Interresponse times in serial recall: Effects of intraserial repetition.

Abstract

The authors examined the effects of intraserial repetition on multitrial serial learning of random consonant lists, analyzing both learning rates and perfect trial inten-esponse times (IRTs). Lists varied along 3 dimensions: list length, presence or absence of a repeated element, and lag between repeated elements. After achieving a forward-recall criterion on a given list, participants (N = 20) attempted backward recall. At small lags, IRTs between the repeated elements were very short (compared with IRTs from identical positions in nonrepetition lists). At larger lags, the IRT to recall the second repeated item was substantially longer than in control lists. These results reveal a latency analogue of the Ranschburg pattern seen in accuracy data. A Ranschburg pattern was also found in participants' learning rates. These results both generalize the Ranschburg phenomenon and present further challenges to theories of serial order memory.

Time and cognitive load in working memory.

“…The authors observed a significant reduction of memory span under the combined-tasks condition (from 4.75 to 3, approximately), but 2 It could be argued that presenting the memory items for 1,500 ms or the stimuli to be processed for 1 s or more, as we did here, does not allow one to consider that time was controlled. It is true that items to be recalled are usually presented for 1,000 ms (Conlin & Gathercole, 2006;Kahana & Jacobs, 2000;Oberauer et al, 2004;Rosen & Engle, 1997;Shah & Miyake, 1996), but it should be remembered that this duration is generally used for convenience and out of habit rather than being theoretically grounded. Longer presentations are not rare (1,250 ms in Hale, Myerson, Rhee, Weiss, & Abrams, 1996; 1,500 ms in Miyake, Friedman, Rettinger, Shah, & Hegarty, 2001; 2,000 ms in Duff & Logie, 2001).…”

Decomposing serial learning: What is missing from the learning curve?

“…Furthermore, to facilitate comparison of these two studies, we included trials only through the first perfect recall, rather than through all three consecutive perfect recalls, in our analyses of Kahana and Jacobs (2000). For Kahana and Jacobs's study (recall of consonants), the mean number of trials to learn the list was three, whereas the mean number for Kahana and Caplan's (2002) study (recall of words) was five.…”

“…In plotting the learning curves for recall of consonants (Kahana & Jacobs, 2000) and recall of words (Kahana & Caplan, 2002), we compared three scoring methods: strict positional scoring, relative order scoring, and lenient (item) scoring (Drewnowski & Murdock, 1980). Strict positional scoring counts a recalled list item as correct only if it is in the correct serial position.…”

“…In the first study (Kahana & Jacobs, 2000), participants learned lists of 11, 12, and 13 consonants for an immediate serial recall test using the study-test method (lists were learned to a criterion of three consecutive perfect recalls, although only trials through the first perfect recall will be analyzed here). Consonants were displayed individually on the screen for 1 sec, followed by a 250-msec blank interstimulus interval.…”

Laminar cortical dynamics of cognitive and motor working memory, sequence learning and performance: Toward a unified theory of how the cerebral cortex works.

“…This class of models, of which the LIST PARSE model is an example, has the advantages of being able to naturally account for certain data sets (e.g., response latency data; for a review: Farrell & Lewandowsky, 2004) that other models are incapable of accommodating, being conceptually simple, capable of self-organizing in a neural network context, and enjoying straight-forward biological interpretations. However, these models tend to (a) lack full treatments of item repetition phenomena (e.g., the Ranschburg effect, in which repeated items separated by more than one item are less likely to be recalled than distinct items, whereas less separation increases probability of recall, reviewed in Jacobs, 2000, andHenson, 1998a;however, see Bradski et al, 1994 for a partial treatment of repetition), and (b) fail to handle some of the positional error data for which other (positional) models have more ready explanations (e.g., the ability of Burgess & Hitch (1999) and Henson (1998b) to treat positional item interchanges across trials or temporal groupings). The limitations in (b) suggest that direct positional information of some sort may indeed be used in the coding of temporal order in the brain.…”