"Involving Interface": An Extended Mind Theoretical Approach to Roboethics

In 2008 the authors held Involving Interface, a lively interdisciplinary event focusing on issues of biological, sociocultural, and technological interfacing (see Acknowledgments). Inspired by discussions at this event, in this article, we further discuss the value of input from neuroscience for developing robots and machine interfaces, and the value of philosophy, the humanities, and the arts for identifying persistent links between human interfacing and broader ethical concerns. The importance of ongoing interdisciplinary debate and public communication on scientific and technical advances is also highlighted. Throughout, the authors explore the implications of the extended mind hypothesis for notions of moral accountability and robotics

Outline of a new approach to the nature of mind

I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin’s continuity hypothesis and proposes that the mental gap is within our own species

Neuroeconomics: infeasible and underdetermined

Advocates of neuroeconomics claim to offer the prospect of creating a “unified behavioral theory” by drawing upon the techniques of neuroscience and psychology and combining them with economic theory. Ostensibly, through the “direct measurement” of our thoughts, economics and social science will be “revolutionized.” Such claims have been subject to critique from mainstream and non-mainstream economists alike. Many of these criticisms relate to measurability, relevance, and coherence. In this article, we seek to contribute to this critical examination by investigating the potential of underdetermination, such as the statement that testing involves the conjunction of auxiliary assumptions, and that consequently it may not be possible to isolate the effect of any given hypothesis. We argue that neuroeconomics is especially sensitive to issues of underdetermination. Institutional economists should be cautious of neuroeconomists’ zeal as they appear to over-interpret experimental findings and, therefore, neuroeconomics may provide a false prospectus seeking to reinforce the nostrums of homo economicus

Considering Convergence: A Policy Dialogue About Behavioral Genetics, Neuroscience, and Law

Garland and Frankel issue a call for scientists, lawyers, courts and lawmakers to begin a critical dialogue about the implications of scientific discoveries and technological advances in criminal law, behavioral genetics and neuroscience

Spectators’ aesthetic experiences of sound and movement in dance performance

In this paper we present a study of spectators’ aesthetic experiences of sound and movement in live dance performance. A multidisciplinary team comprising a choreographer, neuroscientists and qualitative researchers investigated the effects of different sound scores on dance spectators. What would be the impact of auditory stimulation on kinesthetic experience and/or aesthetic appreciation of the dance? What would be the effect of removing music altogether, so that spectators watched dance while hearing only the performers’ breathing and footfalls? We investigated audience experience through qualitative research, using post-performance focus groups, while a separately conducted functional brain imaging (fMRI) study measured the synchrony in brain activity across spectators when they watched dance with sound or breathing only. When audiences watched dance accompanied by music the fMRI data revealed evidence of greater intersubject synchronisation in a brain region consistent with complex auditory processing. The audience research found that some spectators derived pleasure from finding convergences between two complex stimuli (dance and music). The removal of music and the resulting audibility of the performers’ breathing had a significant impact on spectators’ aesthetic experience. The fMRI analysis showed increased synchronisation among observers, suggesting greater influence of the body when interpreting the dance stimuli. The audience research found evidence of similar corporeally focused experience. The paper discusses possible connections between the findings of our different approaches, and considers the implications of this study for interdisciplinary research collaborations between arts and sciences

The "Cognitive Turn": A Short Guide for Nervous Drivers.

In this brief primer on the emergent field of cognitive literary criticism, I aim to offer a tentative outline of its more representative lines of research after roughly twenty to twenty five years of activity. One of my main concerns will be to attend to some of the main objections that the field has been charged with in its short life, and to highlight the ways in which cognitive critics have addressed such objections. After a brief sketch of the main fields of activity, I will consider some of the possible future directions, with a focus on the different ways in which cognitive critics have embraced enactive approach-es to embodied and embedded cognition

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks