Archive for the ‘Cog. Sci.’ Category

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Can there be spatially distributed parts in a mechanistic explanation?

June 9, 2014

Morgan Thompson

Abstract: Some mechanists maintain that mechanistic explanation is the ideal type of explanation in neuroscience and that mechanistic explanations can contain spatially distributed parts. There is a tension between these two claims. Carl Craver (2007) lists the following criteria for parts that are appropriate for featuring in mechanistic explanations: being detectable by multiple theoretically independent techniques (a la Wimsatt), having a stable cluster of properties (a la Boyd), being manipulatable, and being physiologically plausible. However, spatially distributed parts are not clearly appropriate on those criteria. I appeal to examples from neuroscience where researchers use multivariate pattern analysis to analyze spatially distributed networks. I conclude that mechanists should either adjust their criteria for parts appropriate for mechanisms so that they include spatially distributed parts or they should give up mechanistic explanation as the ideal explanatory scheme in neuroscience.

 

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The Cognitive Neuroscience Revolution

February 24, 2014

Trey Boone

Abstract: Once upon a time, there was cognitive science—the interdisciplinary study of cognition. It included (aspects of) six disciplines: psychology, computer science, linguistics, anthropology, neuroscience, and philosophy. The six disciplines were supposed to work together towards understanding cognition, but there was also a clear division of labor between them. On one side stood psychology, with the help of computer science, linguistics, anthropology, and philosophy; on the other side stood neuroscience. Psychology etc. studied the functional, cognitive, or—in Marr’s terminology—the computational and algorithmic levels; neuroscience investigated the neural, mechanistic, or implementation level. These two approaches were considered to be autonomous from one another. This division of labor leaves no room for cognitive neuroscience. Indeed, from this perspective, the very term “cognitive neuroscience” is almost an oxymoron, because neuroscience is supposed to deal with the mechanisms that implement cognitive processes, not with cognition proper. Yet cognitive neuroscience has emerged as the new mainstream in cognitive science. What gives?

We argue that cognitive science as traditionally conceived is on its way out and is being replaced by cognitive neuroscience, broadly construed. Cognitive neuroscience is still an interdisciplinary investigation of cognition. It still includes (aspects of) the same six disciplines (psychology, computer science, linguistics, anthropology, neuroscience, and philosophy). But the old division of labor is gone.

The old two-level view (functional/cognitive/computational vs. neural/mechanistic/implementation) is being replaced by a view on which there are many levels of mechanistic organization. No one level has a monopoly on cognition proper. Instead, different levels are more or less cognitive depending on their specific properties. Old psychological theories pitched at the “functional level” are simply sketches of mechanistic explanations at one of many levels of mechanistic organization (Piccinini and Craver 2011). The disciplines contributing to cognitive science are not autonomous from one another. Instead, these different disciplines contribute to the common enterprise of constructing multilevel mechanistic explanations of cognitive phenomena.

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Varieties of Neural Multi-Functionality

February 7, 2014

Joseph B. McCaffrey

Abstract: Many philosophers and cognitive scientists worry that the prevalence of multi-functional brain areas raises new challenges for the project of structure-function mapping in cognitive neuroscience.  Cathy Price and Karl Friston, on one hand, and Colin Klein, on the other, have recently offered competing accounts of the nature and significance of neural multi-functionality.  Price and Friston argue that brain areas perform many functions at one level of description and a single function at another.  Thus, researchers will need to develop a new ontology of brain functions to obtain robust structure-function mappings.  According to Klein, Price and Friston’s strategy is bound to yield vague or uninformative mappings.  Klein proposes that neuroscientists should restrict structure-function mappings to particular contexts instead of seeking functional descriptions that hold across different contexts.  In this essay, I claim that neither target account is likely to succeed as a general treatment of multi-functionality in cognitive neuroscience.  Using Carl Craver’s distinction between “activities” and “role functions,” I distinguish two ways of interpreting the dispute between Price and Friston and Klein.  Drawing on this distinction, I argue that both accounts rely on unmotivated theoretical commitments or unwarranted assumptions about the functional architecture of the brain. Drawing on examples from neurobiology and cognitive neuroscience, I argue it is plausible that the brain contains different kinds of multi-functional parts.  I conclude that a more nuanced account of neural multi-functionality would need to countenance this possibility.

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Day-O-WIPs 1.0

June 11, 2013

An unprecedented workshop-style afternoon packed with  five different WIPs:

“It is a good thing for every man to know a little about astronomy; it will make him a better man” Nora Boyd

“Boundary Conditions, Laws, and Nomological Content in Quantum Scattering Theory” Bihui Li

“From Waveguides to Field Theory” Michael Miller

“Psychiatric Objects in Research and Practice: Introducing the RDoC”  Kathryn Tabb

“Range Content, Attention, and the Precision of Representation” Trey Boone

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What is a Brain Area For? The Concept of “Function” in Cognitive Neuroscience

April 18, 2013

Joseph McCaffrey

Popular science abounds with claims that neuroscientists have uncovered the brain areas responsible for fear, social reasoning, romantic commitment, and numerous other aspects of human thought and emotion.  Neuroscientists frequently attribute cognitive functions (e.g., face recognition, motion detection, or analog representation of number) to particular regions of the brain.  However, several theorists have recently criticized these functional attributions because they fail to respect the diversity of cognitive tasks that recruit any brain region.  Furthermore, these theorists sometimes contend that our current taxonomies of brain functions do little more than project whatever view of the mind we already have (be it from psychology or folk psychology) onto the surface of the brain. These concerns may call for a revision of the notion of “brain function” in cognitive neuroscience. In this talk, I pose the question: What concepts of brain function are applicable to, and useful for, neuroimaging research?  My talk will mainly explore the landscape of a conceptual problem by outlining the dimensions along which new theories of brain function are situated.  I will briefly suggest an alternative conception of “brain function” that I think will ultimately work better than the candidates I identify in the extant literature.

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Operationalizing Consciousness: Subjective Report and Task Performance

October 26, 2012

Trey Boone

There are two distinct but related threads in this paper. The first thread is methodological and is aimed at exploring the relative merits and faults of different operational definitions of consciousness. The second thread is conceptual and is aimed at understanding the prior commitments regarding the nature of conscious content that motivate these operationalizations. The first approach I consider operationalizes consciousness in terms of dichotomous subjective reports. This approach is motivated by the assumption that consciousness is a maximally specific binary property. The second approach operationalizes consciousness in terms of graded subjective reports, and is correspondingly motivated by a view of consciousness as a graded property. I ultimately argue for a third position that maintains that consciousness is a binary property, but that it is not maximally specific. This alternative supports an operationalization of consciousness that involves integration of subjective report and task performance.

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Charles Darwin and Medical Associationism: Marks on a Blank Slate

April 12, 2012

Katie Tabb

It is widely recognized that Charles Darwin upended contemporary concepts of human nature by showing that the human mind, like the bestial one, was the product of evolution. This paper argues that a revision of traditional notions of human rationality was, in fact, a prerequisite for the development of Darwin’s theory, rather than simply a corollary of it. Examining Darwin’s early reflections on instinct during his so-called “Notebook Period,” I argue that Darwin drew on association psychology – particularly associationist theories of madness – in order to formulate his theory of inherited mental characteristics. Stemming from the work of John Locke and popularized during the following century by David Hartley and Joseph Priestley, associationism posited the interconnections of ideas and, concomitantly, the spirits or nerves that bore them, to be the foundation of human understanding and rationality. Associationists believed that the mentally ill differed in degree rather than kind from sane people, and replaced classical theories of the rational agent with an embodied theory of a contingent complex of ideas that could become pathological. Under the associationist model, the mentally ill misassociated ideas, and thus acquired corrupted chains of irrational thoughts. It was these pathological chains of ideas, rather than a dysfunction of any faculty of reason, that led to mental illness. Combining this theory with an embodied view of the mind (in part borrowed, I argue, from his phrenologist contemporaries) Darwin was able to construct a theory in which unconscious thoughts, feelings, and behaviors could be acquired and inherited across generations. I will conclude that in so doing Darwin buried in the foundations of his mature theory a vision of self that can be traced back to John Locke – of the human not as the rational animal, but as the animal with a memory of his own past.