The demographic change leads to an increase of older persons in all societies world-wide. Even healthy aging is accompanied by a variety of motivational, emotional, sensory, psychomotor, and cognitive changes (e.g., Grady, 2008; Salthouse, 1976; Schaie & Gribbin, 1975), which influence work ability and everyday life activities. Ageaccompanying cognitive changes are extremely different among the older population, resulting in very poor, equivalent, or even better performance as in younger persons. Such variability among the older population often result from compensatory mechanisms as activated by the ‘‘good’’ older performers (e.g., Getzmann, 2012). Cognitive abilities in elderly are influenced by multiple factors, such as genetics (e.g., Gajewski, Hengstler, Golka, Falkenstein, & Beste, 2013), education (Stern, 2012) lifestyle (Chan, Yan, & Payne, 2013; Getzmann, Falkenstein, & Gajewski, 2013) and work conditions (Gajewski, Wild-Wall, Schapkin, Erdmann, Freude, & Falkenstein, 2010; Marquie, Duarte, Bessi res, Dalm, Gentil, & Ruidavets, 2010). Age-related cognitive changes are not always seen in overt behavior, since older subjects very often initiate compensatory mechanisms (e.g., Zcllig & Eschen, 2009). Such mechanisms can exist on a macroscopic, usually conscious, level (e.g., in driving more slowly or avoiding difficult traffic situations) or on a microscopic, process-related and usually unconscious, level (e.g., by increasing attention or preparation). One way to elucidate age-related compensation mechanisms is the use of neuroscientific methods and techniques. Such methods can shed more light on the source(s) of age-related cognitive changes per se (e.g., Grady, 2008), or on compensation mechanisms at the process level (e.g., Alperin, Mott, Rentz, Holcomb, & Daffner, 2014; Wiegand, Tcllner, Dyrholm, M ller, Bundesen, & Finke, 2014; Wild-Wall, Hahn, & Falkenstein, 2011). In the field of human neurosciences, the main methods are electroencephalography (EEG), with the analysis of oscillatory activity in distinct frequency bands (e.g., Bornas et al., 2013; Gilmore & Fein, 2013; Knyazev, SlobodskojPlusnin, Yu, & Bocharov, 2012), coherence/correlation between locations (e.g., Blum, Lutz, & J ncke, 2007), and in particular event-related potentials (ERPs; e.g., Berti & W hr, 2012; Blom, Wiering, & Van der Lubbe, 2012; Boksem, Kostermans, Tops, & De Cremer, 2012, Sulykos, Kecsk s-Kov cs, & Czigler, 2013; Wronka & Walentowska, 2014), structural and functional magnetic resonance imaging (fMRI; e.g., Eyler, Sherzai, Kaup, & Jeste, 2011; Fjell & Walhovd, 2010), and more recently near-infrared spectroscopy (NIRS; e.g., Fabiani, Gordon, Maclin, Pearson, Brumback-Peltz, Low, McAuley, Sutton, Kramer, & Gratton, 2014). Finally, genetic methods are increasingly important and show the profound influence of genetic variations on cognition in elderly (Gajewski, Hengstler, Golka, Falkenstein, & Beste, 2013; Getzmann, Gajewski, Hengstler, Falkenstein, & Beste, 2013). All those methods have been used in addition to behavioral and neuropsychological methods. Because of their miniature technical equipment and minimum intrusivity, EEG/ERP methods are particularly useful in applied research, such as in exposure chambers (Juran, van Thriel, Kleinbeck, Sch per, Falkenstein, Iregren, & Johanson, 2013), in driving simulators (Kostermans, Spijkerman, Engels, Bekkering, & de Bruijn, 2013), or in clinical research (e.g., Carozzo, Martinoli, & Sannita, 2014). While all those methods have their pros and cons, electroencephalography, and event-related potentials are particularly suitable for elderly and old participants. In comparison to the heavy and somehow threatening character of the fMRI method for elderly, EEG electrodes and caps are only minimum intrusive and hence well tolerated by elderly. The disadvantage of the EEG method, its relatively poor spatial resolution, can be overcome by the use of sophisticated source analysis methods (e.g., Debener, Hine, Bleeck, & Eyles, 2008). Despite the clear advantage of the EEG/ERP method it has been less used in aging research than the fMRI method. However, there is a slowly rising world-wide tendency to recognize the potential of the method in aging research (e.g., Bender, Bluschke, Dippel, Rupp, Weisbrod, & Thomas, 2014; Getzmann, 2012; Kopp,
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