Monday, September 29, 2014

Two years in

Faculty of Language was launched September 28, 2012. This means that it is now entering its third year and FoL is now in its terrible twos (TT). So no more cute quiet complaisant blog. No more walking on tip toes around important issues. No more shying away from polemics and vigorous debate. Now that we are in the TTs it's time to say what we really think and pursue the intellectual debate loudly and vigorously.

With this in mind, I would like to invite those who have been passive readers to join the fray.  FoL was started to focus on the big issues that initially motivated the Generative enterprise. These, IMO, had lost the prominence they once had, and linguistics did not benefit from this. GG was once at the center of the cognitive revolution. Sadly, this is no longer so. It is similarly absent from much discussion in the cog-neuroscience of language. In other words, much of what GG has discovered has remained a well kept secret and the influence GG should have had on work in these areas has dissipated. I believe that we need to change this, both for the good of linguistics as a discipline and because we have important (indeed vital) contributions to make to the brain and cognitive sciences.

We need to reconnect with the big issues and vociferously push the consequences of our discoveries hard in the larger cog-neuro community. And part of this involves getting clear what we think these consequences are and part involves making sure that what we've done is neither misunderstood nor ignored. And this means talking up in public venues where the issues are raised and making sure that others get it, even if this means being intellectually pushy. And this means being ready to critique what we take to be work that ignores or /and flies in the face of all we know.

So let's make year 3 a good boisterous one. No more pussy-footing around. Please send me things YOU find important and relevant. Please send suggestions for things to discuss. Let's make lots of noise!! We will all benefit.

Friday, September 26, 2014

Never trust a fact that is not backed up with a decent theory, and vice versa

Experimental work is really hard. Lila once said loud enough for me to hear that you need to be nuts to do an experiment if you really don't have to. The reason is that they are time consuming, hard to get right and even harder to evaluate.  We have recently being finding out how true this is, with paper after paper coming out arguing that much (most?) of what's in our journals is of dubious empirical standing.  And this is NOT because of fraud.  But because of how experiments get done, reported, evaluated and assessed with respect to professional advancement.  Add to this the wonders of statistical methodology (courses in stats seem designed as how to manuals for gaming the system) and what we end up with is, it appears, junk science with impressive looking symbols.  Paul Pietroski sent me this link to a book that reviews some of this in social psychology. But don't snigger, the problems cited go beyond this field, as the piece indicates.

I said that statistical methods are partly to blame for this. This should not be taken to imply that such methods when well used are not vital to empirical investigation. Of course they are!  The problem is first, that they are readily abusable, and second the industry has often left the impression that facts that are statistically scrutinized are indubitable. In other words, the statistical industry has left the impression that facts are solid while theories are just airy fairy confabulation, if not downright horse manure.  And you get this from the greats, i.e. how theory is fine but in the end the test of a true theory come from real world experiments yada yada yada.  It is often overlooked how misleading real world experiments can be and how it often takes a lot of theory to validate them.

I think that there is a take home message here. Science is hard. Thinking is hard. There is no magic formula for avoiding error or making progress.  What makes these things hard is that they involve judgment and this cannot be automated or rendered algorithmically safe.  Science/thinking/judgment is not long division! But many think that it really is. That speculation is fine so long as made to meet the factual tribunal on a regular basis. On this view, the facts are solid, the theories in need of justification.  Need I say that this view has a home in a rather particular philosophical view? Need I say that this view has a name (psst, it starts with 'Emp…). Need I say that this view has, ahem, problems?  Need I say that the methodological dicta this view favors are misleading at best?  We like to think that there are clear markers of the truth. That there is a method which if we follow it will get us to knowledge if only we persevere. There isn't. Here's a truism: We need both solid facts and good theories and which justify which is very much a local contextual matter. Facts need theoretical speculation as match as theoretical speculations need facts. It's one big intertwined mess, and we forget this, we are setting ourselves up for tsuris (a technical term my mother taught me).

Sunday, September 21, 2014

Mirror mirror in the brain

Lila Gleitman once conjectured that Empiricism, with its associationist commitments, is innate. How else to explain its zombie like capacity to repeatedly come back from intellectual death?  One possible explanation for associationism’s robustness is that it never returns in quite the same form. To paraphrase Mark Twain, Empiricist history never repeats itself, but it often rhymes.  I see this rhyming constantly. Technologically, neural nets were perfectly compatible with Rationalist sentiments (just a matter of initial weightings)[1], nonetheless virtually all of the work done in this framework stank of associationsism.  The same holds, IMO, for lots of recent Bayesian modeling and deep learning.  There is nothing inherent in these approaches that requires a coupling with Empiricist conceptions, but it seems that every computational innovation seems drawn to Empiricism the way flies are to…, well you know.  It seems that we can now add mirror neurons to the list.  Why do I say this? Because I’ve just finished reading a terrific new book by Greg Hickock that critically reviews the mirror neuron literature and its spiritual affinities with Behaviorism. But his book is not merely a debunking (though don’t fret it does do a lot of that) of some bad ideas which quickly became widely influential (another characteristic of Empiricist fads). It is also both a nice accessible report of research on the neuro frontier from a distinguished practitioner, and a nice case study in the philo of science. What follows are some reasons I liked the book and why you might find it worth dipping into.

In case you haven’t heard, mirror neurons are the philosopher’s stones of contemporary neuro-science.  Since their discovery in macaques in the late 1990s in Italy (I don't think macaques are native to Italy, just vacationing there), they have been used to neuronally explain almost everything of cognitive interest from language and its evolution to human empathy and autism.  What are these amazing brain mechanisms?  Well, it seems that they are neurons that fire both when the actor is acting and when the actor is watching someone else act. They are neurons that seem part of both the motor and the conceptual system. Or at least fire both when a monkey is reaching for something and when s/he is watching someone else reaching for something. This has led to a robust version of the motor theory of everything. In other words, understanding is actually re-doing. I understand what reaching cognitively means by simulating the reaching that I see. I understand what I hear by producing what I’ve heard. I understand what someone is feeling, by reproducing the feeling in myself. Talk about walking a mile in someone else’s shoes! That’s the basic idea, and if Greg is right (and I am sure he is) this idea has really caught on.

What Greg does in the book is reveal that this simple idea is, well, at best too simple and at worst, devoid of actual content. The problem is not with the data: there are neurons that do what they have been observed to do. However, the interpretation of what these firings mean has, Greg argues, been deeply over-interpreted; over-interpreted to the point that it is unlikely that much of a claim is being made in most cases. 

All the book is great, but I particularly recommend the sections on the role of anomalies in driving research and the terrific deflationary section on embodied cognition, a notion that really deserves some critical discussion, which Greg more than provides.  I’ve never understood why neuro types thought that embodied cognition could serve as a basis for the “semantics” of action words, but it has. I would recommend reading Greg on this and then, if you still want more, go back and read Fodor and Pylyshyn on compositionality.

 I also recommend you take a careful look at Greg’s discussion of imitation (chapter 8) and its role in “learning.” Here’s a short quote to give you the gist. There is

…a logical error in thinking about imitation as the foundation for more complex capacities like theory of mind, or that imitation itself had to evolve to unleash a great leap forward. Maybe we should think the other way around. Imitation is not the cause but the consequence of the evolution of human cognitive abilities…(200)

For imitation to be at all useful, you have to know what and when to imitate and you have to have the mental machinery behind imitative behavior to put it to good use…More specifically, to understand the role of imitation in language learning, we need to study how language works…Or to frame it a bit differently, rather than centering our theoretical efforts on imitation and then seeing what computational tasks imitation might be useful for, we might center our focus on particular computational tasks (language, understanding actions, grasping for objects) and then see what role imitation may play…(201).

Imitation is a current refuge for associationist theories of learning. And mirror neurons are the latest neuronal candidate for the grounding of associationism.  Greg’s critical discussion, IMO, effectively blows up this bankrupt train of theorizing. I’m not surprised, but I am grateful. Someone’s got to clean out the Augean stables and Greg is very effective with a shovel.

Here’s another quote making the all too common link to associationsism (228):

We’ve been down a similar road before. Behaviorists had very simple mechanisms (association and reinforcement) for explaining complex human behavior. But removing the mind as a mediator between the environment and behavior ultimately didn’t have the required explanatory oomph. Mirror neuron resonance theory isn’t quite behaviorism, but there are not many degrees of separation because “it stresses… the primacy of a “direct matching” between the observation and the execution of an action.” The notion of “direct matching” removes the sort of operations that might normally be thought to mediate the relation between observation and action systems…The consequence of such a move is loss of explanatory power. The mirror neuron direct matching claim results ina  failure to explain how mirror neurons know when to mirror in the first place. We then have to look to the “cognitive system” for an explanation, which lands us back where we started: with a complex mind behind the mirror neuron curtain of explanation of complex mental functions.

As Greg notes, his critique of mirror neurons is a modern revamping of Chomsky’s critique of Skinnerian behaviorism. Where it’s clear, it’s clearly false and where it seems true it borders on the truistic and vapid. 

There is lots more in the book. For neophytes (e.g. me) there is a good discussion of the dorsal and ventral systems of brain organization (the how vs what organization of brains that Greg and David Peoppel did so much to make part of the contemporary common neural wisdom in the domain of language), and the various kinds of techniques that modern neuro types use to probe brain structure.  In addition, there are lots of great examples that signal to the careful reader that Greg is clearly a pretty good surfer and that he loves dogs. 

So, if you are looking for a good popular neuro book or just a good debunking, Greg’s book is a great place to go. Would make a marvelous Rosh Hashanna present or a great Yom Kippur stocking stuffer.

[1] As Rumelhart and Maclelland noted in their fat initial volumes (here).

Thursday, September 18, 2014

Commenting on Posts

Many have written to tell me that they had problems leaving a comment on a post. I am not sure why but I suspect it's because you have not chosen an "identity." At the bottom of the comment sections there is a box that asks you to choose an identity for posting. I have a google account and post as 'Norbert.' There are other options if you click on the box. But you need one of these to do anything. When I go to my parents and use their computer, I often forget to check this and my comments disappear (I know, would be better were this to happen more frequently) never to be seen again. Here's a little primer on how to comment.

IMO, lots of that's valuable on this site has come from the very many useful comments readers have provided. They are often (almost always) more thoughtful than the posts that they are commenting on.  So please keep them coming.

Rethinking MOOCs

When MOOCs first came to the scene I expressed skepticism about their ultimate value for teaching and their capacity to really reduce costs without reducing educational quality (here, here). This, remember, was the selling point: more for less.  Flash forward to today and it seems that the problems with MOOCs is becoming more and more apparent. Sure, high tech has a role to play in education (sort of like overhead projectors and power point) but it is not the panacea bureaucrats and entrepreneurs like to hype (no doubt for only purely reasons, like moving large amounts of money into their nap accounts).  Well, it seems that MOOCs have hit their high water mark and skepticism about their general educational value is being reassessed. Not surprisingly, they can bring good results, but only if labor intensively used. Also, not surprisingly, it seems that getting people to use them means lowing what MOOCs are used to do. Here's a discussion. I don't buy it all, but it's a good sign of where the discussion is heading.

More on genes and language

Bill Idsardi sent this to me. Research on genes and language seems to be hotting up. Here is a study on rate of early word learning and a genetic difference that correlates with the variable rates.

Wednesday, September 17, 2014

Another Foxp2 article

Rich Hilliard sent me another report on the Foxp2 article that I brought to your attention yesterday. This one from the CBC, and being a very proud and smug Canadian I am bringing it to you attention as well. In addition, it has a very nice photo of a mouse with a re-engineered "humanized" Foxp2 gene (it really is adorable, btw).  It also gives a few more details of the experiment and the different kinds of information that humanized mice integrated better than "just" mice did. Here's the short version of the experiment as told by the CBC: The experimenters
"...trained mice to find chocolate in a maze. The animals had two options: use landmarks like lab equipment and furniture visible from the maze ("at the T-intersection, turn toward the chair") or by the feel of the floor ("smooth turn right, nubby turn left"). Mice with the human gene learned the route as well by seven days as regular mice did by 11….Surprsingly, however, when the scientists removed all the landmarks in the room, so mice could only learn by the feel-of-the-floor rule, the regular rodents did as well as the humanized ones. They also did just as well when the landmarks were present but the floor textiles were removed. It was only when mice culduse both learning techniques that those with the human brain gene excelled."
This is the basis for the speculation that Foxp2 helps with language, for Graybiel interprets the results to "suggest" that Foxp2 enhances the capacity to transition "from thinking about something consciously to doing it unconsciously." And this relates to language how?  Well when kids learn to speak they transition from consciously mimicking words they hear to speaking automatically. Really? This is the linking hypothesis? Am I alone in thinking that this gives speculation a bad name?  It doesn't even rise to the level of a just-so story.

Jerry Fodor is reputed to have said that neuroscience has taught us virtually nothing about the mind. I am not sure that I entirely agree, but I am pretty sure that this work tells us next to nothing about language. Look, I love mice. They sing, they are cute, they run mazes better than I can, they navigate well in the dark. I am even sort of interested that one can put a human Foxp2 gene into a mouse. But the results of this experiment are very modest and have nothing whatsoever to tell us about language. I assume the language link is just there to hype the work. Show business.