Combining robotics with enhanced serotonin-driven cortical plasticity improves post-stroke motor recovery

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As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

Stroke is the main source of long-lasting disability, affecting dominantly motor functions. The extent and course of recovery are highly heterogeneous between patients, with a minority of patients fully recovering from their initial impairments, leaving 85 ...

Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and m ...

Soft robots aim to revolutionize how robotic systems interact with the environment thanks to their inherent compliance. Some of these systems are even able to modulate their physical softness. However, simply equipping a robot with softness will not genera ...

There is a growing trend towards designing learning activities featuring robots as collaborative exercises where children work together to achieve the activity objectives, generating interactions that can trigger learning processes. Witnessing such activit ...

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

Gender inequality is a widespread problem in our society. It can manifest itself in many ways and contexts, and starting as early as primary school. While an increasing number of initiatives aim at tackling gender biases and inequalities, few of them are a ...

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system' ...

Novel technologies, fabrication methods, controllers and computational methods are rapidly advancing the capabilities of soft robotics. This is creating the need for design techniques and methodologies that are suited for the multi-disciplinary nature of s ...

The collective behavior of animals has been traditionally studied through observation, quantitative models of behavior, and devices of low intelligence. Nowadays, the advancements in the field of robotics allow for closed-loop experiments that occur in rea ...

Combining robotics with enhanced serotonin-driven cortical plasticity improves post-stroke motor recovery

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Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Identifying important sensory feedback for learning locomotion skills

Longitudinal evaluation of the mechanisms supporting post-stroke motor recovery using TMS-EEG coupling

Piecewise Affine Curvature model: a reduced-order model for soft robot-environment interaction beyond PCC

Prescribing Cartesian Stiffness of Soft Robots by Co-Optimization of Shape and Segment-Level Stiffness

Computational Models of Mutual Understanding for Human-Robot Collaborative Learning

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Participatory design of a social robot and robot-mediated storytelling activity to raise awareness of gender inequality among children

Principles of Network Plasticity in Neocortical Microcircuits

A Provably Stable Iterative Learning Controller for Continuum Soft Robots

The science of soft robot design: A review of motivations, methods and enabling technologies

A biohybrid interaction framework for the integration of robots in animal societies