: A growing body of evidence suggests that traditional views of automaticity are in need of revision. For example, automaticity has often been treated as an all-or-none phenomenon, and traditional theories have held that automatic processes are independent of attention. Yet recent empirial data suggests that automatic processes are continuous, and furthermore are subject to attentional control. In this paper we present a model of attention which addresses these issues. Using a parallel distributed processing framework we propose that the attributes of automaticity depend upon the strength of a process and that strength increases with training. Using the Stroop effect as an example, we show how automatic processes are continuous and emerge gradually with practice. Specifically, we present a computational model of the Stroop task which simulates the time course of processing as well as the effects of learning.

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On the control of automatic processes: A parallel distributed processing account of the stroop effect

What are the psychological, computational and neural underpinnings of language? Are these neurocognitive correlates dedicated to language? Do different parts of language depend on distinct neurocognitive systems? Here I address these and other issues that are crucial for our understanding of two fundamental language capacities: the memorization of words in the mental lexicon, and the rule-governed combination of words by the mental grammar. According to the declarative/procedural model, the mental lexicon depends on declarative memory and is rooted in the temporal lobe, whereas the mental grammar involves procedural memory and is rooted in the frontal cortex and basal ganglia. I argue that the declarative/procedural model provides a new framework for the study of lexicon and grammar.

A neurocognitive perspective on language: the declarative/procedural model.

Following much work in linguistic theory, it is hypothesized that the language faculty has a modular structure and consists of two basic components, a lexicon of (structured) entries and a computational system of combinatorial operations to form larger linguistic expressions from lexical entries. This target article provides evidence for the dual nature of the language faculty by describing recent results of a multidisciplinary investigation of German inflection. We have examined: (1) its linguistic representation, focussing on noun plurals and verb inflection (participles), (2) processes involved in the way adults produce and comprehend inflected words, (3) brain potentials generated during the processing of inflected words, and (4) the way children acquire and use inflection. It will be shown that the evidence from all these sources converges and supports the distinction between lexical entries and combinatorial operations.Our experimental results indicate that adults have access to two distinct processing routes, one accessing (irregularly) inflected entries from the mental lexicon and another involving morphological decomposition of (regularly) inflected words into stem+affix representations. These two processing routes correspond to the dual structure of the linguistic system. Results from event-related potentials confirm this linguistic distinction at the level of brain structures. In children's language, we have also found these two processes to be clearly dissociated; regular and irregular inflection are used under different circumstances, and the constraints under which children apply them are identical to those of the adult linguistic system.Our findings will be explained in terms of a linguistic model that maintains the distinction between the lexicon and the computational system but replaces the traditional view of the lexicon as a simple list of idiosyncrasies with the notion of internally structured lexical representations.

Lexical entries and rules of language: a multidisciplinary study of German inflection.

Analog computation via neural networks

https://www.allpsych.uni-giessen.de/rauisch06/readings/Deco.Rolls.ProgNeurobio.2005.pdf

Attention, short-term memory, and action selection: a unifying theory.

We show that an arbitrary “connectionist” model of n neutrons, defined by an n X n real matrix, can be simulated by a system of O(n3log n) Boolean gates with an O(log n) time slow-down factor. This establishes that, even though n2 real numbers possibly of high precision are required to define it, connectionist models do not possess any basic properties different from those of other (nonuniform) highly parallel hardware models.

Jiawei Hong

Papers

On connectionist models