Meaning dominance norms for 120 homographs

Over the past two decades, homographs have been used in psychological experiments aimed at testing a variety of theoretical issues concerning memory and language. Often, such research requires prior knowledge of the dominance relations among various meanings of the homographs. Previously available homograph meaning norms are limited because they are now more than 10 years old, and they have typically reported only the two most dominant meanings even though many homographs have three or more common meanings. This paper presents normative data on 120 homographs from a relatively large, heterogeneous sample of subjects (N = 100). Meaning dominance was assessed by having subjects write the first definition that came to mind for each homograph. Definition responses were grouped by similarity, and the resulting meaning categories were verified against dictionary meaning classifications. The number of distinct meanings varied from two to six for the homographs investigated, and frequency of response is reported for all definition categories.     

Teaching the Rescorla-Wagner model using STELLA-II

Although the Rescorla-Wagner model is widely taught in learning courses, most textbooks present a simplified version that does not contain all of its parameters. On the basis of Rescorla and Wagner 1972) and the Turbo PASCAL program by Lachnit, Schneider, Lipp, and Kimme! (1988), we created a simulation using STELLA-II, an icon-based program by High Performance Systems, Inc. We argue that this simulation facilitates teaching the complete Rescorla-Wagner model. Using trans-switching (Kimmel & Ray, 1978; Lachnit, 1986; Murrin & Kimmel, 1986) as an example, we demonstrate the effectiveness of the STELLA-II version of the Rescorla-Wagner model as a heuristic tool.     

Hinton diagrams: Viewing connection strengths in neural networks

A graphical analysis similar to that used by Hinton and Shallice (1991) was applied to the hair cells of a simulated auditory transducer. The graphical analysis made it apparent that there were hair cells that responded to a narrow range of frequencies, as would be predicted by the tonotopic organization of the real physiology. In short, this study demonstrates the efficacy of using graphic techniques to examine the nature of the autopoetic organization of the hidden layer of back-propagation networks.     

Characterization of state transitions in spatially distributed,chaotic, nonlinear,dynamical systems in cerebral cortex

The neurons of cerebral cortex are largely autonomous and generate activity that is manifested in trains of microscopic axonal action potentials. The neurons interact by sparse but numerous synaptic connections to generate macroscopic dendritic activity patterns that are observed in electroencephalographic (EEG) waves. The macroscopic patterns are constructed by the populations and they shape the output of cortical neurons in parallel arrays. Sensory cortexes receive sensory information in the form of microscopic action potentials, which induce state transitions in population dynamics. Each state transition transforms sensory information to perceptual meaning. The EEG reflects both kinds of activity. The sensory input is accessed by time ensemble averaging, whereas the perceptual output is found by spatial ensemble averaging. Spatial phase gradients in the EEG are useful for identifying EEG segments in a sequence of state transitions in response to sensory input. The rapidity and flexibility with which they take place give strong reason to postulate that the mechanism for the construction of these sequences of patterns is a dynamical system operating in a chaotic domain.     

The temporal selectivity of additive factor effects on the reaction process revealed in ERP component latencies

An experiment was conducted to relate individual components of the event-related brain potential to specific stages of information processing in a two-choice reaction time (RT) task in a group of undergraduate students. Specifically, the latency of the P300 component and the lateralized readiness potential (LRP) were studied as a function of variations in stimulus degradation and response complexity. It was hypothesized that degrading the stimulus would delay the P300 and LRP to the same extent as RT, and that increasing response complexity would affect RT but not P300 latency. The extant literature did not permit any hypothesis regarding the effect of response complexity on LRP latency. The two task variables were found to have additive effects on RT. As predicted, variations in stimulus degradation influenced the latencies of both components, whereas alterations in response complexity had no effect on P300 latency. A significant new finding was that the onset latency of the LRP remained unchanged across levels of response complexity. The overall pattern of results supports the notion of temporal selectivity of stage manipulations that is derived from discrete stage models of human information processing. Furthermore, these results refine the functional interpretation of the LRP by indicating that within the conceptual framework of a stage model the processes this component indexes succeed the start of response choice but precede the start of motor programming.