Neurobiology of Learning and Memory 171 (2020) 107204

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Neurobiology of Learning and Memory

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Age-related emotional in associative memory consolidation: The role of sleep T ⁎ Sheng-Yin Huana, Kun-Peng Liua, Xu Leia, Jing Yua,b, a Faculty of Psychology, Southwest University, Chongqing, China b Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China

ARTICLE INFO ABSTRACT

Keywords: Sleep plays a crucial role in memory consolidation. However, the influence of sleep on emotional memory Aging consolidation in older adults, especially in the context of associative memory, which is more cognitively de- Sleep-related memory consolidation manding than item memory, remains elusive. For this study we recruited young and older adults, and randomly Associative memory assigned them into the sleep or wake condition. They were administrated a visual-spatial associative memory Emotional bias task, which required them to remember a picture and its location. We measured memory performance for po- Drift rate sitive, neutral, and negative stimuli before and after a 12-h interval of being awake or asleep. An accuracy analysis indicated a beneficial effect of sleep on location memory regardless of age and valence. In addition, in a more fine-grained analysis, the drift rate from diffusion modeling showed that sleep facilitated the consolidation of negative stimuli in young adults, while this bias shifted to positive stimuli in older adults. Moreover, negative correlations were observed between the change of memory performance and sleep characteristics in older adults, indicating that more sleep results in fewer negative memories. Our results provide a relatively weak support for an age-related emotional bias in the context of associative memory, manifested in the absence of an age-by-valence interaction in accuracy, whilst a modeling parameter in consideration of both accuracy and response time yielded evidence consistent with the predictions of the socioemotional selectivity theory.

1. Introduction & Spencer, 2016; Payne & Kensinger, 2010; Payne, Chambers, & Kensinger, 2012). Specifically, studies regarding beneficial effects of People can easily recall events to which strong emotion is attached, sleep have shown that young adults retain negative emotional stimuli like weddings, graduations, and intense arguments. In general, emo- better than neutral stimuli, since the negative information is more vital tional events are remembered with greater accuracy and vividness than for survival (Bennion, Payne, & Kensinger, 2015; Tempesta et al., 2017; neutral events. Emerging experimental evidence shows that memories Wagner, Degirmenci, Drosopoulos, Perras, & Born, 2005). However, not associated with the evocation of emotion, as defined by valence or/and all of the findings have reached the same conclusion, as a considerable by , are encoded and persist more strongly than memories number of studies did not find the moderation effect of sleep on emo- lacking affective tones (Chambers & Payne, 2014; Nishida, Pearsall, tional memory (Cellini, Torre, Stegagno, & Sarlo, 2016; Harrington, Buckner, & Walker, 2008). In recent decades, researchers have begun to Nedberge, & Durrant, 2018). In fact, two recent meta-analysis studies discuss the role of sleep in the consolidation of emotional memory. showed no overall effect for preferential sleep-related consolidation of Sleep benefits memory consolidation, as shown by the fact that post- emotional over neural stimuli (Lipinska, Stuart, Thomas, Baldwin, & learning memory performance is better after an interval of being asleep Bolinger, 2019; Schäfer et al., 2019), neither for the negative versus rather than an interval of being awake (Jenkins & Dallenbach, 1924; neutral nor for positive versus neutral. Nevertheless, both studies noted Stickgold, 2005; Walker & Stickgold, 2004). With respect to emotional that specific sleep stages (e.g., slow wave sleep or rapid eye movement memory, some previous studies have suggested that sleep plays a se- sleep), different variants of tasks (e.g., recall or recognition task), in- lective role in the consolidation of emotional stimuli. The facilitation of dices of memory performance (e.g., hit rate or d’), and sample char- sleep on memory may have a greater effect on emotional stimuli than acteristics (e.g., young or older adults) should be considered when we neutral stimuli, either after a nap (Alger, Kensinger, & Payne, 2018; discuss the role of sleep on emotional memory consolidation. Indeed, Nishida et al., 2008) or nocturnal sleep (Jones, Schultz, Adams, Baran, older adults’ emotion processing shows an age-specific sleep-related

⁎ Corresponding author at: Faculty of Psychology, Southwest University, Tiansheng Road, Beibei District, Chongqing 400715, China. E-mail address: [email protected] (J. Yu). https://doi.org/10.1016/j.nlm.2020.107204 Received 18 November 2019; Received in revised form 31 January 2020; Accepted 2 March 2020 Available online 04 March 2020 1074-7427/ © 2020 Elsevier Inc. All rights reserved. S.-Y. Huan, et al. Neurobiology of Learning and Memory 171 (2020) 107204 emotional consolidation pattern. calculate the effect of sleep (Lipinska, Stuart, Thomas, Baldwin, & Numerous studies have documented an age-related positivity effect Bolinger, 2019), and these indices were often considered in- manifested as older adults exhibiting increasing cognitive processing of dependently. However, young and older adults may have different positive as opposed to negative stimuli across cognitive domains, such trade-offs between response time and accuracy, especially with asso- as memory (Carstensen & Mikels, 2005), (Mather & ciative memory. Here we used the diffusion model (Ratcliff, 1978; Carstensen, 2005), and decision making (Löckenhoff & Carstensen, Ratcliff & McKoon, 2008) to provide a combined explanation from re- 2004). Recently, researchers have adopted sleep-related consolidation sponse time and accuracy on age-by-valence effect of sleep-related paradigms to investigate the possible age-related emotional bias of the consolidation. The diffusion model is frequently used to decompose beneficial effect of sleep. For example, Jones et al. (2016) found a va- performance in forced two-alternative choice tasks (e.g., old or new) lence-based dichotomy in the function of sleep on emotional memory, into underlying processes of decision making, where noisy information in that negative (but not positive) memory was facilitated by sleep in from a stimulus is accumulated over time from a starting point until a young adults, whereas positive (but not negative) memory was fa- boundary (i.e., old or new) is reached, at which point a response is cilitated by sleep in older adults. In line with this finding, Gui et al. executed. Among all the parameters reported by model, we focused on (2019) used a within-subject experiment design and found that sleep the drift rate (v) to do the following analyses. This index models the selectively enhanced positive memory in older adults, whereas sleep efficiency with which information could be integrated across trials to enhanced neutral memory in young adults. Both these studies in- approach a boundary (Fig. 3a). High drift rate reflects more efficient vestigated the age-related selective role of sleep in emotion in the information integration, manifested as a steeper approach toward one context of item memory. In the present study, we aim to further explore of the two boundaries (Ratcliff & McKoon, 2008, 2015). The drift rate whether this positive preferential effect of sleep consolidation in older thus captures memory strength, or discriminability, and is related to the adults can still be observed in the context of associative memory, which memory accuracy. Older adults tend to emphasize accuracy more than is more cognitively demanding than item memory (Balota, Dolan, & young adults relative to response time (Ratcliff & McKoon, 2015; Duchek, 2000; Naveh-Benjamin, 2000). Two previous meta-analysis Salthouse, 1979), which could result in small or non-significant effects studies have shown that task characteristics should be considered when of age on accuracy. Therefore, we adopted the drift rate index in order we discuss the age-related positivity effect. First, the positivity effect is to account for speed/accuracy tradeoffs. Moreover, the role of sleep is larger in studies that do not constrain (i.e., instructing participants to to downscale synaptic strength to a baseline level that could increase remember all information) cognitive processing, like instructing parti- signal-to-noise ratio of information processing (Tononi & Cirelli, 2006). cipants to view images as they would a TV, which could reflect older The diffusion model allows prediction of the response time distribution adults’ natural information processing references (Reed, Chan, & under different contexts and various levels of noise (Ratcliff & Mikels, 2014). Second, within constrain tasks, recognition studies were Tuerlinckx, 2002). In the context of sleep, previous studies have shown observed with significant age differences, as older adults showed less that vulnerable participants have significantly lower drift rate than non- negativity preferences than young adults, whereas there was no salient vulnerable participants after one night of sleep deprivation (Patanaik, age-by-valence interaction in recall studies (Murphy & Isaacowitz , Zagorodnov, Kwoh, & Chee, 2014). Diffusion modeling appears to have 2008). In our study, we adopted a visual spatial associative memory promise in predicting and dissociating cognitive processes with respect task (Lecerf, Ribaupierre, & Anik, 2005; Mather et al., 2006), in which to sleep (Patanaik et al., 2014; Ratcliff, Dongen, & Hans, 2011). participants were instructed to remember a picture and its location. In Our goal is to investigate the possible age-by-valence effect on sleep- the recognition phase, participants were required to have old/new related consolidation in the context of associated memory, which has judgment in the first step, and then if participants recognized an item as been previously demonstrated in the context of item memory (Gui old, they had to further indicate in which quadrant they believed the et al., 2019; Jones et al., 2016). Moreover, in addition to the tradi- item had been presented. As this paradigm is a cognitive constrain and tionally used index of accuracy, we also included the drift rate index recognition/recall mixed task, according to the findings from the from the diffusion model to further address a possible effect of a speed/ aforementioned meta-analyses, we hypothesized that the age-by-va- accuracy tradeoff. Based on previous evidence, we predict that (1) the lence interaction of sleep beneficial effects could be weak or even not accuracy analysis may exhibit weak or non-salient age-by-valence ef- salient in the context of associative memory. fect, since associative memory is not the optimal task in which the age- Most previous sleep-related consolidation research has used like- related positive effect can be observed; (2) the drift rate (v) reported by lihood ratio, hit rate, false alarm rate, accuracy, or response time to the diffusion model could reflect the performance of task, manifested as

Table 1 Participants’ characteristics and neuropsychological data.

YW M (SD)YSM (SD) YW vs. YS (p-value) OW M (SD)OSM (SD) OW vs. OS (p-value) Young vs. old (p-value)

Age 20.67(1.54) 20.87(1.76) 0.33 66.87(3.56) 66.53(4.81) 0.39 < 0.001 Education (years) 14.67(1.79) 15.27(1.70) 0.69 8.93(3.42) 10.02(2.67) 0.27 < 0.001 MMSE –– – 27.48(2.89) 28.33(1.75) 0.62 – SDS 36.53(7.90) 34.40(7.48) 0.09 31.07(5.77) 37.41(7.89) 0.90 0.23 SAS 33.67(6.03) 32.40(6.78) 0.71 32.20(6.03) 29.00(5.71) 0.79 < 0.05 ISI 7.03(5.22) 8.00(5.91) 0.92 4.90(5.26) 5.24(4.93) 0.23 0.05 PSQI 5.63(1.85) 5.73(2.79) 0.15 6.23(3.23) 6.70(4.00) 0.47 0.24 MEQ 51.37(7.13) 45.73(8.02) 0.15 67.77(5.51) 65.62(6.25) 0.27 < 0.001 SE (%) – 86.39(1.32) ––85.99(1.46) – 0.44 WV (min) – 2.95 (0.29) ––4.38 (0.54) – < 0.05 WASO (min) – 54.8 3(6.45) ––44.92(8.34) – 0.59 WE (num.) – 19.00(1.30) ––14.14(1.41) – 0.83 TST (min) – 369.40(8.72) ––371.48(8.34) – 0.71 TTB (min) – 429.23(10.02) ––430.83(9.96) – 0.59

Note: YW, young adults in the wake condition; YS, young adults in the sleep condition; OW, older adults in the wake condition; OS, older adults in the sleep condition; MMSE, the mini-mental state examination; SDS, the self-rating scale; SAS, the self-rating scale; ISI, the insomnia severity index; PSQI, the Pittsburgh sleep quality index; MEQ, the morningness-eveningness questionnaire; SE, sleep efficiency; WV, wake variance; WASO, wake after sleep onset; WE, wake episodes; TST, total sleep time; TTB, total time in bed.

2 S.-Y. Huan, et al. Neurobiology of Learning and Memory 171 (2020) 107204 a high correlation with participants’ accuracy; (3) Model-based analysis negative (arousal, 5.44 ± 0.16), and neutral valence (arousal, could be more sensitive than accuracy analysis. Drift rate (v) would be 5.33 ± 0.19; F (2, 69) = 2.86, p = 0.06). Half of the 72 pictures were modulated by age and sleep; thus, the sleep-related emotional con- learned during the study phase, and the other half served as new items solidation bias will be observed accordingly. during the recognition phase.

2. Method 2.3. Procedure

2.1. Participants The experiment consisted of 2 sessions. In the first session, partici- pants were required to learn the pictures and their locations either in Participants included 60 young adults (aged 19–23) and 60 older the morning (7:30 AM-9:30 AM; the wake condition), or in the evening adults (aged 61–71). Young adults were university students, and older (7:30 PM-9:30 PM; the sleep condition), followed immediately by a adults were recruited from nearby communities. Participants reported recognition test (i.e., pre-test). The second session was a retest (i.e., no history of neurological diseases or psychiatric conditions. Older post-test) conducted 12 h later (Fig. 1a). adults were administered the Mini-Mental State Examination (MMSE), Participants first were instructed to complete a battery of neu- and whoever had a score below 26 were not recruited for the study. ropsychological assessments, including the Pittsburgh sleep quality Participants were instructed to remain free of caffeine, drugs, and al- index (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989), the self- cohol, and refrain from napping in the daytime during the study period. rating depression scale (Zung, 1965), the self-rating anxiety scale Participants were randomly assigned to the wake and sleep condition. (Zung, 1971), the insomnia severity index (Morin, Belleville, Bélanger, The demographic and neuropsychological characteristics of each age & Ivers, 2011), and the morningness-eveningness questionnaire (Horne group for each experimental condition are shown in Table 1. Partici- & Östberg, 1975). Then, they were instructed to complete a visual- pants in the wake and sleep condition were matched in demographic spatial memory task (Ladenbauer et al., 2016). For each trial, first there and neuropsychological characteristics across age groups at baseline. was a fixation presented for 1000 ms. Then a grey square appeared as a Older adults were less educated and more morningness-oriented com- cue in one of four possible quadrants on the screen for 2000 ms. This pared with young adults; thus, we controlled education and the was followed by a picture in that square for 2000 ms. Participants were morningness-eveningness tendency for further analyses. required to remember both the picture and the location in which it was presented (Fig. 1b). In total, during the encoding phase, participants 2.2. Materials learned 36 pictures (12 positive, 12 negative, and 12 neutral) twice. The items were pseudo-randomly presented, such that the same valence We selected 72 pictures from the International Affective Picture trials occurred consecutively, at most, three times. During recognition, System (IAPS; Lang, Bradley, & Cuthbert, 1997), with 24 pictures for following a fixation, a picture (studied or unstudied) was displayed in each of positive (valence, 7.06 ± 0.34), negative (valence, the center of the screen for 2000 ms. Then participants were asked to 2.48 ± 0.63), and neutral valence (valence, 5.05 ± 0.33). Because we press one of two keys (“old” or “new”) in order to indicate whether they focused on the valence aspect of emotion, it is important to note that we had seen this picture before. If they recognized the picture as “old,” matched the ratings of arousal among positive (arousal, 5.40 ± 0.11), they needed to further indicate in which quadrant they believed the

Fig. 1. Experimental procedure and memory task. (a) Encoding phase was conducted either in the morning (wake condition) or in the evening (sleep condition) followed by an immediately recognition (pre-test) and a post-test after a 12-h sleep/wake interval. (b) The associative memory task includes encoding and re- two phases. During encoding, participants were told to remember both the picture and the location of it. During recognition, participants first needed to decide whether the presented picture was learned before, if yes, then they needed to indicate its location during learning.

3 S.-Y. Huan, et al. Neurobiology of Learning and Memory 171 (2020) 107204 picture had been presented. If they indicated the picture as “new,” it young adults in the sleep condition, older adults in the wake condition, would move on to the next recognition trial (Fig. 1b). In the recognition and older adults in the sleep condition), are 0.6%, 1.9%, 3.5%, and phase, participants viewed 72 pictures with half of them being novel 2.0% respectively. For the post-test, the elimination rates of responses foil pictures. for the four experiment groups are 2.6%, 2.8%, 4.8%, and 3.9% re- Participants were asked to wear an Actigraph (Bluetooth® Smart spectively. wGT3X-BT) on their non-dominant wrist to record their nocturnal sleep. Sleep parameters, such as total sleep time, sleep latency, sleep/ 3.1. The accuracy of picture and location memory wake pattern throughout the night with a sleep efficiency score, were retrieved from sense wear software (Actigraph 6). Data processing and The accuracy change of picture memory (post-test –pre-test) after a thus frequency filtering was moved into the analysis software ActiLife 12-h interval was assessed with an age × condition × valence three- to provide flexible and off-line handing. We calculated the variables of way repeated-measure ANOVA. The result only yielded a significant total sleep time (TST), sleep efficiency (SE), total time in bed (TTB), interaction effect of age × condition (F (1, 115) = 5.23, p < 0.05, 2 wake variance (WV), wake episodes (WE) and wake after sleep onset ɳp = 0.45). Further, the simple effect analysis showed that, for the (WASO) for further analyses. sleep condition, picture memory decline is less in young adults than in older adults (t = 4.12, p < 0.05); for the wake condition, there was no 2.4. Data analysis difference between two age groups (t = 0.02, p = 0.90), which in- dicates that older adults’ picture memory may benefit less from sleep The change of memory accuracy (post-test – pre-test) after a 12-h than their younger counterparts (Fig. 2a). No other significant main interval was assessed with three-way repeated-measure ANOVAs, with effects or interactions were observed. age (young versus old) and condition (sleep versus wake) as between- The accuracy change of location memory (post-test – pre-test) was subject factors, and valence (negative versus positive versus neutral) as also assessed with an age × condition × valence three-way repeated- a within-subject factor. The accuracy change of picture and location measure ANOVA. The result showed that the significant main effect is was calculated respectively. Moreover, the drift rate (v) derived from condition, as participants in the sleep condition had less accuracy de- the EZ-diffusion model (Wagenmakers, Van Der Maas, & Grasman, cline than participants in the wake condition (F (1, 115) = 4.93, 2 2007) was calculated for picture memory in the pre-test and in the post- p < 0.05, ɳp = 0.04; Fig. 2b). No other significant main effects or test, and a three-way repeated-measure ANOVAs, with age and condi- interactions were observed. The accuracy and reaction times for picture tion as between-subject factors and valence as a within-subject factor, and location memory in each condition of young and older adults are was conducted respectively. In the present study, we did not calculate provided in the supplementary for reference (Table S1). Together, as the drift rate for location memory, since the EZ-diffusion model is re- predicted, no age-by-valence effect was found for the role of sleep on stricted for two-choice tasks, whereas location memory was similar to a emotional stimuli in the context of associative memory, and the sleep recall task with four possible options. Next, we conducted correlation beneficial effect on location memory was found regardless of age. analyses between the drift rate and accuracy of both picture and loca- Supplementary data associated with this article can be found, in the tion for young and older adults respectively. Also, we conducted cor- online version, at https://doi.org/10.1016/j.nlm.2020.107204. relation analyses between sleep and memory performance. Statistical analyses were performed using SPSS Version 22.0 (IBM Corporation, 3.2. The drift rate of picture memory Armonk, NY, USA), and the diffusion modeling was conducted with Matlab 2018a (MATLAB 2018a, Natick, MA). Drift rates (v) represent an individual’seffectiveness to access in- formation from the stimuli, and a higher drift rate indicates a stronger 3. Results ability to integrate information. For the drift rate of picture memory, we conducted an age × condition × valence three-way repeated-measure Responses shorter than 200 ms were eliminated from analyses, as ANOVA for the pre-test and the post-test. For the pre-test, the result were responses longer than 1500 ms for young adults and longer than showed a significant main effect of age (F (1,115) = 5.46, p < 0.05, 2 2000 ms for older adults. Older adults’ have relatively longer response ɳp = 0.05), in that older adults’ drift rate (0.17 ± 0.01) was lower time than young adults, so different cutoff values were chosen based on than young adults (0.24 ± 0.01; Fig. 3b). No other main effects or the performance of the different age groups (Ratcliff, Voskuilen, & interactions were observed, suggesting that participants’ memory McKoon, 2018). For the pre-test, the elimination rates of responses for strength was matched between conditions (sleep versus wake) at the four experiment groups (i.e., young adults in the wake condition, baseline. For the post-test, the result found a significant three-way

Fig. 2. The accuracy change of memory after a 12-h interval of wake or sleep condition. (a) The accuracy change of picture memory for four groups in each valence. There was an interaction between age and condition that in the sleep condition older adults benefited less from sleep than young adults, whereas there was no age difference in the wake condition. (b) The accuracy change of location memory for four groups in each valence. There was a main effect of condition that participants benefited more from sleep for the consolidation of location memory compared with wake interval. Note: YW, young adults in the wake condition; YS, young adults in the sleep condition; OW, older adults in the wake condition; OS, older adults in the sleep condition.

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Fig. 3. The drift rate of picture memory in the pre-test and post-test. (a) Illustration of the diffusion model. (b) The drift rate of picture memory in the pre-test. Beside the main effect of age, there was no difference among different conditions and valences. (c) The drift rate of picture memory in the post-test after a 12-h interval in wake or sleep. There was an interaction effect between age, condition and valence, shown as the negative valence of pictures obtained higher drift rate than positive pictures in young adults, whereas for older adults the positive valence of pictures obtained higher drift rate than both negative and neutral pictures after sleep. Note: YW, young adults in the wake condition; YS, young adults in the sleep condition; OW, older adults in the wake condition; OS, older adults in the sleep condition. interaction effect of age × condition × valence (F (2, 230) = 5.27, change of negative valence of location memory was negatively related 2 p < 0.01, ɳp = 0.05). The further simple effect analysis showed that with the total time in bed in older adults (r = −0.53, p < 0.01; FDR after sleep, the negative valence of pictures obtained a higher drift rate corrected, p = 0.01), whereas this correlation was not significant in than positive pictures in young adults (t = 4.78, p < 0.01), whereas young adults (r = −0.21, p = 0.27; Fig. 5b). These results indicate that for older adults the positive valence of pictures obtained a higher drift with increasing sleep quantity, older adults’ negative valence of rate than both negative (t = 2.99, p < 0.05) and neutral pictures memory decreased accordingly. This association was only observed in (t = 4.98, p < 0.001; Fig. 3c). However, no valence effect (F (2, older adults, but not in their younger counterparts. 2 114) = 0.47p = 0.63, ɳp = 0.01) nor age × valence interaction (F (2, ɳ 2 114) = 0.20, p = 0.82, p < 0.01) were observed in the wake con- 4. Discussion dition. These results indicated that the sleep interval facilitated the consolidation of positive pictures in older adults, and it facilitated the In the current study, we investigated the age-related differences of consolidation of negative pictures in young adults. sleep-related consolidation on emotional stimuli in the context of as- Next, the correlation analyses showed that the drift rate was sig- sociative memory. With traditional accuracy analysis, we found a nificantly correlated with the accuracy of picture memory in both age beneficial effect of sleep on location memory regardless of age and groups with a mean correlation r of 0.58 and the lowest pairwise cor- valence. However, with a more fine-grained analysis that provides a relation r of 0.33. Meanwhile, the drift rate was also significantly cor- goodness-of-fit index, integrated accuracy and response time, an age- related with the accuracy of location memory with a mean correlation r by-valence interaction was observed, manifested as the finding that of 0.46 and the lowest pairwise correlation r of 0.18 (Fig. 4). sleep facilitated the consolidation of negative stimuli in young adults, while it facilitated the consolidation of positive stimuli in older adults. 3.3. The correlation between sleep and memory performance To the best of our knowledge, this is the first study that has in- vestigated the emotional bias of sleep-related memory consolidation In the sleep condition, the accuracy change of negative valence of with aging under an associative memory paradigm. Unlike the findings picture memory was negatively related with the total sleep time in older from the item memory paradigm (Gui et al., 2019; Hu, Stylos-Allan, & adults (r = −0.39, p < 0.05; marginally significant after FDR cor- Walker, 2006; Jones et al., 2016), which suggested a salient age-by- rection, p = 0.08), whereas this correlation was not significant in valence interaction effect on memory consolidation, the accuracy ana- young adults (r = 0.15, p = 0.43; Fig. 5a). In addition, the accuracy lysis of associative memory yielded no significant age nor valence

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Fig. 4. This integration plot shows the histograms, correlations, and scatter plots between the drift rate and accuracy of picture and location memory for young and older adults. It shows that the drift rate was significantly correlated with the accuracy of picture and location memory in both age groups. The diagonal plots are histograms of corresponding values (i.e., picture memory, location memory, and drift rate v in three valences). In each plot, the panels above and to the right of diagonal show the correlation r, and the size of the number represents the strength of correlation. The panels below and to the left of diagonal show the scatter plots and each dot represent an individual participant. The identity of comparison in each off-diagonal plot or correlation is obtained moving vertically and horizontally from the task labels in the corresponding diagonal plots.

Fig. 5. Relationships between sleep and memory performance. (a) The correlation between the accuracy change of negative picture memory and total sleep time in young and older adults respectively. (b) The correlation between the accuracy change of negative location memory and total time in bed in young and older adults respectively.

6 S.-Y. Huan, et al. Neurobiology of Learning and Memory 171 (2020) 107204 effect, but only a main effect of sleep on location memory. This null We also calculated the correlation between participants’ change of effect is not unusual considering the methodology and stimulus para- memory accuracy and their sleep characteristics. There was no sig- meters. First, associative memory relative to item memory needs more nificant association in young adults, whereas negative associations cognitive consumption and mixes with recognition (i.e., picture were found between the change of picture memory in negative valence memory) and recall (i.e., location memory) in the current paradigm. As and total sleep time, and between the change of location memory in previous meta-analysis studies suggested, tasks with more cognitive negative valence and total bed time in older adults. For young adults, processing constraints (Reed, Chan, & Mikels, 2014) and recall rather the change of memory accuracy was more centralized around zero than than recognition (Lipinska, Stuart, Thomas, Baldwin, & Bolinger, 2019; older adults (Fig. 5), which indicates that the difference between pre- Rhodes et al., 2019) typically give rise to smaller or even non-age dif- test and post-test was small in young adults. It is similar to the ceiling ference on emotional bias. The socioemotional selectivity theory (SST; effect, which states that there is small room for young adults to enhance Carstensen, Fung, & Charles, 2003; Carstensen, Isaacowitz, & Charles, their memory performance through sleep. For older adults, the negative 1999) posits that older adults deploy cognitive control to avoid nega- association between memory and sleep is interesting and somewhat tive information and to seek out positive information in order to purse controversial for our understanding of sleep’s beneficial role on con- their emotion goals (rather than their knowledge acquisition goals). solidation. It must be noted that the negative associations only stand for Thus, when older adults are imbued with goals that conflict with their negative memories in older adults, illustrated as more sleep resulting in chronically activated emotion goals, like here, they need to allocate fewer retained negative memories. One possibility is that this decrease most of their cognitive resources on remembering in the context of the of negative memory is a result of passive abandonment. With degen- associative memory paradigm, so the age-related positivity effect may erative alterations of neurons in older adults, limited neural resources not be observed. Second, we matched the arousal aspect of emotion to may allocate on positive memory reactivation, while the remaining discuss the valence aspect of emotion in this study, which could also resources would be left for negative memories. Another possibility is weaken the age-related emotion bias exhibited in previous studies. As that this decrease of negative memory is a result of active regulation. in the studies of Gui et al. (2019) and Jones, Mackay, Mantua, Schultz, During sleep, the learned materials could be redressed and reorganized and Spencer (2018, 2016), they did not control the arousal aspect of (Backhaus et al., 2007; Cherdieu et al., 2014). As for older adults, they emotion, manifested as emotional (i.e., positive and negative) stimuli might regulate their negative memories and distort them into less ne- with higher arousal rating than neutral stimuli. Jones et al. especially gative ones in order to achieve an emotional goal. With the metho- found that sleep not only preserved memory, but also preserved parti- dology of neuroimaging, including functional magnetic resonance cipants’ emotion ratings including both aspects of valence and arousal. imaging (fMRI), positron emission tomography (PET), and magne- Most importantly, the emotion rating was also moderated by age, with toencephalography (MEG), future work could directly verify these as- only negative emotion rating retained in young adults and only positive sumptions by the illustration of potential neuroendocrine and neural emotion rating retained in older adults, which could be an underlying circuits underlying these age-related differences. correlate emphasizing the age-related emotional bias reflected in their Limitations of this study should be considered. First, the diffusion sleep-related consolidation. Third, there could be another possibility model we used in the current study is restricted to a two-alternative that the index might not be sensitive enough. A shortcoming of accu- option task, so we cannot compare the performance between picture racy-based modeling approaches is that they do not account for re- memory and location memory from the aspect of drift rate. Future sponse time data. Thus, in this study we also conducted diffusion studies could consider a variant associative memory paradigm, for ex- modeling in an attempt to overcome this limitation (Ratcliff, 1978; ample, changing the location memory into a recognition task in order to Ratcliff & McKoon, 2015; Ratcliff, Voskuilen, & McKoon, 2018). investigate the age differences on item and associative memory by drift With diffusion modeling, we found that the drift rates were matched rates directly. Second, we used wrist actigraphy to collect sleep data in between the sleep and wake condition, and at baseline we only found the present study. It is unable to differentiate subdivided sleep structure an effect of age, suggesting that in the context of associative memory, or activity, although it is convenient for data collection and minimizes older adults exhibited less memory strength compared with younger the influence of experimental manipulation on normal sleep. In order to adults regardless of valence. After a 12-h interval of being asleep or illustrate the underlying mechanisms between the age-related emo- awake, an age-by-valence interaction was found in emotional memory tional memory alterations and sleep characteristics, it is more ideal for consolidation, with sleep facilitating the negative memory consolida- future studies to use actigraphy as well as polysomnography to collect tion in young adults and positive memory consolidation in older adults. more comprehensive sleep data. Finally, this is a between-subject de- This result is in line with the previous finding (Gui et al., 2019), which sign, which could involve disadvantages, such as individual variability. states that although the age-related emotional preferences were absent In the present study, the drift rate between sleep and wake condition at the baseline, it showed up after a nocturnal sleep. Emotional memory was matched across and within age groups, which would reduce the consolidation is facilitated by the bidirectional connections between the impact of individual differences brought by between-subject design. In hippocampus and (Diekelmann, Wilhelm, & Born, 2009; of its limitations, between-subject design is often used in the AM- McGaugh, 2004; Payne & Kensinger, 2010). The “hippocampal-neo- PM paradigm, and a recent meta-analysis showed that the experiment cortical dialogue” posits that the hippocampus reactivates during sleep design (between-subject versus within-subject) was not a significant and transfers information to long-term storage in the neocortex moderator in the e ffect of sleep-related consolidation (Gui et al., 2017). (Cherdieu, Reynaud, Uhlrich, Versace, & Mazza, 2014; Mueller & Weiner, 2009; Spencer, Walker, & Stickgold, 2017; Walker, Stickgold, 5. Conclusion Alsop, Gaab, & Schlaug, 2005). The reactivation of the hippocampus may also induce the activity of the amygdala, which could also re- To conclude, our results provide relatively weak support for an age- activate and reinforce the emotion processing. Moreover, this link be- related emotional bias in an associative memory context. This is shown tween the hippocampus and amygdala might be moderated by age, in that although there is an absence of an age-by-valence interaction in shown in the present study as negative preference in young adults and accuracy, a finer-grained analysis with the consideration of both ac- positive preference in older adults. This finding is aligned with the curacy and response time yielded evidence consistent with the predic- prediction of SST that sleep selectively consolidating positive memories tions of the SST (Carstensen, Fung, & Charles, 2003; Carstensen, might underlie older adults’ general better emotional well-being in Isaacowitz, & Charles, 1999; Carstensen & Mikels, 2005). This shift of daily life, while sleep selectively consolidating negative memories emotional preferences from negative to positive memories during sleep might underlie young adults’ knowledge acquisition for more in- could be crucial in clarifying older adults’ emotion goal posited in the formative or adaptive value of stimuli (Jones et al., 2016). SST and the general enhanced emotional well-being in daily life. Our

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