The cognitive neuroscience revolution

Abstract

We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain cognition. To a large extent, practicing cognitive neuroscientists have already accepted this shift, but philosophical theory has not fully acknowledged and appreciated its significance. As a result, the explanatory framework underlying cognitive neuroscience has remained largely implicit. We explicate this framework and demonstrate its contrast with previous approaches.

From symbols to icons: the return of resemblance in the cognitive neuroscience revolution

“…This new research paradigm, they argue, abandons the strong autonomy assumption at the core of TCS in favour of a multilevel mechanistic approach to neurocognitive explanation: a theoretical "revolution [that] requires a different way of thinking about levels, cognitive explanation, representation, and computation" (Boone andPiccinini 2015, p. 1513) We are in full agreement with Boone and Piccinini's thesis, and return in more detail in Sect. 4 to the nature of multilevel mechanistic explanation.…”

“…Second, a central assumption of cognitive neuroscience is that computations over internal representations causally explain intelligence (Bechtel 2008;Boone and Piccinini 2015). But detection as such cannot explain intelligence: the kind of exquisite informational sensitivity to environmental contingencies that advocates of indicator semantics appeal to in order to explain representation is an instance of the very intelligence supposed to be explained by representation (Churchland 2012;Cummins 1996).…”

“…2 Symbols and syntax in traditional cognitive science Boone and Piccinini (2015) identify three central features of "traditional cognitive science" (henceforth TCS), the research programme they take cognitive neuroscience to have superseded. First, TCS understands cognition as a form of digital computation, as exemplified in Newell and Simon's (1976) famous "physical symbol systems" hypothesis, according to which the essence of intelligence lies in the rule-governed manipulation of symbolic data structures.…”

“…The second was closely allied to this commitment: cognitive-scientific explanation is functional explanation that abstracts away from "implementational" details in the brain, in much the same way that a software description of processes implemented in commercial digital computers abstracts away from details of their hardware. Third, this led to what Boone andPiccinini (2015, p. 1510) call the "strong autonomy assumption": scientific psychology is theoretically independent from neuroscience; the former concerns the functional architecture of cognition, the latter merely the contingent matter of implementation.…”

“…As Boone andPiccinini (2015, p. 1510) note, this assemblage of commitments has the embarrassing upshot of making "cognitive neuroscience" sound like an oxymoron-embarrassing, because cognitive neuroscience has emerged as the "mainstream approach to studying cognition." This new research paradigm, they argue, abandons the strong autonomy assumption at the core of TCS in favour of a multilevel mechanistic approach to neurocognitive explanation: a theoretical "revolution [that] requires a different way of thinking about levels, cognitive explanation, representation, and computation" (Boone andPiccinini 2015, p. 1513) We are in full agreement with Boone and Piccinini's thesis, and return in more detail in Sect.…”