From cognitive to biological psychology: Psychology as an interdisciplinary approach

Authors
Citation
W. Klimesch, From cognitive to biological psychology: Psychology as an interdisciplinary approach, Z PSYCHOLOG, 209(1), 2001, pp. 17-33
Citations number
39
Categorie Soggetti
Psycology
Journal title
ZEITSCHRIFT FUR PSYCHOLOGIE
ISSN journal
00443409 → ACNP
Volume
209
Issue
1
Year of publication
2001
Pages
17 - 33
Database
ISI
SICI code
0044-3409(2001)209:1<17:FCTBPP>2.0.ZU;2-I
Abstract
The purpose of this article is to show that (i) representational assumption s play a key role for any psychological theory and that (ii) their elaborat ion leads to the foundation of an interdisciplinary psychology which is con sidered a discipline of neuroscience. The basic logic underlying this appro ach is characterized by the necessity to define representational assumption s as explicitely as possible and to evaluate their plausibility or empirica l validity whenever feasible. Thus, when pursuing the representational prob lem, it is a logical consequence to focus also on the biological basis of p sychological processes. In an attempt to demonstrate this interdisciplinary perspective, representational assumptions of memory theories are discussed as an example. An interesting phenomenon which nicely demonstrates this cl ose link between representational assumptions and neuronal processes is the unrealistic paradox of retrieval interference which can be derived from tr aditional memory models. It predicts that the more information is stored in memory, the slower it works. It can be shown, however, that the combinatio n of assumptions about interconnected codes and oscillatory activation patt erns (during processes such as encoding or retrieval) agrees well with the law of temporal and spatial summation (at dendritic synapses) and predicts (in the same way as physiological findings do) that activation processes ru n the faster the more interconnected codes are stored in memory. It is conc luded that even at a theoretical level a psychological model can be evaluat ed by findings in neuroscience, provided that representational assumptions are stated as explicitely as possible.