Can a connectionist model explain the processing of regularly and irregularly inflected words in German as L1 and L2?

The connectionist model is a prevailing model of the structure and functioning of the cognitive system of the processing of morphology. According to this model, the morphology of regularly and irregularly inflected words (e.g., verb participles and noun plurals) is processed in the same cognitive network. A validation of the connectionist model of the processing of morphology in German as L2 has yet to be achieved. To investigate L2-specific aspects, we compared a group of L1 speakers of German with speakers of German as L2. L2 and L1 speakers of German were assigned to their respective group by their reaction times in picture naming prior to the central task. The reaction times in the lexical decision task of verb participles and noun plurals were largely consistent with the assumption of the connectionist model. Interestingly, speakers of German as L2 showed a specific advantage for irregular compared with regular verb participles

The Fallacy of the Homuncular Fallacy

A leading theoretical framework for naturalistic explanation of mind holds that we explain the mind by positing progressively "stupider" capacities ("homunculi") until the mind is "discharged" by means of capacities that are not intelligent at all. The so-called homuncular fallacy involves violating this procedure by positing the same capacities at subpersonal levels. I argue that the homuncular fallacy is not a fallacy, and that modern-day homunculi are idle posits. I propose an alternative view of what naturalism requires that reflects how the cognitive sciences are actually integrating mind and matter

Associative learning in baboons and humans: Species differences in learned attention to visual features

We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features

Order of acquisition in learning perceptual categories: a laboratory analogue of the age-of-acquisition effect?

In the age-of-acquisition (AoA) effect, an advantage for recognition and production is found for items learned early in life, as compared with items learned later. In this laboratory analogue, participants learned to categorize novel random checkerboard stimuli. Some stimuli were presented from the onset of training; others were introduced later. At test, when early and late stimuli had equal cumulative frequency, early stimuli were classified significantly more quickly. Because stimuli were randomly assigned to be introduced either early or late, we can conclude that early stimuli were categorized more quickly because of their order of acquisition. This finding suggests that age- or order-of-acquisition effects are a general property of any learning system

A Connectionist Theory of Phenomenal Experience

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches vehicle and process theories of consciousness, respectively. However, while there may be space for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are dissociable, and on the other, by the classical computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of connectionism; and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: phenomenal experience consists in the explicit representation of information in neurally realized PDP networks. This hypothesis leads us to re-assess some common wisdom about consciousness, but, we will argue, in fruitful and ultimately plausible ways