Online research in philosophy

The need for representations and computations over their contents in psychological explanations is often cited as both the mark of the genuinely cognitive and a source of skepticism about the reducibility of cognitive theories to neuroscience. A generic version of this anti-reductionist argument is rejected in this paper as unsound, since (i) current thinking about associative learning emphasizes the need for cognitivist resources in theories adequate to explain even the simplest form of this phenomena (Pavlovian conditioning), and yet (ii) the most widely accepted recent theory of associative learning, which utilizes cognitivist resources, has already been reduced to a purely neurophysiological account. Psychoneural reduction of genuinely cognitivist theories is thus already an accomplished scientific fact, despite pronouncements by anti-reductionists about its conceptual impossibility or empirical implausibility. In addition, the specific form of reduction involved in this case (“combinatorial” reduction) provides a promising model for further cognitivist-to-neuroscience theory reductions.

Clark & Thornton take issue with my claim that parity is not a generalisation problem, and that nothing can be inferred about back-propagation in particular, or learning in general, from failures of parity generalisation. They advance arguments to support their contention that generalisation is a relevant issue. In this continuing commentary, I examine generalisation more closely in order to refute these arguments. Different learning algorithms will have different patterns of failure: back-propagation has no special status in this respect. This is not to deny that a particular algorithm might fortuitously happen to produce the “intended” function in an (oxymoronic) parity-generalisation task.

At 14 months, children appear to struggle to apply their fairly well-developed speech perception abilities to learning similar sounding words (e.g., bih/dih; Stager & Werker, 1997). However, variability in nonphonetic aspects of the training stimuli seems to aid word learning at this age. Extant theories of early word learning cannot account for this benefit of variability. We offer a simple explanation for this range of effects based on associative learning. Simulations suggest that if infants encode both noncontrastive information (e.g., cues to speaker voice) and meaningful linguistic cues (e.g., place of articulation or voicing), then associative learning mechanisms predict these variability effects in early word learning. Crucially, this means that despite the importance of task variables in predicting performance, this body of work shows that phonological categories are still developing at this age, and that the structure of noninformative cues has critical influences on word learning abilities.

The notion of schema has been given a major role by Recanati within his conception of primary pragmatic processes, conceived as a type of associative process. I intend to show that Recanati’s considerations on schemata may challenge the relevance theorist’s argument against associative explanations in pragmatics, and support an argument in favor of associative (versus inferential) explanations. More generally, associative relations can be shown to be schematic, that is, they have enough structure to license inferential effects without any appeal to genuine inferential processes. Associative processes are thus able to explain a number of pragmatic and linguistic phenomena which have instead been thought to require specialized inferential processes.

The absence of a clear influence of an animal's behavioral responses to Hebbian associative learning in the cerebral cortex requires some changes in the Hebbian learning rules. The participation of the brain monoaminergic systems in Hebbian associative learning is considered.

Parsimony and simplicity in cognition theory are not achieved by excluding either the “cognitive unconscious” or consciousness from theoretical modeling, but rather, by eliminating redundant constructs independent of their location on the conscious-unconscious axis. Hence, Perruchet & Vinter's (P&V's) case against the “cognitive unconscious” does not work as an argument for consciousness, but rather as a rejection of the redundant background computational processes postulated in traditional cognition theory.

Perruchet & Vinter (P&V) claim that all mental representations are conscious and that the cognitive unconscious does not exist. Unfortunately, support for these claims is garnered illicitly, by defining the terms representation and computation in a way that is unduly restrictive and misleading. In addition, their proposals fail to engage adequately with critically important evidence and theory from neuropsychology concerning consciousness and cognition.

We propose that the isomorphism generally observed between the representations composing our momentary phenomenal experience and the structure of the world is the end-product of a progressive organization that emerges thanks to elementary associative processes that take our conscious representations themselves as the stuff on which they operate, a thesis that we summarize in the concept of Self-Organizing Consciousness (SOC). Key Words: Associative learning; automatism; consciousness; development; implicit learning; incubation; language; mental representation; perception; phenomenal experience.