Neurophilosophy Forum is an interdisciplinary group of faculty and students who meet for discussion and debate on issues at the intersection of philosophy, neuroscience, and cognitive psychology. Feel free to bring your lunch and spread the word. All are welcome!
All talks occur in the Department of Philosophy on the 16th floor of 25 Park Place.
Abstract from Dr. Schwitzgebel: On an intellectualist approach to belief, the intellectual endorsement of a proposition (such as “the working poor deserve as much respect as the handsomely paid”) is sufficient or nearly sufficient for believing it. On a pragmatic approach to belief, intellectual endorsement is not enough. Belief is behaviorally demanding. To really, fully believe, you must also “walk the walk”. I argue that the pragmatic approach is preferable on pragmatic grounds: It rightly directs our attention to what matters most in thinking about belief.
Friday, October 13, 10:00 am
Adina Roskies (Dartmouth University) *This talk is part of the Brains & Behavior Distinguished Lecture Series in 124 Petit Science Center*
Title: Disorders of Consciousness: Neurotechnologies and Neuroethics
Abstract: The Precision Medicine Initiative, introduced under the Obama administration in 2015, has been heralded as a paradigm shift in twenty-first century medicine. Instead of traditional diagnostic categories, precision medicine focuses on re-stratifying the medical population on the basis of genetic and molecular markers that correspond with treatment protocols. In particular, the precision medicine platform can be characterized as standing on three legs. It is anti-nosological (opposed to traditional classification schema); reductionistic (favoring lower-level descriptions of systems); and big-data-driven. These three aspects of the initiative are often conceived of as concomitant factors in its success. Indeed one way to frame the ambition of precision medicine is in terms of the abolition of traditional nosological categories in favor of diagnostic biomarkers, themselves discovered through new techniques of data collection and analysis. In this paper I argue that the ideal of precision may have to be reinterpreted in order to apply to psychiatry, because psychiatry’s autonomy as a biomedical science is dependent on maintaining a non-reductive nosology. New classification protocols for psychiatric research projects, like the NIMH’s Research Domain Criteria project, are unable to distinguish psychiatric objects from those of related branches of medical science (such as neurology) and basic science (such as cognitive science). Other recent proposals for new classification protocols, such as the Hierarchical Taxonomy of Psychopathology, Person-Centered Psychiatry, and ROAMER (Roadmap for Mental Health Research in Europe), have countered with taxonomies that keep psychiatry focused on higher-level targets, such as psychological or phenomenological constructs or social and environmental factors. I defend the importance of such efforts by showing, first of all, that due to the integrated complexity of psychiatric diseases, precision psychiatry cannot expect the ready successes achieved in other fields, like oncology or immunology, in which biomarkers have been linked with treatment protocols through the discovery of causal mechanisms. Second, I argue that this does not mean that psychiatry cannot be in any sense precise; one need not be reductionistic in order to be anti-nosological, nor in order to avail oneself of new data sets and analytic tools. Third, I show that psychiatry’s capacity to participate in these two aspects of the precision medicine turn will rely on it embracing one or more taxonomic systems that can link our best theories of psychopathology with our best biomedical research. I conclude by suggesting that the arguments presented here may apply to other areas of medicine; as such, the three legs of precision medicine should not be seen as concomitant, but rather as contingently complementary.
Friday, September 23, 2016
Fiery Cushman (Harvard University)
Why learning matters for morality
Abstract: Humans use punishment and reward to modify each others' behavior, and we also learn from others' rewards and punishments. This simple dynamic animates much of our moral psychology, and I explore two of its consequences in detail. First, human punishment should be adapted to the contours and constraints of human learning. This can explain a peculiar feature of our moral judgments that philosophers call "moral luck": The fact that accidental outcomes play a large roll in determining punishment. Second, the architecture of human learning should dictate when and how we choose to harm others. I borrow from current neurobiological models of reinforcement learning to understand why we deem some harmful actions impermissible and others permissible. These case studies illustrate the role that learning systems play as a basic organizing principle in the moral domain.
For more information about Professor Cushman, visit his website here.
Friday, November 11 , 2016
Kevin LaBar (Duke University)
Neural Decoding of Emotional States
Abstract: An unresolved debate in affective neuroscience centers on how discrete emotions emerge from nervous system activity. I will describe recent evidence showing that multivariate pattern classifiers can reliably predict subjective feeling states during inductions of specific emotions from readouts of functional neuroimaging (fMRI) and psychophysiological data. Machine learning models were constructed to identify patterns of data from these measures that differentiate feelings of amusement, contentment, surprise, fear, anger, sadness, and neutral states in response to music and film clips. Classification performance was significantly above chance in predicting the target emotions. Errors in psychophysiological classification tracked the distance between emotions according to a categorical but not a dimensional model of emotion. The fMRI results revealed spatially-distinct and distributed voxel patterning that differentiated emotions from one another, and error analyses again favored predictions from categorical models. Finally, we found that the emotion-specific patterns emerged spontaneously during resting-state fMRI, and their frequency of occurrence predicted individual differences in anxiety, depression, and angry hostility. These findings highlight the utility of multivariate statistical methods in characterizing the nature of affect in the brain and autonomic nervous system.
For more information about Professor LaBar, visit his website here.
Friday, October 23, 2016
Kevin LaBar (Duke University)
Explanation: The Good, The Bad, and the Beautiful
Abstract: Like scientists, children and adults are often motivated to explain the world around them, including why people behave in particular ways, why objects have some properties rather than others, and why events unfold as they do. Moreover, people have strong and systematic intuitions about what makes something a good (or beautiful) explanation. Why are we so driven to explain? And what accounts for our explanatory preferences? In this talk I’ll present evidence that both children and adults prefer explanations that are simple and have broad scope, consistent with many accounts of explanation from philosophy of science, and with ties to ideas about inference to the best explanation in epistemology. The good news is that a preference for simple and broad explanations can sometimes improve learning and support effective inferences. The bad news is that under some conditions, these preferences can systematically lead children and adults astray.
For more information about Professor Lombrozo, visit her website: http://psychology.berkeley.edu/people/tania-lombrozo
Friday, September 25, 2015
Joshua Knobe (Yale University)
The Ordinary Notion of a “True Self”
Abstract: People’s ordinary understanding of the mind appears to be shaped in part by the notion of a ‘true self.’ A question then arises as to how people ordinarily make sense of this notion. Which aspects of your mind will people regard as belonging to your true self? Across a series of studies, we find that people’s true self attributions are impacted in a surprising way by their value judgments. (People tend to pick out whichever part of you they regard as most valuable and see that part as your true self.) Subsequent studies then show that this fact about people’s true self attributions then explains a number of otherwise puzzling aspects of people’s cognition.
For more information about Professor Knobe, visit his website: http://pantheon.yale.edu/~jk762/
Tuesday, April 14, 2015 (Part of the Brains & Behavior Distinguished Lecture Series)
Patricia Churchland (UC San Diego)
The Brains Behind Morality
For further information about Professor Churchland, visit her website: http://philosophyfaculty.ucsd.edu/faculty/pschurchland/index_hires.html
Friday, February 6, 2015
Chandra Sripada (University of Michigan):
Addiction, Fallibility, and Responsibility
Abstract: The debate about whether or not addicts have control over their drug-directed desires has reached a standoff, with substantial—even overwhelming—quantities of evidence marshaled by each side. My aim in this talk is to suggest a new direction for resolving this standoff. The current impasse arises because participants in the debate think about addiction using a resistibility framework; they focus on the question of whether desires to use drugs are too powerful to be contained. Drawing on a number of recent developments in the cognitive neuroscience of self-control, I instead propose a new model that emphasizes not resistibility, but rather fallibility. The key idea is that on every occasion of use, self-control processes exhibit a low but non-zero rate of stochastic failure. When these processes confront highly recurrent drug-directed desires, the cumulative probability of a self-control lapse rises inexorably towards certainty. In the final part of the talk, I take up the question of moral responsibility. The Fallibility Model presents problems for standard control-based accounts of moral responsibility and suggests the need to look for alternatives.
For more information about Professor Sripada, visit his website: http://sites.lsa.umich.edu/sripada/