This article was downloaded by: [Stony Brook University]On: 02 November 2014, At: 06:10Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK

Philosophical PsychologyPublication details, including instructions for authorsand subscription information:http://www.tandfonline.com/loi/cphp20

Cognitive science andneuroscience: New wavereductionismRobert C. RichardsonPublished online: 19 Aug 2010.

To cite this article: Robert C. Richardson (1999) Cognitive science andneuroscience: New wave reductionism, Philosophical Psychology, 12:3, 297-307, DOI:10.1080/095150899105774

To link to this article: http://dx.doi.org/10.1080/095150899105774

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all theinformation (the “Content”) contained in the publications on our platform.However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, orsuitability for any purpose of the Content. Any opinions and views expressedin this publication are the opinions and views of the authors, and are not theviews of or endorsed by Taylor & Francis. The accuracy of the Content shouldnot be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions,claims, proceedings, demands, costs, expenses, damages, and other liabilitieswhatsoever or howsoever caused arising directly or indirectly in connectionwith, in relation to or arising out of the use of the Content.

This article may be used for research, teaching, and private study purposes.Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly

forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

PHILOSOPHICAL PSYCHOLOGY, VOL. 12, NO . 3, 1999

Cognitive science and neuroscience: new

wave reductionism

ROBERT C. RICHARDSON

ABSTRA CT John Bickle’ s Psychoneural reduction: the new wave (Cambridge, MA: MIT Press,

1998) aims to resurrect reductionism within philosophy of mind. He develops a new model of scienti® c

reduction, geared to enhancing our understanding of how theories in neuroscience and cognitive

science are interrelated. I put this discussion in context, and assess the prospects for new wave

reductionism, both as a general model of scienti® c reduction and as an attempt to defend reductionism

in the philosophy of mind.

Reduction has a bad reputation within philosophy. This is an interesting fact,

particularly in light of its evident successes within the special sciences. Physical

chemistry is often a matter of atomic physics. Cell biology depends on biochemistry.

The behavior of organic systems is a function of constituent organ systems. Group

behavior often needs to be understood in terms of local, individual, interactions.

These are all cases of reduction at work in the sciences. Such successes do not

compromise the equally evident complexity of the underlying processes. Biochem-

istry is one of the more straightforward cases, though the cases it provides are

inherently complex. The synthesis of relatively simple organic compounds from

simpler ones within the cell is highly sensitive to initial conditions, involving a large

number of interacting components, with multiple pathways and a variety of potential

outcomes. The resulting organic compounds will not function properly unless they

have not only the right sequence of atoms, but the right three dimensional confor-

mation and surface properties. The intracellular processes involved in such synthesis

themselves are carefully orchestrated, and understanding the process is anything but

trivial. The techniques for dealing with such complexity are varied, and include not

only the production of detailed analytical solutions, but a variety of approximations

and averaging that facilitate linearization. Social behavior and physiology are no less

complex than biochemistry. Neither are the neurosciences, or psychology. Re-

duction has still played an important role in these sciences.

John Bickle’ s Psychoneural reduction: the new wave is an ambitious attempt to

improve the bleak reputation of reduction within philosophy of mind and to give it

Robert C. Richardson, Department of Philosophy, University of Cincinnati, Cincinnati OH

45221± 0374, USA; e-mail: Robert.Richardson@uc.edu

ISSN 0951-5089 (print) ISSN 1465-394X (online)/99/030297 ± 11 Ó 1999 Taylor & Francis Ltd

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

298 ROBERT C. RICHARDSON

a new face. Drawing on work within philosophy of science, and especially structural-

ist work on the semantic view of theories by Balzer et al. (1987), Bickle wants to

convince us that reduction is alive and well even within cognitive science. The more

general problem is essentially one of understanding how theories pitched at different

levels of organization are related. There are many cases, varying in their complexity.

The sea slug, Aplysia, is a favorite of neuroscientists. Its nervous system consists of

aggregates of neurons, called ª ganglia,º each of which contains several thousand

nerve cells. They underlie learning and memory in Aplysia, in ways we now

understand relatively well. The brain of a bee is moderately more complex, with

roughly a million neurons that control an elaborate ensemble of behaviors, including

navigation and communication. Understanding the behavior of bees, or even of

slugs, is not merely a matter of summing up the effects of the multitude of neurons.

At the other extreme, a human brain has a hundred billion neurons with trillions of

interconnections. We can describe and explain human behavior at a variety of levels.

Bickle sees that whether we are concerned with ion channels, neuronal behavior,

brain circuits, or the cognitive and emotional systems they subserve, it is important

to understand how these various levels of explanation are related, how models

geared to one level are relevant to those developed at others, and how the theories

pitched at these several levels in¯ uence one another. This is the broader agenda of

Psychoneural reduction.

Without losing sight of the broader issues, Bickle is especially concerned to

develop a critique of the antireductionist consensus which dominates much of

Anglo-American philosophy of mind. The consensus has survived a number of

changes, but is derived from work by Jerry Fodor, Hilary Putnam, Donald David-

son, and others. Two salient facts support the consensus. First, it is possible to

interpret, explain and predict genuinely cognitive phenomena by appeal to represen-

tations and the operations on them. We do not have to venture far from more

standard psychological paradigms to make the point. False memories can be in-

duced by the presentation of related ideas. Given a prose passage or a simple list

containing, say, ª valley,º ª summit,º ª peak,º and ª climb,º subjects will recognize

ª mountainº as among the words presented as often as they recognize those that

actually did occur. The evident explanation for such false memories is in terms of

representational content. Memory is, sometimes at least, organized around semantic

representations. Explanations of such things as the patterns of forgetting, false

memories, and recollection do make use of representational models, and without

representations we seem to have no explanation of them at all. The second pillar of

the antireductionist consensus depends on the differences between the level of

cognition and that of physiology: the same representation, the same belief, or the

same emotion can be realized by a wide variety of neural systems, systems which are

physiologically distinct to varying degrees. Distinct neural states are involved in

Bickle’ s appreciation of the ocean and in mine. For that matter, distinct neural states

are involved in Bickle’ s appreciation of the ocean now, as contrasted with his love

of it as a child. Given that cognition is a matter of rules and representations, even

an arti ® cial system or an alien could share an appreciation of the ocean. The neural

organization of Klingons or androids is unlikely to share much with ours, though

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

COG NITIVE SCIENCE AND NEU ROSCIENCE 299

they too might still appreciate the ocean. These twin commitments are used as

warrant for the autonomy of psychology: the reliance on rules and representations

in cognitive explanations supports the need for some distinctively psychological

level of explanation, and multiple realization guarantees that those explanations

cannot be captured at a lower level. The psychology is both relevant and indispens-

able.

Bickle recognizes that the antireductionist consensus also depends on a particu-

lar way of understanding scienti® c reduction. This picture is most commonly

associated with Ernst Nagel’ s The structure of science (1961, Chapter 11). It has been

rehearsed in a variety of discussions since. Reduction on this view consists in the

explanation of laws at a higher level in terms of a lower level science, sometimes with

the help of ª bridge lawsº connecting the sciences. Bickle offers us a somewhat

different picture of reduction, freed from many of the assumptions which underlie

Nagel’ s account. The problem of how mind and brain are related is, Bickle says,

ª ¼ a problem stemming from the existence of distinct levels of theory and explanation

for a range of phenomena (behavior), and in particular about how these distinct levels

relate when our concerns are ontologicalº (p. 16). Bickle draws extensively on work

by Hooker (1981) to construct a general theory of reduction. It begins with the

observation that the process of reduction invariably involves some degree of correc-

tion and modi® cation in the theory reduced. As Kuhn and Feyerabend insisted,

Galilean physics is not deduced as is from Newtonian physics any more than

Newtonian physics is deduced as is from Relativistic mechanics. Likewise, the

molecularizat ion of the gene has not left our understanding of the gene unmodi® ed

in the process. Both functional features of genesÐ their mutagenic, catalytic, and

autocatalytic propertiesÐ and more structural featuresÐ their composition and

arrangementÐ have been involved in understanding genes and genetics (cf. Burian

et al., 1996). The theories initially developed at a higher level are corrected and

modi® ed as they are explained. Hooker and Bickle, like Kenneth Schaffner (1967),

claim that what is derived is a modi® ed theory that is analogous or similar to the

theory reduced (Hooker, 1981, p. 49). What can be derived within Relativistic

mechanics is at best similar to what was constitutive of Newtonian mechanics. What

is explained by molecular genetics is not quite what was constitutive of Mendelian

genetics, though it does incorporate such features as dominance and recombination.

What we should expect to be explained by neuroscience need not exactly replicate

cognitive models, though a reduction would retain some of the central features.

Bickle develops and elaborates his model for reduction by appeal to the war

horse of theoretical reduction: the relationship between statistical mechanics and

thermodynamics. A brief overview and reminder may help. It is useful to begin with

Boyles’ law and the law of Charles and Gay-Lussac. Boyles’ law says that, at least

to a ® rst approximation, the product of the pressure and volume for a sample of gas

is constant at a constant temperature. The law of Charles and Gay-Lussac says

essentially that the increase in volume as a function of increasing temperature is

constant for a gas held at a constant pressure. The combined law is a straightforward

consequence. It says that for ideal gases, the product of pressure and volume is a

constant function of temperature:

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

300 ROBERT C. RICHARDSON

PV 5 kT

The law is strictly limited in scope. The regularities it describes are maintained only

for a few ª idealº gases at low densities and moderate temperatures. At extreme

temperatures or high densities, the law breaks down. Though the Boyle± Charles law

is but one of several macro-properties of medium density gases, it has assumed an

important role in the uni® cation of thermodynamics and kinetic theory. It is one of

the central postulates which a uni® ed theory needs to explain, just as the uni® ed

theory needs to explain the well-known deviations from the law. This takes us to

statistical mechanics. A simple, if somewhat anachronistic, presentation of the

statistical theory begins with three postulates:

1. gases can be identi® ed with aggregates of particles that can be assumed to lack

any internal structure;

2. the particles constituting a gas are of a constant size, which is vanishingly small

in comparison with the distance between them; in the limit, they are taken to

be point masses; and

3. the thermal energy of a gas is identi® ed with the aggregate kinetic energy of the

particles constituting the gas, and an increase/decrease in the temperature of

the gas is due to an increase/decrease in the aggregate kinetic energy of these

partic les.

The ® rst two assumptions are unabashedly counterfactual. The idealizations they

embody make the theory analytically tractable. The third assumption is tantamount

to an identi® cation of temperature with kinetic energy. With these three assump-

tions, it is a relatively trivia l matter to explain the equation of state for a gas, on the

further assumption that Newton’ s laws of motion apply unchanged at the atomic

level. It is a matter simply of calculating the average force exerted on the sides of a

container by a gas with a known number N of molecules of determinate mass m. The

result is the Bernoulli formula:

PV 5 (Nmv2)/3

Since the total kinetic energy due to translational motion of the molecules, et, will

be (Nmv2)/2, the Bernoulli formula can be rewritten thus:

PV 5 (2/3)et

The Bernoulli formula is a syntactic analogue of the Boyle± Charles law, as Hooker

requires. It has the exactly same form, as is clearly seen in the second version of it.

So what is deduced within statistical mechanics is indeed analogous to the original

Boyle± Charles law. This is exactly as Bickle’ s views require.

The thermodynamics/statistical mechanics case, nonetheless, is not well suited

as a paradigm for Bickle’ s purposes. The problem Bickle originally poses, recall, is

how theories pitched at different levels of organization are related to one another. He

assumes, as is often done, that statistical mechanics and thermodynamics offer such

a case. The thermodynamics of the 19th century was deeply deterministic, embed-

ded in a Newtonian framework. The idealized molecules of the gas laws were

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

COG NITIVE SCIENCE AND NEU ROSCIENCE 301

understood as Newtonian particles: elastic, solid, unidimensional and particulate. If

we compare an explanation of, say, a change in pressure using Boyle’ s law, with an

explanation of the same change couched in statistical mechanics, it is tempting to

think that the latter is a better mechanical explanation, that the former is somehow

incomplete, and that the latter lies at a lower level of organization. This is an

illusion, as Woodward (1989) has shown us. Though gases are conceived within

statistical thermodynamics as aggregates of molecules, the prospect of tracking the

trajectories and interactions of each moleculeÐ or of even one molecule Ð is wildly

unrealistic. It also is not what is done in statistical thermodynamics. Instead of

appealing to the molecular behaviors that underlie the behavior of gases, statistical

mechanics abstracts from such causal processes and focuses on the behavior of the

aggregate. The most important feature of the structure of gases for statistical

mechanics is that they lack structure altogether. They are random aggregates.

Accordingly, the explanation of the macroscopic properties of gases is irreducibly

statistical. Statistical mechanics thus is corrective relative to classical thermodynam-

ics, just as Bickle would predict, insofar as the apparently deterministic laws at the

macroscopic level are actually probabilistic [1]. The important thing to realize is

that, contrary to more familiar presentations, there is no more compete, determin-

istic, causal/mechanical explanation of the behavior of gases at a lower level offered

within statistical mechanics. Statistical mechanics is not a theory pitched at a lower

level, but offers a statistical theory of the macrobehavior of gases. Moreover, even if

we were in a position to produce a serious explanation at the level of the underlying

mechanical processes for some speci® c change in pressure within a gas over a period

of time, we should be unsatis® ed with it. It would fail to capture the pattern that is

captured by the Boyle± Charles law or its statistical counterpart. Ultimately, the

pattern is more important than the pieces, and the pattern is a statistical property of

the aggregate (see Richardson, in press). Thus, as we move from classical thermo-

dynamics to statistical mechanics, we do displace one theory and one explanation

with another. We do correct the former signi® cantly, moving to an irreducibly

statistical explanation. We do not shift from one level to another. Statistical mecha-

nics does not lie at a lower level of organization, explaining the macroscopic

behavior of gases in terms of microstructure. We are still concerned with the

properties of the aggregate.

My discomfort in relying on this paradigm for reduction re¯ ects a more general

skepticism. If the goal is one of understanding the relationship of theories or models

at different levels of organization, then relying on theories or models at the same

level may signi® cantly mislead us. Robert McCauley, following William Wimsatt,

has argued that we should distinguish between intralevel contexts and interlevel

contexts when discussing intertheoretic relations. Elimination in favor of a scienti® c

successor is a consequence of displacement by a scienti® c competitor framed for

similar explanatory purposes. We do not ® nd a reduction of phlogiston chemistry in

Lavoisier’ s work, though we do ® nd many of the same phenomena explained in

both. A successful program of research geared toward theories at different levels of

organization, by contrast, generally does not result in elimination, but integration

(cf. Wimsatt, 1976; McCauley, 1986, 1996). We can, for example, explain the

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

302 ROBERT C. RICHARDSON

synthesis of organic compounds in terms of physical chemistry, but it is no part of

physical chemistry to explain their evolution. Bickle’ s treatment, like that of Paul

and Patricia Churchland (1990), treats intralevel and interlevel contexts as being of

a piece. They are treated in essentially the same terms. I am skeptical that they

should be [2].

An even more historically realistic account of the relation between thermo-

dynamics and statistical mechanics also differs in other signi® cant ways from

Bickle’ s more orthodox and ontologically oriented account of reduction. The motive

force for the uni® cation of kinetic theory and thermodynamics was not a desire to

explain or derive the ª lawsº of thermodynamics; philosophical and ontological issues

were even more remote. The actual scienti® c motivation was the need to explain

such things as the interconversion of thermal energy with other forms, and this could

not be done without a serious recasting of the problem. I believe that the point is

quite general. The motivation for reduction is explanatory adequacy. It is for this

reason that anomalies, whether experimental or theoretical, play such crucial roles in

reductionistic theorizing: experimental anomalies (such as the behavior of isomers in

molecular bonding) suggest a failure of higher level models to explain the pheno-

mena within their domain, and theoretical anomalies (such as the interconversion of

thermal energy with mechanical) suggest that the models fail to unify signi® cantly

similar domains (see Bechtel & Richardson, 1993). Wimsatt explained the point:

When a macro-regularity has relatively few exceptions, redescribing a

phenomenon that meets the macro-regularity in terms of an exact micro-

regularity provides no (or negligibly) further explanation. All (or most) of

the explanatory power of the lower level description is ª screened offº by

the success of the macro-regularity. The situation is different however for

cases which are anomalies for or exceptions to the upper level regularities.

Since an anomaly does not meet the macro-regularity, the macro-regularity

cannot ª screen offº the micro-level variables. If the class of macro-level

cases within which exceptions occur is signi® cantly non-homogeneous

when described in micro-level terms, then going to a lower-level descrip-

tion can be signi® cantly explanatory. (1974, p. 690)

With an adequate higher level theory, there would be no explanatory gain by shifting

to a lower level. In the face of anomalies, a shift in level can offer an explanatory

gain. The drive is not one for lower level explanatory suf® ciency, but is one geared

toward gaining overall explanatory adequacy. What we see is an emphasis on

explaining selected upper level phenomena and limited upper level regularities in

terms of mechanisms framed at the lower level, but no demand to explain all the

upper level phenomena in lower level terms. For example, the explanation of genetic

dominance, the position effect and development were central problems that lay

beyond the scope of Mendelian genetics. What was explained by Mendelian genetics

did not need explaining in terms of molecular mechanisms. Mendelian genetics,

though, was not the whole story. Reduction does not eliminate higher level theories,

or ª displaceº them in favor of theories and models framed solely in terms appropri-

ate to the lower level. Reduction is a process that is more akin to the construction

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

COG NITIVE SCIENCE AND NEU ROSCIENCE 303

of a uni® ed theory with causal parameters at multiple levels, employing lower level

mechanisms to explain ª criticalº phenomena. The resulting view is what McCauley

calls ª explanatory pluralism,º the result of which is ª a diverse set of partially

integrated yet semi-autonomous explanatory perspectivesº (1996, p. 28). Levels of

explanation mirror levels of organization, integrating different perspectives rather

than eliminating one in favor of another.

Bickle follows Patricia Churchland (1986) and Paul Churchland (1979) in

thinking that the problem of the relationship of mind to body is properly understood

in terms of the reduction of commonsense, folk, psychology to neuroscience. If the

outcome were a full and proper reduction of psychology to neuroscience, we would

be left with an identity theory. Without anything approximating a reduction, we

would be left with either eliminativism or functionalism, depending on whether we

are willing to dispense with psychological explanation. Bickle, like Hooker and the

Churchlands, recognizes that this is not a simple dichotomy but a continuum of

cases. Elimination and retention are opposite ends of a continuum, depending on

the extent of the corrections involved. This way of thinking of the issue is useful,

though it is a mystery to me why we should be concerned with folk psychology at all.

Folk psychology is a philosopher’ s ® ction. The substantive problem is the relation-

ship of cognitive psychology to neuroscience. If our best cognitive science requires

rules and representations, then one problem we face is the relationship of those

features of our cognitive life to the revelations of neuroscience. This is a topic that

we will revisit as does Bickle throughout his book.

Bickle’ s own more detailed account of intertheoretic reduction is a modi® cation

and elaboration of Hooker’ s in light of the structuralist program which has been

elaborated on the continent (see Balzer et al., 1987). It is framed in an elaborate set

theory, intended to demonstrate that the account is suf® ciently ª rigorousº to satisfy

the most stringent demands for clarity and consistency. The structuralist framework

in which Bickle sets his view is sometimes tough going, but the work is worth it. I

do not recommend skipping over the details. An ideal reduction, according to

Bickle, appears to have four main elements, each of which we may capture infor-

mally. First, we must specify a model within the reducing theory and a reduction

relation r giving a mapping from the reducing theory into the reduced theory. This

reduction function must be an ª ontologically reductive linkº which preserves the

empirical domain of the reduced theory. Second, for every con® rmed application of

the reduced theory, there must be a model in the reducing theory bearing the

relation r to the former. Third, there generally will be some models within the

reducing theory which have no corresponding models in the reduced theory. The

reducing theory generally will be stronger than the reduced theory, and will correct

it signi® cantly outside the domain for which it was elaborated. Finally, Bickle

introduces what he calls ª blursº to accommodate cases of approximation and

correction. When the reduced theory, or its empirical models, are subject to

systematic correction, the degree of blur is the amount of approximation or correc-

tion allowed. The ® rst two conditions are analogous to the condition of

ª connectabilityº in Nagel’ s classic account of reduction. The ® rst provides for a

mapping from the reducing theory to the reduced theory, and the second for a

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

304 ROBERT C. RICHARDSON

mapping from the reduced theory to the reducing theory. The third condition allows

for anomalies to be explained by the reducing theory, and allows that the reducing

theory may have a signi® cantly broader scope. The extent of the blurring allowed

can also be seen as the extent to which there is an analogy between the reduced

theory and whatever can be explained by the reducing theory. With minimal blur,

the reduced theory is retained. The analogy between reduced and reducing theories

is high. With maximal blur, the theories become incommensurable. The analogy is

weak. Elimination is the result.

With this apparatus in place, Bickle sets about to defuse the arguments against

the reduction of cognitive science to neuroscience. This includes not only a dis-

cussion of multiple realization and the problem it causes for reduction, but also

Davidson’ s anomalism. Bickle’ s discussion of the latter is interesting, but I will

bypass it here. With regard to the former, Bickle points out that his reduction

functions are relations from the models of the reducing theory into the models of the

reduced theory, and says this permits many models in the reducing theory to be

related to a single potential model within the reduced theory (p. 115) [3]. Multiple

realization is an option consistent with new wave reductionism. This at least is a

welcome result. As Bickle recognizes, multiple realization is a ubiquitous phenom-

enon within science. Chemical elements have isotopic variants, with the same

bonding properties but different atomic weights. Molecules have isomeric variants,

with the same chemical elements in the same proportionsÐ and hence the same

molecular weight and the same chemical formula Ð but different chemical properties.

Different neucleotide sequences code for the same protein in the cell. Different

enzymes can serve the same function within the cell or the organism. Such examples

are easy to multiply. An account of reduction inconsistent with multiple realization

of this sort is an account which is inadequate given actual scienti® c practice. Bickle

appropriately adjusts his model to the scienti® c reality rather than insisting on the

model in the face of a resistant reality.

The last major task Bickle sets for himself is showing the empirical plausibility

of psychoneural reduction, in new wave fashion. To do so, Bickle appeals to some

well-known and important work by Rescorla (1988) and by Kandel and Schwartz

(1982). This has been in¯ uential work, and is well regarded by neurobiologists. As

Bickle explains, current work on associative learning is cognitivist insofar as it

appeals to representations even to explain classical conditioning. Explaining some of

the patterns in learning depend on appeals to such things as what the animal

expects, anticipates, or notices. Kandel, Schwartz, and their collaborators, in turn,

have revealed the mechanisms underlying classical conditioning in the sea slug.

Aplysia exhibits a number of simple re¯ exes that can be modi® ed through condition-

ing, including a gill withdrawal re¯ ex that is a defensive reaction to noxious stimuli.

Under a variety of conditions, this re¯ ex can be enhanced. This sensitization can

also be extended to previously neutral stimuli. The basic result, for Bickle’ s pur-

poses, is that the learning curves modeled on Aplysia match the learning curves for

associative learning. That is, the ª lawsº are analogous. We now understand the

neural and molecular mechanisms behind sensitization, and these in turn conform

to the expectations of classical conditioning. Sensitization even can be explained

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

COG NITIVE SCIENCE AND NEU ROSCIENCE 305

neurophysiologically: it is dependent on an increase in the amount of neurotransmit-

ters, and, in the case of short-term sensitization, depends on closing the potassium

channels. This makes the interneurons more excitable, which increases sensitivity.

Bickle is optimistic about how far this paradigm can be extended though he admits

that it is ª an open question how much more of cognitive psychology might reduce

to neuroscienceº (p. 187). Ultimately, he opts for what he calls a ª revisionary

physicalism,º suggesting that at least some of the posits of a cognitive psychology will

have no close analogues in cognitive neuroscience, though some other properties will

be largely preserved (p. 202 ff).

Bickle’ s Psychoneural reduction is important for bringing a more realistic account

of scienti® c reduction to bear on problems in the philosophy of mind. His analysis

of reduction is carefully developed, and responsive to scienti® c work. Likewise,

when he turns to philosophy of mind, what he says again is informed by the scienti® c

work. Nonetheless, I am not wholly convinced by his ® nal solution. To begin with,

over the last two decades, there has been a good deal of work in cognitive

neuroscience that does not ® t the agenda of microreduction. Work with neural

networks need not be thought of as revealing the mechanisms underlying our mental

life, so much as providing a systematic alternative to the symbolic models which

played a central role in earlier cognitive psychology. They have been favored by

modelers in part because they allow for things such as gradual degradation and

neural plasticity. Work with neuroimaging has suggested detailed models of neural

pathways. This work is carried on at a level of abstraction much higher than the sort

of cases Bickle generally relies on. It is not clear how well they ® t the paradigm of

microreduction.

There is, of course, neurophysiological work that does lie well within the sphere

of microreduction, as Bickle illustrates. Even here, there is some reason for concern.

The Aplysia work, in particular, may not generalize as far as Bickle suggests. It is

reasonable to think that the basic mechanisms of facilitation and potentiation may

be similar across a wide range of organisms. It is problematic, at best, to hold that

there will be one mechanism underlying learning, and even less plausible that

Aplysia offers a general model of learning. Aplysia provides an excellent model for

the neurosciences. The number of neurons is small, and there is an unusual amount

of regularity in their projections. We can map the entire system in detail. These very

advantages should make us wary that Aplysia offers a good model for human

learning. As Valerie Hardcastle has emphasized in discussion, human learning, by

contrast, is exceedingly plastic and the underlying neural systems are highly

modi® able. There must be some signi® cant differences between the neural mecha-

nisms. There are even more speci® c reasons for skepticism. The set of problems that

gave rise to modern cognitivism, as Bickle acknowledges, derives from the need for

internal representations in explaining behavior. It is not just that there are internal

states mediating behavior. That has never been at issue, even among the most

devoted behaviorists. The key to modern cognitivism is the presence of composi-

tional structure in internal representations, and the role that compositional structure

has in explaining our capacities (see Fodor, 1975). Language comprehension and

use depends on syntactic rules that are structure sensitive. Intelligent cognition

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

306 ROBERT C. RICHARDSON

employs structurally complex mental representations; and cognitive processing in

turn is sensitive to these differences in the structure of these representations. It was

the recognition of the internal complexity of mental representations that gave rise to

arguments for their indispensability in explaining behavior; for example, recursive

properties of language were decisive in undercutting behaviorist psychology, and an

understanding of memory which does not acknowledge semantic organization is

inadequate. These very properties have been important, as well, in the continuing

discussions over connectionism and its adequacy as a general model of learning (see

e.g. Fodor & Pylyshyn, 1988; Pinker & Prince, 1988; Bechtel & Abrahamsen, 1991,

Chapter 7). We need not revisit those particular debates here. My point is simply

that structure sensitivity has been one of the principal features in those discussions.

In his defense of his revisionary physicalism , structure dependency plays no signi® cant

role. Bickle focuses on sentential content, and even there accepts that, ® nally,

ª ¼ there is no need to posit propositional attitudes to do any causal work in

generating cognition and behaviorº (p. 204). Bickle’ s own computational models

make no use of sentential structure, and re¯ ect neither the generative nor the

recursive nature of cognition. The Aplysia paradigm likewise relies on no structured

representations, even if it does involve internal states. Bickle’ s revisionary physical-

ism incorporates, instead, disarticulated representations, lacking internal structure.

They therefore lack suf® cient resources to deal with our cognitive capacities.

Without structured representations and without an understanding of the plasticity in

human learning, such a reductionism will not go very far in converting the convinced

cognitivist.

Acknowledgements

I am thankful to John Bickle, Peggy DesAutels, Don Gustafson, Larry Jost, and

Valerie Hardcastle for discussion of the book, the many issues it involves and for

comments on an earlier draft of this review. I am also indebted for the support of the

Taft Faculty Committee.

Notes

[1] It is also possible to explain the deviations from the Boyle± Charles law at extremes of temperature

and density, though this does not derive from the statistica l theory proper.

[2] In their response to McCauley (1996), Churchlands point out that the assumption that psycholog-

ical explanations do constitute a distinct level is itself a problematic assumption (p. 224). That

point is fair enough. It is an empirical issue, with much actually lying on McCauley’ s side. The

Churchland’ s response to McCauley and others unfortunately displays the same ambivalence over

whether their own connectionist paradigm is intended as a competitor at the same level for

cognitive (folk) psychology or is a consequence of neuroscience (see Churchland & Churchland,

1996). At some points connectionism becomes psychology and at others neuroscience. It was that

ambivalence that inspired McCauley’ s original discussion.

[3] In a passage I ® nd mystifying, Bickle says that, nonetheless, ª Merely conditional connecting

principles seem insuf® cient to serve the aim of ontological uni® cation via intertheoretic reductionº

(p. 120). In the same context, he embraces the view that reductive ª identitiesº are ª speci® c to a

domain.º Domain speci® c ª identitiesº are, properly, functions from one domain to another and can

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14

COG NITIVE SCIENCE AND NEU ROSCIENCE 307

be represented without loss as conditionals. The general point is that reduction functions need not

be one-to-one, but can be many-to-one (cf. Richardson, 1979, 1982).

References

BALZER, W., MOULINES, C.U. & SNEED, J. (1987). An architectonic for science. Dordrecht: Reidel.

BECHTEL, W. & ABRAHAMSEN, A. (1991). Connectionism and the mind. Cambridge: Basil Blackwell.

BECHTEL, W. & RICHARDSON, R.C. (1993). Discovering complexity. Princeton: Princeton University

Press.

B ICKLE, J. (1998). Psychoneural reduction: the new wave. Cambridge, MA: MIT Press.

BURIAN, R., RICHARDSON, R.C. & VAN DER STEEN, W.J. (1996). Against generality: meaning in genetics

and philosophy. Studies in History and Philosophy of Science, 27, 1± 29.

CHURCHLAND, P.M. (1979). Scienti® c realism and the plasticity of mind. Cambridge: Cambridge Univer-

sity Press.

CHURCHLAND, P.M. & CHURCHLAND, P.S. (1990). Intertheoretic reduction: a neuroscientist’ s ® eld

guide. Seminars in the Neurosciences, 2, 249± 256.

CHURCHLAND, P.M. & CHURCHLAND, P.S. (1996). Replies. In R.N. MCCAULEY (Ed.) The Churchlands

and their critics. London: Basil Blackwell.

CHURCHLAND, P.S. (1986). Neurophilosophy: toward a uni® ed theory of the mind/brain. Cambridge, MA:

MIT Press/Bradford Books.

FODOR, J.A. (1975). The language of thought. New York: Crowell.

FODOR, J.A. & PYLYSHYN, Z.W. (1988). Connectionism and cognitive architecture. In S. PINKER & J.

MEHLER (Eds) Connections and symbols. Cambridge, MA: MIT Press.

HOOKER, C.A. (1981). Towards a general theory of reduction (in three parts). Dialogue, 20, 38± 59,

201 ± 236, 496± 529.

KANDEL, E. & SCHWARTZ, J.H. (1982). Molecular biology of learning. Science, 218, 433± 442.

MCCAULEY, R.N. (1986). Intertheoretic relations and the future of psychology. Philosophy of Science, 53,

179± 199.

MCCAULEY, R.N. (1996). Explanatory pluralism and the co-evolution of theories in science. In R.N.

MCCAULEY (Ed.) The Churchlands and their critics. London: Basil Blackwell.

NAGEL, E. (1961).The structure of science. New York: Harcourt, Brace & World.

P INKER, S. & PRINCE, A. (1988). On language and connectionism: analysis of a parallel distributed

processing model of language acquisition architecture. In S. PINKER & J. MEHLER (Eds) Connections

and symbols. Cambridge, MA: MIT Press.

RESCORLA, R. (1988). Pavlovian conditioning: it’ s not what you think it is. American Psychologist, 43,

151± 160.

R ICHARDSON, R.C. (1979). Functionalism and reductionism. Philosophy of Science, 46, 533± 558.

R ICHARDSON, R.C. (1982). How not to reduce a functional psychology. Philosophy of Science, 49,

125± 137.

R ICHARDSON, R.C. (in press). Explication et causalite dans les systeÁ mes auto-organise s. In B. FELTZ, M.

CROMMELINCK & P. GOUJON (Eds) Auto-organisation et e mergences dan les sciences de la vie. Brussels:

OUSIA.

SCHAFFNER, K. (1967). Approaches to reduction. Philosophy of Science, 34, 137± 147.

W IMSATT, W.C. (1974). Reductive explanation: a functional account. In R.S. COHEN et al. (Eds) PSA

1974 . Dordrecht: Reidel.

W IMSATT, W.C. (1976). Reductionism, levels of organization, and the mind± body problem. In G.

GLOBUS, G. MAXWELL & I. SAVODNIK (Eds) Consciousness and the brain. New York: Plenum Press.

W OODWARD, J. (1989). The causal mechanical model of explanation. In P. KITCHER & W.C. SALMON

(Eds) Scienti® c explanation. Minneapolis: University of Minnesota Press.

Dow

nloa

ded

by [

Ston

y B

rook

Uni

vers

ity]

at 0

6:10

02

Nov

embe

r 20

14