Publications

Chronic use of cannabis leads to both motor deficits and the downregulation of CB1 receptors (CB1R) in the cerebellum. In turn, cerebellar damage is often related to impairments in motor learning and control. Further, a recent motor learning task that measures cerebellar-dependent adaptation has been shown to distinguish well between healthy subjects and chronic cannabis users. Thus, the deteriorating effects of chronic cannabis use in motor performance point to cerebellar adaptation as a key process to explain such deficits. We review the literature relating chronic cannabis use, the endocannabinoid system in the cerebellum, and different forms of cerebellar-dependent motor learning, to suggest that CB1R downregulation leads to a generalized underestimation and misprocessing of the sensory errors driving synaptic updates in the cerebellar cortex. Further, we test our hypothesis with a computational model performing a motor adaptation task and reproduce the behavioral effect of decreased implicit adaptation that appears to be a sign of chronic cannabis use. Finally, we discuss the potential of our hypothesis to explain similar phenomena related to motor impairments following chronic alcohol dependency. © 2022

JTD Keywords: adaptation, addiction, alcohol-abuse, cerebellum, chronic cannabis use, cognition, deficits, endocannabinoid system, error processing, explicit, modulation, motor learning, release, synaptic plasticity, Adaptation, Adaptation, physiological, Alcoholism, Article, Behavioral science, Cannabinoid 1 receptor, Cannabis, Cannabis addiction, Cerebellum, Cerebellum cortex, Cerebellum disease, Chronic cannabis use, Computer model, Down regulation, Endocannabinoid, Endocannabinoid system, Endocannabinoids, Error processing, Hallucinogens, Human, Humans, Motor dysfunction, Motor learning, Nerve cell plasticity, Nonhuman, Physiology, Psychedelic agent, Purkinje-cells, Regulatory mechanism, Sensation, Sensory dysfunction, Sensory error processing impairment, Synaptic transmission, Task performance

In cognitive science, Theory of Mind (ToM) is the mental faculty of assessing intentions and beliefs of others and requires, in part, to distinguish incoming sensorimotor (SM) signals and, accordingly, attribute these to either the self-model, the model of the other, or one pertaining to the external world, including inanimate objects. To gain an understanding of this mechanism, we perform a computational analysis of SM interactions in a dual-arm robotic setup. Our main contribution is that, under the common fate principle, a correlation analysis of the velocities of visual pivots is shown to be sufficient to characterize the self (including proximo-distal arm-joint dependencies) and to assess motor to sensory influences, and the other by computing clusters in the correlation dependency graph. A correlational analysis, however, is not sufficient to assess the non-symmetric/directed dependencies required to infer autonomy, the ability of entities to move by themselves. We subsequently validate 3 measures that can potentially quantify a metric for autonomy: Granger causality (GC), transfer entropy (TE), as well as a novel “Acceleration Transfer” (AT) measure, which is an instantaneous measure that computes the estimated instantaneous transfer of acceleration between visual features, from which one can compute a directed SM graph. Subsequently, autonomy is characterized by the sink nodes in this directed graph. This study results show that although TE can capture the directional dependencies, a rectified subtraction operation denoted, in this study, as AT is both sufficient and computationally cheaper.

JTD Keywords: agency, attention, autonomy, cognitive development, computational cognition, developmental psychology, sensorimotor learning, Agency, Attention, Autonomy, Cognitive development, Computational cognition, Developmental psychology, Model, Sensorimotor learning, Theory of mind

© The Author(s) 2021. Background: The negative discrepancy between residual functional capacity and reduced use of the contralesional hand, frequently observed after a brain lesion, has been termed Learned Non-Use (LNU) and is thought to depend on the interaction of neuronal mechanisms during recovery and learning-dependent mechanisms. Objective: Albeit the LNU phenomenon is generally accepted to exist, currently, no transdisciplinary definition exists. Furthermore, although therapeutic approaches are implemented in clinical practice targeting LNU, no standardized diagnostic routine is described in the available literature. Our objective was to reach consensus regarding a definition as well as synthesize knowledge about the current diagnostic procedures. Methods: We used a structured group communication following the Delphi method among clinical and scientific experts in the field, knowledge from both, the work with patient populations and with animal models. Results: Consensus was reached regarding a transdisciplinary definition of the LNU phenomenon. Furthermore, the mode and strategy of the diagnostic process, as well as the sources of information and outcome parameters relevant for the clinical decision making, were described with a wide range showing the current lack of a consistent universal diagnostic approach. Conclusions: The need for the development of a structured diagnostic procedure and its implementation into clinical practice is emphasized. Moreover, it exists a striking gap between the prevailing hypotheses regarding the mechanisms underlying the LNU phenomenon and the actual evidence. Therefore, basic research is needed to bridge between bedside and bench and eventually improve clinical decision making and further development of interventional strategies beyond the field of stroke rehabilitation.

JTD Keywords: diagnosis, experience-dependent non-use, perceptual disorders, rehabilitation, sensorimotor learning, Diagnosis, Experience-dependent non-use, Perceptual disorders, Rehabilitation, Sensorimotor learning

The mechanisms of how the brain orchestrates multi-limb joint action have yet to be elucidated and few computational sensorimotor (SM) learning approaches have dealt with the problem of acquiring bimanual affordances. We propose a series of bidirectional (forward/inverse) SM maps and its associated learning processes that generalize from uni- to bimanual interaction (and affordances) naturally, reinforcing the motor equivalence property. The SM maps range from a SM nature to a solely sensory one: full body control, delta SM control (through small action changes), delta sensory co-variation (how body-related perceptual cues covariate with object-related ones). We make several contributions on how these SM maps are learned: (1) Context and Behavior-Based Babbling: generalizing goal babbling to the interleaving of absolute and local goals including guidance of reflexive behaviors; (2) Event-Based Learning: learning steps are driven by visual, haptic events; and (3) Affordance Gradients: the vectorial field gradients in which an object can be manipulated. Our modeling of bimanual affordances is in line with current robotic research in forward visuomotor mappings and visual servoing, enforces the motor equivalence property, and is also consistent with neurophysiological findings like the multiplicative encoding scheme.

JTD Keywords: Affordances, Bimanual affordances, Goal babbling, Interlimb coordination, Motor equivalence, Sensorimotor learning

Background—The cerebellum has been recently suggested as an important player in the addiction brain circuit. Cannabis is one of the most used drugs worldwide, and its long-term effects on the central nervous system are not fully understood. No valid clinical evaluations of cannabis impact on the brain are available today. The cerebellum is expected to be one of the brain structures that are highly affected by prolonged exposure to cannabis, due to its high density in endocannabinoid receptors. We aim to use a motor adaptation paradigm to indirectly assess cerebellar function in chronic cannabis users (CCUs). Methods—We used a visuomotor rotation (VMR) task that probes a putatively-cerebellar implicit motor adaptation process together with the learning and execution of an explicit aiming rule. We conducted a case-control study, recruiting 18 CCUs and 18 age-matched healthy controls. Our main measure was the angular aiming error. Results—Our results show that CCUs have impaired implicit motor adaptation, as they showed a smaller rate of adaptation compared with healthy controls (drift rate: 19.3 +/− 6.8° vs. 27.4 +/− 11.6°; t(26) = −2.1, p = 0.048, Cohen’s d = −0.8, 95% CI = (−1.7, −0.15)). Conclusions—We suggest that a visuomotor rotation task might be the first step towards developing a useful tool for the detection of alterations in implicit learning among cannabis users.

JTD Keywords: Cerebellum, Cannabis, Implicit motor learning, Motor adaptation, Visuomotor rotation

What are the principles underlying effective neurorehabilitation? The aim of neurorehabilitation is to exploit interventions based on human and animal studies about learning and adaptation, as well as to show that the activation of experience-dependent neuronal plasticity augments functional recovery after stroke. Instead of teaching compensatory strategies that do not reduce impairment but allow the patient to return home as soon as possible, functional recovery might be more sustainable as it ensures a long-term reduction in impairment and an improvement in quality of life. At the same time, neurorehabilitation permits the scientific community to collect valuable data, which allows inferring about the principles of brain organization. Hence neuroscience sheds light on the mechanisms of learning new functions or relearning lost ones. However, current rehabilitation methods lack the exact operationalization of evidence gained from skill learning literature, leading to an urgent need to bridge motor learning theory and present clinical work in order to identify a set of ingredients and practical applications that could guide future interventions. This work aims to unify the neuroscientific literature relevant to the recovery process and rehabilitation practice in order to provide a synthesis of the principles that constitute an effective neurorehabilitation approach. Previous attempts to achieve this goal either focused on a subset of principles or did not link clinical application to the principles of motor learning and recovery. We identified 15 principles of motor learning based on existing literature: massed practice, spaced practice, dosage, task-specific practice, goal-oriented practice, variable practice, increasing difficulty, multisensory stimulation, rhythmic cueing, explicit feedback/knowledge of results, implicit feedback/knowledge of performance, modulate effector selection, action observation/embodied practice, motor imagery, and social interaction. We comment on trials that successfully implemented these principles and report evidence from experiments with healthy individuals as well as clinical work.

JTD Keywords: Neurorehabilitation, Motor learning, Plasticity, Stroke, Principles

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb