When one begins learning a set of associations in a new domain, the associations do not exist in a vacuum but rather affect each other in various ways. Consider the example that a novice bartender learns that a ‘martini’ is made with dry vermouth and later that a ‘Manhattan’ is made with sweet vermouth. In this case, previously learning about the martini could affect memory for the Manhattan by diminishing it (proactive interference [PI]) or improving it (proactive facilitation [PF]).

Here, we ask whether this outcome can be predicted by the semantic relatedness between the learning events. In so doing, we re-visit a classic proposal by Osgood, 1949 that has been elaborated upon in the intervening decades (Bugelski and Cadwallader, 1956; Eich, 1982; Mensink and Raaijmakers, 1988) that memory changes critically depend on the relatedness between events. A recent paper of ours (Antony et al., 2022b) showed that later learning affected memory for prior events (i.e. retroactively) based on relatedness. The current paper can be considered a twin companion of that prior effort, in that we are keeping the same subject population, stimuli, experimental procedure, and timing, and we vary only the order of list learning to focus on proactive, rather than retroactive, effects. Additionally, we mirror that paper’s formatting and figures to ease comparisons among the studies, and we directly compare some data between the studies.

There are theoretical reasons to support directly opposing outcomes for how semantic relatedness with previously learned stimuli proactively affects new episodic memories (Brunmair and Richter, 2019). That is, relatedness could interfere with the new memory, promoting PI, or it could cause one to recall the prior memory and link it with the new one, which may make the new memory more resistant to forgetting and promote PF. In favor of the PI account, the presence of multiple targets for one cue could benefit from more mental separation among the targets (Underwood, 1969). In fact, increasing relatedness in some paradigms can increase interference (Bower et al., 1994; McGeoch and McDonald, 1931; McGeoch and McGeoch, 1937) and/or intrusions (Dallett, 1962; Dallett, 1964; Osgood, 1946; Postman, 1961; Underwood, 1951), and intrusions have been shown to increase specifically with similarity in proactive paradigms (Young, 1955). Conversely, in favor of the PF account, we consider two main related theories. The first is the importance of ‘remindings’ in memory, which involve reinstating representations from an earlier study phase during later learning (Hintzman, 2011). This idea centers study-phase retrieval, which involves being able to mentally recall prior information and is usually applied to exact repetitions of the same material (Benjamin and Tullis, 2010; Hintzman et al., 1975; Siegel and Kahana, 2014; Thios and D’Agostino, 1976; Zou et al., 2023). However, remindings can occur upon the presentation of related (but not identical) material and can result in better memory for both prior and new information when memory for the linked events becomes more interdependent (Hintzman, 2011; Hintzman et al., 1975; McKinley et al., 2019; McKinley and Benjamin, 2020; Schlichting and Preston, 2017; Tullis et al., 2014; Wahlheim and Zacks, 2019). The second is the memory-for-change framework, which builds upon these ideas and argues that humans often retrieve prior experiences during new learning, either spontaneously by noticing changes from what was learned previously or by instruction (Jacoby et al., 2015; Jacoby and Wahlheim, 2013). The key advance of this framework is that recollecting changes is necessary for PF, whereas PI occurs without recollection. This framework has been applied to paradigms including stimulus changes, including common paired associate paradigms (e.g. A-B, A-D) that we cover extensively later. Because humans may be more likely to notice and recall prior information when it is more related to new information, these two accounts would predict that semantic relatedness instead promotes successful remindings, which would create PF and interdependence among the traces.

One popular method for testing these accounts is to use paired associated learning paradigms in which original associations (A-B) change on a later presentation (A-D; Barnes and Underwood, 1959; Briggs, 1954). Here, we refer to this A-B, A-D paradigm as ΔTarget learning. Under conditions of no semantic relatedness between the B and D targets, ΔTarget learning typically causes PI in the form of impaired A-D memory relative to a control condition, likely because B and D compete at retrieval (Anderson and Neely, 1996; Bower et al., 1994; Caplan et al., 2014; Castro et al., 2002; Jung, 1962; Jung, 1967; Postman, 1962; Postman and Underwood, 1973; Twedt and Underwood, 1959; Young, 1955). However, as the semantic relationship between B and D increases, PI decreases and, in some cases, PF occurs (Bruce, 1933; Dallett, 1964; Martin and Dean, 1964; Mehler and Miller, 1964; Metcalfe et al., 1993; Morgan and Underwood, 1950; Osgood, 1946; Russell and Storms, 1955; although see Mills, 1973 for one case in which PI increases) An important early result using ΔTarget learning showed PF only when participants performed a mental linking strategy, in which they thought back to and integrated the prior and new pairs (Martin and Dean, 1964). Collectively, these findings indicate that prior learning can improve or impair memory for more recent information based on how people notice and consider relationships to prior information during new learning.

Over the last decade, several studies have rigorously addressed this issue by asking participants during new learning if they notice changes in new stimuli relative to existing memories, and if they can recall the existing memories. On later memory tests of the updated associations, participants are also asked to indicate if they recollect earlier changes. These studies consistently showed that noticing and recollecting changes are associated with enhanced memory for new associations (for a review, see Wahlheim et al., 2021). Largely, these proactive benefits parallel those in the retroactive direction – that is, increased similarity between B and D also reduces retroactive interference (RI) or causes retroactive facilitation (RF; Antony et al., 2022b; Barnes and Underwood, 1959; Dallett, 1962; Kanungo, 1967; Osgood, 1946; Young, 1955); we review the similarities and differences between proactive and retroactive operations more extensively below. In sum, proactive benefits of relatedness suggest that higher semantic relatedness may result in A-B and A-D becoming integrated (Wahlheim, 2014), perhaps by promoting the extent to which changed associations trigger remindings of existing memories with both shared and unique features.

An association can be modified in ways other than changing the target. Indeed, in Osgood’s proposal and in our prior paper (Antony et al., 2022b), we investigated how numerous associational changes affected original memories. Under A-B, C-B learning conditions, which we call ΔCue learning, C-B memory relative to memory for unrelated stimuli (e.g. C-D) tends to be similar (recall condition of Postman et al., 1969; Traxler, 1973) or slightly worse (Amundson et al., 2003; Postman et al., 1969; Twedt and Underwood, 1959; see Amundson et al., 2003 for a similar finding in rodents). Nevertheless, new learning of C-B associations can occur more quickly with ΔCue learning (Mandler and Heinemann, 1956), and it appears at least possible that under certain conditions, C-B could also show proactive facilitation in subsequent memory, perhaps by making B responses more accessible (Estes, 1979; Martin, 1965). When instead investigating retroactive effects of ΔCue learning, studies have found little-to-no RI when A and C are unrelated (Houston, 1966; Keppel and Underwood, 1962; Twedt and Underwood, 1959) and even RF when A and C are semantically related (Antony et al., 2022b; Bugelski and Cadwallader, 1956; Hamilton, 1943).

Finally, when learning associations with completely new cues and targets (typically called A-B, C-D learning, but which we call ΔBoth learning), the C-D memory is generally regarded as distinct from A-B. In the retroactive direction, when A is related to C and B related to D, RI has been observed when testing memory after a few minutes (Baddeley and Dale, 1966; Bugelski and Cadwallader, 1956; McGeoch and McGeoch, 1937; Saltz and Hamilton, 1967). However, when both relationships are very strong (e.g. learning beer-late followed by keg-tardy) and a longer delay is used, we previously showed reliable RF (Antony et al., 2022b). These latter results also accord with the idea that, with high similarity between both items of the pair, participants may think back and recollect prior associations, which aids their long-term maintenance. However, no studies to our knowledge have used ΔBoth learning with varying relationships between earlier and recent word pairs and tests of proactive effects of memory, as we do here.

To visualize this complicated collection of effects, Osgood proposed a three-dimensional surface by which old and new associations may interact to influence memory (Eich, 1982; Mensink and Raaijmakers, 1988; Figure 1A). Briefly, one can summarize Osgood’s argument by carefully considering three continuous relationships between cues and targets. With a constant cue, one can draw a ΔTarget line from an unrelated to an identical target (i.e. from A-B, A-D to A-B, A-B). Somewhere along this line, PI should shift to PF. Next, with a constant target starting from the A-B, A-D point (i.e. from A-B, A-D to A-B, C-D), PI should disappear as the pair becomes a wholly new association. Finally, with a constant target starting from the A-B, A-B point towards A-B, C-B (the ΔCue line), Osgood posited that PI generally did not occur. Therefore, proactive effects went from no memory change at the A-B, C-B point to maximum PF at identity. Osgood also speculated how a full surface spanning all cue-target relatedness values would influence later memory (Figure 1A), although it was based on scant data.

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Osgood largely considered proactive and retroactive effects of memory to be identical (or considered the data too insufficient to assert otherwise) – that is, he used the same surface to describe both effects. Nevertheless, there may be differences between them. First, if remindings retroactively benefit existing memories by evoking rehearsals (Antony et al., 2017; Roediger and Karpicke, 2006; Rowland, 2014) and promoting associations across episodes, then the conditions that promote remindings (such as strong relatedness or instructions to think back) could benefit existing memories more than new ones. That is, the additional retrieval trial would only occur for old, and not new, associations. Conversely, if the sole mechanism behind these benefits were the interdependence across episodes, then proactive and retroactive effects may be equal. Second, by virtue of being learned second and subject to possible fatigue or prior learning effects (Postman and Keppel, 1977; Tulving and Watkins, 1974; Underwood, 1957), newer associations may be more susceptible to interference than old associations when probed after a delay (but see Melton and von Lackum, 1941 and Szpunar et al., 2008 for how this interference is mitigated by intermittent testing, which we use here). If it were the case that interference occurred more strongly for the second-learned list, we would expect worse memory for even the ΔBoth or Control pairs in the proactive case than in the retroactive case.

In our prior paper, we examined how the full space of Osgood’s predictions resulted in RI versus RF by systematically varying the semantic relatedness of cues, targets, or both. We did this using global vector similarity (GloVe; Pennington et al., 2014), a distributional semantic model, and associative strength (AS), collected using free association norms (Nelson et al., 2004), to obtain quasi-continuous measures of relatedness. We also obtained a large dataset (N=1000 across experiments) so that we could sample each point in the space under two different memory delays and two different average levels of relatedness. Here, we will use a nearly identical approach with a similar dataset to instead investigate proactive memory effects (N=800 across the first four experiments and N=200 for a final experiment performed for the purposes of comparing retroactive and proactive effects; Figure 1B).

Briefly, subjects initially learned 36 unrelated word pairs, which we will call supplemental pairs (Figure 1C). We call the first learned list supplemental pairs because they are less important to our aims – our primary memories of interest were the base pairs, which were learned afterwards. Supplemental pairs belonged to four of the five within-participant conditions: pairs in the No Δ condition were the same as later-learned base pairs (e.g. sick-push), whereas other pairs belonged to the ΔTarget (e.g. sick-shove), ΔCue (e.g. ill-push), or ΔBoth (e.g. ill-shove) conditions. Next, subjects learned 45 base pairs (e.g. sick-push), which also included pairs from a fifth (Control) condition that had no relationship to any supplemental pairs. In both blocks of learning, subjects learned each pair until they could correctly retrieve it once, after which it dropped out. Across every five subjects, pair assignments were counterbalanced, such that the same base pairs rotated among the five conditions (Figure 1D).

Across the first four experiments, we manipulated two factors: range of relatedness among the pairs and retention interval before the final test. The narrower range of relatedness used direct AS between pairs using free association norms, such that all pairs had between 0.03 and 0.96 association strength. Although this encompasses what appears to be a full range of relatedness values, pairs with even low AS are still related in the context of all possible associations (e.g. pious-holy has AS = 0.03 but would generally be considered related; Figure 1B). The stimuli using a wider range of relatedness spanned the full range of global vector similarity (Pennington et al., 2014) that included many associations that would truly be considered unrelated (Figure 1—figure supplement 1A). One can see the range of the wider relatedness values in Figure 1—figure supplement 1B and comparisons between narrower and wider relatedness values in Figure 1—figure supplement 1C. Numerous studies have shown that delays affect the extent of interference versus facilitation in retroactive and proactive designs (Antony et al., 2022b; Antony and Bennion, 2022a; Baran et al., 2010; Chan, 2009; Liu and Ranganath, 2019; Lustig et al., 2004; Ortega et al., 2015; Wahlheim et al., 2024; Wixted, 2004). Intriguingly, RI tends to decrease over time (Antony et al., 2022b; Antony and Bennion, 2022a; Baran et al., 2010; Chan, 2009; Liu and Ranganath, 2019; Lustig et al., 2004; Ortega et al., 2015; Wixted, 2004), whereas PI tends to grow over time via increased intrusions and/or worse memory (Greenberg and Underwood, 1950; Mensink and Raaijmakers, 1988; Postman et al., 1969; Underwood, 1948; Underwood, 1949). We therefore employed two different delays of 5 min and 48 hr to assess how PI versus PF would change over time with varying levels of semantic relatedness (Figure 1E).

Overall, we predicted that relatedness would accelerate learning, benefit later memory, and increase interdependence of linked pairs across lists. Our first analyses focused on overall memory performance, based on proportion of words recalled, across each of five conditions. Following this, we asked whether this changed as a function of semantic relatedness along the respective dimension of each condition (e.g. B-D similarity in the ΔTarget condition) and found the relative memorability of each base pair across subjects by comparing memory for that condition against the Control condition. This allowed us to eliminate the incidental memorability of each individual base pair and focus on how each condition and level of relatedness affected memory. We later visualized these effects as Osgood’s proposed surface by plotting the No Δ condition at the cue and target identity point, the ΔTarget condition as a line of values at cue identity spanning target relatedness, the ΔCue condition as a line of values at target identity spanning cue relatedness, and the ΔBoth condition as a surface spanning bivariate cue and target relatedness (see Figure 1A for the full Osgood surface; see Figure 1B for a visualization from the narrower stimulus set and Figure 1—figure supplement 1 from the wider set). Later, we examined the speed of learning (based on the number of rounds to reach the criterion of one correct recall per trial) across conditions and levels of relatedness. Finally, we conducted a set of analyses comparing our proactive results from this paper to the retroactive results in our prior paper (Antony et al., 2022b). While these results diverge from convention in that they compare groups that were not randomly assigned, they do involve the same stimuli, experimental procedure, timing, and subject population, and we use our control conditions to further adjust for any meaningful differences between the studies (other than learning order). We believe that these similarities make these comparisons suggestive of important differences between proactive and retroactive effects, and we include appropriate caveats to avoid exceptionally strong conclusions. Additionally, to assess whether all retroactive versus proactive differences could be attributed to the fact that we measured memory for the second-learned (base pair) list first at the final test, we ran a control experiment in which base pairs were learned first and supplemental pairs second (i.e. the design from our prior paper) while testing the supplemental pairs first. We then compared this condition to the same learning condition from our prior paper that tested the lists in the original order.

We found that, as old and new information became more semantically related, memory for new information increased and the two grew more interdependent. When considering overall memory across experimental conditions, an overall high level of relatedness between old and new information (as in the narrower stimulus set) resulted in profound long-term PF for the ΔCue, ΔTarget, and ΔBoth conditions relative to the Control condition. When the overall level of relatedness was lower (in the wider stimulus set), we found classic PI effects in the ΔTarget condition in the 5 min delay experiment. Additionally, in the 48 hr delay experiment, the overall memory benefits were smaller (ΔCue condition) or eliminated (ΔTarget condition), but we found an intriguing pattern by which PI occurred with low relatedness and PF with high relatedness in both the ΔCue and ΔTarget conditions. We did not find relatedness correlations with memorability in the ΔBoth condition of any experiment. Additionally, we found benefits of relatedness on interdependence in all experimental conditions of all 48 hr delay experiments but weaker or less reliable effects in 5 min delay experiments.

These results converged strongly with those from our prior study (Antony et al., 2022b) focusing on retroactive memory effects. In both studies, we found overall benefits of each experimental condition in the narrower stimulus set, 48 hr delay experiment. In both studies, we found correlations between relatedness and memorability in the ΔCue and ΔTarget conditions in the wider stimulus set, 48 hr delay experiment, though this was less reliable in the ΔCue condition of the prior study. In fact, in the prior study, you could directly see how delay and relatedness combined to determine retroactive facilitation versus interference. In the ΔTarget condition of the wider stimulus set experiments, retroactive effects went from interference with low relatedness to no interference with high relatedness in the 5 min experiment to no interference with low relatedness to facilitation with high relatedness in the 48 hr experiment. Here, we found this crossover from PI with low relatedness and PF with high relatedness in the same experiment. Therefore, in both studies, the only condition showing overall RI and PI was in the wider stimulus set, 5 min delay condition, supporting the idea that RI and PI are relatively limited to these cases. Thus, the tendency to study memory with short delays and without interrelationships among study material led to the predominance of this idea in interference studies and theories throughout the 20th century. Additionally, in both studies, we also found correlations between relatedness and interdependence in all experimental conditions in the narrower stimulus set, 48 hr delay experiment and the ΔCue and ΔTarget conditions of the wider stimulus set, 48 hr delay experiments. This finding also supports recent studies showing that interdependence increases with contextual similarity between episodes (Cox et al., 2021; Yu et al., 2023), which may also be more likely to become integrated during encoding.

There were also some differences between the studies. Here, we found an unexpected null relationship between relatedness and memorability in the ΔTarget condition of the 48 hr, narrower stimulus set condition that was significant in the prior experiment. Notably, this was not simply a function of the direction of the associative strength (AS) measure, because flipping around the direction of AS from supplemental target → base target to base target → supplemental target also produced non-significant results. We note that there’s an overall ΔTarget benefit in this condition, and the y-intercept of Figure 3A, top right, is significantly above zero, reflecting memorability benefits even with 0 AS. However, the precise level of relatedness was not predictive of memorability benefits. We also found a weaker effect in the ΔBoth condition of the narrower stimulus set, 48 hr delay experiment, such that additive cue +target relatedness did not produce significant memorability benefits (although it still predicted interdependence). Critically, we also found overall differences when directly comparing memory in the otherwise identical retroactive and proactive designs. These comparisons consistently resulted in larger retroactive than proactive memory benefits in each of the experiments showing overall memory facilitation (ΔCue, ΔTarget, and ΔBoth in the narrower stimulus set; ΔCue and ΔTarget in the wider stimulus set). With the caveat that these comparisons do not use random assignment, these highly consistent results support the idea that, while remindings produce benefits for both old and new information, they disproportionally benefit old information, likely due to the additional retrieval trial (Carpenter et al., 2008; Gates, 1917; Roediger and Karpicke, 2006; Rowland, 2014).

We will now offer a cumulative explanation of our results, starting with key points about the recursive remindings hypothesis (Hintzman, 2011). A series of studies using paired associate learning tasks akin to those here have shown that encouraging subjects to recall existing memories during new learning can reduce PI and promote PF, depending on how well the information is integrated and later recollected (for a review, see Wahlheim et al., 2021). In these cases, subjects must both notice and subsequently recollect a change between prior and new information to gain these benefits. Similar findings have been observed when using measures of recollecting change at test to infer noticed changes that were not measured during new learning (Wahlheim, 2015). Additionally, remindings promote interdependence between the old and new information while preserving memory for the specific list contexts (Jacoby et al., 2015; Wahlheim and Jacoby, 2013). To link our results to this remindings-based account of proactive and retroactive effects of memory, referred to as the memory-for-change framework, we propose that pre-existing relationships between base and supplemental pairs increased the likelihood of remindings, which resulted in retrieval practice benefits to more existing memories and provided more opportunities to integrate them with changed associations during new learning. This account could be verified in future studies including manipulations of semantic relatedness along with overt measures of noticing and recollecting changes.

We next consider these results in more detail for each condition. In the ΔTarget condition, we found overall 48 hr benefits (relative to the Control condition) but no correlation with target relatedness using the narrower stimulus set. Conversely, we found no overall long-term benefits using the wider stimulus set, but we did find correlations between target relatedness and memorability. We note the surprising result of a non-significant correlation between relatedness and memorability using the narrower stimulus set, but the analyses combining narrower and wider stimulus sets at a 48 hr delay produced a positive correlation. No PF occurred in the 5 min experiments, but we found overall PI using the wider stimulus set (Figure 6—figure supplement 1). Altogether, these results showed that PI can still occur with low relatedness, like in other studies finding PI in ΔTarget (A-B, A-D) paradigms (for a review, see Anderson and Neely, 1996), but PF occurs with higher relatedness. In fact, the absence of low relatedness pairs in the narrower stimulus set likely led to the strong overall PF in this condition across all pairs (positive y-intercept in the upper right of Figure 3A). In this instance, there may have been a stronger influence of a binary factor (whether they are related or not), though this remains speculative and is not the case for other analyses in our paper. We believe these effects arise from the competing processes of impairments between competing responses at retrieval that have not been integrated versus retrieval benefits when that integration has occurred (which occurs especially often with high target relatedness). These types of competing processes appear operative in various associative learning paradigms such as retrieval-induced forgetting (Anderson and McCulloch, 1999; Carroll et al., 2007), and the fan effect (Moeser, 1979; Reder and Anderson, 1980). This is exactly the proposal of the memory-for-change framework, which has received support from studies showing that PF occurs when changes (integrated representations) are recollected and PI when such changes are not recollected (for a review, see Wahlheim et al., 2021).

In the ΔCue condition, we generally found PF in every experiment. Moreover, PF increased with cue relatedness at a 48 hr delay using the wider stimulus set; the only PI in any experiment was for low relatedness items using the wider stimulus set at a 48 hr delay, wherein memorability values from pairs (averaged across subjects) in the lowest third of relatedness were recalled worse than the Control condition. These results are consistent with Osgood’s observation that interference tends to be absent or low when targets remain constant and cues change as opposed to when targets change and cues remain constant (e.g. the ΔTarget condition). The general facilitation and lack of interference effects are consistent with the idea that each independent cue does not become overloaded and can elicit the same (and only) target with which it was paired (Anderson and Neely, 1996; Antony et al., 2022b; Watkins and Watkins, 1975). Additionally, repeating the target, even with another cue, may increase its accessibility (at minimum) or evoke a reminding, leading to overall benefits (Estes, 1979; Martin, 1965). The prior literature on results for this condition has not been particularly reliable or theoretically extensive; we speculate that the selective PI we see could arise via confusion over whether the same target was indeed assigned twice or due to a very weak form of interference involving weight changes after targets become assigned to a new memory. Benefits could indicate that subjects could mentally link Δcue → cue → target, which would link both cues together via the reminding event; the overall correlations between relatedness and interdependence support this idea. In sum, the ΔCue condition largely resulted in more consistent PF than the ΔTarget condition, perhaps because benefits arose via the same mechanism (remindings-enabled interdependence) or even enhanced target response availability while not suffering the same drawbacks of competition that occurs when multiple non-integrated targets are linked to the same cue.

Next, we will discuss proactive effects in the ΔBoth condition, for which the prior literature is virtually non-existent. In the narrower stimulus set, 48 hr delay experiment, we found overall PF effects. These findings resemble those from our prior retroactive study (Antony et al., 2022b), such that this was the only experiment in which we found overall memory effects. However, unlike that prior study, here there was no correlation between cue +target relatedness and memorability. These findings also resemble general benefits of relatedness in other conditions and experiments, with the difference being that changes to both cues and targets mean that both relatedness values need to be relatively high for remindings (and their associated strengthening) to occur. That is, it is much easier for a subject to consider a new pair with both a cue related to an old cue and a target related to an old target to simply be a new word pair, causing fewer reminders overall. Interestingly, in three of the experiments, we found significant correlations between cue +target relatedness and interdependence. It is less clear why we found interdependence in some experiments with an absence of memory boost; we speculate that in some cases, subjects may recognize the link between related pairs in the ΔBoth condition only at final retrieval.

Putting these conditions together, we consider our findings to largely support Osgood’s key ideas. That is, Osgood had the bold idea that the memory surface predicting facilitation vs. interference applied in both the retroactive and proactive directions. We propose that semantic relatedness, by increasing the likelihood of remindings, provides a mechanism by which existing memories can become more accessible and associated with new learning as part of integrated memory representations that preserve targets and their contexts. Specifically, along both the cue and target identity lines of Osgood’s surface, the increasing proactive benefits strongly support his proposal that PI becomes PF with high enough relatedness. However, he did not predict PI in the ΔCue condition, and additionally, we found weak support for PF inching towards the cue and target identity point along the 2-D part of the surface in the ΔBoth condition (which was present in the retroactive narrower stimulus set, 48 hr experiment of our prior paper).

While Osgood predicted that retroactive and proactive memory effects worked in both directions, he never explicitly stated whether they should be symmetric. By showing stronger retroactive than proactive benefits here, we propose that the retroactive benefits are greater, presumably because target responses receive retrieval practice during remindings. Indeed, there are recent similar results in between-subjects comparisons of retroactive and proactive memory effects in A-B, A-D paradigms (Wahlheim et al., 2024). However, our assertion awaits additional empirical verification using experiments that directly compare retroactive and proactive effects within-subjects and at various retention intervals. Additionally, these effects partially resemble those on spontaneous recovery, whereby original associations tend to face interference after new, conflicting learning, but slowly recover over time (either absolutely or relative to the new learning) and often eventually eclipse memory for the new information (Barnes and Underwood, 1959; Postman et al., 1969; Wheeler, 1995). In both cases, original associations appear more robust to change over time, though it is unclear whether these similar outcomes stem from similar mechanisms.

Our experiment had a few limitations. First, although we showed highly consistent results across retroactive and proactive comparisons and used the same subject populations and procedure, these comparisons across experiments did not involve random assignment (i.e. all experiments assessing retroactive comparisons were completed before those assessing proactive comparisons). Second, we largely explained our results using remindings-based accounts, but we did not directly manipulate remindings or measure such remindings during new learning (Jacoby et al., 2015). These limitations could be considered in future research. Yet another promising future direction would be to investigate how learning in this paradigm affects different aspects of the memory trace, either by investigating perceptual versus conceptual changes (Lifanov et al., 2021; Melega and Sheldon, 2023) or the semantic representations themselves (Walsh and Rissman, 2023). Finally, future studies could ensure these effects are not limited to these stimuli and generalize to other word stimuli in addition to testing other domains (Baek and Papaj, 2024; Holding, 1976).

Our goal in this paper was to examine fundamental questions about learning and memory for related pieces of information. Our prior work examined the retroactive impact of relatedness on existing memories (Antony et al., 2022b), whereas, here, we examined how relatedness proactively affected memory for new learning. Both studies were inspired by Osgood’s proposal that relatedness facilitates memory strength in both directions – and both largely support his proposal. Here we offer support to the idea that, by increasing the likelihood of remindings, both old and new information can mutually benefit from the newly integrated memories, so long as they promote later recollection. Nevertheless, because retrieved memories enjoy the benefits of retrieval practice, retroactive effects appear to produce stronger benefits for memories recalled at a 48 hr delay. Therefore, to return to the example about vermouth from the introduction, if one first learns to make a martini using dry vermouth and then, while learning about making Manhattans using sweet vermouth, they recall the martini ingredients, both memories should benefit from this mental integration, but the martini memory could benefit more. We believe these findings have important ramifications for how linking old and new associations can influence human decision-making (Nicholas et al., 2023; Shohamy and Daw, 2015; Wimmer and Shohamy, 2012) and reinforce and clarify the significance of building up complex networks of associations for learning and memory theory.

All code and data related to this paper are available at https://osf.io/u29hy/.

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Author details

1. Kelly A Bennion

   Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   kbennion@calpoly.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3301-7744

2. Jade Phong

   Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, United States

   Contribution

   Supervision, Project administration

   Competing interests

   No competing interests declared

3. Mytien Le

   Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, United States

   Contribution

   Supervision, Project administration

   Competing interests

   No competing interests declared

4. Kunhua Cheng

   Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, United States

   Contribution

   Supervision, Project administration

   Competing interests

   No competing interests declared

5. Christopher N Wahlheim

   Department of Psychology, University of North Carolina at Greensboro, Greensboro, United States

   Contribution

   Writing – review and editing

   Competing interests

   No competing interests declared

6. James W Antony

   Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   jwantony@calpoly.edu

   Competing interests

   No competing interests declared

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