scholarly journals Reconstructing the Study of Human Cognition

2021 ◽  
Author(s):  
Richard Prather
Keyword(s):  
Human Behavior ◽  
Real World ◽  
Human Cognition ◽  
Levels Of Analysis ◽  
Modern Approach ◽  
Contextual Variation ◽  
Cognitive Revolution ◽  
Multiple Levels ◽  
Methodological Approaches ◽  
Significant Change

The study of human cognition is a prominent part of psychology and related disciplines. While the modern approach begun during the Cognitive Revolution hasbeen seemingly successful, it is not without concerns. I address five concerns with how human cognition is studied: (1) reliance on homogeneous participant sampleswhen trying to generalize behavior to real-world contexts; (2) focus on controlling for or ignoring "extraneous" variables; (3) assumption of a generic human actor instead of a focus on individual and contextual variation; (4) insufficient theory building.I contend that these concerns are deeply connected and that the solution is a significant change in how we study human cognition, similar in scope to the Cognitive Revolution. We need to reconsider the assumption of cognitive universals and how that assumption is built into the norms of the discipline. I propose a reconstruction of how researchers study human cognition by implementing acombination of methodological approaches and theoretical positions. These combined approaches (1) integrate human heterogeneity, (2) consider human behavior in context, (3) incorporate multiple levels of analysis and non-cognitivefactors, (4) focus not only on averaged behavior but variation across individuals and context, (5) create theory that combines cognition and context.

The weirdest brains in the world

2010 ◽  
Vol 33 (2-3) ◽  
pp. 88-90 ◽  
Author(s):  
Joan Y. Chiao ◽  
Bobby K. Cheon
Keyword(s):  
Human Behavior ◽  
Levels Of Analysis ◽  
Cultural Neuroscience ◽  
Behavioral Sciences ◽  
Compelling Argument ◽  
The World ◽  
Multiple Levels

AbstractHenrich et al. provide a compelling argument about a bias in the behavioral sciences to study human behavior primarily in WEIRD populations. Here we argue that brain scientists are susceptible to similar biases, sampling primarily from WEIRD populations; and we discuss recent evidence from cultural neuroscience demonstrating the importance and viability of investigating culture across multiple levels of analysis.

Developmental Psychology

2013 ◽  
pp. 2-12 ◽  
Author(s):  
Philip David Zelazo
Keyword(s):  
Human Behavior ◽  
Neural Plasticity ◽  
Social Cognitive ◽  
Developmental Psychology ◽  
Psychological Development ◽  
Levels Of Analysis ◽  
Synthetic Approach ◽  
Psychological Phenomena ◽  
Multiple Levels ◽  
Biological Maturity

This Handbook surveys what is now known about psychological development from birth to biological maturity, and it reflects the emergence of a new synthetic approach to developmental science that is based on several theoretical and methodological commitments. According to this new view: (1) psychological phenomena are usefully studied at multiple levels of analysis; (2) psychological development depends on neural plasticity, which extends across the lifespan; (3) the effect of any particular influence on psychological development will depend on the context in which it occurs; (4) psychological phenomena, and developmental changes in psychological phenomena, typically reflect multiple, simultaneous causal influences; and (5) these causal influences are often reciprocal. Research based on this synthetic approach provides new insights into the way in which processes operating at many levels of analysis (cultural, social, cognitive, neural, and molecular) work together to yield human behavior and changes in human behavior.

Developmental Psychology

2013 ◽  
Author(s):  
Philip David Zelazo
Keyword(s):  
Human Behavior ◽  
Neural Plasticity ◽  
Social Cognitive ◽  
Developmental Psychology ◽  
Psychological Development ◽  
Levels Of Analysis ◽  
Synthetic Approach ◽  
Psychological Phenomena ◽  
Multiple Levels ◽  
Biological Maturity

ThisHandbooksurveys what is now known about psychological development from birth to biological maturity, and it reflects the emergence of a new synthetic approach to developmental science that is based on several theoretical and methodological commitments. According to this new view: (1) psychological phenomena are usefully studied at multiple levels of analysis; (2) psychological development depends on neural plasticity, which extends across the lifespan; (3) the effect of any particular influence on psychological development will depend on the context in which it occurs; (4) psychological phenomena, and developmental changes in psychological phenomena, typically reflect multiple, simultaneous causal influences; and (5) these causal influences are often reciprocal. Research based on this synthetic approach provides new insights into the way in which processes operating at many levels of analysis (cultural, social, cognitive, neural, and molecular) work together to yield human behavior and changes in human behavior.

scholarly journals Different algorithms, different models

2021 ◽  
Author(s):  
Martyna Daria Swiatczak
Keyword(s):  
Comparative Analysis ◽  
Real World ◽  
Qualitative Comparative Analysis ◽  
Comparative Methods ◽  
Data Sets ◽  
Simulation Studies ◽  
Threshold Values ◽  
Real World Data ◽  
Software Packages ◽  
Methodological Approaches

AbstractThis study assesses the extent to which the two main Configurational Comparative Methods (CCMs), i.e. Qualitative Comparative Analysis (QCA) and Coincidence Analysis (CNA), produce different models. It further explains how this non-identity is due to the different algorithms upon which both methods are based, namely QCA’s Quine–McCluskey algorithm and the CNA algorithm. I offer an overview of the fundamental differences between QCA and CNA and demonstrate both underlying algorithms on three data sets of ascending proximity to real-world data. Subsequent simulation studies in scenarios of varying sample sizes and degrees of noise in the data show high overall ratios of non-identity between the QCA parsimonious solution and the CNA atomic solution for varying analytical choices, i.e. different consistency and coverage threshold values and ways to derive QCA’s parsimonious solution. Clarity on the contrasts between the two methods is supposed to enable scholars to make more informed decisions on their methodological approaches, enhance their understanding of what is happening behind the results generated by the software packages, and better navigate the interpretation of results. Clarity on the non-identity between the underlying algorithms and their consequences for the results is supposed to provide a basis for a methodological discussion about which method and which variants thereof are more successful in deriving which search target.

scholarly journals HEALTH TECHNOLOGY REASSESSMENT: THE ART OF THE POSSIBLE

2013 ◽  
Vol 29 (4) ◽  
pp. 418-423 ◽  
Author(s):  
Gail MacKean ◽  
Tom Noseworthy ◽  
Adam G. Elshaug ◽  
Laura Leggett ◽  
Peter Littlejohns ◽  
...  
Keyword(s):  
Monitoring And Evaluation ◽  
Health Technology ◽  
Economic Effects ◽  
Policy And Practice ◽  
Political Will ◽  
Multiple Levels ◽  
Methodological Approaches ◽  
Context Specific ◽  
Constant Comparative Analysis ◽  
Health Technology Reassessment

Background:Health technology reassessment (HTR) is “a structured, evidence-based assessment of the clinical, social, ethical, and economic effects of a technology currently used in the healthcare system, to inform optimal use of that technology in comparison to its alternatives.” The purpose of this study is to describe the key themes in the context of current HTR activities and propose a way forward for this newly emerging field.Methods:Data were gathered from a workshop held as part of the 2012 Canadian Agency for Drugs and Technology in Health (CADTH) symposium. The workshop consisted of two panel presentations followed by discussion; data gathered, including presentations and rich audience discussion transcripts, were analyzed for key themes emerging in the field of HTR using constant comparative analysis.Results:The language chosen to describe HTR will set the tone for engagement. The identification of champions at multiple levels and political will are essential. Key lessons from international experience are: disinvestment is difficult, focus on clinical areas not specific technologies, identify clear goals of the HTR agenda. Six key themes were identified to move the HTR agenda forward: emphasize integration over segregation, focus on development of HTR methods and processes, processes are context-specific but lessons must be shared, build capacity in synergistic interdisciplinary fields, develop meaningful stakeholder engagement, strengthen postimplementation monitoring and evaluation.Conclusions:To move this field forward, we must continue to build on international experiences with a focus on developing novel methodological approaches to generating, incorporating, and implementing evidence into policy and practice.

scholarly journals Revisiting the CompCars Dataset for Hierarchical Car Classification: New Annotations, Experiments, and Results

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 596
Author(s):  
Marco Buzzelli ◽  
Luca Segantin
Keyword(s):  
Real World ◽  
High Performance ◽  
Ad Hoc ◽  
Future Research ◽  
Levels Of Detail ◽  
Excellent Starting Point ◽  
Starting Point ◽  
Hierarchical Nature ◽  
Multiple Levels ◽  
Entire Dataset

We address the task of classifying car images at multiple levels of detail, ranging from the top-level car type, down to the specific car make, model, and year. We analyze existing datasets for car classification, and identify the CompCars as an excellent starting point for our task. We show that convolutional neural networks achieve an accuracy above 90% on the finest-level classification task. This high performance, however, is scarcely representative of real-world situations, as it is evaluated on a biased training/test split. In this work, we revisit the CompCars dataset by first defining a new training/test split, which better represents real-world scenarios by setting a more realistic baseline at 61% accuracy on the new test set. We also propagate the existing (but limited) type-level annotation to the entire dataset, and we finally provide a car-tight bounding box for each image, automatically defined through an ad hoc car detector. To evaluate this revisited dataset, we design and implement three different approaches to car classification, two of which exploit the hierarchical nature of car annotations. Our experiments show that higher-level classification in terms of car type positively impacts classification at a finer grain, now reaching 70% accuracy. The achieved performance constitutes a baseline benchmark for future research, and our enriched set of annotations is made available for public download.

scholarly journals Instantiating the multiple levels of analysis perspective in a program of study on externalizing behavior

2012 ◽  
Vol 24 (3) ◽  
pp. 1003-1018 ◽  
Author(s):  
Theodore P. Beauchaine ◽  
Lisa M. Gatzke-Kopp
Keyword(s):  
Middle Childhood ◽  
Externalizing Behavior ◽  
Developmental Psychopathology ◽  
Personality Development ◽  
Developmental Model ◽  
Self Report ◽  
Levels Of Analysis ◽  
Quarter Century ◽  
Trait Impulsivity ◽  
Multiple Levels

AbstractDuring the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide.

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