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An argument recently proposed by Chirimuuta (2014) seems to motivate the rejection of the claims that every neurocognitive phenomenon can have a mechanistic explanation and that every neurocognitive explanation is mechanistic. In this paper, I focus on efficient coding models involving the so-called "canonical neural computations" and argue that although they imply some form of pluralism, they are compatible with two mechanistic generalizations: all neurocognitive explanations are (at least in part) mechanistic; and all neurocognitive phenomena that have an explanation have (at least) a purely mechanistic explanation. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine the relevance of an informational theory of knowledge to address recently discussed epistemic problems. I argue that Dretske’s classical approach is equivalent to the safety condition proposed by Pritchard to avoid epistemic luck. However, I claim that Pritchard’s condition has to be modified to avoid the so-called “generality problem” for reliabilism. I propose an alternative version of the requirement to deal with these problems and provide an equivalent informational condition. I conclude that this informational version is preferable since it reveals conceptual relationships between the constituents of knowledge. [ABSTRACT FROM AUTHOR]