Gray's Reinforcement Sensitivity Theory: a psychometric critique

This study identifies valid orthogonal scales of Gray's animal learning paradigms, upon which his Reinforcement Sensitivity Theory (RST) is based, by determining a revised structure to the Gray-Wilson Personality Questionnaire (GWPQ) (Wilson, Gray, & Barrett, 1990). It is also determined how well Gray's RST scales predict the surface scales of personality, which were measured in terms of Eysenck Personality Profiler (EPP) scales, the EPQ-R and the learning styles questionnaire (LSQ) scales. First, results suggest that independent pathways of RST scales may exist in humans. Second, Fight seems related to Anxiety and not the Fight/Flight system as proposed by RST. Third. a remarkably consistent story emerges in that Extraversion scales are predicted by Fight, Psychoticism scales are predicted by Active-avoidance, Fight and/or Flight, and Neuroticism scales tend not to be predicted at all (except for Anxiety). Fourth, Gray's revised scales are Unrelated to gender and age effects and show a predictable overlap with the LSQ and original GWPQ scales. It is concluded that Gray's model of personality might provide a stable biological basis of many surface scales of personality, but that there must also be other influences on personality. These results question the finer structure of Gray's RST whilst also showing that RST has greater range of applicability than a strict interpretation of theory implies. (C) 2002 Elsevier Science Ltd. All rights reserved.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Are interactions in Gray's Reinforcement Sensitivity Theory proximal or distal in the prediction of religiosity: a test of the joint subsystems hypothesis

Gray's Reinforcement Sensitivity Theory (RST) consists of the Behavioural Activation System (BAS) which is the basis of Impulsivity, and Behavioural Inhibition System (BIS) which is the basis of Anxiety. In this study, Impulsivity and Anxiety were used as distal predictors of attitudes to religion in the prediction of three religious dependent variables (Church attendance, Amount of prayer, and Importance of church). We hypothesised that Impulsivity would independently predict a Rewarding attitude to the Church and that Anxiety would independently predict an Anxious attitude to the church, and that these attitudes would be proximal predictors of our dependent variables. Moreover, we predicted that interactions between predictors would be proximal. Using structural equation modelling, data from 400 participants supported the hypotheses. We also tested Eysenck's personality scales of Extraversion and Neuroticism and found a key path of the structural equation model to be non-significant. (C) 2003 Elsevier Ltd. All rights reserved.

Reinforcement drives rapid allopatric speciation

Allopatric speciation results from geographic isolation between populations. In the absence of gene flow, reproductive isolation arises gradually and incidentally as a result of mutation, genetic drift and the indirect effects of natural selection driving local adaptation(1-3). In contrast, speciation by reinforcement is driven directly by natural selection against maladaptive hybridization(1,4). This gives individuals that choose the traits of their own lineage greater fitness, potentially leading to rapid speciation between the lineages(1,4). Reinforcing natural selection on a population of one of the lineages in a mosaic contact zone could also result in divergence of the population from the allopatric range of its own lineage outside the zone(4-6). Here we test this with molecular data, experimental crosses, field measurements and mate choice experiments in a mosaic contact zone between two lineages of a rainforest frog. We show that reinforcing natural selection has resulted in significant premating isolation of a population in the contact zone not only from the other lineage but also, incidentally, from the closely related main range of its own lineage. Thus we show the potential for reinforcement to drive rapid allopatric speciation.

The new reinforcement sensitivity theory: Implications for personality measurement

In this article, we review recent modifications to Jeffrey Gray's (1973, 1991) reinforcement sensitivity theory (RST), and attempt to draw implications for psychometric measurement of personality traits. First, we consider Gray and McNaughton's (2000) functional revisions to the biobehavioral systems of RST Second, we evaluate recent clarifications relating to interdependent effects that these systems may have on behavior, in addition to or in place of separable effects (e.g., Corr 2001; Pickering, 1997). Finally, we consider ambiguities regarding the exact trait dimension to which Gray's It reward system corresponds. From this review, we suggest that future work is needed to distinguish psychometric measures of (a) fear from anxiety and (b) reward-reactivity-from trait impulsivity. We also suggest, on the basis of interdependent system views of RST and associated exploration using formal models, that traits that are based upon RST are likely to have substantial intercorrelations. Finally, we advise that more substantive work is required to define relevant constructs and behaviors in RST before we can be confident in our psychometric measures of them.