Supervenience and Computational Explanation in Vision Theory

1993 ◽  
Vol 60 (1) ◽  
pp. 86-99 ◽  
Author(s):  
Peter Morton
1997 ◽  
Vol 5 (2) ◽  
pp. 253-281 ◽  
Author(s):  
Josefa Toribio

The paper has a negative and a positive side. The negative side argues that the classical notions of narrow and wide content are not suitable for the purposes of psychological explanation. The positive side shows how to characterize an alternative notion of content (ecological content) that is suitable for those purposes. This account is supported by (a) a way of conceptualizing computation that is constitutively dependent upon properties external to the system and (b) empirical research in developmental psychology. My main contention is that an adequate computational explanation of the behavior involved in cognitive activities should invoke a concept of content that can capture the intimate dynamical relationship between the inner and the outer. The notion of content thus reaches out to include the set of skills, abilities and know-hows that an agent deploys in a constantly variable environment. The assumption underlying my attempt to characterize this ecological notion of content is that cognition is better understood when treated as embedded cognition and that the idea of cognitive significance ought to be cashed out in non-individualistic and pragmatic terms.


Author(s):  
Silvano Zipoli Caiani

AbstractIn this paper I defend the epistemic value of the representational-computational view of cognition by arguing that it has explanatory merits that cannot be ignored. To this end, I focus on the virtue of a computational explanation of optic ataxia, a disorder characterized by difficulties in executing visually-guided reaching tasks, although ataxic patients do not exhibit any specific disease of the muscular apparatus. I argue that addressing cases of patients who are suffering from optic ataxia by invoking a causal role for internal representations is more effective than merely relying on correlations between bodily and environmental variables. This argument has consequences for the epistemic assessment of radical enactivism, whichRE invokes the Dynamical System Theory as the best tool for explaining cognitive phenomena.


1998 ◽  
Vol 10 (1) ◽  
pp. 151-156
Author(s):  
María Del Carmen Puerta-Melguizo ◽  
María Teresa Bajo

2013 ◽  
Vol 25 (12) ◽  
pp. 2107-2123 ◽  
Author(s):  
Anna C. Schapiro ◽  
James L. McClelland ◽  
Stephen R. Welbourne ◽  
Timothy T. Rogers ◽  
Matthew A. Lambon Ralph

Human and animal lesion studies have shown that behavior can be catastrophically impaired after bilateral lesions but that unilateral damage often produces little or no effect, even controlling for lesion extent. This pattern is found across many different sensory, motor, and memory domains. Despite these findings, there has been no systematic, computational explanation. We found that the same striking difference between unilateral and bilateral damage emerged in a distributed, recurrent attractor neural network. The difference persists in simple feedforward networks, where it can be understood in explicit quantitative terms. In essence, damage both distorts and reduces the magnitude of relevant activity in each hemisphere. Unilateral damage reduces the relative magnitude of the contribution to performance of the damaged side, allowing the intact side to dominate performance. In contrast, balanced bilateral damage distorts representations on both sides, which contribute equally, resulting in degraded performance. The model's ability to account for relevant patient data suggests that mechanisms similar to those in the model may operate in the brain.


Synthese ◽  
2021 ◽  
Author(s):  
Nir Fresco ◽  
B. Jack Copeland ◽  
Marty J. Wolf

AbstractDo the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question ‘What does a particular neuronal system do?’ is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends some support to the idea that a single neuronal structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation.


2011 ◽  
Vol 11 (11) ◽  
pp. 64-64
Author(s):  
X. Yang ◽  
Z. Liu

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