This paper, in opposition to the standard theories of social cognition found in psychology and cognitive science, defends the idea that direct perception plays an important role in social cognition. The two dominant theories, theory theory (TT) and simulation theory (ST), both posit something more than a perceptual element as necessary for our ability to understand others, i.e., to “mindread” or “mentalize.” In contrast, certain phenomenological approaches depend heavily on the concept of perception and the idea that we have a direct perceptual grasp of the other person’s intentions, feelings, etc. This paper explains precisely what the notion of direct perception means, offers evidence from developmental studies, and proposes a non-simulationist interpretation of the neuroscience of mirror systems.

Key words: direct perception, theory theory, simulation theory, mirror neurons, social cognition.

In this chapter, I want to address two issues. The first one is a local issue within current debates about social cognition pertaining to differences between simulation theory (ST) and interaction theory (IT) in the understanding of intercorporeity. I then want to use this issue to address a larger, less local one concerning science. More specifically, depending on what one concludes about the debate between ST and IT, the implication is that either one can continue to do science as we have been doing it, or one has to do it differently. This distinction between ways of doing science is not the same as the distinction between normal and revolutionary science described by Thomas Kuhn (1962). Something different is at stake. It’s not simply a paradigm shift that would change our conception of nature (or in this case, the nature of human behavior) in a way that would allow us to do science as usual, but rather a change in our conception of nature that would suggest a different way of doing science. This change, I’ll argue, is prefigured in the thinking of Merleau-Ponty (1967, 2012) concerning the notion of form or structure in his early works.

Key words: social cognition, interaction theory, body schema, simulation theory, social cognitive function

Open peer commentary on the article “Circularity and the Micro-Macro-Difference” by Manfred Füllsack. Upshot: We join Füllsack in his effort to untangle the concepts of circular causation, macro states, and observation by reanalyzing one of our own simulations in the light of these concepts. This simulation presents an example agent that keeps track of its own macro states. We examine how human observers (experimenters and readers of this commentary) can consider such an agent as an observing agent on its own.

Many current programs for cognitive science sail under the banner of “embodied cognition.” These programs typically seek to distance themselves from standard cognitive science. The present proposal for a conception of embodied cognition is less radical than most, indeed, quite compatible with many versions of traditional cognitive science. Its rationale is based on two elements, each of which is theoretically plausible and empirically well-founded. The first element invokes the idea of “bodily formats,” i.e., representational codes primarily utilized in forming interoceptive or directive representations of one’s bodily states and activities. The second element appeals to wideranging evidence that the brain reuses or redeploys cognitive processes having different original uses. When the redeployment theme is applied to bodily formats of representation, they jointly provide for the possibility that body-coded cognition is a very pervasive sector of cognition. Keywords

Key words: Cognitive science, intentional object, distance judgment, motor simulation, mirror activity

Although prediction plays a prominent role in mental processing, we have only limited understanding of how the brain generates and employs predictions. This paper develops a theoretical framework in three steps. First I propose a process model that describes how predictions are produced and are linked to behavior. Subsequently I describe a generative mechanism, consisting of the selective amplification of neural dynamics in the context of boundary conditions. I hypothesize that this mechanism is active as a process engine in every mental process, and that therefore each mental process proceeds in two stages: (i) the formation of process boundary conditions; (ii) the bringing about of the process function by the operation – within the boundary conditions – of a relatively ‘blind’ generative process. Thirdly, from this hypothesis I derive a strategy for describing processes formally. The result is a multilevel framework that may also be useful for studying mental processes in general.

Key words: anticipation, embodied valuation, forward model, mental simulation, objectification, predictive coding

Open peer commentary on the article “Communication Emerging? On Simulating Structural Coupling in Multiple Contingency” by Manfred Füllsack. Upshot: Our criticism aims at the premises of Füllsack’s simulation model, i.e., we claim that his interpretation of the Luhmannian concept of double contingency contradicts the systems theoretical approach in fundamental ways. Neither the view of communication as an emergent system, nor the theory of double contingency is addressed in an adequate manner. Thus Füllsack in fact does not simulate a systems theoretical approach to double contingency but simulates a mere reduction of the social to the individual psyches

A constructivist approach to cognition assumes the minimal and the simplest set of initial principles or mechanisms, embeds them in realistic circumstances, and lets the entire system evolve under close observation. This paper presents a line of research along this approach trying to connect embodiment to social cognition. First, we show that a mere physical body, when driven toward some task goal, provides a clear information structure, for action execution and perception. As a mechanism of autonomous exploration of such structure, “embodiment as a coupled chaotic field” is proposed, with experiments showing emergent and adaptive behavior. Scaling up the principles, a simulation of the fetal/neonatal motor development is presented. The musculo-skeletal system, basic nervous system, and the uterus environment are simulated. The neural-body dynamics exhibit spontaneous exploration of a variety of motor patterns. Lastly, a robotic experiment is presented to show that visual-motor self-learning can lead to neonatal imitation.

Key words: embodiment, actions, symbols, information structure, emergent behavior, learning, imitation, fetus, cortical maps, body schema/image, coupled chaos system

Open peer commentary on the article “Homeostats for the 21st Century? Simulating Ashby Simulating the Brain” by Stefano Franchi. Upshot: Ashby’s view of the organism as an essentially passive machine is not quite as original as the target article may suggest, since it can be traced to Freud’s pleasure principle and from there back to Fechner’s ideas about different kinds of stability in deterministic systems. A modification of the author’s distinction between “simulation of real objects” and “simulation of concepts” is also suggested, and it is argued that the main aim of Ashby’s simulations was to explore the possibility of high-level (structural) explanations of real phenomena, especially learning and memory.

The concept of autopoiesis was introduced by Matura and Varela in the middle of the seventies. It consists in a minimal definition of life based on the observation of living cells. Any closed structure able to synthesize within its boundary all its constituents and to self-maintain by substituting the old substances with the new ones is considered a living system according to the autopoietic theory. In this framework, Luisi and his co-workers, from the early 1990s onwards, began to implement chemical systems that exhibit autopoietic behaviors. They focused their attention mainly on solutions of amphiphiles that spontaneously self-assemble in the aqueous environment. Many different amphiphilic systems have been realized over the years starting from caprylic acid inverse micelles (Bachmann et al. 1990), aqueous caprylate micelles (Bachmann et al. 1992), oleate vesicles (Walde et al. 1994a) vesicles of chiral methyl-dodecanoic acid (Morigaki et al. 1997), and oleate giant vesicles (Wiek et al. 1995). In all these systems spontaneous self-assembly processes take place along with the amphiphile production that is catalyzed by the aggregates themselves producing highly coupled reactions schemes that exhibit non linear kinetic behaviors. The aim of the present dissertation is to elaborated kinetic models to elucidate the mechanism of the processes and the experimentally observed data. Two different approaches has been used: the classical deterministic approach and the Gillespie’s Monte Carlo method. In the deterministic approach, the basic hydrolysis of the water insoluble organic compound, which produces the surfactant molecules, has been assumed to be the rate- determining step and it has been treated as a surface reaction that can occur both at the macroscopic interface and on the aggregate boundary. All the other processes will be assumed to rapidly reach equilibrium, being not perturbed by the surfactant formation. As a consequence, the kinetic differential equation set could be largely reduced to few variables directly related to the available experimental data. It has been possible to rationalize the experimentally observed autocatalytic effect in spite of the well known inhibition due to the electrostatic repulsion between the negatively charged aggregates and the hydroxide ions. In fact, during the process’s slow stage the hydrolysis can occur only at the macroscopic interface, whereas when the aggregates are formed they quickly solubilize the hydrophobic compound and the reactive surface can grow enormously. The limit of this approach is, of coarse, that it can not be applied to systems where the surfactant production rate is comparable with the self-assembly rate. To overcome this restriction a program based on the Monte Carlo algorithm introduced by Gillespie (GiIlespie 1976 and 1977) has been developed. The original procedure consists in an exact simulation of the stochastic master equation for a generic homogeneous well stirred chemically reacting system. This procedure has been optimized and tested successfully by simulating irreversible self-assembly processes for which analytical solutions for specific association constant definitions are available in literature. Therefore, the kinetics of the micellization process has been studied by simulating surfactant solution jump experiments and following the relaxation of the total ennamer concentration towards the new equilibrium state. A decay with two distinct processes has been found by the simulations in agreement to experimental observations. The trend of the simulated time decays against the reduced surfactant concentrations was found in agreement with the Aniansson and Kahlweit theories. Since the program was able to reproduce the dynamic behavior of a micelle solution it was used to simulate an autopoietic micellar system by using a mechanism that was slightly different but kinetically equivalent to those used in the deterministic model. In this case, the main features of the process were also well reproduced by the simulations. The autocatalytic effect was elucidated with the huge increase of the ester concentration in water, due to the micelle solubilization that could also overcome the supposed inhibition effect. In addition, this approach made it possible to confirm the validity of the pseudo-equilibrium assumption of the deterministic model, showing that only the micelle formation is slightly perturbed during the catalytic stage. Finally, the Monte Carlo program was used to investigate two irreversible mechanisms that in particular conditions shows the emergence of irreversible autopoietic units both in a continuous growth or in a homeostatic regime sustained by molecular flows from the outside.

Two kinetic models describing the emergence of autopoietic chemical units are presented and discussed: the single reagent autopoietic mechanism (SRAM) and a reduced version (rSRAM). The proposed schemes are inspired to the autopoietic vesicles studied by Zepik et al (2001 Angew. Chem., Int. Ed. Engl. 40 199–202). Deterministic and stochastic analyses are then performed in order to obtain conditions for growth, homeostasis and decay time behaviours of the overall amphiphiles concentration. Only the reduced SRAM is able to exhibit all the three regimes as experimentally observed and in order to obtain details on the time evolution of the aggregates’ size distribution, stochastic simulations are carried out. What emerges from the rSRAM simulation outcomes is that random fluctuations can act as selection rules for the size of the autopoietic units in the homeostatic regime suggesting how, in a prebiotic scenario, stochastic fluctuations can select the more robust, in this case larger, as the fittest ‘organisms’.