Lenneberg and Brain Dynamics: Comments on Balari & Lorenzo (2017)

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Sergio Balari and Guillermo Lorenzo have a paper in the current volume of Biolinguistics, which is dedicated to celebrating the 50th anniversary of Lenneberg’s Biological Foundations of Language. The paper includes a number of unusual claims about computational approaches to neurobiology which I want to briefly address here.
They begin their discussion of neuolinguistics by claiming that “it is our contention that most self-declared biolinguistic approaches … have systematically misapplied the [Marrian] notion of ‘level’ in their attempts at solving the unification problem [of unifying linguistic computation with neurobiology]”. They claim that the connectome (the set of neural connections) and dynome/oscillome (brain dynamics) “are clearly not levels in any possible sense” purely because there is an ongoing project (that the authors are not involved in) to map how brain regions are dynamically connected. But this project crucially is far from over, and so even though at some point direct connectome-oscillome connections should be made, at the moment they clearly are fundamentally distinct levels of description – unless Balari and Lorenzo can explain how they are unified.
The following four paragraphs proceed to repeat the claim that we do not currently understand neural computation. This is true, but only insofar as a physics paper containing four paragraphs lamenting the lack of a Grand Unified Theory is also true. It is common knowledge in the field that neural computation is not understood, yet there are in fact a number of theoretical attempts to solve this conundrum, which Balari and Lorenzo do not critically engage with but rather dismiss out of hand:
“We raise these issues hopefully not for provoking a paralyzing effect, but to caution against an excessively enthusiastic reading of certain recent proposals concerning the computational character of brain oscillations (e.g., those of Murphy 2015, 2016) which do not seem to have taken into account the complications we just alluded to. To repeat, this is not to deny the potential relevance of brain oscillations in an eventual account of neural computation, but evidence so far is only correlational, in the sense that oscillations do play some role in linguistic tasks (e.g., Lewis et al. 2015, Lewis & Bastiaansen 2015, Ding et al. 2016), but we have so far been unable to disentangle the computational role they purportedly play.”
Had they read the papers they cite, they would have found that Murphy (2016a: 16) provides precisely the kind of analysis they claim is lacking in the field, discussing recent indications that oscillations play a causal role in the perceptual segregation of sound patterns – a topic expanded on in Murphy (2016b) which explores other recent tACS experiments into the theta-gamma code for working memory lending these oscillations a causal role in explaining the physical limitations of cognition. Citing existing work into the causal role of oscillations in behaviour is not an “excessively enthusiastic” thing to do, it is simply a way of providing evidence for one’s claims, a procedure seemingly alien to the authors.
More generally, as Uriagereka has already pointed out, expecting a one-to-one mapping between higher-order computational or psycholinguistic theories and neurobiology is similar to expecting a one-to-one mapping between cosmic background radiation and the Big Bang – certainly possible, but highly unlikely, and not even the goal of the neurolinguist attempting to rebuild our understanding of linguistic computation from the bottom-up.
In short, Balari and Lorenzo claim to provide a bold critique of the oscillation literature but in fact do no such thing.
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