Sverker Sikström

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TECO

I BOKEN "TECO A Connectionist Model for Dependency in Successive Episodic Tests" av Sverker Sikström utforskas sambandet mellan erkännande och ledtrådsminne inom kognitiv psykologi. Genom att analysera data från ett stort antal experimentella förhållanden, belyser författaren hur dessa minnesprocesser är relaterade och under vilka omständigheter avvikelser kan uppstå.

• TECO-teorin förklarar beroendet mellan erkännande och ledtrådsminne.

• Boken presenterar fyra studier som testar TECO:s hypoteser.

• En neural nätverksmodell simulerar TECO-teorin med empiriska data.

I den första studien introduceras TECO-teorin, som står för Target, Event, Cue & Object, och förklarar hur olika typer av ledtrådar påverkar minnesåterkallande. Sikström argumenterar för att beroendet mellan erkännande och ledtrådsminne kan mätas kvantitativt och att detta beroende varierar beroende på vilken typ av ledtråd som används.

Den andra studien testar TECO:s förutsägelser i olika minnestester, vilket ger insikter om hur minnet fungerar i praktiken. I den tredje studien diskuteras fenomenet erkännandefel och dess matematiska begränsningar, vilket ger en djupare förståelse för de psykologiska processer som ligger bakom dessa misslyckanden.

Avslutningsvis simuleras TECO-teorin i en Hopfield-typ neural nätverksmodell i den fjärde studien, vilket visar på en rimlig överensstämmelse med empiriska data. Genom att kombinera teoretiska analyser med praktiska simuleringar bidrar boken till en ökad förståelse av minnesfunktioner och deras komplexitet inom kognitiv psykologi. "TECO" är därmed en betydelsefull resurs för forskare och studenter inom området.

Data from a large number of experimental conditions in published studies have shown that recognition and cued recall exhibit a moderate dependency described by the Tulving-Wiseman function. Exceptions from this lawfulness, in the form of higher dependency, are found when the recall test lacks effective cues (i.e., free recall exceptions) or when the recognition test is cued (i.e., cued recognition exceptions). In Study I, the TECO (Target, Event, Cue & Object) theory for dependency in successive tests, is proposed to account for the dependence between recognition and cued recall through the fact that both tests are cued with the instruction to retrieve from the learning episode (i.e., the event).

Independence is accounted by differences in cueing; the recall test is cued by a contextual cue, whereas the recognition test is cued by the target. A quantitative degree of dependence, measured by ẞ, is predicted to be one-third by counting the number of shared cues divided by the total number of cues. Free recall exceptions are predicted to reveal a dependency of one-half because the recall test lacks effective cues. Cued recognition exceptions are predicted to reveal a dependency of two-thirds because both tests are cued with the cue word. A function is derived to predict the conditional probabilities and the results show a reasonable fit with the predictions. In, Study II, the predictions of TECO on successive tests of cued recall and cued recognition, free recall and cued recall, recognition and cued recognition is tested. A database is presented for successive episodic tests. In, Study III the lawfulness of recognition failure is discussed. Hintzman claimed that the conditional probability of recognition given recall is constrained by the P(Rn)/P(Rc) boundary and that the phenomenon of recognition failure is, thus, a mathematical artefact. It is argued that this boundary is due to a psychological process and that this bounddary carries important information regarding the underlying system. Furthermore, half of the deviation from the predictive function of recognition given cued recall is shown to arise from the lack of statistical power. In Study IV, TECO is simulated in a neural network of a Hopfield type. A Theoretical analysis is proposed and nine sets of simulations are conducted. The results show that the theory can be simulated with reasonable agreement to empirical data.