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Explaining the BrainReview - Explaining the Brain
Mechanisms and the Mosaic Unity of Neuroscience
by Carl F. Craver
Oxford University Press, 2007
Review by Roy Sugarman, Ph.D.
Mar 25th 2008 (Volume 12, Issue 13)

Craver applies lessons from the philosophy of science to propose a unified framework for the philosophy of neuroscience: in this, he sets out to develop a kind of neuroepistemology.  He sets the question "What is required of an adequate explanation in neuroscience" in this way.

One of his major tenets, reasonably enough, is that explanations in neuroscience describe mechanisms, span multiple levels, and integrate multiple fields, a set of descriptive claims he has set out to defend and create setpoints for.  This is his mosaic, and he sets out to integrate the mosaic.

In order to manage the brain, we have to measure it, and these two goals define neuroscience.  Manage in this case is to diagnose and treat either damage or decay in the brain and nervous system beyond. This is also a hard task, since neurology only deals with what it can see, and psychiatry only with what cannot be seen.  Both struggle with epistemological issues, which neuropsychiatry tries to address, but without a unifying philosophy.

Not only do explanations describe mechanisms, they are also multilevel, as they refer to behaviors of organisms, mostly seen elsewhere as second order homeostatic ecosystems. Drawing on neuroscience as a multi-field discipline, it is essential then to integrate multiple fields, the so-called integrative approach to neuroscience, namely bringing together what has otherwise been studied in isolation.  This could mean pooling data, or doing all of these tests in one person.  This already is a well established field, which interestingly as a philosopher, Craver has apparently never heard anything related to this, or the Journal of Integrative Neuroscience. Or at least he doesn't mention it or the authors associated with it and their hundreds of articles.

One flaw in this argument is that neuroinformatics has largely struggled as it is virtually impossible to pool data from different researchers or different machinery using different protocols: to do this, the process would have to be standardized, and integrated, and a large collaborative database developed.  In a world of neurocentrism, that is hard to do, although some have.

The model of explanation he will develop from here on takes no notice of how this has been addressed elsewhere. His criteria for an adequate account of explanation, or at least, descriptive adequacy are illuminated and provide a convincing rationale for how integrative approaches might work.

To do this integrative weaving requires that issues of causal relevance be addressed, so that understanding and misunderstanding can be distinguished from each other. He does this by using an argument drawing on an explanation of how calcium explains neurotransmitter release in turn. This discussion will lead him to plead the case for a unification model, where explanation is not a matter of deriving the explanatory phenomena from laws, but a matter of unifying disparate beliefs under a series of what is known as argument patterns. This is an ideal, perhaps realized by few, such as Newton and Darwin, and of course subject to falsification when the diverse elements, under a few unifying argument patterns, are unified. It is difficult however to see how some of the basic constraints on neuroscientific explanation can be accommodated. One way is that discovering mechanisms helps unify beliefs by relating them to underlying causal structures, something the DSM has failed in for instance, as lamented by the NIMH and other bodies reviewing the DSM V.

Causal relevance and manipulation, in the view of Woodward and others, are related in that causal relevance relations in neural mechanisms are relationships that can be used for the purposes of manipulation, and thus management.

Having discussed 5 constraints on explanations in neuroscience, he embarks on discussing the mechanism of long term potentiation to provide a view of causal relevance that accommodates the mechanistic 'fragility' and historical contingency of neuroscientific generalizations but that satisfy these constraints. In this argument, the manipulationist account readily satisfies these constraints: it does not reduce ideas of causation to something less problematic to deal with, or something that only metaphysical accounts can deal with, but it is not clear that a reductive account of causation can provide a satisfactory treatment of causal relevance. It does however add a normative component, in aiding Craver to develop a causal-mechanistic model of constitutive explanation.

This is no small task, requiring that systems theoretic traditions would have to be amended and revised, as well as provide an alternative to classical reduction, but he sets out an argument that does that. Since both systems tradition and reduction traditions share a common goal of understanding constitutive explanation, the understanding how the behaviors of a whole is explained in terms of its parts without falling into what Bateson, drawing on Whitehead and  Russell, called epistemological error: In fact, this takes Craver 56 pages.  In other terms, there is the risk of a confusion of levels of abstraction, which he deals with in a following chapter. One cannot integrate unless there are multiple levels, and in explanations in neuroscience we find many such levels, for which he now provides a 'field guide' in the next chapter.

Using spatial memory as an example, he develops a standard for keeping these levels clear of each other and prevent them getting in what Bateson called "a muddle". This is a flexible metaphor, but ambiguous, as Russell and Whitehead noted in 1926 at least, hence Craver's creation of a taxonomy to deal with it. This leads to non-fundamental explanations, and to do this he must argue against a possible metaphysical objection to the idea that explanations in neuroscience describe mechanisms at multiple levels, without confusion, at least no confusion if the taxonomy is clear. The question here is whether non-fundamental properties have real causal powers over and above the powers of fundamental properties. He sets out to show that the common arguments against higher level causes should not lead one to abandon the idea of a mosaic brain, where non-fundamental epistemologies fall through the ceiling into ontological structures, as Paul Dell suggested was inevitable, decades ago, when one begins to take objective views of self-organizing systems.  Or maybe that was von Glasersfeld or Varela?

The question to now be resolved is whether multilevel mechanistic explanations scaffold the unity of neuroscience, and can neuroscience then inform on other disciplines that rely on applied neuroscience?

He will argue in contrast to others that the unity of neuroscience is achieved as different fields integrate their research by adding constraints on multilevel mechanistic explanations. Mosaic views are thus not reductionistic, but unifying.  So for instance, if one tries to look at small numbers of research participants, one may find fMRI changes, and rely on this and the hope it can be replicated.  However let's say 20 studies attempt to replicate it, and discover they do not do so.  In contrast, 20 researchers, all using the same technology, each do both fMRI, QEEG, neuropsychological testing, DNA swabs, psychophysiological measures, heart rate variability, and do so exactly the same way using an invariate protocol, then the pooled data represents an ecosystem, a complex mosaic where the power of the system allows for a shared taxonomy, proving the argument that non-fundamental causal properties are meaningful given the chances for enhanced probability from the pooling of data.

Craver will conclude, quoting Dupre:

"Sensitivity to empirical fact, plausible background assumptions, coherence with other things we know, exposure to criticism from the widest variety of sources, and no doubt others" p 270.

Although it appears to be a dense argument, where only philosophical angels fear to tread, the concepts are not that dense, and with a little effort, one can make it through the argument for an integrative approach, overcoming the neurocentrism that currently dominates the field and has done so for years. Each researcher believes that their bit of the elephant defines the whole field, which of course relates back to Gregory Bateson and further, to epistemological error as defined more than 80 years ago.  Finally, in neuroscience, someone is working out the philosophy of integrative neuroscience, 3 decades after it began, and large databases began to appear.

© 2008 Roy Sugarman

Roy Sugarman, Ph.D., Director of Clinical and Neuropsychological Services, Brain Resource Company, Ultimo, Australia

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