Sleep, Cognition, and Normal Aging

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PPSXXX10.1177/1745691614556680Scullin, BliwiseSleep, Cognition, and Aging research-article5566802014

Perspectives on Psychological Science 2015, Vol. 10(1) 97–137 Sleep, Cognition, and Normal © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav Aging: Integrating a Half Century of DOI: 10.1177/1745691614556680 Multidisciplinary Research pps.sagepub.com

Michael K. Scullin1,2 and Donald L. Bliwise2 1Department of Psychology and Neuroscience, Baylor University, and 2Department of Neurology, Emory University School of Medicine

Abstract Sleep is implicated in cognitive functioning in young adults. With increasing age, there are substantial changes to sleep quantity and quality, including changes to slow-wave sleep, spindle density, and sleep continuity/fragmentation. A provocative question for the field of cognitive aging is whether such changes in sleep physiology affect cognition (e.g., memory consolidation). We review nearly a half century of research across seven diverse correlational and experimental domains that historically have had little crosstalk. Broadly speaking, sleep and cognitive functions are often related in advancing age, though the prevalence of null effects in healthy older adults (including correlations in the unexpected, negative direction) indicates that age may be an effect modifier of these associations. We interpret the literature as suggesting that maintaining good sleep quality, at least in young adulthood and middle age, promotes better cognitive functioning and serves to protect against age-related cognitive declines.

Keywords memory consolidation, epidemiology, napping, sleep deprivation, actigraphy, polysomnography, neuropsychology, sleep pharmacology

Across an 85-year life span, an individual may sleep whether aging moderates the association between sleep nearly 250,000 hours, or over 10,000 full days. People and memory. often disparage time spent sleeping as “lost” time, but the The present article focuses on sleep’s implications for persistent internal drive to sleep and its presumed univer- cognitive aging. Referring back to the estimate of 250,000 sality across species would suggest that sleep is purpose- hours of sleep in a lifetime, a few assumptions become ful. Sleep-science pioneer Allan Rechtschaffen put it most evident. First, this estimate assumes 8 hours of sleep per eloquently: “If sleep does not serve an absolutely vital night, but sleep duration often declines across the life function, then it is the biggest mistake the evolutionary span (Bliwise, 1993). Furthermore, as depicted in Figure 1, process has ever made” (Rechtschaffen, 1971, p. 88). sleep quality may change dramatically from young to Sleep does serve many functions, and these range older age: Sleep becomes more fragmented (i.e., older from tissue restoration (K. Adam & Oswald, 1977) to adults wake up more at night; e.g., Bliwise et al., 2009), brain-metabolite clearance (Xie et al., 2013). Of particu- and there is a decline in the quantity and quality of the lar interest to psychological scientists is sleep’s role in “deep” stages of sleep, such as slow-wave sleep (SWS) cognitive functioning. Sleep loss has long been recog- and REM sleep (Ohayon, Carskadon, Guilleminault, & nized to impair performance on attention and execu- Vitiello, 2004). tive-control tasks (see Bonnet, 2011, for a review). The If sleep functions to benefit memory and cognition in more exciting possibility, however, is that normal sleep young adults, but is substantially altered in quantity and might actively promote memory stabilization and integration (see Table 1 for theories of the relation between Corresponding Author: sleep and memory), and this hypothesis has been sup- Michael K. Scullin, Department of Psychology and Neuroscience, ported across a diversity of psychological tests in young Baylor University, One Bear Place, #97334, Waco, TX 76798 adults (see the Appendix). A topic of current interest is E-mail: [email protected]

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Table 1. Influential Theories of the Relation Between Sleep and Memory

Theory name Description References Interference Sleep passively protects memories against daytime Jenkins and Dallenbach (1924) interference System consolidation The hippocampus reactivates memories and transfers them Marr (1971); McClelland, McNaughton, to neocortical regions, primarily during sleep and O’Reilly (1995) Synaptic consolidation Hippocampal long-term potentiation, primarily induced Bramham and Srebro (1989) during REM sleep, strengthens synaptic representations of memories Dual-stage consolidation SWS promotes episodic-memory consolidation, and REM Plihal and Born (1997) sleep promotes procedural-memory consolidation Multiple trace Each memory reactivation results in a new—but altered Nadel and Moscovitch (1997); Nadel, and distributed—memory trace, rendering retrieval Hupbach, Gomez, and Newman-Smith increasingly easier (2012) Synaptic homeostasis Sleep promotes global downscaling of synaptic weights, Tononi and Cirelli (2003) resulting in an improved signal-to-noise ratio for memories Permissive/opportunistic Sleep affords an environment conducive to, but not Wixted (2004); Mednick, Cai, Shuman, consolidation necessary for, consolidation Anagnostaras, and Wixted (2011) Recovery and stabilization Sleep stabilizes memories and recovers performance Brawn, Fenn, Nusbaum, and Margoliash following daytime interference (2010) Selective consolidation Only memories tagged as “relevant” during encoding are Stickgold and Walker (2013) reactivated during sleep and consolidated

Note: Theories are listed chronologically. For further critical review of these theories, see Ellenbogen, Payne, and Stickgold (2006) and Frankland and Bontempi (2005). SWS = slow-wave sleep.

quality across the life span, then an alluring question is breadth of this review and the depth of each literature whether life-span changes in sleep contribute to the included. To foreshadow, some literatures produce curi- widespread changes in cognitive functioning commonly ous findings (e.g., that sleep deprivation affects young observed in older adults (for an overview of cognitive adults more than older adults), whereas other literatures aging, see Cabeza, Nyberg, & Park, 2005). If so, then highlight the potential for augmenting sleep (e.g., via improving sleep might delay or reverse cognitive aging, afternoon naps) to benefit cognitive functioning in mid- as many authors have suggested (Altena, Ramautar, Van dle-aged adults. We contend that these seven literatures Der Werf, & Van Someren, 2010; Bruce & Aloia, 2006; provide complementary perspectives on how sleep and Buckley & Schatzberg, 2005; Cipolli, Mazzetti, & Plazzi, cognition interact as we age. 2013; Cirelli, 2012; Engel, 2011; Fogel et al., 2012; Göder Wherever possible, we discuss findings separated & Born, 2013; Harand et al., 2012; Hornung, Danker- across young (18–29 years old), middle-aged (30– Hopfe, & Heuser, 2005; Kronholm, 2012; Pace-Schott & 60 years old), and healthy older (≥60 years old) adult Spencer, 2011; Rauchs, Carrier, & Peigneux, 2013; Vance, groups (Roebuck, 1979). By doing so, we can begin to Heaton, Eaves, & Fazeli, 2011; Wilckens, Erickson, & address whether age modifies sleep–cognition associa- Wheeler, 2012). This “sleep–cognition hypothesis” tions. Given our focus on “normal” aging, we consider (Feinberg & Evarts, 1969) has previously been challeng- studies of abnormal aging (e.g., in patients with demen- ing to verify because sleep, cognition, and aging repre- tia, insomnia, or sleep apnea; e.g., Cipolli et al., 2013) as sent three topics that are individually extremely rich, well as developmental studies (e.g., Kopasz et al., 2010) deeply broad, and diversely complex. to be beyond the scope of this review. Finally, to ensure To fully address the question of whether age-related that positive findings constitute strong supportive evi- changes in sleep may be associated with age-related dence, we have employed the conservative approach of changes in cognition, we have taken an integrative, mul- reporting results following adjustment for demographics tidisciplinary approach that incorporates experimental, and comorbidities whenever possible. clinical-neuropsychological, and epidemiological literatures. Here, we review research from seven distinct and Self-Report Studies seldom cross-referenced domains, ranging from large- scale correlational studies that assessed self-reported We can begin to address the relationships among sleep, sleep to experimental studies that manipulated sleep cognition, and aging by examining the most fully devel- duration and quality. Table 2 provides an overview of the oped literature in this review: studies in which adults

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b Awake Stage 1 (N1) Stage 2 (N2) Slow-Wave Sleep (N3) REM Sleep

20-Year-Old 4 6 48 20 22

45-Year-Old 7.5 6 52 14 20.5

70-Year-Old 10.5 6.5 55 9 19

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Fig. 1. Typical sleep histogram (a) and stage distribution (b) in young and older adults. Example data are derived from Bliwise (1993) and Ohayon, Carskadon, Guilleminault, and Vitiello (2004). Older adults tend to spend more time than young adults in “lighter” stages of sleep (“N1” and “N2” in contemporary nomenclature; Iber, Ancoli-Israel, Chesson, & Quan, 2007); however, the duration of slow-wave sleep (SWS; blue shading) and REM sleep (red shading) may decline with increasing age. were simply asked how well they usually sleep. In these night, and how sleepy they feel during the day. The limi- self-report studies, participants report how many hours tations of these studies will be evident in their reliance on they typically sleep per night, how long it takes them to subjective sleep measures and insensitive cognitive mea- fall asleep, how often they wake up in the middle of the sures (e.g., the Mini-Mental State Examination, MMSE),

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Table 2. Overview of Reviewed Sleep, Cognition, and Normal-Aging Literatures

Number of Typical sample Findings on Findings on Findings on Literature studies size young age middle age older age Self-reported-sleep Many Large to very Cross-sectional Cross-sectional Fewer correlations correlational studies large samples and longitudinal and longitudinal correlations correlations Motor-activity (actigraphy) Few/medium Medium to large N/A (too few studies) Activity and Activity and and neuropsychology samples cognition often cognition often correlational studies correlate correlate Sleep brain-wave (PSG) Medium Small to Some sleep–cognition Some sleep– Some sleep– and neuropsychology medium correlations cognition cognition correlational studies samples correlations correlations Sleep-deprivation Medium Small samples Many adverse Some adverse Minimal or experiments cognitive cognitive no cognitive consequences consequences consequences Napping experiments Few Small samples Naps benefit cognitive Naps may benefit Naps have few or functioning cognitive no benefits for functioning cognition Sleep-dependent memory- Medium/ Small samples Sleep benefits Memory Memory consolidation experiments many memory consolidation may consolidation is consolidation be reduced often absent Nocturnal-sleep- Medium Small samples Better/more sleep Some cognitive Few cognitive intervention experiments benefits cognition benefits observed benefits observed

Note: This table provides an introduction to each literature and is not intended to capture the nuances, exceptions, and moderating variables existent in each domain. Number of studies that used healthy middle-aged or healthy older adults is estimated as few (e.g., 10), medium (e.g., 20–30), and many (e.g., >50). Typical group sample size is approximated as small (e.g., n = 20), medium (e.g., n = 100), large (e.g., n = 1,000), and very large (e.g., n = 10,000). PSG = polysomnography. but their advantages in statistical power, descriptions of over time. Consistent with this hypothesis, short sleep habitual sleep patterns, adjustment for confounding vari- duration in cognitively normal adults was recently linked ables, and use of both cross-sectional and longitudinal to greater cortical beta-amyloid burden (Spira et al., designs are laudable. 2013), which is a precursor to cognitive declines (Bateman et al., 2012). We elaborate on this potential mechanism in Cross-sectional studies the Conclusions and Interpretations section. Several cross-sectional studies have restricted their sam- Table 3 summarizes more than 40 studies that correlated ples to older adults (i.e., ages ≥ 60 years). Table 3 clearly self-reported sleep measures and cognitive functioning at shows that, as a whole, these studies have produced a single time point. Studies conducted in middle-aged weaker results. First, consider the evidence for short sleep adults consistently linked short sleep duration and wak- duration. After controlling for demographic and/or health- ing up at night to poorer executive control (Regestein related variables, most studies showed nonsignificant asso- et al., 2004), working memory (Sternberg et al., 2013), ciations between cognitive measures and short sleep in episodic memory (Kronholm et al., 2009), attention (e.g., older adults (see also Ramos et al., 2014). Interestingly, Krieg et al., 2001), and frequency of cognitive complaints recent work has indicated that the association between (e.g., Roane et al., 2014). One explanation for these asso- short sleep and episodic memory changes with increasing ciations is that night-to-night sleep quality dictates day- age, such that middle-aged, but not older, adults show this to-day cognitive performance in middle-aged adults. For short-sleep–cognition association (Miller, Wright, Ji, & example, when middle-aged adults maintained a sleep Cappuccio, 2014). diary and repeated a cognitive battery for 2 to 3 weeks, Perhaps sleep fragmentation rather than short sleep is their cognitive composite scores were lower the day after the critical correlate of cognition in older adults. Increased they got either less sleep or more sleep than normal nighttime awakenings were associated with poor mem- (Gamaldo, Allaire, & Whitfield, 2010; cf. Smith, Lack, ory in a small-sample study (Mary, Schreiner, & Peigneux, Lovato, & Wright, 2014). Another interesting potential 2013; see also Sampaio, Sampaio, Yamada, Tsuboyama, & mechanism is that poor sleep in middle-aged adults Arai, 2014), but puzzlingly, at least four studies have could cause neurobiological impairments that summate found the opposite pattern (Foley et al., 1995; Maggi

Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 − − ns ns ns ns ns ns ns PSQI/ SMHSQ (continued) − − ns ns sleepiness Excessive daytime − naps Daily Night waking − − ns − Early + − − − waking − − latency Sleep-onset − − Long sleep ns Short sleep measure Cognitive n -back, CPT age ≥ 51 Double span ≥ 24 Stroop ≥ 61 MMSE ≥ 60 MMSE ≥ 60 MMSE ≥ 45 Battery ≥ 50≥ 50 EPT MMSE ns − ≥ 60 ≥ 60 Battery ≥ 30≥ 50 Battery≥ 50 MMSE, VerM − − Battery − − ≥ 50 − Battery − ≥ 55 − Self-report≥ 60 − ≥ 60 ns Battery ≥ 60 MMSE Self-report − ns ns − ns ≥ 18≥ 20 Battery Self-report ≥ 30 − Self-report − ≥ 18 Self-report Subjects’ 49 60 50 43 75 48 78 88 100 927 5,171 8,789 1,506 1,389 3,212 1,026 8,362 1,504 size 28,670 32,142 Sample 127,048 d,c d,c d d,c c d d,c d,c d,c d d d,c d,c d Cross-Sectional Studies on Self-Reported Sleep Disturbances and Cognitive Function

d,c d,c Walsh (2004) (2014) and Snodgrass (2014) Belenky (2012) 2005) Humphreys (2013) Theorell, and Nilsson (2013) Riemann (2008) (1994) Alperovitch (1996) Abdel Galeel (2013) Foley, Ancoli-Israel, Britz, and Jennum and Sjøl (1994) Wan (2013) Miller, Wright, Ji, and Cappuccio Regestein et al. (2004) Gildner, Liebert, Kowal, Chatterji, Parsey, Schmitter-Edgecombe, and Ohayon and Vecchierini (2002, Lovato, Lack, Wright, Cant, and Miyata et al. (2013) Stenfors, Hanson, Oxenstierna, Spiegelhalder, Espie, Nissen, and Sternberg et al. (2013) Hoch, Dew, Reynolds, and Monk Xu et al. (2011) Ramos et al. (2013) Cross et al. (2013) Dealberto, Pajot, Courbon, and Faubel et al. (2009) Amer, Hamza, El Akkad, and Kronholm et al. (2009) Reference Roth and Ancoli-Israel (1999) 1,000 Table 3.

101 Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 − − p > ns ns ns PSQI/ SMHSQ − − ns ns ns ns ns sleepiness − Excessive daytime ns naps Daily − ns ns Night waking ) variables are indicated when more sleep complaints correlate Early c − + − ns ns waking − + ns − ns ns ns ns ns latency Sleep-onset ) and comorbidity ( d Long sleep ns ns ns ns 1 − − Short sleep DVT measure Cognitive age ≥ 70 Battery ≥ 65≥ 65 Battery Battery ns ≥ 65≥ 66 FOSQ-V Battery ≥ 75≥ 90 Battery MMSE ns − − ≥ 65 MMSE ≥ 70 Battery≥ 71 − CASI ns ≥ 65 VerM ≥ 65≥ 65≥ 65 MMSE ≥ 65 MMSE VerM MMSE ≥ 65 + MMSE, TMT, ≥ 65≥ 65 SPMSQ Battery ≥ 65 SPMSQ Subjects’ 76 84 16 124 157 174 375 660 272 5,201 1,844 2,905 2,398 2,287 3,097 4,578 2,9473,132 ≥656,444 MMSE ns − − 9,282 size Sample d,c d,c d d,c d,c d,c d,c d,c c d,c d d d,c d,c dc d,c d,c (2008) Haponik (1997) (2012) Thomas-Anterion, and Roche (2012) (2001) and Grodstein (2006) and Monk (2009) (2013) Might also or instead indicate that longer sleep is associated with poorer memory. Foley et al. (1999) Gamaldo, Allaire, and Whitfield Newman, Enright, Manolio, and Chang-Quan, Bi-Rong, and Yan Hayward et al. (1992) Saint Martin, Sforza, Barthélémy, A. M. Adam et al. (2014) Cricco, Simonsick, and Foley Auyeung et al. (2013) Whitney et al. (1998) Ward et al. (2013) Tworoger, Lee, Schernhammer, Schmutte et al. (2007) Gooneratne et al. (2003) Habte-Gabr et al. (1991) Blackwell et al. (2011a) Foley et al. (1995) Nebes, Buysse, Halligan, Houck, Reference Maggi et al. (1998) Mary, Schreiner, and Peigneux with poorer (−) or better (+) cognitive scores. Merged cells indicate combined measures, and blank measures that were not collected reported. Nonsignificant results ( .05) are marked as “ns.” CASI = Cognitive Abilities Screening Instrument; CPT Continuous Performance Test; DVT Digit Vigilance DWRT delayed-word-recall test; EPT Everyday Problems Test; FOSQ-V = Functional Outcomes of Sleep Questionnaire – Vigilance subscale; MMSE Mini-Mental State Examination; PSQI Pittsburgh Quality Index (total score); SMHSQ = St. Mary’s Hospital Sleep Questionnaire; SPMSQ Short Portable Mental Status TMT Trail Making Test; VerM verbal memory. Note: Studies are sorted by age (lower limit). Significant effects following adjustment for demographic ( 1 Table 3. (continued)

102 Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 Sleep, Cognition, and Aging 103 et al., 1998; McCrae, Vatthauer, Dzierzewski, & Marsiske, combined healthy adults and patients known to differ 2012; Miller et al., 2014). The peculiar finding that greater cross-sectionally in both sleep and cognition), and a amount of wake time at night could be related to better more perspicacious inspection of the literature reveals no cognitive performance in older adults is in notable con- shortage of null PSQI effects (≥10 studies) across a range trast to the findings in young and middle-aged adults. of attention, executive-control, working memory, prob- Such unexpected results could be interpreted as indicat- lem-solving, global-cognition, and episodic-memory ing (a) a hyperarousal mechanism (i.e., less sleep leads tasks (Table 3). To presage a reoccurring theme across to hyperarousal, which increases participants’ efforts to several domains covered in this review, Sutter, Zöllig, perform the task), (b) better self-awareness of sleep in Allemand, and Martin (2012) concluded that, in healthy adults who are more cognitively intact (e.g., Lauderdale, older adults, “poor sleep quality per se seems not to lead Knutson, Yan, Liu, & Rathouz, 2008), or (c) Type I error to changes in cognitive performance” (p. 773). in older adults. With regard to these three explanations, we note that similar correlations have sometimes emerged Longitudinal studies in studies that have objectively measured sleep and that recent animal studies have suggested that sleep depriva- Does poor sleep in recent months predict cognitive tion decreases hippocampal synaptic plasticity in young decline years into the future? Table 4 summarizes the rodents but increases prefrontal-cortex synaptic plasticity prospective epidemiological studies that have assessed in older rodents (Acosta-Peña et al., 2015; see also self-reported sleep complaints as predictors of subse- Donlea, Ramanan, Silverman, & Shaw, 2014). quent cognitive decline. At least eight such studies that One frequent cognitive association in older adults is included middle-aged adults have reported significant with long sleep duration (e.g., ≥10 hours). Long sleep cognitive associations with short and/or fragmented can indicate several diverse factors, including underlying sleep (e.g., waking up at night). Increased wake time at diseases and failing health (Grandner & Drummond, night predicted increased cognitive complaints and 2007). Additional consistent cognitive associations in instrumental disabilities 2 years later (Stenfors, Hanson, older adults are with difficulty falling asleep and daytime Oxenstierna, Theorell, & Nilsson, 2013) and 28 years later sleepiness (measured subjectively or as the frequency of (Kulmala et al., 2013), respectively. Moreover, short sleep needing to take daytime naps; but cf. Bliwise, Carskadon, duration predicted poorer performance on telephone- Seidel, Nekich, & Dement, 1991). The conundrum here is based cognitive tests 22 years later (Virta et al., 2013). whether one should interpret such associations as sleep- Complementary and supportive evidence has arisen from specific effects when most supportive studies simultane- five studies that indicated that poor sleep at baseline pre- ously found no correlation with short or fragmented dicted the later development of cognitive disorders, sleep. including mild cognitive impairment and Alzheimer’s dis- Sleep epidemiology studies typically incorporate one ease (Table 4; Benedict et al., 2014; Lobo et al., 2008). to four sleep questions, but the complexity and diversity These studies, however, did not always control for of sleep symptoms might require more extensive ques- comorbidities. tionnaires. The Pittsburgh Sleep Quality Index (PSQI; The Whitehall II study (Ferrie et al., 2011) has provided Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) is a some of the strongest evidence in support of a role for popular 19-item questionnaire that uses a cutoff score to sleep in middle-aged adults as a protector against cogni- distinguish poor and good sleepers. In young adults, tive declines in normal aging. In this epidemiologically poorer executive-function and attention performance is famous longitudinal study, a shift from relatively normal associated with poorer PSQI-defined sleep, independent sleep duration (i.e., 6 to 8 hours of sleep per night) at of potentially confounding variables such as depression baseline to shorter sleep duration 5 years later was associ- (Benitez & Gunstad, 2012). In older adults, some research ated with lower cognitive performance on most cognitive has suggested an association between PSQI and global- measures (the surprising exception was no effect on epi- cognition scores (e.g., on the MMSE; Amer, Hamza, El sodic memory; cf. Devore et al., 2014). Thus, there is sup- Akkad, & Abdel Galeel, 2013; Chang-Quan, Bi-Rong, & port for the hypothesis that sleeping well in middle age Yan, 2012; Lo, Loh, Zheng, Sim, & Chee, 2014; Potvin promotes sustained cognitive integrity. et al., 2012), executive control (Blackwell et al., 2014; In older adults, poor sleep at baseline may be a weaker Nebes, Buysse, Halligan, Houck, & Monk, 2009), and predictor of declining cognition. As in the cross-sectional even spectroscopy estimates of glial functioning in brain studies, sleep fragmentation (i.e., nighttime awakenings) regions associated with memory (i.e., the hippocampus; was not a strong predictor of cognitive performance in Cross et al., 2013; see also Sexton, Storsve, Walhovd, older adult samples, and two studies even reported that Johansen-Berg, & Fjell, 2014). However, some of these nighttime-awakening frequency (“difficulty maintaining studies did not control for cognitive status (i.e., they sleep”) was associated with significantly better cognitive

Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 − − − ns ns ns sleepiness Excessive daytime p > .05) are marked – naps Daily ns + Night waking − − − Early ns waking − ns ns ns ns ns nsns + ns + latency Sleep onset Long sleep Short sleep 4 9 ns 7.7 (years) Follow-up ) variables (if reported) are indicated when more sleep complaints associated with poorer (−) or better c measure diagnosis diagnosis diagnosis Cognitive age Subjects’ ) and comorbidity ( d 346 ≥24 Dementia 689 ≥40838 TICS ≥46 8.5 MMSE ns 3 − 214 ≥75 Dementia size 3,264 ≥20 Self-report2,9945,431 2 ≥44 ≥452,336 IADL Battery ≥49 TICS, TELE 28 5.4 22.11,389 −2,012 ≥59 −1,664 ≥65 − − ≥65 MMSE MMSE MMSE 4 6,444 104,894 ≥65 12,822 ≥65 −1,844 SPMSQ ≥65 MMSE, VisM − ns ≥702,242 MMSE, TMT 8 1,085 3 − 3.4 ≥71 Battery ns ≥75 ns − CASI 2 MMSE ns 3 3 ns ns 2,715 ≥65 MMSE 3 ns − 3,286 ≥65 MMSE 3 ns − 11,19628,697 ≥50 ≥50 MMSE, VerM15,385 3.8 Dementia ≥56 − Battery – 6 − − Sample d,c d,c d,c d,c d,c d,c d,c d,c c d,c d d,c d d,c d,c d,c d,c d,c

Longitudinal Studies on Self-Reported Sleep and Cognition d,c d d,c

and Nilsson (2013) Grodstein (2006) Louis (2009) (2010) (2013) and Raji (2012) (2013) Osorio et al. (2011) Blackwell et al. (2014) Reference Stenfors, Hanson, Oxenstierna, Theorell, Virta et al. (2013) Devore et al. (2014) Keage et al. (2012) Jaussent et al. (2012) Tworoger, Lee, Schernhammer, and Hahn, Wang, Andel, and Fratiglioni (2013) Kulmala et al. (2013) Jelicic et al. (2002) Xu et al. (2014) Quesnot and Alperovitch (1999) Benito-León, Bermejo-Pareja, Vega, and Foley et al. (2001) Loerbroks, Debling, Amelang, and Stürmer Ferrie et al. (2011) Sterniczuk, Theou, Rusak, and Rockwood Pedraza, Al Snih, Ottenbacher, Markides, Cricco, Simonsick, and Foley (2001) Benito-León, Louis, and Bermejo-Pareja Potvin et al. (2012) Table 4. Note: Significant effects following adjustment for demographic ( (+) cognitive functioning. Merged cells indicate combined sleep measures, and blank measures that were not collected or reported. Nonsignificant results ( as “ns.” Studies are listed by chronological age (lower limit). Dementia diagnoses included of Alzheimer’s disease. “Sleep onset latency” refers to difficulty falling asleep. CASI = Cognitive Abilities Screening Instrument; IADL = instrumental activities of daily living; MMSE Mini-Mental State Examination; PSQI Pittsburgh Sleep Quality Index; SPMSQ Short Portable Mental Status Questionnaire; TICS = telephone interview for cognitive status; TMT-B Trail Making Test B; VerM verbal memory; VisM visual memory.

104 Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 Sleep, Cognition, and Aging 105 preservation (Jaussent et al., 2012; Pedraza, Al Snih, insensitive to cognitive variability in healthy adults. Ottenbacher, Markides, & Raji, 2012). Such findings are Furthermore, sleep neuroscientists are likely to question somewhat surprising given much of the zeitgeist of the validity of the subjective nature of the sleep mea- sleep–cognition findings in young adults (Rasch & Born, sures. In the remaining sections, we discuss attempts to 2013) and animal models (Rolls et al., 2011). more objectively measure sleep and more precisely mea- Though difficulty falling asleep correlated with cogni- sure cognitive performance. tive functioning in older adults in cross-sectional studies (Table 3), five of the seven longitudinal studies in older Motor Activity (Actigraphy) and adults suggested no association (see the “Sleep onset latency” column in Table 4). Subjective sleepiness is a Neuropsychological Testing moderately consistent predictor of cognitive decline (see Actigraphy is the measure of motor activity using a small the “Excessive daytime sleepiness” column in Table 4), device that is typically worn as a wristband (e.g., Fitbit, but we would caution the reader that even this finding Actiwatch). Some sleep researchers have capitalized on becomes nonsignificant after controlling for depression actigraphy-defined periods of little or no movement as (Quesnot & Alperovitch, 1999) and general health being a proxy for sleep. The benefits of actigraphy are (Blackwell et al., 2014; Sterniczuk, Theou, Rusak, & that it places minimal burden on the participant and Rockwood, 2013). The strongest evidence for short sleep researcher and it can be worn for weeks (i.e., to assess duration in old age leading to speedier cognitive decline habitual sleep patterns). Though actigraphy estimates arises from the Nurses’ Health Study (N > 15,000; Devore sleep/wake state, it cannot measure sleep stages, and et al., 2014), but readers might suspend judgment on this importantly, as sleep quality gets worse, the reliability issue because at least five other studies failed to show and validity of actigraphy diminishes (de Souza et al., this effect (Table 4). 2003; Paquet, Kawinska, & Carrier, 2007; Sivertsen et al., 2006). Put bluntly, it is possible to lie motionless for hours Summary, critique, and future and still be unable to sleep, but an actigraph may score research directions this motionlessness as sleep (e.g., Montgomery-Downs, Insana, & Bond, 2012). Nonetheless, actigraphy is an In middle-aged adults, short and poor-quality sleep is attractive option for attempting some objective measure- often associated with, and can even precede, cognitive ment of sleep. declines. In older adults, self-reported sleep measures Studies with small- to medium-sized samples of cogni- have been less consistently linked to poorer cognitive tively normal older adults have produced varied associa- functioning. This pattern sets the stage for predicting age- tions between actigraphy variables and episodic-memory, related modification of sleep–cognition associations, a problem-solving, executive-function, and processing- theme that we consider in the remaining sections. speed performance (Cochrane, Robertson, & Coogan, Some of the modest effects in this literature might 2012; Miyata et al., 2013; Oosterman, van Someren, reflect our conservative approach of emphasizing effects Vogels, Van Harten, & Scherder, 2009; Parsey, Schmitter- following correction for demographic and health-related Edgecombe, & Belenky, 2012; Regestein et al., 2004; variables, including depression. The interplay of sleep Scullin, 2013; Westerberg et al., 2010; Wilckens, Woo, and depression is fascinating in that even though depres- Erickson, & Wheeler, 2014; Wilckens, Woo, Kirk, Erickson, sion might independently explain cognitive effects & Wheeler, 2014). These studies typically did not control (Lichtenberg, Ross, Millis, & Manning, 1995), sleep depri- for demographic or health-related variables (cf. Olaithe vation has sometimes been experimentally linked to et al., 2014). In one study that controlled for age and increased depressive symptoms (Kahn-Greene, Killgore, depression, Cochrane et al. (2012) found one significant Kamimori, Balkin, & Killgore, 2007). Therefore, future unexpected correlation (shorter sleep duration was asso- research in aging populations should attempt to disen- ciated with better episodic memory), one significant tangle causality (perhaps using structural equation mod- expected correlation (greater wake time at night was eling; Olaithe, Skinner, Hillman, Eastwood, & Bucks, associated with poorer Stroop performance), and many 2014) among sleep, depression, and cognitive variables null correlations. (cf. Chang et al., 2014; Vanderlind et al., 2014). Three epidemiology studies collectively involving The sleep-epidemiology literature provides a founda- thousands of participants—the Rush Memory and Aging tion for beginning to understand sleep, cognition, and Project, the Study of Osteoporotic Fractures, and the aging associations. Despite its strengths, this literature is Osteoporotic Fractures in Men Study—have reported limited in several important ways. Cognitive psycholo- several significant correlations (Blackwell et al., 2011a; gists will lament the overuse of the MMSE, which may be Blackwell et al., 2006; Blackwell et al., 2014; Lim et al.,

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2012; Lim et al., 2013). Though their findings consistently rs < .25), and low actigraphy outcome scores may reflect demonstrated that individuals with poorer actigraphy- underlying disorders (Mehra et al., 2008), which can defined “sleep” (i.e., rest-activity variability) showed independently explain poorer cognitive functioning (e.g., poorer cognitive performance (sometimes even in longi- Kushida et al., 2012; Pearson et al., 2006). Prudence thus tudinal analyses; Lim et al., 2013), there is some evidence requires us to look for converging evidence for cognitive that a weakening of circadian-activity rhythms may be a associations using polysomnography (PSG). stronger predictor of cognitive decline than sleep per se (Walsh et al., 2014). Furthermore, these studies typically Polysomnography and used very old age groups, and they often included patients with mild cognitive impairment and dementia. Neuropsychological Testing Thus, their meaning for “normal” aging is uncertain. On PSG is the gold-standard measurement for capturing the the one hand, these results could be viewed as support- complexity of sleep physiology. PSG measurement ing findings that poor sleep is associated with beta- involves recording electrophysiological data from elec- amyloid deposition (Spira et al., 2013). On the other hand, trodes attached to the scalp (at frontal, central, and occip- collapsing across control and dementia groups that are ital EEG sites), beside the eyes (to identify rapid eye known to differ on both sleep and cognition (possibly as movements), and on the chin (to evaluate muscle tone). a result of a third, unrecognized process) might bias one to More elaborate PSG recordings are possible (e.g., detec- find actigraphy–cognition correlations, even if an association of apneas), but even this simple approach allows tion did not exist in the healthy controls. Consider, for one to measure sleep stages, microarchitecture (e.g., example, that in the Osteoporotic Fractures in Men Study sleep spindles), and sleep continuity/fragmentation (Blackwell et al., 2011a), age significantly moderated the (Fig. 1). cognitive association with nighttime awakenings, such that One might hypothesize that several PSG variables these correlations were minimal or absent in 65- to 79-year- should correlate with cognitive functioning. First, sleep old adults (i.e., the group more likely to include cognitively duration (and nighttime awakenings) can be precisely normal adults) and emerged only in the adults who were measured using PSG; if the subjective and actigraphy- 80 years of age or older (i.e., the group more likely to based reports (see the previous sections) validly reflect include mild cognitive impairment and dementia patients). associations between sleep and cognition, then they should replicate with PSG. Second, PSG allows measure- Summary, critique, and future ment of SWS, which has a neurophysiological signature research directions suggestive of cortical plasticity and memory processing in young adults. In SWS, brain regions that are recog- The results of large-scale actigraphy studies suggest an nized to be important to memory functioning (e.g., hip- association between motor activity (“sleep”) and cogni- pocampus, frontal cortex) are believed to “dialog” against tive measures. Many of the actigraphy studies focused on a quiet subcortical background (Buzsáki, 1996; Buzsáki & very old age groups (cf. Blackwell et al., 2011a), and thus Peyrache, 2013; Logothetis et al., 2012; Massimini, Huber, age modification of sleep–cognition associations was not Ferrarelli, Hill, & Tononi, 2004). Third, sleep spindles, a strong theme in this literature (cf. the Self-Report Studies which have been suggested to reflect synaptic-plasticity section). Because most of the actigraphy studies were processes (Rosanova & Ulrich, 2005), are also detected cross-sectional, we need to consider the direction of cau- with PSG. Fourth, one can isolate periods of REM sleep, sation: Evidence that cognitive declines can precede which is characterized by vivid dreaming, increased cere- changes in sleep (Yaffe, Blackwell, Barnes, Ancoli-Israel, bral blood flow in several regions (e.g., the amygdala; & Stone, 2007) may indicate that a common neurobio- Maquet et al., 1996), and increased cholinergic activity, logical substrate (e.g., amyloid deposition; Ju et al., 2013) which might promote long-term potentiation (Diekelmann underlies both cognitive and sleep impairments in older & Born, 2010). adults. Thus, the major unanswered question is whether Table 5 summarizes studies that have evaluated over- common neurobiological underpinnings are caused by night PSG in relation to neuropsychological testing in poor sleep, poor cognition, both factors, or a related third older adults. These studies sometimes included patients process. with dementia or psychiatric conditions, and cross-sec- Actigraphy is a low-cost and noninvasive tool for mea- tional differences in PSG variables between such patients suring sleep in population-based studies, but its use and healthy older adults are well recognized (e.g., Cipolli remains highly controversial. Correlations between actig- et al., 2013; Foley et al., 2003; Loewenstein et al., 1982; raphy- and electroencephalography- (EEG) defined sleep Palma, Urrestarazu, & Iriarte, 2013; Prinz, Vitaliano, et al., variables in older adults are lamentably low (oftentimes 1982; Reynolds et al., 1985). In this section, we focus on

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PIQ VIQ VIQ CPT PVT speed n -back WRT, DS measures WMS, VerM VerM, DS, VF, MMSE, TMT-B Nonsignificant PIQ, TMT, VF, VIQ, PIQ, RPM VIQ, PIQ, WMS WMS, VIQ, PIQ VisM, TMT-A/B, ns MMSE, TMT-A ns VerM, VisM, VIQ, VerM) + (VisM/ CPT, Bells) ) variables (if reported). The cognitive correlate c ns ns ns ns ERFC) + (Digit) + (MMSE) ns + (TMT-B, DVT) ns + (MMSE, Vocab, ns ns ns + (PIQ, WMS) ns ) and comorbidity ( d + (VF) + (VerM) + (VerM,VF – (RPM) + (PIQ, WMS) ns + (BNT) + (VisM) CFI, ToL) + (WCST, VF, ns ns ns ns ns N1/N2 N3/SWS REM Spindle + (VIQ) + (VIQ, RPM) + (VIQ, RPM) MMSE [N1]) + (VerM [N2]) ns – (TMTB, DVT, – (MMSE, TMTB) ns ns First Wave CP) Second Wave ERFC) + (MMSE, – (MMSE) WCST, PB) – (VerM, VF, – (SRT, SAT) time Wake Total sleep sample Mean age of N 30 77 5015 75 77 + (RPM) – (RPM) 58 6324 ns30 67 25 67 ns 19 67 14 68 72 ns ns 16 80 90 81 – (MMSE) – (MMSE) 20 63 ns – (VerM, 57 64 12 82 43 69 48 72 298 82 ns ns 119 58 ns – (AA7, RPM) + (AA7, RPM [N1]) ns 2,909 76 2,601 76 d d,c d d,c d d,c d d d,c d,c Polysomnography- and Neuropsychological-Testing Studies

d (2013) (2012); Hita-Yañez, Atienza, and Cantero (2013) R. Spiegel, Herzog, & Köberle (1999) is listed in each cell, and additional (nonsignificant) cognitive measures are the rightmost column. Blank cells indi cate that data were not collected or reported. Studies sorted first by timing, as in the main text (e.g., First Wave), and then by chronological age (mean age, rounded). “Wake” indicates number of nighttim e awakenings, sleep efficiency, arousal index, non-REM shifts, or total time awake. AA7 = Army Alpha Test 7; BNT Boston Naming Test; Bells CP Constructional Praxis; CPT continuous performance test; CFI Cattell Fluid Intelligence; Digit Wechsler Adult Intelligence Scale – Digit Symbol; DS = digit span (forward and backward); DVT Vigilance Test; ERFC Évaluation rapide des fonctions cognitives; MMSE Mini-Mental State Examination (including modified versions); N1 = Stage 1 sleep; N2 2 N3/SWS slow-wave-sleep duration, slow-wave density/sl ope, or delta spectral power; PB Purdue Pegboard Test; PIQ Wechsler Adult Intelligence Scale – Performance Quotient; PVT = psychomotor vigilance task; SAT switching attention; SRT simple reaction time; speed processing speed; ToL Tower of London; TMT = Trail Making Test (A and/or B); VerM verbal memory; VF fluency; VisM visual VIQ Wechsler A dult Intelligence Scale – Verbal Quotient; Vocab Wechsler Adult Intelligence Scale – Vocabulary subtest; WCST = Wisconsin Card Sorting Task; WMS Memory Scale; WRT Wilkinson reaction time. Berry and Webb (1985) Table 5. Reference Note: The table shows statistically significant ( p < .05) positive (+) or negative (−) correlations following adjustment for demographic Mander, Rao, Lu, Saletin, Ancoli-Israel, et al. Feinberg, Koresko, and Heller (1967) Kahn and Fisher (1969) Blackwell et al. (2011b) Song et al. (in press) Cole et al. (2009) Bastien et al. (2003) Kim, Lee, Jhoo, and Woo (2011) R. Spiegel (1981) Anderson and Horne (2003) Hita-Yañez, Atienza, Gil-Neciga, and Cantero Yaffe et al. (2011) Prinz (1977) Seeck-Hirschner (2012) R. Spiegel, Köberle, and Allen (1986) Edinger, Means, Carney, and Krystal (2008) 84 49 Guazzelli et al. (1986) Lafortune et al. (2014) Hoch, Dew, Reynolds, and Monk (1994)

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normal aging and whether neuropsychological-test per- however, has seen a “Second Wave” (Vertes, 2004, p. 135) formance—which is presumably trait-like but may incor- of interest. One advancement is the utilization of more porate some state-like effects—is associated with PSG technologically sophisticated analyses of PSG data. One measures of sleep duration, SWS, REM sleep, or spindle approach is to calculate the number of microarousals density. To foreshadow, early studies (First Wave) did not (i.e., very brief awakenings) that occur during SWS and consistently link PSG variables to cognitive measures, but REM sleep (Hita-Yañez, Atienza, Gil-Neciga, & Cantero, more recent studies (Second Wave) have suggested a 2012), but these precise sleep-fragmentation measures potential age-related modification of PSG–cognitive have not correlated significantly with episodic memory in associations. cognitively normal older adults after controlling for age (J. Cantero, personal communication, February 15, 2013). First Wave (1967–1999) Another approach is to analyze EEG spectral power so as to capture not only the quantity but presumably also Feinberg, Koresko, and Heller (1967) pioneered the study the quality of SWS. Analyzing spectral power in the delta of whether PSG variables correlate with performance on range (0.5–4.0 Hz) provides a measure that conflates the intelligence tests in older adults. They found that perfor- incidence and amplitude of slow waves. Null effects are mance correlated positively with REM sleep and nega- still sometimes observed (e.g., Seeck-Hirschner et al., tively with SWS. Most early PSG–cognition studies were 2012), however, in one study (Anderson & Horne, 2003) limited by sample size. However, in one impressive early that limited spectral-power analyses to only the 0.5- to study, 119 middle- to older-aged adults underwent five 1.0-Hz frequency range (motivated by Steriade, Nunez, & consecutive nights of PSG recording (Berry & Webb, Amzica’s, 1993, studies) during the first 42 minutes of 1985). Consistent with the conclusions from the literature non-REM sleep, spectral power correlated positively with on self-reported sleep (e.g., Sutter et al., 2012), “sleep performance on many attention, executive-function, and and cognitive variables known to be sensitive to aging intelligence tests in older adults (cf. Mathias, Zihl, Steiger, processes failed to intercorrelate robustly” (Berry & & Lancel’s, 2005, experimental study). Webb, 1985, p. 334). Similarly focused attempts to extract precise compo- It is impressive that the First Wave of PSG and neuro- nents of sleep physiology include computer-automated psychological studies included four longitudinal studies analyses of sleep spindles. Sleep-spindle counts have (Guazzelli et al., 1986; Hoch, Dew, Reynolds, & Monk, been associated with cognitive performance in young 1994; Prinz, 1977; R. Spiegel, 1981). Two studies sug- adults (Fogel & Smith, 2011; Nader & Smith, 2001), and gested that poor cognitive performance at baseline as two studies reported that episodic memory correlated well as faster longitudinal cognitive decline predicted with spindle density in aging adults (Table 5). Thus, it is poorer PSG-measured sleep, rather than the reverse possible that early studies (First Wave) missed some hypothesis that poor sleep should predict poor cognition PSG–cognition correlations because they primarily (Hoch et al., 1994; Prinz, 1977). The other studies reported focused on sleep-stage quantity rather than on early- very few significant effects with cognitive measures. For sleep delta spectral power or sleep spindles. Another example, Feinberg and colleagues (Guazzelli et al., 1986) worthwhile consideration is that many studies in this lit- found that the correlations expected by current memory erature used broad age ranges. Returning to an overarch- studies (Rasch & Born, 2013)—such as correlations of ing theme initially prompted by the findings of the frontal spindle density with face recognition and memory self-report literature, could age be a modifier of the PSG– for names—were consistently near zero or nominally cognition relationship? negative (even in a 3-year follow-up; I. Feinberg, per- Three studies in different age groups examined SWS sonal communication, June 23, 2013). Likewise, a 14-year correlates of a vigilance task. In young adults, poorer study produced sporadic correlations (i.e., in both posi- vigilance-task performance was associated with less SWS tive and negative directions) with REM measures (Jurado, Luna-Villegas, & Buela-Casal, 1989), and similar (R. Spiegel, Herzog, & Köberle, 1999; R. Spiegel, Köberle, findings emerged in middle-aged adults, albeit perhaps & Allen, 1986). Counterintuitively, older adults who less consistently (Edinger, Glenn, Bastian, & Marsh, 2000). showed greater awakenings from sleep/SWS at baseline By contrast, in healthy older adults, no such correlations showed more preserved cognition. were observed (Crenshaw & Edinger, 1999). These findings suggested that “the degree to which slow-wave sleep Second Wave (1999–present) restores neurocognitive processes among normal sleepers changes as a function of aging” (Edinger et al., 2000, With a few exceptions, interest in correlating PSG and p. 127). neuropsychological measures in healthy older adults An exciting possibility is that it is age-related physio- dwindled in the 1980s (Bliwise, 1989). The past decade, logical changes—and not age per se—that modify

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SWS–cognition relations. As an initial step toward in studies in which the analyses ignored traditional ampli- addressing this possibility, one study measured cerebral tude criteria (e.g., Berry & Webb, 1985). oxygen reserve (or, more broadly, cerebrovascular risk) A weakness of the PSG literature is its overreliance on during SWS-rich sleep in 112 older adults without sleep small sample sizes (except Blackwell et al., 2011b; Song, apnea (Carlson, Neelon, Carlson, Hartman, & Bliwise, Blackwell, Yaffe, Ancoli-Israel, Redline, & Stone, in press; 2011). During early SWS, cerebral oxygenation increases Yaffe et al., 2011), which is commonly assumed to in most young adults, but it decreases or does not change decrease statistical power but also increases the risk of in most older adults (Carlson, Neelon, Carlson, Hartman, Type I errors (Button et al., 2013; Yarkoni, 2009). Another & Dogra, 2008). Critically, older adults who showed a limitation is that computer-automated spindle detection similar increase (as young adults) in cerebral oxygen- has been validated extensively in healthy young adults ation during SWS showed relatively preserved episodic- but only minimally in older adults. A third challenge for memory performance. the field will be to demonstrate that spectral-power correlations with cognitive measures represent sleep-specific Summary, critique, and future effects and not trait-based EEG correlations that could be observed during wakefulness (Finnigan & Robertson, research directions 2011; Vlahou, Thurm, Kolassa, & Schlee, 2014). The PSG and neuropsychological-testing literature has a Despite equivocal evidence for short sleep and SWS rich, but often forgotten, history. Across nearly half a cen- quantity, REM sleep often correlated with cognitive per- tury of research, PSG studies in older adults have failed formance in older adults. Such findings seem to converge to provide converging evidence for actigraphy-based with those of early animal studies (Markowska et al., findings that short sleep duration correlates with cogni- 1989; Stone, Altman, Berman, Caldwell, & Kilbey, 1989) tive performance (Table 5). Furthermore, there was little and with reports of cross-sectional differences in REM evidence for specific relations between particular cogni- sleep between healthy controls and dementia patients tive abilities and particular PSG variables in older adults. (Allen, Seiler, Stähelin, & Spiegel, 1987; Dykierek et al., Consider, for example, studies that used tasks dependent 1998; Feinberg et al., 1967; Prinz, Peskind, et al., 1982; on executive function (the n-back, the Wisconsin Card Prinz, Vitaliano, et al., 1982; Reynolds et al., 1988; Sorting Task, Trail Making Test B, switching attention): Reynolds et al., 1985; Vitiello et al., 1984). The crucial, The predominant finding was of no PSG correlation with unanswered question here is whether the reduction in executive function, and although some significant sleep– REM and the development of dementia are both epiphe- cognition correlations were observed, the particular PSG nomenal to other mechanisms such as decreased cholin- correlate was observed in only a single study. ergic neurotransmission (cf. Stone, Rudd, Parsons, & Does preserved SWS correlate with preserved episodic Gold, 1997; Yaffe et al., 2007) or if loss of REM sleep memory in older adults? This popular hypothesis was not drives cognitive changes (via, e.g., reduced long-term supported by the studies summarized in Table 5, which potentiation). included tests of visual memory, verbal memory, face– Moreover, multiple studies suggested associations name pair learning, and the Wechsler Memory Scale (see between cognitive measures and time awake after going Table 5 for some significant correlations with REM sleep, to bed (Table 5; cf. Tables 3 and 4). The correlational spindle density, and nighttime awakenings, though null findings with time awake converge with some of the correlations were most common). Verbal fluency, which actigraphy literature’s findings. However, in the next sec- is presumably a measure of semantic memory that relies tion, readers will likely be surprised by the striking con- on the frontal and temporal lobes (Baldo, Schwartz, trast between these correlational findings and the findings Wilkins, & Dronkers, 2006), was the only cognitive ability of the experimental sleep-deprivation literature. to demonstrate any replicability in correlating with SWS measures in older adults. Experimental Sleep-Deprivation One important technical consideration for SWS is that Studies older adults show a strong reduction in slow-wave EEG amplitude, and traditional SWS scoring criteria A typical finding in healthy young adults is that sleep (Rechtschaffen & Kales, 1968) dictate that slow-wave deprivation causes poorer cognitive performance (H. L. amplitude must exceed 75 µV. Therefore, one might be Williams, Lubin, & Goodnow, 1959; for reviews, see concerned that SWS duration does not correlate with Durmer & Dinges, 2005; Killgore, 2010), which some cognitive variables only because of the scoring method have pointed out to be reminiscent of cognitive impair- used (i.e., the use of amplitude rather than frequency). ments with increasing age (Harrison, Horne, & Rothwell, This explanation does not account for null SWS findings 2000). Sleep deprivation has numerous neurobiological

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and psychological effects (e.g., stress) that could poten- deprivation primarily impairs cognitive performance in tially mediate sleep–cognition associations (Bonnet, young adults at the nadir of their body-temperature 2011), but the general approach in the literature is to rhythm (i.e., a circadian, not a sleep, effect; Bonnet, view loss of sleep as a manipulation of sleep per se. The 2011); the reduced change in cognitive performance in experimental sleep-deprivation literature therefore pro- older adults might therefore reflect that the strength of vides a reasonable test of the hypothesis, generated by such body-temperature fluctuations diminishes with the correlational studies reviewed in all three previous aging. A second possibility is that the cognitive repercus- sections, that short sleep duration (or increased wake sions of sleep deprivation are mediated by sleep-loss- time at night) causes poorer cognitive functioning in induced cortisol elevations (K. Spiegel, Leproult, & Van older adults. Cauter, 1999). Elevated cortisol is a known correlate of Several behavioral studies examined sleep deprivation cognitive impairments (McEwen & Sapolsky, 1995), but in groups of only middle-aged or older adults (i.e., with- cortisol would be unlikely to explain the age interactions out young-adult control groups). These studies suggested discussed here (Maggio et al., 2013) because age does some detrimental consequences of sleep deprivation/ not moderate the relationship between cortisol and sleep fragmentation to “state” cognition (Bonnet, 1985; loss or between cortisol and cognition (Lee et al., 2007; Carskadon & Dement, 1985; Fröberg, Karlsson, Levi, & Vgontzas et al., 2003). It could also be that older adults Lidberg, 1975; Webb, 1986; H. L. Williams, Gieseking, & engage greater compensatory efforts under conditions of Lubin, 1966; H. L. Williams et al., 1959). For example, Van sleep deprivation than young adults, a pattern that might Der Werf et al. (2009) reported that in a sample of 12 be identified using neuroimaging (Almklov, Drummond, middle- to older-aged adults, fragmenting SWS led to Orff, & Alhassoon, 2014). impairments in visual-memory encoding. Next consider sleep-specific interpretations. One pos- Table 6 lists experimental studies that compared young sibility is that older adults are chronically sleep deprived adults to middle-aged or healthy older adults following and that depriving them of additional sleep has minimal normal sleep versus sleep deprivation/fragmentation. effects. However, age-based dissociations have been Early studies by Webb and colleagues (Webb, 1985; Webb observed in studies that selected for older adults who & Levy, 1982) conducted with middle-aged faculty mem- sleep well (e.g., M. Adam, Retey, Khatami, & Landolt, bers raised the possibility that the cognitive effects of 2006). Additional possibilities are that older adults need sleep deprivation increase with age. Yet the more com- less sleep than young adults (e.g., Bliwise, 2000, 2011) or mon theme that has emerged from 30 years of experimen- that sleep is less restorative to cognitive functions and tal research is that sleep deprivation/fragmentation affects therefore less detrimental to cognition when sleep is lost cognitive functioning in young adults but has less of an (Edinger et al., 2000). The behavioral results of the sleep- effect, no effect, or even a facilitating effect on cognitive deprivation and aging literature are clear, but the expla- functioning in older adults (16 of the 20 studies in Table nation for such effects requires further attention. 6). It is possible that some of the reduced effects in older adults reflect diminished baseline performance (i.e., floor Experimental Napping and Sleep- effects), but this explanation cannot account for studies in which older adults outperformed their younger counter- Extension Studies parts following sleep deprivation (e.g., Duffy, Willson, People are encouraged to sleep 8 hours per night, but Wang, & Czeisler, 2009; Stenuit & Kerkhofs, 2005). Another they often fail to achieve this standard. If chronic sleep concern is the overreliance on vigilance tasks, but similar loss plagues modern American society, and if even mild age-modification effects have been observed with epi- sleep deprivation impairs cognition (Van Dongen, sodic memory (Bonnet & Rosa, 1987) and multitasking Maislin, Mullington, & Dinges, 2003), then extending (Nesthus, Scarborough, & Schroeder, 1998). sleep would be expected to improve cognitive functioning (cf. Buysse, Grunstein, Horne, & Lavie, 2010). Could Summary, critique, and future taking a daily nap be our society’s solution? The practice research directions of regular napping has been observed in “Blue Zones” (Buettner, 2012)—areas such as Icaria, Greece, where Sleep deprivation’s minimal (acute) impact on cognition adults commonly live healthy lives into their 90s (see also in older adults is somewhat surprising in light of the stud- Asada, Motonaga, Yamagata, Uno, & Takahashi, 2000; cf. ies that correlated short sleep and/or increased time correlational studies in Table 3). Furthermore, in infants, awake at night with poorer cognitive performance (Tables children, adolescents, and young adults, daytime naps 3–5). First consider non-sleep-specific mechanisms for have been linked to improved cognitive performance and this age dissociation. Some have argued that sleep memory consolidation (for reviews, see Kopasz et al.,

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Table 6. Experimental Sleep Deprivation/Restriction Studies That Assessed Whether Cognitive Impairment Varied by Age

Length of Outcome Study Young adults Middle-aged adults Older adults manipulation measure Age-effect interpretation

Total-sleep-deprivation procedures

Brezinova, Hort, and N = 5 (mean N = 5 (mean 64 hours EEG Young adults impaired more Vojtĕchovský (1969) age = 22 years) age = 40 years) than middle-aged adults Webb and Levy (1982) N = 6 (age range N = 10 (age range 41 hours Cognitive Young adults impaired less = 18–22 years) = 40–49 years) battery than middle-aged adults Webb (1985) N = 6 (age range N = 12 (age range 2 nights Cognitive Age effect dependent on task = 20–25 years) = 50–60 years) battery Nesthus, Scarborough, N = 14 (mean N = 13 (mean 34 hours Cognitive Young adults impaired more and Schroeder (1998); age = 27 years) age = 51 years) battery than middle-aged adults Nesthus, Scarborough, and Schroeder, Kaplan, et al. (1998) Killgore, Balkin, and N = 34 (age range = 19–39 years) 49.5 hours IGT Young adults impaired less Wesensten (2006) than middle-aged adults Bonnet and Rosa (1987) N = 12 (age range N = 12 (age rage = 55–71 years) 64 hours Memory, Young adults impaired more = 18–28 years) RT than older adults Philip et al. (2004) N = 10 (mean age N = 10 (mean age = 58 years) 1 night RT Young adults impaired more = 23 years) than older adults Lowden, Anund, N = 10 (age range N = 10 (age range = 55–64 years) 4:00 a.m. EEG Young adults impaired more Kecklund, Peters, and = 18–24 years) testing than older adults Åkerstedt (2009) Brendel et al. (1990) N = 14 (mean age N = 10 (mean 1 night Vigilance Young adults impaired more = 20 years) age = 80 years) than older adults Smulders, Kenemans, N = 12 (mean age N = 12 (mean 28 hours Multiple Young adults impaired more Jonkman, and Kok = 21 years) age = 67 years) RT tasks than older adults (1997) Mertens and Collins N = 16 (mean age N = 14 (mean 1 night Cognitive Young adults impaired (1986) = 21 years) age = 67 years) battery more than older adults (in morning) M. Adam, Retey, Khatami, N = 12 (mean age N = 11 (mean 40 hours PVT Young adults impaired more and Landolt (2006) = 25 years) age = 66 years) than older adults Blatter et al. (2006) N = 16 (mean age N = 11 (mean 40 hours PVT Young adults impaired more = 25 years) age = 65 years) than older adults Duffy, Willson, Wang, N = 26 (mean age N = 11 (mean 26 hours PVT Young adults impaired more and Czeisler (2009) = 22 years) age = 68 years) than older adults Sagaspe et al. (2012) N = 14 (mean age N = 11 (mean 40 hours Go/No-Go, Young adults impaired more = 23 years) age = 68 years) RT than older adults (some tests)

Sleep-restriction and -fragmentation procedures

Bliese, Wesensten, and N = 65 (mean age = 38 years) 3, 5, 7, or 9 PVT Younger adults impaired Balkin (2006) hours for 7 slightly more than older days adults Stenuit and Kerkhofs N = 11 (mean age N = 10 (mean age = 60 years) 4 hours for 3 PVT, MWT Young adults impaired more (2005) = 23 years) nights than older adults Stenuit and Kerkhofs N = 10 (mean age N = 10 (mean age = 60 years) 4 hours for 3 Cognitive Young adults impaired to the (2008) = 23 years) nights battery same degree as older adults Bonnet (1989) N = 12 (mean age N = 12 (mean age = 63 years) 14 arousals per Addition Young adults impaired more = 22 years) hour for 2 task than older adults nights Filtness, Reyner, and N = 20 (mean age N = 19 (mean 5 hours for 1 Driving Young adults impaired more Horne (2012) = 23 years) age = 67 years) night simulator than older adults

Note: Sample sizes and mean age (rounded) or range are separated by age groups. Studies are sorted by age comparison group and split by total-sleep-deprivation versus sleep-restriction/fragmentation procedures. Merged cells indicate that two age ranges were combined in one group. EEG = electroencephalogram; IGT = Iowa Gambling Task; MWT = Maintenance of Wakefulness Test; PVT = psychomotor vigilance task; RT = reaction-time task.

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2010; Mednick, 2006; Milner & Cote, 2009). Similar cogni- (no-nap condition) across 17 days (Monk, Buysse, Carrier, tive benefits of prophylactic naps (Schweitzer, Randazzo, Billy, & Rose, 2001). The experimental manipulations Stone, Erman, & Walsh, 2006) and naps during a night increased 24-hour-sleep duration in both studies, but no shift (Purnell, Feyer, & Herbison, 2002) have been docu- experimental group differences were observed across a mented in middle-aged shift workers (Ficca, Axelsson, range of executive-control, intelligence, and attention Mollicone, Muto, & Vitiello, 2010). In this section, we tasks. evaluate experimental studies that investigated whether napping on a single day or across several weeks boosts Summary, critique, and future cognitive functioning in (non-shift-worker) aging adults. research directions Nap experiments (1–2 days) Taking an afternoon nap improves cognitive functioning in middle-aged adults. Such benefits might not extend to Some early napping, cognition, and aging work was well older adults, and this finding converges with evidence designed but limited by ceiling effects (Tamaki, Shirota, that older adults’ cognitive functioning is minimally Hayashi, & Hori, 2000; Tamaki, Shirota, Tanaka, Hayashi, impacted by sleep deprivation. Future research should & Hori, 1999). Subsequent work, however, has provided use no-nap control conditions and control the amount of compelling evidence that an afternoon nap benefits mid- nocturnal sleep prior to the nap. This literature would dle-aged adults’ cognitive functioning. When 32 healthy also benefit from disentangling whether naps improve middle- to older-aged adults were given a 2-hr early overall cognitive ability (transfer), or, alternatively, con- afternoon nap or rest opportunity, napping led to solidation of trained tasks, the topic to which we next improved reaction time and Stroop performance turn our attention. (Campbell, Murphy, & Stauble, 2005). Similarly, 10 young adults, 10 middle-aged adults, and 12 middle- to older- Experimental Studies of Memory aged adults completed cognitive testing before and after taking short naps (20 minutes), taking long naps (60 min- Consolidation utes), and reading without napping (control condition; The newest frontier in sleep, cognition, and aging Milner & Cote, 2008). Some nap-related cognitive bene- research focuses on memory consolidation. There exist fits were observed (e.g., improved serial addition/sub- several theories of memory consolidation (see Table 1), traction performance), and these benefits did not but a consistent theme is that after a memory is encoded significantly interact with age. However, statistical power (i.e., learned or perceived), it must undergo a process of may have been a limiting factor; for example, in the long- stabilization and integration (i.e., consolidation) if it is to nap condition, serial-addition/subtraction accuracy later be retrieved (i.e., recollected). For at least 50 years, improved after a nap in the young and middle-aged psychological scientists have hypothesized that memory adults, but it worsened in the middle- to older-aged consolidation declines with increasing age (Doty & Doty, adults. In another study that focused only on older adults 1964), but researchers have only recently focused on (N = 24), there were no significant differences in episodic sleep-dependent memory consolidation and aging. memory, attention, working memory, or procedural Sleep’s role in memory consolidation has been ele- memory across 60-min-nap versus rest conditions (Wan, gantly demonstrated in human and animal studies that 2013). Thus, there is persuasive evidence for the cogni- have shown that memories are “replayed” and strength- tive value of napping in young and middle-aged adults, ened during sleep (Rasch, Büchel, Gais, & Born, 2007; but such benefits may decrease with increasing age. Wilson & McNaughton, 1994; Yang et al., 2014). Though the sleep and memory-consolidation field is not without Nap-based sleep-extension some controversy and debate (Rickard, Cai, Rieth, Jones, & interventions (weeks) Ard, 2008; Siegel, 2001; Vertes, 2004; Vertes & Siegel, 2005), our interpretation is that the diversity of supportive empiri- Some napping studies have been designed to increase cal evidence (see the Appendix) is sufficiently compelling 24-hour sleep across several days or weeks (Creighton, to conclude that there exists an active role for sleep in 1995). These studies have failed to demonstrate an experi- memory in young adults (Hennevin, Huetz, & Edeline, mental benefit of increased sleep duration on cognitive 2007; Oudiette & Paller, 2013; Rasch & Born, 2013). functioning. In one study, 21 middle- to older-aged adults In a typical memory-consolidation study, participants adhered to a monthlong short- or long-nap regimen (there study verbal materials or learn a motor memory task in was not a no-nap control group; Campbell, Stanchina, the evening, then sleep and are retested in the morning. Schlang, & Murphy, 2011), and in another study, 9 healthy Memory consolidation is a state-dependent effect that is older adults took a 90-min early-afternoon nap or rested inferred following sleep relative to wake-only intervals

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when procedural (nondeclarative) memory performance The early conclusion that “REM sleep does not criti- increases, when episodic (declarative) memory forgetting cally affect procedural memory consolidation in old age” is reduced, or when a qualitative change in the memory (Hornung et al., 2007, p. 755) has been generally sup- trace is observed (e.g., integration). The procedures in ported by subsequent research. Consider Table 7. the memory-consolidation literature are typically derived Whereas at least 10 studies in middle-aged adults showed from experimental psychology (see the Appendix) rather behavioral evidence for overnight procedural-memory than from clinical neuropsychology or epidemiology. improvements (but perhaps less so than young adults; The most straightforward prediction for aging is that Dresler, Kluge, Genzel, Schüssler, & Steiger, 2010; Roig, as sleep becomes shortened, fragmented, and less “deep” Ritterband-Rosenbaum, Lundbye-Jensen, & Nielsen, 2014; (i.e., lower SWS), the sleeping brain may engage in less Wilson, Baran, Pace-Schott, Ivry, & Spencer, 2012), no memory consolidation. The loss of memory consolida- sleep-specific improvements were observed in 7 of the 8 tion during sleep might be one reason for the weakened studies that experimentally contrasted sleep and wake evidence for sleep–cognition associations in older adults: retention intervals in middle- to older-aged adult groups. If active cognitive processes are not occurring during The studies that suggested relatively preserved proce- sleep, then sleep variables would not be expected to cor- dural-memory consolidation with aging either mixed relate with cognitive variables (Tables 3–6). Indeed, in wake and sleep over long intervals or suggested that animal studies, both young rodents and “middle-aged” sleep-related benefits emerge only after repeated testing rodents tend to show “replay” of memories during sleep (i.e., “late/plateau” improvements; e.g., Tucker, McKinley, (i.e., reactivation of learned hippocampal sequences; & Stickgold, 2011). Huxter, Miranda, & Dias, 2012), but sleep-dependent Current research focuses on how procedural-memory memory replay is diminished in older rodents (Gerrard, consolidation changes with aging. One possibility is that Burke, McNaughton, & Barnes, 2008). Behavioral evi- procedural-memory consolidation in older adults occurs dence from animal models also supports the idea of an equally across both wake and sleep intervals (Nemeth age-related decline in memory consolidation (e.g., et al., 2013; Nemeth et al., 2010; Pace-Schott & Spencer, Hermann et al., 2007; Oler & Markus, 1998; M. T. Ward, 2013). Though young adults are expected to display Oler, & Markus, 1999). In the following section, we some consolidation across wake intervals (e.g., Dewar, address whether there is an age-related change in sleep- Alber, Butler, Cowan, & Della Sala, 2012), the absence of dependent procedural-memory (Table 7) and episodic- additional benefits from sleep might reflect a failure of memory (Table 8) consolidation in aging humans. the sleeping brain to “replay” the procedural memory (cf. animal models; Gerrard et al., 2008). Supportive evidence Procedural-memory consolidation for a lack of memory replay in older adults has arisen from two studies in which young and older adults were Procedural memory is a type of implicit memory for per- trained on a motor skill and then slept. In one study that forming actions or practiced skills. In young adults, con- used neuroimaging (Fogel et al., 2014), young adults solidation of procedural memories is most often linked to showed post-training activation in frontal, parietal, and sleep spindles and REM sleep (Plihal & Born, 1997; Walker, hippocampal regions during sleep; these patterns were 2009). These aspects of sleep change in quantity and qual- not observed in older adults. In another study (Peters, ity across the life span (e.g., Martin et al., 2013; Ohayon Ray, Smith, & Smith, 2008), young adults demonstrated a et al., 2004). Therefore, one would predict less procedural- significant boost in sleep-spindle density following memory consolidation during sleep in older adults. motor-skill training, a finding that has been replicated (in One of the largest experimental studies on procedural- young adults; Fogel & Smith, 2011). By contrast, older memory consolidation in older adults compared REM adults did not demonstrate training-related increases in fragmentation, non-REM fragmentation, REM rebound spindle density, but interestingly, they showed a signifi- (i.e., increased REM sleep following a night of REM depri- cant increase in SWS quantity. Could SWS therefore act as vation), and pharmacologically enhanced sleep (using a a compensatory mechanism in older adults? Additional cholinesterase inhibitor) conditions to a placebo, normal- work on this intriguing hypothesis is required because sleep control group (Hornung, Regen, Danker-Hopfe, SWS did not correlate with memory measures (K. Peters, Schredl, & Heuser, 2007). The major finding was that only personal communication, March 6, 2013). the cholinergic medication accelerated overnight improvements in the procedural-memory task. The char- Episodic-memory consolidation acteristics of REM sleep (e.g., REM density) certainly dif- fered across experimental conditions, but it was still Episodic memory refers to explicit memories for events surprising that, relative to the control group, the sleep- and is often distinguished from other forms of declarative fragmentation groups did not show detrimental effects memory, such as semantic (general-knowledge) memory on procedural-memory consolidation (but see Table 6). (Tulving, 1972, 2002). In young adults, episodic-memory

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Table 7. Procedural-Memory-Consolidation Studies in Healthy Middle-Aged and Older Adults

PSG–memory Procedural-memory Retention Sleep-related improvement Study and sample tests interval benefit? correlations Studies that primarily included middle-aged adults (mean age <60 years) Djonlagic et al. (2014) N = 20 (mean age = 35.3 years) PVT, MST ~10 hours (sleep only) Yes (MST) – (arousals)Age Backhaus et al. (2006) N = 13 (mean age = 40.1 years) MT ≥8 hours (sleep only) Yes Genzel et al. (2014) N = 16 (mean age = 41.8 years) MST—fast versus ≥9 hours (sleep only) Yes + (spindle trend) paced (within subjects) Manoach et al. (2010) N = 15 (mean age = 42 years) MST 9 hours; wake versus sleep Yes (late) Null effectAge,1 (within subjects) Manoach et al. (2004) N = 14 (mean age = 44 years) MST 24 hours (wake plus sleep) Yes N/A Deak, Stickgold, Pietras, Nelson, and Bubrick (2011) N = 9 (mean age = 44.7 years) MST 12 hours; wake versus sleep Yes (late) (within subjects) Nissen et al. (2006) N = 7 (mean age = 44.9 years) MT 10 hours (sleep only) Yes Null effects Nissen et al. (2011) N = 53 (mean age = 46.6 years) MT 12 hours; wake versus sleep Yes + (REM density) (between subjects) Kloepfer et al. (2009) N = 20 (mean age = 47.4 years) MT 10.5 hours (sleep only) Yes Null effects Nemeth et al. (2013) N = 17 (mean age = 57.8 years) Implicit ASRT 24 hours (wake plus sleep) Yes N/A Oudiette et al. (2011) N = 18 (mean age = 57.9 years) Modified SRRT 13 hours (sleep only) Yes Studies that primarily included older-aged adults (mean age >60 years) Siengsukon and Boyd (2009a, 2009b) N = 40 (mean age = 62.3 years) Explicit versus 12 hours; wake versus sleep No N/A implicit CTT (between subjects) (between subjects) Siengsukon and Boyd (2008) N = 18 (mean age = 65.6 years) Implicit CTT 12 hours; wake versus sleep No N/A (between subjects) Terpening et al. (2013) N = 20 (mean age = 66.1 years) MST ~10 hours (sleep only) Yes (late) + (SWS; late)Age Hornung, Regen, Danker-Hopfe, Schredl, and Heuser (2007) N = 107 (mean age = 66.1 years) MT 10 hours; AChE-I, REM Yes Null effectsExp rebound, REM/non-REM deprivation, normal sleep (between subjects) Studies that compared multiple age groups Wilson, Baran, Pace-Schott, Ivry, and Spencer (2012) N = 24 (mean age = 25.9 years) 10-item SRTT 12 hours; wake versus sleep Yes N/A N = 32 (mean age = 44.0 years) (explicit) (within subjects) Reduced N/A N = 31 (mean age = 63.1 years) No N/A (continued)

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Table 7. (continued)

PSG–memory Procedural-memory Retention Sleep-related improvement Study and sample tests interval benefit? correlations Dresler, Kluge, Genzel, Schüssler, and Steiger (2010) N = 12 (mean age = 25.3 years) MST 24 hours (wake plus sleep) Yes N/A N = 38 (mean age = 47.0 years) Reduced N/A Brown, Robertson, and Press (2009) N/A N = 14 (mean age = 20.4 years) SRTT 24 hours (wake plus sleep) Yes N/A N = 12 (mean age = 58.3 years) No N/A Spencer, Gouw, and Ivry (2007) N = 38 (mean age = 20.8 years) 10-item SRTT 12 hours; wake versus sleep Yes N/A N = 32 (mean age = 59.0 years) (explicit, implicit) (within subjects) No N/A Pace-Schott and Spencer (2013) N = 62 (mean age = 20.1 years) Goal- versus muscle- 12 hours; wake versus sleep Yes (goal) N/A N = 50 (mean age = 62.0 years) based (between (between subjects) No N/A subjects) Fogel et al. (2014) N = 28 (mean age = 24.0 years) MST 90 minutes; nap versus no nap Yes N = 29 (mean age = 62.6 years) (between subjects) No Tucker, McKinley, and Stickgold (2011) N = 15 (mean age = 20.1 years) MST 12 versus 24 hours; wake Yes N/A N = 16 (mean age = 68.0 years) versus sleep (within subjects) Yes (late) Null effects Nemeth et al. (2010) N = 25 (mean age = 21 years) Implicit ASRT 12 hours; wake versus sleep No N/A N = 24 (mean age = 69.8 years) (between subjects) No N/A Peters, Ray, Smith, and Smith (2008)) N = 14 (mean age = 20.1 years) Pursuit rotor Up to 1 week (wake plus Yes Nonsignificant trends N = 14 (mean age = 69.8 years) sleep) Yes Nonsignificant trends

Note: Studies are sorted first by number of age groups studied and then by mean age of sample. “Sample” refers only to the healthy (control) group in each study. Plus and minus signs indicate positive and negative polysomnography (PSG) correlations, respectively. PSG correlations (if reported; left blank if not reported) with overnight memory improvement are listed after adjusting for performance baseline (when reported); superscript notations indicate whether chronological age and experimental group (Exp) were also adjusted. “Late” indicates that plateau, not immediate, improvement was observed. AChE-I = acetylcholinesterase inhibitor donepezil; ASRT = alternating serial reaction time; CTT = continuous tracking task; MST = finger-tapping-motor-sequence test; MT = mirror tracing; PVT: psychomotor vigilance test; SRTT: serial-reaction-time task. 1The authors reported this correlation following removing an outlier.

consolidation has most often been linked to SWS contextual prospective-memory procedures, methodolo- (Diekelmann & Born, 2010) or to spindles (Fogel & gies which have been critical to convincingly demonstrat- Smith, 2011), both features of sleep that change in quan- ing sleep-dependent memory consolidation in young tity and quality with aging (Carrier et al., 2011; Ehlers & adults (see the Appendix). Furthermore, these studies Kupfer, 1989; Martin et al., 2013). Table 8 illustrates that have generally not evaluated possible neurobiological, most (aging) studies using young and middle-aged adults cardiovascular, or endocrine moderators of consolidation provided some behavioral evidence for sleep-dependent which may explain variability across studies (Mander, episodic-memory consolidation. In older groups, one Rao, Lu, Saletin, Lindquist, et al., 2013; but see Carlson well-designed study suggested preserved sleep-depen- et al., 2011). dent episodic-memory consolidation (Wilson et al., 2012), Identifying the PSG correlate(s) of episodic-memory but at least five other studies indicated some age-related consolidation in aging adults has been challenging, per- impairments on at least some episodic-memory tests haps because most work has shown no behavioral evi- (Table 8). With few exceptions, these studies used simple dence for consolidation in older adults; if there is no verbal learning procedures rather than employing exper- memory consolidation, then there should be no PSG cor- imental-psychology manipulations such as emotion- relate of the memory-consolidation measure. Nevertheless, induced memory trade-off, directed forgetting, or some researchers have reported correlations between

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Table 8. Declarative-Memory-Consolidation Studies in Healthy Middle-Aged and Older Adults

Declarative-memory Retention Sleep-related PSG-retention Study and sample tests interval effect correlations Studies that primarily included middle-aged adults (mean age <60 years) Backhaus et al. (2006) N = 13 (mean age = 40.1 years) PAL (40 pairs to 60%) ≥8 hours (sleep only) (No wake + (SWS)Age control) Mawdsley, Grasby, and Talk (2014) N = 40 (mean age = 40.3 years) Item and source 12 hours; wake versus Marginal N/A memory sleep (between subjects) age-based reduction Deak, Stickgold, Pietras, Nelson, and Bubrick (2011) N = 9 (mean age = 44.7 years) Selective reminding 12 hours; wake versus No + trend (SWS) task sleep (within subjects) Nissen et al. (2011) N = 53 (mean age = 46.6 years) VVM 12 hours; wake versus Yes Null effects sleep (between subjects) Kloepfer et al. (2009) N = 20 (mean age = 47.4 years) VVM 10.5 hours (sleep only) (No wake Null effects control) Studies that primarily included older-aged adults (mean age >60 years) Mazzoni et al. (1999) N = 30 (mean age = 68 years) PAL (20 pairs; no Sleep only (No wake + (sleep cycles); immediate test) control) − trend (SWS) Hornung, Regen, Danker-Hopfe, Schredl, and Heuser (2007) N = 107 (mean age = 66.1 years) PAL (34 pairs studied 10 hours; AChE-I, REM No group effects Null effectsExp two times) rebound, REM/non-REM deprivation, normal sleep (between subjects) Schredl, Weber, Leins, and Heuser (2001) N = 8 (mean age = 66.5 years) 40 words (read, 11 hours; baseline sleep (No wake + (REM) on AChE-I recalled eight times) versus AChE-I (within control) night subjects) Lo, Sim, and Chee (2014) N = 14 (mean age = 66.6 years) DRM lists (lures, 8.3 hours; wake versus No (study item); Studied: null effects; studied words) sleep (within subjects) yes (lure item) lures: − (SWS) Seeck-Hirschner (2012) N = 19 (mean age = 68 years) Rey-Osterrieth ≥10 hours (sleep only) (No wake – (SWS), + (wake), Complex Figure Test control) + (spindles)Age Conte, Carobbi, Errico, and Ficca (2012) N = 16 (mean age = 72.5 years) PAL (168 pairs studied >9 hours (sleep only) (No wake − (arousals), three times) control) − (transitions) Westerberg et al. (2012) N = 16 (mean age = 72.7 years) PAL (44 pairs studied Sleep only (2 nights) (No wake + (PAL: delta, theta); two times); face-fact control) null effects (face-fact pairs pairs) Hot et al. (2011) N = 14 (mean age = 76.7 years) 15 words (studied five Sleep only Ceiling effects N/A (ceiling effects) times)

(continued)

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Table 8. (continued)

Declarative-memory Retention Sleep-related PSG-retention Study and sample tests interval effect correlations Studies that compared multiple age groups Wilson, Baran, Pace-Schott, Ivry, and Spencer (2012) N = 24 (mean age = 25.9 years) PAL (32 pairs to 62.5%) 12 hours; wake versus Yes N/A N = 32 (mean age = 44.0 years) sleep (within subjects) Yes N/A N = 31 (mean age = 63.1 years) Yes N/A Backhaus et al. (2007) N = 16 (mean age = 20.4 years) PAL (40 pairs to 60%) 3.5 hours; early versus Retention better + (SWS)Age N = 12 (mean age = 50.0 years) late sleep (within after early + (SWS)Age subjects) sleep than late sleep Giambra and Arenberg (1993; Experiment 1) N = 24 (age range = 18–21 years) 48 sentences (studied Up to 24 hours Similar forgetting N/A N = 24 (age range = 55–64 years) two times) rates N/A Giambra and Arenberg (1993; Experiment 2) N = 24 (age range = 17–21 years) 48 sentences (studied Up to 24 hours Forgetting rate N/A N = 24 (age range = 65–74 years) three times) faster in older N/A adults Cherdieu, Reynaud, Uhlrich, Versace, and Mazza (2014) N = 20 (mean age = 22.1 years) Object-location task 12 hours; wake versus Yes + (Cycle time/sleep N = 20 (mean age = 68.9 years) sleep (between subjects) No time) Mary, Schreiner, and Peigneux (2013) N = 16 (mean age = 21.0 years) PAL (study 28 pairs five 7 days Forgetting rate N/A N = 16 (mean age = 69.7 years) times or 100%) was faster in N/A older adults Scullin (2013) N = 57 (mean age = 19.7 years) PAL (20 pairs to 80% 12 versus 24 hours Yes + (SWS) N = 41 (mean age = 70.7 years) criterion) (between subjects); No Null effects wake versus sleep (between subjects) Mander, Rao, Lu, Saletin, Lindquist, et al. (2013) N = 32 (mean age = 20.7 years) PAL (120 pairs to 10 hours; wake versus Yes + (delta) N = 26 (mean age = 73.4 years) 100%) sleep (between subjects) No + (delta) Rauchs et al. (2008) N = 14 (mean age = 23.4 years) Study 15 words three (Sleep only) Age reduction Null effects times (young adults) trend (ceiling) N = 14 (mean age = 75.1 years) or five times (older Age reduction Null effects adults); stories trend (ceiling) Aly and Moscovitch (2010) N = 10 (mean age = 22.8 years) WMS stories; personal 12 hours; wake versus Yes N/A N = 12 (mean age = 75.2 years) memory sleep (within subjects) Yes; reduced N/A

Note: Studies are sorted by number of age groups. “Sample” refers only to the healthy (control) group in each study. Plus and minus signs indicate positive and negative polysomnography (PSG) correlations, respectively. PSG correlations with overnight retention are listed after adjusting for baseline (when reported); superscript notations indicate whether chronological age and experimental group (Exp) were also adjusted. Sleep-related benefits are reported relative to wake/control conditions. AChE-I = acetylcholinesterase inhibitor donepezil; DRM = Deese- Roediger-McDermott lists; PAL = paired associate word learning; VVM = visual- and verbal-memory task; WMS = Wechsler Memory Scale.

Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 118 Scullin, Bliwise overnight episodic-memory retention and spindle density performance regardless of experimental effects is a very (Seeck-Hirschner et al., 2012) and ability to maintain common practice (e.g., Scullin, 2013), but should we sleep continuously (i.e., few awakenings; Conte, Carobbi, interpret such correlations as sleep-specific effects? Errico, & Ficca, 2012; Mazzoni et al., 1999). Others have Cognitive measures correlate with delta and theta spec- failed to observe correlations with sleep spindles (and tral power during wake states in older adults (Finnigan & sigma spectral power; Hornung et al., 2007; Hornung Robertson, 2011; Vlahou et al., 2014), and therefore, we et al., 2009; C. Westerberg, personal communication, July caution against interpreting PSG–memory correlations as 22, 2013) or reported a positive correlation between evidence for sleep-dependent memory consolidation in retention and time awake at night (Seeck-Hirschner et al., the absence of converging experimental evidence for 2012). memory consolidation. Much work on episodic-memory consolidation and Despite some limitations, several interesting themes aging has focused on the role of SWS. Table 8 indicates are emerging in the aging and memory-consolidation that in some middle-aged adult samples, memory con- field. Middle-aged adults tend to demonstrate damp- solidation correlated with SWS duration (Backhaus ened evidence for sleep-dependent episodic- and pro- et al., 2007; Backhaus et al., 2006; Deak, Stickgold, cedural-memory consolidation. In many cases, older Pietras, Nelson, & Bubrick, 2011). The SWS picture is adults show reduced (or no) evidence for overnight still murky in older adults: SWS duration is typically not memory consolidation. To the extent that memory con- associated with overnight retention of episodic memo- solidation forms the building blocks of optimal cogni- ries, but some have reported positive correlations with tive functioning (e.g., Mazzoni et al., 1999), the loss of delta spectral power, which quantitatively blends the sleep-dependent memory consolidation might acceler- incidence and amplitude of slow waves (Mander, Rao, ate cognitive aging and result in weaker sleep–cognition Lu, Saletin, Lindquist, et al., 2013; Westerberg et al., associations. 2012). We were again surprised to see multiple reports of These positive findings notwithstanding, three studies negative correlations between memory and SWS quantity observed negative correlations between SWS duration (Bastien et al., 2003; Buechel et al., 2011; Feinberg et al., and retention of veridical memories (Mazzoni et al., 1967; Lo, Sim, & Chee, 2014; Mazzoni et al., 1999; Platt 1999; Seeck-Hirschner et al., 2012) and lure (false mem- et al., 2011; Scullin, 2013; Seeck-Hirschner et al., 2012; R. ory) recognition (Lo, Sim, & Chee, 2014). Perhaps this Spiegel, 1981), though some studies did not show a con- literature can be cohesively explained by drawing a dis- comitant experimental sleep effect. One interpretation of tinction between SWS quantity and SWS quality (opera- negative SWS–cognition correlations is that relatively tionalized as delta spectral power), but before drawing high SWS leads to “overactive” synaptic downscaling this conclusion, we encourage researchers to consider (Table 1), whereby too much SWS might prune synapses the following evidence: (a) Delta power during wakeful- that would otherwise support memory in older adults ness is associated with cognitive performance in older (Scullin, 2013; cf. Chang et al., 2006). Another interpreta- adults (Vlahou et al., 2014); (b) overnight word-pair tion is that slow EEG activity represents pathologic neu- retention was unaffected in older adults when non-REM ral activity, as suggested by waking EEG data in severe sleep was experimentally fragmented (Hornung et al., cognitive disorders (Fernández et al., 2002). A third alter- 2007); and (c) overnight episodic-memory retention was native is that because SWS duration is negatively associ- not affected by pharmacologically increasing delta ated with REM duration, the negative correlations might power in SWS (Hornung et al., 2009). potentially reflect a compensatory role for REM sleep in episodic-memory consolidation in older adults (cf. Table Summary, critique, and future 5). A fourth interesting possibility is that negative SWS research directions correlations might indicate more gist-like memory processing (e.g., Payne et al., 2009). According to this view, The burgeoning memory-consolidation and aging litera- the negative SWS correlations may reflect the tendency ture is still developing, and therefore a few methodologi- for older adults to engage in gist-based rather than detail- cal weaknesses remain to be addressed. The reliance on based remembering (Adams, 1991; Castel, McGillivray, & small sample sizes and the absence of young-adult and Friedman, 2012). wake-only control conditions are frequent limitations. We It is important to recognize that not all SWS is created also must carefully consider the inferences drawn from equal (consider, e.g., fragmented SWS, low-density SWS, studies that reported significant correlations between etc.). Understanding the individual and contextual condi- PSG and memory variables but demonstrated no experi- tions supporting memory-promoting SWS should there- mental benefit of sleep (relative to wake control condi- fore be a priority for future research on aging. For tions). Correlating PSG variables with memory example, memory consolidation in older adults might

Downloaded from pps.sagepub.com at BAYLOR LIBRARY on January 15, 2015 Sleep, Cognition, and Aging 119 depend on initial learning strength (Tucker & Fishbein, adults used transcranial current stimulation (Eggert et al., 2008), retrieval efficiency (Bizzozero et al., 2008), mem- 2013), which when applied to young adults increases ory strategy (Daselaar, Veltman, Rombouts, Raaijmakers, SWS density and episodic-memory consolidation & Jonker, 2003), anxiety or arousal levels (Nielson, Wulff, (Marshall, Mölle, Hallschmid, & Born, 2004). However, in & Arentsen, 2014; Platano, Fattoretti, Balietti, Bertoni- older adults, the stimulation neither benefited SWS nor Freddari, & Aicardi, 2008), prefrontal-cortex and hippo- affected memory consolidation. campal connectivity (Mander, Rao, Lu, Saletin, Lindquist, A fascinating but controversial question is whether et al., 2013), and cerebral oxygenation (Carlson et al., pharmacologically impairing or improving sleep impacts 2011), as well as cholinergic (e.g., Schredl, Weber, Leins, cognitive functioning. Antidepressants have been associ- & Heuser, 2001) and/or dopaminergic modulation ated with REM suppression, and their (lack of) impact (Chowdhury, Guitart-Masip, Bunzeck, Dolan, & Düzel, on cognitive function was the subject of much debate a 2012; Scullin, Trotti, Wilson, Greer, & Bliwise, 2012), but decade ago (Vertes, 2004; Walker & Stickgold, 2004; for there are likely other influential factors. a potential resolution, see Dresler et al., 2010, and Goerke, Cohrs, Rodenbeck, & Kunz, 2014). Furthermore, Nocturnal Sleep Interventions for there is a paradox that sleep hypnotics might improve Cognition memory consolidation (e.g., Mednick et al., 2013; but see Hall-Porter, Schweitzer, Eisenstein, Ahmed, & Walsh, An important final question is whether interventions that 2013) while also causing anterograde amnesia or psy- improve the quantity and/or quality of overnight sleep chomotor slowing in young adults. Though clearly a also improve cognitive functioning (cf. napping). One complex and controversial area (Vermeeren & Coenen, approach to improving overnight sleep is to extend total 2011), we can currently ask whether common sleep time in bed or adjust nighttime habits (e.g., routinize bed- medications demonstrate any benefits to memory con- times). These behavior-based sleep-extension manipula- solidation or cognitive performance in older adults after tions have been linked to positive cognitive outcomes in the hypnotic effect of the medication has presumably adolescents, young adults, and middle-aged adults (e.g., dissipated. Dewald-Kaufmann, Oort, & Meijer, 2013; Lucassen et al., In young adults, zolpidem (e.g., Ambien) increases 2014; Mah, Mah, Kezirian, & Dement, 2011; but see sleep spindles (Feinberg, Maloney, & Campbell, 2000) Sadeh, Gruber, & Raviv, 2003). One study has suggested and possibly episodic-memory consolidation (Hall-Porter a similar benefit in healthy older adults (Klerman & Dijk, et al., 2013; Mednick et al., 2013). Research is inconclu- 2008), but this study did not control for practice effects sive regarding zolpidem’s effect on delta spectral power (Shipstead, Redick, & Engle, 2012). In a similar vein, psy- (for review, see Monti, Spence, Pandi-Perumal, Langer, & chological therapies such as cognitive-behavioral therapy Hardeland, 2009). In older adults, zolpidem can improve can be applied to treat insomnia in older adults (Morin, sleep continuity, REM sleep, and SWS duration (e.g., Culbert, & Schwartz, 1994), but such clinical trials typi- Kummer et al., 1993), but it does not improve next-day cally have not included cognitive performance or mem- memory or cognitive performance (Allain, Bentué-Ferrer, ory consolidation as an outcome (cf. Altena, Van Der Tarral, & Gandon, 2003; Fairweather, Kerr, & Hindmarch, Werf, Strijers, & Van Someren, 2008; Haimov & Shatil, 1992; Hindmarch, Legangneux, Stanley, Emegbo, & 2013; Sun, Kang, Wang, & Zeng, 2013). Dawson, 2006; Otmani et al., 2008; Scharf, Mayleben, Another approach is to bolster sleep-dependent Kaffeman, & Krall, 1991). Similar null effects (or even memory consolidation—for example, via targeted mem- reversed-direction effects) in older adults have been ory reactivation (Oudiette & Paller, 2013). One method reported with eszopiclone (Lunesta; Hemmeter, Müller, for reactivating memories during sleep is to wait until Bischof, Annen, & Holsboer-Trachsler, 2000; Leufkens & the participant is in SWS and then play sounds that were Vermeeren, 2009). previously encoded during word learning, such as a Pharmacological studies that specifically targeted SWS “meow” sound if the word cat was previously studied (using tiagabine, sodium oxybate, and gaboxadol) pro- (Rudoy, Voss, Westerberg, & Paller, 2009). Enhanced duced results consistent with age-based modification of memory consolidation is inferred when recall is greater SWS–cognition associations. These SWS medications for cued words than for non-cued words (counterbal- improved cognitive performance in young and middle- anced). This procedure was successfully applied to aged adults (Walsh et al., 2010; Walsh et al., 2006) but increase memory consolidation in a small sample that did not impact episodic memory or working memory in included middle-aged adults (Fuentemilla et al., 2013), healthy older adults, even when delta spectral power but no such study involving older adults has been pub- was enhanced (Mathias et al., 2005; also see Baker & lished. The only published attempt at increasing SWS- Vitiello, 2013; Benedict, Chapman, & Schiöth, 2013). dependent episodic-memory consolidation in older Finally, controversy surrounds whether melatonin is a

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“true” hypnotic (van den Heuvel, Ferguson, Mila Macchi, of life (Arakawa, Tanaka, Toguchi, Shirakawa, & Taira, & Dawson, 2005; Zhdanova, 2005), but there are inter- 2002; Faubel et al., 2009; Reid et al., 2010), better mental esting pilot data indicating that melatonin may benefit health (Driscoll et al., 2008; Tanaka et al., 2001; Tanaka cognition in healthy older adults (Peck, LeGoff, Ahmed, et al., 2002), and greater longevity (Dew et al., 2003; & Goebert, 2004) and Alzheimer’s-disease patients Marin, Carrizo, Vicente, & Agusti, 2005). Thus, regardless (Cardinali, Furio, & Brusco, 2010). of the cognitive effects, sleeping 250,000 hours across the life span is time well spent! Summary, critique, and future research directions Conclusions and Interpretations The extent to which increasing memory consolidation Nearly half a century of research has investigated sleep– on a nightly basis could ameliorate cognitive declines cognition associations in normal aging (Feinberg et al., and/or (re)strengthen sleep–cognition associations is an 1967). One of the most exciting trends in the self-report exciting avenue for further research. We expect this line literature is that poor sleep in middle age is linked to of work to be challenging because the external stimula- neurodegeneration-related biomarkers (e.g., amyloid tion techniques used to reactivate memories in young deposition) and subsequent cognitive decline. Similar adults (e.g., playing a “meow” sound for the studied findings have emerged from studies using movement- word cat) might cause disruptions to sleep in older based actigraphy and EEG-based PSG, but such studies adults because older adults are more likely to awaken in often mixed healthy older adults with patient groups. response to auditory stimuli (even during SWS; Zepelin, Furthermore, healthy older adults did not always demon- McDonald, & Zammit, 1984). Age-related neurobiologi- strate clear associations between sleep and cognitive cal changes such as decreased hippocampal–neocortical functioning. connectivity (Grady, McIntosh, & Craik, 2003) and In the experimental literatures, several thought-pro- reduced brain-derived neurotrophic factor (Calabrese, voking themes have materialized: Sleep deprivation Guidotti, Racagni, & Riva, 2013) may also constitute sig- causes greater cognitive impairments in young adults nificant barriers to increasing memory consolidation in than in older adults; sleep promotes memory consolida- older adults. tion in young adults more than in older adults; and nap- Current attempts at pharmacologically enhancing ping and enhancing nocturnal sleep benefit cognitive sleep, which have produced some positive outcomes in functioning in young and middle-aged adults but often young adults, have nearly uniformly failed to improve not in older adults. Thus, the seven literatures reviewed memory and cognition in older adults. The null findings here indicate that in older adults, inter- and intravariabil- do not seem to be attributable only to lingering hypnotic ity in sleep often do not relate to cognitive functioning, effects or to failures to augment SWS duration or delta and solely improving sleep may not reverse cognitive spectral power. These experimental studies might indi- impairments. We will consider five perspectives that cate that sleep physiology (e.g., SWS, sleep continuity) is might account for these findings. not causally related to cognitive functioning in older The first explanation is that sleep does not relate to adults; however, this literature still needs to evaluate cognitive functions—in particular, to memory consolida- whether sleep medications do not improve memory tion—even in young adults (Rickard et al., 2008; Siegel, because they are not enhancing spindles in the “fast” 2001; Vertes, 2004). Therefore, memory consolidation spindle-frequency range (Fogel & Smith, 2011) and (and trait-like cognition) should not be associated with whether melatonin can benefit cognitive functioning by sleep in older adults. Though we acknowledge that improving sleep quality. memory-consolidation studies have sometimes suffered The most successful intervention for improving cogni- from methodological weaknesses such as small sample tive functioning in aging adults might combine treatments sizes, analytical missteps, and inflated effect sizes (Button that target not only sleep but also psychological health, et al., 2013), the quantity and breadth of evidence for a the endocrine and cardiovascular systems, and exercise role of sleep in memory consolidation in young adults is (among other factors; Benloucif et al., 2004; Dzierzewski impressive (see the Appendix and Rasch & Born, 2013). et al., 2014; Fang, Wheaton, & Ayala, 2014; Horne, 2013; The mechanisms underlying this relationship, however, Naylor et al., 2000; Snigdha, de Rivera, Milgram, & are still a matter of lively debate (Table 1). Cotman, 2014; Tanaka & Shirakawa, 2004). Importantly, A second explanation is that all sleep–cognition even if sleep interventions ultimately have no impact on findings in older adults are complementary at a holistic memory in older adults, improving sleep may still have level and point to specific, preserved associations several noncognitive benefits, including improved quality between particular cognitive domains and particular

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aspects of sleep quality. For example, one might pre- can no longer efficiently support sleep-specific cognitive dict an association only between SWS quality and epi- processes. Several researchers have noted this “functional sodic memory. The null findings in these seven weakening” possibility (Edinger et al., 2000; Kronholm, literatures may therefore be due to misguided selection 2012; McCrae et al., 2012; Pace-Schott & Spencer, 2011; of cognitive tests, imprecise measurements of cognitive Schmidt, Peigneux, & Cajochen, 2012; Scullin, 2013; functioning (e.g., the MMSE), and/or inadequate mea- R. Spiegel et al., 1986), and some supportive evidence surement and analysis of sleep (self-report vs. PSG, was observed in most of the domains reviewed herein. sleep quantity vs. quality, etc.). Functional weakening requires further investigation, but The two above explanations might be considered oppo- this view uniquely predicts that increasing the quantity of site ends of a spectrum ranging from no cognitive associa- sleep in older adults is unlikely to restore cognitive abili- tion with sleep per se to a wholly preserved association in ties because the neurobiological mechanisms that are older adults that is masked by measurement. We are presumably necessary to support sleep-specific cognitive inclined to believe that the truth lies somewhere in between. processes will still be impaired in older adults (e.g., neu- If we assume that sleep and cognitive functions are associ- ral atrophy, decreased plasticity, nocturnal hypoxia, neu- ated in young adults (see the Appendix), then the seven roendocrine changes, altered neuromodulation). In the sleep, cognition, and aging literatures we have reviewed context of episodic-memory consolidation, the wide- might indicate that there is an age-related change in sleep– spread age-related neurobiological changes may cause cognition associations. The next three perspectives— SWS to no longer be “memory promoting” even when reduced need for sleep, compensation, and functional SWS density and amplitude are relatively preserved. For weakening—consider the possible nature of this change. example, consider functional weakening within the con- One idea is that we need sleep less as we age. Rather text of the system-consolidation view (Table 1) that than lamenting the loss of SWS with increasing age, some memories are reactivated in the hippocampus and trans- researchers have argued that SWS declines simply ferred to the neocortex during SWS: If the hippocampus, because it is a remnant of maturational processes from neocortex, or hippocampal–neocortical connections are earlier in life (Feinberg, 2000). Or, if degree of daytime greatly impaired (Grady, 2012), then hippocampal– learning dictates amount of SWS (rather than the reverse; neocortical consolidation should not occur regardless of see synaptic-downscaling theory, Table 1, and the results the quantity of SWS. of cognitive training studies; Diamond et al., 2014; A particularly intriguing possibility is that sleep dis- Haimov & Shatil, 2013), and if learning tendency or abil- turbances per se cause changes in sleep’s cognitive ity decreases with aging, then the need for SWS would functions across the life span (e.g., by prompting com- decrease as a natural consequence (Cirelli, 2012). This pensation attempts and/or weakening sleep–cognition “sleep need” view is provocative, but it has been difficult links). Acute sleep deprivation and chronic sleep restric- to test (e.g., Bliwise, 2000). tion have diverse effects on allostatic load, including Assuming similarity in sleep need with increasing increases in blood pressure, evening cortisol levels, age, a fourth possibility draws on the compensation insulin, proinflammatory cytokines, and sympathetic theory of neurocognitive aging (e.g., Park & Reuter- tone (McEwen, 2006; Vgontzas et al., 2004), all which Lorenz, 2009). According to this view, specific cognitive are hypothesized to accelerate cognitive aging (McEwen functions (e.g., procedural memory) that were once & Sapolsky, 1995). Furthermore, sleep deprivation/ supported by specific aspects of sleep (e.g., REM) might restriction in young animals can cause protein misfold- receive additional support (or become dedifferentiated) ing (Naidoo, Ferber, Master, Zhu, & Pack, 2008), from another aspect of sleep (e.g., SWS; cf. Peters et al., decreased tau phosphorylation (Di Meco, Joshi, & 2008). Consider also that in young adults, sleep prefer- Praticò, 2014; Rothman, Herdener, Frankola, Mughal, & entially supports memory consolidation, but consolida- Mattson, 2013), and increased amyloid deposition (Kang tion can still occur in the quiet waking state (e.g., Carr, et al., 2009; Xie et al., 2013), which impair memory con- Jadhav, & Frank, 2011; Dewar et al., 2012). Thus, it is solidation (e.g., Borlikova et al., 2013; Freir et al., 2011) possible that in response to age-related changes in sleep and underpin Alzheimer’s disease (Hardy & Selkoe, physiology, older adults’ brains compensate by increas- 2002). If these effects accrue “for years in a silent but ing the frequency of wake-based memory consolidation irreversible manner” (Hita-Yañez et al., 2012, p. 293), during intervals of quietude (e.g., Nemeth et al., 2013; then sleep disturbances in young and middle age could Pace-Schott & Spencer, 2013; Salas et al., 2014). be at the root of subsequent cognitive decline, even A fifth perspective is that the sleep–cognition link when no sleep–cognition associations are observed in grows less resilient as we age because the aging brain old age.

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Appendix Table A1. Sample List of Cognitive Tests and Experimental Paradigms Implicated in Sleep and Consolidation Studies

Cognitive test Reference Procedural/perceptual memory Visual discrimination Karni, Tanne, Rubenstein, Askenasy, and Sagi (1994) Mirror-tracing task Plihal and Born (1997) Semantic priming Stickgold, Scott, Rittenhouse, and Hobson (1999) Finger tapping Walker, Brakefield, et al. (2002) Opposition task Fischer, Hallschmid, Elsner, and Born (2002) Visuomotor adaptation Huber, Ghilardi, Massimini, and Tononi (2004) Implicit tone structure Durrant, Taylor, Cairney, and Lewis (2011) Melody production Antony, Gobel, O’Hare, Reber, and Paller (2012) Creativity and insight Anagrams Walker, Liston, et al. (2002) Number reduction Wagner, Gais, Haider, Verleger, and Born (2004) Transitive inference Ellenbogen, Hu, Payne, Titone, and Walker (2007) Remote Associates Test Cai, Mednick, Harrison, Kanady, and Mednick (2009) Unusual Uses task Ritter, Strick, Bos, Van Baaren, and Dijksterhuis (2012) Working memory and updating n-back Kuriyama, Mishima, Suzuki, Aritake, and Uchiyama (2008) Backward digit span Scullin, Trotti, Wilson, Greer, and Bliwise (2012) Animal learning Inhibitory avoidance Fishbein (1971) Vocal learning Dave and Margoliash (2000) Courtship conditioning Donlea, Thimgan, Suzuki, Gottschalk, and Shaw (2011) Location of food reward Martin-Ordas and Call (2011) Auditory classification Brawn, Nusbaum, and Margoliash (2013) Episodic memory Nonsense syllables Jenkins and Dallenbach (1924) Word associates Ekstrand (1967) Emotional and neutral texts Wagner, Gais, and Born (2001) Virtual maze Peigneux et al. (2004) Face–name pairs Clemens, Fabo, and Halasz (2005) Remember/know judgment Hu, Stylos-Allan, and Walker (2006) Object locations Rasch, Büchel, Gais, and Born (2007) Face locations Talamini, Nieuwenhuis, Takashima, and Jensen (2008) Emotional scenes Payne, Stickgold, Swanberg, and Kensinger (2008) DRM lists Fenn, Gallo, Margoliash, Roediger, and Nusbaum (2009) Prospective memory Scullin and McDaniel (2010) Retrieval-induced forgetting Racsmány, Conway, and Demeter (2010) Dream content Wamsley, Tucker, Payne, Benavides, and Stickgold (2010) Microeconomics lecture Scullin, McDaniel, Howard, and Kudelka (2011) Directed forgetting Rauchs et al. (2011) IAPS pictures Baran, Pace-Schott, Ericson, and Spencer (2012) Survival processing Abel and Bäuml (2013) Cartoons Chambers and Payne (2014) Testing effect Bäuml, Holterman, and Abel (2014) Language acquisition French class De Koninck, Lorrain, Christ, Proulx, and Coulombe (1989) Phonemes Fenn, Nusbaum, and Margoliash (2003) Abstraction Gómez, Bootzin, and Nadel (2006) Vocabulary Gais, Lucas, and Born (2006) Lexical competition Dumay and Gaskell (2007) Storybooks Williams and Horst (2014)

Note: References are sorted chronologically within cognitive domains.

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