Fall 2016 - Thursdays, 12:00 - 1:00 pm, Elliott Hall S204

Next UP ...

December 1 - We will discuss Sarah Kaufman's book "The Art of Grace: On Moving Well Through Life." The author will be attending the discussion.

 

Previously this semester ...

 

September 15 - Discussion topics chosen.

 

September 22 - "Is it the real deal? Perception of virtual characters versus humans: an affective cognitive neuroscience perspective" by Aline W. de Borst and Beatrice de Gelder.

Abstract
Recent developments in neuroimaging research support the increased use of naturalistic stimulus material such as film, avatars, or androids. These stimuli allow for a better understanding of how the brain processes information in complex situations while maintaining experimental control. While avatars and androids are well suited to study human cognition, they should not be equated to human stimuli. For example, the uncanny valley hypothesis theorizes that artificial agents with high human-likeness may evoke feelings of eeriness in the human observer. Here we review if, when, and how the perception of human-like avatars and androids differs from the perception of humans and consider how this influences their utilization as stimulus material in social and affective neuroimaging studies. First, we discuss how the appearance of virtual characters affects perception. When stimuli are morphed across categories from non-human to human, the most ambiguous stimuli, rather than the most human-like stimuli, show prolonged classification times and increased eeriness. Human-like to human stimuli show a positive linear relationship with familiarity. Secondly, we show that expressions of emotions in human-like avatars can be perceived similarly to human emotions, with corresponding behavioral, physiological and neuronal activations, with exception of physical dissimilarities. Subsequently, we consider if and when one perceives differences in action representation by artificial agents versus humans. Motor resonance and predictive coding models may account for empirical findings, such as an interference effect on action for observed human-like, natural moving characters. However, the expansion of these models to explain more complex behavior, such as empathy, still needs to be investigated in more detail. Finally, we broaden our outlook to social interaction, where virtual reality stimuli can be utilized to imitate complex social situations.

 

September 29 - "Perception and reality: Why a wholly empirical paradigm is needed to understand vision" by Dale Purves, Yaniv Morgenstern and William T. Wojtach.

Abstract
A central puzzle in vision science is how perceptions that are routinely at odds with physical measurements of real world properties can arise from neural responses that nonetheless lead to effective behaviors. Here we argue that the solution depends on: (1) rejecting the assumption that the goal of vision is to recover, however imperfectly, properties of the world; and (2) replacing it with a paradigm in which perceptions reflect biological utility based on past experience rather than objective features of the environment. Present evidence is consistent with the conclusion that conceiving vision in wholly empirical terms provides a plausible way to understand what we see and why.

 

October 6 - "The Construction of Visual Reality" by Donald D. Hoffman.

Abstract
This chapter examines the standard definitions of illusion and hallucination. These definitions assume a standard theory of perception in which a goal of perception is to estimate true properties of an objective physical world. This standard theory of perception is usually justified on evolutionary grounds: Those creatures that see more truly are ipso facto more fit. However, a closer examination of perceptual evolution using the tools of evolutionary game theory reveals that this standard assumption is incorrect. Perception has not evolved to report truth, but instead to guide adaptive behavior within a niche. In this regard, our perceptions are much like the windows desktop of a computer, which serves to guide useful interactions with the computer while sparing the user from having to know the truth of its structure and function. This understanding of perceptual evolution requires us to replace the standard definitions of illusion and hallucination with new ones that better reflect the central role of perception as a guide to adaptive behavior.

 

October 20 - "The predictive processing paradigm has roots in Kant" by Link R. Swanson.

Abstract
Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly PP links back to Kant. In this article, I argue that several core aspects of PP were anticipated by Kant (1996/1787) in his works on perception and cognition. Themes from Kant active in PP include: (1) the emphasis on "top-down" generation of percepts; (2) the role of "hyperpriors"; (3) the general function of "generative models"; (4) the process of "analysis-by-synthesis"; and (5) the crucial role of imagination in perception. In addition to these, I also point out that PP echoes Kant's general project in that it aims to explain how minds track causal structure in the world using only sensory data, and that it uses a reverse-engineer or "top-down" method of analysis. I then locate a possible source of Kant's influence on PP by tracing the paradigm back to Hermann von Helmholtz, who saw himself as providing a scientific implementation of Kant's conclusions. I conclude by arguing that PP should not be regarded as a new paradigm, but is more appropriately understood as the latest incarnation of an approach to perception and cognition initiated by Kant and refined by Helmholtz.

 

October 27 - "Qualitative differences between naive and scientific theories of evolution" by Andrew Shtulman.

Abstract
Philosophers of biology have long argued that Darwin's theory of evolution was qualitatively different from all earlier theories of evolution. Whereas Darwin's predecessors and contemporaries explained adaptation as the transformation of a species' "essence," Darwin explained adaptation as the selective propagation of randomly occurring mutations within a population. The present study explored the possibility of a parallel between early "transformational" theories of evolution and modern naive theories. Forty-two high school and college students and three evolutionary biologists were tested on their understanding of six evolutionary phenomena: variation, inheritance, adaptation, domestication, speciation, and extinction. As predicted, a plurality of participants demonstrated transformational reasoning inconsistent with natural selection. Correlational analyses revealed that participants who demonstrated transformational reasoning were as internally consistent as participants who demonstrated an understanding of natural selection, with the exception of one group of participants who appeared to have assimilated two heuristics-"survival of the fittest" and "acquired traits are not inherited"-into an otherwise transformational framework. These findings suggest that the widespread and early-developing tendency to essentialize biological kinds precludes students from conceptualizing species as populations of individuals differentially affected by the environment.

 

November 3 - "Scientific knowledge suppresses but does not supplant earlier intuitions" by Andrew Shtulman and Joshua Valcarcel.

Abstract

When students learn scientific theories that conflict with their earlier, naive theories, what happens to the earlier theories? Are they overwritten or merely suppressed? We investigated this question by devising and implementing a novel speeded-reasoning task. Adults with many years of science education verified two types of statements as quickly as possible: statements whose truth value was the same across both naive and scientific theories of a particular phenomenon (e.g., "The moon revolves around the Earth") and statements involving the same conceptual relations but whose truth value differed across those theories (e.g., "The Earth revolves around the sun"). Participants verified the latter significantly more slowly and less accurately than the former across 10 domains of knowledge (astronomy, evolution, fractions, genetics, germs, matter, mechanics, physiology, thermodynamics, and waves), suggesting that naive theories survive the acquisition of a mutually incompatible scientific theory, coexisting with that theory for many years to follow.