1

Title: Semantic associates create retroactive interference on an independent spatial task

Authors: James W. Antony1, Kelly A. Bennion2

1Center for Neuroscience, University of California, Davis, Davis, CA, 95618, USA

2Department of Psychology and Child Development, California Polytechnic State University, San Luis

Obispo, San Luis Obispo, CA

Corresponding author:

Dr. James Antony University of California, Davis [email protected] Center for Neuroscience

Phone: (262) 347-8224 Davis, CA 95618, USA

Funding: This work was supported by the Princeton University CV Starr Fellowship to JWA.

Author note: Code / data for this project can be found here:

Antony, J.W. & Bennion, K.A. (2020). attack by semantic mediator: causing retroactive interference via Deese-Roediger-McDermott lists. Retrieved from osf.io/khrmx. 2

Abstract

Semantic similarity between stimuli often leads to false , but how it causes retroactive interference (RI) in veridical recall has been less explored. Here, in Phase 1, participants learned spatial locations for “critical” words that reliably produce false memories in the Deese-Roediger-McDermott paradigm. In Phase 2, participants centrally viewed words that were semantically associated with half of the critical words. In Phase 3, participants retrieved the Phase 1 critical word locations. We found RI for critical words whose semantic associates were shown (vs. not shown), suggesting that semantic relatedness caused retroactive interference. This effect was present in three experiments when the interfering information was presented shortly before spatial recall, but not after a one-hour delay between associate and test or after reversing the order of the critical word spatial learning phase and the associate learning phase. These findings suggest that memory impairments from

RI can occur solely via semantic associates on an independent test where all relevant responses are freely available. We consider these findings to be an example of cue overload theory, whereby overload can interfere indirectly via semantic associates, and explain them by citing computational models of RI such as the search of associative memory theory.

Keywords: Retroactive interference; ; ; ; cue overload 3

Long-term memory relies on , retrieval, and processes (including new learning) that occur between encoding and retrieval. Retroactive interference (RI), or the process by which newly learned information interferes with previously learned information, has been shown for over a century to have a profound and reliable effect on memory (Müller & Pilzecker, 1900; Wixted, 2004). In one of the most common demonstrations of RI, participants forget more from a list of paired associates (A-B) when it is followed by a new list involving the same cue words (A-C) than when it does not (D-E).

Interestingly, in a phenomenon that has been studied little since the late 1960s, RI also occurs when newly learned information is semantically similar, but not identical, to previously learned information.

That is, memory for A-B pairs can be impaired by A’-C learning, where A and A’ are synonyms, relative to

D-E learning (Baddeley & Dale, 1966; McGeoch & McDonald, 1931; Saltz & Hamilton, 1967).

Generally, psychological theories related to these RI effects propose that new learning either causes the unlearning of previously learned information (Briggs, 1954) or acts independently of previously learned information and causes interference due to enhanced competition between previously and newly learned responses (Bower, Thompson-Schill, & Tulving, 1994; Mensink &

Raaijmakers, 1988; Saltz & Hamilton, 1967; Slamecka & Ceraso, 1960). One form of competition is cue overload, or the finding that as more information becomes associated with a cue, any specific instance becomes less likely to come to mind at retrieval (Nairne, 2002; Robin, Garzon, & Moscovitch, 2019;

Watkins & Watkins, 1976; Watkins & Watkins, 1975). However, it is unclear to what extent RI occurs via cue overload when information related to a cue, rather than the cue itself, is subsequently learned, and to what extent RI relies on the availability of responses at test.

To address these questions in the present work, we investigated RI by presenting semantically similar, but not identical, information during new learning. Critically, this information did not interfere with the primary target response, as participants learned peripheral word locations on a spatial memory 4 task, but the interfering associations were all presented centrally. Moreover, all peripheral target locations were available at test, indicating that could not be attributed to the availability of the correct response. This contrasts with prior work in two ways. First, in most prior work, newly learned and previously learned information was identical (e.g., A cues), which, because participants often consciously notice this identical information, they can form strategies to overcome interference (e.g.,

Martin, 1968; Negley, Kelley, & Jacoby, 2018; Osgood, 1949). Second, in the studies employing semantic associates in long-term memory interference (e.g., Baddeley & Dale, 1966; McGeoch & McDonald, 1931;

Saltz & Hamilton, 1967), the target responses (e.g., B cues) overlapped in their lexical nature with the new information (i.e., they were both words) and were also not available as choices at test.

We created semantic similarity between previously and newly learned information by using lists of words from the Deese-Roediger-McDermott (DRM) paradigm (Deese, 1959b; Roediger & McDermott,

1995). In this paradigm, lists of words (e.g., marker, crayon) reliably elicit false recall and recognition for one unpresented critical word to which they are all related (e.g., pen). Notably, this false memory effect seems to rely partly on the backward associative strength (BAS) between the words (Deese, 1959a;

Roediger, Watson, McDermott, & Gallo, 2001), which is a measure of how often critical lure words are freely given when prompted by the associates (e.g., marker  pen) in free association tests (Nelson,

McEvoy, & Schreiber, 1998). Here, rather than assessing false memory for critical words, we used the related associates to create RI after presenting the critical words and measured RI as a function of BAS.

Figure 1 shows the procedures within and the sequencing of the three phases used in the five experiments. In the spatial encoding phase of Experiment 1, participants learned spatial locations for critical words (e.g., pen) (A-B learning, with critical words indicated by A and locations by B) (Fig 1). In the associate learning phase, participants centrally viewed words that were semantically related associates of half of the critical words (e.g., marker, crayon) (A’-C learning, with related associates 5 indicated by A’ and the center location as C). To reduce the likelihood of participants being able to notice the similarity between these associates and the critical words (and thereby enabling the ability to form conscious strategies), these lists of associates were intermixed with each other and shown in a random order. Finally, participants retrieved the spatial locations for the critical words (to test recall for

A-B) and distinguished previously seen critical words from novel words (to test recognition for A). These manipulations allowed us to determine whether interference via cue overload could occur in the absence of 1) direct cue competition, as the original (critical words) and interpolated material

(associated words) differed; 2) direct target competition, as the original (peripheral locations) and interpolated material (central locations) differed; 3) interference due to response availability, as all spatial responses were available at test; and 4) participants’ awareness of whether the interpolated words were related to the original cue words.

To foreshadow, we found that critical word spatial memory, but not recognition, was significantly worse for words whose related associates were presented (vs. not presented) in the associate learning phase, an effect we pre-registered and directly replicated in Experiment 2. In

Experiment 3, we swapped the order of these two phases and found no spatial memory RI for words whose related associates were previously presented; instead, we found an improvement in recognizing critical words whose related associates were previously shown.

In Experiments 4 and 5, we contrasted two possible accounts for the above findings: a reactivation/ account and a retrieval impairment account. If presenting associates leads to relatively long-lasting RI (e.g., 60 minutes), spatial recall for the related condition (relative to the control condition) should remain impaired after a 60-minute delay between presentation of related associates and final test (Experiment 4). According to the reactivation/storage account, RI would occur if the memory trace for the critical word-location association (A-B) were reactivated to a modest extent during the subsequent associate phase (A’-C), which, according to behavioral and neural evidence, would result 6 in weakening or suppression of the previously stored long-term memory traces for A-B (Anderson, 2003;

Lewis-Peacock & Norman, 2014; Norman, Newman, & Detre, 2007). However, if presenting associates shortly before testing leads to greater temporary retrieval interference for the critical word-location associations due to cue overload, as shown previously (Anderson & Neely, 1996; Briggs, 1954; Saltz &

Hamilton, 1967) and as predicted by computational models of retrieval interference (Mensink &

Raaijmakers, 1988), spatial recall for the critical words in the related condition should be more impaired when A’-C learning occurs 60 minutes after A-B learning but is directly followed by a test (Experiment 5).

Note that the reactivation/storage account would also predict RI in Experiment 5 [i.e., modest reactivation of the A-B (critical word-location) association during later A'-C learning could still weaken the stored A-B memory trace, thereby leading to impaired test performance briefly afterward], but the retrieval interference account would be supported if RI occurred in Experiment 5, but not in Experiment

4.

We found RI did not occur with a one-hour delay between the associate and test phases

(Experiment 4) but did occur with a one-hour delay between the spatial and associate phases

(Experiment 5), supporting the retrieval interference account. Finally, whereas the recognition enhancement for critical words (in Experiment 3) was most reliable at high mean BAS levels, spatial memory impairments (in Experiments 1, 2, and 5) were most reliable at low-to-moderate BAS levels. 7

Figure 1. Experimental paradigms used in the five experiments. A) In the spatial encoding phase (S), participants learned spatial locations for 32 words. In the associate interference phase (A), participants learned centrally presented words semantically related to half of the words from Phase 1. In the spatial test (T), participants were instructed to answer whether 32 old and 16 new words were old or new and, if old and they could remember the location, to click the box where it was originally presented. B) The orderings of and delays between the three phases. 8

Method

Participants

All participants across the five experiments (Experiment 1: N = 92, 45 females; Experiment 2: N =

134, 57 females; Experiment 3: N = 123, 50 females; Experiment 4: N = 140, 93 females; Experiment 5: N

= 115, 78 females) were undergraduate students with normal or corrected-to-normal vision. In

Experiments 2-5, we preregistered a sample size of 112, based on a power analysis (β = 0.8, α = 0.05)

performed on Experiment 1 using the within-participant effect size, dz = 0.27. We used an online scheduling software to recruit participants and stopped new signups after that number had been reached (allowing for all of those who had signed up before we completed 112 in the lab to still participate). Participants performed the experiment in a lab on computers angled away from one another. All procedures were in accordance with the California Polytechnic State University, San Luis

Obispo Institutional Review Board. Participants provided informed consent and earned research credits for a psychology course in exchange for participation.

Materials

The 48 critical words used in this study came from DRM lists which Roediger et al. (2001) showed had false recall proportions exceeding 0.05 (see Table S1 for the full list of stimuli). Semantic associates were the 15 words related to these 48 critical words. All backward and forward associative strength (BAS/FAS) values (shown in Table S1) were also taken from Roediger et al. (2001).

Procedure

Experiment 1. First, in the spatial encoding phase (Phase 1), participants learned spatial locations for 32 of the 48 critical words (e.g., pen, war) (Fig 1) chosen at random for each participant.

These 32 studied critical words would later fall into the related condition (16 words) and the control condition (16 words). Participants were instructed to begin each trial by looking at the center fixation cross (which was red). On each trial, a word appeared in one of the eight boxes circling the fixation 9 cross. After one second (when the fixation cross turned green), participants had unlimited time to click within the box once they had registered its location, before immediately continuing to the next trial.

Participants were told that they would later be tested on the locations of each of the words, but were naïve to the format of this test, and were instructed to do their best to remember them. Across all trials, four critical words were presented in each peripheral box, two each from the related and control conditions.Therefore, any effects due to competing traces from critical words associated with the same box would be equal across both conditions.

In the following associate learning phase (Phase 2), participants studied 240 words total. These words were made up of 15 associates each of 16 of the 32 critical words that had been studied in Phase

1. Thus, the 16 critical word-location associations learned in the related condition in Phase 1 were subject to RI from 15 semantically related words and 225 semantically unrelated words, whereas the other 16 in the control condition were subject to RI from 240 semantically unrelated words. The associates were presented in a random order with intermixed lists (e.g., “marker” could be followed by the “sweet”-related word, “candy”); note that whereas the DRM effect classically involves presenting associates in blocks, the effect persists with interleaved presentations (e.g., McDermott, 1996).

Participants were told to do their best to remember each of these words because they would be tested later whether these words were presented in this phase. These words were shown centrally for 3 seconds each with intermittent breaks every 15 trials in which participants were told to rest and to click the mouse when they were ready to continue.

Lastly, in the test phase (Phase 3), participants were centrally presented with each of the 32 critical words they learned during Phase 1, as well as the remaining 16 of the original 48 critical words that had not been presented in Phase 1. Thus, the recognition test consisted of 32 old items (targets) and 16 new items (lures). Participants were given one of three possible response options (see Figure 1):

(1) If they remembered seeing the word in Phase 1 and its location, they clicked the box where the word 10 was previously shown. (2) If they remembered seeing the word, but not in which box it was presented, they clicked “Old.” (3) If they did not think they had seen the word, they clicked “New.” There was one second between the end of one test trial and the start of another.

Experiment 2 was a pre-registered, direct replication of Experiment 1 (Antony & Bennion, 2020).

We predicted spatial memory RI would occur once again as in Experiment 1 for critical words whose associates were presented.

Experiment 3 swapped the order of Phases 1 and 2 to assess whether proactive interference would occur if the interfering material was introduced before the spatial dimension became relevant.

That is, participants first viewed semantic associates (previously Phase 2) of half of the words they would later see during the spatial encoding phase (previously Phase 1). To hold the timing between completing the spatial encoding phase and starting the test phase constant across the three experiments, participants in Experiment 3 waited 20 minutes after completing the first two phases before beginning the test. We predicted there would be no differences in spatial memory between the related and control conditions (Antony & Bennion, 2020) because the interfering location information would occur before the spatial dimension became relevant. Therefore, the critical word cues at test would not face the same interference as when the semantically related words intervened.

In Experiments 4 and 5, we followed an identical protocol to Experiments 1 and 2 except for imposing 60-minute delays between the associate phase and test (Experiment 4) or between the spatial and associate phases (Experiment 5). The null RI effect in Experiment 4 disconfirmed the reactivation/storage account's prediction that RI would still be obtained. Because the retrieval interference account of RI can accommodate Experiment 4's finding that RI was reduced/eliminated when there was a 60-minute delay between Phase 2 and Phase 3, in Experiment 5 we asked whether the effect decayed when we imposed a 60-minute delay between learning and test but kept the original timing between the associate phase and test. Based on the retrieval interference account’s prediction 11 that RI is greatest shortly after the new information is learned (Mensink & Raaijmakers, 1988), we predicted spatial memory impairments would occur for critical words whose associates were presented shortly before test (Antony & Bennion, 2020).

Questionnaire. Following the computer portion of each experiment, participants completed a questionnaire that included various questions about their engagement during each phase and whether they were aware of the semantic relatedness between Phase 1 and Phase 2 words.

Memory measurements. Spatial recall was calculated as the proportion of learned items placed in the correct location (chance = 0.125). In experiments with a spatial recall impairment, spatial precision was calculated by finding the mean number of boxes away that errors were placed in both clockwise and counterclockwise directions, from 1 (nearest box) to 4 (furthest box 180o away). Only participants with at least one spatial error in each experimental condition were included in the spatial precision analysis, which dropped 35, 37, and 36 participants from Experiments 1, 2, and 5, respectively.

Note that these participants were dropped only from this analysis and not from the main spatial recall and recognition analyses of interest. For recognition, hit rate was the proportion of learned items placed in any peripheral location or selected as “Old”. False alarms were the proportion of non-studied lures selected as anything but “New”. Recognition measures (d’) were calculated as z(hit rate) – z(false alarm rate) separately for each condition. With 16 possible critical words in each of the conditions (related, control, and new words), rates of 0 or 1 were changed to 1/(16*2) = 0.031 or 1-1/(16*2) = 0.969, respectively, to avoid infinite values during this calculation (MacMillan & Creelman, 2004).

Statistical tests. The main comparisons in this study were within-participant measures compared by paired t-tests (α = 0.05) between words in the related condition versus the control condition. Comparisons across participants, such as whether the size of the spatial recall impairment depended on participants being aware of the relatedness between words in the spatial and associate phases, were performed using mixed 2 (awareness: aware, unaware) x 2 (condition: related, control) 12

ANOVAs. One-sample Bayes Factor tests (Rouder, Speckman, Sun, Morey, & Iverson, 2009) were calculated in R using the ‘ttestBF’ function from the ‘BayesFactor’ package (Team, 2018). For tests investigating spatial memory using only spatial responses, mixed effects logistic regression models were calculated in R using the ‘lmer’ function from the ‘lme4’ and ‘lmerTest’ packages, with condition (related vs. control) as a fixed effect and participant as a random effect (Bates, Mächler, Bolker, & Walker, 2015).

To measure effects related to properties of individual critical words, such as their BAS/FAS values, we used the following rationale (using BAS effects on spatial recall as an example). Because each participant received a different subset of words in each condition, the BAS values each participant had in each condition varied. Therefore, a particular participant may not have had any words at, say, a mean

BAS value above 0.35, making it difficult to properly ascertain these effects at a participant level.

However, this problem can be approached by bootstrapping. We conducted this analysis by randomly re-sampling participants with replacement 200 times and finding all words across re-sampled participants that fit within a small range of BAS values (step increment: 0.02, range: ± 0.075 around a given BAS value). Within this subset of words, we separated words based on whether they were in the related or control condition, and then we calculated the RI effect (proportion correct for related– control). Next, we sorted these samples within each BAS value and asked whether RI differed from zero at a 95% confidence level (< 0.025 or > 0.975 of samples); in other words, we had a permuted distribution at each BAS value against which we queried whether there was an effect. Then, we calculated the number of consecutive BAS values differing from zero. We also computed Pearson correlations between BAS values and the mean RI effect at those BAS values to assess whether these variables were related in a linear fashion. Finally, we re-ran this entire procedure 200 times after randomly scrambling the labels of each word condition (related or control) to determine a normal distribution of the number of consecutive BAS values differing from zero and the strength of correlations across BAS values that we should expect to see by chance. For FAS values, which had a smaller range 13 across words, we used a step increment of 0.002 and moving window of ± 0.004. For trial number at test, which had a larger range, we used a step increment of 1 and moving window of ± 3. For recognition, we considered only the hit rate for these words, because subtracting false alarms would be the same in each experimental condition.

Results

Semantic Associates after Spatial Encoding Impairs Critical-word Spatial Recall but Does Not Affect

Critical-word Recognition

We found that the presence (versus absence) of semantically related words in the associate phase impaired spatial critical-word recall in both Experiment 1 [related: 0.37 ± 0.03, control: 0.41 ±

0.03, t(91) = 2.57, dz = 0.27, p = 0.012; Fig 2A] and Experiment 2 [related: 0.38 ± 0.02, control: 0.42 ±

0.02, t(133) = 3.13, dz = 0.27, p = 0.002; Fig 2A]. This strongly suggests that spatial memory RI occurs via the presence of semantic associates, and moreover, it can occur when the interfering information was presented in the same non-overlapping spatial location and when all responses were available at test. In other words, RI occurs in A-B, A’-C learning, where A and A’ are semantic associates and B and C do not directly overlap (peripheral vs. central location). We also asked if these impairments stemmed from an increased tendency to choose nearby locations by finding the number of boxes away on the circle errors were placed, from 1 (nearest box) to 4 (furthest box). We found no differences in precision accuracy in

either experiment [Experiment 1, related: 1.96 ± 0.10, control: 1.87 ± 0.09, t(56) = 0.66, dz = 0.09, p =

0.51, Bayes Factor supporting the null (BFnull)= 5.6, indicating moderate evidence (van Doorn et al.,

2019); for Experiment 2, related: 2.05 ± 0.08, control: 2.10 ± 0.10, t(96) = 0.43, dz = 0.04, p = 0.67, BFnull =

8.1, indicating moderate evidence], suggesting that the relatedness effect on overall spatial recall accuracy was not merely due to an effect of relatedness on spatial memory precision.

We further asked if RI arose simply because participants endorsed “Old” (non-peripheral) responses rather than guessing the wrong spatial location (see Fig 1). We did this by performing an 14 analysis using only spatial guesses. As this analysis results in a different number of trials for each participant, we ran a mixed effects logistic regression model with word condition as a fixed effect

(related vs. control) and participant as a random effect, and we combined participants from the two experiments. RI was once again observed in the related condition [β = 0.026 ± 0.013, t = 1.979, p =

0.048].

We also measured recognition performance for the critical words as d’ [z(hit rate) – z(false alarm rate)], where any “Old” response or a response in any spatial location was considered an endorsement of the critical word as old. In contrast to spatial recall, we found no effect of relatedness on recognition

performance [Experiment 1: related: 1.95 ± 0.10, control: 2.01 ± 0.10, t(91) = 0.97, dz = 0.10, p = 0.34;

Experiment 2: related: 1.90 ± 0.08, control: 1.95 ± 0.08, t(133) = 1.10, dz = 0.09, p = 0.28; Fig 2B]. To increase the statistical power, we ran this analysis combining the two experiments [related: 1.92 ± 0.06,

control: 1.97 ± 0.06, t(225) = 1.46, dz = 0.10, p = 0.15]; given this effect size, we estimate it would take

787 participants to find a significant effect at 80% power, and BFnull was 4.76, indicating moderate evidence in favor of the null hypothesis (van Doorn et al., 2019). 15

Figure 2. Spatial recall and recognition results for the critical words from all five experiments. (A) Proportion of correctly recalled spatial associations are plotted for Experiments 1-5. Dotted line indicates chance performance. (B) d’ recognition performance for the critical words is shown for all experiments. Error bars represent the SEM in each condition after removing across-participant variability (subtracting the mean across both conditions for each participant). *: p < 0.05. **: p < 0.005. 16

We next ran exploratory analyses combining data from Experiments 1 and 2 to determine whether participant awareness of the relatedness between the words in the spatial and associate phases modulated the effects. For this analysis, we submitted spatial recall proportion to a mixed, 2

(awareness: aware, unaware) x 2 (condition: related , control) ANOVA. We found a significant main effect of condition [related: 0.37 ± 0.02; control: 0.42 ± 0.02; F(1,224) = 16.3, p < 0.001] and a marginal main effect of awareness [aware: 0.42 ± 0.02; unaware: 0.36 ± 0.02; F(1,224) = 2.9, p = 0.09], but no interaction [F(1,224) = 0.17, p = 0.68]. Follow-up, within-participant t-tests indicated that RI did not differ for aware participants than for unaware participants [related - control difference, aware, N = 132:

-0.04 ± 0.01, t(131) = 2.65, dz = 0.23, p = 0.009; unaware, N = 94: -0.05 ± 0.01, t(93) = 3.25, dz = 0.34, p =

0.002]. Thus, the semantically based RI effects persist (Nelson, McKinney, Gee, & Janczura, 1998;

Nelson, Schreiber, & McEvoy, 1992) and are equivalent regardless of whether participants are consciously aware of the relatedness between the Phase 1 critical words and their Phase 2 associates.

However, in a recent A-B, A-C paradigm, promoting awareness of A-B associations during A-C learning in the form of reminders caused retroactive facilitation, rather than RI, of A-B memory (Negley et al.,

2018). Therefore, the effects of awareness of previous learning during new learning may depend on the nature of the paradigm and interference.

Semantic Associates before Spatial Encoding Improves Recognition and Does Not Impair Spatial Recall

Having established that semantic associates caused RI for spatial recall, in Experiment 3, we swapped the order of the spatial and associate phases to ask whether semantic associates produce proactive interference. Our prediction – that the presence (versus absence) of semantically related words before spatial encoding would have no effect on spatial recall – was confirmed [related: 0.31 ±

0.02, control: 0.32 ± 0.02, t(122) = 0.77, dz = 0.07, p = 0.44; Fig 2A]. Given this effect size, we estimate it

would take 1637 participants to find a significant effect at 80% power, and the BFnull was 7.5, indicating moderate evidence for the null hypothesis. This divergence from the previous experiments suggests that 17 the presence of the associates between learning and spatial recall causes the RI. In contrast to spatial recall, we found a strong increase in recognition for critical words studied in the spatial learning phase in

the related condition [related: 1.59 ± 0.08, control: 1.36 ± 0.08, t(122) = 4.46, dz = 0.40, p < 0.001; Fig

2B]. This accords well with numerous studies showing that DRM lists cause false recognition of unstudied critical lures (Roediger III, Balota, & Watson, 2001; Stadler, Roediger, & McDermott, 1999) and supports the idea that processes that promote false recognition also enhance true recognition when that information is actually shown (Doss, Bluestone, & Gallo, 2016; Neely & Tse, 2007).

As in Experiments 1 and 2, we ran exploratory analyses to determine whether awareness of the semantic relatedness between phase 1 and 2 words (aware: N = 66, unaware: N = 57) modulated these effects. We again submitted spatial recall proportions for critical word-location memory to a mixed, 2

(awareness: aware, unaware) x 2 (condition: related, control) ANOVA. We found a marginally significant main effect of awareness [aware: 0.35 ± 0.02; unaware: 0.28 ± 0.02; F(1,121) = 3.6, p = 0.06], but a null main effect of condition [related: 0.31 ± 0.02; control: 0.32 ± 0.02; F(1,121) = 0.59, p = 0.44] and a null interaction [F(1,121) = 0.003, p = 0.96]. We next submitted recognition performance for critical words studied in the spatial learning phase to a similar ANOVA. We found a significant main effect of condition

[related: 1.59 ± 0.08; control: 1.36 ± 0.08; F(1,121) = 19.8, p < 0.001] and a marginally significant main effect of awareness [aware: 1.60 ± 0.08; unaware: 1.32 ± 0.08; F(1,121) = 3.4, p = 0.07], but no interaction [F(1,121) = 0.21, p = 0.65]. Follow-up, within-participant t-tests indicated that semantically enhanced recognition for critical words was consistent at both levels of awareness [related - control

difference: aware of relatedness: 0.21 ± 0.07, t(65) = 2.9, dz = 0.36, p = 0.005; unaware of relatedness:

0.26 ± 0.07, t(56) = 3.45, dz = 0.46, p = 0.001]. This supports and extends findings showing that, though conscious lure activation increases the DRM effect, the effect persists in the absence of awareness (e.g.,

Seamon, Luo, & Gallo, 1998). 18

Semantic Associates Impair Spatial Recall when Presented Shortly Before, but not with a 1-hour Delay before Testing

RI effects have been shown to decrease after longer delay intervals between the presentation of interfering information and tests in both A-B, A-C (Briggs, 1954; though see e.g., Archer & Underwood,

1951) and A-B, A’-C learning (Saltz & Hamilton, 1967). Therefore, we next asked whether and how our spatial recall effects would change with various time delays.

In Experiment 4, we had predicted RI for critical words in the related condition, in line with the reactivation/storage account. This prediction was not supported [related: 0.37 ± 0.02, control: 0.36 ±

0.02, t(139) = 0.54, dz = 0.05, p = 0.59, BFnull = 9.2, indicating moderate evidence; Fig 2A]. Relatedness also had a null effect on the recognition of the critical words [related: 1.76 ± 0.08, control: 1.72 ± 0.08,

t(139) = 0.81, dz = 0.07, p = 0.42; Fig 2B]. Thus, the one-hour delay between the associate phase and test eliminated RI, and the reactivation/storage account was not supported.

Cumulatively, the results in Experiments 1-4 and from prior work (Doss et al., 2016; Saltz &

Hamilton, 1967) support the conclusion that presentation of semantic associate words at the center of the screen shortly before testing impairs recall of the spatial locations of critical words given in Phase 1.

Therefore, we next predicted an impairment would again occur when there is a delay between Phase 1

A-B critical-word spatial learning and Phase 2 A'-C associate learning in Experiment 5. Supporting this prediction, spatial recall was now once again impaired by the presence (versus absence) of semantically

related associate words [related: 0.28 ± 0.02, control: 0.33 ± 0.02, t(114) = 4.97, dz = 0.46, p < 0.001; Fig

2A]. This effect size was notably larger than in Experiments 1 and 2 (0.27), perhaps because the relative strength of A-B to A’-C was lower, due to more A-B forgetting during the delay inserted before the A'-C associate learning, thereby rendering the A-B critical word-spatial location association more susceptible to retrieval interference (Doss, Picart, & Gallo, 2018). Similar to Experiments 1 and 2, we found no RI

relatedness effect for precision accuracy [related: 2.09 ± 0.08, control: 2.15 ± 0.09, t(78) = 0.55, dz = 0.06, 19

p = 0.58, BFnull = 7.0, indicating moderate evidence], again suggesting RI for spatial recall occurred for accuracy instead of precision. To assess whether performance was impaired only by criterion shifting towards the “Old” response, we included only the spatial guesses in a mixed effects logistic regression model with word condition as a fixed effect and participant as a random effect. RI for spatial memory was marginally greater in the related than the control condition [β = 0.037 ± 0.021, t = 1.8, p = 0.072].

As in Experiments 1 and 2, RI occurred whether or not participants were aware of the relatedness between words in the spatial learning and associate learning phases: We again submitted spatial recall proportions to a mixed, 2 (awareness: aware, unaware) x 2 (condition: related, control)

ANOVA. There was a significant main effect of condition [related: 0.28 ± 0.02; control: 0.33 ± 0.02;

F(1,113) = 24.7, p < 0.001], but no effect of awareness [aware: 0.30 ± 0.02; unaware: 0.31 ± 0.02;

F(1,113) = 0.03, p = 0.87] nor an interaction [F(1,113) = 0.75, p = 0.39]. Follow-up, within-participant t- tests indicated that the spatial recall RI effects were significant across levels of awareness [related-

control difference, aware, N = 59: -0.06 ± 0.01, t(58) = 4.4, dz = 0.57, p < 0.001; unaware, N = 56: -0.04 ±

0.02, t(55) = 2.71, dz = 0.36, p = 0.009]. Also similar to Experiments 1 and 2, we found no relatedness

effect on critical-word recognition [related: 1.56 ± 0.09, control: 1.60 ± 0.09, t(114) = 0.81, dz = 0.08, p =

0.42; Fig 2B]. These results suggest that the interfering associate learning needed to occur temporally close to critical word-location learning to produce RI for critical-word locations. However, the temporal closeness of the interfering associate learning to the test was not important. This favors a retrieval interference account over a reactivation/storage account of the RI obtained here.

BAS Differentially Affects Spatial Memory RI and Proactive Recognition Enhancement for Critical

Words

The difference between RI effects on spatial recall in Experiments 1, 2, and 5 and proactive facilitation effects for critical-word recognition in Experiment 3 suggest different mechanisms explaining how semantic relatedness modulates memory. We next explored these differences by analyzing 20 relationships between memory for critical words and their BAS to their related associates. Specifically, we investigated mean BAS, or the mean of the free association norm strengths from the related associate words to their critical word (e.g., marker  pen) (Nelson et al., 1998), which has been shown to strongly predict DRM critical word false recall and false recognition effects (Deese, 1959a; Roediger et al., 2001) (Fig 3A). For spatial recall, we considered recall performance for each word at a particular BAS value. For recognition, we considered the hit rate for the critical words. Next, we sorted these samples and calculated the interval of consecutive BAS values for which correct spatial recall differed from zero at a 95% confidence level. We also ran correlations between the mean effect versus BAS values to assess whether these variables were linearly related. Finally, we re-ran this procedure after randomly scrambling the labels of each word condition (related or control) to determine a distribution of intervals of consecutive BAS values differing from zero and the strength of correlations across BAS values that we should expect to see by chance. See Methods for more details. 21

Figure 3. BAS between related and critical words predicted both impaired spatial recall and increased recognition for critical words. (A) Depicted is the relationship between related words to one critical word (BAS) (left) and the BAS value for each word and mean BAS (right). (B,C) RI effects for spatial recall in Experiments 1 and 2 (combined) and Experiment 5 were maximal for critical words with low-to-moderate BAS values. Blue line indicates the means of all samples (resampled with replacement) for a particular BAS value and blue shading indicates the 95% confidence intervals around the mean (based on the distribution of RI effects across samples). (D) Recognition enhancements for the related condition in Experiment 3 were maximal for critical words with the largest BAS values. 22

Combining data from Experiments 1 and 2, we found the strongest spatial recall RI for low-to- moderate mean BAS values (0.04-0.24), which exceeded what could be expected by chance (p < 0.01)

(Fig 3B). This effect did not seem to linearly increase or decrease with BAS values (r = -0.03, p = 0.97), suggesting it could be a non-linear relationship, and the effects did not accumulate with BAS. Similarly, in Experiment 5, we also found the strongest spatial recall RI for low-to-moderate mean BAS values

(0.04-0.24), which exceeded what could be expected by chance (p < 0.01). Similarly, this effect did not seem to linearly increase or decrease with BAS values (r = -0.08, p = 0.98). We next repeated these analyses for critical-word recognition differences between the related – control conditions. This analysis did not produce a significant interval of BAS values differing from zero or a linear correlation either when combining Experiments 1 and 2 or in Experiment 5 (Experiments 1 and 2 interval: p = 0.7; correlation:r = -0.18, p = 0.96; Experiment 5 interval: p = 0.38; correlation: r = 0.16, p = 0.14).

In stark contrast, in Experiment 3 we found increasingly strong proactive critical-word recognition enhancements with increasing BAS. These were significant from 0.06 to 0.42, an above-zero segment that exceeded what could be expected by chance (p < 0.005). Moreover, there was a significant correlation between this effect and BAS (r = 0.95, p < 0.005). The relationship between mean BAS value and spatial recall RI was not significant for any interval (p = 1.0) or as a linear correlation (r = -0.56, p =

0.48). These diverging results suggest different mechanisms underlie the critical-word spatial recall RI and critical-word recognition facilitation.

Forward Associative Strength (FAS) Effects Did Not Occur for Spatial Recall RI or for Proactive

Recognition Enhancements for Critical Words

Lastly, to examine the specificity of the above effects to BAS (e.g., directed strength from associate  critical word), we investigated the impact of FAS from each critical word to its associate

(e.g., pen  marker) on spatial recall in Experiments 1, 2, & 5 and recognition in Experiment 3. We repeated the analysis above using FAS values by combining data from Experiments 1 and 2. Spatial recall 23

RI tended to lessen with higher FAS values (r = 0.36, p = 0.54), although this was not significant when compared with the null distribution. Similarly, this was not significant in Experiment 5 (r = 0.27, p =

0.76), nor were there significant relationships between critical-word recognition and higher FAS values

(Experiments 1 and 2 correlation: r = 0.08, p = 0.96; Experiment 5 correlation: r = 0.27, p = 0.66).

We also asked whether proactive recognition enhancements for critical words in Experiment 3 correlated with FAS values. Contrary to this idea, these recognition enhancements tended to lessen with higher FAS values (r = -0.71, p = 0.1), although this was not significant when compared with the null distribution, suggesting that proactive recognition enhancement is specific to BAS. The relationship between mean FAS value and spatial recall RI was also not significant (r = -0.02, p = 0.83).

Discussion

The present experiments examined a novel form of RI whereby memory for the location of critical words on a spatial task (A-B) is impaired by the later presentation of semantically related associates in a central, non-overlapping location (A’-C). RI was present when the associates were shown shortly before the spatial test for the A-B associations (Experiments 1, 2, and 5) but not when they were shown before spatial encoding of the A-B associations (Experiment 3) nor when there was a one-hour delay before the final A-B spatial test (Experiment 4). Spatial recall RI stemmed from a decrease in overall accuracy rather than a decrease in precision (Experiments 1, 2, and 5). In contrast, the presence of semantic associates never produced RI for the recognition of the A critical words; conversely, when associates were presented before A-B spatial encoding, critical A word recognition was facilitated

(Experiment 3). Finally, whereas the recognition facilitation for critical words (in Experiment 3) was most reliable at high levels of BAS from associates to critical words, RI (in Experiments 1 and 2) was most reliable at low-to-moderate BAS levels. 24

To explain these effects, we will first highlight relevant principles from theories and computational models about semantic representations, contextual retrieval, and temporal representations.

Principle 1: Vectorized semantic representations. Computational models of memory, such as

Eich (1982), represent semantic attributes as vectorized representations of semantic attributes related to the word, rather than indivisible units for the word itself. These models suggest that, if one encounters related words like ‘pen’ and ‘marker’ during learning, the later presentation of the word,

‘pen’ as a retrieval cue, will also partially activate units associated with ‘marker’.

Principle 2: Retrieval cue interference. In cue overload theory (Watkins & Watkins, 1975), as one accumulates memories related to a particular cue, interference increases when presented with that cue at retrieval, making the likelihood of recalling any specific target decrease. Combining this idea with the vectorized semantic models, interference not only occurs when a specific cue (e.g., ‘pen’) is associated with multiple experiences, but may also occur when items having semantic attributes overlapping with that cue are associated with different experiences (Saltz & Hamilton, 1967; Underwood, 1969).

Principle 3: Old learning reactivation during new learning. A broad array of recent findings and theories point to the importance of the cognitive operations that occur during new learning for determining the fate of memory for related, previously learned information. Behaviorally, a notable account – termed the “memory for change” account (Jacoby, Wahlheim, & Kelley, 2015; Wahlheim &

Jacoby, 2013; Wahlheim, Smith, & Delaney, 2019; Wahlheim & Zacks, 2019) – suggests that, when encountering new information resembling previously learned information, noticing and recollecting the previous information actually leads to retroactive facilitation for the old information. Conversely, failing to recollect previously learned information causes RI. This account shares intriguing similarities with findings that have emerged from the neural literature on memory reactivation. Upon new learning, strong activation in brain regions associated with prior learning often predicts better memory retention 25 for the old information, the new information, or both (Kuhl, Shah, DuBrow, & Wagner, 2010; Lee,

Samide, Richter, & Kuhl, 2018). Intriguingly, while strong reactivation of previously learned information improves its retention, moderate reactivation (relative to no reactivation) often impairs it(Kim, Lewis-

Peacock, Norman, & Turk-Browne, 2014; Norman et al., 2007; Wang, Placek, & Lewis-Peacock, 2019).

Although speculative, these accounts could converge in that conscious recollection of previously learned information amounts to strong neural reactivation in learning regions, whereas a failure to recollect may result in moderate or little recollection. Taken together, these accounts strongly implicate the importance of recollection of previously learned information during new learning in its subsequent retention. Additionally, these accounts could supplement theories (Osgood, 1949; Underwood, 1969) that explain how semantic information retroactively interferes with (or facilitates) episodic memory

(Robbins & Bray, 1974; Robbins & Irvin, 1976). Because differing degrees of semantic overlap between the newly learned and old information could moderate the amount of reactivation of the old information, this could account for some studies finding that RI decreases with increasing similarity between original and later learning (e.g., Dreis, 1933), others finding that RI increases with increasing similarity (e.g., Bugelski & Cadwallader, 1956; McGeoch & McDonald, 1931; Robinson, 1927), while still others finding that RI is maximum at some moderate level of similarity, increasing and then decreasing with increasing similarity (e.g., Osgood, 1949).

Tying together the three principles above, competition among memories – whether involving the exact same information (e.g., A-B, A-C) or information that shares numerous attributes and input units, as in A-B, A’-C [see Principle 1: Vectorized semantic representations] – generally causes cue overload when given an A cue at retrieval [see Principle 2: Retrieval cue interference]. However, in cases where new learning allows for consciously recollecting and strongly reactivating the previous A-B information [whether it be during A-C or A’-C learning; see Principle 3: Old learning reactivation during 26 new learning], cue overload effects causing RI are eliminated, or sometimes even reversed. Whether or not this recollection/reactivation occurs relies partially on the similarity between the two events, such that high similarity may make it more likely the previously learned information comes back to mind, whereas low similarity makes this less likely, producing the potential for RI.

Principle 4: Temporal context effects in RI. Finally, a relevant and influential theory of memory interference (Mensink & Raaijmakers, 1988; Raaijmakers & Shiffrin, 1981), named the search of associative memory, highlights the importance of temporal context in RI that is relevant for Experiments

4 and 5. In this model, temporal context is represented as a vectorized representation of active units that slowly drift over time (in the manner of “bit flips” at successive time steps) as learning occurs (Estes,

1955). The temporal context vector is also operative and critical at the time of testing – in the case of RI, retrieval strength is proportional to the overlap between the temporal contexts at test and A-B learning versus the overlap between the temporal contexts at test and A-C learning. The model predicts high RI when A-C occurs shortly before testing (e.g., Briggs, 1954; Saltz & Hamilton, 1967) because, in this case, the temporal context at test strongly overlaps with the temporal context during A-C learning, meaning that the relative accessibility of A-B to A-C is low. However, with longer delays between A-C and test, the relative strength of the A-B temporal context to the strength of the A-C temporal context increases, leading to of the A-B association and a decrease in A-C recall.

Considering the four foregoing principles, we now offer our account of how spatial RI arises here and place our results in the context of the literature. In accordance with Principle 1: Vectorized semantic representations and Principle 2: Retrieval cue interference, attempting to retrieve spatial information associated with the critical word (e.g., ‘pen’) during the test in Experiments 1, 2, and 5 could occasionally activate elements of its semantic associates (e.g., ‘marker’) and their central spatial location more than its correct spatial location (e.g., Tomlinson, Huber, Rieth, & Davelaar, 2009), making participants less likely to recover the previously learned B association due to cue overload. Furthermore, associative 27 strength analyses revealed that RI was maximal for low-to-moderate BAS levels, rather than monotonically increasing with BAS. In light of Principle 3: Old learning reactivation during new learning, in Experiments 1, 2, and 5, high levels of BAS for Phase 2 associates might be most likely to cause participants to recollect the Phase 1 critical word and its associated location, thereby creating a sort of testing effect (Gates, 1917; Halamish & Bjork, 2011; Negley et al., 2018; Spitzer, 1939; Wahlheim et al.,

2019) that could counteract the cue overload/retrieval interference effect. Conversely, low-to-moderate

BAS levels may not cause sufficient recollection of the Phase 1 information, during Phase 2 learning, such that retrieval interference at test dominates and produces RI.

In accordance with Principle 4: Temporal context effects in RI, we found that RI only occurred when A’-C learning occurs shortly before test (Experiments 1, 2, and 5). In these cases, the temporal context at test strongly overlapped with the temporal context during A’-C learning, making the retrieval of A' and its associated central location more likely to interfere with the previously learned A-B association. In Experiments 3 and 4, A’-C learning occurred 25 minutes and 60 minutes before testing, and given that forgetting is a negatively accelerated function of the retention interval, these increases in the A'-C retention interval would decrease the retrievability of the interfering A'-C association more than the retrievability of the A-B association and thereby decrease RI. Importantly, after finding that RI was greatest for critical words with low-to-moderate BAS levels, we predicted that RI may occur because presentation of the semantic associates in Phase 2 led to only a moderate level of A-B reactivation, thereby bringing about a weakening rather than a strengthening of the A-B association produced by

Phase 2 new learning. Therefore, we predicted that RI would persist in Experiment 4 when we imposed a delay after Phase 2 A’-C learning; however, this prediction was not supported, suggesting that RI in the current paradigm is mostly, if not entirely, due to retrieval interference rather than reactivation of the A-

B association leading to a storage decrement in the A-B association being produced by A'C learning. 28

Taken together, we suggest that our results can be viewed as a combination of the negative effects of retrieval interference via cue overload that arises via vectors of semantic representations, the positive effects of recollecting previously learned information when overlap between previous and new information is sufficiently high, such as at high levels of BAS here, and the relative amounts of overlap between the temporal context vector at test and the temporal context vectors associated with A-B vs.

A'-C learning.

Related research offers alternative explanations for our findings to varying extents. One is that introducing semantically related misinformation increases the likelihood of endorsing false memories, an effect that was more prominent when the misinformation was presented just before test (Doss et al.,

2016; Doss, Picart, & Gallo, 2019). These effects resemble ours in their verbal semantic nature and time scale of the interference, though we see impairments in critical-word spatial recall accuracy rather than an effect of falsely endorsing information as old. Our effects also resemble the inhibitory effects of and part-set cuing, whereby presenting semantically related information at the time of test impairs recognition performance (Neely, Schmidt, & Roediger, 1983; Slamecka, 1968, 1975; Todres &

Watkins, 1981). However, priming and part-set cuing are typically seen on timescales of multiple seconds, or within , which contrasts with the multiple minutes between associate and test phases employed here. Additionally, to the best of our knowledge, these effects have primarily been shown for recognition rather than recall. We consider it an open question whether the two effects share similar mechanisms.

In Experiment 3, we found enhanced recognition memory for critical words whose associates had been presented before critical word-location learning. These results follow readily from an activation-based explanation: associate words often produce false recognition of critical words when they are unstudied (Roediger III et al., 2001; Stadler et al., 1999), so it follows that they might also produce increased true recognition when they are studied, which has been found (Neely & Tse, 2007). 29

However, the fact that associate words did not enhance recognition for critical words when critical words were learned first (as in Experiments 1, 2, 4, & 5) suggests that the order of the learning phases determines the effects of associates on critical-word recognition. This suggests that the facilitated recognition was based on "forward priming" from the associates to the critical word enhancing storage/ encoding of the critical word during Phase 2 rather than being due to facilitated retrieval of the contextual elements associated with the critical word. Future work could further explore this issue.

Additionally, critical-word spatial RI did not occur in Experiment 3, for which we now offer a few possible explanations. We originally predicted that encoding associates centrally before spatial encoding would fail to cause interference (in this case, proactive interference) because the spatial dimension was not yet relevant. However, because the time delay between associate learning and the final test was longer than a few minutes in Experiment 3 (~25 minutes; the duration of the spatial learning phase plus a 20- minute delay), the null RI effect could have instead been due to retrieval of the interfering A'-C association at test being less likely over time, as in Experiment 4. Further research is needed to distinguish between these two explanations.

Our results also have notable limitations. One is that, while we chose the central location for the associate words to avoid direct competition with the learned information and we omitted it as an option at the final test, it is unclear whether interference is caused by participants recalling specifically the central location or just the word itself. That is, if an associate (A’) is activated by an A cue at test, does the interference occur because the central location (C) is activated (even though C is not one of the peripheral response options), or can RI occur simply by activating A’? For example, would the same RI effects occur if associates were presented orally (e.g., without a screen location)? Such investigations could prove interesting in future work. Another limitation is that the interference shown here differs from most other RI paradigms in that 15 different A’-C associations were learned rather than only a single newly learned association; whether similar effects could be seen with a single A’-C association in 30 which the C location is always central or one of the locations in which unrelated critical words had appeared remains to be seen. Additionally, we did not test memory for the associate words, which – assuming that recognition memory for the associates was strong – could have strengthened our findings that presentation of the associates led to interference in the spatial domain. A final limitation is that the recognition phase comprised 2/3 old words and 1/3 new words, which may have created a response bias toward ‘Old’. However, as this was counterbalanced across our conditions of interest, it does not confound our results.

In conclusion, we flipped the classical Deese-Roediger-McDermott effect on its head and found that RI can occur for a critical word-location association even when 1) the subsequently learned associations that produce the RI contain associates of the critical word rather than the critical word itself, and 2) the associates are presented in a task-irrelevant location, and 3) when the relevant responses are available at the time of test. We interpreted these effects within the framework of semantic models of memory, cue overload theory, and models accounting for how temporal context affects RI. 31

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Author Contributions

J.W.A. conceived, programmed, and analyzed data from the experiment, and drafted the manuscript. K.A.B. contributed to study design and coordinated all data collection. Both authors discussed the results and revised the manuscript.

Acknowledgements

The authors thank Mytien Le for her help scheduling research assistants, as well as scheduling and running participants. The following individuals (all Cal Poly students) also assisted with data collection: Kenia Alba, Brooke Begg, Madeleine Cenac, Valentina Gomez, Stephanie Goryl, Ethan Heh,

Reilly Kleven, McKenna Kumnick, Nancy Lagunas, Michael Lothringer, Alaina Martine, Catherine Palmer,

Lauren Romano, America Romero, Ava Salehi, Samantha Shute, Noah Stashower, Alexander Stater,

Arushi Tewari, Natalie Thomas, Akuekegbe Uwadiale, Jacob Van Dam, Anthony Vierra, Emma Whitwam, and Amy Yang. The authors also thank Manoj Doss and Sean Polyn for comments on an early draft of this manuscript. This work is supported by the CV Starr Fellowship to JWA.

Declaration of interests

The authors declare no competing interests. 38

Table S1. List of critical items, their corresponding forward and backward associative strength values (FAS/BAS), and the related words presented in the associate phase. These word lists (and their corresponding FAS/BAS values) comprise those used in Roediger et al. (2001) after excluding words with false recall rates less than or equal to 0.05.