Applying an exemplar model to the serial reaction-time task: Anticipating from experience

Abstract

We present a serial reaction time (SRT) task in which participants identified the location of a target by pressing a key mapped to the location. The location of successive targets was determined by the rules of a grammar, and we varied the redundancy of the grammar. Increasing both practice and the redundancy of the grammar reduced response time, but the participants were unable to describe the grammar. Such results are usually discussed as examples of implicit learning. Instead, we treat performance in terms of retrieval from a multitrace memory. In our account, after each trial, participants store a trace comprising the current stimulus, the response associated with it, and the context provided by the immediately preceding response. When a target is presented, it is used as a prompt to retrieve the response mapped to it. As participants practise the task, the redundancy of the series helps point to the correct response and, thereby, speeds retrieval of the response. The model captured performance in the experiment and in classic SRT studies from the literature. Its success shows that the SRT task can be understood in terms of retrieval from memory without implying implicit learning.

An Instance Theory of Semantic Memory

“…More generally, our demonstration shows that an established and classic theory for memory that has previously been applied to understand a suite of behaviors including (a) recognition memory (Hintzman 1984), (b) frequency judgment (Hintzman 1988), (c) cued recall (Hintzman 1986), (d) classification (Hintzman 1986), (e) function learning (Kwantes and Neal 2006), (f) judgment and decision (Dougherty et al 1999;Thomas et al 2008), (g) speech normalization (Goldinger 1998), (h) confidence/accuracy inversions in eyewitness identification (Clark 1997), (i) language processing (Rosch and Mervis 1975), (j) false memory (Arndt and Hirshman 1998), (k) memory dissociations in aging (Benjamin 2010), (l) implicit learning (Jamieson and Mewhort 2009a, 2010, (m) speeded choice (Jamieson and Mewhort 2009b), (n) associative learning (Jamieson et al 2010b, (o) the production effect in recognition memory (Jamieson et al 2016a), and (p) selective memory impairment in amnesia (Jamieson et al 2010a;Curtis and Jamieson 2018) can also be used to understand semantics. The cross-lab and cross-domain effort represents the way that science ought to progress-by developing a general account of memory and its processes in a working computational system to produce a common explanation of behavior rather than a set of labspecific and domain-specific theories for different behaviors (Newell 1973).…”

Episodic contributions to sequential control: Learning from a typist's touch.

“…In particular, the role of exemplar-based memory processes in sequence learning has been thoroughly documented in the context of artificial grammar learning (for a review, see Neal & Hesketh, 1997), and has been suggested in the context of the serial reaction time (SRT) paradigm (Stadler, 1992(Stadler, , 1993(Stadler, , 1995. More recently, computational accounts of the exemplar approach have been proposed both in the domain of artificial grammar learning (Jamieson & Mewhort, 2009a), and in the SRT domain (Jamieson & Mewhort, 2009b). Our findings fall in line with this previous work, and we assume that the processing principles described to account for sequence learning in terms of exemplar-based memory processes would also apply to the domain of typing.…”

An instance theory of associative learning

“…Minerva 2 is an instance theory of human memory for explaining episodic recognition and judgment of frequency. The theory has since been applied to a wide range of memory phenomena (e.g., Arndt & Hirshman, 1998;Benjamin, 2010;Clark, 1997;Dougherty, Gettys, & Ogden, 1999;Goldinger, 1998;Hicks & Starns, 2006;Jamieson, Holmes & Mewhort 2010;Jamieson, Hannah & Crump 2010;Jamieson & Mewhort, 2009a, 2009b, 2010Kwantes, 2005;Kwantes & Mewhort, 1999;Kwantes & Neal, 2006;Thomas, Dougherty, Sprenger, & Harbison, 2008).Informally, Minerva 2 is a theoretic framework that describes the memorial processes involved in representing, storing, and retrieving instances of experience. The model assumes that each experience is stored in memory as a unique trace (i.e., an instance).…”