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Journal Cover Psychological Review
  [SJR: 5.287]   [H-I: 168]   [168 followers]  Follow
   Full-text available via subscription Subscription journal
   ISSN (Print) 0033-295X - ISSN (Online) 1939-1471
   Published by APA Homepage  [74 journals]
  • A novel ecological account of prefrontal cortex functional development.
    • Abstract: In this paper, we argue that prefrontal cortex ontogenetic functional development is best understood through an ecological lens. We first begin by reviewing evidence supporting the existing consensus that PFC structural and functional development is protracted based on maturational constraints. We then examine recent findings from neuroimaging studies in infants, early life stress research, and connectomics that support the novel hypothesis that PFC functional development is driven by reciprocal processes of neural adaptation and niche construction. We discuss implications and predictions of this model for redefining the construct of executive functions and for informing typical and atypical child development. This ecological account of PFC functional development moves beyond descriptions of development that are characteristic of existing frameworks, and provides novel insights into the mechanisms of developmental change, including its catalysts and influences. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
      PubDate: Mon, 06 Nov 2017 05:00:00 GMT
  • Strategy selection as rational metareasoning.
    • Abstract: Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question of how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost–benefit tradeoff by learning a predictive model of each strategy’s performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to arithmetic by capturing the variability of people’s strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and 4 new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the 2 poles of the debate about human rationality by integrating heuristics and biases with learning and rationality. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
      PubDate: Mon, 06 Nov 2017 05:00:00 GMT
  • A dynamic approach to recognition memory.
    • Abstract: We present a dynamic model of memory that integrates the processes of perception, retrieval from knowledge, retrieval of events, and decision making as these evolve from 1 moment to the next. The core of the model is that recognition depends on tracking changes in familiarity over time from an initial baseline generally determined by context, with these changes depending on the availability of different kinds of information at different times. A mathematical implementation of this model leads to precise, accurate predictions of accuracy, response time, and speed–accuracy trade-off in episodic recognition at the levels of both groups and individuals across a variety of paradigms. Our approach leads to novel insights regarding word frequency, speeded responding, context reinstatement, short-term priming, similarity, source memory, and associative recognition, revealing how the same set of core dynamic principles can help unify otherwise disparate phenomena in the study of memory. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
      PubDate: Mon, 06 Nov 2017 05:00:00 GMT
  • From needs to goals and representations: Foundations for a unified theory
           of motivation, personality, and development.
    • Abstract: Drawing on both classic and current approaches, I propose a theory that integrates motivation, personality, and development within one framework, using a common set of principles and mechanisms. The theory begins by specifying basic needs and by suggesting how, as people pursue need-fulfilling goals, they build mental representations of their experiences (beliefs, representations of emotions, and representations of action tendencies). I then show how these needs, goals, and representations can serve as the basis of both motivation and personality, and can help to integrate disparate views of personality. The article builds on this framework to provide a new perspective on development, particularly on the forces that propel development and the roles of nature and nurture. I argue throughout that the focus on representations provides an important entry point for change and growth. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
      PubDate: Thu, 21 Sep 2017 04:00:00 GMT
  • Visual shape perception as Bayesian inference of 3D object-centered shape
    • Abstract: Despite decades of research, little is known about how people visually perceive object shape. We hypothesize that a promising approach to shape perception is provided by a “visual perception as Bayesian inference” framework which augments an emphasis on visual representation with an emphasis on the idea that shape perception is a form of statistical inference. Our hypothesis claims that shape perception of unfamiliar objects can be characterized as statistical inference of 3D shape in an object-centered coordinate system. We describe a computational model based on our theoretical framework, and provide evidence for the model along two lines. First, we show that, counterintuitively, the model accounts for viewpoint-dependency of object recognition, traditionally regarded as evidence against people’s use of 3D object-centered shape representations. Second, we report the results of an experiment using a shape similarity task, and present an extensive evaluation of existing models’ abilities to account for the experimental data. We find that our shape inference model captures subjects’ behaviors better than competing models. Taken as a whole, our experimental and computational results illustrate the promise of our approach and suggest that people’s shape representations of unfamiliar objects are probabilistic, 3D, and object-centered. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
      PubDate: Thu, 14 Sep 2017 04:00:00 GMT
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