Abstract Background Mental fatigue is a psychobiological state induced by sustained periods of demanding cognitive activity and is characterized by feelings of tiredness which are common in everyday life. Recently, it has been hypothesized that mental fatigue might have an impact on gait performance in old adults. Therefore, the effect of mental fatigue on gait performance under single- and dual-task conditions was investigated in young and old participants. Methods Spatio-temporal gait parameters of 16 young and 16 old healthy participants were measured using a photoelectric system during single- and dual-task walking before and after a randomly assigned mental fatigue (performing a stop-signal task for 90 minutes) and control intervention (watching a video for 90 minutes), respectively. Changes in subjective fatigue, wakefulness, mood, arousal, and psychophysiological workload (heart rate variability indices) were assessed. Results Psychometric measures indicated increased subjective fatigue and arousal as well as decreased mood and wakefulness after the mental fatigue task. Heart rate variability indices revealed a higher psychophysiological workload during the mental fatigue intervention in old compared to young participants. Gait measures (coefficient of variation of speed, stride length, and stance time) revealed impaired dual-task walking performance following the mental fatigue intervention only in old participants. Conclusion Data indicate that mental fatigue, induced by sustained cognitive activity, can impair gait performance during dual-task walking in old adults. The susceptibility to mental fatigue could be a new intrinsic risk factor for falls in older people and should be taken into account when dual-task gait analyses are performed. Cognitive fatigue, State fatigue, Trait fatigue, Gait analysis, Aging, Cognitive-motor interference, Fall risk According to Enoka and Duchateau (1) fatigue can be defined as a self-reported disabling symptom which is derived from two interdependent attributes: perceived fatigability and performance fatigability. Perceived fatigability is characterized by changes in the sensations that regulate the integrity of the performer, whereas performance fatigability is related to changes in objective measures of performance over a defined period of time. Based on this assumption, the symptom fatigue can only be measured by self-report and requires the individual to interpret relevant psychological and physiological factors. Similar to other symptoms, fatigue can be assessed as a trait characteristic or a state variable. While the trait level of fatigue comprises the fatigue experienced during the previous day(s), the state level of fatigue reflects the rate of change of fatigue during a fatiguing task (for reviews, see refs. (1,2)). In general, fatigue can emerge after physical as well as cognitive activity. Prolonged and/or sustained periods of demanding cognitive activity can result in state fatigue, here termed mental fatigue. Some authors prefer the term cognitive fatigue to describe the psychobiological state associated with sustained cognitive activity. However, it has been recently proposed that the term mental fatigue is more appropriate, since it also includes motivational and emotional aspects associated with task accomplishment and not only cognition (3). Mental fatigue can manifest subjectively (ie, feelings of tiredness or even exhaustion) and/or objectively (ie, change in cognitive and behavioral performance as well as physiological correlates) (3–5). The extent of mental fatigue largely depends on the amount of time spent on a given task (6) and is probably modulated by task complexity. Recently, it was hypothesized that mental fatigue might have an impact on gait performance in old adults. This assumption is based on the outcome of studies that have shown an association between poor cognitive function and poor gait performance in healthy older people (7). Conversely, the acute increase of cognitive functioning, for example, by ingestion of methylphenidate, has been shown to decrease gait variability in old adults (8). Moreover, it has been revealed that the level of trait fatigue was associated with an attenuated increase in prefrontal cortex oxygenation from single- to dual-task walking as well as an altered trajectory of the oxygenation signal during the completion of repetitive dual-task walking trials (9). Based on the outcomes of the above-mentioned studies, temporarily impaired cognitive functioning due to mental fatigue could have distinct effects on gait performance especially during dual-task walking, for example, walking while simultaneously performing a cognitive interference task. Structural and functional changes within the brain have been observed with aging probably leading to a decline in cognitive performance which is particularly associated with dual-task gait measures (10). By contrast, the relationship between cognitive performance and dual-task gait measures was not observed in young adults (11). Therefore, it might be that the susceptibility to mental fatigue and the potential decline in gait performance is more pronounced in older compared to younger adults. To the authors’ knowledge, no study exists that has investigated the impact of mental fatigue, induced by sustained cognitive activity, on single- and dual-task gait performance in young and old adults. In consideration of this, we assessed single- and dual-task walking performance in young and old participants before and after a randomly assigned mental fatigue and control intervention, respectively. It was hypothesized that mental fatigue impairs gait performance in old adults, in particular while performing a concurrent attention demanding cognitive interference task. Methods Participants Sixteen young and 16 old participants without known history of neurological disorders and/or musculoskeletal injuries volunteered to participate in the present study. Demographic characteristics of the participants are given in Supplementary Table 1. All volunteers were informed about the experimental procedures and possible risks associated with the experiment before giving their written consent. The participants were asked to refrain from strenuous exercise as well as alcohol and caffeine consumption 48 hours prior to the experiments. The study was conducted according to the declaration of Helsinki and was approved by the local ethics committee. Experimental Protocol This study employed a randomized and counterbalanced cross-over design. The participants visited the laboratory on two different occasions with at least one week in between. They completed questionnaires and were instructed regarding the experimental procedures. During the experiments, participants completed two randomly assigned interventions on different days: (i) stop-signal task for 90 minutes to induce mental fatigue and (ii) control treatment consisting of watching a neutral video for 90 minutes. Before and after each intervention subjective fatigue, wakefulness, mood, arousal as well as gait performance under single- and dual-task conditions were recorded. The order of the gait tests was randomized. Questionnaires The Mini-Mental State Examination (MMSE) was applied to verify proper cognitive functioning of the participants (12). Furthermore, the Falls Efficacy Scale International (FES-I) was used as a measure of fall related self-efficacy in older persons (13). The Modified Fatigue Impact Scale (MFIS) was utilized to assess trait fatigue and the fatigue scale of the Profile of Mood States (POMS-F) was used to measure state fatigue (14). Moreover, the Multidimensional Mood Questionnaire (MDMQ) was employed to assess wakefulness, mood, and arousal (15). Gait Analysis Spatio-temporal gait parameters were measured using a photoelectric walkway (OptoGait, Microgate, Italy) as described previously (16,17). Briefly, participants walked in their own, flat shoes through a 6-m walkway at self-selected comfortable gait speed, starting and stopping each trial 2 m before and after the walkway. During the gait tests, the subjects wore always the same shoes. Two familiarization and five experimental trials were performed for the single- and dual-task condition, respectively. The order of the gait tests was randomized. The following parameters were calculated: speed normalized to height (speed × height–1), step length and stride length normalized to height (step length × height–1, stride length × height–1), step time, single support time, double support time, stance time, and swing time. Furthermore, the coefficient of variation (CV), an index of gait variability and a predictor of falls in older adults (18), was calculated for each parameter (CV = standard deviation × mean–1 × 100). Cognitive Interference Task In addition to the single-task walking trials, gait parameters were also recorded while performing a concurrent attention demanding cognitive interference task (without explicit instructions regarding prioritization). The task consisted of serial subtractions by three, starting from a randomly selected number between 300 and 900. The results of this arithmetic task had to be recited verbally by the participants and the cognitive interference task performance was calculated by subtracting the number of mistakes from the total number of subtractions. The higher the value, the better the performance (19). Psychophysiological Workload Psychophysiological workload during the 90 minutes lasting mental fatiguing and control task was analyzed using heart rate variability. Inter-heartbeat intervals (RRI) were continuously recorded during both interventions using a heart rate monitor (Polar Electro, Finland). The root mean square of the successive differences of adjacent RRI (RMSSD) and the natural log-transformed power in the low frequency range (0.05–0.15 Hz) of the R-R frequency spectrum (lnLFP), both able to reflect mental effort (20,21), were calculated (Kubios HRV 2.2, University of Kuopio, Finland). Mental Fatigue and Control Intervention During the mental fatigue intervention, participants had to perform a stop-signal task (22) for 90 minutes on a personal computer. This task is a commonly used laboratory measure of inhibitory control that consisted of presenting concurrent go and stop tasks. Participants had to press a button with the right or left hand as quickly and accurately as possible in response to the visual presentation of the letter X or O, respectively. The stop signal consisted of a delayed tone presented by headphones and, if it occurred, required stopping the ongoing response to the letter X or O. To increase engagement in and motivation for the stop-signal task, a cash prize was announced. The stop-signal reaction times were computed (23,24) to monitor performance during the mental fatiguing task. The average of this parameter was calculated for eight blocks during the stop-signal task. The control intervention consisted of watching the documentary “Earth” for 90 minutes on the same computer used for the mental fatigue task (25). Statistical Analyses Data were screened for normal distribution using the Shapiro-Wilk test. Data analysis of the performance measures during the mental fatigue task revealed missing values. To account for missing data, multiple imputation (10 imputed data sets) with the Markov Chain Monte Carlo method was used (26). Repeated measures analyses of variance (ANOVAs) with time of measurement (pre, post) as well as condition (mental fatigue, control) as within-subject variables and group (young, old) as between-subject variable were conducted for the average of each parameter. Due to the unequal distribution of males and females between groups, sex was entered as a covariate. In case of statistical significant interactions, Bonferroni-corrected post-hoc tests were carried out. Effect sizes were expressed as partial eta-squared (ηp2). The level of statistical significance was set at p ≤ .050. In addition, tendencies towards statistical significance were also interpreted (p ≤ .055). Data were analyzed using the SPSS statistical package 22.0 (SPSS Inc., USA). Results Questionnaires The scores of the MMSE (28.3 ± 1.6) and FES-I (18.3 ± 1.5) indicated that the old participants were cognitively healthy and without any serious concerns about falling. MFIS scores, a measure of trait fatigue, did not differ between groups (young: 14.6 ± 10.0, old: 11.4 ± 8.9, p = .424). Significant main effects of time, condition, and group were found for the POMS-F, a measure of state fatigue. A time × condition interaction was observed for the POMS-F (Supplementary Table 2). Post-hoc analysis revealed that the POMS-F score increased significantly in both groups after performing the mental fatigue task (mental fatigue: p < .001, control: p = .115). Several significant main and interaction effects of time, condition, and group were found for the MDMQ wakefulness, mood and arousal scores. Time × condition interactions were observed for the MDMQ wakefulness, mood and arousal scores (supplemental Table 2). Post-hoc analysis showed that the participants felt more tired following the mental fatigue task (mental fatigue: p < .001, control: p < .001). In addition, significant changes of the participants’ scores towards negative mood (mental fatigue: p = .001, control: p = .072) and feeling nervous (mental fatigue: p = .016, control: p = .286) were only observed in the mental fatigue condition (Figure 1, Supplementary Table 3). No time × condition × group interactions were found. Figure 1. View largeDownload slide State fatigue (Profile of Mood States-Fatigue, POMS-F) (A) as well as the dimensions wakefulness (awake-tired) (B), mood (positive-negative) (C), and arousal (calm-nervous) (D) of the Multidimensional Mood Questionnaire (MDMQ) for the young and old participants before and after the mental fatigue and control intervention. Please note that the lower the value of the respective MDMQ score, the more tired, negative and nervous the participants felt. Time × condition interactions were observed for these variables indicating that mental fatigue was induced successfully in all participants. Figure 1. View largeDownload slide State fatigue (Profile of Mood States-Fatigue, POMS-F) (A) as well as the dimensions wakefulness (awake-tired) (B), mood (positive-negative) (C), and arousal (calm-nervous) (D) of the Multidimensional Mood Questionnaire (MDMQ) for the young and old participants before and after the mental fatigue and control intervention. Please note that the lower the value of the respective MDMQ score, the more tired, negative and nervous the participants felt. Time × condition interactions were observed for these variables indicating that mental fatigue was induced successfully in all participants. Gait Performance Single-task walking Significant main and interaction effects of time, condition, and group were observed for several single-task gait parameters. Significant time × condition interactions were found for the parameters speed × height–1, step length × height–1, stride length × height–1, step time, double support time, CVsingle support time, CVstance time, and CVswing time (Supplementary Table 2). However, post-hoc analyses did not yield a significant change of any variable over time. No time × condition × group interactions were found (Supplementary Table 4). Dual-task walking Significant main and interaction effects of time, condition, and group were observed for several dual-task gait parameters. No time × condition interactions were found. Significant and tendential significant time × condition × group interactions were revealed for the parameters CVspeed, CVstride length, CVdouble support time, CVstance time, and CVswing time (Supplementary Table 2). Post-hoc analyses yielded significant changes of these variables over time in the mental fatigue condition only for the old participants (Figure 2, Supplementary Table 5). Figure 2. View largeDownload slide Coefficient of variation (CV) for the spatio-temporal dual-task gait parameters speed (A), stride length (B), stance time (C), double support time (D), and swing time (E) for the young and old participants recorded before and after the mental fatigue and control intervention, respectively. *p = .013, **p ≤ .008. Figure 2. View largeDownload slide Coefficient of variation (CV) for the spatio-temporal dual-task gait parameters speed (A), stride length (B), stance time (C), double support time (D), and swing time (E) for the young and old participants recorded before and after the mental fatigue and control intervention, respectively. *p = .013, **p ≤ .008. Cognitive Interference Task Performance A significant main effect of group and interaction effects of time, condition, and group were observed for the cognitive interference task performance (Supplementary Table 2). A significant time × condition interaction was found for the cognitive interference task performance (Supplementary Table 2). Post-hoc analysis revealed that the performance index decreased significantly in both groups after performing the mental fatigue task (mental fatigue: p = .016, control: p = .286). No time × condition × group interactions were found (Supplementary Table 3). Psychophysiological Workload Significant main and interaction effects of time, condition, and group were found for the heart rate variability measures. Significant condition × group interactions were found for lnLFP and RMSSD (Supplementary Table 2). Post-hoc analyses revealed that, compared to the young participants, RMSSD (p = .022) and lnLFP (p = .002) in the old participants were lower during the mental fatiguing task but not during the control condition (p = .196 and p = .063) (Supplementary Table 3). Performance Measure During the Mental Fatigue Intervention Missing data amounted 8.5% and was refilled using multiple imputation (see statistical analyses). A significant main effect of group was observed for stop-signal reaction time (Supplementary Table 2). The stop-signal reaction times of the young and old participants did not change significantly over time and no time × group interaction was found (Supplementary Table 6). Discussion The present study was designed to investigate, for the first time, the effect of an increased level of state fatigue induced by sustained cognitive activity, that is, mental fatigue, on single- and dual-task gait performance in young and old adults. Changes in self-reported state fatigue as well as in self-reported wakefulness, mood, and arousal indicate that mental fatigue was induced successfully in our participants. This is in line with the results of studies that have used a similar computer-controlled task to provoke mental fatigue (25). Heart rate variability analyses implicate a stronger psychophysiological workload response and a higher cognitive effort during the mental fatiguing task in the old adults (20,21). However, performance measure during the stop-signal task did not change significantly. An increase in subjective measures of mental fatigue without a change in performance during the fatiguing task has been revealed in various studies. Therefore, it has been stated that mental fatigue does not necessarily lead to performance decrements during the fatiguing task (5). Recently, Holtzer et al. (9) analyzed the effect of trait fatigue, assessed over a 24-hour period, on dual-task gait measures in old adults. They could not reveal an association between subjective fatigue and dual-task gait performance. However, they have shown that stride velocity declined progressively during the completion of repetitive dual-task walking trials but not during single-task walking trials. Thus, they suggested that the decrease in stride velocity during dual-task walking could serve as an index for objective mental fatigue during this motor task. In accordance with our hypothesis, mental fatigue negatively affected gait variability. Interestingly, this was only observed for the old participants in the dual-task condition. Data indicate that dual-task gait variability, in terms of walking speed, stride length, stance time, double support time, and swing time, increased significantly following the mental fatiguing task only in the old participants. In addition, cognitive interference task performance was decreased following the mental fatiguing task in all participants. It has been shown that specific brain areas (eg, prefrontal cortex, parietal areas) are more and/or additionally activated during dual-task compared to single-task walking. Moreover, brain areas implicated in dual-task walking are also involved in executive functioning, indicating that executive resources are essential for dual-task walking (27). Structural alterations of the brain, for example, in the prefrontal areas, have been observed with aging. This factor has been identified as a contributor to decreased gait performance under dual-task conditions in older people (10). Challenging these brain areas by means of a mental fatiguing task seems to increase gait variability during dual-task walking and impairs cognitive interference task performance in the old age. This effect of mental fatigue on gait variability during dual-task walking was not observed in young people. These results indicate that young adults can cope with the cognitive interference task in a mental fatigued state without attenuating (i) processing capacity for the motor task (central capacity sharing model) and/or (ii) sequential neural processing of the motor and cognitive interference task (bottleneck model) (27). The following limitations should be considered when interpreting the results of the current study. First, although the effect of mental fatigue on dual-task gait performance of the old participants could be demonstrated, the sample size was relative small and a large number of measures was performed. Thus, further studies should be conducted to verify the present preliminary results. Second, although the old participants seemed to be active according to their self-reported physical activity level, the physical status was not quantified and its effect on the outcome measures is unknown. Third, it might be reasonably assumed that the dual-task gait parameters, which underwent a significant change, are highly related to each other. Thus, one of these parameters could be used as a surrogate in future studies. Although it is currently common, the present study was not notified to a clinical trial register and therefore lacks a trial registration number. In conclusion, data indicate, for the first time, that mental fatigue, induced by sustained cognitive activity, can impair gait performance during dual-task walking in old adults. Therefore, the susceptibility to mental fatigue could be a new intrinsic risk factor for falls in older people. Moreover, the potential influence of mental fatigue on gait measures should be taken into account when dual-task gait analyses are performed in a scientific or clinical context. That is, state as well as trait fatigue should be assessed prior to the measurements and should be considered when interpreting the results. Future studies should investigate (i) the underlying neural mechanisms by using neurophysiological techniques, (ii) when aging starts to exert negative effects on dual-task gait performance during states of mental fatigue, and (iii) the dose-response relationship between the extent of mental fatigue and the increase in gait variability in older adults. The latter aspect is of particular importance due to the fact that the extent of mental fatigue largely depends on the amount of time spent on a given task (6) and is probably modulated by task complexity. Besides the effect of mental fatigue on dual-task gait performance in healthy older adults, the relevance of our findings for patient populations, particularly those with neurologic diseases showing a high prevalence and severity of fatigue symptoms, should be analyzed. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Conflict of Interest None reported. References 1. Enoka RM , Duchateau J . Translating fatigue to human performance . Med Sci Sports Exerc . 2016 ; 48 : 2228 – 2238 . doi: 10.1249/MSS.0000000000000929 Google Scholar CrossRef Search ADS PubMed 2. Kluger BM , Krupp LB , Enoka RM . Fatigue and fatigability in neurologic illnesses: proposal for a unified taxonomy . Neurology . 2013 ; 80 : 409 – 416 . doi: 10.1212/WNL.0b013e31827f07be Google Scholar CrossRef Search ADS PubMed 3. Van Cutsem J , Marcora S , De Pauw K , Bailey S , Meeusen R , Roelands B . The effects of mental fatigue on physical performance: a systematic review . Sports Med . 2017 ; 47 : 1569 – 1588 . doi: 10.1007/s40279-016-0672-0 Google Scholar CrossRef Search ADS PubMed 4. Boksem MA , Tops M . Mental fatigue: costs and benefits . Brain Res Rev . 2008 ; 59 : 125 – 139 . doi: 10.1016/j.brainresrev.2008.07.001 Google Scholar CrossRef Search ADS PubMed 5. Leavitt VM , DeLuca J . Central fatigue: issues related to cognition, mood and behavior, and psychiatric diagnoses . PM R . 2010 ; 2 : 332 – 337 . doi: 10.1016/j.pmrj.2010.03.027 Google Scholar CrossRef Search ADS PubMed 6. Sandry J , Genova HM , Dobryakova E , DeLuca J , Wylie G . Subjective cognitive fatigue in multiple sclerosis depends on task length . Front Neurol . 2014 ; 5 : 214 . doi: 10.3389/fneur.2014.00214 Google Scholar CrossRef Search ADS PubMed 7. Grobe S , Kakar RS , Smith ML , Mehta R , Baghurst T , Boolani A . Impact of cognitive fatigue on gait and sway among older adults: a literature review . Prev Med Rep . 2017 ; 6 : 88 – 93 . doi: 10.1016/j.pmedr.2017.02.016 Google Scholar CrossRef Search ADS PubMed 8. Ben-Itzhak R , Giladi N , Gruendlinger L , Hausdorff JM . Can methylphenidate reduce fall risk in community-living older adults? A double-blind, single-dose cross-over study . J Am Geriatr Soc . 2008 ; 56 : 695 – 700 . doi: 10.1111/j.1532-5415.2007.01623.x Google Scholar CrossRef Search ADS PubMed 9. Holtzer R , Yuan J , Verghese J , Mahoney JR , Izzetoglu M , Wang C . Interactions of subjective and objective measures of fatigue defined in the context of brain control of locomotion . J Gerontol A Biol Sci Med Sci . 2017 ; 72 : 417 – 423 . doi: 10.1093/gerona/glw167 Google Scholar PubMed 10. Yogev-Seligmann G , Hausdorff JM , Giladi N . The role of executive function and attention in gait . Mov Disord . 2008 ; 23 : 329 – 42; quiz 472 . doi: 10.1002/mds.21720 Google Scholar CrossRef Search ADS PubMed 11. Springer S , Giladi N , Peretz C , Yogev G , Simon ES , Hausdorff JM . Dual-tasking effects on gait variability: the role of aging, falls, and executive function . Mov Disord . 2006 ; 21 : 950 – 957 . doi: 10.1002/mds.20848 Google Scholar CrossRef Search ADS PubMed 12. Folstein MF , Folstein SE , McHugh PR . “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician . J Psychiatr Res . 1975 ; 12 : 189 – 198 . Google Scholar CrossRef Search ADS PubMed 13. Kempen GI , Todd CJ , Van Haastregt JC et al. Cross-cultural validation of the Falls Efficacy Scale International (FES-I) in older people: results from Germany, the Netherlands and the UK were satisfactory . Disabil Rehabil . 2007 ; 29 : 155 – 162 . doi: 10.1080/09638280600747637 Google Scholar CrossRef Search ADS PubMed 14. Albani C , Blaser G , Geyer M et al. [The German short version of “Profile of Mood States” (POMS): psychometric evaluation in a representative sample] . Psychother Psychosom Med Psychol . 2005 ; 55 : 324 – 330 . doi: 10.1055/s-2004-834727 Google Scholar CrossRef Search ADS PubMed 15. Hinz A , Daig I , Petrowski K , Brahler E . [Mood in the German population: norms of the Multidimensional Mood Questionnaire MDBF] . Psychotherapie, Psychosomatik, medizinische Psychologie . 2012 ; 62 : 52 – 57 . doi: 10.1055/s-0031-1297960 Google Scholar CrossRef Search ADS PubMed 16. Stöckel T , Jacksteit R , Behrens M , Skripitz R , Bader R , Mau-Moeller A . The mental representation of the human gait in young and older adults . Front Psychol . 2015 ; 6 : 943 . doi: 10.3389/fpsyg.2015. 00943 Google Scholar CrossRef Search ADS PubMed 17. Jacksteit R , Mau-Moeller A , Behrens M et al. The mental representation of the human gait in patients with severe knee osteoarthrosis: a clinical study to aid understanding of impairment and disability . Clin. rehabil . 2017 . doi: 10.1177/0269215517719312 18. Verghese J , Holtzer R , Lipton RB , Wang C . Quantitative gait markers and incident fall risk in older adults . J Gerontol A Biol Sci Med Sci . 2009 ; 64 : 896 – 901 . doi: 10.1093/gerona/glp033 Google Scholar CrossRef Search ADS PubMed 19. Granacher U , Wolf I , Wehrle A , Bridenbaugh S , Kressig RW . Effects of muscle fatigue on gait characteristics under single and dual-task conditions in young and older adults . J Neuroeng Rehabil . 2010 ; 7 : 56 . doi: 10.1186/1743-0003-7-56 Google Scholar CrossRef Search ADS PubMed 20. Aasman J , Mulder G , Mulder LJ . Operator effort and the measurement of heart-rate variability . Hum Factors . 1987 ; 29 : 161 – 170 . doi: 10.1177/001872088702900204 Google Scholar CrossRef Search ADS PubMed 21. Vicente KJ , Thornton DC , Moray N . Spectral analysis of sinus arrhythmia: a measure of mental effort . Hum Factors . 1987 ; 29 : 171 – 182 . doi: 10.1177/001872088702900205 Google Scholar CrossRef Search ADS PubMed 22. Verbruggen F , Logan GD . Response inhibition in the stop-signal paradigm . Trends Cogn Sci . 2008 ; 12 : 418 – 424 . doi: 10.1016/j.tics.2008.07.005 Google Scholar CrossRef Search ADS PubMed 23. Logan GD , Cowan WB , Davis KA . On the ability to inhibit simple and choice reaction time responses: a model and a method . J Exp Psychol Hum Percept Perform . 1984 ; 10 : 276 – 291 . Google Scholar CrossRef Search ADS PubMed 24. Logan GD , Schachar RJ , Tannock R . Impulsivity and inhibitory control . Psychological Science . 1997 ; 8 : 60 – 64 . doi: 10.1111/j.1467–9280.1997.tb00545.x Google Scholar CrossRef Search ADS 25. Pageaux B , Marcora SM , Lepers R . Prolonged mental exertion does not alter neuromuscular function of the knee extensors . Med Sci Sports Exerc . European Medicines Agency : UK ; 2013 ; 45 : 2254 – 2264 . doi: 10.1249/MSS.0b013e31829b504a Google Scholar CrossRef Search ADS PubMed 26. Agency EM. Guideline on Missing Data in Confirmatory Clinical Trials . 2010 . 27. Leone C , Feys P , Moumdjian L , D’Amico E , Zappia M , Patti F . Cognitive-motor dual-task interference: a systematic review of neural correlates . Neurosci Biobehav Rev . 2017 ; 75 : 348 – 360 . doi: 10.1016/j.neubiorev.2017.01.010 Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
The Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences – Oxford University Press
Published: Oct 25, 2017
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