The dynamics of embodiment: a field theory of infant perseverative reaching.

The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7-12 month-old-infants. In Piaget's classic "A-not-B error," infants who have successfully uncovered a toy at location "A" continue to reach to that location even after they watch the toy hidden in a nearby location "B." Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects or other static mental structures. Instead, we demonstrate that the A-not-B error and its previously puzzling contextual variations can be understood by the coupled dynamics of the ordinary processes of goal-directed actions: looking, planning, reaching, and remembering. We offer a formal dynamic theory and model based on cognitive embodiment that both simulates the known A-not-B effects and offers novel predictions that match new experimental results. The demonstration supports an embodied view by casting the mental events involved in perception, planning, deciding, and remembering in the same analogic dynamic language as that used to describe bodily movement, so that they may be continuously meshed. We maintain that this mesh is a pre-eminently cognitive act of "knowing" not only in infancy but also in everyday activities throughout the life span.

Representation in natural and artificial agents: an embodied cognitive science perspective.

The goal of the present paper is to provide an embodied cognitive science view on representation. Using the fundamental task of category learning, we will demonstrate that this perspective enables us to shed new light on many pertinent issues and opens up new prospects for investigation. The main focus of this paper is on the prerequisites to acquire representations of objects in the real world. We suggest that the main prerequisite is embodiment which allows an agent--human, animal or robot--to manipulate its sensory input such that invariances are generated. These invariances, in turn, are the basis of representation formation. In other words, the paper does not focus on representations per se, but rather discusses the various processes involved in order to make learning and representation acquisition possible. The argument structure is as follows. First we introduce two new perspectives on representation, namely frame-of-reference, and complete agent. Then we elaborate the complete agent perspective and focus in particular on embodiment and situatedness. We argue that embodiment has two main aspects, a dynamic and an information theoretic one. Focusing on the latter, there are a number of implications: Representation can only be understood if the embedding of the neural substrate in the physical agent is known, which includes morphology (shape), positioning and nature of sensors. Because an autonomous mobile agent in the real world is exposed to a continuously changing high-dimensional stream of sensory stimulation, if it is to learn category distinctions, it first needs a focus of attention mechanism, and then it must have a way to reduce the dimensionality of this high-dimensional sensory stream. Learning is very hard because the invariances are typically not found in the sensory data directly--the classical problem of object constancy: it is a so-called type 2 problem. Rather than trying to improve the learning algorithms--which is the standard approach--the embodied cognitive science view suggests a different approach which focuses on the nature of the data: the agent is not passively exposed to a given data distribution, but, by exploiting its body and through the interaction with the environment, it can actually generate the data. More specifically, it can generate correlated data that has the property that it can be easily learned. This learnability is due to redundancies resulting from the appropriate interactions with the environment. Through such interactions, the former type 2 problem is transformed into a type 1 problem, thus reducing the complexity of the learning task by orders of magnitude. By observing the frame-of-reference problem we will discuss to what extent these invariances are reflected--represented--in the "neural substrate", i.e. the internal mechanisms of the agent. It is concluded, that representation is not a concept that can be studied in the abstract, but should be elaborated in the context of concrete agent-environment interactions. These ideas are all illustrated with examples of natural agents and artificial agents. In particular, we will present a suite of experiments on simulated and real-world artificial agents instantiating the main arguments.

Dynamical analysis of schizophrenia courses.

In order to assess the working hypothesis that schizophrenia may be viewed as a nonlinear dynamical disease, we examined the long-term psychoticity dynamics of 14 patients. The data consist of daily ratings of psychopathology observed for 200 or more consecutive days in each patient. We implemented nonlinear dynamical analysis methods with a potential of being applicable even to relatively short and noisy time series: two different forecasting approaches combined with surrogate methods that allow statistical testing in each single case. The resulting classification of dynamics gives evidence that eight patients show nonlinear evolutions of symptom courses. Four cases can be modeled linearly, two as random processes. Thus, a larger proportion of the schizophrenic psychoses we studied shows nonlinear time courses. In this way the validity of the concept of dynamical diseases could be supported on statistical grounds in this important area of psychopathology. The nonlinear view-a low-dimensional nonlinear system generating psychotic symptoms--may provide the foundation for a more parsimonious theory of schizophrenia compared to traditional multicausal models. In several of the nonlinear cases we also observed the qualitative "fingerprint" of deterministic chaos: a decay of deterministic features of the course of disorder with time.