventions tailored to self-emerging clusters signaling fundamentally different types of gait pathologies. We frame our results using the principle of reafference and operationalize them using causal prediction, thus renovating the theory of internal models for the study of neuromotor control.

An Open-Source ROS-Gazebo Toolbox for Simulating Robots With Compliant Actuators

To enable the design of planning and control strategies in simulated environments before their direct application to the real robot, exploiting the Sim2Real practice, powerful and realistic dynamic simulation tools have been proposed, e.g., the ROS-Gazebo framework. However, the majority of such simulators do not account for some of the properties of recently developed advanced systems, e.g., dynamic elastic behaviors shown by all those robots that purposely incorporate compliant elements into their actuators, the so-called Articulated Soft Robots ASRs. This paper presents an open-source ROS-Gazebo toolbox for simulating ASRs equipped with the aforementioned types of compliant actuators. To achieve this result, the toolbox consists of two ROS-Gazebo modules: a plugin that implements the custom compliant characteristics of a given actuator and simulates the internal motor dynamics, and a Robotic Operation System (ROS) manager node used to organize and simplify the overall toolbox usage. The toolbox can implement different compliant joint structures to perform realistic and representative simulations of ASRs, also when they interact with the environment. The simulated ASRs can be also used to retrieve information about the physical behavior of the real system from its simulation, and to develop control policies that can be transferred back to the real world, leveraging the Sim2Real practice. To assess the versatility of the proposed plugin, we report simulations of different compliant actuators. Then, to show the reliability of the simulated results, we present experiments executed on two ASRs and compare the performance of the real hardware with the simulations. Finally, to validate the toolbox effectiveness for Sim2Real control design, we learn a control policy in simulation, then feed it to the real system in feed-forward comparing the results.

Raynold Dwi Agung Wardana

Robot sepak bola beroda adalah suatu robot yang bekerja secara tim untuk melakukan permainan sepak bola. Peran penjaga gawang dalam permainan ini sangat penting di lapangan karena merupakan pertahan terakhir menyelamatkan bola sebelum bola masuk gawang pertahanan area sendiri. Robot sepak bola penjaga gawang dengan menggunakan metode odometry diatur oleh pergerakan pada robot menuju titik yang ditarget di (x,y) sehingga penggerakan robot penjaga gawang. Odometry yang menggunakan empat rotary encoder internal motor sebagai pembacaan pulsa, mempunyai selisih sudut motor satu 45⁰, motor dua 135⁰, motor tiga 225⁰, motor empat 315⁰. Dengan system metode PID untuk mengatur kecepatan roda sehingga didapatkan respon kecepatan yang cepat mencapai set point serta setabil. Pada pengujian metode ini memakai lapangan robot sepak bola beroda dengan ukuran setengah lapangan 4.5m x 6m, pada sensor rotary encoder internal motor sebesar 0.5 putaran 37.5 pulsa jarak dihasilkan 10 cm, 1 putaran 75 pulsa jarak dihasilkan 24 cm, 1,5 putaran 112.5 pulsa jarak dihasilkan 35 cm, 2 putaran 150 pulsa jarak dihasilkan 49 cm, dan Mean Error 1%.

Optimal Time Lags from Causal Prediction Model Help Stratify and Forecast Nervous System Pathology

Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing question thus is how to automatically stratify a given random cohort of the population, such that treatment can be better tailored to each cluster’s symptoms, and severity of any given group forecasted to provide neuroprotective therapies. In this work we introduce new methods to automatically stratify a random cohort of the population composed of healthy controls of different ages and patients with different disorders of the nervous systems. Using a simple walking task and measuring micro-fluctuations in their biorhythmic motions, we show that gait is compromised in healthy aging and that in young FMR1 premutation carriers, gait forecasts, even by 15 years ahead, symptoms resembling those of elderly with Parkinson’s disease. Our methods combine non-linear causal network connectivity analyses in the temporal and frequency domains with stochastic mapping, defining a new type of internal motor timings amenable to create personalized clinical interventions. We frame our results using the principle of reafference and operationalize them using causal prediction, thus renovating the theory of internal models for the study of neuromotor control.

Optimal Time Lags from Causal Prediction Model Help Stratify and Forecast Nervous System Pathology

Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing question thus is how to automatically stratify a given random cohort of the population, such that treatment can be better tailored to each cluster’s symptoms, and severity of any given group forecasted to provide neuroprotective therapies. In this work we introduce new methods to automatically stratify a random cohort of the population composed of healthy controls of different ages and patients with different disorders of the nervous systems. Using a simple walking task and measuring micro-fluctuations in their biorhythmic motions, we show that gait is compromised in healthy aging and that in young FMR1 premutation carriers, gait forecasts, even by 15 years ahead, symptoms resembling those of elderly with Parkinson’s disease. Our methods combine non-linear causal network connectivity analyses in the temporal and frequency domains with stochastic mapping, defining a new type of internal motor timings amenable to create personalized clinical interventions. We frame our results using the principle of reafference and operationalize them using causal prediction, thus renovating the theory of internal models for the study of neuromotor control.

The Relationship Between Internal Motor Imagery and Motor Inhibition in School-Aged Children: A Cross-Sectional Study

Functional equivalence hypothesis and motor-cognitive model both posit that motor imagery performance involves inhibition of overt physical movement and thus engages control processes. As motor inhibition in internal motor imagery has been fairly well studied in adults, the present study aimed to investigate the correlation between internal motor imagery and motor inhibition in children. A total of 73 children (7-year-olds: 23, 9-year-olds: 27, and 11-year-olds: 23) participated the study. Motor inhibition was assessed with a stop-signal task, and motor imagery abilities were measured with a hand laterality judgment task and an alphanumeric rotation task, respectively. Overall, for all age groups, response time in both motor imagery tasks increased with rotation angles. Moreover, all children’s response times in both tasks decreased with age, their accuracy increased with age, and their motor inhibition efficiency increased with age. We found a significant difference between 7-year-olds and 9-year-olds in the hand laterality judgment task, suggesting that the involvement of motor inhibition in internal motor imagery might change with age. Our results reveal the underlying processes of internal motor imagery development, and furthermore, provide practical implications for movement rehabilitation of children.

Proprioception in Action: A Matter of Ecological and Social Interaction

The aim of this paper is to provide a theoretical and formal framework to understand how the proprioceptive and kinesthetic system learns about body position and possibilities for movement in ongoing action and interaction. Whereas most weak embodiment accounts of proprioception focus on positionalist descriptions or on its role as a source of parameters for internal motor control, we argue that these aspects are insufficient to understand how proprioception is integrated into an active organized system in continuous and dynamic interaction with the environment. Our strong embodiment thesis is that one of the main theoretical principles to understand proprioception, as a perceptual experience within concrete situations, is the coupling with kinesthesia and its relational constitution—self, ecological, and social. In our view, these aspects are underdeveloped in current accounts, and an enactive sensorimotor theory enriched with phenomenological descriptions may provide an alternative path toward explaining this skilled experience. Following O'Regan and Noë (2001) sensorimotor contingencies conceptualization, we introduce three distinct notions of proprioceptive kinesthetic-sensorimotor contingencies (PK-SMCs), which we describe conceptually and formally considering three varieties of perceptual experience in action: PK-SMCs-self, PK-SMCs-self-environment, and PK-SMC-self-other. As a proof of concept of our proposal, we developed a minimal PK model to discuss these elements in detail and show their explanatory value as important guides to understand the proprioceptive/kinesthetic system. Finally, we also highlight that there is an opportunity to develop enactive sensorimotor theory in new directions, creating a bridge between the varieties of experiences of oneself and learning skills.

Internal Motor Tempo Contributes to the Determination of Preferred Music Tempo Regardless of Music Familiarity.

Humans have long listened to music. However, it is still unclear why people prefer some types of music over others. To investigate how music preference is determined, previous studies have focused on preferred music tempo since tempo can essentially determine music preference. Such studies have reported that external music components as well as internal motor tempo determine tempo preference. Moreover, it has been suggested that familiarity with a piece of music affects the impact of external music components on tempo preference. However, the question of how the contributions of the internal motor tempo and external music components for tempo preference simultaneously change depending on familiarity has not been investigated. Moreover, the issue of which external music components contribute to tempo preference depending on familiarity has not been clarified. Here, we investigate how the preference for music tempo is determined by the internal motor tempo and external music components depending on familiarity with a piece of music. Twenty-three participants adjusted music tempos according to their preferences and rated their music familiarity. In addition, they engaged in finger tapping at their preferred tempo. Music components, such as typically performed tempo or the number of notes, were also analysed. Analysis of the collected data with multiple linear regressions showed that the preferred tapping tempo contributed to the preferred music tempo regardless of familiarity, whereas the contributions of some of the music components changed depending on familiarity. The typically performed tempo that might relate to the memory of a piece of music contributed to the estimation of the preferred music tempo for familiar music, and the number of notes or the pitch that might relate to perceived tempo contributed to the estimation of unfamiliar music. These results suggested that internal motor tempo is constantly involved in tempo preference regardless of music familiarity, whereas the contribution of external music components varies depending on whether a piece of music has been memorized.

Cortical Localization of the Sensory-Motor Transformation in a Whisker Detection Task in Mice

Responding to a stimulus requires transforming an internal sensory representation into an internal motor representation. Where and how this sensory-motor transformation occurs is a matter of vigorous debate. Here, we trained mice in a whisker detection go/no-go task in which they learned to respond (lick) following a transient whisker deflection. Using single unit recordings, we quantified sensory-, motor- and choice-related activities in whisker primary somatosensory cortex (S1), whisker primary motor cortex (wMC) and anterior lateral motor cortex (ALM). Based on the criteria of having both strong sensory and motor representations and early choice probability, we identify whisker motor cortex as the cortical region most directly related to the sensory-motor transformation. Our data support a model of sensory amplification occurring between S1 and wMC, sensory-motor transformation occurring within wMC, and propagation of a motor command occurring between wMC and ALM.

The role of motor and environmental visual rhythms in structuring auditory cortical excitability

SUMMARYOne of the ways we perceive our external world is through the process of active sensing in which biological sensors (e.g. fingers and eyes) sample the environment utilizing mostly rhythmic motor routines. Previous studies indicate that these motor sampling patterns modulate neuronal excitability in sensory brain regions by entraining brain rhythms, a process termed motor-initiated entrainment. Additionally, rhythms of the external environment, that are independent of internal motor commands, are also capable of entraining rhythmic brain activity. The goal of our study was twofold. First, we aimed to investigate the properties of motor-initiated entrainment in the auditory system using the most prominent motor sampling pattern in primates, eye movements. Second, we wanted to determine whether/how motor-initiated entrainment by eye movements interacts with visual environmental entrainment. By examining laminar profiles of neuronal ensemble activity in the primary auditory cortex of non-human primates, we found that while motor-initiated entrainment has a suppressive, visual environmental entrainment has an enhancive effect. We also found that the two processes are temporally coupled during free viewing, and their temporal relationship ensures that their effect on neuronal ensemble excitability is complementary rather than interfering. Taken together, our results provide strong evidence that motor and sensory systems continuously interact in orchestrating the brain’s rhythmic context for the optimal sampling of our multisensory environment.