An Associative Model of Rat Serial Pattern Learning in Three-Element Sequences

Abstract

Hypotheses ranging from subsymbolic to symbolic have been proposed to account for rat sequential behaviour, and in the subsymbolic domain alone there are multiple proposed subsymbolic processes or factors thought to affect serial behaviour. A behavioural study and computer simulations were conducted to evaluate these hypotheses, and a new computational associative model based on pairwise associations and generalization was evaluated. Seven 3-element sequences were selected for study that systematically (1) varied sequence discriminability, (2) varied reward magnitude, and (3) manipulated the order of food quantities. Neither element discriminability nor response enhancement subsymbolic processes in isolation were able to account for the behavioural data; however, simulations from the computational model known as the sequential pairwise associative memory (SPAM) model with a log-linear mapping of stimulus dimension items to food quantities correlated well with the behavioural data. SPAM accounts for differential element anticipation in different sequences by appealing to pairwise association of sequence events and generalization between cues as the principal factors mediating pattern tracking in three-element sequences.

Associative sequence learning in humans.

“…This leads us to conclude that the match between experimental and simulation results is a good one, particularly as the simulations were conducted before the experiments. Less powerful associative models of sequence learning (e.g., associative chaining in a Jordan net; Jordan, 1986) or Wallace and Fountain's (2002, 2003) sequential pairwise associative memory model cannot easily accommodate our findings. They have difficulty solving the basic problem, as a chaining explanation cannot easily deal with nonpredictive elements within a sequence (the Cs), and this difficulty is exacerbated if there are variable numbers of such elements in the sequences to be learned.…”

“…In this article, we have two main aims: to present evidence that establishes that humans are able to learn sequences in an associatively based fashion, with the proviso that this probably requires a model that goes beyond what even sophisticated versions of associative chaining theory (e.g., Wallace & Fountain, 2002, 2003) are capable of. We argue that variants on Elman's (1990) simple recurrent network (SRN) are suitable for this task and present simulation results using the basic SRN in support of this claim.…”

Concurrent cognitive processes in rat serial pattern learning: II. Discrimination learning, rule learning, chunk length, and multiple-item memories

“…However, Hunter found that if rats were provided an additional differentiating cue that uniquely predicted the outcome on the next trial, then they could easily master double alternation or even more complex sequential problems. This outcome foreshadowed later work on sequential learning as depending on discrimination learning mechanisms by Hull (1931), Skinner (1934), and Capaldi and colleagues, who proposed that sequential learning depended on "multiple-item memory" (Capaldi, Blitzer, & Molina, 1979;Wallace & Fountain, 2002, 2003.…”

Blocking in rat serial pattern learning.

“…The result is, to our knowledge, the first demonstration of the blocking phenomenon in serial pattern learning. It should be noted that Capaldi and colleagues have demonstrated overshadowing in food quantity serial pattern learning (Capaldi, Birmingham, & Miller, 1999; Capaldi, Verry, Nawrocki, & Miller, 1984) in a paradigm that lends itself to associative analysis and mathematical models based exclusively on interitem associations (Wallace & Fountain, 2002, 2003). However, associative analysis and the latter mathematical model have so far failed to account for rats’ behavior in the serial multiple-choice paradigm used in the present study.…”

“…Thus, our results in the present study, like those of Capaldi and colleagues, speak to the generality and explanatory power of associative learning principles and reinforce the idea that we should be careful not to discount associative explanations of even putatively complex behavior (cf. Wallace & Fountain, 2002, 2003).…”