Converging measures of workload capacity

Parallel interactive retrieval of item and associative information from event memory

“…To address these issues and answer this outstanding question, we augment our SFT analysis by jointly modeling accuracy and response time for each individual within a Linear Ballistic Accumulator (LBA) framework (Brown & Heathcote, 2008). LBA models have been useful for corroborating conclusions derived from SFT (Eidels et al, 2010;Donkin et al, 2014) and have the advantage of jointly modeling both accuracy and response time for both correct and error responses 5 . In addition, the LBA modeling framework allows a natural way to express each of the seven possible parallel retrieval architectures 6 and to separately estimate the contributions of interactions prior to retrieval versus those during retrieval.…”

Workload capacity spaces: A unified methodology for response time measures of efficiency as workload is varied

“…Fitting parametric models to data can provide estimates, rather than assumptions, about such parameters and whether they vary with workload. In a recent study, Eidels, Donkin, Brown, and Heathcote (2010a) have analyzed data from a redundant-target OR task by using the nonparametric C OR (t) measure, as well as by fitting the linear ballistic accumulator model (Brown & Heathcote, 2008). They found close agreement between the techniques and, in particular, discovered that the efficiency of processing across load conditions (single vs. double target) was driven by channels' accumulation rates, and not by other parameters such as base time.…”

“…Indeed, Eidels et al (2010a) estimated for the group of participants above a lower threshold value for yes trials, as compared with no trials, presumably because, in the standard OR design, 75% of the trials require a positive response. However, in the OR task, this difference cannot contaminate C OR (t) estimates, since the index is calculated only on the basis of yes trials.…”

Numerical predictions for serial, parallel, and coactive logical rule-based models of categorization response time

“…In addition, nonparametric measures of capacity and parallel interaction have been shown to correspond closely to the drift rate in parametric sequential-sampling models such as the single-channel models described here (Eidels et al, 2010). Future work will be needed to derive predictions for more complicated parametric parallel models in order to capture the processes underlying facilitatory and inhibitory interactions in categorization.…”

“…In sum, the benefits include the ease with which the models can be tested, extensibility, neural plausibility, and a relation to previously published work; however, the parametric approach taken here should be viewed as complementary to the nonparametric approach. In fact, the two approaches can provide converging evidence regarding the underlying cognitive architecture (Eidels, Donkin, Brown, & Heathcote, 2010).…”