The Modularity of the Motor System

Myrto Mylopoulos — Department of Philosophy and Institute of Cognitive Science, Carleton University

The extent to which the mind is mod­u­lar is a found­a­tion­al con­cern in cog­nit­ive sci­ence. Much of this debate has centered on the ques­tion of the degree to which input sys­tems, i.e., sens­ory sys­tems such as vis­ion, are mod­u­lar (see, e.g., Fodor 1983; Pylyshyn 1999; MacPherson 2012; Firestone & Scholl 201; Burnston 2017; Mandelbaum 2017). By con­trast, research­ers have paid far less atten­tion to the ques­tion of the extent to which our main out­put sys­tem, i.e., the motor sys­tem, qual­i­fies as such.

This is not to say that the lat­ter ques­tion has gone without acknow­ledge­ment. Indeed, in his clas­sic essay Modularity of Mind, Fodor (1983)—a pion­eer in think­ing about this topic—writes: “It would please me if the kinds of argu­ments that I shall give for the mod­u­lar­ity of input sys­tems proved to have applic­a­tion to motor sys­tems as well. But I don’t pro­pose to invest­ig­ate that pos­sib­il­ity here” (Fodor 1983, p.42).

I’d like to take some steps towards doing so in this post.

To start, we need to say a bit more about what mod­u­lar­ity amounts to. A cent­ral fea­ture of mod­u­lar systems—and the one on which I fill focus here—is their inform­a­tion­al encap­su­la­tion. Informational encap­su­la­tion con­cerns the rangeof inform­a­tion that is access­ible to a mod­ule in com­put­ing the func­tion that maps the inputs it receives to the out­puts it yields. A sys­tem is inform­a­tion­ally encap­su­lated to the degree that it lacks access to inform­a­tion stored out­side the sys­tem in the course of pro­cessing its inputs. (cf. Robbins 2009, Fodor 1983).

Importantly, inform­a­tion­al encap­su­la­tion is a rel­at­ive notion. A sys­tem may be inform­a­tion­ally encap­su­lated with respect to some inform­a­tion, but not with respect to oth­er inform­a­tion. When a sys­tem is inform­a­tion­ally encap­su­lated with respect to the states of what Fodor called “the cent­ral system”—those states famil­i­ar to us as pro­pos­i­tion­al atti­tude states like beliefs and intentions—this is referred to as cog­nit­iveimpen­et­rab­il­ityor, what I will refer to here as cog­nit­ive imper­meab­il­ity. In char­ac­ter­iz­ing the notion of cog­nit­ive per­meab­il­ity more pre­cisely, one must be care­ful not to pre­sup­pose that it is per­cep­tu­al sys­tems only that are at issue. For a neut­ral char­ac­ter­iz­a­tion, I prefer the fol­low­ing: A sys­tem is cog­nit­ively per­meable if and only if the func­tion it com­putes is sens­it­ive to the con­tent of a sub­ject S’s men­tal states, includ­ing S’s inten­tions, beliefs, and desires. In the fam­ous Müller-Lyer illu­sion, the visu­al sys­tem lacks access to the subject’s belief that the two lines are identic­al in length in com­put­ing the rel­at­ive size of the stim­u­lui, so it is cog­nit­ively imper­meable rel­at­ive to that belief.

On this char­ac­ter­iz­a­tion of cog­nit­ive per­meab­il­ity, the motor sys­tem is clearly cog­nit­ively per­meable in vir­tue of its com­pu­ta­tions, and cor­res­pond­ing out­puts, being sys­tem­at­ic­ally sens­it­ive to the con­tent of an agent’s inten­tions. The evid­ence for this is every inten­tion­al action you’ve ever per­formed. Perhaps the uncon­tro­ver­sial nature of this fact has pre­cluded fur­ther invest­ig­a­tion of cog­nit­ive per­meab­il­ity in the motor sys­tem. But there are at least two inter­est­ing ques­tions to explore here. First, since cog­nit­ive per­meab­il­ity, just like inform­a­tion­al encap­su­la­tion, comes in degrees, we should ask to what extent is the motor sys­tem cog­nit­ively per­meable. Are there inter­est­ing lim­it­a­tions that can be drawn out? (Spoiler: yes.) Second, inso­far as there are such lim­it­a­tions, we should ask the extent to which they are fixed. Can they be mod­u­lated in inter­est­ing ways by the agent? (Spoiler: yes.)

Experimental res­ults sug­gest that there are indeed inter­est­ing lim­it­a­tions to the cog­nit­ive per­meab­il­ity of the motor sys­tem. This is per­haps most clearly shown by appeal to exper­i­ment­al work employ­ing visuo­mo­tor rota­tion tasks (see also Shepherd 2017 for an import­ant dis­cus­sion of such work with which I am broadly sym­path­et­ic). In such tasks, the par­ti­cipant is instruc­ted to reach for a tar­get on a com­puter screen. They do not see their hand, but they receive visu­al feed­back from a curs­or that rep­res­ents the tra­ject­ory of their reach­ing move­ment. On some tri­als, the exper­i­menters intro­duce a bias to the visu­al feed­back from the curs­or by rotat­ing it rel­at­ive to the actu­al tra­ject­ory of their unseen move­ment dur­ing the reach­ing task. For example, a bias might be intro­duced such that the visu­al feed­back from the curs­or rep­res­ents the tra­ject­ory of their reach as being rotated 45°clockwise from the actu­al tra­ject­ory of their arm move­ment. This manip­u­la­tion allows exper­i­menters to determ­ine how the motor sys­tem will com­pensate for the con­flict between the visu­al feed­back that is pre­dicted on the basis of the motor com­mands it is execut­ing, and the visu­al feed­back the agent actu­ally receives from the curs­or. The main find­ing is that the motor sys­tem gradu­ally adapts to the bias in a way that res­ults in the recal­ib­ra­tion of the move­ments it out­puts such that they show “drift” in the dir­ec­tion oppos­itethat of the rota­tion, thus redu­cing the mis­match between the visu­al feed­back and the pre­dicted feed­back.

Figure 1. A: A typ­ic­al set-up for a visuo­mo­tor rota­tion task. B: Typical error feed­back when a coun­ter­clock­wise dir­ec­tion­al bias is intro­duced. (Source: Krakauer 2009)

In the paradigm just described, par­ti­cipants do not form an inten­tion to adopt a com­pens­at­ory strategy; the adapt­a­tion the motor sys­tem exhib­its is purely the res­ult of impli­cit learn­ing mech­an­isms that gov­ern its out­put. But in a vari­ant of this paradigm (Mazzoni & Krakauer 2006), par­ti­cipants are instruc­ted to adopt an expli­cit “cheat­ing” strategy—that is, to form intentions—to counter the angu­lar bias intro­duced by the exper­i­menters. This is achieved by pla­cing a neigh­bour­ing tar­get (Tn) at a 45°angle from the prop­er tar­get (Tp) in the dir­ec­tion oppos­itethe bias (e.g., if the bias is 45°counterclockwise from the Tp, the Tn is placed 45°clockwise from the Tp), such that if par­ti­cipants aim for the Tn, the bias will be com­pensated for, and the curs­or will hit the Tp, thus sat­is­fy­ing the primary task goal.

In this set-up, reach­ing errors related to the Tp are almost com­pletely elim­in­ated at first. The agent hits the Tp (accord­ing to the feed­back from the curs­or) as a res­ult of form­ing the inten­tion to aim for the stra­tegic­ally placed Tn. But as par­ti­cipants con­tin­ue to per­form the task on fur­ther tri­als, some­thing inter­est­ing hap­pens: their move­ments once again gradu­ally start to show drift, but this time towardsthe Tn and away from the Tp. What this res­ult is thought to reflect is yet anoth­er impli­cit pro­cess of adap­tion by the motor sys­tem, which aims to cor­rect for the dif­fer­ence between the aimed for loc­a­tion (Tn) and the visu­al feed­back (in the dir­ec­tion of the Tp).

Two fur­ther details are import­ant for our pur­poses: First, when par­ti­cipants are instruc­ted to stop using the strategy of aim­ing for the Tn (in order to hit the Tp) and return their aim to the Tp “[s]ubstantial and long-lasting” (Mazzoni & Krakauer 2006, p.3643) afteref­fects are observed, mean­ing the motor sys­tem per­sists in aim­ing to reduce the dif­fer­ence between the visu­al feed­back and the earli­er aimed for loc­a­tion. Second, in a sep­ar­ate study by Taylor & Ivry (2011) using a very sim­il­ar paradigm wherein par­ti­cipants had sig­ni­fic­antly more tri­als per block (320), par­ti­cipants did even­tu­ally cor­rect for the sec­ond­ary adap­tion by the motor sys­tem and reverse the dir­ec­tion of their move­ment, but only gradu­ally, and by means of adopt­ing expli­cit aim­ing strategies to coun­ter­act the drift.

On the basis of these res­ults, we can draw at least three inter­est­ing con­clu­sions about cog­nit­ive per­meab­il­ity and the motor sys­tem:  First, although it is clearly sens­it­ive to the con­tent of the prox­im­al inten­tions that it takes as input (in this case the inten­tion to aim for the Tn), it is not always, or only weakly so, to the distal inten­tions that those very prox­im­al inten­tions serve—in this case the inten­tion to hit the Tp. If this is cor­rect, it may be that the motor sys­tem lacks sens­it­iv­ity to the struc­ture of prac­tic­al reas­on­ing that often guides an agent’s present action in the back­ground. In this case, the motor sys­tem seems not to register that the agent intends to hit the Tp by way ofaim­ing and reach­ing for the Tn.

Second, giv­en that afteref­fects per­sist for some time even once the expli­cit aim­ing strategy (and there­fore the inten­tion to aim for the Tn) has been aban­doned, we may con­clude that the motor sys­tem is only sens­it­ive to the con­tent of prox­im­al inten­tions to a lim­ited degree in that it takes time for it to prop­erly update its per­form­ance rel­at­ive to the agent’s cur­rent prox­im­al inten­tion. The impli­cit adapt­a­tion, indexed to the earli­er inten­tion, can­not be over­rid­den imme­di­ately.

Third, this degree of sens­it­iv­ity is not fixed, but rather can vary over time as the res­ult of an agent’s inter­ven­tions, as determ­ined in Taylor & Ivry’s study, where the drift was even­tu­ally reversed after a suf­fi­ciently large num­ber of tri­als wherein the agent con­tinu­ously adjus­ted their aim­ing strategy.

To close, I’d like to out­line what I take to be a couple of import­ant upshots of the pre­ced­ing dis­cus­sion for neigh­bour­ing philo­soph­ic­al debates:

  1. Recent dis­cus­sions of skilled action have sought to determ­ine “how far down” action con­trol is intel­li­gent (see, e.g., Fridland 2014, 2017; Levy 2017; Shepherd 2017). And, on at least some views, this is a func­tion of the degree to which the motor sys­tem is sens­it­ive to the con­tent of an agent’s inten­tions. Here we see that this sens­it­iv­ity is some­times lim­ited, but can also improve over time. In my view, this reveals anoth­er import­ant dimen­sion of the motor system’s intel­li­gence that goes bey­ond mere sens­it­iv­ity, and that per­tains to its abil­ity to adapt to an agent’s present goals through learn­ing pro­cesses that exhib­it a reas­on­able degree of both sta­bil­ity and flex­ib­il­ity.
  2. Recently, action the­or­ists have turned their atten­tion to solv­ing the so-called “inter­face prob­lem”, that is, the prob­lem of how inten­tions and motor rep­res­ent­a­tions suc­cess­fully coordin­ate giv­en their (argu­ably) dif­fer­ent rep­res­ent­a­tion­al formats (see, e.g., Butterfill & Sinigaglia 2014; Burnston 2017; Fridland 2017; Mylopoulos & Pacherie 2017, 2018; Shepherd 2017; Ferretti & Caiani 2018). The pre­ced­ing dis­cus­sion may sug­gest a more lim­ited degree of inter­fa­cing than one might have thought—obtaining only between an agent’s most prox­im­al inten­tions and the motor sys­tem. It may also sug­gest that suc­cess­ful inter­fa­cing depends on both the learn­ing mechanism(s) of the motor sys­tem (for max­im­al smooth­ness and sta­bil­ity) as well as a con­tinu­ous inter­play between its out­puts and the agent’s own prac­tic­al reas­on­ing for how best to achieve their goals (for max­im­al flex­ib­il­ity).


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