A contextualist approach to functional localization in the brain

Burnston, Daniel C.

doi:10.1007/s10539-016-9526-2

Cited by 42 publications

(32 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 1). It also adds neuromodulation and physiological circuit properties as noncognitive kinds of context to Burnston's contextualist approach to multifunctionality (Burnston 2016). Although these arguments will have to be developed in detail elsewhere, the examples of resting-state research and multifunctionality show that the patchwork approach can help neuroscientists and philosophers to overcome cognitive myopia in a variety of topics surrounding the concept of neural function.…”

Section: Resultsmentioning

confidence: 99%

“…5 For example: FEF activity represents a visual stimulus that is salient to the animal. Neuroscientists mostly use "information" in this narrow sense: sequences of neuronal action potentials carry information about differences in stimuli from the environment (deRieke et al 1999, deCharms and Zado 2000, Garson 2003, Burnston 2016. Noncognitive mechanisms do not carry information in this narrow sense.…”

Section: )mentioning

confidence: 99%

“…Philosophers who discuss the problem of multifunctionality reinforce this exclusive focus on cognitive function. Philosophical accounts of this problem aim to show how functional localization is possible when a neural structure contributes to different cognitive and behavioral tasks in different contexts (Rathkopf 2013, McCaffrey 2015, Burnston 2016. These accounts exhibit cognitive myopia because they implicitly assume that "multifunctionality" means "cognitive multifunctionality".…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Beyond cognitive myopia: a patchwork approach to the concept of neural function

Haueis

2018

Synthese

View full text Add to dashboard Cite

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing "neural function". Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive "patches" of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain's capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Beyond cognitive myopia: a patchwork approach to the concept of neural function

Haueis

2018

Synthese

View full text Add to dashboard Cite

show abstract

“…The case study is offered as an exemplar of this kind of explanation. In addition, it shows how extant contextualist approaches to neural function (Burnston [2016a(Burnston [ ], [2016b; Klein [2012]) can help make sense of massively multifunctional brain networks.…”

Section: The Context Objection To Reduction 7 Conclusion ------------mentioning

confidence: 99%

Getting over Atomism: Functional Decomposition in Complex Neural Systems

Burnston¹

2021

The British Journal for the Philosophy of Science

Self Cite

View full text Add to dashboard Cite

Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of decomposition, which I call ‘atomism’, and not with decomposition writ large. Atomism posits that function ascriptions must be made to parts with minimal reference to the surrounding system. Complexity does indeed falsify atomism, but I contend that there is a weaker, ‘contextualist’ notion of decomposition that is fully compatible with the properties that holists cite. Contextualism suggests that the function of parts can shift with external context, and that interactions with other parts might help determine their context-appropriate functions. This still admits of functional decomposition within a given context. I will give examples based on the notion of oscillatory multiplexing in systems neuroscience. If contextualism is feasible, then holist inferences are faulty—one cannot infer from the presence of complexity to the failure of decomposition, mechanism, and reductionism. 1Introduction2Atomism3Holist Inferences in Detail4Contextualism as an Alternative5Multiplexing and Contextualist Decomposition 5.1Internal dynamics5.2Dynamic interaction5.3Network dependence6Philosophical Upshot 6.1The scope and limits of mechanistic explanation6.2The context objection to reduction7Conclusion

show abstract

“…We are now in a position to see why LRIs are so controversial. The non‐selective nature of most brain regions is not (and should not) be disputed, as emphasized by the growing scientific and philosophical literature on multi‐functional brain areas (Anderson, ; Burnston, ; McCaffrey, ; Rathkopf, ). As mentioned above, areas such as the amygdala underlie an entire host of different cognitive processes.…”

Section: The Lack Of Selectivity Objectionmentioning

confidence: 99%

The Future of Cognitive Neuroscience? Reverse Inference in Focus

Nathan

Pinal

2017

Philosophy Compass

View full text Add to dashboard Cite

This article presents and discusses one of the most prominent inferential strategies currently employed in cognitive neuropsychology, namely, reverse inference. Simply put, this is the practice of inferring, in the context of experimental tasks, the engagement of cognitive processes from locations or patterns of neural activation. This technique is notoriously controversial because, critics argue, it presupposes the problematic assumption that neural areas are functionally selective. We proceed as follows. We begin by introducing the basic structure of traditional “location‐based” reverse inference (§1) and discuss the influential lack of selectivity objection (§2). Next, we rehearse various ways of responding to this challenge and provide some reasons for cautious optimism (§3). The second part of the essay presents a more recent development: “pattern‐decoding reverse inference” (§4). This inferential strategy, we maintain, provides an even more convincing response to the lack of selectivity charge. Due to this and other methodological advantages, it is now a prominent component in the toolbox of cognitive neuropsychology (§5). Finally, we conclude by drawing some implications for philosophy of science and philosophy of mind (§6).

show abstract

A contextualist approach to functional localization in the brain

Cited by 42 publications

References 43 publications

Beyond cognitive myopia: a patchwork approach to the concept of neural function

Beyond cognitive myopia: a patchwork approach to the concept of neural function

Getting over Atomism: Functional Decomposition in Complex Neural Systems

The Future of Cognitive Neuroscience? Reverse Inference in Focus

Contact Info

Product

Resources

About