Functional Localization—Complicated and Context-Sensitive, but Still Possible

Dan Burnston—Assistant Professor, Philosophy Department, Tulane University, Member Faculty in the Tulane Brain Institute

The ques­tion of wheth­er func­tions are loc­al­iz­able to dis­tinct parts of the brain, aside from its obvi­ous import­ance to neur­os­cience, bears on a wide range of philo­soph­ic­al issues—reductionism and mech­an­ist­ic explan­a­tion in philo­sophy of sci­ence; cog­nit­ive onto­logy and men­tal rep­res­ent­a­tion in philo­sophy of mind, among many oth­ers. But philo­soph­ic­al interest in the ques­tion has only recently begun to pick up (Bergeron, 2007; Klein, 2012; McCaffrey, 2015; Rathkopf, 2013).

I am a “con­tex­tu­al­ist” about loc­al­iz­a­tion: I think that func­tions are loc­al­iz­able to dis­tinct parts of the brain, and that dif­fer­ent parts of the brain can be dif­fer­en­ti­ated from each oth­er on the basis of their func­tions (Burnston, 2016a, 2016b). However, I also think that what a par­tic­u­lar part of the brain does depends on beha­vi­or­al and envir­on­ment­al con­text. That is, a giv­en part of the brain might per­form dif­fer­ent func­tions depend­ing on what else is hap­pen­ing in the organism’s intern­al or extern­al environment.

Embracing con­tex­tu­al­ism, as it turns out, involves ques­tion­ing some deeply held assump­tions with­in neur­os­cience, and con­nects the ques­tion of loc­al­iz­a­tion with oth­er debates in philo­sophy. In neur­os­cience, loc­al­iz­a­tion is gen­er­ally con­strued in what I call abso­lut­ist terms. Absolutism is a form of atomism—it sug­gests that loc­al­iz­a­tion can be suc­cess­ful only if 1–1 map­pings between brain areas and func­tions can be found. Since genu­ine mul­ti­func­tion­al­ity is anti­thet­ic­al to atom­ist assump­tions it has his­tor­ic­ally not been a closely ana­lyzed concept in sys­tems or cog­nit­ive neuroscience.

In philo­sophy, con­tex­tu­al­ism takes us into ques­tions about what con­sti­tutes good explan­a­tion—in this case, func­tion­al explan­a­tion. Debates about con­tex­tu­al­ism in oth­er areas of philo­sophy, such as semantics and epi­stem­o­logy (Preyer & Peter, 2005), usu­ally shape up as fol­lows. Contextualists are impressed by data sug­gest­ing con­tex­tu­al vari­ation in the phe­nomen­on of interest (usu­ally the truth val­ues of state­ments or of know­ledge attri­bu­tions). In response, anti-contextualists worry that there are neg­at­ive epi­stem­ic con­sequences to embra­cing this vari­ation. The res­ult­ing explan­a­tions will not, on their view, be suf­fi­ciently power­ful or sys­tem­at­ic (Cappelen & Lepore, 2005). We end up with explan­a­tions that do not gen­er­al­ize bey­ond indi­vidu­al cases. Hence, accord­ing to anti-contextualists, we should be motiv­ated to come up with the­or­ies that deny or explain away the data that seem­ingly sup­port con­tex­tu­al variation.

In order to argue for con­tex­tu­al­ism in the neur­al case, then, one must first estab­lish the data that sug­gests con­tex­tu­al vari­ation, then artic­u­late a vari­ety of con­tex­tu­al­ism that (i) suc­ceeds at dis­tin­guish­ing brain areas in terms of their dis­tinct func­tions, and (ii) describes genu­ine generalizations.

Usually, in sys­tems neur­os­cience, the goal is to cor­rel­ate physiolo­gic­al responses in par­tic­u­lar brain areas with par­tic­u­lar types of inform­a­tion in the world, sup­port­ing the claim that the responses rep­res­ent that inform­a­tion. I have pur­sued a detailed case study of per­cep­tu­al area MT (also known as “V5” or the “middle tem­por­al” area). The text­book descrip­tion of MT is that it rep­res­ents motion—it has spe­cif­ic responses to spe­cif­ic pat­terns of motion, and vari­ations amongst its cel­lu­lar responses rep­res­ent dif­fer­ent dir­ec­tions and velo­cit­ies. Hence, MT has the uni­vocal func­tion of rep­res­ent­ing motion: an abso­lut­ist description.

However, MT research in the last 20 years has uncovered data which strongly sug­gests that MT is not just a motion detect­or. I will only list some of the rel­ev­ant data here, which I dis­cuss exhaust­ively in oth­er places. Let’s con­sider a per­cep­tu­al “con­text” as a com­bin­a­tion of per­cep­tu­al features—including shape/orientation, depth, col­or, luminance/brightness, and motion. On the tra­di­tion­al hier­archy, each of these fea­tures has its own area ded­ic­ated to rep­res­ent­ing it. Contextualism, altern­at­ively, starts from the assump­tion that dif­fer­ent com­bin­a­tions of these fea­tures might res­ult in a giv­en area rep­res­ent­ing dif­fer­ent inform­a­tion.

  • Despite the tra­di­tion­al view that MT is “col­or blind” (Livingstone & Hubel, 1988), MT in fact responds to the iden­tity of col­ors when col­or is use­ful in dis­am­big­u­at­ing a motion stim­u­lus. Now in this case, MT still argu­ably rep­res­ents motion, but it does use col­or as a con­tex­tu­al cue for doing so.
  • Over 93% of MT cells rep­res­ent coarse depth (the rough dis­tance of an object away from the per­ceiv­er. Their tun­ing for depth is inde­pend­ent of their tun­ing for motion, and many cells rep­res­ent depth even in sta­tion­ary These depth sig­nals are pre­dict­ive of psy­cho­phys­ic­al results.
  • A major­ity of MT cells also have spe­cif­ic response prop­er­ties for fine depth (depth sig­nals res­ult­ing from the 3‑d shape and ori­ent­a­tion of objects) fea­tures of tilt and slant, and these can be cued by a vari­ety of dis­tinct fea­tures, includ­ing bin­ocu­lar dis­par­ity and rel­at­ive velocity.

How do these res­ults sup­port con­tex­tu­al­ism? Consider a par­tic­u­lar physiolo­gic­al response to a stim­u­lus in MT. If the data is cor­rect, then this sig­nal might rep­res­ent motion, or it might rep­res­ent depth—and indeed, either coarse or fine depth—depending on the con­text. Or, it might rep­res­ent a com­bin­a­tion of those influ­ences.[1]

The con­tex­tu­al­ism I advoc­ate focuses on the type of descrip­tions we should invoke in the­or­iz­ing about the func­tions of brain areas. First, our descrip­tions should be con­junct­ive: the func­tion of an area should be described as a con­junc­tion of the dif­fer­ent rep­res­ent­a­tion­al func­tions it serves and the con­texts in which it serves those func­tions. So, MT rep­res­ents motion in a par­tic­u­lar range of con­texts, but also rep­res­ents oth­er types of inform­a­tion in dif­fer­ent contexts—including abso­lute depth in both sta­tion­ary and mov­ing stim­uli, and fine depth in con­texts involving tilt and slant, as defined by either rel­at­ive dis­par­ity or rel­at­ive velocity.

When I say that a con­junc­tion is “open,” what I mean is that we shouldn’t take the func­tion­al descrip­tion as com­plete. We should see it as open to amend­ment as we study new con­texts. This open­ness is vital—it is an induc­tion on the fact that the func­tion­al descrip­tion of MT has changed as new con­texts have been explored—but also leads us pre­cisely into what both­ers anti-contextualists (Rathkopf, 2013). The worry is that open-descriptions do not have the the­or­et­ic­al strength that sup­ports good explan­a­tions. I argue that this worry is mistaken.

First, note that con­tex­tu­al­ist descrip­tions can still func­tion­ally decom­pose brain areas. The key to this is the index­ing of func­tions to con­texts. Compare MT to V4. While V4 also rep­res­ents “motion” con­strued broadly (in “kin­et­ic” or mov­ing edges), col­or, and fine depth, the con­texts in which V4 does so dif­fer from MT. For instance, V4 rep­res­ents col­or con­stan­cies which are not present in MT responses. V4’s spe­cif­ic com­bin­a­tion of sens­it­iv­it­ies to fine depth and curvature allows it to rep­res­ent pro­tuber­ances—curves in objects that extend towards the perceiver—which MT can­not rep­res­ent. So, the types of inform­a­tion that these areas rep­res­ent, along with the con­texts in which they rep­res­ent them, tease apart their functions.

Indexing to con­texts also points the way to solv­ing the prob­lem of gen­er­al­iz­a­tion, so long as we appro­pri­ately mod­u­late our expect­a­tions. For instance, on con­tex­tu­al­ism it is still a power­ful gen­er­al­iz­a­tion that MT rep­res­ents motion. This is sub­stan­ti­ated by the wide range of con­texts in which it rep­res­ents motion—including mov­ing dots, mov­ing bars, and color-segmented pat­terns. It’s just that rep­res­ent­ing motion is not a uni­ver­sal gen­er­al­iz­a­tion about its func­tion. It is a gen­er­al­iz­a­tion with more lim­ited scope. Similarly, MT rep­res­ents fine depth in some con­texts (tilt and slant, defined by dis­par­ity or velo­city), but not in all of them (pro­tuber­ances). Of course, if the func­tion of MT is genu­inely con­text sens­it­ive, then uni­ver­sal gen­er­al­iz­a­tions about its func­tion will not be pos­sible. Hence, insist­ing on uni­ver­sal gen­er­al­iz­a­tions is not an open strategy for an absolutist—at least not without ques­tion begging.

The real crux of the debate, I believe, is about the notion of pro­ject­ab­il­ity. We want our the­or­ies not just to describe what has occurred, but to inform future hypo­thes­iz­ing about nov­el situ­ations. Absolutists hope for a power­ful form of law-like pro­ject­ab­il­ity, on which a suc­cess­ful func­tion­al descrip­tion tells us for cer­tain what that area will do in new con­texts. The “open” struc­ture of con­tex­tu­al­ism pre­cludes this, but this doesn’t both­er the con­tex­tu­al­ist. This situ­ation might seem remin­is­cent of sim­il­ar stale­mates regard­ing con­tex­tu­al­ism in oth­er areas of philosophy.

There are two ways I have sought to break the stale­mate. First is to define a notion of pro­ject­ab­il­ity that informs sci­entif­ic prac­tice, but is com­pat­ible with con­tex­tu­al­ism. Second is to show that even very gen­er­al abso­lut­ist descrip­tions fail to deliv­er on the sup­posed explan­at­ory advant­ages of abso­lut­ism. The key to a con­tex­tu­al­ist notion of pro­ject­ab­il­ity, in my view, is to look for a form of pro­ject­ab­il­ity that struc­tures invest­ig­a­tion, rather than giv­ing law­ful pre­dic­tions. The basic idea is this: giv­en a new con­text, the null hypo­thes­is for an area’s func­tion in that con­text should be that it per­forms its pre­vi­ously known func­tion (or one of its known func­tions). I call this role a min­im­al hypo­thes­is, and the idea is that cur­rently known func­tion­al prop­er­ties struc­ture hypo­thes­iz­ing and invest­ig­a­tion in nov­el con­texts, by provid­ing three options: (i) either the area does not func­tion at all in the nov­el con­text (per­haps MT does not make any func­tion­al con­tri­bu­tion to, say, pro­cessing emo­tion­al valence); (ii) it func­tions in one of its already known ways, in which case anoth­er con­text gets indexed to, and gen­er­al­izes, an already known con­junct, or (iii) it per­forms a new func­tion in that con­text, for­cing a new con­junct to be added to the over­all descrip­tion of the area (indexed to the nov­el con­text, of course). While I won’t go into details here, I argue in (Burnston, 2016a) that this kind of reas­on­ing has shaped the pro­gress of under­stand­ing MT function.

One option open to a defend­er of abso­lut­ism is to attempt to explain away the data sug­gest­ing con­tex­tu­al vari­ation by chan­ging the type of func­tion­al descrip­tion that is sup­posed to gen­er­al­ize over all con­texts (Anderson, 2010; Bergeron, 2007; Rathkopf, 2013). For instance, rather than say­ing that a part of the brain rep­res­ents a spe­cif­ic type of inform­a­tion, maybe we should say that it per­forms the same type of com­pu­ta­tion, whatever inform­a­tion it is pro­cessing. I have called this kind of approach “com­pu­ta­tion­al abso­lut­ism” (Burnston, 2016b).

While com­pu­ta­tion­al neur­os­cience is an import­ant the­or­et­ic­al approach, it can’t save abso­lut­ism. My argu­ment against the view starts from an empir­ic­al premise—in mod­el­ing MT, there is not one com­pu­ta­tion­al descrip­tion that describes everything MT does. Instead, there are a range of the­or­et­ic­al mod­els that each provide good descrip­tions of aspects of MT func­tion. Given this lack of uni­ver­sal gen­er­al­iz­a­tion, the com­pu­ta­tion­al abso­lut­ist has some options. They might move towards more gen­er­al levels of com­pu­ta­tion­al descrip­tion, hop­ing to sub­sume more spe­cif­ic mod­els. The prob­lem with this is that the most gen­er­al com­pu­ta­tion­al descrip­tions in neur­os­cience are what are called canon­ic­al com­pu­ta­tions (Chirimuuta, 2014)—descriptions that can apply to vir­tu­ally all brain areas. But if this is the case, then these descrip­tions won’t suc­cess­fully dif­fer­en­ti­ate brain areas based on their func­tion. Hence, they don’t con­trib­ute to func­tion­al localization.

On the oth­er hand, sug­gest­ing that it is some­thing about the way these com­pu­ta­tions are applied in par­tic­u­lar con­texts runs right into the prob­lem of con­tex­tu­al vari­ation. Producing a mod­el that pre­dicts what, say, MT will do in cases of pat­tern motion or reverse-phi phe­nom­ena simply does not pre­dict what func­tion­al responses MT will have to depth—not, at least, without invest­ig­at­ing and build­ing in know­ledge about its physiolo­gic­al responses to those stim­uli. So, even if gen­er­al mod­els are help­ful in gen­er­at­ing pre­dic­tions in par­tic­u­lar instances, they don’t explain what goes on in them. If this descrip­tion is right, then the sup­posed explan­at­ory gain of CA is an empty prom­ise, and con­tex­tu­al ana­lys­is of func­tion is neces­sary. My view of the role of highly gen­er­al mod­els mir­rors those offered by Cartwright (1999) and Morrison (2007) in the phys­ic­al sciences.

Some caveats are in order here. I’ve only talked about one brain area, and as McCaffrey (2015) points out, dif­fer­ent areas might be amen­able to dif­fer­ent kinds of func­tion­al ana­lys­is. Perceptual areas are import­ant, how­ever, because they are paradigm suc­cess cases for func­tion­al loc­al­iz­a­tion. If con­tex­tu­al­ism works here, it can work else­where, as well as for oth­er units of ana­lys­is, such as cell pop­u­la­tions and net­works (Rentzeperis, Nikolaev, Kiper, & van Leeuwen, 2014). I share McCaffrey’s plur­al­ist lean­ings, but I think that a place for con­tex­tu­al­ist func­tion­al ana­lys­is must be made if func­tion­al decom­pos­i­tion is to suc­ceed. The con­tex­tu­al­ist approach is also com­pat­ible with oth­er frame­works, such as Klein’s (2017) focus on “difference-making” in under­stand­ing the func­tion of brain areas.

I’ll end with a teas­er about my cur­rent pro­ject on these top­ics (Burnston, in prep). Note that, if the func­tion of brain areas can genu­inely shift with con­text, this is not just a the­or­et­ic­al prob­lem, but a prob­lem for the brain. Other parts of the brain must inter­act with MT dif­fer­ently depend­ing on wheth­er it is cur­rently rep­res­ent­ing motion, coarse depth, fine depth, or some com­bin­a­tion. If this is the case, we can expect there to be mech­an­isms in the brain that medi­ate these shift­ing func­tions. Unsurprisingly, I am not the first to note this prob­lem. Neuroscientists have begun to employ con­cepts from com­mu­nic­a­tion and inform­a­tion tech­no­logy to show how physiolo­gic­al activ­ity from the same brain area might be inter­preted dif­fer­ently in dif­fer­ent con­texts, for instance by encod­ing dis­tinct inform­a­tion in dis­tinct dynam­ic prop­er­ties of the sig­nal (Akam & Kullmann, 2014). Contextualism informs the need for this kind of approach. I am cur­rently work­ing on explic­at­ing these frame­works and show­ing how they allow for func­tion­al decom­pos­i­tion even in dynam­ic and context-sensitive neur­al networks.


[1] The high pro­por­tion and reg­u­lar organ­iz­a­tion of depth-representing cells in MT res­ists the tempta­tion to try to save inform­a­tion­al spe­cificity by sub­divid­ing MT into smal­ler units, as is nor­mally done for V1. V1 is stand­ardly sep­ar­ated into dis­tinct pop­u­la­tions of ori­ent­a­tion, wavelength, and displacement-selective cells, but this kind of move is not avail­able for MT.



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