Ali Yousefi Heris

This paper argues that the key distinguishing feature between simulation and mere resemblance lies in its representational function. Defining this function requires addressing two critical conditions: how neural resemblance denotes its object and how specific content is grounded in such resemblance when it functions as representation. To begin with, the paper posits that the object of simulation is determined by its cognitive role within a broader cognitive system. Second, it examines three potential frameworks for grounding the content of simulation: the Neural Correspondence Thesis (NCT), the Functional Correspondence Thesis (FCT), and the Context-Dependent Correspondence Thesis (CDCT). Both NCT and FCT, the paper shows, encounter problems of content indeterminacy because of their oversimplified assumptions about the relationship between neural activations and mental states. FCT, in particular, faces the issue of over-permissiveness, wherein multiple neural activation patterns correspond to the same mental state, undermining the connection between functional roles and specific content. In response, the paper introduces CDCT as a more robust replacement, addressing both content indeterminacy and over-permissiveness by incorporating context-sensitive mappings between neural states and mental content. Drawing an analogy from the idea of cognitive maps in rats, the paper demonstrates how CDCT clarifies the role of context in shaping the mapping between neural activations and mental content, thereby offering a more precise framework for tackling the complexities of content determination in mental simulations.

One of the central problems in cognitive science concerns our ability to understand others in terms of mental state attribution. We, humans, think of each other as having minds, an assumption which indeed forms the basis of our daily communication: by attributing mental state we understand and predict each other’s behavior. But what mechanisms underpin this ability? This is a question that has preoccupied philosophers and cognitive scientists for more than four decades. In this paper, I will examine two dominant solutions, Theory-Theory and Simulation-Theory, to this question. In section one, I distinguish between two different senses of "theory" and cite considerable evidence in favor of the modular version of Theory-Theory. In section two, after introducing Simulation Theory as an alternative to Theory-Theory, I distinguish between three possible senses of "similarity" in simulation, argue that none of them are free from certain difficulties.

This paper examines the role of simulational mindreading in pragmatic interpretation (conceived of in a Gricean manner). There are two parts to this paper. In part one, I argue that mirroring, in the form of direct or indirect simulation, underdetermines pragmatic interpretation. Nevertheless, to deliver a unique interpretation, mirroring can contribute either by reducing the number of salient interpretations or to be accompanied by theoretical considerations. This results in a hybrid view in which theory and simulation cooperate. The second part of the paper examines the imaginative or perspective-taking sense of simulation. Drawing on evidence from several clinical populations, I will show that subjects with difficulty in pragmatic interpretation often show little or no difficulty in perspective taking, and subjects with difficulty in perspective taking do not always show difficulty in pragmatic interpretation. This, I conclude, suggests that simulation in the sense of perspective taking is not necessary or plays no significant role in pragmatic interpretation.

Some simulationists have argued that the information obtained during the perceptual process of facial expression (the geometric features) is sufficient for recognition of the emotion intended by that expression. Drawing on evidence from cross-cultural studies, with particular attention to conceptual act theories, I show that both emotion expression and recognition are top-down modulated by expressivity norms, observer-specific internal representations, and expectations. I thus conclude that direct simulation, or a purely bottom-up approach, is not sufficient for emotion recognition. Next, I will consider the generate and test strategy as an alternative to direct simulation. This is a highly promising approach in that top-down and bottom-up processes work in parallel, according to the presence, or not, of additional information. For this reason, it avoids the difficulties of direct simulation. I will argue, however, that it is based on a misconception of emotions, specifically on how emotions are represented in the brain. To improve the model, I distinguish between two different categorical approaches to emotions, then argue that only one of which is viable in a simulational account of emotion recognition.

According to a dominant interpretation of the simulation hypothesis, in recognizing an emotion we use the same neural processes used in experiencing that emotion. This paper argues that the view is fundamentally misguided. I will examine the simulational arguments for the three basic emotions of fear, disgust, and anger and argue that the simulational account relies strongly on a narrow sense of emotion processing which hardly squares with evidence on how, in fact, emotion recognition is processed. I contend that the current body of empirical evidence suggests that emotion recognition is processed in an integrative system involving multiple cross-regional interactions in the brain, a view which squares with understanding emotion recognition as an information-rich, rather than simulational, process. In the final section, I discuss possible objections.