Integrating predictive frameworks and cognitive models of face perception
نویسندگان
چکیده
منابع مشابه
Computational Models of Face Perception.
Faces are one of the most important means of communication in humans. For example, a short glance at a person's face provides information on identity and emotional state. What are the computations the brain uses to solve these problems so accurately and seemingly effortlessly? This article summarizes current research on computational modeling, a technique used to answer this question. Specifica...
متن کاملIntegrating perception and action through cognitive neuropsychology (broadly conceived).
This special issue of Cognitive Neuropsychology aims at providing a forum for empirical and theoretical research on the integration of perceptual and motor processes in the human mind. The initiative originated at a workshop on “Integrative approaches to perception and action” (Trieste, 27 October, 2006), a satellite event to the 14th Kanizsa Lecture. The 2006 lecture addressed the architecture...
متن کاملHeritability of the Specific Cognitive Ability of Face Perception
What makes one person socially insightful but mathematically challenged, and another musically gifted yet devoid of a sense of direction? Individual differences in general cognitive ability are thought to be mediated by "generalist genes" that affect many cognitive abilities similarly without specific genetic influences on particular cognitive abilities [1]. In contrast, we present here evidenc...
متن کاملIntegrating Cognitive Process and Descriptive Models of Attitudes and Preferences
Discrete choice experiments--selecting the best and/or worst from a set of options--are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive proc...
متن کاملDiscovering Predictive Variables When Evolving Cognitive Models
A non-dominated sorting genetic algorithm is used to evolve models of learning from different theories for multiple tasks. Correlation analysis is performed to identify parameters which affect performance on specific tasks; these are the predictive variables. Mutation is biased so that changes to parameter values tend to preserve values within the population’s current range. Experimental result...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Psychonomic Bulletin & Review
سال: 2018
ISSN: 1069-9384,1531-5320
DOI: 10.3758/s13423-018-1433-x