The Components of Aging
Abstract and Keywords
This chapter reviews the effects of aging on a variety of ERP components. These include the relatively early-latency P50, N1 and P2 potentials, which are thought to reflect primarily the processing of sensory aspects of experience. Although more data are required, study of these components suggests that older adults do not exhibit sensory deficits per se but may exhibit deficiencies in inhibitory processing at the relatively early stages of information processing. Other longer-latency components, such as the N2b, P3a (novelty P3) and P3b reflect higher-order cognitive functions and are modulated more by task characteristics than by the sensory properties of the events that elicit them. Age-related studies indicate prolonged latency of the N2b and P3b, consistent with the general slowing reported in the behavioral literature. The P3a, a neural sign of the orienting response thought to depend upon prefrontal cortex and its interconnections, does not habituate in older adults, suggesting that older adults continue to recruit prefrontal cortical mechanisms for events that should no longer capture their attention. Several ERP modulations are defined on the basis of a difference between electrical activity in one condition compared to that in another. These comprise the mismatch negativity, reflecting relatively automatic deviance detection, the parietal old/new or episodic memory (EM) effect, an index of recollective processing, the N400, a measure of semantic processing, the error-related negativity (ERN) and the medial-frontal negativity (MFN), the latter two reflecting executive aspects of cognition. Studies of the MMN indicate less sensitivity to deviance as we age. The parietal EM effect is sometimes smaller in older relative to young adults, suggesting an age-related reduction in the quality of information retrieved from episodic memory. The N400 literature indicates that, although the N400 shows age-related diminution, semantic processing is generally intact in older adults. Too little is known about the ERN and MFN to come to conclusions at this time. In general, this review indicates a mixed picture of spared and impaired cognitive functions as individuals age.
Keywords: cognitive aging, deviance detection, executive function, recollection, event-related potential (ERP), mismatch negativity, parietal EM effect, error-related negativity, medial-frontal negativity, P50, N1 (N100), P2 (P200), N400, N2b, P3a, P3b
Normal aging carries certain risks, not the least of which is change in those aspects of cognition, such as top-down, executive control, and mnemonic processing, that are critical for navigating everyday life and, therefore, successful aging. However, not all aspects of cognition are impaired as we age. The age-related pattern of spared and relatively compromised cognition in aging populations appears to be reflected in a pattern of spared and relatively compromised event-related potential (ERP) components. Unfortunately, the amount of research work devoted to higher-order cognitive processes as opposed to putatively sensory processes is disproportionately weighted toward the endogenous components (Friedman et al., 1997; Polich, 1996). Endogenous components are relatively insensitive to the stimulus’s physical properties, but their amplitudes and latencies are intimately linked (p. 514) to the nature of the task in which those stimuli are embedded (Sutton et al., 1967). As a result, the current review of age-related change in ERP components will, of necessity, be slanted toward these components.
Within the endogenous domain, the greatest amount of research attention has been paid to the P300 family of components (see Chapter 7, this volume), primarily using the ubiquitous oddball paradigm (Donchin & Coles, 1988). Despite what could be considered an overemphasis on the oddball task, P300s have also been recorded in an extremely wide variety of other task paradigms, including working memory (McEvoy et al., 2001), episodic memory (Friedman, 2007; Friedman et al., 2007a), task switching (Friedman et al., 2007b; Themanson et al., 2006), repetition priming (Hamberger & Friedman, 1992; Rugg et al., 1997), semantic priming (Kutas & Iragui, 1998), and selective attention (Gaeta et al., 2003; Karayanidis et al., 1995).
Because a large number of studies on aging have involved the auditory oddball paradigm (Iragui et al., 1993) and to a lesser extent its visual counterpart (Beck et al., 1980), there are a number of investigations of the aging brain’s response to the sensory information inherent in the standard, target, and novel stimuli typically presented during this task (manifested in the middle- and longer-latency components between 50 and 100 ms poststimulus), such as P1 or P50 and N1 or N100 (Reinvang et al., 2005). These relatively early components are thought to reflect the arrival of sensory information at midbrain and higher, modality-specific, cortical processing centers. Very little is known about the impact of aging on the very-early-latency auditory brainstem responses (ABRs) occurring within the first 10 ms following stimulus onset (see Chapter 4, this volume). These ABRs reflect the arrival of auditory information in the nuclei of the brainstem.
Several ERP modulations are defined on the basis of a difference between electrical activity in one condition compared to that in another, including the mismatch negativity (MMN; Näätänen et al., 2007), the negative difference (Nd) waveform in studies of selective attention (Hansen & Hillyard, 1980), the N400 in linguistic and semantic memory assessments (Chapters 6, 11, and 15, this volume), the lateralized readiness potential (LRP; Coles et al., 1988; Chapter 9, this volume), and the error-related (Falkenstein et al., 2001) and medial frontal (Gehring & Willoughby., 2002) negativities in studies of executive control (see Chapter 10, this volume). With the exception of the Nd (Gaeta et al., 2003; Karayanidis et al., 1995; Woods, 1992) and the LRP (e.g., Falkenstein et al., 2006; Zeef & Kok, 1993), for which only a small number of studies exist, age-related changes in these remaining components will be reviewed below.
I will first review aging effects on the components between 50 and 200 ms poststimulus recorded primarily in passive and active auditory oddball paradigms. Although similar studies have been conducted with comparable findings in the visual modality (see De Sanctis et al., 2008, for a review), a much greater number have used auditory stimuli. Four components have been assessed: P50, N1 (N100), P2 (P200), and N2 (N200). The MMN is part of the “N2 complex” (Näätänen et al., 2007), which includes the N2b.
Relatively Early-Latency Components
Because some of these ERP activities appear to be affected by attention, it is safest to measure them when attention is not an issue, as in the passive oddball paradigm, in which participants are instructed to ignore the stimuli. One can also measure the frequent standards within the active oddball paradigm, as these presumably do not recruit the same degree of attentional processing as targets (which typically require a reaction time, or RT, response) or novel stimuli; the latter, if sufficiently surprising, typically capture attention involuntarily (Friedman et al., 2001).
To illustrate the basic phenomena that will be reviewed in this section, Figure 18.1 (data modified from Gaeta et al., 2001a) depicts the grand-averaged young- (18–30 years old) and older-adult (65–85 years old) ERPs elicited by first-position standards occurring in a train of eight identical standards each separated by a 500 ms interstimulus-interval (ISI). Participants watched a silent movie while ignoring the trains of stimuli. Prominent P50 (also known as P1), N1, and P2 components are present in both the young and older adult grand mean data. The P50 appears larger in the older adult waveforms, whereas the N1 component is of similar magnitude in the two groups. The P2 is larger in the young adult data but only at the 8 s intertrial interval (ITI; i.e., the interval between the last tone in one train and the first tone in the next train). Furthermore, there is a marked effect of ITI on the N1 and P2 components, both of which are larger after an 8 s interval. By contrast, the P50 does not appear to be influenced by the amount of time between stimulus trains. The greater reduction in the N1 and P2 components following a 1 s compared to an 8 s ITI is (p. 515) most likely due to the refractoriness or “fatigue” of the neural generators. This is explained a few paragraphs below in greater detail. The effects of the ITI appear to be similar in both age groups because both show larger N1 and P2 components at the longer ITI. Some of these observations are mirrored in the age-related studies reviewed below.
In reviewing the evidence, there appears to be a consensus that the P50 is larger in older than young adults when it has been measured directly and reported in the published reports (Amenedo & Diaz, 1998b; Bennett et al., 2004; Bertoli et al., 2005; Chao & Knight, 1997; Czigler et al., 1992; Fabiani et al., 2006; Smith et al., 1980; Snyder & Alain, 2005) or observed by visual inspection of the published waveforms by the current author (Bertoli & Probst, 2005; Gaeta et al., 1998; Golob et al., 2007; but see Bertoli et al., 2002). Interestingly, there does not appear to be any evidence that P50 is of longer latency in older relative to young adults
The enhanced P50 amplitudes observed in older adults might reflect a deficit in inhibitory function. For example, Knight and colleagues (1989) recorded P50 components to auditory clicks in patients with dorsolateral prefrontal lesions. P50 amplitudes were reliably larger in the patients compared to the age-matched controls. A highly similar result was reported by Alho and coworkers (1994). Knight and colleagues (Alho et al., 1994; Knight et al., 1989) interpreted this to mean that the prefrontal lesion patients had lost inhibitory control over thalamically mediated gating of inputs to sensory cortex. Thus, extrapolating this result to normally aging older adults might implicate a deficit in prefrontal inhibitory control as a cause of age-related enhancement of P50 amplitudes (see also Chao & Knight, 1997; see also the review of N1 amplitude below).
Similarly, based on P50 magnitude findings, there is some support for the possibility that probable Alzheimer’s disease (PAD) patients may be characterized by deficits in inhibitory control. Further, there is limited evidence that some individuals within the aging population who show poor inhibitory control may eventually develop PAD. In healthy persons, the second of a two-click pair separated by a 500 ms interval elicits a smaller P50 than the first click (i.e., the P50 to the second click is suppressed), which has been labeled sensory gating (Freedman et al., 1987). Reduced suppression of P50 relative to normal controls was originally reported in schizophrenia patients (i.e., the response to the second click was less suppressed in the patients; Adler et al., 1985; Siegel et al., 1984; Chapter 19, this volume). The reduced suppression was interpreted as indexing a deficit in inhibition, or sensory gating (i.e., a failure to filter irrelevant input) and a proclivity to sensory overload, consistent with some schizophrenia symptomatology (Braff & Geyer, 1990; Freedman et al., 1987). Based on these findings, there is some very limited evidence that altered P50 suppression might be a marker of PAD (Ally et al., 2006; Cancelli et al., 2006; Jessen et al., 2001), because, as in schizophrenia patients, the suppression has been reported to be smaller in PAD patients than in age-matched controls. Applying the interpretation proffered for schizophrenia patients would suggest that PAD patients may also be characterized by sensory gating difficulties. However, the results of the studies of P50 suppression in PAD are difficult to evaluate because, in two of them, the waveforms from PAD patients and controls were not depicted, precluding a determination of the quality of the data and the measurement technique (Donchin et al., 1977). Other studies have indicated that the P50 component itself is larger in patients with mild cognitive impairment (MCI), a putative precursor stage to PAD, compared to age-matched, healthy controls. Hence, poor inhibitory control (i.e., enhanced P50 magnitudes relative to age-matched controls) may be a predictor of conversion to PAD (Golob et al., 2001, 2007; Irimajiri et al., 2005).
(p. 516) Like the P50, the N1 has also been reported to be larger in older than young adults (Alain & Woods, 1999; Amenedo & Diaz, 1999; Anderer et al., 1996; Chao & Knight, 1997; Gaeta et al., 2002; Karayanidis et al., 1995; Kisley et al., 2005; Snyder & Alain, 2005), although there is little evidence for age-related prolongation of N1 latency (Anderer et al., 1996; Goodin et al., 1978; Iragui et al., 1993). On the other hand, there are also data suggesting that young, relative to older, adults show larger amplitudes (Bennett et al., 2004; Bertoli & Probst, 2005; Cooper et al., 2006; Ford et al., 1995; Golob et al., 2001). Confusing the picture further, still other studies have reported equivalent amplitudes between young and older adults (Bertoli et al., 2002; Czigler et al., 1992; Ford et al., 1995; Friedman et al., 1993b; Gaeta et al., 1998, 2001b, 2003; Iragui et al., 1993; Pekkonen et al., 1996; Picton et al., 1984; Woods, 1992). One possible explanation for these disparate results is the quite different paradigms under which the N1 has been measured, including passive and active oddballs, startle-noise oddball, delayed match-to-sample, and selective and cued attention tasks. As noted, N1 is modulated by attention; for example, it is larger to targets (deviants) than standards and to attended compared to unattended standards during selective attention tasks (Hillyard et al., 1973; Näätänen & Picton, 1987; Chapter 11, this volume). To the extent that these attentional effects differ for young and older adults, some of these differences could be accounted for on this basis. However, as shown by Amenedo and Diaz (1999), older adults demonstrated larger N1 magnitudes whether the standards were attended or unattended. Hence, although the data are clearly limited, age-related differences in attentional function may not explain these discrepancies (see also Gaeta et al., 2003).
An alternative explanation might lie in age-related differences in the recovery cycle or refractory period of the N1. That is, if the time between successive auditory events is short (e.g., 500 ms), the N1 to the second in a series of tones will be markedly smaller than that to the first. As the interval between successive stimuli becomes longer, the N1 generators “recover” some of their amplitude, producing equivalent magnitude to the first tone at an interval between 6 and 10 s (Davis et al., 1966). There is some recent evidence that older adults do show different N1 recovery functions than their young adult counterparts (Fabiani et al., 2006), although the underlying mechanism may not be a simple age-related change in the refractory period of N1 generators (Sable et al., 2004). Fabiani et al. (2006; see also Gaeta et al., 2001a) presented trains of five auditory events (400 ms ISIs), with each train separated by either 1 or 5 s ITIs. Fabiani et al. (2006) reported that the recovery rate for N1 was similar for young and older adults (i.e., the N1 to the first standard in the train was larger for the 5 s compared to the 1 s ITI in both older and young adults; see also Figure 18.1). However, relative to the first tone of a train, older adults showed reliably less N1 suppression to the remaining tones compared to young adults, suggesting the possibility, as noted earlier, of age-related inefficiency in inhibitory control, or sensory gating (Chao & Knight, 1997; Hasher et al.,1991). Because N1 amplitude to the first tone in the 1 s ITI was equivalent in both age groups and was as large in older adults as in young adults in the 5 s ITI condition, the authors concluded that sensory memory was intact in older adults. On the other hand, evidence based on the MMN, suggests that sensory memory decays faster in older adults (Pekkonen, 2000), but this interpretation is open to question. I consider this issue further in the section on the MMN.
There is a dearth of studies of the N1 in PAD and MCI. Intriguingly, however, in a study in which MCI patients and controls listened passively to tones at two ISIs (2/s and 1.5/s), the two groups had equivalent N1s at the longer ISI, whereas MCI subjects showed greater N1 at the shorter ISI (Irimajiri et al., 2005). On the other hand, there is, to my knowledge, no evidence that this is also the case in PAD. In fact, one study (Pekkonen et al., 1994) found equivalent N1 magnitudes in PAD patients and controls at both 1 s and 3 s ISIs. In another study, Yamaguchi and colleagues (2000) reported reliably smaller N1 magnitudes in PAD patients relative to age-matched controls. Hence, these results must be interpreted cautiously. Nonetheless, they suggest that this phenomenon should be explored further in PAD patients, MCI patients, and controls, in the hope that reduced suppression may help identify older persons at greatest risk for the development of PAD.
One could use N1 amplitude (or, for that matter, any component’s amplitude) as a “biomarker” for a given disease without knowledge of the underlying processes. However, it would arguably be more useful diagnostically if those processes were known. N1, like the earlier P50, is an “obligatory” component of the auditory ERP because it is elicited whether the stimuli are attended or ignored, although its magnitude can be affected by attention. (p. 517) According to Näätänen and Picton’s (1987) exhaustive review, there are potentially three sets of processes contributing to the “true N1 component” recorded at the scalp (i.e., those processes not reflecting aspects of the MMN and the Nd). Two of these are thought to reflect the activity of cerebral generators in and around primary and secondary auditory cortex. Hypotheses advanced by Näätänen and Picton (1987) suggest that one or both of these cortical generators could reflect the representation of sensory information and/or the formation of a sensory memory within the auditory cortex (see also Näätänen et al., 2005; Chapter 4, this volume). Based on the Fabiani et al. (2006) data detailed above, it does not appear that aging adversely affects the representation or formation of auditory sensory memories, but these mechanisms might be disrupted in aging individuals with PAD or in those with a diagnosis of MCI who progress to PAD. However, there are simply too few data to determine whether or not this is the case.
Relative to the P50 and the N1, age-related change in the P2 component has been less well studied, and only a handful of investigators have directly measured it. Czigler and colleagues (1992) used ISIs of 800, 2400, and 7200 ms in a passive oddball task. While P2 magnitude increased with ISI (as would be expected based on a refractory-period explanation, just as for the N1), this increment was much less dramatic for older adults. A similar finding was also reported in the Fabiani et al. (2006) study described earlier and is reminiscent of their N1 finding. Amenedo and Diaz (1999) reported larger P2 amplitudes in older compared to younger adults, again regardless of whether the standards were attended or unattended. Similar age-related enhancements have been described by Anderer et al. (1996), although one study found a larger P2 magnitude in young compared to older adults (Bertoli et al., 2002) and another (Iragui et al., 1993) reported no difference between young and older adults.
Early-latency components in the visual modality analogous to the P50 and N1 have also been reported to show age-related change. However, this literature is as mixed in its results as the data on age-related change in the auditory modality described above. For the sake of brevity, I refer the reader to a recent paper in which these studies are reviewed (De Sanctis et al., 2008). In this paper, De Sanctis and colleagues observed that the amplitude of the visual N1 (which was significantly larger in older adults) was much more variable in older than young adults. Whereas young adults showed a fairly tight distribution of amplitude values, older adults showed a bimodal distribution; 10 older adults with lower-amplitude N1s showed values similar to those of the young adults, whereas the remaining 9 produced the highest-magnitude N1s. This potentially important observation might explain some of the variability among studies in both the auditory and visual modalities.
To summarize, relative to the N1 and P2, the age-related enhancement of auditory P50 (P1) seems to be better established in the literature. The lack of suppression of the N1 observed by Fabiani et al. (2006) is intriguing and deserves follow-up. Both of these phenomena may be indicative of an age-related inhibitory deficit and could provide additional evidence for the frontal-lobe and inhibitory-control deficit hypotheses of cognitive aging (West, 1996). In addition, there is some, albeit limited, evidence that P50 enhancement may be a marker of risk status in some older adults who progress to PAD. Hence, this phenomenon may be worthy of pursuit in large samples of PAD patients, MCI patients, and age-matched controls.
A reasonably large age-related literature has accumulated on the automatic deviance detection system, as reflected by the MMN (Pekkonen, 2000). Figure 18.2 presents data recorded during the ignore paradigm described earlier (Gaeta et al., 2001a). In the figure, the ERPs to first-position standards and deviants from the 1 s ITI condition are depicted. In addition, grand-averaged preliminary data from five PAD patients are shown. Two basic age-related phenomena are reflected in these data: the MMN is somewhat smaller and of longer latency in healthy older and PAD participants compared to young adults, and PAD patients appear to produce MMN magnitudes and latencies similar to those of healthy controls. Despite the overall age-related difference in MMN amplitude, its scalp distribution appears similar in all three groups. The current source density (CSD) maps are consistent with bilateral generators in and around auditory cortex, which is thought to be a primary contributor to the MMN recorded at the scalp (Giard et al., 1990; Näätänen, 1992; Näätänen et al., 2007).
As described by Näätänen in this volume (Chapter 6) and elsewhere (Näätänen et al., 2007), the relatively automatic, preattentive, MMN-based deviance detection system is recruited in a wide variety of situations, including simple changes in (p. 518) pitch, intensity, duration, phonetic characteristics, and spatial location, as well as by more “abstract” changes in the acoustic background, such as whether two tones are rising or falling in pitch (Paavilainen et al., 1998). Moreover, on the basis of this latter finding, the MMN deviance detection system cannot reflect a simple sensory (echoic) memory of the acoustic past but rather appears to reflect a memory of the regularities or invariances in the acoustic stream (whether it is for pitch or the abstract nature of the regularity). Because of these properties, it has been natural for investigators to ask whether aging affects any aspects of the MMN deviance detection system.
In the early stages of research on the MMN’s characteristics, it was thought that it reflected a short-lived sensory memory (Sams et al., 1993). On this basis, several of the early studies of aging compared short (e.g., 200 ms) and long (e.g., 4000 ms) stimulus onset asynchronies (SOAs) to determine whether the memory on which the MMN was based had a shorter duration in older than young adults. However, as noted above, the MMN is not thought to reflect a simple sensory memory. There are also methodological limitations in assessing the effects of SOA even in young adults (see Ritter et al., 2002, for a discussion). Therefore, these investigations are equivocal with respect to age-related changes in the duration of the memory on which the MMN is based at short and long SOAs using the typical oddball paradigm (Gaeta et al., 2001a; Ritter et al., 1998; Winkler et al., 2002). Hence, the review below only considers the results of experiments in which auditory stimuli were ignored and a short SOA was used (between 0.5 and 2 s) even if a long SOA was also included. When considered in this fashion, although there are exceptions, there appears to be a consensus that the MMN is reduced in older adults. This suggests the possibility that sensitivity to regularities in the acoustic environment decreases as we age.
In one of the first of these investigations, Czigler et al. (1992) used infrequent changes in pitch. They found that older adults showed smaller-amplitude MMNs than young adults. Similarly, Cooper et al. (2006) reported smaller MMNs in older compared to young adults whether deviance was defined by pitch or duration. Furthermore, two reports suggested that when the MMN was recorded to duration deviants in an unattended channel (i.e., the ear of input) during selective attention paradigms, it was smaller in older compared to young adults (Karayanidis et al., 1995; Woods, 1992; see also Gaeta et al., 2001b, for frequency deviants; but see Pekkonen et al., 1996) even at very short ISIs between 200 and 400 ms. Gaeta et al. (1998) also reported smaller MMNs in older relative to young adults whether elicited by small-frequency (50 Hz difference from the standard) or large-frequency (300 Hz difference) deviants or novel environmental sounds. In fact, older adults did not show a reliable MMN to the small-frequency deviants. Alain and Woods (1999) assessed MMN magnitudes to (p. 519) both frequency changes (small [122 Hz] and large [414 Hz]) and pattern deviants (tones of two different pitches alternated and interrupted infrequently by a repeat). They observed reduced MMNs to small- and large-frequency as well as pattern deviants. In another study from this same group, Alain and colleagues (2004) assessed the sensitivity of older adults’ deviance detection system by varying systematically the gap between tone pips constituting a deviant event. Tones with gaps occurred infrequently, and continuous tones served as standards. The MMN amplitudes were smaller in older than young adults. Importantly, when MMNs were computed to near-threshold gap deviants, thereby matching the performance of young and older subjects, young but not older adults showed reliable MMNs. In a very similar paradigm, Bertoli et al. (2002) varied the gap duration of deviant stimuli between 6 and 24 ms. The MMNs were smaller in older compared to young participants. Moreover, similar to the results of Alain et al. (2004), it took a longer-duration gap (15 ms) to produce a reliable MMN in older compared to young (9 ms) adults.
The results of these investigations suggest that the preattentive deviance detection system of older adults is less sensitive than that of young adults. Employing rule-based auditory features to create invariances in the acoustic environment, the results of a study by Gaeta et al. (2002) support this hypothesis. Stimuli were either a frequent ascending tone pair or an infrequent descending tone pair. Tone pairs were presented under three conditions: (1) physical feature monaural (1 tone pair), (2) abstract feature monaural (10 tone pairs of different pitches), and (3) abstract feature binaural (10 tone pairs of different pitches; the first presented to the left ear and the second to the right). Relative to young adults, older adults showed smaller-magnitude MMNs, which were elicited under all three conditions for young adults but only in the monaural conditions for older adults. Thus, rule-based neural representations were created by both age groups under monaural conditions, but only by the young adults in the binaural condition. Reliable MMNs in the rule-based conditions were present despite the fact that behavioral discrimination (after the MMN recordings) fell to near chance levels for both age groups, suggesting an age-related decline in the efficacy of integrating multiple sources into a single auditory stream.
By contrast with the studies reviewed above, there are some reports of age-equivalent MMN amplitudes. For example, with pitch deviants and a 1 s ISI, Pekkonen and colleagues (1993) reported that MMN magnitude was similar in young and older adults, a finding also reported by Gunter and coworkers (1996) with a 1 s ISI. In a follow-up of their earlier study, Pekkonen et al. (1996) found age-equivalent MMN magnitudes to pitch deviants at .5 and 1.5 s ISIs. Using frequency deviants and a selective attention procedure similar to those mentioned earlier with 600 ms ISIs, Amenedo and Diaz (1998a) did not observe age-related differences in MMN magnitudes. However, these latter results are equivocal because there appeared to have been no effect of selective attention on the ERP waveforms, calling into question the sensitivity of the paradigm.
Using the design described above in the section on relatively early-latency components, Gaeta et al. (2001a; see Figure 18.2) showed that at a 1 s ITI, the vast majority of young and older subjects showed a robust MMN. However, at the 8 s ITI, only six young and five older adults showed robust MMNs. Although this might suggest that the memory on which the MMN was based had decayed at the 8 s ITI for both age groups, Gaeta et al. (2001a) argued that it was the nature of the perceptual grouping of the trains that was modulating the MMN magnitude. That is, when the SOA is constant between the standards within a train and the interval between standards and deviants is short (1 s ITI), all tones are treated as belonging to the same perceptual group. Therefore, a deviant is detected as a departure from invariance, resulting in a robust MMN. When the SOA between standards within a train is short and the interval between standards and deviants is long (8 s ITI), the perceptual group that comprises the invariance is the train of standards and the deviant lies outside the frame of temporal relevance for some subjects. Hence, presentation of a deviant is not perceived by the MMN system as a divergence from regularity and an MMN is not elicited for these subjects. A similar interpretation is possible to account for the data of Fabiani et al. (2006), who also reported age-invariant MMNs using a highly similar design with 1 and 5 s ITIs. Hence, although the findings of these two studies are ostensibly at odds with much of the data reviewed above, it is likely that the age-equivalent MMNs in these studies is peculiar to the types of stimuli used (trains rather than single events) and reflect the maintenance with age of perceptual grouping of acoustic stimuli.
With respect to abnormal aging, very few investigations exist. In the earliest of these, Pekkonen et al. (1994) reported that the MMN was of similar (p. 520) amplitude in PAD patients and controls at a 1 s ISI. This was confirmed in a subsequent study by the same group using the magnetoencephalographic analog of the electrical MMN (Pekkonen et al., 2001). Similarly, Gaeta and colleagues (1999) observed that MMN magnitudes were similar in PAD patients and age-matched controls.
In summary, it seems fairly clear that the system upon which the MMN relies is relatively less sensitive in older compared to young adults and, based on very limited evidence, is similar in PAD patients and controls, at least in the fairly simple paradigms used to date. What is less clear is whether there is an age- and/or PAD-related reduction in the duration of the memory upon which the MMN is based. This will certainly require further work.
The Novelty P3 (P3a)
Although the MMN reflects the detection of a change in the invariance of the acoustic environment, it does not reflect the capture of attention by that change. The involuntary capture of attention is reflected by the novelty P3 or P3a, which is elicited if the change in the background is sufficiently deviant (Friedman et al., 2001; see also Chapter 7, this volume). The novelty P3, therefore, reflects an aspect of the orienting response, a fundamental biological mechanism necessary for survival (Sokolov, 1990).
An example of the dissociation between the MMN and the novelty P3 is depicted in Figure 18.3, which illustrates the averaged ERPs elicited by standards and small (50 Hz) and large (i.e., novel environmental sound) deviants recorded while young and older adults watched a silent movie and ignored the background auditory events (Gaeta et al., 1998). While a MMN was elicited by both small and large deviants in young as well as older adults (although the MMN was not reliable in the latter), only the environmental-sound deviants elicited the novelty P3. Note also that the novelty P3 was reduced in older compared to young adults, an age-related phenomenon that has been replicated most often with auditory stimuli but has also been observed in the visual and somatosensory modalities (Czigler et al., 2006; Fabiani & Friedman, 1995; Friedman & Simpson, 1994; Friedman et al., 1993b, 1998; Gaeta et al., 1998, 2001b; Knight, 1987; Weisz & Czigler, 2006; Yamaguchi & Knight, 1991a; but see Daffner et al., 2006b).
Although the majority of studies have employed active oddball designs, in which the participant is asked to respond to targets via RT and withhold responding to standards (and novel stimuli), it is perhaps more ecologically valid to assess the ERP concomitants of the orienting response while participants ignore the background events. Using this method, one can obtain a truer assessment of how and to what extent deviant events involuntarily capture attention, because the participant is engaged in the primary task of reading, watching a silent movie, or performing a visual discrimination (Alain & (p. 521) Woods, 1999; Friedman et al., 1998; Gaeta et al., 1998; Yago et al., 2003; see Figure 18.3).
Like older adults in the Gaeta et al. (1998) study, PAD patients showed a novelty P3 only in response to the environmental-sound deviants that did not differ in amplitude from that of age-matched controls (Gaeta et al., 1999). A similar finding was reported by Yamaguchi et al. (2000), also in the auditory modality, although with an active paradigm. The results of these latter two studies contrast with those from an investigation by Daffner et al. (2001) using visual stimuli. They reported that the novelty P3a was reliably smaller in PAD patients than in age-matched controls. The methods used by Daffner et al. (2001) are quite different than those typically employed to assess either age- or dementia-related changes in the processing reflected by the novelty P3. For example, these investigators collect looking times (i.e., how long a participant spends viewing a given standard, target, or novel visual event), as well as RTs to predesignated targets. Participants are allowed to view the stimuli for as long as they deem necessary. Although an intriguing method for assessing the extent to which novel events are processed, this technique may change the oddball task significantly, such that brain systems other than those reflecting the involuntary capture of attention (novelty P3) may be recruited. It may be one or more of those very systems, such as controlled attention (effortful processing resources), that are dysfunctional in PAD (Parasuraman & Haxby, 1993), leading to the reduction in the P3 elicited by the novel objects.
A critical aspect of the orienting response is its habituation over time (Lynn, 1966). Accordingly, several investigators have shown that, like other ubiquitous markers of the orienting response such as the galvanic skin response, novelty P3 amplitude diminishes in young adults as more and more novel events are experienced or the same novel event is repeated (Czigler et al., 2006; Friedman & Simpson, 1994; Kazmerski & Friedman, 1995; Knight, 1984, 1996; Yamaguchi & Knight, 1991b; see the reviews by Friedman et al., 2001, and Ranganath & Rainer, 2003). By contrast, in older adults, the novelty P3 has been shown not to habituate (Czigler et al., 2006; Fabiani & Friedman, 1995; Friedman & Simpson, 1994; Kazmerski & Friedman, 1995; Weisz & Czigler, 2006), whether those events are attended or ignored (Friedman et al., 1998). Because the scalp-recorded novelty P3 receives contributions from prefrontal cortex (Daffner et al., 2000; Halgren et al., 1998a; Knight, 1984) and because patients with prefrontal damage do not show habituation to these types of stimuli (Knight, 1984; Woods & Knight, 1986), this type of finding has been interpreted by some to indicate support for the frontal-lobe deficit hypothesis of cognitive aging (Friedman et al., 1998; see also Buckner, 2004, and West, 1996; but see Greenwood, 2000, 2007).
This hypothesis has also been motivated by the well-replicated finding that older, relative to young, adults show more frontally oriented scalp distributions to both oddball targets and deviant, novel events (Fabiani & Friedman, 1995; Fjell & Walhovd, 2003; Friedman & Simpson, 1994; Friedman et al., 1993b; Kutas et al., 1994; Pfefferbaum et al., 1984a; Yamaguchi & Knight, 1991a; see Figure 18.4), suggesting that older adults may call on frontal lobe resources to a greater extent than young adults even for events that should have been well encoded and categorized. However, recent evidence suggests that some older adults may call on these resources to a greater extent than others (Daffner et al., 2006a; Fabiani et al., 1998; Riis et al., 2008). An open question is whether the change in scalp distribution (and, presumably, the underlying generators) reflects a compensatory mechanism in high-functioning older adults whose brains might have the capacity to produce this change. That is, relative to young adults, the topographic change in older adults ought to be associated with equivalent or near-equivalent performance that, without such compensatory activity, would have been lower. On the other hand, the change could represent an attempt on the part of low-functioning older adults performing poorly on the task to compensate for the deleterious effects of brain aging (Raz, 2000). Adjudicating between these alternatives is difficult and, in fact, examples of both interpretations have been advanced. For example, Fabiani and colleagues (1998) divided their older participants into good and poor frontal-lobe test performers. The poor performers showed target P3 scalp distributions that had frontal maxima (the more typical finding when averages are computed across all participants’ data within the older age group), whereas the good performers showed parietal-maximal scalp topographies. In this case, the data suggested that the frontal scalp topography reflected less efficient processing. On the other hand, in a series of investigations, Daffner and coworkers, using the visual oddball paradigm described earlier, came to the opposite conclusion (Daffner et al., 2005, 2006a, 2006b; Riis et al., 2008): that more frontal P3 activity indicates greater compensatory recruitment of frontal resources and reflects (p. 522) successful cognitive aging. Notwithstanding the differences in design and stimulus materials between the Daffner experiments and those predominating in the literature (for discussion, see Fjell & Walhovd, 2005, and Daffner et al., 2005), the compensation hypothesis is currently highly controversial (Colcombe et al., 2005; Friedman, 2003; Greenwood, 2007; Zarahn et al., 2007). Determining whether a pattern of brain activity is compensatory, inefficient, detrimental, or unrelated to performance will require more precise definitions of what is meant by compensation (see Davis et al., 2007, and Stern, 2002, for examples), and under which conditions such compensation might or might not be expected.
To summarize, with the exception of the studies by Daffner and colleagues, the majority of investigations of age-related change in the novelty P3 have shown it to be reduced and its topography to be more frontally oriented in older compared to young adults. Consistent with these findings, some data suggest that only highly deviant events are likely to capture the older adult’s attention. Moreover, unlike young adults, who show a reduction in amplitude after the first few presentations of unexpected novel events, older adults do not, suggesting that they repeatedly recruit prefrontal cortical mechanisms for stimulus events that should no longer involuntarily capture attention. Finally, the extent to which compensatory mechanisms are responsible for the recruitment of frontal resources in response to novel events by some older adults is currently equivocal and requires further experimentation and documentation.
N2b and P3b
By contrast with the MMN, which appears to reflect a relatively automatic, preattentive mechanism, the N2b (at approximately 200–300 ms poststimulus), like the P3b, is typically observed only when participants are focusing attention on the sequence of events in order to make a task-relevant decision (Ritter et al., 1979; Chapter 11, this volume). The N2b is also elicited in the passive oddball paradigm when highly deviant stimuli, such as environmental sounds, involuntarily capture attention (Kazmerski et al., 1997). The P3b component is arguably the best-studied of the ERP components. It is, therefore, not surprising that much more research effort has been expended in assessing age-related changes in its amplitude, latency, and scalp topography compared to the N2b.
To illustrate some of the effects of aging on the N2b and P3b components, Figure 18.4 depicts the grand mean ERPs elicited by targets and, for comparison, novel environmental sounds in young (N = 10) and older (N = 10) adults recorded during a version of the novelty oddball task (Friedman, unpublished data). The scalp distribution maps to the right of the waveforms depict, as noted earlier, (p. 523) one of the most consistent findings in the ERP/aging literature: relative to young adults, older adults’ novel (P3a) and target (P3b) topographies are more frontally oriented. Another ubiquitous finding evident in the figure is the age-related prolongation of the latency of both novel and target P3 components (e.g., Brown et al., 1983; Fjell & Walhovd, 2003; Iragui et al., 1993; Picton et al., 1984). The most comprehensive assessment to date of age-related effects on P3b latency has been published by Polich (1996), and the reader is referred to that publication for more details. A third well-replicated finding observable in Figure 18.4 is the smaller-amplitude P3b component in older compared to young adults. This phenomenon has been reported in a wide variety of tasks in addition to the oddball paradigm (e.g., Ford et al., 1997; Friedman et al., 1997, 2007b; Gaeta et al., 2003; Iragui et al., 1993; McEvoy et al., 2001).
The N2b also shows age-related variation. For example, its latency increases with age in highly similar fashion to that demonstrated for the P3b (Anderer et al., 1996; Enoki et al., 1993; Goodin et al., 1978a; Iragui et al., 1993). This can be seen in Figure 18.4, where, relative to young adults, a prominent though prolonged-latency N2b component is evident in the target ERPs of the older adults. By contrast with latency, one of the difficulties in assessing the consistency of age-related change in N2b magnitude is that, although it is typically recorded in a wide range of paradigms, it has often not been measured directly. Nonetheless, when N2b amplitude has been calculated, there is a somewhat greater number of studies whose results show larger N2b magnitudes in older compared to young adults (Anderer et al., 1996; Czigler et al., 2006; Friedman et al., 1993b; Gaeta et al., 2003; Woods, 1992) than indicate the converse (Bertoli et al., 2005; Czigler & Balazs, 2005; Karayanidis et al., 1995).
With respect to pathological aging, the results are quite mixed. Although, as might be expected, PAD patients sometimes show prolonged-latency P3b components relative to age-matched controls (e.g., Bennys et al., 2007; Golob & Starr, 2000; O’Donnell et al., 1990; Patterson et al., 1988; Williams et al., 1991), other research groups have reported a failure to distinguish PAD participants from controls on the basis of this metric (Gordon et al., 1986; Kazmerski & Friedman, 1998; Kraiuhin et al., 1990; Pfefferbaum et al., 1984b). Whether the P3b latency prolongation has sufficient sensitivity and specificity for clinical diagnosis is, therefore, open to question (Gordon et al., 1986; Patterson et al., 1988). Similarly, P3b amplitudes are sometimes (Frodl et al., 2002; Goodin et al., 1978b; Saito et al., 2001), but not always (Golob & Starr, 2000; Kazmerski & Friedman, 1998) reported to be smaller in PAD patients compared to controls. Moreover, the scalp distribution of P3b does not appear to differ between PAD patients and controls, at least in the auditory modality (Ford et al., 1997; Kazmerski & Friedman, 1998). Hence, as for P3b latency, the utility of amplitude and topography for clinical diagnosis is equivocal. This conclusion is further supported by the results of a recent study by Golob et al. (2007), who reported that neither P3b latency prolongation nor amplitude reduction was able to predict which MCI patients converted to PAD (see Taylor & Olichney, 2007, for a review of ERPs in dementia).
In sum, the evidence to date is fairly conclusive that the mental operations indexed by N2b and P3b increase in latency as individuals age, consistent with the phenomenon of general slowing reported in the behavioral literature (Salthouse, 1991). Whether P3b latency slowing is exacerbated in pathological aging is not yet certain. The tenuousness of this finding in PAD may be due to the fairly simple oddball paradigms that have most often been used to assess P3b latency. N2b is thought to be the first brain event indicating that a conscious sensory discrimination has been made (Ritter et al., 1979). P3b, therefore, must reflect a subsequent stage of processing, although a consensus on its functional significance has yet to be reached (see below).
One of the major theoretical positions advanced to account for age-related changes in cognition postulates that even relatively early stages of processing are slowed (Salthouse, 1996). If this hypothesis is valid, then the early latency ERP components (e.g., P50, N100) should be of longer latency in older adults compared to young adult controls. The prolongation of these relatively early-latency components could engender a cascade of slowing that might be manifested in the age-related RT retardation that has been ubiquitously observed in a wide variety of cognitive paradigms (Salthouse, 1996) and prolonged P3b latencies, one of the most often replicated findings in the ERP aging literature (Polich, 1996). However, there is very little evidence for retardation in the early-latency components (Anderer et al., 1996; Goodin et al., 1978a; Iragui et al., 1993). By contrast, the ERP data suggest that the slowing is restricted to the later stages of information processing, as indexed by N2b and P3b. Hence, because of this fact, the retardation in N2b and P3b latencies in older adults cannot be due (p. 524) simply to information loss from slowed operations at earlier stages in the processing stream.
Like P3 latency, the evidence for an age-related reduction in P3b amplitude is compelling. By contrast, the evidence for further reduction by PAD and MCI is equivocal. However, the implications of the age-related reduction in P3b amplitude for understanding the underpinnings of cognitive aging phenomena are not clear at this time. Complicating the picture further is the age-related change in P3b scalp topography. This is somewhat problematic for interpretation of the age-related significance of the changes in cognition that underlie the P3b recorded at the scalp because it is well known that it receives contributions from a widespread intracranial network (Halgren et al., 1998b), any aspect of which could be altered with aging. Hence, these alterations could be functionally driven, reflecting, for example, an age-related change in the source regions that contribute to the P3b or, less interestingly, to age-related structural changes within the brain. For example, age-related shrinkage in brain volume, which is well documented (Raz et al., 2004), might alter the orientation of the brain generators, thereby modifying older adults’ P3b scalp topography even though the processes reflected by the P3b do not change with age. However, for this account to be viable, the topographic change would most likely have to be highly similar across tasks (e.g., oddball, Sternberg short-term memory, repetition priming). Although this proposition has, to my knowledge, not been tested directly, there is some evidence that, although older adults typically produce more frontally oriented P3b distributions in a variety of cognitive paradigms, those topographies can be modified by task demands (Friedman et al., 1997). Then again, the Friedman et al. (1997) topographic comparisons were made between independent samples of subjects who had participated in similar, though not identical, experiments. Thus, the evidence from the Friedman et al. investigation is limited and needs to be bolstered by within-subject, task-related comparisons of P3b topography in older adults.
One influential theory of the functional significance of the P3b posits that it reflects updating when the subject’s model of the environment requires revision (Donchin & Coles, 1988), a key aspect of working memory (Baddeley, 1992). Furthermore, a major hypothesis used to account for cognitive decline in aging is that working memory, which has been conceptualized as the amount of resources available to process information online, is reduced (Craik & Byrd, 1982; Park, 2000a). Therefore, it could be the case that older adults call upon this type of general-purpose, working memory/attentional resource much more often than young adults, thereby accounting for the ubiquity and prominence of the frontal aspect of the P3b distribution in a wide variety of tasks (Fabiani & Friedman, 1995; Ford et al., 1997; Friedman et al., 2007b; see Friedman et al., 1997, for discussion). However, as for the novelty P3, whether this topographic change reflects a compensatory modification of brain activity to counteract the deleterious effects of brain aging is unknown at this time and clearly requires further research effort (Friedman, 2003, 2007).
The presentation of a phrase or sentence-ending pictorial or verbal concept that is incongruent with the meaning of the preceding material produces a large-amplitude N400 effect in young adults (Kutas & Hillyard, 1980; Chapter 15, this volume). This incongruity effect, defined by subtracting the ERP to incongruous endings from that to congruous endings, has been assessed in a number of age-related investigations (see the reviews by Federmeier, 2007; King & Kutas, 1995; Kok, 2000). Generally, the N400 effect shows an amplitude reduction and a latency prolongation with increasing age (Cameli & Phillips, 2000; Gunter et al., 1992, 1996; Hamberger & Friedman, 1992; Hamberger et al., 1995; Harbin et al., 1984; Iragui et al., 1996; Kutas & Iragui, 1998; Phillips & Lesperance, 2003), with latency retardation similar to those observed for the N2b and P3b. Like the P3b latency findings, age-related retardation in N400 latency does not appear to be accounted for by delays in earlier, primary visual components (Gunter et al., 1992; Kutas & Iragui, 1998). The age-related N400 reduction appears to be generalizable across a variety of conditions, including, but not limited to, category and repetition priming (Hamberger & Friedman, 1992; Harbin et al., 1984; Kutas & Iragui, 1998), antonymic contexts (Kutas & Iragui, 1998), and visual as well as auditory sentence contexts (Cameli & Phillips, 2000; Federmeier et al., 2003; Hamberger et al., 1995; Woodward et al., 1993). Interestingly, when sentences were presented in the more natural context of connected speech, the age-related prolongation in N400 latency reported for visually presented completions was not observed (Federmeier et al., 2003).
Because semantic-memory impairments are often observed in Alzheimer’s disease (Nebes, 1989), the semantic incongruity effect has also been studied in (p. 525) patients with a diagnosis of PAD. Although there are exceptions (Ford et al., 2001; Hamberger et al., 1995), the results suggest that, by and large, the N400 effect produced by PAD patients is reduced and its latency is prolonged compared to age-matched controls (Ford et al., 1996; Iragui et al., 1996; Ostrosky-Solis et al., 1998; Revonsuo et al., 1998; Schwartz et al., 1996; see the review by Taylor & Olichney, 2007). Moreover, some very limited evidence suggests that the reduction in the N400 effect may predict conversion from MCI to PAD (Olichney et al., 2002).
As reviewed briefly above, the majority of evidence indicates that the magnitude of the N400 effect is reduced in older adults and further reduced in PAD. In addition, N400 latency shows a similar age- and disease-related pattern. Nonetheless, as in young adults, the N400 in older adults, and to some extent in PAD patients, is inversely related to the degree to which a given context “primes” the eliciting word (or picture). Hence, the data could be interpreted to indicate that the semantic memory network is intact in older adults, consistent with a large behavioral literature suggesting that semantic knowledge is maintained and/or increases with age (Park et al., 2002; Salthouse, 1993). Therefore, N400 latency prolongation might be a consequence of an age-related increment in the size of the semantic network—it takes longer to search a larger network. The amplitude reductions in the N400 effect may also have a similar cause: in older relative to young adults, the preceding context could have primed a wider range of words related to the best completion. Alternatively, the possibility exists that older adults activate a wider range of terminal words due to age-related alteration in inhibitory processing (Phillips & Lesperance, 2003), consistent with the inhibitory-deficit hypothesis of cognitive aging (Hasher & Zacks, 1988). Age-related limitation in working memory/processing resources might also account for these data, since when these resources are taxed, older adults show subtle differences in the N400 effect (Federmeier, 2007; Federmeier et al., 2003).
Episodic Memory Components
Mnemonic function has proven to be an important aspect of research on cognitive aging due to the well-documented age-related deficits in episodic memory (EM; Light, 1991). Several ERP investigations of recognition memory aging are available (Friedman et al., 2007a). The ERP episodic-recognition memory effects are computed by subtracting the ERP to unstudied (i.e., new) items from those studied previously (i.e., old), yielding the old/new or EM effect (Friedman & Johnson, 2000; Rugg & Curran, 2007; Chapter 14, this volume). In studies of young adults, two of these EM effects, the medial-prefrontal and left-parietal, have been consistently recorded in the retrieval phases of recognition-memory paradigms. They have been associated with, respectively, familiarity- and recollection-based processes (Friedman & Johnson, 2000; Rugg & Curran, 2007; Rugg & Yonelinas, 2003), which have been hypothesized by dual-process theorists to underlie recognition-memory performance (Mandler, 1980; Yonelinas, 2002). However, the extent to which the medial-prefrontal effect reflects episodic, familiarity-driven processes as opposed to semantically driven conceptual processing is currently the subject of much debate (Paller et al., 2007). Figure 18.5 depicts these two EM effects in the grand-averaged ERP waveforms elicited by correctly rejected new and correctly recognized old items in young and older adults from a study by Nessler et al. (2007a). As can be observed, these EM effects overlap large-amplitude potentials such as the N400 and P3b. Nonetheless, they have been shown to be relatively independent of these components on the basis of differences in scalp topography (see Johnson, 1993, for a rationale and overview; see Friedman, 2000, for an application to aging). Note that the medial-prefrontal EM effect is of similar magnitude in young and older adults, whereas the left-parietal EM effect is reduced in older relative to young adults. In age-related studies that have measured directly the medial-prefrontal EM effect (Nessler et al., 2007a, 2008; Trott et al., 1999; Wegesin et al., 2002), its amplitude has been found to be age equivalent. By contrast, in some investigations, the left-parietal EM effect has been reported to be smaller in older relative to young adults (Friedman et al., 1993a; Nessler et al., 2007a, 2008; Rugg et al., 1997; Swick & Knight, 1997), primarily when participants are asked to make simple old/new recognition judgments. Under these relatively simple old/new retrieval conditions, older adults often do not show impaired recognition memory or their performance does not differ markedly from that of young adults (Craik & McDowd, 1987). Then again, when source- or contextual-memory judgments are required, age equivalence of the left-parietal EM effect has been observed (Mark & Rugg, 1998; Trott et al., 1999; Wegesin et al., 2002), despite the fact that older adults typically perform worse than young adults under these more taxing retrieval circumstances (Spencer & (p. 526) Raz, 1995). The findings for the medial-prefrontal EM effect have generally been interpreted as reflecting maintained familiarity-based processes in aging, consistent with current theories of memory aging (Yonelinas, 2002). The paradoxical finding of smaller left-parietal EM effects in the face of relatively preserved performance during old/new recognition memory might then indicate that, in these retrieval situations, older adults rely primarily on familiarity to make their recognition decisions (Nessler et al., 2008). This may be due to the possibility that older adults retrieve a smaller amount of contextual detail because their memory representations are qualitatively diminished as a result of inefficient encoding (Nessler, Johnson, Bersick, & Friedman, 2006) However, when necessary, as in source-memory paradigms, older adults can use recollection-based processes to support their retrieval performance, albeit to a lesser extent than their young adult counterparts. Hence, these data as a whole suggest a default retrieval strategy in which familiarity is the primary basis for recognition decisions in older individuals, perhaps due to the more effortful, resource-demanding nature of recollective processing (Jennings & Jacoby, 1997).
In some memory retrieval conditions, a few studies have reported the presence of electrical activity in older adult waveforms that could be interpreted as compensatory. For example, a left-frontal negative activity (∼400–1000 ms poststimulus) has been reported only in older adult ERPs during the retrieval phases of recognition-memory investigations (Czernochowski et al., 2007; Li et al., 2004; Swick et al., 2006). Because this negativity has been observed most often during source-memory paradigms (but see Nessler et al., 2007a, for left-frontal negativity in a standard old/new recognition task), some authors have suggested that the negativity reflects alternate retrieval strategies necessitated, in older adults, by the greater demands on control processes required to retrieve contextual information from stored memory traces (Czernochowski et al., 2007; Li et al., 2004; Swick et al., 2006; Wegesin et al., 2002). However, in direct opposition to this argument, Duarte and colleagues (2006) reported what appears to be a similar negativity in a source-memory paradigm in the ERPs of low-performing older adults, but not in those of high-performing older or young adults. Hence, in the current state of knowledge, the functional significance of this activity is unclear.
To sum up briefly, to the extent that the medial-prefrontal and left-parietal EM effects reflect, respectively, familiarity- and recollection-based processes (see Rugg & Curran, 2007, and Paller et al., 2007, for extended discussions), the data indicate that both are relatively intact in older adults. Nonetheless, the predominant retrieval mode in older adults appears to be one based on familiarity. Whether, on the basis of ERP studies, older adults compensate to overcome these episodic recognition deficits is an open question; the data are simply too sparse to permit a definitive conclusion. Categorization of older (and young) adults as low and high performers on a variable of theoretical importance might aid in that endeavor, and investigators should consider this in future studies (Czernochowski et al., 2007; Duarte et al., 2006).
Error-Related and Medial Frontal Negativities
The error-related negativity (ERN; Falkenstein et al., 2001) occurs on trials in which an error has been made (see Chapter 10, this volume), whereas the medial-frontal negativity or (MFN; Gehring & (p. 527) Willoughby., 2002; Nessler et al., 2007b) occurs on trials in which a correct response has been made. These two ERP modulations are best observed in response as compared to the typical stimulus-locked average (Figure 18.6). Both are thought to reflect cognitive-control functions (Botvinick et al., 2001, 2004; Ridderinkhof et al., 2004), although there is reasonably good evidence to indicate that they signal at least partially nonoverlapping behavioral processes with neural generators located in different regions of the anterior cingulate cortex (ACC; Friedman et al., 2007b; Johnson et al., 2004; Masaki et al., 2007; Nessler et al., 2007). The ACC monitors for and detects response conflict and plays a critical role in goal-directed action by signaling other prefrontal regions to adjust behavior in the presence of competing-response information (Botvinick et al., 2001).
As shown in Figure 18.6, the ERN has consistently been found to be smaller in older relative to young adults (Band & Kok, 2000; Falkenstein et al., 2001; Gehring & Knight, 2000; Mathalon et al., 2003; Nessler et al., 2007b; Themanson et al., 2006; West, 2004; but see Eppinger et al., 2008). Figure 18.6 depicts the response-locked ERPs recorded during a modified version of the Eriksen flanker task (Friedman et al., 2009). Note that, whereas the ERN on error relative to correct trials is larger in young relative to older adults, the MFN on high-response-conflict (see the Figure 18.6 caption), incompatible-response trials relative to lower-conflict, compatible-response trials is larger in older than young adults, suggesting an age-related dissociation in the processes reflected by the ERN and MFN (see also Nessler et al., 2007b). Studies showing that the amplitude of the MFN increases with the degree of conflicting response information suggest that the MFN is an indicator of the amount of response conflict detected (Botvinick et al., 2004; Hogan et al., 2005; Johnson et al., 2004; Kray et al., 2005; Nessler et al., 2007b; West, 2004). Although the ERN has also been interpreted as reflecting some aspects of conflict monitoring (e.g., an error is in conflict with the appropriate response), it likely reflects additional error-specific processes that appear to undergo age-related change (Nieuwenhuis et al., 2002; Taylor et al., 2007).
Unlike the ERN, there is a paucity of age-related studies of response conflict monitoring and detection as reflected by the MFN. In three investigations from this laboratory, including response-competition (Nessler et al., 2007), task switching (Friedman (p. 528) et al., 2007b), and Eriksen flanker paradigms (Friedman et al., 2009), MFN magnitude was similar in young and older adults at low to medium levels of cognitive demand (but see Kray et al., 2005). At high levels of cognitive demand (such as in incompatible-response trials following an error), older adults produced larger MFNs than younger adults (Nessler et al., 2007b), indicating that they detected a greater amount of response conflict than young adults. One reason for the greater MFN magnitudes in older adults under high-demand conditions might have been that attempts to resolve the heightened response conflict by upregulating cognitive control were relatively unsuccessful, thereby resulting in high residual levels of response conflict. This is attested to by the fact that in these high-demand situations, older adults performed more poorly than young adults.
In summary, although the ERN and MFN have the potential to shed light on different aspects of cognitive control in older adults, the scarcity of age-related data in which the two have been compared hinders interpretation at this time. Nonetheless, based on the extant ERN data, there do appear to be age-related changes in error-monitoring processes, although a recent study strongly questions this conclusion (Eppinger et al., 2008). The age-related MFN literature is scant, and more studies are called for. The limited data suggest that the processes involved in response-conflict monitoring and detection are relatively intact. Hence, the older adult difficulty is more likely attributable to a deficit in some aspects of top-down, executive-control processing (Friedman et al., 2009; Nessler et al., 2007b).
Overall Conclusions and Directions for Future Work
Several unifying theories have been proposed to account for the wide variety of cognitive aging phenomena that have been described in the literature (Craik & Salthouse, 2007; Park, 2000b). These include deficits in working memory/processing resources (Craik & Byrd, 1982), general slowing (Salthouse, 1996), deficits in inhibitory control (Hasher & Zacks, 1988), and losses in sensory acuity (Baltes & Lindenberger, 1997). Unfortunately, the study of ERP components has not always been directed explicitly at providing support for or against these theoretical positions. Nonetheless, some of the ERP findings presented above have the potential, at least preliminarily, to contribute evidence to these hypotheses. For example, the fairly consistent finding that P3b amplitude is reduced in a wide variety of paradigms in older adults suggests that age-related cognitive deficits may be due to reduced processing resources and/or alterations in working memory (Donchin & Coles, 1988; Kramer et al., 1986; but see Polich, 2007). On the other hand, age-related changes in primary components such as the P50 and N1 do not appear likely, at least currently, to account for a large percentage of the variance in cognitive change with aging. Age-related alterations in these early-latency components may fit better with the inhibitory-rather than the sensory-deficit theory of cognitive aging, but much more work is required before this will be known with any certainty. Nonetheless, the interaction between age-related sensory processing deficits and downstream cognitive processes, which receives support in the behavioral literature (Wingfield et al., 2005), has rarely been considered in ERP/aging research. This might prove to be a fruitful research area. The processing speed theory of cognitive aging does not receive much support from the extant data because age-related delays in early-latency components (such as P50 and N1) have not been reported or, if they have, those delays are much too small to account for the long delays in the latencies of the N2b, P3a, and P3b components.
Despite these hints at putative mechanisms, there are difficulties that need to be overcome before a clearer picture of the underlying causes of cognitive change with aging using ERP data can be painted. The greater variability observed in older adult data needs to be exploited, as some individuals fare better than others as they age, and ERP components may aid in understanding why. Although attempts in this direction have been made (Czernochowski et al., 2007; Duarte et al., 2006; Fabiani et al., 1998; Riis et al., 2008), more work is certainly necessary. The omnipresence of the frontal-maximum scalp distribution of the P3a and P3b in older adults presents some difficulty for interpretation of the age-related functional significance of these components. Future studies need to attempt to manipulate this topographic feature via experimental design to determine whether it can be modified and, if so, by which variables. Moreover, this feature of older adults’ scalp distribution may aid in understanding individual differences in cognitive aging and what they imply about preserved and impaired cognition (Fabiani et al., 1998; Riis et al., 2008). Similarly, tantalizing hints at difficulties in inhibitory control based on relatively early-latency components such as the P50 and N1 need to be followed up, employing an individual differences approach. For example, (p. 529) because a decrease in inhibitory control has been hypothesized to underlie the age-related enhancement of the P50 and N1 components (Alain & Woods, 1999; Fabiani et al., 2006; Chao & Knight, 1997), perhaps older adults with enhanced amplitudes are those who also show deficits in other, higher-order cognitive tasks that require executive processes, such as inhibitory control, for good task performance (e.g., selective attention, task switching, flanker paradigms). More research effort directed at the validity of the compensation hypothesis, which is based almost exclusively on functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) data, is necessary (Cabeza et al., 2002). Because of its high temporal precision, the ERP technique may contribute information not available from fMRI or PET.
Moreover, a great deal of age-related ERP data has been obtained using some variant of the oddball paradigm. It is difficult to assess the validity of the major cognitive-aging hypotheses using this task because levels of cognitive complexity are generally not built into the oddball design. Therefore, it assesses cognition only in a very general fashion. Hence, ERP paradigms that assess directly such constructs as attentional resources, inhibitory control, and working and episodic memory, separately as well as in combination, are required. For instance, ERP investigations of age-related change in episodic memory have not usually incorporated assessments of executive control, although deficits in cognitive control are clearly present as we age and may be a cause of episodic memory failure (Braver & West, 2007; Friedman, 2007). Hence, investigators should take greater advantage of the ERN and MFN in studies of episodic memory (Curran et al., 2007), as well as in other domains such as attentional and inhibitory control. Further research using the full armamentarium of ERP components in the variety of domains reviewed above will certainly provide a better understanding of the mechanisms underlying the preservation and disruption of neurocognitive functions as individuals age.
The research reported in this chapter was supported by NIA Grants AG005213 and AG009988 and by the New York State Department of Mental Hygiene. I thank my colleagues Drs. Helen Gaeta, Ray Johnson, Jr., Doreen Nessler, and Walter Ritter for many fruitful discussions concerning the data reported here. I also thank Mr. Charles Brown, Jr., for technical assistance and software development.
Address correspondence and reprint requests to: David Friedman, Ph.D., Cognitive Electrophysiology Laboratory, New York State Psychiatric Institute, 1051 Riverside Drive, Unit 6, New York City, NY 10032, USA. Phone: 212–543-5476; Fax: 212–543-6002; E-mail: mailto:email@example.com.
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