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EFFECTS OF AGING ON ASSOCIATIVE MEMORY

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1 Abstract

Associative memory involves the ability to make meaningful connections between individual units of information and to remember this more complex, larger unit of bound information. Prior research has found that as meaningful connections are harder to make,

associative memory for this information suffers. Additionally, associative memory is weaker for older adults than for younger adults due to aging-related cognitive declines. However, the effects of encoding difficulty and aging on associative memory for information presented in sentences is less studied. Thus, with our current study, we tested associative memory in 65 older and 86 younger adults for information presented in sentences varying in encoding difficulty. We expected to find an interaction between sentence type and age on recall and encoding time such that older adults would not differ with younger adults for common sentences, but would do significantly worse on cued recall and have longer encoding times than younger adults for bizarre stimuli. This expectation was based on the findings in prior research that older adults show relatively little decline in memory for text but show significant decline in their ability to make and recall associations between unrelated stimuli. Our results showed no interaction of age and sentence type on recall or encoding time, but did show main effects of age and sentence type on each. The findings of this study demonstrate an age-related difference between older and younger adults for encoding time and recall for sentences, and indicates a significant effect of encoding difficulty on overall encoding time and recall.

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Introduction

With healthy aging there are many declines in cognitive processes such as perception, attention, motor control, and memory. As reading and the ability to remember what has been read rely heavily on all of these processes, such declines have significant effects on the

performance of older adults in reading and memory tasks (Craik & Salthouse, 2008; Kemper & McDowd, 2008; Schaie & Willis, 2011). However, performance in some areas related to reading and memory are relatively preserved in healthy aging. One example of this preservation is the knowledge of language, an aspect of crystallized intelligence that heavily influences reading ability. Older adults perform just as well, and frequently out-perform, younger adults on tests of knowledge of language (Gordon, Lowder, & Hoedemaker, 2016; Laubrock, Kliegl, & Engbert, 2006; Rayner, Reichle, Stroud, Williams, & Pollatsek, 2006).

Exceptions to the cognitive declines that occur with aging may be better understood by studying how information is encoded during reading. One method of studying this is by

examining how time is allocated during reading. While older and younger adults are very similar in how they allocate time during reading, there are some significant differences between the two groups. Older and younger adults both allocate more time at major and minor clause boundaries when reading text; however, older adults tend to spend less time at sentence boundaries and at new concepts than younger adults (Smiler, Gagne, & Stine-Morrow, 2003; Stine, 1990; Stine, Cheung, and Henderson; 1995).

This pattern of spending more time during reading at the ends of sentences is referred to as the wrap-up effect (Fraundorf, Hourihan, Peters & Benjamin, 2019). Information that is found at sentence boundaries aids in comprehension and supports the binding of information in texts. This information is used to resolve lexical and syntactical ambiguities and aids in the ability to

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3 make inferences during reading. Thus, because greater wrap-up effects imply more time spent encoding and processing information, they are associated with better comprehension of text as well as with better recollection (Chin, 2015; Haberlandt et al., 1986; Stine, Cheung, &

Henderson, 1995; Stine-Morrow, Loveless, & Soederberg, 1996). Older adults tend to exhibit weaker wrap-up effects than younger adults, as is seen in the fact that older adults spend less time at sentence boundaries than younger adults (Stine, et al., 1995).

Preservation of Text Memory

Although memory is classified as one of the processes that declines with healthy

cognitive aging, different aspects of memory vary in how they are affected by healthy aging. For example, memory for isolated words (i.e. words in lists) declines with healthy aging but memory for texts does not (Matzen & Benjamin, 2013; Fraundorf et al., 2019). In regards to performance on recognition tests, Matzen and Benjamin (2013; also Fraundorf et al., 2019) found that

memory for words studied in the context of sentences or text is preserved whereas memory for words studied in the context of lists declines with healthy aging, as older adults showed superior memory for words studied in texts to younger adults (Matzen & Benjamin, 2013; Fraundorf et al., 2019). Research testing the recall memory of older adults has found similar effects

(Alexander et al., 2012; Zelinski & Kennison, 2007). Memory for functional relations has also been found to be preserved in older adults, as studies have shown no age-related differences in memory for items with functional relationships. In contrast, a significant age-related difference in memory was found for items without functional relationships (Radvansky, Copeland & Zwaan, 2003).

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4 One finding in past research is that older adults tend to have more difficulty recalling multiple units of information that have been bound together than recalling smaller, individual units of information. For example, older adults presented with objects and colors separately may be able to remember these items well. However, when required to bind object and color

information together and to recall both an object and its color, older adults struggle to remember this information significantly more than younger adults (Chalfonte & Johnson, 1996). This effect suggests that older adults have greater difficulty with binding information together and

remembering this bound information than younger adults (Chalfonte & Johnson, 1996; Old & Naveh-Benjamin, 2008; Spencer & Raz, 1995). This decline in the ability to bind and remember bound information is referred to as the associative memory deficit, as it is a deficit in the ability to create and recall associations between items.

The hypothesis that associative memory declines with age is called the Associate Deficit Hypothesis, and it is widely supported by aging research on associative memory. Research has found that older adults have significantly poorer memory for contextual information than younger adults, but age differences are smaller in memory for content information (Spencer & Raz, 1995). This finding may be explained by research that shows that older adults have more difficulty encoding and binding information into more complex memories. Because older adults are able to remember the features individually, but have difficulty remembering the information when it is bound or contextualized, this suggests that while older adults have relatively preserved ability to remember content information, they experience deficits in their ability to bind bits of information, impairing their ability to remember contextual information (Chalfonte & Johnson, 1996; Old & Naveh-Benjamin, 2008; Spencer & Raz, 1995).

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5 The fact that the Associative Deficit Hypothesis is so widely supported is puzzling when considered alongside the support for the hypothesis that text memory is relatively preserved in healthy aging while memory for isolated words is not. Reading, comprehending, and

remembering texts relies much more heavily on the ability to make meaningful associations between features than does reading, comprehending and remembering isolated words (Chalfonte & Johnson, 1996). Thus, the findings that memory for texts is better preserved in aging than memory for isolated words directly contradicts the finding that the ability to make and remember meaningful associations between bits of information declines with age.

Current Study

In order to investigate this seeming contradiction, the current study will test associative memory for information presented in text by manipulating how well the information can be bound. Measures of how time is allocated during reading will be recorded to inform how easily the readers make associations between bits of information in texts. Measures of memory will be recorded using cued-recall tests to inform how well text memory is actually preserved in older adults.

Recall tests not only measure memory, but also serve as a measure of how well

information is encoded, bound, and comprehended. One way of measuring comprehension is by examining how well individual bits of information are bound together into more complex ideas. While free-recall tests measure whether or not an item is remembered, cued-recall tests measure this as well as the ability to bind information together. When making efficient use of the cues provided in cued-recall tests, participants must be able to use that cue to recall information that was bound to it during the study phase of the experiment. Thus, better performance on cued-recall tests suggests better ability to bind information together during reading. Intact memory

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6 generally relies on both the ability to remember separate features as well as the ability to bind the features together in a meaningful way (Chalfonte & Johnson, 1996). Because performance on cued-recall tests relies more heavily on both these abilities than does performance on free-recall tests, only cued-recall tests are used in the current study.

In this experiment, participants will read sentences that are manipulated by inserting bizarre or common words into text, and then participants will complete a cued-recall test. An example of a common sentence might be “Bill used the peeler to slice the green pear,” whereas an example of a bizarre sentence might be “Bill used the pump to inflate the green pear.” The insertion of bizarre words into text is expected to disrupt the encoding and binding of

information and increase reading times. Additionally, it is expected that the results of this experiment will show preserved memory of common texts in older adults, which would be supported by results showing larger age differences in recall for bizarre stimuli than for common stimuli. This would support the idea that memory for text is preserved in aging because if

memory for texts does decline with age, then older adults would have significantly worse recall than younger adults for both common and bizarre stimuli. Greater reading times for bizarre stimuli would show interruption in encoding processes due to the information being more difficult to bind, and worse recall for bizarre stimuli would support the idea that the difficulty in binding and making sense of bound information is related to memory performance.

Method

Participants

The participants included 86 undergraduate students (YAs) at the University of North Carolina and 65 older adults (OAs) from Chapel Hill and Greenville, NC. YAs were aged between 18 to 36 (M = 19.2, SD = 2.3), and OAs were between the ages of 65 and 96 (M = 73.7,

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7 SD = 5.6). YAs had a mean of 12.0 years of education (SD= .000 years), and OAs had a mean of 16.4 years of education (SD= 2.6 years). To take part in this study, participants had to meet the following inclusion criteria: (a) no reported history of psychiatric or neurodegenerative disorders, (b) a score of 25 or higher on the Mini Mental State Exam (MMSE; Folstein, Folstein, McHugh, & Fanjiang, 2001), (c) no depression at the time of study, as measured by the Geriatric

Depression Scale (GDS; Brink, Yesavage, Lum, Heersema, Adey, & Rose, 1982), and (d) normal or corrected-to-normal visual acuity, as well as normal or corrected-to-normal hearing within functional limit. Additionally, all participants were required to be native English speakers.

In addition to age and years of education, individual difference measures of participants included scores on the MMSE, GDS, Author Recognition Test (ART; Stanovich & West, 1989; Gordon & Wright, in prep), the Advanced Vocabulary Test (AVT; Ekstrom, French, Harman, & Dermen, 1976), WAIS Vocabulary Subscale (Wechsler, 1997), Verbal Paired Associated (VPA) Total Recall (Wechsler, 2008) and reaction time to an auditory stimulus (Montgomery &

Windsor, 2007). On the MMSE, YAs had a mean of 29.2 (SD = 1.2) and OAs had a mean of 28.5 (SD = 1.6). On the GDS, YAs had a mean of 1.0 (SD = 1.5) and OAs had a mean of .9 (SD= 1.2). For the ART, the YAs had a mean of 21.3 (SD = 9.0) and OAs had a mean of 35.3 (SD = 14.0). The YAs had a mean of 18.0 (SD = 4.1) on the AVT and OAs had a mean of 24.1 (SD = 7.9). On the WAIS, YAs had a mean of 51.5 (SD = 6.2) and OAs had a mean of 55.1 (SD = 7.7). For the VPA Total Recall, YAs had a mean of 21.5 (SD = 7.4) and OAs had a mean of 18.1 (SD = 7.2). YAs had a mean auditory reaction time of 322.1ms (SD = 47.1ms) and OAs had a mean auditory reaction time of 405.0ms (SD = 156.9ms).

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8

Materials

Twenty-four pairs of experimental sentences were constructed by modifying the sentence stimuli listed by Rayner, Warren, Juhasz, and Liversedge (2004). Each sentence pair consisted of a common sentence and a bizarre sentence. Each bizarre sentence shared the same structure and critical words as its paired common sentence, with the exception that one critical word was replaced with another word that did not make sense in the context of the sentence. The 24 pairs of experimental sentences were counterbalanced across two lists, such that each list contained 12 common sentences and 12 bizarre sentences. Each pair was separated between the lists, such that none of the critical words were ever repeated within the same list. For example, the common sentence “Bill used the peeler to slice the green pear,” and its paired bizarre sentence “Bill used the pump to inflate the green pear,” share critical words and would thus be placed on separate lists. The stimuli were modified so that it would be highly unlikely for any participant to be able to predict a sentence’s phrases from the remainder of the sentence. For example, in the sentence “Bill used the peeler to slice the green pear,” none of the phrases in the sentence (e.g., the peeler; to slice; the green pear) can be guessed when given the remainder of the sentence.

Procedure

An EyeLink 1000 system was used to record participants’ eye movements at a sampling rate of 1,000 Hz. The EyeLink 1000 system was calibrated at the beginning of each session and recalibrated as needed. A chinrest was used to stabilize the head and minimize head movement. Participants began with a reading task, the study phase of the experiment. For the reading task, participants were instructed to read each sentence at a natural pace and respond to the prompt immediately following each sentence. At the start of each trial, a fixation point was presented near the left edge of the monitor, marking the location where the first word of the sentence would

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9 appear. When the participant’s gaze was steady on this point, the experimenter presented the sentence. After reading the sentence, the participant pressed a button on a handheld console to continue to the yes-no plausibility question. The prompt asked whether the sentence just read described an event that was plausible or an event that was implausible. Participants pressed one button to answer “yes,” (the sentence was plausible) and another button to answer “no,” (the sentence was not plausible). The sentences were presented in a different random order for each participant.

After participants had completed the study phase, they were given a sheet of math problems and told to solve as many of the problems as they could within three minutes. After three minutes had passed, each participant was given a surprise cued-recall memory test.

For the cued-recall task, participants were seated in front of a computer and viewed sentences resembling those they had read in the study phase of the experiment, but some of the words in each sentence had been removed. These participants were instructed to read each sentence to themselves and try to fill in each blank with the correct word based on what they had read during the study phase. The missing words for each item in the cued-recall task were either the instrument and the verb (i.e., The green pear was VERB with a NOUN ), or the adjective and the patient (e.g., A peeler was used to slice the ADJECTIVE NOUN ). Each blank in the presented sentences was labeled with the part of speech of the missing word, as has been done in the examples above.

Two versions of the cued-recall task were created, such that each sentence was presented with the verb and instrument omitted in one version, and the adjective and patient omitted in the other version. Each version of the cued-recall task included 24 sentences: 12 sentences missing the verb and instrument and 12 sentences missing the adjective and patient. The sentences were

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10 presented one at a time in a different random order for each participant. The participants were randomly assigned to each version of the cued-recall task, with half the participants completing one version and the other half completing the other version. For the recall task, participants were allowed to take as much time as they needed to complete the task.

Guessing

In order to assess the likelihood that a participant would be able to simply guess the missing parts of the sentences from the cued-recall task, a norming pretest was completed with twenty-two separate YAs who had not participated in the reading task portion of the experiment. These participants viewed the same items from the cued-recall task that the other participants completed. The participants were asked to fill in the blanks with words they felt best completed each sentence. On average, the participants provided the actual words from the common

condition less than 3% of the time and provided the actual words from the bizarre condition 0% of the time.

Analysis of Eye Tracks

For the purpose of better analyzing how time is allocated during reading, the sentences were divided into five regions of interest: intro, instrument NP (instrument noun phrase), VP (verb phrase), adjective, and patient. The intro region included the first two words of the sentence, which were always a proper name and the verb used (e.g., Bill used). The instrument NP region included the third and fourth words of the sentence, which were a determiner and instrument noun (e.g., a peeler). The VP region included the fifth and sixth words of the sentence, which were always an infinitival verb phrase (e.g., to slice). The adjective region included the seventh and eighth words of the sentence, which constituted a determiner and

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11 adjective (e.g., the green). The patient region was the ninth, and final, word of the sentence, which was always the patient noun (e.g., pear).

Analyses of reading-time effects focused on two standard eye-movement measures that reflect a range of processing stages: gaze duration and rereading duration (see Clifton, Staub, & Rayner, 2007; Rayner, 1998). Gaze duration is found by averaging the sum of the first-pass fixations for a word or region; the measure spans from when the word or region is first fixated on to when gaze is directed away from that word or region, regardless of the direction (left or right) that gaze is directed. Rereading duration (for the purpose of this study, referred to as second pass reading) is equal to the sum of all the fixations, on a word or region, that are not included in gaze duration. Unlike the gaze duration, second pass reading includes zeroes (i.e., trials in which the word was not re-fixated after first-pass reading).

An automatic procedure in the EyeLink software combined fixations that were shorter than 80 ms and within one character of another fixation into one fixation. Any remaining fixations that were either shorter than 80ms or longer than 1,000ms were removed. This was done to remove any fixations that were not a part of the task, such as fixations recorded after the subject had finished reading or fixations that occurred during blinking.

Results

Encoding Time

We conducted a 2 X 2 (Age Group: OA, YA) by (Sentence Type: bizarre, common) analysis of variance (ANOVA) on reading time, split by the five regions of the sentences. This was done for both gaze duration and second pass reading time. Table 1 presents the results of the

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12 inferential statistics for reading-time measures, while Figures 1 and 2 present descriptive results for gaze duration and second pass reading time respectively.

For gaze duration, Table 1 and Figure 1 show that there was a main effect of age such that OAs had longer gaze durations than YAs in all sentence regions. In contrast, sentence type only influenced gaze duration in the patient region, such that for the bizarre condition, gaze durations were longer (M = 295.1ms, SD = 60.8ms) than in the common condition (M =

268.3ms; SD = 53.7ms), F (1, 146) = 51.27, p < .001. However, as seen in Table 1, there was no interaction between sentence type and age group on gaze duration for any region of text.

For second pass reading time, Table 1 and Figure 2 show that there was a significant main effect of age group on second pass duration, such that OAs had longer second pass reading times than YAs in all sentence regions. Additionally, there was a significant main effect of sentence type on second pass reading times for all sentence regions, such that second pass reading times were longer for bizarre sentences than for common sentences. However, there was only a significant interaction between sentence type and age on second pass reading time for the verb phrase region, F (1,145) = 4.57, p=.034, and for the adjective region, F (1,146) = 7.34, p =.008, such that the difference on second pass reading times between bizarre and common sentences were greater for OAs than for YAs.

Memory Performance

To determine whether the effect of the type of sentence (bizarre vs. common) on recall differed as a function of age, we conducted a 2 (Sentence Type: bizarre, common) X 2 (Age Group: OA, YA) analysis of variance (ANOVA). There was a significant main effect of sentence type on recall, such that for the bizarre condition, recall was worse (M = .28, SD = .24) than in the common condition (M = .47; SD =.23), F (1, 146) = 102.56, p < .001. There was also a

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13 significant main effect of age on recall, such that OAs had worse recall (M = .26; SD = .44) than YAs (M = .44; SD = .50) F (1,146) = 28.90, p <.000. There was no interaction between age and sentence type on recall, F (1,146) = 1.04, p = .310.

Individual Differences

We ran separate factor analyses for YAs and OAs on individual difference measures that were most likely to load on common factors. These measures included ART, AVT, WAIS, MMSE, and VPA Total Recall. Table 2 shows the two-factor solutions obtained for OAs and YAs. We labeled the first factor “Knowledge Factor,” because, as seen in Table 2, this factor loaded most heavily on ART, AVT, and WAIS, which all test either knowledge of authors or of word meanings. We labeled the second factor “Memory Factor” because, as seen in Table 2, it loaded most heavily on MMSE and VPA Total Recall, which measure mental state and memory.

Table 3 shows correlations between the Knowledge and Memory Factors (also years of education for the OAs) with overall accuracy in cued recall as well as separate accuracy for recall of bizarre and common sentences. Because the patterns of correlation were similar for bizarre and common sentences, discussion will focus on the relationship between overall accuracy and individual differences measures. For YAs, recall was correlated with the

Knowledge Factor (p < .001), but not with the Memory Factor (p = .833). For YAs, since level of education was equal for all these participants, no correlations could be found with education. For OAs recall was correlated with both the Knowledge Factor (p = .002) and Memory Factor (p <.001). Recall also correlated with level of education for OAs (p = .014). The Knowledge Factor was not correlated with the Memory Factor for YAs (p = .175). However, for OAs, the

Knowledge Factor was correlated with education (p < .001) as well as with the Memory Factor (p = .005). Additionally, for OAs the Memory Factor was correlated with education (p = .025).

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14 Regression analysis was used to determine if either factor made unique predictions on recall. For YAs the Knowledge Factor was the only significant predictor of recall (t = 3.75; p <.001), accounting for 14.3% of the variance in cued recall. However, for OAs recall was predicted by both the Memory Factor (t = 3.33; p = .002), accounting for 23.1% of the variance in cued recall, and the Knowledge Factor (t = 2.13; p = .037), accounting for an additional 5.5% of the variance in cued recall. These results are supported by those shown in Table 3.

Discussion

In the current study sentence types were manipulated and tested for recall in order to assess the effects of aging on associative memory for information contained in sentences. This study focused on associative memory for sentences because, though associative memory has been shown to decline selectively with aging, memory for texts, which relies significantly on associative memory, shows less clear-cut evidence for aging-related decline (Chalfonte & Johnson, 1996). Prior research has found that OAs have significantly more trouble than YAs with binding small units of information and recalling these larger, more complex units of

information (Chalfonte & Johnson, 1996; Old & Naveh-Benjamin, 2008; Spencer & Raz, 1995). We believed that the manipulation of bizarre vs common sentence types would make it more difficult for participants to build associations between information presented in bizarre sentences and would negatively affect recall for these sentences.

Based on the prior research that found that OAs have more difficulty than YAs with both the encoding and recall of complex information, we expected to find a significant interaction of age and sentence type on cued recall. While we did not find a clear interaction, we did find a significant main effect of age on encoding times and recall, such that YAs had shorter gaze durations and second pass durations as well as better recall than OAs. We also found a

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15 significant main effect of sentence type on encoding times as well as recall, such that gaze

durations, second pass durations, and recall were all better for common sentences than bizarre sentences.

The strongest predictor of cued recall for YAs was the Knowledge Factor, which

included measures from ART, AVT, and WAIS. These measures are all related to knowledge of language and test either knowledge of authors or knowledge of vocabulary. For OAs, recall was most strongly predicted by the Memory Factor, which included measures from the MMSE and VPA. These two measures examine mental state and memory. These results suggest that for YAs stronger knowledge of language is more related than memory and mental state to better recall of text information. For OAs knowledge of language is less important to recall of text information, while memory and mental state are a much stronger predictor. This is significant to us because prior research on cognitive aging has shown that as healthy aging occurs, knowledge of language stays intact and even becomes stronger (Gordon, Lowder, & Hoedemaker, 2016; Laubrock, Kliegl, & Engbert, 2006; Rayner, Reichle, Stroud, Williams, & Pollatsek, 2006), while memory and other processes decline (Craik & Salthouse, 2008; Kemper & McDowd, 2008; Schaie & Willis, 2011). The results found in this study suggest that though knowledge of language is a predictor of recall, as seen in YAs and to a small degree in OAs, the effect of OAs’ equal or better knowledge of language on their recall is overshadowed by the negative effect of their worsening memory and mental state. The negative effect of worsening memory on recall can be used to explain our finding that OAs had worse performance on cued recall than YAs.

The main effect of age on encoding time, such that OAs had longer gaze durations and second pass reading times than YAs, can be explained in part by looking at the decline in various cognitive processes that occurs due to aging, such as with perception, attention, motor control,

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16 and memory. Reading relies heavily on these processes, and research has shown that, because of declines in cognitive processes such as these, OAs respond more slowly than YAs on a range of timed tasks (Grant & Dagenbach, 2000; Ratcliff, Thapar, & McKoon, 2001; Verhaeghen & Cerella, 2002). However, this slowing is not as pronounced in reading as it is in other tasks (Rayner et. al., 2006).

The finding that recall for bizarre sentences was worse than recall for common sentences is supported by research that has found that memory for complex information is worse than memory for simple information (Old & Benjamin, 2008; Chalfonte & Johnson, 1996). The bizarre sentences are more complex than the common sentences because the information

presented in these sentences are much less likely to fit schemas already present in the mind than the information presented in common sentences. Thus, the cues provided in the cued recall tasks are less likely to activate schemas and aid recall for bizarre sentences than for common

sentences.

Our finding of a main effect of sentence type on encoding, such that encoding times were longer for bizarre stimuli and recall was worse for bizarre stimuli, can be explained by the increased difficulty of binding unrelated information. As a person reads information presented in sentences, in order to comprehend the sentence they must relate the new information presented within each additional sentence region to the information from past sentence regions (Haberlandt et. al., 1986; Stine, 1990). The insertion of bizarre stimuli into these sentences interrupts the binding process by presenting information that cannot reasonably be bound to information presented in past sentence regions. As participants struggle to create associations between bizarre information and the rest of the sentence, encoding takes longer, resulting in greater gaze

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17 While we did not find a significant interaction of age and sentence type on gaze duration, we did find a significant interaction on second pass reading time for some regions. Second pass reading time is a measure of time spent rereading portions of the sentence. Our finding of this interaction implies that OAs spent significantly more time than YAs rereading information presented in bizarre sentences, but did not spend significantly more time than YAs rereading information presented in common sentences.

The lack of an interaction on gaze-duration or recall was surprising to us as we expected that since OAs have worse associative memory than YAs, especially with more complex

information, OAs would have much more significant differences from YAs with bizarre stimuli than common stimuli. Though we did find an interaction on second pass reading time, the lack of an interaction for gaze-duration means that we did not find a clear interaction effect on overall encoding time. Further research with a larger number of participants is needed to better

understand the effects of age and sentence type on encoding time.

Though we could not find any clear interaction of sentence type and age on recall, this does not mean that one does not exist. Many of our OAs recalled none or very few of the bizarre sentences. Thus, it is possible that the manipulation of sentence type in our study may have been too extreme, causing a floor effect to hide the effect of sentence type in the interaction.

Additionally, effects may have been hidden due to using too small of a sample size. Our findings do not support an interaction but point to the possibility that one could exist. If this study is replicated in the future with less extreme bizarre stimuli and a larger sample size, it is possible that a significant interaction between age and sentence type on recall and encoding time will be found.

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18 In this study, we found that associative memory for information presented in texts is worse for OAs than for YAs and worse for bizarre, nonsense sentences than for common, logical sentences. The observed effects of age on recall and on encoding time suggests that OAs may experience cognitive declines that cause their encoding time and recall for information presented in texts to be worse than that of YAs. Additionally, our results suggest that sentences that are more difficult to understand, such as bizarre sentences, may result in longer encoding processes and worse recall of the information presented in these sentences for all individuals, regardless of age. In order to understand whether or not there is an interaction of age and sentence type on recall and encoding time, more research may be needed. Future research on aging and associative memory for information presented in texts may make use of larger sample sizes and less extreme bizarre stimuli in order to ensure that if there is a lack of an interaction, it is not due to floor effects.

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23 Appendix

Table 1. Inferential statistics for reading time measures by sentence region. There is a significant main effect of sentence type (Biz.) on gaze duration for the patient region, and a significant main effect of age on gaze duration for all sentence regions. There is no interaction (Int.) between sentence type and age on gaze duration for any sentence region. There is a significant main effect of sentence type (Biz.) on second pass reading time for all sentence regions. Additionally, there is a significant main effect of age on second pass reading time for all sentence regions. There is an interaction of sentence type and age on second pass reading time for the verb phrase region and adjective region.

Intro Instrument VP Adjective Patient

F(1,146) p F(1,146) p F(1,145) p F(1,146) p F(1,146) p GZD (ms) Biz. .04 .848 1.35 .247 .00 .955 .67 .414 51.27 .000 Age 12.40 .001 18.22 .000 3.94 .049 7.51 .007 22.56 .000 Int. 2.23 .138 .09 .768 .55 .460 .34 .564 .00 .995 Second Pass (ms) Biz. 4.85 .029 13.23 .000 50.90 .000 80.29 .000 73.36 .000 Age 45.41 .000 42.18 .000 26.22 .000 35.20 .000 6.01 .015 Int. .18 .671 1.02 .315 4.57 .034 7.34 .008 .09 .771

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24 Figure 1. Mean gaze duration by sentence region. OAs have longer mean gaze durations than YAs for common sentences and bizarre sentences in all sentence regions. The patient region is the only region in which sentence type affects gaze duration.

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25 Figure 2. Mean second pass reading time by sentence region. OAs have longer mean gaze

durations than YAs for common sentences and bizarre sentences in all sentence regions. An effect of sentence type on second pass duration can be seen primarily in the verb phrase region and adjective region.

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26 Table 2. Individual differences factor analysis. For both YAs and OAs, the WAIS, AVT, and ART measures all loaded on Factor 1, the Knowledge Factor, while the MMSE and VPA Total Recall load on Factor 2, the Memory Factor.

YA OA Factor Factor 1 2 1 2 WAIS .789 .207 WAIS .729 .627 AVT .837 AVT .941 .314 ART .746 .154 ART .928 .258 MMSE .169 .810 MMSE .325 .752

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27 \

Table 3. Correlational analyses of recall with education, the Knowledge Factor, and the Memory Factor. For YAs, overall recall as well as recall for common stimuli and recall for bizarre stimuli individually are all significantly correlated with the Knowledge Factor, but not with the Memory Factor. For OAs, overall recall as well as recall for common stimuli are significantly correlated with education level. Additionally, for OAs, overall recall as well as recall for common stimuli and recall for bizarre stimuli are all correlated with both the Knowledge Factor and the Memory Factor.

Recall Recall.Com Recall.biz

YA Knowledge .378* .360* .304* Memory -.023 -.058 .014 OA Education .309* .311* .197 Knowledge .390* .338* .317* Memory .480* .456* .341* *. p < .05

Figure

Table 1. Inferential statistics for reading time measures by sentence region. There is a significant
Table 3. Correlational analyses of recall with education, the Knowledge Factor, and the Memory

References

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