Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-vvkck Total loading time: 0 Render date: 2024-04-26T23:35:30.206Z Has data issue: false hasContentIssue false

3 - Neural network models in psychiatric diagnosis and symptom recognition

from Part one - General Concepts

Published online by Cambridge University Press:  12 January 2010

Dan J. Stein
Affiliation:
University of Stellenbosch, South Africa
Jacques Ludik
Affiliation:
University of Stellenbosch, South Africa
Get access

Summary

Matters historical

Psychiatric diagnosis has been conceptualized as either a ‘one-off’ (‘recognition’) type of cognitive act or as a ‘recursive (constructional) process’. History teaches us that scientists choose their models not on the basis of some ‘crucial empirical test’ (such tests do not exist at this level of abstraction) but on the more humdrum (but rarely owned up to) dictate of fashion. For example, during the eighteenth century, when the so-called ‘ontological’ notions of disease (as it was then based on the more botanico tradition) (Berg, 1956; López-Piñero, 1983), reigned supreme, there was little problem in accepting the view that the diagnosis (recognition) of disease happened at one fell (cognitive) swoop. This was because the Platonic (ontological) assumption lurking behind such a notion amply justified the belief that disease was ‘fully bounded and out there’ and, furthermore, that inklings of its existence had been planted at birth (like everything else) in the mind of the diagnostician. The a priori privileging of some features of a disease (the successful strategy that Linné had already tried on plants), and the view that such features actually ‘signified’ the disease, was just one version of the ontological approach. Indeed, a century earlier, a similar view had governed the study of linguistics (Aarsleff, 1982). That it was fashion and Zeitgeist that sustained the popularity of the ontological view is illustrated by the fact that a rival approach put forward at the time by Adanson was given short shrift (Stevens, 1984).

Type
Chapter
Information
Neural Networks and Psychopathology
Connectionist Models in Practice and Research
, pp. 34 - 56
Publisher: Cambridge University Press
Print publication year: 1998

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×