caesJ6eronm1BPeiOi5asaC3S03Ve5R65g8 ◆GERONTOLOGICAL doi:10.1093/geronb/gby7 Advance Access publication June6018 OXFORD SOCIETY OF AMERICA Research Article Onset Time of Inhibition of Return Is a Promising Index for Assessing Cognitive Functions in Older Adults Tingni Li,BSc,Lei Wang,MEng,Wanyi Huang, PhD,Yanfen Zhen,BSc, Chupeng Zhong,BSc,Zhe Qu,PhD,and Yulong Ding,PhD Brain and Cognition Laboratory,Department of Psychology,Sun Yat-Sen University,Guangzhou,China. rsity,132 Waihua E-mail:quzhe@mail.sysu.edu.cn Received:August 13,17Editorial Decision Date:May.018 Decision Edito Nicole Anderson,PhD,CPsych Abstract Objectives:Developing efficient tools for assessing general cognitive functions in older adults is essential.Previous studies found that inhibition of retu (IOR)occurred later in the older adults than in the younger.However,little is known abour Methods:In two studies,the IOR-OT of healthy younger and older adults was measured by a modified Posner peripheral kEcoencnicoehecmndhAhnokoscaeeEwm 47535:33575MsG sho nt correlation tween IOR-OT and cognitive functions as assessed by was ace owlcdge K score latively st IOR-OT and cognitive adults.These inding provide new evidence supporting deficit theory of aging and lay the foundation of using IOR-OT as an objective measure of cognitive functions in the aging population. Keywords:ACE-R,Cognitive aing,,Visual attention With population aging,the cognitive wellbeing of older Della Sala.Henry.2004).could lead to an abnorma adults has become an important issue for society.Cognitive cognitive decline-a major challenge for healthy aging.The screening of abnormal cognitive decline requires objective on 04 Ma with age in late adulthood.Many cogni age,such as process 20222 Verhaeghen &Cerela 2002)and memory (Krame Robins,Helzer,1983;Tombaugh Mclntyre,1992) et al.,2006).In the process of cognitive aging,some dis and Montreal Cognitive Assessment (MoCA)(Nasreddine eases.such as Alzheimer's disease (AD)(Amieva.Phillips et al,2005)are the most widely used cognitive assessment
© The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 753 Research Article Onset Time of Inhibition of Return Is a Promising Index for Assessing Cognitive Functions in Older Adults Tingni Li, BSc, Lei Wang, MEng, Wanyi Huang, PhD, Yanfen Zhen, BSc, Chupeng Zhong, BSc, Zhe Qu, PhD, and Yulong Ding, PhD Brain and Cognition Laboratory, Department of Psychology, Sun Yat-Sen University, Guangzhou, China. Address correspondence to: Yulong Ding, PhD, Brain and Cognition Laboratory, Department of Psychology, Sun Yat-Sen University, 132 Waihuan Donglu, Higher Education Mega Center, Guangzhou 510006, China. E-mail: edsdyl@mail.sysu.edu.cn Or Zhe Qu, PhD, Brain and Cognition Laboratory, Department of Psychology, Sun Yat-Sen University, 132 Waihuan Donglu, Higher Education Mega Center, Guangzhou 510006, China. E-mail: quzhe@mail.sysu.edu.cn Received: August 13, 2017; Editorial Decision Date: May 22, 2018 Decision Editor: Nicole Anderson, PhD, CPsych Abstract Objectives: Developing efficient tools for assessing general cognitive functions in older adults is essential. Previous studies found that inhibition of return (IOR) occurred later in the older adults than in the younger. However, little is known about the relationship between the onset time of IOR (IOR-OT) and cognitive functions in the aging population. The present study examined this issue and investigated the potential of using IOR-OT as an index of cognitive functioning in older adults. Methods: In two studies, the IOR-OT of healthy younger and older adults was measured by a modified Posner peripheral cueing task, and cognitive functions of the older adults were evaluated with the Addenbrooke’s Cognitive Examination Revised (ACE-R). Results: Both studies showed a significant correlation (r = ~.5) between IOR-OT and cognitive functions as assessed by ACE-R in older individuals: later IOR-OT was accompanied by a lower ACE-R score. Discussion: To our knowledge, the present studies are the first to discover a relatively strong correlation between IOR-OT and cognitive functions in older adults. These findings provide new evidence supporting the inhibition deficit theory of aging and lay the foundation of using IOR-OT as an objective measure of cognitive functions in the aging population. Keywords: ACE-R, Cognitive aging, Inhibition ability, Visual attention With population aging, the cognitive wellbeing of older adults has become an important issue for society. Cognitive aging refers to the phenomenon that individuals’ cognitive functions decline with age in late adulthood. Many cognitive functions decline with age, such as processing speed (e.g., Cerrella, 1985; Salthouse, 1996), attention (e.g., Verhaeghen & Cerella, 2002), and memory (e.g., Kramer et al., 2006). In the process of cognitive aging, some diseases, such as Alzheimer’s disease (AD) (Amieva, Phillips, Della Sala, & Henry, 2004), could lead to an abnormal cognitive decline—a major challenge for healthy aging. The screening of abnormal cognitive decline requires objective and efficient tools for assessing cognitive functions in older adults. The Mini-Mental State Examination (MMSE) (Folstein, Robins, & Helzer, 1983; Tombaugh & McIntyre, 1992) and Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005) are the most widely used cognitive assessment Journals of Gerontology: Psychological Sciences PSYCHOLOGICAL SCIENCES Journals of Gerontology: Psychological Sciences cite as: J Gerontol B Psychol Sci Soc Sci, 2020, Vol. 75, No. 4, 753–761 doi:10.1093/geronb/gby070 Advance Access publication June 6, 2018 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
754 niicapracticc.Theseowevrae on (in ator able for evaluatine cognition comprehensively To address long SOA conditions (e.g>500 ms),the response pattern these limitations,researchers have developed a more sen- reverses(i.e.,responses to targets occurring at the cued loca menon is called IOR.Although 2000)ACE-R extends the content of MMSE me five major cognitive functions:attention and orientation ing,Hopfinger Mangun,2001),the prevailing view holds function,epis odic and semantic memory, verbal flue hat IOR,a ry after functio pre Dawson.Mirchell.Arnold-Hodges.2006).the ACE-R is tion may begin when atrention mov away from the cuce recommended as a suitable and efficient tool for evaluar location,or when the cue is presented(but the early,atten ons in older adults (Larner Mitchell. obscures the inhibition;Klein ding the with norma cognitive functions o on the However there are two maio sho for thes The IOR effect a neuropsychological tests in practical application.First,per facilitation,therefore any mechanism that decreases inhibi formance on neuropsychological tests may be influenced by the eve Prev tud 014 eof IOR cipants with limir 50 and 3 000 ms Castel.Chas ity or low education may have difficulty completing the Pratt (2003)compared the time course of IOR in younge assessment. and older adults.When rese rs plotted cueing effects as also and/o they found mpare in. SOA rhat th to develop more objective and efficient asses ssment tools onset time (IOR-OT)delayed A novel approach to this issue is to identify key cognitive This delay in IOR-OT has been repli ed in a numbe processes mpacted by cog ive aging and then to ex (e.g,Bao,Zhe Fu,2 abili in th Amon the many theories addressing th auses of co 2016:Wasch The inhibitory deficit theory may account for the delay of IOR-OT in older adults.Inhibi ory processes are consic to act the vice of goals to (a)preve rrelevan dthe mos g ac ally would not effectively inhibit irelevant information tion,and (c)restrain prepotent re nses (Hasher.Lustig nctions (e.g..slowdo might no Hash mer ding compre rom a and he by a sulting in a 014)R L. a weaker inhibitory ability woud It remain unclear howeyer whether the delay of nitive functions IOR-OT in the aging population is associated with their genera function (IOR)is w of IOp an teddcross ral cueing task develo and Cohen (1984).In d that IOR-OT and functionin sence of are related.However,in many conditions,if we merel Before the 0 mpar the ma (SOA) both foo and intelli short (e.g.,200 ms),the reaction time (RT)at the cued and adults,which leads to an apparent"correlation"that
tools in clinical practice. These tests, however, are insensitive in differentiating levels of cognitive functioning (Luis, Keegan, & Mullan, 2009; Mitchell, 2009), and are not suitable for evaluating cognition comprehensively. To address these limitations, researchers have developed a more sensitive and comprehensive cognitive test battery, known as the Addenbrooke’s Cognitive Examination Revised (ACER) (Mathuranath, Nestor, Berrios, Rakowicz, & Hodges, 2000). ACE-R extends the content of MMSE, measuring five major cognitive functions: attention and orientation function, episodic and semantic memory, verbal fluency, language function, and visuo-spatial ability. With good validity and cross-culture usability (Fang et al., 2014; Mioshi, Dawson, Mitchell, Arnold, & Hodges, 2006), the ACE-R is recommended as a suitable and efficient tool for evaluating cognitive functions in older adults (Larner & Mitchell, 2014), including those with normal cognitive functions or unnoticeable cognitive declines. However, there are two major shortcomings for these neuropsychological tests in practical application. First, performance on neuropsychological tests may be influenced by the language capacity or education level of the participants (Gamaldo et al., 2018; Velayudhan et al., 2014). Specifically, participants with limitations in language ability or low education may have difficulty completing the assessment. Second, using these neuropsychological tests also requires professional assessment skills and/or language skills of interviewers, which could consume social resources in personnel training. Therefore, it is necessary to develop more objective and efficient assessment tools. A novel approach to this issue is to identify key cognitive processes impacted by cognitive aging and then to examine whether these processes could account for individual differences in general cognitive ability in the aging population. Among the many theories addressing the causes of cognitive aging (see Anderson & Craik, 2017 for a review), the inhibitory deficit theory (Hasher, Stoltzfus, Zack, & Rypma, 1991; Hasher & Zack, 1988) is arguably the most influential. This theory proposes that older adults generally would not effectively inhibit irrelevant information or stop prepotent responses, leading to a decline of cognitive and behavioral functions (e.g., slowdown of response, reduced memory, and poor reading comprehension, Weeks & Hasher, 2014). Based on this theory, an older adult with a weaker inhibitory ability would have poorer general cognitive functions. In the study of inhibitory processes, inhibition of return (IOR) is widely regarded as a reliable indicator of inhibitory attentional control. IOR is measured by the Posner peripheral cueing task developed by Posner and Cohen (1984). In this task, participants are asked to detect the presence of the target and respond as quickly as possible. Before the display of the target, an uninformative peripheral cue that does not predict the location of the target is presented. When the cue-target stimulus onset asynchrony (SOA) is short (e.g., 500 ms), the response pattern reverses (i.e., responses to targets occurring at the cued location are slowed). This phenomenon is called IOR. Although the specific processes of information processing affected by IOR remain controversial (e.g., response processes, Pastötter, Hanslmayr, & Bäuml, 2008; or sensory processing, Hopfinger & Mangun, 2001), the prevailing view holds that IOR, as an inhibitory aftereffect, reflects inhibition of the previously attended location (Dukewich & Klein, 2015; Gazzaniga, Ivry, & Mangun, 2014; Klein, 2000). The inhibition may begin when attention moves away from the cued location, or when the cue is presented (but the early, attentionally-mediated facilitation obscures the inhibition; Klein, 2000). The IOR effect may depend on the relative strength of two opponent processes (i.e., facilitation vs inhibition). The IOR effect appears when the inhibition dominates the facilitation, therefore any mechanism that decreases inhibitory control will delay the appearance of IOR. Previous studies found an age-related difference of IOR effects. For instance, with 11 cue-target SOAs that ranged between 50 and 3,000 ms, Castel, Chasteen, Scialfa, and Pratt (2003) compared the time course of IOR in younger and older adults. When researchers plotted cueing effects as a function of cue-target SOAs they found that, compared with younger adults, IOR effects appeared in longer cuetarget SOA conditions in older adults, meaning that the onset time of IOR (IOR-OT) in older adults was delayed. This delay in IOR-OT has been replicated in a number of subsequent studies (e.g., Bao, Zhou, & Fu, 2004; Langley, Friesen, Saville, & Ciernia, 2011; Muiños, Palmero, & Ballesteros, 2016; Wascher, Falkenstein, & Wildwall, 2011). The inhibitory deficit theory may account for the delay of IOR-OT in older adults. Inhibitory processes are considered to act in the service of goals to (a) prevent irrelevant information from gaining access to the focus of attention, (b) delete irrelevant information from the focus of attention, and (c) restrain prepotent responses (Hasher, Lustig, & Zack, 2007). Thus, due to their deficits in inhibitory ability, older adults might not efficiently prohibit and/or recover from attentional capture by a distracting cue, resulting in a longer dwell time and hence a later onset of IOR. It remains unclear, however, whether the delay of IOR-OT in the aging population is associated with their decline in general cognitive functions. Previous crosssectional studies have identified an age-related decline in both onset of IOR and general cognitive functioning. These results suggested that IOR-OT and cognitive functioning are related. However, in many conditions, if we merely compare the data of different age groups and neglect the confounding effect of age, we may find an unreliable “correlation” between factors. For example, there are differences in both foot size and intelligence between children and adults, which leads to an apparent “correlation” that 754 Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
Journals of Gerontology:PSYCHOLOGICAL SCIENCES,2020,Vol.75,No.4 those with bigger feet have higher intelligence.But when were functionally normal using the screening criteria of Fang controlling for et al.(2014).To ensure reliable asse ment of ACE-R,olde correlation were redu the use of IOR-OT in ing cognitive functionsinolder individuals.To the best of Sun Yat-Sen Universiry. our knowl dge,however,no research has been conducted directh Apparatus and procedure OR-OT cognitive functions in older individuals.Specifically,we The part hhrghrmforanedhe a sound attenuate given a posne eripheral cueing task and an ACE-R assess ate ment within half a day.The order of the ACE-R and Posner general cognitive functioning in older adults:the later one's .200 IOR-OT i its Chinese translation version Hodges (2013),translated on,thi by Xiong,Liu Yang and edited by Zhou). The Posner peripheral cueing task was similar to that of stand what is"normal"in cognitive aging and can help tal.(2003).Parti define what is“abn in future studies (e.g..Petersen. with a 1.024 768 resolution (32 cm19 cm Res were made on an external numeric kevpad.Participants were asked to stare at a fixation cross at the center of the creen.I e of cach t is sh wn In l Study 1 nd on each trial a white oss fixation(0.5° en lor-OT and general cognitive functions in older adults We adopted a Posner peripheral cue play and these remained on the screen until a response was with six SOAs tim oxes w of the initial dis observer showed an IOR effect of at least 10 ms,the pr play,a bigger and concentric white box (the cue,1.4 sent study innovatively evaluates IOR-OT for each individ. 1.4)app red at the outer o one of the two horizonta ual using a quadratic polynomial fitting approach boxes for 50 ms.In 80 of the trials,a (th the cent one of th T Method c0 uld be50.100.250,500,750,0r1,000ms;these S0A randomly selected with withir Th older adults (56-85 =70.39,1 rget w as the cue alid(valid m the from the community in Zhuhai,China.They had an averag 12.79(SD ties The remaining 20%of trials served as catch trials in 2.8 range:6- 16)years of edu tion.For repl cating the Cn the to respond as acc (18-23 vears.mean age=20.59.8males)were also recruited. wa presente o0 ms Yat-Sen Un 139 (including 7 catch trials)with five short breaks.Twelve d younger participants were practice trials were given before the formal study. fluent in Chinese.All participants reported normal or cor Data prepro cessing For the ACE-R evaluation,the total score of each partic known genera In the Posne r peripheral cucing task and had an ACE-R score not which means they RTs bevond SD above or below a given participant's mear
those with bigger feet have higher intelligence. But when controlling for age, the correlation between foot size and intelligence would disappear. The correlation between IOR-OT and general cognitive functions among a group of older adults would support the use of IOR-OT in assessing cognitive functions in older individuals. To the best of our knowledge, however, no research has been conducted to explore their relationship. The main purpose of this research was to directly explore the relationship between IOR-OT and the general cognitive functions in older individuals. Specifically, we used the Posner peripheral cueing task to measure individual’s IOR-OT and the ACE-R to evaluate cognitive functions of older adults. Based on the inhibitory deficit theory, we expect to find a negative association between IOR-OT and general cognitive functioning in older adults: the later one’s IOR-OT is, the worse are his/her general cognitive functions. In addition, this research focuses on the assessment of cognitive function in healthy older adults. The data from cognitively normal older adults allow us to better understand what is “normal” in cognitive aging and can help define what is “abnormal” in future studies (e.g., Petersen, 2004; Sperling et al., 2011). Study 1 The main purpose of Study 1 is to directly explore the relationship between IOR-OT and general cognitive functions in older adults. We adopted a Posner peripheral cueing task with six SOAs to characterize the time course of IOR. Unlike previous studies (e.g., Castel et al., 2003), which defined individual IOR-OT as the first SOA where each observer showed an IOR effect of at least 10 ms, the present study innovatively evaluates IOR-OT for each individual using a quadratic polynomial fitting approach. Method Participant Thirty-three older adults (56–85 years, mean age = 70.39, 11 males) participated in Study 1. Older adults were recruited from the community in Zhuhai, China. They had an average 12.79 (SD = 2.88; range: 6–16) years of education. For replicating the age difference in the time course of IOR reported in previous studies (i.e., Castel et al., 2003), 22 younger adults (18–23 years, mean age = 20.59, 8 males) were also recruited. The younger adults were undergraduate students from Sun Yat-Sen University and had an average 14.32 (SD = 1.39) years of education. All older and younger participants were recruited as paid volunteers. Informed consent was obtained from all participants before the study. All participants were fluent in Chinese. All participants reported normal or corrected-to-normal vision. None of the participants suffered any known general psychiatric or neurological disease. All older participants self-reported no obvious behavioral impairment and had an ACE-R score not less than 85, which means they were functionally normal using the screening criteria of Fang et al. (2014). To ensure reliable assessment of ACE-R, older participants were required to have at least 6 years of education (i.e., primary school education). The study was approved by the Ethics Committee of the Department of Psychology, Sun Yat-Sen University. Apparatus and procedure The participants performed the tasks in a sound attenuated room with bright illumination. All older participants were given a Posner peripheral cueing task and an ACE-R assessment within half a day. The order of the ACE-R and Posner peripheral cueing task administration was counterbalanced across participants. The measurement of ACE-R was in strict accordance with the standards (Hodges, 2007; and its Chinese translation version Hodges (2013), translated by Xiong, Liu & Yang and edited by Zhou). The Posner peripheral cueing task was similar to that of Castel et al. (2003). Participants were seated 60 cm in front of a 14-inch color monitor of an IBM Thinkpad laptop, with a 1,024 × 768 resolution (32 cm × 19 cm). Responses were made on an external numeric keypad. Participants were asked to stare at a fixation cross at the center of the screen. The sequence of each trial is shown in Figure 1. Full contrast stimuli (white or green) were presented on a black background. On each trial, a white cross fixation (0.5° × 0.5°) and two white boxes (1° × 1°) served as an initial display and these remained on the screen until a response was made. The boxes were centered 5° from the fixation cross and located horizontally to the left and right of the fixation. About 1,000–1,200 ms after the presence of the initial display, a bigger and concentric white box (the cue, 1.4° × 1.4°) appeared at the outer of one of the two horizontal boxes for 50 ms. In 80% of the trials, a green circle (the target, 0.7°) was presented at the center of one of the two boxes for 2,000 ms or until response. The cue-target SOA could be 50, 100, 250, 500, 750, or 1,000 ms; these SOAs were randomly selected with equal probabilities within blocks of trials. The location of the target was either same as the cued location (valid trial) or different from the cued location (invalid trial), randomized with equal probabilities. The remaining 20% of trials served as catch trials in which no target was presented. The participants were asked to respond as accurately and quickly as possible if the target was presented. A 500 ms blank display was presented after a response. The entire session consisted of 360 trials (including 72 catch trials) with five short breaks. Twelve practice trials were given before the formal study. Data preprocessing For the ACE-R evaluation, the total score of each participant was calculated. In the Posner peripheral cueing task, the RTs of noncatch trials were computed and analyzed. RTs beyond 3 SD above or below a given participant’s mean Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 755 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
56 of:PSYCHOLGICAL SCIENCES,0,Vol.75,No.4 Typical participants + Cu-tame sr Gpn Group moans te square) sed 6 cu target SOA tch trials)to discourage anticipatory response SOA in Study 1 and 2.Each poir 1e0 2.09 n of stimulus onset asynchrony.The curved ine repres unger adults rest ectively res se accuracies includin hit rates of noncatch trials and false-alarm rates of catchtr r adults:bl dults).Th als,were also analyzed. Cueing effects (RTs in in alid trial the time e of the cue typica minus RIs h pa rive the IOR-OT,which is defined as the SOA at which the means for each age group in Studies1and. cucing effect is zero(typical cases are shown in Figure 2A). IOR-OT reflects the me poin ,996±0.002，Mean±SEFA:.007±0.002)and the younger e)to ar (hit99300o4h:08±002，mhn (sce Fig idity (valid,invalid)and SOA (six cu SOAs)as within ftcipansineach OA co subject factors and Age (old,young)as a between-subject polynomi led IOR-OT for S0A5.256 perspective,the time course function of IOR effects looks 1,53=42.134.p43) Posner peripheral cueing task,the hit rates were high and Consistent with the significant three-way inter the false-alarm(FA)rates were low for both the older (hit: action described above,the IOR-OT estimated by
were removed from further analysis. On average, 2.0% and 2.2% of noncatch trials were removed for the older and the younger adults, respectively. Response accuracies, including hit rates of noncatch trials and false-alarm rates of catch trials, were also analyzed. Cueing effects (RTs in invalid trials minus RTs in valid trials) in the six SOAs for each participant were fitted with quadratic polynomial function to derive the IOR-OT, which is defined as the SOA at which the cueing effect is zero (typical cases are shown in Figure 2A). IOR-OT reflects the time point that the cueing effect begins to change from a facilitatory effect (positive value) to an IOR effect (negative value). We also computed the onset time of group average IOR effect for each age group (see Figure 2B). For each group, we averaged the cueing effects across all participants in each SOA condition and then used the quadratic polynomial curve fitting to compute the group IOR-OT. Quadratic polynomial curve-fit was chosen to compute IOR-OT for the following reasons. First, from the graphic perspective, the time course function of IOR effects looks like a quadratic polynomial curve both in our results (see Figure 2) and in previous studies (e.g., Castel et al., 2003). Second, from the data-driven perspective, the time course of IOR effects in the present study fits well with the quadratic polynomial curve. The mean fitting degree R2 s using quadratic polynomial curve fitting are .706 (0.041, SE) and .731 (0.032) for the older group and the younger group, respectively. These R2 s are much better than the fitting degree R2 s of linear fitting (ps 0.47), which are .579 (0.053) and .529 (0.046) for the older group and the younger group, respectively. Result In the ACE-R assessment, the older participants obtained a mean score of 92.67 (SE = 0.753; range: 85–100). In the Posner peripheral cueing task, the hit rates were high and the false-alarm (FA) rates were low for both the older (hit: .996 ± 0.002, Mean ± SE; FA: .007 ± 0.002) and the younger participants (hit: .993 ± 0.004; FA: .008 ± 0.002), with no significant differences between groups (ps > .5). A three-way mixed-design analysis of variance (ANOVA) with Cue validity (valid, invalid) and SOA (six cue-target SOAs) as withinsubject factors and Age (old, young) as a between-subject factor was conducted on RTs. This revealed significant main effects of Cue validity (F(1, 53) = 4.658, p = .035, ηp 2 = .081), SOA (F(5, 256) = 6.835, p .43). Consistent with the significant three-way interaction described above, the IOR-OT estimated by Figure 2. Time courses of cueing effects in Study 1 and 2. Each point (red circle for the old and blue triangle for the young) represents a cueing effect (reaction time [RT] for invalid trials minus RT for valid trials) as a function of stimulus onset asynchrony. The curved line represents the quadratic polynomial curve indicating the time course of cueing effects (red = older adults; blue = younger adults). The abscissa where the fitted line crosses the horizontal axis represents the IOR-OT. Panel A and C show the time course of the cueing effects of a typical participant in each age group in Studies 1 and 2, respectively. Panel B and D show the time course of the cueing effects derived from the group means for each age group in Studies 1 and 2, respectively. Figure 1. The sequence of trial events in the Posner peripheral cueing task in Study 1 and 2. In this task, participants pressed a key in response to a target (a green circle) that was preceded by a non-predictive cue (a bigger white square). Study 1 used 6 cue-target SOAs, whereas Study 2 used 58 cue-target SOAs. The target was not present on 20% of trials (catch trials) to discourage anticipatory responses. SOA = Stimulus onset asynchrony. 756 Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
Journals of Gerontology:PSYCHOLOGICAL SCIENCES,2020,Vol.75,No.4 757 quadratic polynomial fitting was much later in the older factors,such as general processing speed and age.Is such 359 ms) ms;(53) eters use ,or reprod nnemof1oROofiheoa adopted a modifed os task with 58 that of the younger group (sSupplementary Figure 1B) OIs in th younger lation IOR-OT and gen eral cognitive functions of the older adults,Pearson's cor Method relation analyses were carried out As shown in Figure 3A corr the ParicipantoderadhlspanidipaiedinsSndy2,olde adults were recruited from the community in Zhuhai 311 524.=0021.Th s that.for older adults,worse performance on the ACE-R assessment smen use he ha led to 85 Th ut the ning 27 p s5993 :Salth 19g 5 males)were included in further analyses,with an aver tial correlation analyses were used to further verify the cor age 11.37 (SD=3.28;range:6-16)years of education rty-hve young adults (16-2 an age 19. 11 gage mean R and had an average 13.84 (SD =0.67)vears of cducation 6 IOR OT ACE R remained significant (s)and these partial correla- All older and younger participants were recruited as paid ed was obtai ed fron all par tions did not significantly differ from the simple correlation ween IOR-OT nd ACE-R 73).These re Chin had at least 6years of education.Non of the participants suffered any k nown general psychiatri The study was by the Study2 In Study 1,a significant negative correlation between ACE-R performance in old r individuals was ion was invulnerable to confounding Apparatus and procedure The procedure in Study 2 was similar to Study 1,except that Study 1:6 SOAs Study 2 58 SOAS in Study 2,the Posner peripheral cueing task contained 58 Table 1.Partial Correlations Between IOR-OT and ACE-R Performance in Older Adults After Controlling for Processing Speed (RT or RT/ACC of the Posner peripheral cueing task). ti and Age,Respectively Contro factor RT RTIACC Age Study 1 ,三-517* =-516 ,=-524* p=.002 p=.002 p=.002 M酒 Study 2 4 516 516 2 Combined p<.001 p<.001 pc.001 OR-OT and ACE-R in th
quadratic polynomial fitting was much later in the older participants (597.2 ± 45.9 ms) than in the younger adults (252.8 ± 33.5 ms; t(53) = 6.055, p .73). These results indicated that the correlation could not be simply explained by decline of general processing speed or an increase of age. Study 2 In Study 1, a significant negative correlation between IOR-OT and ACE-R performance in older individuals was found, and this correlation was invulnerable to confounding factors, such as general processing speed and age. Is such a correlation limited to the specific experimental parameters used in Study 1, or reproducible with different experimental parameters? To address this question, in Study 2, we adopted a modified Posner peripheral cueing task with 58 SOAs (similar to the task used in Song, Meng, Chen, Zhou, & Luo, 2014), and explored the relationship between IOR-OT and ACE-R performance in an older group again. Method Participant Twenty-eight older adults participated in Study 2. Older adults were recruited from the community in Zhuhai, China. One of the older participants was excluded after the ACE-R assessment, because he had failed to meet the criteria of normal cognitive function, with a score below 85. The remaining 27 participants (59–83 years, mean age = 65.74, 5 males) were included in further analyses, with an average 11.37 (SD = 3.28; range: 6–16) years of education. Forty-five young adults (16–23 years, mean age = 19.89, 11 males) also participated in Study 2. The younger adults were undergraduate students from Sun Yat-Sen University and had an average 13.84 (SD = 0.67) years of education. All older and younger participants were recruited as paid volunteers. Informed consent was obtained from all participants before the study. All participants were fluent in Chinese. All participants reported normal or corrected-tonormal vision and had at least 6 years of education. None of the participants suffered any known general psychiatric or neurological disease. The study was approved by the Ethics Committee of the Department of Psychology, Sun Yat-Sen University. Apparatus and procedure The procedure in Study 2 was similar to Study 1, except that in Study 2, the Posner peripheral cueing task contained 58 Figure 3. The correlation between IOR-OT and ACE-R score in the older group for Study 1 (A), Study 2 (B), and Studies 1 and 2 combined (C). Table 1. Partial Correlations Between IOR-OT and ACE-R Performance in Older Adults After Controlling for Processing Speed (RT or RT/ACC of the Posner peripheral cueing task), and Age, Respectively Control factor RT RT/ACC Age Study 1 r = −.517** r = −.516** r = −.524** p = .002 p = .002 p = .002 Study 2 r = −.504** r = −.507** r = −.485* p = .009 p = .008 p = .012 Studies 1 and 2 Combined r = .516*** r = −.515*** r = .516*** p < .001 p < .001 p < .001 Notes: RT = Reaction time; ACC = Accuracy. *Correlation is significant at the .05 level (two-tailed). **Correlation is significant at the .01 level (two-tailed). ***Correlation is significant at the .001 level (two-tailed). Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 757 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
758 were The ever als (including 87 catch trials)with five short breaks. ative correlation hetweer these two variables was found (Pearson's r(25)=-.506 an older indiv dual with Data preprocessing nced hy factors such as g eral res d (mean RTs d.In th or RT/accuracy)or age:the partial correlations (as shown peripheral cueing task,RTs beyond 3 SD above or below a given participant's mean R (ps Ihis result 3.0%of noncatcl ls for the studies (Study 1,N=33;Study 2,N=27),there was still according to the cueing effects in 58 SOAs for each partici- earson's r(58)= 517, 001 hHeoe2Dareaec1oRtsiastoreahgupow pant(typical cases are presented in Figure 2C).The onset wn in r C).This e or gr ing task isee r tial correlation results in table 1.The correlations betweer IOR-OT were Result In the ACE-R the olde older individuals can score of 92.48 (SE 0.711:a ngc:85-99).In the One may argue that the correlation between IOR-OT Posner peripheral cueing task,the hit rates and the FA rates and ACE-R performance resulted from overlapping pro the older (hit:.997 ±0.002 y IOR. and the n994 1001.FA 14.Acpan mixed-des ANOVA with Cu we defined a partial ACE-R as the sum of the other four lid)and SOA (58 cue-target SOAs)as within-subject factors and Age (old,young)as a between-subject factor was con To bette understan one's IO his s 4.32 showc ts of IOR-OTwith corre d fu 701118036 001 28h latte difference in response time between the Table 1)showed that the negative correlation betweer IOR-O and the (347.4 ±4.9 s).Ih cant (8 .001 cluded. attention SOA (F tions between IOR-OT and the subscale scores of ACE-R can wer not only found in ention/orientation function three-way interaction of Cue validity x SOA x Age (F(57, (58) 29,=.001).butinv rbal flu cmcy(58) .401 0)10) 41 the Cue va n re ee. d the C marginally significant)as well.These results su est that SOA Age interaction indicated that older and younger the connec on between IOR-OT and cognitive functions adults had different temporal dynamic patterns of cucing older adults was not limited to attentional orienting,but reflected general associations the IO of younger participants (357.739.5 ms;0)=4.412 Discussion p<.001,Col en'sd=1.055;see Supplementary Figure 2A) The present study compared the temporal dynamic pat Again,the IOR-OTs of th older group were mostly di terns of cueing effects in older and younger adults,and tributed afte 300 ms h he maje furth ccitioitebhccenoRoran previ
levels of SOAs instead of six levels. The 58 cue-target SOAs were variable from 50 to 1,000 ms with every 16.67 ms interval. The entire Posner cueing task consisted of 435 trials (including 87 catch trials) with five short breaks. Data preprocessing The data preprocessing procedure in Study 2 was similar to that in Study 1. For the ACE-R evaluation, the total score of each participant was calculated. In the Posner peripheral cueing task, RTs beyond 3 SD above or below a given participant’s mean were excluded from analysis. This resulted in removal of 2.1% and 3.0% of noncatch trials for the older participants and the younger participants, respectively. The individual IOR-OT was computed according to the cueing effects in 58 SOAs for each participant (typical cases are presented in Figure 2C). The onset time of group average IOR effects for each group is shown in Figure 2D. Result In the ACE-R assessment, the older participants obtained a mean score of 92.48 (SE = 0.711; range: 85–99). In the Posner peripheral cueing task, the hit rates and the FA rates were comparable between the older (hit: .997 ± 0.002, Mean ± SE; FA: .003 ± 0.001) and the younger participants (hit: .994 ± 0.001; FA: .005 ± 0.001), ps > .14. A threeway mixed-design ANOVA with Cue validity (valid, invalid) and SOA (58 cue-target SOAs) as within-subject factors and Age (old, young) as a between-subject factor was conducted on RTs. This showed significant main effects of SOA (F(57, 3990) = 4.377, p .55). When we merged two sets of older group samples across studies (Study 1, N = 33; Study 2, N = 27), there was still a significant negative correlation between IOR-OT and ACE-R performance (Pearson’s r(58) = −.517, p < .001, shown in Figure 3C). This correlation remained significant after controlling factors such as age, mean RT or inverse efficiency (RT/accuracy) of the Posner cueing task (see partial correlation results in Table 1). The correlations between IOR-OT and ACE-R performance in older adults were comparable in each study, indicating a reliable and robust link between IOR-OT and general cognitive functions in older individuals. One may argue that the correlation between IOR-OT and ACE-R performance resulted from overlapping processes captured by IOR-OT and the attention/orientation subscale in ACE-R, since both are related to participants’ attentional orienting abilities. To address this concern, we defined a partial ACE-R as the sum of the other four subscales, excluding the attention/orientation subscale. To better understand how one’s IOR-OT relates with his/ her performance in ACE-R, we explored the correlation of IOR-OT with the partial ACE-R and further with the five subscales respectively. The results (see Supplementary Table 1) showed that the negative correlation between IOR-OT and the partial ACE-R score remained significant (r(58) = −.455, p < .001), even though the attention/ orientation subscale was excluded. Significant correlations between IOR-OT and the subscale scores of ACE-R were not only found in attention/orientation function (r(58) = −.429, p = .001), but in verbal fluency (r(58) = −.401, p = .001), language function (r(58) = −.392, p = .002), and episodic and semantic memory (r(58) = −.241, p = .064, marginally significant) as well. These results suggest that the connection between IOR-OT and cognitive functions in older adults was not limited to attentional orienting, but reflected general associations. Discussion The present study compared the temporal dynamic patterns of cueing effects in older and younger adults, and further examined the relationship between IOR-OT and general cognitive functions in older individuals. Consistent with previous studies (e.g., Castel et al., 2003; Muiños 758 Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
Journals of Gerontology:PSYCHOLOGICAL SCIENCES,2020,Vol.75,No.4 et al.,2016;Wascher et al.,2011),a group difference in that involving inhibitory control (e.g.,Mayer,Dorflinger. Rao,Sei a The ed the idea that lor-ot is a between IOR-OT and cognitive functions in older adults: an part cipant ex ins,the nctions in ol is relia d by ognitive geofheoltracha5genc of our kno and was inyuln ng fa edge,the present study was the first to reveal a significant as age or general response speed.In addition,the Posne association bety peripheral cueing task is simple enough for most partici ionsinolkicra an (even those with ons in I ngs broaden ding of the role of The inkibi of IOR/IOR-OT can be conducted by computers reducing the manual operation during the assessment pro posed that an inhibition deficit could account for numerou cess and thus improving the evaluation efhciency Many stu d ol ave foun sing a Farcentstud of older adults ple with Stroop task (e.g Davidson,Zacks,Williams,2003),go amnestic mild cognitive impairment (aMC,patients with no go task dementia,and h althy controls.The IOR effect in aMC read ension (e. than that in h controls of IOR-OTP 0 olde According to dominant thee ries of IOR,this reflects a a7o (Belanger,Belleville,Gauthier,2010):the resistanc corre ne e in M S W lth that of age and ger eral r eed were controlled ou to the development of cognitive impairment in older adults finding is well aligned with the prediction of the inhibi The onset time of IOR thus seems sensitive to both large tory defici theor hhrnndeawahg specifical s in cognitive wellbeing,as Baye et al.'s JOR-OT) atego ng the diffe adult samples,as the current results show.Together,these function between differen age groups,the present stud results suggest that the IOR onset time may serve as a sen tha further sitive indicator of cognitive decline, ch potentially car Its wh between this inhibition decline and the decline of general cognitive function. As initial research on the relationship between IoR-OT nterestingly,the nhibitory abili sured by a sim ple P and ind ed w Future only in the at ion/prientation subscale but also in the of IOR.OT in the agin verbal fluency,language function,and (at the trend level) ies.IOR-OT 25%of the episodic and semanti memory subscales.One possibl iance in ACE- scores Although this Ma ough t requ ind other indicato involve a common inhibitory control system.The activit and to develop an integrated tool set for assessing genera of this inhibitory control system changes with age (e.g.,th cognitive functions of older individuals more comprehen ont ctw Camp l,Gr cly and Li t a 2015),inu
et al., 2016; Wascher et al., 2011), a group difference in IOR-OT between older and younger groups was found; that is, IOR-OT in the older adults was much later than that of the younger adults. More importantly, the present study revealed a significant and reliable correlation between IOR-OT and cognitive functions in older adults: the later the IOR-OT was, the worse the ACE-R score an older participant exhibited. This correlation was not caused by confounding factors such as general processing speed or age of the older adults. To the best of our knowledge, the present study was the first to reveal a significant association between the onset of IOR and cognitive functions in older adults. The present findings broaden our understanding of the role of inhibition in cognitive aging. The inhibitory deficit theory (Hasher et al., 1991; Hasher & Zack, 1988) proposed that an inhibition deficit could account for numerous age-related cognitive changes. Many studies have found that there are differences between young and old people in various tasks involving inhibition mechanisms, such as the Stroop task (e.g., Davidson, Zacks, & Williams, 2003), go/ no go task (e.g., Rodríguez-Villagra, Göthe, Oberauer, & Kliegl, 2013), and reading comprehension (e.g., McGinnis, 2012). The present study found that, compared to young adults, there was a delay of IOR-OT in older adults. According to dominant theories of IOR, this reflects a deficit in inhibitory ability in aging people. Moreover, our results revealed a reliable correlation between IOR-OT and general cognitive functions in the older adult samples. This correlation remained significant even when factors of age and general processing speed were controlled. Our finding is well aligned with the prediction of the inhibitory deficit theory, specifically that an individual with a poorer inhibitory function (which was reflected by a later IOR-OT) would have a worse general cognitive function. Instead of merely comparing the difference in inhibition function between different age groups, the present study provides new evidence that further supports the inhibition deficit theory: there is not only a decline in attentional inhibition ability in the older adults, but also a close link between this inhibition decline and the decline of general cognitive function. Interestingly, the inhibitory ability measured by a simple Posner cueing task was associated with performance in broader and more complex cognitive tasks in ACE-R, not only in the attention/orientation subscale, but also in the verbal fluency, language function, and (at the trend level) episodic and semantic memory subscales. One possible explanation is that, although the task requirements and measurement processes were quite different between the Posner cueing task and various tasks in ACE-R, both might involve a common inhibitory control system. The activity of this inhibitory control system changes with age (e.g., the frontoparietal control network; Campbell, Grady, Ng, & Hasher, 2012; Grady, Sarraf, Saverino, & Campbell, 2016; Li et al., 2015), influencing performance of various tasks that involving inhibitory control (e.g., Mayer, Dorflinger, Rao, & Seidenberg, 2004). In other words, inhibitory deficits might be one common cause of age-dependent declines in multiple cognitive functions. The present study supported the idea that IOR-OT is a promising and objective index for assessing the cognitive functions of older adults. The correlation between IOR-OT and general cognitive functions in older adults is reliable and robust. This correlation was replicated in different task settings, and was invulnerable to confounding factors, such as age or general response speed. In addition, the Posner peripheral cueing task is simple enough for most participants (even those with limitations in language ability or low education) to understand and complete. The evaluation of IOR/ IOR-OT can be conducted by computers, greatly reducing the manual operation during the assessment process and thus improving the evaluation efficiency. Using a Posner peripheral cueing task, a recent study (Bayer et al., 2014) compared cueing effects at various SOAs across three groups of older adults: people with amnestic mild cognitive impairment (aMCI), patients with dementia, and healthy controls. The IOR effect in aMCI persons occurred later than that in healthy controls, but earlier than that in dementia patients. A similar pattern of group differences in inhibitory ability among MCI, AD, and healthy older adults was also found in the Stroop task (Bélanger, Belleville, & Gauthier, 2010): the resistance to interference in MCI persons was worse than that in healthy older adults, but better than that in AD patients. These findings indicate that deficits of inhibition are closely linked to the development of cognitive impairment in older adults. The onset time of IOR thus seems sensitive to both large differences in cognitive wellbeing, as Bayer et al.’s comparisons across diagnostic category indicated, and smaller differences in cognitive functioning within healthy older adult samples, as the current results show. Together, these results suggest that the IOR onset time may serve as a sensitive indicator of cognitive decline, which potentially can be used to effectively identify older adults who are prone to cognitive impairment. This requires future validation in clinical studies. As initial research on the relationship between IOR-OT and individual general cognitive functions, our studies had relatively small sample sizes. Future studies need to adopt a larger sample size to establish the norm and distribution of IOR-OT in the aging population. In the present studies, IOR-OT accounted for approximately 25% of the variance in ACE-R scores. Although this is a pretty sizeable amount, it indicates that cognitive functioning in older adults is accounted for by other independent factors as well. Future studies are needed to explore other indicators and to develop an integrated tool set for assessing general cognitive functions of older individuals more comprehensively and efficiently. In conclusion, this study provides direct evidence for a robust and meaningful correlation between IOR-OT and Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 759 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
760 stroop task.Ne inlucate nd IOR-OT Campbell,K.L Grady,C.L.Ng.C.Hasher,L.(2012).Age ereat potential as a relible and obiective inde for assess ing cognitive functions of older individuals arach Np s0.212- Castel,A.D.Chasteen,A.LScialfa,C&Pratt,2003).Adul Supplementary Material age diffe return.Tb -759.doi 10. Sciences online. Cerella,J.(1985).Information processing rates in the cl doi:10.10370033 Funding Davidson,D.JZacks,R.T&Williams,C.C.(2003).Stroop inter 10.85-98 4-10 107 carch of a det doe10.375813414015-083S-3e 7,1647-1654 Author Contributions ang,J.P,Tang,H.D.,Wang .J2014 ersion o data under the e and ing mild Alzheimer's disease and mild ognitive imnair Ding De eriatrie Cogiie Disorders,37223-231 g11T、a mini m eral Psychiatry,40.812 Acknowledgments R y Andel R A 018)The on m,k parameters and n00017S104 1021700Py Conflict of Interest vry.R.B..Mangun.G.R.(2014).Cognitite euroscience:The biology of the mind (4th ed.).New York The authors declare no conflict of interest. CCampbel Reference 016.0 964.doi10.1093r h043 the control of attention.In Ce way.A arrold.C E1.(2017 Kane,M.,Miy (Eds.).V Sciences and Social Sciences,72.1-6.doi:10.1093/geronb Hasher.L Stolzfus.ER..Zacks,R.T.Rypma,B.(1991).Age gbw108 and inhibition.of Experimental Psycology.Leaming Fu,I C0gt0m,17,163-169 doi:10.1037027 239317L16 ta.64.403-414 Hasher I Zacks R T (1988)Workin and aging:A revie ce of prodomal dementia? Ho R. doi10.1016S A oumal of Albeimer's Disease,40,177-189.doi: New York:Oxford University Press Hodges,J.R.(2013).Cognitive for clinicians.(in Ch s s Gauthier s 010) impairments in Alzheimers discase.mild cognitive impair 2nd Han China:Huzh (Ed ment and healthy aging:Effect of congruency proportion in a Technology Press (Original work published in 2007)
general cognitive functions in older adults. Our findings indicate that attentional inhibition ability is a key factor influencing healthy cognitive aging, and IOR-OT may have great potential as a reliable and objective index for assessing cognitive functions of older individuals. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences online. Funding This work was supported by grants from National Nature Science Foundation of China (No. 31471070 and 31271190) to Y. Ding and Z. Qu, and Leading Talents in BaiQianWan Project of Guangdong Special Support Program (No. 201626026) to Y. Ding. Author Contributions Y. Ding conceived and designed the studies. L. Wang, T. Li, W. Huang, and C. Zhong performed the studies and analyzed the data under the supervision of Z. Qu and Y. Ding. L. Wang and Y. Zhen provided research materials; T. Li, Z. Qu, and Y. Ding wrote the manuscript. T. Li and L. Wang contributed equally to the present study and should be considered as co-first authors. Acknowledgments The authors thank Cheng Li for his assistance in data collection and the Editor and Reviewers for their helpful comments. Conflict of Interest The authors declare no conflict of interest. Reference Amieva, H., Phillips, L. H., Della Sala, S., & Henry, J. D. (2004). Inhibitory functioning in Alzheimer’s disease. Brain, 127, 949– 964. doi:10.1093/brain/awh045 Anderson, N. D., & Craik, F. I. (2017). 50 years of cognitive aging theory. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 72, 1–6. doi:10.1093/geronb/ gbw108 Bao, Y., Zhou, J., & Fu, L. (2004). Aging and the time course of inhibition of return in a static environment. Acta Neurobiologiae Experimentalis, 64, 403–414. Bayer, A., Phillips, M., Porter, G., Leonards, U., Bompas, A., & Tales, A. (2014). Abnormal inhibition of return in mild cognitive impairment: Is it specific to the presence of prodromal dementia? Journal of Alzheimer’s Disease, 40, 177–189. doi:10.3233/ JAD-131934 Bélanger, S., Belleville, S., & Gauthier, S. (2010). Inhibition impairments in Alzheimer’s disease, mild cognitive impairment and healthy aging: Effect of congruency proportion in a stroop task. Neuropsychologia, 48, 581–590. doi:10.1016/j. neuropsychologia.2009.10.021 Campbell, K. L., Grady, C. L., Ng, C., & Hasher, L. (2012). Age differences in the frontoparietal cognitive control network: Implications for distractibility. Neuropsychologia, 50, 2212– 2223. doi:10.1016/j.neuropsychologia.2012.05.025 Castel, A. D., Chasteen, A. L., Scialfa, C. T., & Pratt, J. (2003). Adult age differences in the time course of inhibition of return. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 58, P256–P259. doi:10.1093/geronb/58.5.P256 Cerella, J. (1985). Information processing rates in the elderly. Psychological Bulletin, 98, 67–83. doi:10.1037/0033- 2909.98.1.67 Davidson, D. J., Zacks, R. T., & Williams, C. C. (2003). Stroop interference, practice, and aging. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 10, 85–98. doi:10.1076/anec.10.2.85.14463 Dukewich, K. R., & Klein, R. M. (2015). Inhibition of return: A phenomenon in search of a definition and a theoretical framework. Attention, Perception & Psychophysics, 77, 1647–1658. doi:10.3758/s13414-015-0835-3 Fang, R., Wang, G., Huang, Y., Zhuang, J. P., Tang, H. D., Wang, Y., & Ren, R. J. (2014). Validation of the Chinese version of Addenbrooke’s cognitive examination-revised for screening mild Alzheimer’s disease and mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 37, 223–231. doi:10.1159/000353541 Folstein, M. F., Robins, L. N., & Helzer, J. E. (1983). The mini-mental state examination. Archives of General Psychiatry, 40, 812. doi:10.1001/archpsyc.1983.01790060110016 Gamaldo, A. A., Sardina, A. L., Corona, R. T., Willingham, K., Migoyo, R. V., & Andel, R. A. (2018). The association between educational parameters and a cognitive screening measure in older blacks. International Psychogeriatrics, 30, 311–322. doi:10.1017/S1041610217001107 Gazzaniga, M. S., Ivry, R. B., & Mangun, G. R. (2014). Cognitive neuroscience: The biology of the mind (4th ed.). New York: Norton. Grady, C., Sarraf, S., Saverino, C., & Campbell, K. (2016). Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks. Neurobiology of Aging, 41, 159–172. doi:10.1016/j.neurobiolaging.2016.02.020 Hasher, L., Lustig, C., & Zacks, R. T. (2007). Inhibitory mechanisms and the control of attention. In Conway, A., Jarrold, C., Kane, M., Miyake, A., & Towse, J. (Eds.). Variation in working memory (pp. 227–249). New York: Oxford University Press. Hasher, L., Stoltzfus, E. R., Zacks, R. T., & Rypma, B. (1991). Age and inhibition. Journal of Experimental Psychology. Learning, Memory, and Cognition, 17, 163–169. doi:10.1037/0278- 7393.17.1.163 Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. Psychology of Learning and Motivation, 22, 193–225. doi:10.1016/S0079-7421(08)60041–9 Hodges, J. R. (2007). Cognitive assessment for clinicians (2nd ed.). New York: Oxford University Press. Hodges, J. R. (2013). Cognitive assessment for clinicians. (in Chinese; Xiong, L., Liu, H., & Yang, Z. X. (Eds.), Trans. L. Zhou (Ed.), 2nd ed.). Wu Han, China: Huazhong University of Science & Technology Press (Original work published in 2007). 760 Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022
Journals of Gerontology:PSYCHOLOGICAL SCIENCES,2020,Vol.75,No.4 761 HopfingerB.&Mangun,G.R.(21)Tracking the influence Nasreddine,.5 Phillips,N.A Bedirian,V Charbonneau,5. 05).h MoCA:A br doi10.3758CABN.1.156 Klein,R.M.(200 1470-100014 Societ 53.695-699.doi:10.1111M.1532.5415.2005.53221 Kran .S. on.M.S from An ana olombe,A.&Scialfa.C.T.(2006 Aging,memory and ice.20 visual s Psychologica,122,288-304.doi:10.1016/j 65 008.200 Laneler.LK Fricsen.C.K..Saville.A.L&Ciernia,A.T.(2011). l of Medicine.256.183-194 Timing of reflexive visuospatial orienting in young,young-od 46-156 d adul oplrysics.73. Larner A.I Mitchell A I 02014)A metaranalysis of the ad 32.531-556 ed (ACE capa a003088 oral Reviews.57.156-174 doi10.10370033-295X.103.3.403 A.0.1 Luo, H.(2014 the montreal cognitive assessn ent in community agh 0 band.The lo ie34.48374844 adults ding in the do10.1523NEUR05G1.4856-13.2014 4.de G.E Fags.R. A M CH.2011.T R National Institut onnAlheimer'As ociation May A R Do ,L2004 a.7.280-292.do10.1016ia2.201103.003 ing e and exogcnous visua Tom ugh,T.N.,Mclntyre,N.J.(1992).The mini ntal stat age,23,534-541 doi:10.1016f McGinnis,D.(2012).Susceptibility to distraction during eading h01992X and old-old adult 07502 5.H.Raczek,M..Philpot,M.,Lindesay Mioshi.E Da (2006).The addenb oke's C nitive examination revised 1247-1262.doi:10.117 S104161021400041 10100 (2002.A Mitchell,A.(2009).A meta-analysis of the ac racy of the 26,849-857.dot10.1016/50149.7634102y00071 W M.,Wild-Wall,N 2011 431n.101016i hirss 2008 04 014 mation Neuroscience Letters.487 66-69.doi:10.1016/ Muinos,M.,Palmero,E Ballesteros,.(2016).Peripheral vision, eulet.2010.09.07S Ma perceptual and visuospatial attention in yo Hasher,L (201 and beneficia 30-36.doi10.1016.exget2.015.12.006 Fromtiers in Psycology,5,133.doi:10.3389/psyg.2014.00133
Hopfinger, J. B., & Mangun, G. R. (2001). Tracking the influence of reflexive attention on sensory and cognitive processing. Cognitive, Affective & Behavioral Neuroscience, 1, 56–65. doi:10.3758/CABN.1.1.56 Klein, R. M. (2000). Inhibition of return. Trends in Cognitive Sciences, 4, 138–147.doi:10.1016/S1364-6613(00)01452-2 Kramer, A. F., Boot, W. R., McCarley, J. S., Peterson, M. S., Colcombe, A., & Scialfa, C. T. (2006). Aging, memory and visual search. Acta Psychologica, 122, 288–304. doi:10.1016/j. actpsy.2005.12.007 Langley, L. K., Friesen, C. K., Saville, A. L., & Ciernia, A. T. (2011). Timing of reflexive visuospatial orienting in young, young-old, and old-old adults. Attention, Perception & Psychophysics, 73, 1546–1561. doi:10.3758/s13414-011-0108-8 Larner, A. J., & Mitchell, A. J. (2014). A meta-analysis of the accuracy of the Addenbrooke’s Cognitive Examination (ACE) and the Addenbrooke’s Cognitive Examination-Revised (ACE-R) in the detection of dementia. International Psychogeriatrics, 26, 555–563. doi:10.1017/S1041610213002329 Li, H. J., Hou, X. H., Liu, H. H., Yue, C. L., Lu, G. M., & Zuo, X. N. (2015). Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging. Neuroscience and Biobehavioral Reviews, 57, 156–174. doi:10.1016/j.neubiorev.2015.08.013 Luis, C. A., Keegan, A. P., & Mullan, M. (2009). Cross validation of the montreal cognitive assessment in community dwelling older adults residing in the Southeastern US. International Journal of Geriatric Psychiatry, 24, 197–201. doi:10.1002/gps.2101 Mathuranath, P. S., Nestor, P. J., Berrios, G. E., Rakowicz, W., & Hodges, J. R. (2000). A brief cognitive test battery to differentiate Alzheimer’s disease and frontotemporal dementia. Neurology, 55, 1613–1620.doi:10.1212/01.wnl.0000434309.85312.19 Mayer, A. R., Dorflinger, J. M., Rao, S. M., & Seidenberg, M. (2004). Neural networks underlying endogenous and exogenous visualspatial orienting. Neuroimage, 23, 534–541. doi:10.1016/j. neuroimage.2004.06.027 McGinnis, D. (2012). Susceptibility to distraction during reading in young, young-old, and old-old adults. Experimental Aging Research, 38, 370–393. doi:10.1080/0361073X.2012.699365 Mioshi, E., Dawson, K., Mitchell, J., Arnold, R., & Hodges, J. R. (2006). The addenbrooke’s Cognitive Examination Revised (ACE-R): A brief cognitive test battery for dementia screening. International Journal of Geriatric Psychiatry, 21, 1078–1085. doi:10.1002/gps.1610 Mitchell, A. J. (2009). A meta-analysis of the accuracy of the minimental state examination in the detection of dementia and mild cognitive impairment. Journal of Psychiatric Research, 43, 411– 431. doi:10.1016/j.jpsychires.2008.04.014 Muiños, M., Palmero, F., & Ballesteros, S. (2016). Peripheral vision, perceptual asymmetries and visuospatial attention in young, young-old and oldest-old adults. Experimental Gerontology, 75, 30–36. doi:10.1016/j.exger.2015.12.006 Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I.,…Chertkow, H. (2005). The montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53, 695–699. doi:10.1111/j.1532-5415.2005.53221.x Pastötter, B., Hanslmayr, S., & Bäuml, K. H. (2008). Inhibition of return arises from inhibition of response processes: An analysis of oscillatory beta activity. Journal of Cognitive Neuroscience, 20, 65–75. doi:10.1162/jocn.2008.20010 Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194. doi:10.1111/j.1365-2796.2004.01388.x Posner, M. I., & Cohen, Y. (1984).Components of visual orienting. Attention and Performance X: Control of Language Processes, 32, 531–556. Rodríguez-Villagra, O. A., Göthe, K., Oberauer, K., & Kliegl, R. (2013). Working memory capacity in a go/no-go task: Age differences in interference, processing speed, and attentional control. Developmental Psychology, 49, 1683–1696. doi:10.1037/ a0030883 Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403–428. doi:10.1037/0033-295X.103.3.403 Song, K., Meng, M., Chen, L., Zhou, K., & Luo, H. (2014). Behavioral oscillations in attention: Rhythmic α pulses mediated through θ band. The Journal of Neuroscience, 34, 4837–4844. doi:10.1523/JNEUROSCI.4856-13.2014 Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M.,…Phelps, C. H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7, 280–292. doi:10.1016/j.jalz.2011.03.003 Tombaugh, T. N., & McIntyre, N. J. (1992). The mini-mental state examination: A comprehensive review. Journal of the American Geriatrics Society, 40, 922–935.doi:10.1111/j.1532–5415.1992. tb01992.x Velayudhan, L., Ryu, S. H., Raczek, M., Philpot, M., Lindesay, J., Critchfield, M., & Livingston, G. (2014). Review of brief cognitive tests for patients with suspected dementia. International Psychogeriatrics, 26, 1247–1262. doi:10.1017/ S1041610214000416 Verhaeghen, P., & Cerella, J. (2002). Aging, executive control, and attention: A review of meta-analyses. Neuroscience and Biobehavioral Reviews, 26, 849–857. doi:10.1016/S0149-7634(02)00071-4 Wascher, E., Falkenstein, M., & Wild-Wall, N. (2011). Age related strategic differences in processing irrelevant information. Neuroscience Letters, 487, 66–69. doi:10.1016/j. neulet.2010.09.075 Weeks, J. C., & Hasher, L. (2014). The disruptive - and beneficial - effects of distraction on older adults’ cognitive performance. Frontiers in Psychology, 5, 133. doi:10.3389/fpsyg.2014.00133 Journals of Gerontology: PSYCHOLOGICAL SCIENCES, 2020, Vol. 75, No. 4 761 Downloaded from https://academic.oup.com/psychsocgerontology/article/75/4/753/5033575 by Southern Medical University user on 04 May 2022