Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models (...) are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and (...) are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms ‘optimal’ and ‘rational’ have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success. (shrink)

Procrastination is a chronic and widespread problem; however, emerging work raises questions regarding the strength of the relationship between self-reported procrastination and behavioral measures of task engagement. This study assessed the internal reliability, concurrent validity, predictive validity, and psychometric properties of 10 self-report procrastination assessments using responses collected from 242 students. Participants’ scores on each self-report instrument were compared to each other using correlations and cluster analysis. Lasso estimation was used to test the self-report scores’ ability to predict two behavioral (...) measures of delay. The self-report instruments exhibited strong internal reliability and moderate levels of concurrent validity. Some self-report measures were predictive of days to study completion. No self-report measures were predictive of deadline action pacing, the pacing style most commonly associated with procrastination. Many of the self-report measures of procrastination exhibited poor fit. These results suggest that researchers should exercise caution in selecting self-report measures and that further study is necessary to determine the factors that drive misalignment between self-reports and behavioral measures of delay. (shrink)

An empirical procedure is suggested for testing a model that postulates variables that intervene between observed causes and abserved effects against a model that includes no such postulate. The procedure is applied to two experiments in psychology. One involves a conditioning regimen that leads to response generalization; the other concerns the question of whether chimpanzees have a theory of mind.

Insight and strategy 2 Abstract In multiple-cue learning (also known as probabilistic category learning) people acquire information about cue-outcome relations and combine these into predictions or judgments. Previous studies claim that people can achieve high levels of performance without explicit knowledge of the task structure or insight into their own judgment policies. It has also been argued that people use a variety of suboptimal strategies to solve such tasks. In three experiments we re-examined these conclusions by introducing novel measures of (...) task knowledge and self-insight, and using ‘rolling regression’ methods to analyze individual learning. Participants successfully learned a four-cue probabilistic environment and showed accurate knowledge of both the task structure and their own judgment processes. Learning analyses suggested that the apparent use of suboptimal strategies emerges from the incremental tracking of statistical contingencies in the environment. (shrink)

In 1955, Egon Brunswik presented a paper in which he argued that neglect of the environment and over emphasis of the organism was the major downfall of cognitive psychology. His critiques have largely been ignored and research is discussed that demonstrates the same organismic- asymmetry Brunswik detailed in 1955. This research is discussed in attribution terms since experimental psychologists make behavioral attributions. This organismic-asymmetry has resulted in a body of research that is guilty of the fundamental attribution error. Brunswik's theory (...) of representative design, proposed to address organismic-asymmetry, is discussed and contrasted with calls for ecological validity. Although calls for ecological validity are well intentioned, they lack any systematic theory of the environment and fall significantly short of Brunswik's ideal. 2012 APA, all rights reserved). (shrink)

How can we study bounded rationality? We answer this question by proposing rational task analysis —a systematic approach that prevents experimental researchers from drawing premature conclusions regarding the rationality of agents. RTA is a methodology and perspective that is anchored in the notion of bounded rationality and aids in the unbiased interpretation of results and the design of more conclusive experimental paradigms. RTA focuses on concrete tasks as the primary interface between agents and environments and requires explicating essential task elements, (...) specifying rational norms, and bracketing the range of possible performance, before contrasting various benchmarks with actual performance. After describing RTA’s core components we illustrate its use in three case studies that examine human memory updating, multitasking behavior, and melioration. We discuss RTA’s characteristic elements and limitations by comparing it to related approaches. We conclude that RTA provides a useful tool to render the study of bounded rationality more transparent and less prone to theoretical confusion. (shrink)

A popular goal in psychological science is to understand human cognition and behavior in the ‘real world’. In contrast, researchers have typically conducted their research in experimental research settings, a.k.a. the ‘psychologist’s laboratory’. Critics have often questioned whether psychology’s laboratory experiments permit generalizable results. This is known as the ‘real-world or the lab’-dilemma. To bridge the gap between lab and life, the concept of ecological validity has been widely used to evaluate whether laboratory experiments resemble and generalize to the ‘real (...) world’. However, researchers seldom define what they mean with this concept, nor are there any guidelines or criteria available for evaluating a study’s ecological validity. In our view, the popular concept of ecological validity is ill-formed, lacks specificity, and falls short of adequately addressing the fundamental problem of generalizability. In order to move beyond this ‘real-world or the lab’-dilemma, we believe that researchers should be more specific about the contexts of behaviors they are interested in, instead of aiming to understand human cognition and behavior in the ‘real world’. We argue that this is a more constructive way of uncovering the context-specific and context-generic principles of human cognition and behavior. (shrink)

We disagree with Almaatouq et al. that no realistic alternative exists to the “one-at-a-time” paradigm. Seventy years ago, Egon Brunswik introduced representative design, which offers a clear path to commensurability and generality. Almaatouq et al.'s integrative design cannot guarantee the external validity and generalizability of results which is sorely needed, while representative design tackles the problem head on.

Following Brunswik (1952), social judgement theorists have long relied on regression models to describe both an individual's judgements and the environment about which such judgements are made. However, social judgement theory is not synonymous with these compensatory, static, structural models. We compared the characterisations of physicians' judgements using a regression model with that of a non-compensatory process model (called fast and frugal). We found that both models fit the data equally well. Both models suggest that physicians use few cues, that (...) they disagree among themselves, and that their stated cue use is discrepant with the models' stated cue use. However, the fast and frugal model is easier to convey to physicians and is also more psychologically plausible. Implications for how social judgement theorists conceptualise the process of vicarious functioning are discussed. (shrink)

I report on the fate of three methodological and metatheoretical ideas introduced by Brunswik roughly half a century ago. All were greeted with more than the usual hostility because they challenged the conventional beliefs of the time. All have survived in unexpected ways. I also address certain sins of commission and omission made during the neo-Brunswikian phase of the development of Social Judgement Theory. My hopes and fears for the future are mentioned.

This paper first explores a number of themes in the psychological system developed by the Austrian-American psychologist, Egon Brunswik, focusing on those that had a formative influence on Social Judgement Theory. We show that while perception was a recurring ground for Brunswik's empirical and theoretical work, his psychology was a psychology of cognition in the broadest sense. Next, two major themes in Social Judgement Theory functionalism and probabilism are described, and the elegant formulation known as Brunswik's Lens Model is introduced. (...) Some methodological and theoretical implications of these themes are presented. The paper concludes with Hammond's Cognitive Continuum Theory (CCT), which is a theory describing modes of cognition and how those modes are influenced by task characteristics. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)