Gabriel Siegel

The sense of agency is the experience of predicting, initiating, or controlling actions. In this paper, I provide a novel account of the sense of agency that appears in perceptual consciousness. I follow theorists such as Bayne and Prinz in suggesting that the perceptual sense of agency (PSoA) is underpinned by self-monitoring processes. The self-monitoring mechanism compares sensory predictions, made on the basis of motor commands, with sensory feedback. This comparison process distinguishes self-caused from other-caused perceptual changes. I argue for a view where the PSoA is not explained by certain contents represented in perceptual experience. Rather, my account models the PSoA as a type of intentional mode that perceivers bear to contents. After defending this view, I respond to objections and contrast my account with others in the literature.

People are able to take advantage of statistical regularities in scenes, using those regularities to bias their attention to the likely locations of items of interest. People also seem able to learn object-centered statistical regularities—for example, that the top of an object is the most likely target location. We show here that such regularities transfer to new spatial locations even in the absence of any explicit object and hence may not be truly object centered. Additionally, when transfer is measured on a new object with a new shape—the transfer is substantially reduced. The findings suggest that statistical information about likely target locations can be encoded in a configuration-based reference frame that is sensitive to the context established by the objects in the scene. The results lead to a new interpretation of earlier findings and have important implications for understanding the coordinate systems in which attentional priorities are represented.

Perceptual learning is characterized by long-term changes in perception as a result of practice or experience. In this paper, I argue that through perceptual learning we can become newly sensitive to basic perceptual features. First, I provide a novel account of basic perceptual features. Then, I argue that evidence from experience-based plasticity suggests that basic perceptual features can be learned. Lastly, I discuss the common scientific and philosophical view that perceptual learning comes in at least four varieties: differentiation, unitization, attentional weighting and stimulus imprinting (Goldstone 1998, Connolly 2019). Becoming newly sensitive to basic perceptual features, I argue, does not fit into any of these categories. This paper’s contribution to the literature is twofold. First, I present a novel view of basic perceptual features which can be used in subsequent theorizing. Second, I show that learning basic perceptual features, since it does not fit into this standardized taxonomy, constitutes an underappreciated form of perceptual learning. This result has important implications for recent discussions in the philosophy of perception and epistemology.

When does a model explain? When does it promote understanding? A dominant approach to scientific explanation is the interventionist view. According to this view, when X explains Y, intervening on X can produce, prevent or alter Y in some predictable way. In this paper, I argue for two claims. First, I reject a position that many interventionist theorists endorse. This position is that to explain some phenomenon by providing a model is also to understand that phenomenon. While endorsing the interventionist view, I argue that explaining and understanding are distinct scientific achievements. Second, I defend a novel theory of scientific understanding. According to this view, when some model M promotes understanding, M makes available a distinctive mental state. This state is of the same psychological kind as when we grasp events in a narrative as bearing on some ultimate conclusion. To conclude, I show that, given this view, mechanistic explanations often provide a powerful source of understanding that many causal-historical models lack. This paper will be of interest to both philosophers of science and epistemologists engaged in the topics of explanation and understanding.

In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal models, showing that Woodward and Rescorla conflate these problems. Finally, we argue that the temptation to pit mechanistic and interventionist theories of explanation against one another occludes important and scientifically relevant research questions.

Some have defended a Fregean view of perceptual content. On this view, the constituents of perceptual contents are Fregean modes of presentation (MOPs). In this paper, I propose that perceptual MOPs are best understood in terms of object files. Object files are episodic representations that store perceptual information about objects. This information is updated when sensory conditions change. On the proposed view, when a subject perceptually represents some object a under two distinct MOPs, then the subject initiates two object files that both refer to a. My defense of this view appeals to its satisfaction of four constraints that I argue theories of perceptual MOPs should satisfy. Furthermore, I show that some existent accounts of perceptual MOPs fail to satisfy them. The defended constraints also indicate what is unique about perceptual, as opposed to linguistic or cognitive, MOPs.