Michael Barkasi

It is an apparent truism about visual perception that we can see only what is visible to us. It is also frequently accepted that visual perception is dynamic: our visual experiences are extended through, and can evolve over time. I argue that taking the dynamism of visual experience seriously renders certain simplistic interpretations of the first claim, that a subject at a given time can see only what is visible to her at that time, false: we can be meaningfully said to see invisible objects. This counterintuitive result in turn focuses our attention on the relationship between perception and memory. I show that it is difficult to draw a clear or simple distinction between the two. Memory and perception rely on, and blend with, one another. Together, these claims point us away from understanding visual perception as a simple reflection of the environment, and instead as closer to a process of dynamic modelling that draws together occurrent stimulation and stored information.

Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means that the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes.

Perceptions are externally-directed—they present us with a mind-independent reality, and thus contribute to our abilities to think about this reality, and to know what is objectively the case. But perceptions are also internally-dependent—their phenomenologies depend on the neuro-computational properties of the subject. A good theory of perception must account for both these facts. But naive realism has been criticized for failing to accommodate internal-dependence. This paper evaluates and responds to this criticism. It first argues that a certain version of naive realism, often called “selectionism”, does indeed struggle with internal-dependence. It then develops an alternate version of naive realism which does not. This alternate version, inspired by an idea of Martin’s, accommodates the internal-dependence of perceptions by recognizing the role that the subject’s neuro-computational properties play in shaping perceptual phenomenology. At the same time, it retains the distinctive naive realist account of the external-directedness of perceptions.

We perceive smells as perduring complex entities within a distal array that might be conceived of as smellscapes. However, the philosophical orthodoxy of Odor Theories has been to deny that smells are perceived as having a distal location. Recent challenges have been mounted to Odor Theories’ veracity in handling the timescale of olfactory perception, how it individuates odors as a distal entities, and their claim that olfactory perception is not spatial. The paper does not aim to dispute these criticisms. Rather, what will be shown is that Molecular Structure Theory, a refinement of Odor Theory, can be further developed to handle these challenges. The theory is further refined by focusing on distal perception that requires considering the perceptual object as mereologically complex persisting odor against a background scene conceived of as a smellscape. What will be offered is an expansion of Molecular Structure Theory to account for distal smell perception within natural environments.

Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms.

It has been claimed that naïve realism predicts phenomenological similarities where there are none and, thereby, mischaracterises the phenomenal character of perceptual experience. If true, this undercuts a key motivation for the view. Here, we defend naïve realism against this charge, proposing that such arguments fail (three times over). In so doing, we highlight a more general problem with critiques of naïve realism that target the purported phenomenological predictions of the view. The problem is: naïve realism, broadly construed, doesn’t make phenomenological predictions of the required sort. So, as a result, opponents must resign themselves to attacking specific incarnations of naïve realism, or approach matters quite differently.