Contiguity in episodic memory

Abstract

Recall of one event often evokes memories of other events that occurred nearby in time. In the laboratory, this temporal contiguity effect is observed when subjects study and then recall lists of words: the order in which they recall the words tends to be similar to the original presentation order (for early reviews, see Postman 1971Postman , 1972. Here we provide an overview of what we currently know about the contiguity effect by presenting 34 findings concerning how the effect is influenced by various factors and manipulations. seven sections: basic properties of the contiguity effect in free recall, individual and group differences, manipulations of task parameters, manipulations of stimuli, manipulations of encoding tasks, contiguity in other memory tasks, and contiguity at long time scales. Table 1 lists the 34 findings we will discuss and their original references. We conclude with an evaluation of the ability of six different memory mechanisms to account for the findings: associative chaining, short-term memory, positional coding, chunking, contextual dynamics, and control processes. Basic properties of the contiguity effect in free recallFinding 1: Temporal contiguity in free recall Kahana (1996) quantified the contiguity effect in immediate free recall by computing the probability of successively recalling items as a function of their distance from each other in the study list. After recalling an item studied in position i of the list, one can measure the probability of transitioning to next recall an item studied in position i + lag, conditional on the availability of that item for recall. This measure is called the lag conditional-response probability (lag-CRP). When the list is sufficiently long to allow for transitions at long lags, the lag-CRP decreases monotonically with |lag| ( Fig. 1a plots the lag-CRP to |lag| = 10 for 24-item lists). For shorter lists, long-lag AbstractContiguity is one of the major predictors of recall dynamics in human episodic memory. But there are many competing theories of how the memory system gives rise to contiguity. Here we provide a set of benchmark findings for which any such theory should account. These benchmarks are drawn from a review of the existing literature as well as analyses of both new and archival data. They include 34 distinct findings on how various factors including individual and group differences, task parameters, and type of stimuli influence the magnitude of the contiguity effect. We will see that contiguity is observed in a range of tasks including recognition, paired associates, and autobiographical recall and across a range of time scales including minutes, days, weeks, and years. The broad pattern of data point toward a theory in which contiguity arises from fundamental memory mechanisms that encode and search an approximately time scale invariant representation of temporal distance.

Overlap between hippocampal pre‐encoding and encoding patterns supports episodic memory

“…An additional hypothesis we examined was that with time and practice participants' performance will improve and so would the magnitude of pre‐encoding/encoding overlap. In line with this idea is the finding that the Temporal Contiguity effect increases with experience (Healey et al, ). However, we found an increase in the magnitude of pre‐encoding/encoding overlap only on the descriptive level and only for the Hippocampus.…”

“…In humans, such a clustering effect has been well-documented behaviorally (Healey, Long, & Kahana, 2018;Kahana, 1996;Kahana, 2012). Termed the Temporal Contiguity Effect, this phenomenon refers to the increased probability of sequentially recalling two items that were studied in close temporal contiguity.…”

“…Termed the Temporal Contiguity Effect, this phenomenon refers to the increased probability of sequentially recalling two items that were studied in close temporal contiguity. The effect is thought to arise from the largely overlapping temporal contexts shared by neighboring items and is a hallmark of episodic recall (Healey, 2018;Healey & Kahana, 2014;Healey, Long, & Kahana, 2018;Polyn et al, 2009). On the neural level, both memory allocation and the Temporal Context Effect have been shown to be associated with the hippocampus and adjacent structures (Folkerts, Rutishauser, & Howard, 2018;Josselyn & Frankland, 2018;Kragel, Morton, & Polyn, 2015;Manning et al, 2011;Rogerson et al, 2014).…”

Age-related differences in the temporal dynamics of spectral power during memory encoding

“…Two pairs of items from each of the four groups were arranged such that one pair occurred at adjacent serial positions and the other pair was separated by at least two other items. This semantic manipulation has been analyzed elsewhere [14] and will not be considered here as it is not relevant to our present focus and the distribution of these pairs across serial positions ensures that they are not confounded with age differences in neural dynamics. For each list, there was a 1500 ms delay before the first word appeared on the screen.…”

How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach

“…We restrict consideration to first recalls because there are a number of constraints in modeling complete sequences that require additional assumptions. Strong sequential dependencies are present in recalled sequences -a recalled item is very likely to be followed by an item studied adjacent to that item on the study list (Healey, Long, & Kahana, 2019;Kahana, 1996). Modeling sequential dependencies requires mechanisms such as using retrieved items (e.g., Raaijmakers & Shiffrin, 1981) or contexts (e.g., Howard & Kahana, 2002) as cues for subsequent recalls.…”