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Psychological Review
Journal Prestige (SJR): 4.64
Citation Impact (citeScore): 7
Number of Followers: 205  
 
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ISSN (Print) 0033-295X - ISSN (Online) 1939-1471
Published by APA Homepage  [86 journals]
  • A model of the uncertainty effects in choice reaction time that includes a
           major contribution from effector selection.
    • Abstract: Hick’s law describes the relation between choice reaction time (RT) and the number of stimulus-response alternatives (NA). For over half a century, this uncertainty effect has been ascribed primarily to the time taken to map a stimulus to its associated response. Here, data from 2 experiments suggests that selection of the appropriate effector—the particular body part to make a response—also contributes substantially to the uncertainty effect. This insight is important both for our understanding of basic cognitive architecture and because many classic experiments studying stimulus-response mapping have confounded NA with the number of effectors. Our data also suggest that, when stimuli are spatial and linked to the responses in an intuitively simple layout, the time required for stimulus-response mapping depends minimally on the NA, independent of effector. Experiment 1 demonstrated that in order to account for the complex patterns of uncertainty effects observed when stimulus type (spatial vs. symbolic), response mode (typing, with multiple effectors vs. touching with a single, known effector), and participant population (skilled vs. novice typists) are all manipulated a model is required that includes effector selection, along with stimulus-response mapping, and a proper treatment of stimulus-response repetitions. Using spatial indicator stimuli that minimized the contributions of stimulus-response mapping, Experiment 2 compared 4 effector conditions—the factorial combination of 1 or 3 fingers on one or both hands. The results showed that the increase in the uncertainty effect associated with the number of effectors is negatively accelerated and possibly additive across the variation of hands and fingers. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
      PubDate: Mon, 13 May 2019 04:00:00 GMT
       
  • Using response time distributions and race models to characterize primacy
           and recency effects in free recall initiation.
    • Abstract: Primacy and recency effects are common benchmarks for models of free recall and episodic memory. In this work, we show that RT distributions carry diagnostic information about how items enter into competition for recall, and how that competition impacts on the dynamics of recall and leads to novel conclusions about the forms of primacy and recency effects. We jointly fit RT distributions and serial position functions for free recall initiation with both a racing diffusion model and the linear ballistic accumulator (LBA: Brown & Heathcote, 2008). The models were fit in a hierarchical Bayesian framework, factorially varying different assumptions of how primacy and recency are generated. Recency functions were either exponential or power law in shape. Primacy was treated either as a strength boost to the early list items so that both primacy and recency items jointly compete to be retrieved; a mixture of primacy and recency gradients reflecting the usage of different retrieval cues; or a primacy-as-recency account in which primacy items are functionally recent due to the contribution of rehearsal. Although serial position curves do not distinguish between these accounts, they make distinct predictions about how RT distributions vary across serial positions. Results from a number of data sets strongly favor an exponential recency function along with a mixture model of primacy and recency gradients. These results suggest that complete RT distributions can provide informative constraints on models of free recall. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
      PubDate: Thu, 18 Apr 2019 04:00:00 GMT
       
  • A retrieved context model of the emotional modulation of memory.
    • Abstract: Emotion enhances episodic memory, an effect thought to be an adaptation to prioritize the memories that best serve evolutionary fitness. However, viewing this effect largely in terms of prioritizing what to encode or consolidate neglects broader rational considerations about what sorts of associations should be formed at encoding, and which should be retrieved later. Although neurobiological investigations have provided many mechanistic clues about how emotional arousal modulates item memory, these effects have not been wholly integrated with the cognitive and computational neuroscience of memory more generally. Here we apply the Context Maintenance and Retrieval Model (CMR; Polyn, Norman, & Kahana, 2009) to this problem by extending it to describe the way people may represent and process emotional information. A number of ways to operationalize the effect of emotion were tested. The winning emotional CMR (eCMR) model conceptualizes emotional memory effects as arising from the modulation of a process by which memories become bound to ever-changing temporal and emotional contexts. eCMR provides a good qualitative fit for the emotional list-composition effect and the emotional oddball effect, illuminating how these effects are jointly determined by the interplay of encoding and retrieval processes. eCMR can account for the increased advantage of emotional memories in delayed memory tests by assuming a limited ability to reinstate the temporal context of encoding after a delay. By leveraging the rich tradition of temporal context models, eCMR helps integrate existing effects of emotion and provides a powerful tool to test mechanisms by which emotion affects memory in a broad range of paradigms. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
      PubDate: Thu, 11 Apr 2019 04:00:00 GMT
       
  • A double error dynamic asymptote model of associative learning.
    • Abstract: In this article a formal model of associative learning is presented that incorporates representational and computational mechanisms that, as a coherent corpus, empower it to make accurate predictions of a wide variety of phenomena that, so far, have eluded a unified account in learning theory. In particular, the Double Error Dynamic Asymptote (DDA) model introduces: (a) a fully connected network architecture in which stimuli are represented as temporally clustered elements that associate to each other, so that elements of one cluster engender activity on other clusters, which naturally implements neutral stimuli associations and mediated learning; (b) a predictor error term within the traditional error correction rule (the double error), which reduces the rate of learning for expected predictors; (c) a revaluation associability rate that operates on the assumption that the outcome predictiveness is tracked over time so that prolonged uncertainty is learned, reducing the levels of attention to initially surprising outcomes; and critically (d) a biologically plausible variable asymptote, which encapsulates the principle of Hebbian learning, leading to stronger associations for similar levels of cluster activity. The outputs of a set of simulations of the DDA model are presented along with empirical results from the literature. Finally, the predictive scope of the model is discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
      PubDate: Thu, 14 Mar 2019 04:00:00 GMT
       
  • When acute adversity improves psychological health: A
           social–contextual framework.
    • Abstract: Human beings are routinely exposed to varying forms of acute adversity. Our responses take varying forms too, ranging from chronic distress to resilience. Although this pronounced variability is widely recognized, one possible outcome of acute adversity has been invariably, though understandably, ignored: an improvement in psychological and social functioning. In this analysis, I argue that, under some conditions, people can experience marked psychological improvement after acute adversity. I describe this response pattern as psychosocial gains from adversity (PGA) and define it as favorable and reliable change on an index of psychological functioning from before to after exposure to adversity. In the present article, first I distinguish PGA from traditional perspectives on growth after adversity on the basis of key conceptual differences. I then review empirical evidence for PGA as a replicable response pattern following different forms of adversity, including bereavement, military deployment, and mass trauma. I propose a multilevel theoretical model for PGA that focuses on automatic prosocial affiliative behaviors and group-level contextual factors that are conditioned by acute adversity. I describe moderators and boundary conditions at different levels of analysis that will enhance or detract from the likelihood of PGA. I conclude with the implications of PGA for theory and empirical research on postadversity outcomes and outline a research agenda to better understand it. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
      PubDate: Thu, 14 Feb 2019 05:00:00 GMT
       
 
 
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