The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory subscribes to the same (...) theses of the dynamical hypothesis and that it affords covering-law explanations. This however exposes the theory to the mere description worry and generates a puzzle about the role of representations. I then argue that the sensorimotor theory is compatible with a mechanistic framework, and show how this can overcome the mere description worry and solve the problem of the explanatory role of representations. By doing so, it will be shown that the theory should be understood as an enrichment of the orthodoxy, rather than an alternative. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

ABSTRACTIn this paper I offer an interventionist perspective on the explanatory structure and explanatory power of dynamical models in cognitive science: I argue that some “pure” dynamical models – ones that do not refer to mechanisms at all – in cognitive science are “contextualized causal models” and that this explanatory structure gives such models genuine explanatory power. I contrast this view with several other perspectives on the explanatory power of “pure” dynamical models. One of the main results is that dynamical (...) models need not refer to underlying mechanisms in order to be explanatory. I defend and illustrate this position in terms of dynamical models of the A-not-B error in developmental psychology as elaborated by Thelen and colleagues, and dynamical models of unintentional interpersonal coordination developed by Richardson and colleagues. (shrink)

We aim to develop a form of debunking argument according to which an agent’s belief is undermined if the reasons she gives in support of her belief are best explained as rationalizations. This approach is a more sophisticated form of what Shaun Nichols has called best-explanation debunking, which he contrasts with process debunking, i.e., debunking by means of showing that a belief has been generated by an epistemically defective process. In order to develop our approach, we identify an example of (...) such a best-explanation debunking argument in Joshua Greene’s attack on deontology. After showing that this argument is not an instance of process debunking, we offer our best-explanation approach as a generalization of Greene’s argument. Finally, we defend our approach by showing that it is not susceptible to some criticisms that Nichols has leveled against a less sophisticated form of best-explanation debunking. (shrink)

Questions about phenomenology’s role in non-philosophical disciplines gained renewed attention. While we claim that phenomenology makes indispensable, unique contributions to different domains of scientific practice such as concept formation, experimental design, and data collection, we also contend that when it comes to explanation, phenomenological approaches face a dilemma. Either phenomenological attempts to explain conscious phenomena do not satisfy a central constraint on explanations, i.e. the asymmetry between explanans and explanandum, or they satisfy this explanatory asymmetry only by largely merging with (...) non-phenomenological explanation types. The consequence of this dilemma is that insofar as phenomenological approaches are explanatory, they do not provide an own type of explanation. We substantiate our two claims by offering three case studies of phenomenologically inspired experiments in cognitive science. Each case study points out a specific phenomenological contribution to experimental practice while also illustrating how phenomenological approaches face the explanatory dilemma we outline. (shrink)

In recent years phenomenology has attracted the interest of science, acquiring a role far beyond philosophy. Despite Husserl's clear denial of a possible naturalization of phenomenology, scientists from different fields have proposed its naturalization. To achieve this goal, different methodologies have been proposed. Most scientists seem to agree on the claim that phenomenology cannot be a science itself because it fails to respect one of the prerequisites of science, that is, the capacity to explain its phenomena. Phenomenology, thus, is forced (...) to remain a purely descriptive effort, preliminary to authentic scientific practice. I argue, instead, that the experimental development of phenomenology explains phenomena (that is, appearances and/or subjective experiences in first person account) and uses rigorous methods, conducts valid measurements, and can validate its results. The paper provides a variety of examples of how experimental phenomenology works. (shrink)