Archive for the ‘Neuroscience’ Category


“Can Resting State Neuroscience Save Brain Mapping?” (01/07/2016)

January 6, 2016

Joseph McCaffrey

Abstract: Human brain mapping is one of the central goals of cognitive neuroimaging research. Despite the popularity of functional MRI (fMRI) for mapping cognitive functions onto the brain, many philosophers and neuroscientists believe that traditional, “task-based” fMRI is in a state of crisis. In this talk, I present the methodological and conceptual challenges facing task-based fMRI, and examine whether “resting state” fMRI can save brain mapping from this crisis.


The Brain’s Heterogeneous Functional Landscape

September 26, 2014

Joe McCaffrey

Abstract: While many cognitive neuroscientists believe that brain areas are often “multi-functional,” no one knows exactly what this means. Cathy Price and Karl Friston claim that brain areas typically perform many functions at one level of description and a single function at another level of description. Therefore, neuroscientists need to develop new “cognitive ontologies” to capture these functional similarities. Colin Klein draws a very different lesson from the same findings: neuroscientists should map functions onto the brain in a “context-sensitive” fashion. In this essay, I claim that neither account is likely to succeed as a general treatment of multi-functionality. I argue that both accounts rely on a “uniformity assumption,” which holds that brain areas are multi-functional in a canonical way. I contend that this assumption is mistaken—it is plausible that brain areas, like other biological components, are multi-functional in a variety of scientifically-interesting respects. I call this the “Functional Heterogeneity Hypothesis.”



DAY-O-WIPs 4.0

July 14, 2014

“The Nature of Models and Modeling: Two Perspectives” Yoichi Ishida

“The Curious History of the Footless Tortoise” Aaron Novick

Evan Pence


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.



The Multiplicity of Protocols

February 28, 2014

David Colaco

Abstract: I investigate what implications (1) effects being dependent on experimental protocols, and (2) a multiplicity of experimental protocols, have for convergence and generalization – which I refer to jointly as extension – of findings in neuroscience and other sciences. Together, these claims raise concerns over whether we can compare findings across laboratories, or generalize them to the world. I introduce two successful cases of extension despite different protocols. These cases elucidate what kinds of differences are relevant to extension. In particular, I focus on the role the research purpose plays in understanding which differences make a difference and which do not.


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.


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.