Localization and Intrinsic Function

Charles Rathkopf

Published in Philosophy of Science

January, 2013

Abstract

This paper describes one style of functional analysis commonly used

in the neurosciences called task-bound functional analysis. The concept

of function invoked by this style of analysis is distinctive in virtue of the

dependence relations it bears to transient environmental properties. It is

argued that task-bound functional analysis cannot explain the presence

of structural properties in nervous systems. An alternative concept of

neural function is introduced that draws on the theoretical neuroscience

literature, and an argument is given to show that this alternative con-

cept of may help to overcome the explanatory limitations of task-bound

functional analysis.

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1 Introduction

Everyone agrees with Petersen and Fiez’s 1993 oft-cited claim that “there is no

tennis forehand area in the brain.” However, there is presently little agreement

about the grounds for this widely held belief. What precisely makes “tennis

forehand” an inappropriate or unlikely functional designation? Each of the

following options provides the beginning of an answer: (i) it is too specific,

(ii) it is too arbitrary, and (iii) it is too unrelated to the selection pressures

that shaped the development of neural function. There is, no doubt, something

right in each of these suggestions. But it is difficult to turn such truisms into

theories that are substantial enough to impact the ongoing scientific debates

about localization. In this paper, an alternative answer is proposed which, if

successful, has direct consequences not only for the philosophical analysis of

function, but also for neuroscientific practice. The answer proposed is roughly

this: there is no tennis forehand area in the brain because the execution of a

forehand is a behavioral task, and no brain area has a behavioral task as its

principal function.

This paper is comprised of three main sections. In Section 2, one style of

functional analysis—which I call task-bound functional analysis—is described.

Task-bound functional analysis is routinely used in the neurosciences, and some

examples are provided to illustrate its use. In Section 3, an argument is pre-

sented that shows why task-bound functions are incapable of explaining the

presence of structural properties in nervous systems. In Section 4, an alterna-

tive concept of neural function is introduced. It is argued that the explana-

tory strategy associated with this alternative concept is, by virtue of satisfying

two explicit desiderata, not subject to the limitations of task-bound functional

analysis. By contrasting the concept of task-bound function with the newer,

alternative concept, some light is shed on the explanatory depth of certain con-

temporary neuro-functional hypotheses.

2 Task-Bound Functional Analysis

2.1 Context Sensitivity

Even the most celebrated cases of localized neural function remain controver-

sial. Consider the paradigmatic localization of speech production in humans

to Broca’s area (Broadmann areas 44 and 45). Although speech production

2



certainly depends on characteristic activation patterns in Broca’s area, recent

research suggests at least four distinct classes of proposed functions that it also,

ostensibly, realizes. These proposed functions vary along multiple theoretical

dimensions, and there is substantial debate regarding both the extent to which

they are compatible with one another, and whether or not any of them are

correct (Grodzinsky and Santi, 2008). Why should there be such controversy

about the legitimacy of even the best cases of localized neural function? The

answer, I submit, lies in the observation that many neuro-functional hypotheses

make essential reference to transient environmental contexts.1

One might think that making reference to transient environmental contexts

is precisely what neuro-functional hypotheses ought to do. Indeed, in Section

2.3, I argue that such neuro-functional hypotheses play a crucial role in neu-

roscientific investigation. One scientific motivation for appealing to functions

that essentially depend on reference to transient environmental properties is

that such functions are relatively easy to relate to a lower level of description.

Often, researchers identify a neural mechanism that underlies some functional

capacity; a strategy that requires one to descend at least one level (Piccinini

and Craver, 2011). The prospects for success in this endeavor will improve if

the range of environmental contexts within which one’s mechanistic hypothesis

must be tested is relatively narrow. As the range of contexts expands, the num-

ber of processes that might impinge on a hypothesized mechanism will increase,

making the task of theory confirmation (or model validation) more difficult.

In order to make neuro-functional investigation tractable, therefore, neuroscien-

tists often think in terms of context-sensitive functional hypotheses, in which the

number of environmental variables relevant to understanding a neural mecha-

nism is minimized. Jacqueline Sullivan has made a similar claim and supported

it with detailed case studies. Her formulation reads: “. . . given Craver’s own

commitment to the idea that mechanisms have specific components and tempo-

ral and spatial organizations, and given that such features of mechanisms are

sensitive to what set that mechanism into motion, i.e., the events that preceded

it, then it is entirely possible, indeed quite likely, that different experimental

protocols will yield different mechanisms for potentially different phenomena”

(Sullivan, 2009, p. 527).2

1My usage is intended to reflect the meaning of the term “context” as it is used in asso-
ciative learning theory, and especially in classical conditioning.

2Sullivan exploits this feature of mechanistically oriented neuroscience in order to mount an
argument against Craver’s 2007 argument for the unity of the neurosciences. While I cannot
take up that debate here, it should be mentioned that the solution I propose to the problem

3



Although context-sensitive neuro-functional hypotheses are legitimate and

important aspects of neuroscientific investigation, I intend to show that, un-

der some conditions, context-sensitivity systematically prevents such hypothe-

ses from explaining neural structure. The argument for that claim is presented

in the third section. In the remainder of this section I introduce and define the

concept of task-bound functional analysis, a scientific strategy built around the

concept of ‘context-sensitive functional hypotheses.’ Then, I distinguish two

logically distinct forms of explanation in which task-bound functional analysis

plays a central role. Finally, I highlight one of these strategies, and provide an

example of how it works.

2.2 Defining TBFA

Task-bound functional hypotheses are a special case of context-sensitive hy-

potheses. In particular, they are hypotheses about the functional role of a brain

area in which the kind of function posited has the property of being task-bound,

which is defined as follows.

A function F is task-bound just in case (i) its description makes essential

reference to a behavioral task invoked by an experimental paradigm in which

environmental properties P1 . . . Pn are manipulated, and (ii) it is ascribed to

brain areas that are anatomically individuated.

Each component of this definition deserves clarification. In the first com-

ponent, variables P1 . . . Pn serve as partial identity criteria for an experimental

paradigm. (I say partial because other factors may also be relevant to con-

cerns about individuation, such as the content of the hypothesis under scrutiny.)

The values of variables P1 . . . Pn cannot be included in the definition of task-

boundedness without sacrificing generality. This is because the criteria that de-

termine the paradigm to which a particular experiment belongs are local to the

empirical domain in question. Sullivan defines the term experimental paradigm

as: “a standard method or procedure for producing an effect of a certain type”

(Sullivan, 2009, p. 514). The exact set of environmental properties to be ma-

nipulated will depend on the nature of that intended effect. Typically these

properties will include the kind of stimuli used and their temporal presentation,

the shape and spatial layout of objects in close proximity to the organism, the

of task-bound functional analysis in Section 4 might be helpful in defending a version of the
unity thesis. Thanks to an anonymous reviewer bringing this issue to my attention.

4



ambient lighting and acoustic conditions, and many other factors.3 The crucial

thing to note about the first component of the definition is that, among the

identity criteria for a given experimental paradigm will be a set of environmen-

tal properties, the manipulation of which are required by the behavioral task

invoked by that paradigm. The second component of the definition rules out

analytic functional designations. Consider a claim of the following form: area x,

new evidence suggests, does not realize function F1; in fact, it realizes function

F2. If realizing function F1 is both necessary and sufficient for being counted

as a token of type ‘area x,’ then this kind of claim is a matter of definition

rather than empirical discovery. I am only interested in the empirical truth of

task-bound functional hypotheses, so analytic statements must be set aside.

Given the definition of task-bound functional hypotheses, task-bound func-

tional analysis, or TBFA, may be defined as a scientific strategy that attempts

to taxonomize and explain the workings of the central nervous system (in any

species) via the application of task-bound functional hypotheses.

2.3 The Direction of Explanation

I claim that TBFA is explanatorily limited. But the limitation I intend to

identify only manifests itself when TBFA is deployed in the service of potential

explanations with a particular logical form. In neuroscience, as in other fields,

functional claims may be invoked either as explanans or explanandum. When

invoked as explanandum, (probably the more widely discussed strategy in phi-

losophy of biology) the existence of some function is already known, and then a

structure is discovered that realizes the function, explaining how one particular

system-type manages to achieve it. An example of this strategy in neuroscience

is the explanation of photoreception in terms of the isomerisation of retinal and

its subsequent liberation from opsin proteins in the rod and cone cells of the

retina. It had long been known that the retina functions to detect and transduce

light, but the structural realization of this function remained a mystery until the

discovery that only one of two possible conformations of retinal binds to opsin

3In the same paper, Sullivan provides a thorough analysis of the components of experi-
mental paradigms in the neuroscience of learning and memory. On her view, an experimental
paradigm includes production procedures, which specify the experimental setup, measurement
procedures, which specify relevant behavioral responses, and detection procedures, which indi-
cate how empirical consequences can be attributed to dependent variables cast at the cognitive
(as opposed to neurobiological) level. The environmental properties referred to in the defini-
tion of task-boundedness may fall under any of these three headings.

5



proteins (Wolf, 2001).4 In this case, structural properties of retinal explain how

the initial stage of transduction is realized. Let us refer to explanations of this

kind, in which the discovery of structural properties explains how a system-

type achieves some function, as functionally-oriented explanations. TBFA often

makes possible the discovery of functionally-oriented explanations, and in this

capacity, plays a crucial role in neuroscientific practice.5 Much of the literature

on mechanistic explanation illustrates exactly how this role has been, and ought

to be played. (See, for example Craver (2007)).

In other kinds of explanation, the logical positions occupied by functional

claims and structural claims are reversed, such that the discovery of a func-

tion explains why structural properties are present. For example, it was long

known that some neural projections are covered with a layer of fatty tissue,

known as myelin. But it was not until 1949 that Huxley and Stämpfli gath-

ered the electrophysiological evidence required to demonstrate that sheaths of

myelin, interrupted by the nodes of Ranvier, serve to create local circuits that

propagate short electrotonic potentials down the length of the axon, making

the transmission of current faster than it would be if the only mechanism of

propagation were the chain reaction of action potentials, the speed of which

is capped by the refractory period of voltage-gated sodium channels (Huxley

and Stämpeli, 1949). This discovery explained not only why myelin sheaths are

interrupted by the nodes of Ranvier (to create miniature circuits at internode

intervals), but also why those sheaths have the material properties they do (in

order to block current from escaping.) In this example, functional properties

explain the presence of structural properties.

Non-scientific explanations of human artifacts often proceed in a similar

logical fashion. Pinker (2009) relates a vignette in which a customer, browsing

at an antique shop, stumbles upon a perplexing device composed of a stand,

a metal arm bolted perpendicularly to the stand with a horizontally-oriented

4The history of this discovery is complex, but George Wald received the Nobel Prize for
identifying the key molecular pathway that makes use of retinal in 1964.

5My use of the word ‘structure’ needs clarification. In logic and mathematics, the term
often refers to an abstract set of relational properties. In this sense, propositions may have
a logical structure that is independent of the meaning of non-logical terms, and a graph
may have a topological structure that is independent of the identity of the individual nodes
and the underlying geometrical space. In neuroscience, the concept of structure is to be
contrasted with the concept of function. In this sense of the term, structural properties
have to do with the shape and spatial organization of particular objects. At the scale of
observable properties, usage of the term ‘structural’ in neuroscience is often synonymous with
‘anatomical.’ At the scale of unobservables, there exist non-anatomical structural properties,
such as the conformation of a macromolecule.

6



ring on its end, a sharp x-shaped blade capable of pivoting vertically through

the ring, and a lever to control the motion of the blade. The customer cannot

understand why anyone would assemble such a bizarre collection of parts, until

the shopkeeper explains that the device is an old-fashioned olive pitter. The

ring holds an olive, and the lever drives the x-shaped blade through it vertically,

pushing the pit through the flesh on the bottom of the olive and into a container

below. Given that functional insight, the structural properties of the device

suddenly make sense. Moreover, the sense of understanding achieved is not

merely subjective. A person who understands the function of the olive pitter

would almost immediately be in position to know what sorts of interventions

would affect the performance of the device, and what sorts would not. Since the

facts about whether an olive has been pitted are objective, information about

the functional effects of potential interventions on the device constitutes a form

of objective knowledge (as opposed to mere belief, or the subjective feeling of

understanding that is sometimes elicited by the acquisition of knowledge). Let

us refer to explanations of this form, in which the discovery of function explains

the presence of structural properties, as structurally-oriented explanations.

In this paper, I restrict myself to the claim that TBFA faces limitations

when used to generate structurally-oriented explanations; I prefer to set aside

discussion of the potential limitations of TBFA when deployed in the service

of functionally-oriented explanations.6 In order to forestall confusion, I should

emphasize that both ‘functionally-oriented’ and ‘structurally-oriented’ explana-

tions are meant to denote forms of explanation that, one way or the other,

include functional claims.

2.4 An Example of TBFA

With the above qualification in mind, it will be helpful to consider a well-

known example of TBFA that has generated an impressive amount of scientific

6There is a growing philosophical and scientific literature on the forms of inference that are
warranted by brain imaging data. One of the issues in this literature concerns the allegedly
poor justification for what is known as “reverse inference.” Reverse inferences are those that
begin with the observation that brain area X is differentially activated in some behavioral
task B. It is then noted that previously established results support the thesis that brain area
X is involved in a particular cognitive process Y . From these two premises, it is concluded
that behavioral task B engages cognitive process Y . The problems with this form of inference
are intimately related to the limitations of TBFA when deployed in functionally-oriented
explanations. However, philosophical analysis of this issue requires considerable discussion
of brain-imaging technology, and would lead us too far afield. See Poldrack (2006) for an
early criticism of reverse inference, and Hanson and Bunzl (2010) for an overview of the
contemporary debate.

7



controversy.

The hippocampus is an anatomically defined structure in the medial tem-

poral lobe of mammals and birds. It is widely agreed that the hippocampus

serves a memory-related function, but consensus breaks down where more spe-

cific hypotheses are requested. As early as 1984, Nestor Schmajuk, a specialist

in theoretical hippocampus research, was able to provide a list of 20 distinct

theories of hippocampal function, and more have been added since (Morris,

2007; Schmajuk, 1984). Proposals include recording of spatial map coordinates,

transitive inference, behavioral inhibition, and consolidating autobiographical

memory (Per Andersen, 2007).

Perhaps what is most striking about the list of proposed functions is that it

is far from obvious which properties, if any, all items on the list have in common.

One reason for the diversity of proposed functions is, no doubt, the diversity

of species upon which experiments are conducted: experimental paradigms de-

signed for rats hardly resemble those designed for humans. Nevertheless, on

the basis of widespread anatomical and physiological conservation, it is believed

that the function of the hippocampus remains constant across species. Indeed,

the structural similarities have prompted researchers to claim that a hypothet-

ical surgery, replacing a human hippocampus with that of a macaque, could

be entirely successful (Morris, 2007). This impressive degree of evolutionary

conservation, combined with the fact that the organization of hippocampal sub-

structures is characterized by an intricate form of layering that is unique within

the mammalian brain, provide some reason to think there exists a function, at

some level of description, that the hippocampus is expressly designed to perform.

It is therefore puzzling, prima facie, that the existing hypotheses of hippocam-

pal function are so wildly divergent. Moreover, it is puzzling that no unifying

functional theories have emerged that show how the various task-bound theories

are related to one another at a higher level of description.

By stepping back from the details of particular experiments, and focusing

instead on shared methodology, it is not difficult to see how the application of

TBFA makes the multiplicity of hippocampal theories more or less inevitable.

The spatial coordinate mapping hypothesis is an attempt to explain behav-

ioral phenomena observed in Morris water maze paradigms, in which a properly

functioning hippocampus is required for remembering the location of a stable

platform hidden below the surface of opaque water. The hypothesis that hip-

pocampal function has to do with transitive inference is an attempt to explain

behavioral phenomena in an odor-based paired association task, in which associ-

8



ations between bins of food cannot be consolidated over time without an intact

hippocampus (Gilbert and Kesner, 2003). The hypothesis that hippocampal

function has to do with behavioral inhibition is an attempt to explain the fact

that rats with lesions to dentate gyrus cells fail to become still in the presence

of what is normally perceived as danger (Takahashi, 1995).

The list of task-bound functional hypotheses could be extended, but these

few examples suffice to illustrate the feature of TBFA that presently concerns us.

It is this: each functional hypothesis in the literature is tailor-made to account

for phenomena generated by one family of behavioral experimental paradigms.

As the following section demonstrates, this kind of tailoring has the unfortu-

nate consequence of desensitizing functional hypotheses to the data collected

in paradigms that differ substantially from the one upon which a particular

hypothesis is based.

3 Task-bound Functions Do Not Explain Struc-

tural Properties

3.1 Unipotent Structures

The first part of the argument is simple. Consider the strong assumption that

each neuroanatomical structure—under a given description—realizes only one

genuine function. Bastardizing terminology from developmental biology, I’ll

refer to this as the unipotent case.

If a neuroanatomical structure were unipotent, then the diversity of func-

tional hypotheses proposed to explain the presence of structural properties

would contradict one another. Since truth does not accommodate contradiction,

and explanation requires truth, no explanation will be forthcoming until the con-

tradictions between proposals can be resolved.7 Moreover, in order to resolve

those contradictions under the assumption of unipotency, any given anatomical

area would have to be describable by one, uniquely true task-bound functional

hypothesis. But no task-bound functional hypothesis is uniquely true. Since

task-bound functions refer essentially to the environmental properties manipu-

lated in an experimental paradigm, each task-bound hypothesis describes only

7The thesis that explanation entails truth was made explicit by Carl Hempel in his law-
based account of scientific explanation Hempel and Oppenheim (1948). Despite the fact that
Hempel’s account is no longer thought to be as universally applicable as he had intended,
this particular thesis remains popular with most accounts of scientific explanation. (Notable
exceptions include those in Van Fraassen (1980), Achinstein (1985), and Bokulich (2011)).

9



a narrow range of the spectrum of functional contributions associated with an

anatomical area. Given unipotency, then, task-bound functional analysis al-

ways yields contradiction, and for that reason, fails to explain the presence of

structural properties.

3.2 Pluripotent Structures

The unipotency assumption is controversial.8 It will be objected that neuro-

scientists do not always take incompatible functional hypotheses about the role

of an anatomical structure to be logically contradictory. Sometimes, neuro-

scientists circumvent the incompatibility by indexing functional hypotheses to

different environmental contexts. In light of this observation, it is necessary to

consider the status of TBFA when applied to pluripotent neuroanatomical struc-

tures, where pluripotent means that the structure may serve multiple genuine

biological functions over time. If a structure is pluripotent, there need not be

any contradiction between what might otherwise appear to be competing func-

tional hypotheses. Which particular function is realized at a time will depend

on the occurrent behavioral goals of the organism, as well as the particular kind

of environment the organism happens to be in. Howard Eichenbaum, a leader in

hippocampus research, often expresses this ecumenical view: “. . . hippocampal

sequence representation underlies a range of memory performance capacities, in-

cluding episodic recall, cognitive mapping, sequence prediction, and inferential

memory expression” (Fortin, Agster, and Eichenbaum 2002).

However, the possibility of multiple diachronically realized functions does

not suffice to redeem the explanatory status of TBFA. To see this, recall the

definition of task-bound functions: a function F is task-bound just in case its

description essentially refers to a behavioral task in an experimental paradigm

in which environmental properties P1 . . . Pn are manipulated. Consider now

what happens if the functional activity of the structure in question is investi-

gated within a related experimental paradigm in which the set of manipulated

environmental properties are different: P1 . . . Pn. Since task-bound functions

are defined relative to experimental paradigms, a change in paradigm entails a

change in the identity of the task-bound function. This has the consequence that

new task-bound functions are all too easy to generate. Since there is no princi-

pled upper limit on the kinds of behavioral paradigms that might be invented,

8Some neuroscientists do take the unipotent view. With regard to hippocampal function,
one of the best arguments for unipotency can be found in O’Keefe (1999), where the place-cell
theory is advocated as the uniquely correct functional theory.

10



the list of purported task-bound functions for any given anatomical structure is

unbounded: creative variations in the task description yield increasingly many

new functions.

The possibility of an arbitrarily long list of functional ascriptions is the

source of the explanatory weakness inherent in TBFA. There are two reasons for

this. To see the first, assume that functions are defined relative to a containing

system, as suggested by Cummins (1975). A containing system is a system

that exhibits a complex capacity, relative to which the functions of its parts

are defined.9 (For example, the containing system for the pumping action of

the heart is the circulatory system.) If we hold the containing system fixed,

and if we are realists about functional roles, it should always be possible to

construct a true (or approximately true) claim specifying the functional profile

for a given neuroanatomical area. By functional profile, I mean a complete list

of functional capacities. Faced with the specter of an unbounded list, however,

such a construction is impossible. Any finite candidate list could be falsified by

adding just one more functional ascription.10

Note that TBFA faces this problem even if neuroscientists have no empirical

motivation to extend the list of hypotheses beyond its current length. For sup-

pose that TBFA were the only method of discovering structurally-oriented expla-

nations. Then, there could be no grounds for claiming of any list of task-bound

functions that it is complete, even if empirical adequacy had been achieved.11

Any functional contribution to behaviors yet to be taken into account would

demonstrate the incompleteness of the list.

The second reason that the possibility of an arbitrarily long list of func-

tions entails that TBFA is explanatorily limited is that there is a particular

kind of understanding associated with the simplicity of functional insights that

TBFA cannot deliver. Consider again the discovery of the function of myelin

9I do not mean to suggest that Cummins’ theory of functional analysis is the appropriate
one to use in this context. In fact, my account here is more compatible with what are some-
times called teleonomic functions, often associated with the work of Wright (1973). However,
I do not think these two accounts of function are mutually exclusive, nor do I think that
invoking the concept of a containing system commits one to either account.

10The canonical argument against the legitimacy of arbitrarily long disjunctions of realizers
of functional kinds can be found in Fodor (1974).

11Since the theories in question concern the functionally relevant effects of a brain area,
I assume that empirical adequacy is limited to those observations that incorporate neural
data. Since neural data is only made available in an experimental setting, achieving empirical
adequacy for a single theory implies very little about the vast majority of animal behavior.
In order for a theory about one neural structure to yield predictions about behavioral data
outside the confines of a particular experimental paradigm, commitment to a considerable
body of additional theory is required.

11



sheaths. That discovery was powerful in part because the functional insight it

represents is extraordinarily compact, and yet can account for the presence of

at least two otherwise puzzling structural properties. An arbitrarily long list

of functions would lack that conceptual compactness, which, although hard to

quantify, seems essential to achieving significant explanatory depth.12

3.3 Objection I: Levels of Abstraction

One might suspect that the possibility of an unbounded list can be avoided by

ascending to a more abstract level of description. If we characterize environ-

mental properties abstractly, it is possible to derive a generalized functional hy-

pothesis that stands in relation to specific task-bound functions as determinable

stands to determinate. The generalized functional hypothesis will itself be more

abstract than any given task-bound function it determines, and therefore in-

variant with respect to a larger class of changes in environmental properties. As

the number of admissible changes increases, it becomes more difficult and less

trivial to generate new functional hypotheses. For example, sequence prediction

refers to a broad class of behavioral tasks used in learning and memory studies

(Lisman and Redish, 2009). A wide variety of paradigms are counted as tests of

sequence prediction processing capacities: a sequence of stimuli can be gener-

ated over spatial or temporal metrics; it can be either one or two-dimensional;

stimuli can be visual, auditory, or olfactory, etc. We can define a neural function,

FS, as the function of carrying out sequence prediction processing. One specific

instantiation of sequence prediction is a task in which the animal must visually

detect non-random strings of stimuli buried within longer, random sequences

Dunnett et al. (2012). By appealing to this more specific task, we can define

another neural function, FR, such that FR is a determinate of the determinable

FS. Since FS ranges over a broader class of environmental properties than FR,

it is surely less susceptible to the charge of explanatory weakness. So why not

iterate the process of abstraction until a level is reached at which the number

of possible functions is suitably limited?13

Although this iterative process of abstraction is, logically speaking, quite

legitimate, it cannot redeem the explanatory status of TBFA. The amount of

12Unification-based theories of scientific explanation have tried to quantify this kind of
conceptual compactness, with mixed results. See, for example, Kitcher (1981).

13Thanks to Colin Klein for suggesting that the determinate-determinable relation is appli-
cable here. For a different argument about the limitations of abstraction, see Klein (2012).
For empirical data on the wide variety of brain regions associated with memory storage, see
Wager and Smith (2003).

12



explanatory strength to be gained by implementing such an abstraction process

is severely limited by an additional constraint on structurally-oriented explana-

tions: they must be capable of discriminating between distinct neural structures.

If a purported explanation were true of multiple brain areas, each of which ex-

emplified a unique form of structural organization, then, whatever else might

be explained, it would not be the unique structural properties of one of those

areas in particular. The need for this structural discrimination constraint can be

clarified by analogy with the lock-and-key mechanisms of the immune system.

Consider a purported explanation of the peculiar shape of an antibody that cites

the fact that the antibody supports immune system function. Compare it to a

purported explanation that cites the following fact instead: the antibody must

be shaped as it is in order to ensure compatibility with the surface proteins on

the antigen it serves to neutralize. All antibodies promote immune system func-

tion. In order to explain the structural properties of the antibody, a functional

hypothesis must include specific information about the capacities of that partic-

ular molecule. The second of the two aforementioned hypotheses does include

such information, and for that reason is clearly superior to the first. Similarly,

all neuroanatomical areas participate in whatever function(s) are served by the

nervous system as a whole, (i.e. survival) but that information is irrelevant to

understanding the structural eccentricities of any particular area.

The explanatory limitations of very abstract functional hypotheses derive

from the fact that they will be satisfied by many, and in some cases, all neuro-

anatomical structures in the brain. To return to our example: when it is claimed

that the function of the hippocampus is sequence prediction, we say something

which perhaps is true, but which fails to provide insight into its unique structural

properties. Although originally proposed as a generalized theory of hippocampal

function, sequence prediction is so general a concept that some researchers have

ascribed a virtually identical function to the brain as a whole Friston (2010). and

other proponents of the predictive coding theory of brain function argue that

the most adequate general theory of brain function is the prediction of sequences

of perceptual stimuli, given the memory of immediately past sequences. As we

have already seen, however, if a functional theory applies so generally, it cannot

shed light on the structural properties of the hippocampus in particular.

The lesson of this section is this: if we attempt to construct an abstract

functional theory by generalizing over a large class of task-bound functions, the

threat of an unbounded list is inevitable. In Section 4, I sketch an alternative

approach to functional analysis that avoids both the explanatory limitations

13



associated with TBFA, and those of hypotheses that generalize over task-bound

functions. Before moving on to that discussion, one additional objection should

be considered.

3.4 Objection II: Containing Systems are Chosen by Con-

vention

Another objection to the argument that TBFA cannot explain the presence

of structural properties has to do with the distinction between proximal and

distal effects. It can be framed as a reductio: the argument is absurd, one

might think, because it threatens not only task-bound functions, but functional

analysis generally. Compare the functional profile of a gene. If it is stipulated

that the containing system for some activity of a gene is the cell nucleus, then

the function of that gene will be specified in terms of proximal effects, such as

the initiation of RNA transcription. If it is stipulated that the entire nervous

system is the containing system, the function of the same gene will be specified in

terms of distal effects, such as the regulation of neurogenesis. Some philosophers

hold that containing systems are stipulated, rather than discovered. On this

view, it is always possible to construct an arbitrarily long list of functions by

stipulating additional containing systems. If such stipulation is legitimate, then

this case seems parallel to the case of TBFA. If the two cases are parallel, then

the argument in Section 3.2 ought to apply just as well to genetic explanation,

and therefore gives us reason to think that no amount of functional information

could provide insight into genetic structure. But if that is the case, the argument

proves far too much, and should therefore be rejected.

This objection is mistaken for two reasons. First, in the gene case, the gen-

eration of new functions is constrained by the biological pathways that exist

between gene and container. There may be many, but the set is finite.14 In

the case of TBFA, no such biological constraints exist. The number of unique

behavioral tasks in which a neuroanatomical structure can be shown to partici-

pate is limited only by the creativity of the experimental designer. Second, and

more importantly, in order to show that functional profiles generated by TBFA

can be made arbitrarily long, it is not necessary to vary the containing system

itself, as it is in the gene case. Rather, it is only necessary to vary the set of en-

14There are also important distinctions between biological pathways, such that some
pathway-types permit explanatory relations to hold, while others do not. Woodward (2010)
provides a good philosophical analysis of these type differences.

14



vironmental properties P1 . . . Pn referenced in the definition of the experimental

paradigm. So the variability in the TBFA case radically outstrips the variability

in the gene case. Since the two cases are not parallel after all, the objection

fails.

Arbitrarily long lists of function cannot explain the presence of structural

properties. We have seen that TBFA makes impossible the identification of

a principled upper limit on the list of functions associated with a given brain

area. Any actual list generated by the application of TBFA will therefore have

an arbitrary length (whether the magnitude of that length is great or not).

Therefore, TBFA is incapable of explaining the presence of structural properties.

In the next section, an alternative concept of functional analysis in neuro-

science is discussed, and some speculative remarks are made about the research

programs that appeal to it. I argue that the form of functional analysis sug-

gested by this alternative concept is not subject to the explanatory limitations

of TBFA, and therefore deserves further investigation.

4 The Explanatory Depth of Intrinsic Brain

Function

4.1 A New Concept of Neural Function

If the argument in Section 3 is correct, then the explanatory status of certain

neuroscientific theories that depend on TBFA is threatened. Rather than trying

to identify those theories, I propose a more positive, philosophical project: I

propose to provide a rough sketch of a new kind of functional analysis that

avoids the explanatory weakness of TBFA.

Given the vast amount of information yet to be learned about neural struc-

ture, this synthetic project must remain at least partially speculative. Neverthe-

less, it can be made systematic if it is framed in terms of a search for desiderata

that a new, more explanatory concept of neural function ought to satisfy. The

first of these desiderata is this: the new functional concept must denote a prop-

erty capable of being realized in neural processes that span multiple behavioral

tasks. This follows immediately from the argument in Section 3. As suggested

above, in order to be explanatorily robust, neuro-functional hypotheses must

not be susceptible to falsification by the replacement of one set of environmen-

tal properties with another. In order to accommodate alternative environmental

15



properties, a function must be realizable in processes that range across tasks.

4.2 Multiple Cognitive Domains

Recent work in functional neuro-anatomy suggests two additional desiderata.

The first of these is inspired by the work of Michael Anderson, who has ar-

gued for a claim similar to the conclusion reached in Section 3, albeit on very

different, mostly evolutionary grounds (Anderson, 2010, 2007)15. Although An-

derson does not attempt to define a novel concept of neural function, he does

make some suggestive remarks. “Insofar as our approach to discovering the spe-

cific functional role of a given brain area involves modeling its activity across

different cognitive domains, then it makes little sense to try and characterize

the contribution of the area using domain specific terms” (Anderson, 2007, p.

339).

Anderson is suggesting that the concept of neural function appropriate to

capturing the functional role of anatomical areas must be one that is realiz-

able in processes that span multiple cognitive domains.16 This desideratum is

stronger than the first, which only necessitated that our new concept of function

be realizable in processes that span multiple behavioral tasks. To see that the

former demand is stronger than the latter, one must only note the very small

number of cognitive domains relative to the number of (possible) behavioral

tasks. One standard taxonomy of cognitive domains includes just seven: atten-

tion, skill learning, semantic memory, language, episodic memory, and working

memory (Cabeza and Nyberg, 2000). While finer-grained distinctions between

cognitive domains are sometimes used, they are not nearly as fine-grained as the

behavioral tasks invoked by standard experimental paradigms. Consequently,

there will be a greater number of conditions under which one brain area is in-

volved in two behavioral tasks than conditions under which that brain area is

involved in two cognitive domains. Therefore, the requirement that a functional

concept be realizable in processes that span domains is more stringent than the

15Anderson’s “massive redeployment hypothesis” states that it is empirically likely that
anatomically distinct brain areas developed in order to carry out one function, but, via exap-
tation, came to shoulder additional burdens throughout evolutionary history. Because the
multiple etiological functions realized by one anatomical area can differ quite significantly from
one another, the multiple reuse hypothesis is incompatible with the assumption that anatom-
ically distinct brain areas are, generally speaking, dedicated to the realization of behavioral
functions that are themselves defined with respect to a narrow spectrum of environmental
contexts.

16Thanks to Jesse Prinz and Michael Anderson for helpful discussion about the way in which
my thesis differs from Anderson’s own.

16



requirement that it be realizable in processes that span behavioral tasks.

The motivation for imposing this condition is a body of empirical evidence

from imaging meta-analyses that suggest that brain areas traditionally asso-

ciated with one cognitive domain in fact participate in processes that span

multiple domains (Cabeza and Nyberg, 2000; Wager et al., 2007). Such meta-

analyses do not suggest that every brain area is multifaceted in this way, but

they do show that multi-domain activity is common. If so, it would be useful

to have a concept of neural function that can capture the general contribution

of an area across cognitive domains. On this point, it is worth quoting Cabeza

and Nyberg 2000 at length, from a passage in which they interpret the section

of their results in which the data is modeled by anatomical region.

Activations in parietal area 7, for example, were consistently found

in studies of attention, space perception, imagery, working memory,

episodic memory, and procedural memory. The most parsimonious

account of this kind of activation is that they reflect cognitive pro-

cesses that are tapped by tasks in different domains. However, most

functional neuroimaging studies have preferred to interpret activa-

tions within their own domain. . . Area 7 activations, for instance,

were usually attributed to attentional processes in attention studies,

to perceptual processes in perception studies, to working memory

processes in working memory studies, and so on. These domain-

specific interpretations are useful because they allow researchers to

refine hypotheses and plan new experiments. . . At the same time, it

would be useful to systematically compare functional neuroimaging

data in different cognitive domains and to develop general theories

that account for the involvement of brain regions in a variety of

cognitive tasks (Cabeza and Nyberg, 2000, pp. 31-32).

As Cabeza and Nyberg suggest, domain-specific functions are useful, but

explanatorily limited. If we want a more general theory about the functional

role of an anatomical area, we require a concept of neural function that is

divorced from any essential connection to a particular cognitive domain.

4.3 Intrinsic Function

The third desideratum, which is also the strongest of the three, is this: our new

concept of neural function must be capable of eschewing reference to behavior

17



altogether. This desideratum is motivated by a relatively new body of evidence

suggesting that much neural activity is designed to achieve ends that are –

in a sense that requires explication – intrinsic to the central nervous system.

This formulation is inspired by the term ‘intrinsic neural function,’ which was

recently coined by Marcus Raichle, and which he defines as “ongoing neural

and metabolic activity not directly associated with the performance of a task”

(Raichle, 2010). Raichle has marshaled evidence suggesting that at least a large

proportion of neural function must be intrinsic in this sense. If he is right, then

given the lack of association between this alleged class of neural functioning

and the particularities of the behavior with which it is concurrent, we require

a concept of neural function that can be articulated without mention of those

particularities.

One line of evidence for Raichle’s proposal comes from his own work on the

default mode network — a network that is differentially activated whenever

an organism is unencumbered by goal-oriented activity. For example, neuro-

metabolic activity in the resting state (in humans) consumes approximately 20%

of the body’s total energy budget. Relative to resting state energy consumption,

additional activity associated with momentary changes in brain activity is only

about 5%, even during arousing perceptual and motor activity.17 On the rea-

sonable assumption that neuro-metabolic rates are correlated with functional

operation, Raichle concludes that much of our normal brain function is driven

by internal demands, rather than the transient, environmentally-modulated de-

mands of whatever task an organism happens to be engaged in. Raichle’s work

focuses primarily on whole brain analysis, and contains little explicit discussion

of the prospects for localization to anatomically defined areas. Nevertheless,

Raichle’s claims are based on calculations of glucose consumption, a process

that is fundamental to the metabolic capacities of all neurons. Raichle’s find-

ings, therefore, are relevant to any theory of neural function, whether it concerns

activities that are localized to small anatomical structures, or activities that are

distributed across them. If, as this evidence suggests, the majority of localized

neural functions are intrinsic, then we require a concept of neural function that

is compatible with intrinsic functionality. I therefore suggest that the third

desideratum be formulated as follows: the new concept must denote properties

that are realizable in intrinsic processes.

It is important to note that, despite a superficial similarity, this condition

17The molecular evidence for this thesis is presented more fully in Raichle and Mintun
(2006).

18



differs from the first—the one imposed by the result obtained in Section 3.

That argument only shows that if we want structurally-oriented explanations,

the neural functions we appeal to must be realizable in processes that range

across behavioral tasks. In order to capture the contributions of intrinsic neural

activity, the concept of neural function must be capable of eschewing reference

to behavior altogether, which is a considerably stronger condition.

It should also be noted that the second and third desiderata constrain the

concept of neural function in substantially different ways. Consider the (du-

bious) claim that the amygdala is a fear-processing center. Here, no reference

to behavior is made, but the hypothesis still lacks explanatory power to the

extent that the amygdala participates in processes that span other domains.18

Because this case satisfies the second, but not the third desideratum, it serves

to demonstrate the substantive difference between them.

4.4 Containing Systems Inside the Brain

Unfortunately, our three desiderata are difficult to satisfy without immediately

running up against the limitation on abstraction discussed in Section 3.3. In

order to provide non-trivial explanations of structural properties, (why are the

inputs to the hippocampal formation mossy fibres, rather than pyramidal cells?)

functional hypotheses must supply information that is both detailed and free

from reference to particular tasks. The challenge posed by this requirement can

be re-conceptualized as a tradeoff between the explanatory limitations of task-

boundedness, on the one hand, and the explanatory limitations of ungrounded

abstraction on the other.

Fortunately, it may be possible to avoid the tradeoff, at least in part, by re-

considering the kinds of containing system that are compatible with our desider-

ata. Since reference to behavior has been ruled out by the third desideratum,

any containing system to which the new concept of neural function refers must

be internal to the organism. In particular, the new concept of function will be

defined with respect to containing systems inside the brain.19

18For a review of the fear hypothesis, see Rosen and Donley (2006).
19There is a growing literature on task ontology that can be viewed as an independent

solution to the problem articulated in Section 3. The strategy behind constructing a task
ontology is as follows: use imaging meta-analyses to find all the tasks that have elicited
activation in one area. Then search for what these tasks have in common. (For an overview,
see Poldrack et al. (2011)). My view is that this empirical strategy, in combination with
computational modeling, is a very promising way of implementing the signal transformation
approach I advocate here. As meta-analyses increase in sample size, we gain more insight into
the functional profile of the area in question. Moreover, this method has lead quite directly to

19



This restriction forces us to think of neural function in terms of the proximal

effects a brain area has on the circuit of which it forms a part. Since cognitive

and behavioral vocabularies have been ruled out, we are forced to resort to a

more abstract, mathematical level of description to capture those proximal ef-

fects. Rather than framing functional hypotheses about an anatomical area in

terms of its contribution to behavior, or its capacity to realize a cognitive pro-

cess, the new concept of neural function allows us to frame functional hypotheses

in terms of signal transformation. Each anatomical hub in a large-scale brain

circuit exhibits a unique set of structural properties that determines the kinds

of transformation it is capable of carrying out. As a signal flows through the

circuit, it will be transformed in a particular way at each anatomical hub. In

principle, that transformation can be modeled mathematically. If so, functional

ascriptions take on a logical form that is very different from those underlying

most functional ascriptions in biology. Consider the following schema: the func-

tion of brain area A is to transform signal S in manner Φ. If transformation

can be modeled by a mathematical function, then the functional role identified

by this schema provides information that is both detailed and specific. If so,

the tradeoff between task-boundedness and abstraction has been circumvented.

The two-variable formulation of the schema above is designed to make pos-

sible a relatively fine-grained form of functional analysis. Whether or not a

brain region instantiates Φ will be determined by local microanatomy. But the

individuation conditions on S may incorporate information about the sensory

modality from which it originates, as well as information about the site at which

the transformed signal is to be consumed. So even in cases in which two brain

areas are indistinguishable with respect to local anatomy, they can nevertheless

realize distinct functional roles.20

In the past decade, multiple new lines of research have adopted a signal

transformation based view of functional analysis. What they have in common is

their foundation in quantitative analysis of spiking neuron models. For example,

Levy, Hocking, and Wu (2005) offer a theory of hippocampal function that

the kind of computational approach I advocate. For example, Penner-Wilger and Anderson
(2008) use this method to introduce the concept of an “array of pointers” to show how one
signal transformation is at work in the use of both finger and number representations.

20I believe that this proposal is compatible with the two-factor theory of neural semantics
proposed in Eliasmith (2000). However, justification for that claim would require a detailed
discussion of the relation between functional analysis and metaphysical semantics, which,
being a controversial topic in its own right, cannot be included here. Sullivan Sullivan (2009)
suggests that neuroscience would benefit from attempts to make the representational content
of even low-level hypotheses more explicit. My schema could be taken as a sketch of a method
for accomplishing that goal.

20



overcomes the limits of TBFA by appealing to the purely intrinsic concept they

call the “associator of last resort.” Briefly, the idea is that the hippocampus

is designed to form associations between input patterns that are, statistically,

so dissimilar from one another that other anatomical regions cannot “find” the

associations.

Its ability to do this depends on the structural properties that define the

network used to model the brain area, such as percentage connectivity and the

degree of feedback inhibition from interneurons. These anatomical properties

determine which functions (in the mathematical sense) a region is able to ap-

proximate.21 In this functional hypothesis, the capacity that explains the pres-

ence of particular structural properties in the brain region is specified in terms

of intrinsic statistical properties that remain constant over time and across envi-

ronmental changes. Moreover, Levy’s “associator of last resort” concept makes

no reference to experimental tasks, particular cognitive domains, or particular

behaviors, and thereby satisfies the three desiderata we have imposed on an

explanatory concept of neural function.

I hope to have made two overarching points thus far. The first was that

TBFA fails to explain the presence of structural properties. The second point

was that the new concept of neural function suggests ways of overcoming that

limitation. The philosophical upshot of these two points is simply that, when

it comes to the brain, functional analysis will have to be carried out in abstract

terms that are very different from those discussed in philosophy of biology. Lo-

calization of neural function is possible, but we will find the kinds of functions

that can be localized quite surprising. Successful functional analysis will become

integrated with what is currently known as “theoretical neuroscience” and will

most likely draw on fields such as information theory, statistics, genetics, and

perhaps physics, rather than directly from experimental paradigms in wet labo-

ratories. Moreover, functions will be defined with respect to container systems

within the brain itself.

These points return us to the claim made at the outset — that no brain

area has a behavioral task as its principal function. Since task-bound functions

cannot explain structural properties, they also cannot identify the unique con-

21For other brain areas, a similar perspective has been offered Rajesh Rao and colleagues.
(See, for example Doya (2007)). This area of theoretical neuroscience has been growing
exponentially over the past decade, and has provided a host of new concepts for neuroscientists
to work with. This paper can be seen as an attempt to point out the why this mathematical
literature should be considered relevant to concerns about functional analysis that have long
occupied philosophers of biology.

21



tribution an anatomical area makes to the capacities of the brain as a whole.

Since task-bound functions clearly fail to approximate that unique contribu-

tion, they ought not be used to label anatomical areas: the selection of any one

label would be arbitrary. If we want our neuro-functional designations to be

principled, they will have to satisfy the desiderata outlined above.

Acknowledgments

Thanks to Colin Klein, Michael Anderson, and Paul Humphreys for providing

helpful comments on an earlier draft. Thanks also to Jesse Prinz and Matt

Duncan for helpful discussion of the issues here discussed.

22



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