Yup

Steven Gross sent me this link with the subject line "up your alley." He is absolutely right. There are really are some views that are so uninformed and so unresponsive to the obvious that listening carefully can be at least a waste of time and often a hazard to your intellectual health. There are many ideas out there that are truly bast their sell-by date but are nonetheless accorded a kind of respect that verges on the dishonest. I have spent more time than I care to considering some of these views prominent among some linguists, psychologists and neuroscientists and showing their shortcomings. Was it worth it? Not really. Like weeds they spring to life given half a chance. Oh well. At any rate, the Onion, again, gets it right. There is such a thing as being too open-minded.

Poeppel on brains

For those of you who may be in Nijmegen January 21, 22, 23, David Poeppel is going to give three terrific sounding lectures. Here are the abstracts for the three. David is one of those doing God’s work in cog-neuro of language in that he is trying to find how the stuff linguists have discovered live in brains. Moreover, unlike many he understands the difference between where and how (see lecture 3). I can think of no better way of spending three days in January, thoug, truth be told, why couldn’t these have been given in Rome or Barcelona? Oh well. Every silver lining has a cloud.

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David Poeppel - Nijmegen Lectures

Lecture Series Title:

(Un)conventional wisdom: Three neurobiological provocations about brain and language

The lectures discuss recent experimental studies that focus on general questions about the cognitive science and neural implementation of speech and language. On the basis of the empirical findings, I reach (currently) unpopular conclusions, namely that speech is special (not just ‘mere’ hearing), that language is structured (not just ‘mere statistics’), and that linguistic theorizing of an appropriately abstract computational form will underpin proper explanation.

Lecture 1: On how speech is pretty special

In this presentation, I consider the notion of specialization for sounds, and especially speech. Speech contains temporal structure that the brain must analyze to enable linguistic processing. To investigate the neural basis of this analysis, we used sound quilts – stimuli constructed by shuffling segments of a natural sound, approximately preserving its properties at short timescales while disrupting them at longer scales. We generated quilts from foreign speech, to eliminate language cues, and we manipulated the extent of natural acoustic structure by varying the segment length. Using fMRI, we identified bilateral regions of the superior temporal sulcus (STS) whose responses varied with segment length. This effect was absent in primary auditory cortex and did not occur for quilts made from other natural sounds, or acoustically-matched synthetic sounds, suggesting tuning to speech-specific spectrotemporal structure. When examined parametrically, the STS response increased with segment length up to ~500 ms. The results identify a locus of speech analysis in human auditory cortex, distinct from lexical, semantic, or syntactic processes.

Lecture 2: On the sufficiency of abstract structure

The most critical attribute of human language is its unbounded combinatorial nature: smaller elements can be combined into larger structures based on a grammatical system, resulting in a hierarchy of linguistic units, e.g., words, phrases, and sentences. Mentally parsing and representing such structures, however, poses challenges for speech comprehension. In speech, hierarchical linguistic structures do not have boundaries clearly defined by acoustic cues and must therefore be internally and incrementally constructed during comprehension. Previous studies have suggested that the cortical activity is synchronized to acoustic features of speech, approximately at the syllabic rate, providing an initial time scale for speech processing. But how the brain utilizes such syllabic-level phonological representations closely aligned with the physical input to build multiple levels of abstract linguistic structure, and represent these concurrently, is not known. On the basis of MEG experimentation, I demonstrate that during listening to connected speech, cortical activity of different time scales concurrently tracks the time course of abstract linguistic structures at different hierarchical levels, e.g. words, phrases, and sentences. Critically, the oscillatory neural tracking of hierarchical linguistic structures is dissociated from the encoding of acoustic cues as well as from the predictability of incoming words. The results suggest that a hierarchy of neural processing timescales underlies grammar-based internal construction of hierarchical linguistic structure.

Lecture 3: On the insufficiency of correlational cognitive neuroscience

We consider here two inter-related problems that current research attempts to - or should attempt to - solve. The first challenge concerns how to develop a theoretically well- motivated and biologically sophisticated functional anatomy of the language processing system. This "maps problem” is by and large a practical issue. Much as is true for vision, language research needs fine-grained maps of the regions that underpin the domain; which techniques can be harnessed to build an articulated model (in light of having no animal models) remains difficult. The second, closely related challenge concerns the "parts list" (or the set of primitives; or the ontology) for language actually under consideration. Coarse conceptions (such as the original “production" versus “comprehension") are completely insufficient and incoherent. Current ideas, such as phonology versus syntax versus semantics are also unlikely to provide a plausible link to neurobiological infrastructure. This "mapping problem” constitutes a more difficult, principled challenge: what is the appropriate level of analysis and granularity that allows us to map between (or align) the biological hardware and the computational requirements of language processing? The first challenge, the maps problem, addresses how to break down linguistic computation in space. The second challenge, the mapping problem, addresses how to break down language function into computational primitives suitable for neurobiology. If these problems are not explicitly tackled, our answers to ‘brain and language’ may remain correlational, not mechanistic and explanatory.

Media linguistics

Language sells. How else to explain the number of consistently uninformed articles in the major media purporting to bring scientific expertise to one or another language phenomenon.  Most recently, there have appeared a trio of articles in The Age, The Guardian and Newsweek whose aim is to delight he masses with scientific insights into language. I was intending to write about these, especially the horrible piece by Ibbotson and Tomasello. However, I have been (very very happily) been spared the chore. I hate cleaning out stables, and I don't have to do it because Asya Pereltsvaig has done the unpleasant lifting (here).  Let me add three comments to her excellent discussion.

First, I like the tone. It recognizes that this stuff is junk and says so. It also provides a handy set of heuristics for those wanting to identify probable junk. I hope that the popular press takes note and acts accordingly, but I am not going to hold my breath.

Second, Asya links to many detailed comments of relevance to the (ahem) substantive points made. The fact is that there are no substantive points made. The Ibbotson and Tomasello piece, as Asya and others point out, is either vacuous or false (sound familiar?). Yes, social interaction probably has something to do with language, and no this tells us very nothing about linguistic structure in any domain. In fact, it is not clear that the claims made are intended to be taken seriously given how little thought it takes to show how inadequate they are (e.g. see the excellent boxed comment by David Pesetsky on Asya's post). What's evident is that editors allow clearly inflated and uninformed claims to be made without any skepticism whatsoever. I used to find this amazing, but again these are the same people who bring us weapons of mass destruction, lights at ends of tunnels,  the immanent collapse of social security and rampant voter fraud. Why expect better when it comes to linguistics? For these venues, language is a little like animal planet: forget biology, look for cute, fuzzy or odd. This said, kudos to those that engage.

Third, though infuriating, I am suspect that this sort of junk in the popular press does not matter much to the standing of linguistics. What matters a whole lot more is that the absence of reasonable linguistic coverage in the popular science press and the absence of respectable linguistics in the research of our scientific neighbors in computer science, psychology and neuroscience. Let me discuss each briefly in turn.

Not having decent stuff in this venue, I believe, matters a lot. Why? Because this is where scientists cover the science that are not their specialties. That should be our intended audience. Of course, I have nothing against correcting the journalistic unwashed. But, I have doubts that their views would carry much weight in the science community if good stuff were constantly being discussed in venues like Science Daily, Scientific American, or New Scientist and aggregators like Aeon or Nautilus. We should be figuring out how to get the attention of these venues.

Second, we ignore the bad linguistics prevalent in psych, CS and cog-neuro at our peril. These are far more important politically than linguistics is. If we fail to engage with this audience I fear that we will have a short half life. Many linguists have stopped seeing linguistics as part of cognition and biology. Indeed, it often looks like many linguists consider the cognitive/biolinguistics perspective on GG to be windy sentiment. This hurts us far more than a few stupid pieces in the popular press.

So, thanks to Asya for carrying the can here and to others who have jumped in to shovel the garbage. I thank you from the booth of my blogging heart.

Nativist (in)sight

Karthik sent me this link (here) to some very interesting work on vision. It concerns the recovery of sight in people who were blind from birth. It seems that one can be born with cataracts, which completely prevents visual perception. Pawan Sinha (PW), a neuroscientist at MIT, had the generous idea of surgically reversing these cataracts and the bright idea of seeing what would happen to the patients visual capacities once eyesight was regained. The findings illuminate what it means to claim that some capacity is innate. Let me explain.

As I’ve mentioned before (e.g. here), everyone is a nativist.  The question is not whether minds/brains are structured but how they are structured. Why is everyone a nativist? Because everyone believes that minds/brains inherently generalize from experience and there is no generalization (i.e. inductive “leaps”) without natively supplied directions guiding these leaps. No “biases” or given modes of generalization (i.e. projectable predicates) no induction. No induction no thought. Unstructured minds/brains are boring blobs of neuronal protoplasm. So, everyone, and I mean everyone, is a nativist.

So, the question is not if the mind/brain has structure but what structure it has, and this latter question can only be solved empirically. Illusions provide fruitful grounds for inquiry. Why? Because, by hypothesis, illusions are not veridical. In other words, illusions do not “copy” the visual input. They may use it, but they clearly go beyond it (i.e. “add” to it, or ignore it, or distort it or…). And as we wish to know how minds/brains generalize, studying how minds/brains go beyond the information in the input (i.e. how illusions arise) is a good place to look for its biases, for what minds/brains bring to the act of induction.

This is where PW’s unfortunates come in. Because of their cataracts, these people received zero visual input from birth. A plausible way of studying what the mind/brain brings to visual perception is to see what happens when these visual impediments are removed. What do these late seers see?

Well, it seems that they are immediately susceptible to two famous illusions; the Ponzo and Muller-Lyer (see above cited paper and this more technical one). In other words, as soon as the cataracts are removed the subjects “see” the illusions (within 48 hours of the surgery). Or as PS and colleagues put it (here, R2):

…even at the very outset of their visual experience, the Prakash children already exhibit susceptibility to the Ponzo and the Muller-Lyer illusions.

And from this the paper concludes, very reasonably IMO that

This suggests that susceptibility to the Ponzo and Muller-Lyer illusions likely does not depend upon a sophisticated analysis of the scene. [1]

Why not? Because being able to parse scenes is something that comes along somewhat later.[2] Thus, these illusions are likely grounded in “processing mechanisms that do not depend on visual experience.”[3]

This is all very nice stuff. However, it strikes me that “immediate” behavioral expression of the underlying capacity sets the nativist bar very high. Let me explain. In another paper (here) PS and friends discuss a classic problem first mooted in the 17^th century; Molyneux’s Problem (here).

Suppose a man born blind, and now adult, and taught by his touch to distinguish between a cube and a sphere of the same metal, and nighly of the same bigness, so as to tell, when he felt one and the other, which is the cube, which is the sphere. Suppose then the cube and the sphere placed on a table, and the blind man made to see: query, Whether by his sight, before he touched them, he could now distinguish and tell which is the globe, which the cube? To which the acute and judicious proposer answers: ‘Not. For though he has obtained the experience of how a globe, and how a cube, affects his touch; yet he has not yet attained the experience, that what affects his touch so or so, must affect his sight so or so…’

PS & Co uses the cataract subjects to test how quickly it is possible to generalize from one perceptual modality to another, in this case from touch to sight. They find that in contrast to the illusions discussed above that appear immediately, it takes time for the inter-modal transfers to become operative. As PS &Co put it (p.2):

Our results suggest that the answer to Molyneaux’s question is likely negative. The newly sighted subjects did not exhibit an immediate transfer of their tactile shape knowledge to the visual domain.

Note the word ‘immediate.’ The paper suggests that anything but “immediate” generalization implicates a non-native capacity. Why believe this? It’s not crazy to think that being able to coordinate and use two native capacities might take more time than exploiting but one. Moreover, as the paper indicates the inter-modal transfer happens very rapidly. We are talking to transfer in as little as five days. If this be “learning” it is remarkably rapid. It may not be quite one-trial (though who knows) but it’s not exactly la longue duree (here) either. Indeed, PS & Co notes (p. 2) that

Rapidity of acquisition suggests that the neuronal substrates responsible fro cross-modal interaction might already be in place before they become behaviorally manifest.

Indeed. It seems that we are inter-modal transfer “ready” and that it takes very little to get the whole thing into gear. I don’t know about you, but this seems very like saying that we are built for this, rather than that we, in any interesting sense of the word, “learn” it. This suggests that there is a perfectly good sense in which Molyneaux (and Locke who agreed with him) was, in an important sense, wrong. The mind/brain is very ready to jump to inter-modal conclusions, as the smallest input seems able to trigger the cross modal inferences.

As I said at the outset, everyone is a nativist. These papers show that for some visual behaviors no visual input is required and for others very little is needed. This tells us something about what must be native. It implies that minds/brains are (largely) pre-wired for these kinds of perception.

In addition, the work also generates an interesting question: what does the difference between “immediate” vs “very rapid” onset of behavior tell us about the built-in structures of interest? Is this a useful difference? I am unconvinced, but I could be wrong. That said, these are great little papers and usefully advance our thinking about the mind/brain’s native proclivities.

Last note: this stuff is also clearly of interest to critical period hypotheses. Recall that this work is based on systems that were largely dormant until rather late. Nonetheless they quickly became operative when the opportunity arose (i.e. the channels were unclogged). This strongly suggests that not all mind/brain capacities disappear if not used. Which do and which don’t seem like worthwhile things to try to find out.

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[1] I personally find the hedging here unhelpful. What’s with this “suggests” and “likely” stuff. It’s clear that the authors think that this is the right conclusion. The hedging is there, I believe, to sound “scientific,” (i.e. to sound like they are very open minded). But the conclusion from their data seems much stronger than this. The authors do not really believe that a learning explanation of these effects is a reasonable given their data. So they don’t really think that their results leave the question open. And if not, why the hedging? I don’t see the point and it just confuses matters.

[2] Note that while early onset is a good indicator of native structure, late onset is not a good argument for “learning.” Native is what’s needed to bridge the gap from input to acquired capacity. Early onset precludes the capacity of significant environmental input (a pre-requisite for learning). However, late onset does not imply the existence of relevant input, only its possibility. That learning takes time does not mean that anything that takes time is learned. This is what POS arguments have taught us.

[3] I should add that this paper is not arguing against a straw man. Richard Gregory, a very good visual perception person, held that we effectively learn to see the illusion in the sense of inducing it from environmental observations.

More public reactions on the Lingua resignations

Here's something from the non-academic press on the Glossa initiative. Actually, less on that and more on the mass resignation of the Lingua editorial board. It is getting lots of play in the "real" world. It seems that many out there really don't like Elsevier's predatory policies.

Lingua makes it to the Chronicle

I read several news aggregators and the Lingua "revolt" is getting wide press. Here is the coverage in the Chronicle for Higher Ed. Interesting. I wish the old editors luck with their new venture.

Brains, grammars and hype (part 2)

In the previous post (here), I showed how Frankland and Greene identifies a role sensitive region of cortex and sub-areas within that region that are differentially sensitive to the doer and done-to roles. In other words, if correct, F&G offers a hypothesis about where roles like doer and done-to get coded. Finding a region sensitive to thematic parameters would be a useful contribution given our vast ignorance concerning the brain bases of anything (see here discussed here). Let me repeat this loudly lest I not be heard: FINDING A REGION SENSITIVE TO THEMATIC PARAMETERS WOULD BE A USEFUL CONTRIBUTION GIVEN OUR VAST IGNORANCE CONCERNING THE BRAIN BASES OF ANYTHING. However, F&G claims to do a whole lot more than this. Here I want to consider if it does do more. So the question for what follows: does F&G explain how the brain codes thematic information as it appears to claim to do?

No. Not really. The paper may have identified a region that correlates to role information but F&H’s claim that it explains how brains code such information seems to me quite overblown.[1] Here’s what I mean.

What would it mean to show how brains code such information? F&G tells us. In the abstract, it takes its discovered empirical results to support the following claim:

At a high level, these regions may function like topographically defined data registers, encoding the fluctuating values of abstract semantic variables. This functional architecture, which in key respects resembles that of a classical computer, may play a critical role in enabling humans to flexibly generate complex thoughts.

What’s this mean? Those familiar with earlier critiques of connectionism should recognize the allusions. People like Fodor and Pylyshyn, Marcus, and Gallistel argued that brains had a Turing rather than a connectionist architecture. They provided various arguments for this, including observations about the systematicity of cognition (in particular in language), which makes perfect sense if one assumes that brains embodied read/write memories with variables and valuation of variables, being key elements.  Most of the arguments provided were behavioral (though see Gallistel for more direct arguments that brains cannot be connectionist either). F&G is clearly pointing to these claims in the abstract above (indeed, Fodor and Pylyshyn, Marcus and Pinker are noted in the bibliography in relation to this). So, F&G clearly intends its results to be an argument in favor of Turing architectures and a challenge for connectionist architectures. However, if this is the intent, I don’t see that F&G’s argument adds anything to the earlier behavioral arguments. Why not?

F&G notes that its results are consistent with Turing architectures, but then so are most connectionist models so far as I can tell. There is nothing in these models that prevents the hidden layers (appropriately tuned) from isolating doer and done-to roles. Indeed, this is regularly done in such models for other abstract categories. So, if F&G intends to use its results to argue for classical architectures, then it is unclear to me what it has actually added to the arguments advanced by Fodor & Pylyshyn, Marcus or Gallistel. Note, I have nothing against the conclusion that connectionist architectures are bad neural models (less coyly: I am pretty confident that connectionist architectures suck). What I don’t see is that F&G adds anything to the previous arguments. I would go further (as you probably knew I would). The concluding discussion section of F&G notes that there is a “class of models that use matrix operations to combine spatially distributed representations into conjunctive representations…that could potentially be augmented…[to] encode conjunctive representations for distinct semantic roles” (11737). For the uninitiated, this is connectionist speak. In other words, as F&G notes, its results do not argue against a connectionist conception in favor of a more classical Turing view. Or more correctly, the F&G results do not add anything to the earlier (completely compelling arguments) arguments. So, if F&G intends its “how” contribution to consist in an argument for a classical architecture and against a connectionist one, then, by its own admission, it fails.[2]

What else could the “how” mean? Another possible contrast is between the kinds of codes the brain uses to track information; in particular does the brain use a place code or a rate code to track doers and done-tos. Let me expand a bit.

One line of thinking (that F&G says its results endorse) exploits geography to code information: “functional segregation corresponding to spatial segregation” and binding of variables to values executed by bringing the two into spatial proximity. This contrasts with another view wherein binding is signaled through temporal proximity (synchronization) rather than spatial. F&G claims that its results (my emphasis)

…suggest that such temporal correlations may be unnecessary in this case because the bindings may instead be encoded through the instantiation of distributed patterns of activity in spatially dissociable patches of cortex devoted to representing distinct semantic variables” (11736). 

However as the paper notes, and the highlighted mealy-mouthed modals indicate, this conclusion is not particularly well supported by their experiments. Or, more correctly, F&G’s tools preclude a strong choice between the two.  As F&G notes, the hunt was conducted using fMRI and because these have limited temporal resolution (on the order of 1000 ms) fMRI probes cannot generally “see” rate codes. The best that F&G can conclude is that because it was able to localize roles in geographically proximate yet distinct locals this suggests that a place coding of roles might be right, though not to the exclusion of rate codes. The logic is that place codes require segregated (proximate?) geography and this was found. Hence the finding supports the claim that for role information the brain uses a place code. But this conclusion does not follow. To establish it firmly one needs the inverse: if segregated regions then place code. But this is not obviously true. Moreover, and here I am asking, do neuro people believe that anytime they can localize functions in different (nearby) places that this is evidence for place codes? Sounds wrong to me, but, hey, I don’t do this.[3]

I should add that the second experiment is the crucial one for this conclusion, and it is less robust than the first as F&G notes. The bifurcation of lmSTC into doer and done-to areas is quite subtle empirically and some of the participants in the UMD discussion thought that the data here was quite brittle. Again, this is beyond my pay grade.

F&G, then, really says very little (if anything) about the how question. In fact, it never really addresses it except tangentially. “Where?,” not “how?”, is what F&G addresses.  Let me squawk about this for a moment.

IMO, neuro types often confuse how does X work with where is X located. Why they think answering one answers the other I do not know. I don’t object to the claim that knowing where things are in the brain might be/is likely to be a good first step in figuring out how the brain does what it does. But reading F&G (and this paper is hardly unique) leads me to think that CNers can’t tell the difference between where and how.  And this is a problem.

One consequence of the confusion is that it denigrates the cognitive work that it presupposes. F&G relies on an unanalyzed conception of thematic roles. In fact, it relies on a truism: that sentences like John saw Mary do not mean the same as Mary saw John and that the difference has something to do with the fact that what sentences say about John/Mary in the first sentence is effectively reverses what the second sentence says about them.  This is a truism, or as close to one as might be imagined.  However, as any linguist knows, there are many different theories to explain how this truism is true. Some exploit theta roles, some grammatical roles, some the internal/external distinction, some first vs second merge, some predicate argument structure with 1^st and 2^nd argument positions of a predicate, some Deep Structures, some kernel sentences, etc. When a linguist asks how is thematic information represented, s/he means how can we distinguish between these apparently different conceptions all of which code/represent the observed doer/done-to difference. F&G cannot tell us which of these is right, nor does it intend to. This “how?” question is beyond the technical reach of current neuro apparatus.  That’s not a criticism. Here is the criticism: by confusing where with how, F&G continues the tradition of treating distinctions beyond the range of its probes as non-questions, rather than as questions beyond the resolution of its methods. The fact is that cognitive probes into the structure of brains is right now far more powerful than the currently most fashionable technology in neuro-science. fMRI might generate pretty pictures, but it's a pretty coarse technology. Right now, behavioral methods generally allow us to probe brain structure in a far more refined way than neuro methods do. That CN technology cannot usefully probe well motivated behaviorally based claims is what we should expect, and is what we find.

A second feature of the where/how confusion is that it leads one to abstract away from the most serious question in the neuro-sciences. Call it Gallistel’s question: how do brains embody mental constructs?  For example, how does wetware code for a variable or a value thereof? How do brains read and write to memory, bind a variable, distinguish between types and tokens?  Nobody knows. In fact, as Gallistel has observed, most CNers don’t even understand that this is the “how?” question that needs addressing (see here for discussion). The cognitive literature, including that in linguistics, has shown that we need these notions. Much of current neuroscience assumes that brain architectures that cannot do any of this (indeed that apparently deny, if Gallistel is right, that brains ever do this) are serviceable. This is partly abetted by the fact that current thinking fails to distinguish where from how. F&G is another example of this wider confusion.

I could go on, but I won’t. F&G makes a contribution: it identifies one possible place for where role information in some sense (however it is represented and whether it is specifically linguistic or not) might live. Given the current state of neuroscience, this is not nothing. However, the paper’s rhetoric (BS really) is way over the top. The introduction and conclusion motivate the investigation by pointing to really big issues (in particular recursion and Turing architecture). It purports to address these issues but in truth it can’t. The results are neutral wrt them. In the process, F&G sows lots of confusion and makes lots of simple errors thereby makind it hard to find the useful kernel in the morass. This leads me to one final observation.

I have heard it argued that without the overstatement and the BS the paper could never have been published. This is sometimes said in apparent justification of the BS and hype. If so neuroscience is in really bad shape. Moreover, I am skeptical that the hype is necessary, though I am sure that even if it is, it is odious to sling it nonetheless. Let me vent.

First, I doubt that a more measured presentation would have prevented publication. The result is not trivial and could have been presented as relevant to finding where linguistically/conceptually important concepts live in brain tissue.

Second, wanting to get published is no excuse for BS. This is not show business. BS goes against the fundamental values of the scientific enterprise and should not be tolerated, even if it might be useful career-wise.[4] The big problem is that such BS is fast becoming part of standard practice.  And like all S it greases a slippery slope: BS facilitates publication, we become more indulgent towards it and this will serve to further BSify research and publication. There is no excuse for this, or at least not one that should pass the smell test (and BS does smell). Whatever, F&G has told us about brains, it is mired in overstatement and self promotion. That’s the main reason many have reacted so strongly, and rightly so.[5] And that’s too bad because F&G does have something to tell us of interest.

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[1] Steve Pinker’s tweet highlights these F&G ambitions as well. It reads: “The most important paper in cognitive neuroscience in many years: How does the brain represent who did what to whom.” Note the “how.” I wonder if the tweet would have had the same impact if we replaced ‘how’ with ‘where.’ I can’t tell, though I think that the howish version sounds far more interesting. And this is exactly the problem.

[2] In the discussion section, F&G observes relations between its results and some previous findings in the literature. An interesting one relates to deficit studies that identify insult to the lmSTC results in “who did what to whom” problems for stimuli presented aurally and visually. This suggests the possibility, as F&G note, that this area is not linguistically dedicated. In other words, this area might be part of an “amodal language of thought.” If this is so, it might be interesting to see if analogous areas in non-linguistically endowed animals can similarly discriminate doers from done-tos.  This might even have some interesting linguistic significance concerning the theoretical utility of theta roles as discussed here. F&G leaves the linguistic status of lmSTC for future research. Hope it gets done.

[3] Also, how important is the proximity? Say that doers were found in one area and done-tos were found several sulci away. Would this be a problem for place codes? I don’t know. At any rate, the relation between being localizable and being place coded strikes me as looser than F&G suggests. In fact, I could imagine that even were rate codes employed to code some functional feature the sources generating the relevant rates might nonetheless localize somewhat.  I don’t know that this is so, but nothing F&G says leads me to think that this is impossible or even false. So a question to cognoscenti: is this inference from localizable to place code legit?

[4] IMO, BS is the most corrosive feature of much current research. As Frankfurt has argued, it might be even worse than lying for unlike the latter it has no regard for truth whatsoever. Stan Dehaene was the editor for the paper and he should really have removed this BS from the paper. He knows better.

[5] BTW, F&G does not get its BS right either. See the box marked “Significance” on the first page of the paper. It suggests that the problem of theta roles is the same as the problem of recursion. This is false. The roles that F&G addresses have nothing to do with Humboldt’s making infinite use of finite means. Here we have a finite set of possible sentences templatically specifiable wrt roles of two arguments. Recursion gives you sentences with many doers and many done tos, in fact unboundedly many. F&G has nothing to say about where the brain codes this.