Systems Factorial Technology: A Theory Driven Methodology for the Identification of Perceptual and Cognitive Mechanisms

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Daniel Little, Nicholas Altieri, Mario Fific, Cheng-Ta Yang
Academic Press, Apr. 10, 2017 - Psychology - 428 pages
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Systems Factorial Technology: A Theory Driven Methodology for the Identification of Perceptual and Cognitive Mechanisms explores the theoretical and methodological tools used to investigate fundamental questions central to basic psychological and perceptual processes. Such processes include detection, identification, classification, recognition, and decision-making.

This book collects the tools that allow researchers to deal with the pervasive model mimicry problems which exist in standard experimental and theoretical paradigms and includes novel applications to not only basic psychological questions, but also clinical diagnosis and links to neuroscience.

Researchers can use this book to begin using the methodology behind SFT and to get an overview of current uses and future directions. The collected developments and applications of SFT allow us to peer inside the human mind and provide strong constraints on psychological theory.

  • Provides a thorough introduction to the diagnostic tools offered by SFT
  • Includes a tutorial on applying the method to reaction time data from a variety of different situations
  • Introduces novel advances for testing the significance of SFT results
  • Incorporates new measures that allow for the relaxation of the high accuracy criterion
  • Examines tools to expand the scope of SFT analyses
  • Applies SFT to a spectrum of different cognitive domains across different sensory modalities
 

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Contents

Part II Recent Advances in Systems Factorial Technology
53
Part III Applications of Systems Factorial Technology
175
Part IV Bridging Levels of Explanation
333
Index
401
Back Cover
409
Copyright

Common terms and phrases

accuracy Algom Altieri analysis assess attention auditory binaural Blaha capacity coefficient channel coactive model coactive processing color decisional separability distractor double factorial efficiency Eidels evidence Experiment Experimental Psychology face perception faces Fifi´c Fitousi Gestalt hazard function Houpt identify information processing integral dimensions Journal of Experimental Journal of Mathematical limited capacity logical rule models manipulation Mathematical Psychology McGurk effect mean RT measures memory model predictions monaural Neufeld Nosofsky observed panel paradigm parallel model parallel processing parallel self-terminating parameter participants perceptual separability presented processing architecture Psychological Review Psychophysics redundant target redundant-target response RT distributions salience Schweickert selective influence serial processing SIC(t single target speech perception statistical stimuli stochastic stopping rule Stroop effect Stroop task subprocesses supercapacity survivor functions Systems factorial technology theory driven methodology threshold tion Townsend & Nozawa trials UCIP values variable visual workload capacity

About the author (2017)

Daniel R. Little is a Senior Lecturer at the University of Melbourne. He directs the Knowledge, Information & Learning Laboratory in the Melbourne School of Psychological Sciences. His research focuses on the mathematical modeling of complex perceptual decisions in categorization and recognition. Daniel received his PhD in 2009 from the University of Western Australia.

Nicholas Altieri, MS PhD, is an Assistant Professor of Speech Language Pathology at Idaho State University. He currently co-directs the EEG laboratory in the Department of Communication Sciences and Disorders. His research specializes in multi-sensory perception, cognitive neuroscience, speech recognition, and statistical modeling of psychological processes. Nicholas studied as a graduate student for five years in James Townsend's laboratory where he began working with SFT, and continues to apply its theoretical fundamentals across a wide range of research topics.

Mario Fific is an associate Professor of Department of Psychology at Grand Valley State University, Michigan. He directs the Cognitive Science and Decision-Making Laboratory. His research focuses on the development of a highly diagnostic and sophisticated methodology for uncovering mental architecture, known as systems factorial technology (SFT). SFT allows for precise determination of the fundamental properties of mental processes underlying cognitive operations in categorization, face detection, reading and visual/memory search.

Prof. Cheng-Ta Yang is an Associate Professor of Department of Psychology, National Cheng Kung University. He got his PHD degree at Department of Psychology, National Taiwan University in 2009. His primary research interests include attention, visual short-term memory, perceptual decision-making, and cognitive modeling. He has spent more than 10 years on studying Systems Factorial Technology and its application. Recently, he received several awards such as Ta-You Wu Memorial Award from National Science Council (2013), The Outstanding Young Persons (2015), and Academia Sinica Research Award for Junior Research Investigators (2016).

Bibliographic information

QR code for Systems Factorial Technology
TitleSystems Factorial Technology: A Theory Driven Methodology for the Identification of Perceptual and Cognitive Mechanisms
EditorsDaniel Little, Nicholas Altieri, Mario Fific, Cheng-Ta Yang
PublisherAcademic Press, 2017
ISBN0128043865, 9780128043868
Length428 pages
Subjects ›  › 

Psychology / Cognitive Neuroscience & Cognitive Neuropsychology
Psychology / Cognitive Psychology & Cognition
Science / Life Sciences / Neuroscience
  
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