How to build a brain: from function to implementation.
Abstract  To have a fully integrated understanding of neurobiological systems, we must address two fundamental questions: 1. What do brains do (what is their function)? and 2. How do brains do whatever it is that they do (how is that function implemented)? I begin by arguing that these questions a...
| Publicado en: | Synthese Vol. 159; no. 3; pp. 373 - 389 |
|---|---|
| Autor principal: | |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2007
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=27682513&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 27682513 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2007 vid: 159 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 27682513 10.1007/s11229-007-9235-0 ppf: 373 ppct: 16 formats: tig: atl: How to build a brain: from function to implementation. aug: au: Chris Eliasmith affil: University of Waterloo Department of Philosophy Waterloo ON Canada N2L 3G1 su: Neurobiology Developmental neurobiology Brain function localization Neurophysiology sug: subj: Neurobiology Developmental neurobiology Brain function localization Neurophysiology ab: Abstract  To have a fully integrated understanding of neurobiological systems, we must address two fundamental questions: 1. What do brains do (what is their function)? and 2. How do brains do whatever it is that they do (how is that function implemented)? I begin by arguing that these questions are necessarily inter-related. Thus, addressing one without consideration of an answer to the other, as is often done, is a mistake. I then describe what I take to be the best available approach to addressing both questions. Specifically, to address 2, I adopt the Neural Engineering Framework (NEF) of Eliasmith & Anderson [Neural engineering: Computation representation and dynamics in neurobiological systems. Cambridge, MA: MIT Press, 2003] which identifies implementational principles for neural models. To address 1, I suggest that adopting statistical modeling methods for perception and action will be functionally sufficient for capturing biological behavior. I show how these two answers will be mutually constraining, since the process of model selection for the statistical method in this approach can be informed by known anatomical and physiological properties of the brain, captured by the NEF. Similarly, the application of the NEF must be informed by functional hypotheses, captured by the statistical modeling approach. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2007 holdings: @attributes: islocal: N |
|---|