The present study was set up to investigate cued and contextual fear in situations of (un)predictability in a human fear conditioning paradigm. Forty-nine participants were presented with two different contexts (switching on and off the central lighting of the experimental room). In the predictable context, a visual cue (CS1) was systematically followed by an electrocutaneous stimulus (US). In the unpredictable context, CS2 was presented explicitly unpaired with the US. Dependent variables were online US-expectancy ratings and fear-potentiated startle. First, in both measures, the results showed significantly more fear elicited by CS1 than by CS2. Second, larger startle amplitudes during the intertrial intervals demonstrated more contextual fear in the unpredictable than in the predictable context. Hence, these findings illustrate that unpredictability increases contextual fear. Moreover, the US-expectancy ratings during the intertrial intervals were also higher in the unpredictable than in the predictable context. This last finding suggests that a chronic expectation of the threatening US is responsible for sustained levels of anxiety in unpredictable situations.
The peak of learned responding normally occurs at the learning stimulus itself, but can shift to a different stimulus after discriminative learning. This provides important information about the nature of the generalization mechanism, and reveals alternative pathways through which learned responses can increase. Over two experiments, we established the peak-shift effect in a human predictive learning paradigm. Participants were asked to predict the occurrence of a neutral outcome (drawing of a lightning bolt) based on preceding geometrical figures (rings of different sizes). During learning, the middle-sized ring was sometimes followed by the outcome, whereas a larger ring was never followed by the outcome. At test, we presented larger and smaller rings (Experiment 1), or only a slightly smaller ring (Experiment 2). We consistently observed highest prediction of the outcome to the slightly smaller ring. Predictive estimations in humans can reach their height to stimuli that have never actually participated in the learning experiences. We argue that the results are most in line with an associative learning account, rather than an adaptation-level or a rule-learning account.
<p>El propósito del estudio fue evaluar las propiedades psicométricas de la escala SOC-13 en una muestra de 448 universitarios peruanos con edades entre 18-29 años. La confiabilidad se calculó con el coeficiente de alfa de cronbach, y se encontró un .80 para toda la escala. La estructura interna del instrumento se evaluó mediante análisis de escalamiento multidimensional y análisis factorial confirmatorio. El análisis factorial confirmatorio se estimó comparando el ajuste de dos modelos propuestos, uno uni-factorial frente a uno de primer orden con tres factores. Se encontró un buen ajuste para la solución de tres factores (RMSEA = 0.06, CFI = .92). Correlaciones entre SOC y salud mental y física fueron <em>r</em> = .59, <em>p</em> < .001 y <em>r</em> = .40, <em>p</em> < .001 respectivamente. El SOC-13 mostró propiedades psicométricas adecuadas con respecto a confiabilidad, validez de criterio y estructura factorial en esta muestra. Limitaciones se debieron a la homogeneidad en la muestra, edad y poca representatividad de la población Peruana. Estudios posteriores deberían enfocarse en analizar la estructura factorial del SOC-13 y la habilidad de cada ítem para medir adecuadamente Sentido de Coherencia en jóvenes peruanos.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.