The sense of agency – the subjective feeling of being in control of our own actions – is one central aspect of the phenomenology of action. Computational models provided important contributions toward unveiling the mechanisms underlying the sense of agency in individual action. In particular, the sense of agency is believed to be related to the match between the actual and predicted consequences of our own actions. In the study of joint action, models are even more necessary to understand the (...) mechanisms underlying the development of coordination strategies and how the subjective experiences of control emerge during the interaction. In a joint action, we not only need to predict the consequences of our own actions; we also need to predict the actions and intentions of our partner, and to integrate these predictions to infer their joint consequences. Understanding our partner and developing mutually satisfactory coordination strategies are key components of joint action and in the development of the sense of joint agency. Here we discuss a computational architecture which addresses the sense of agency during intentional, real-time joint action. We first reformulate previous accounts of the sense of agency in probabilistic terms, as the combination of prior beliefs about the action goals and constraints, and the likelihood of the predicted movement outcomes. To look at the sense of joint agency, we extend classical computational motor control concepts - optimal estimation and optimal control. Regarding estimation, we argue that in joint action the players not only need to predict the consequences of their own actions, but also need to predict partner’s actions and intentions and to integrate these predictions to infer their joint consequences. As regards action selection, we use differential game theory – in which actions develop in continuous space and time - to formulate the problem of establishing a stable form of coordination and as a natural extension of optimal control to joint action. The resulting model posits two concurrent observer-controller loops, accounting for ‘joint’ and ‘self’ action control. The two observers quantify the likelihoods of being in control alone or jointly. Combined with prior beliefs, they provide weighing signals which are used to modulate the ‘joint’ and ‘self’ motor commands. We argue that these signals can be interpreted as the subjective sense of joint and self agency. We demonstrate the model predictions by simulating a sensorimotor interactive task where two players are mechanically coupled and are instructed to perform planar movements to reach a shared final target by crossing two differently located intermediate targets. In particular, we explore the relation between self and joint agency and the information available to each player about their partner. The proposed model provides a coherent picture of the inter-relation of prediction, control, and the sense of agency in a broader range of joint actions. (shrink)

Generalizing the notion that muscles are positional frames of reference, a high-dimensional muscle space is defined for multi-muscle systems with an embedded low-dimensional motor manifold of functional articulators. A central representation of such a manifold is proposed as computational body schema. The example of the jaw-tongue system is presented, discussing the relation of functional articulators with kinematic invariances and control problems.

The sequence-in/sequence-out cerebellar machinery is considered from the computational point of view. We outline a learning framework which discriminates short-term from long-term learning and is able to explain single-trial adaptation to unexpected loads.

Fitts' law and the [Delta][Lambda] model are theories of motor control because they are limited to the kinematic aspects of movement and do not capture its essential dynamic nature. The internal source of that determines the speed/accuracy trade-off can be associated with the partial compensation of movement-generated forces.

In field computing a topologic organization of CFs is necessary to support sensorimotor planning. A simple model of cortical dynamics can exploit such topologic organization.

The three languages employed by the scientist, the artist, and the objective observer are interpreted in terms of each other using the latest developments in neuroscience and psychoanalysis in an attempt to create a meta-language with sufficient depth to comprehend the nature of the human mind.

This book presents a systematic exploration of the subjective experience, keeping the investigation for the most part within a subjective first person perspective through the use of “vignettes” as sources of data. It also uses incorporates a ‘"third person” objective approach when that is relevant. The goal of Journeys in the Mind is to capture and convey the operations of the mind: both the shared blueprints common to the elaboration of subjective knowledge as well as the immense fishnet of personalized (...) variables that operate in each mental phase-space and act upon the blueprints to continuously recategorize them into sets of coherent, dynamic outcomes, or mental landscapes. Dr. Sanguineti's meditative perspective holds the promise to enrich the way we understand the workings of the human mind. (shrink)