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Journal of Alzheimer’s Disease 44 (2015) 397–408 DOI 10.3233/JAD-140930 IOS Press

Early Visual Evoked Potentials and Mismatch Negativity in Alzheimer’s Disease and Mild Cognitive Impairment George Stotharta,∗ , Nina Kazaninaa , Risto N¨aa¨ t¨anenb,c,d , Judy Haworthe and Andrea Talesf a School

of Experimental Psychology, University of Bristol, Bristol, UK of Psychology, University of Tartu, Estonia c Center of Functionally Integrative Neuroscience, University of Arhus, ˚ Denmark d Institute of Behavioural Sciences, University of Helsinki, Finland e South Gloucestershire Memory Service, Avon and Wiltshire Mental Health Partnership, Bristol, UK f Department of Psychology, Swansea University, Singleton Park, Swansea, Wales, UK b Department

Handling Associate Editor: Charles Duffy

Accepted 2 September 2014

Abstract. Background: Cortical visual association areas are highly vulnerable to Alzheimer’s disease (AD) microscopic pathology. Visual evoked potentials (VEPs) provide the tools to examine the functional integrity of these areas and may provide useful indicators of early disease progression. Objective: To assess the functional integrity of visual association area processing in AD and amnestic mild cognitive impairment (aMCI) using VEPs. Methods: We investigated the visual processing of healthy older adults (n = 26), AD (n = 20), and aMCI (n = 25) patients in a visual oddball paradigm designed to elicit the visual P1, N1, and visual mismatch negativity (vMMN). Results: AD patients showed a significant reduction of P1 and N1 VEP amplitudes and aMCI patients showed a reduction in N1 amplitude compared to healthy older adults. P1 amplitude in response to deviant stimuli and vMMN amplitude were found to be associated with the degree of cognitive impairment as measured by the Mini-Mental State Examination. Conclusions: Changes in VEPs in AD may be a consequence of the microscopic AD pathology typically found in the extrastriate cortex. Neural measures of visual processing may help to better characterize subgroups of aMCI patients likely to develop AD. Additionally, VEPs and vMMN may provide objective markers of cognitive decline. Keywords: Alzheimer’s disease, electroencephalography, mild cognitive impairment, mismatch negativity, visual evoked potentials

INTRODUCTION Alzheimer’s disease (AD) is a debilitating degenerative disease of increasing incidence and prevalence ∗ Correspondence to: George Stothart, School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK. Tel.: +44 117 331 7894; Fax: +44 117 928 8588; E-mail: [email protected].

[1, 2]. Improvement in early detection is imperative given the estimate that AD pathology may have been present for up to 20 years prior to diagnosis [3]. While episodic memory impairment is the primary symptom of AD, its measurement can lack the sensitivity required for early detection. A substantial body of evidence now exists in support of significant abnormality in a much wider range of information processing in

ISSN 1387-2877/15/$27.50 © 2015 – IOS Press and the authors. All rights reserved

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AD, particularly so with respect to the integrity of visual information processing [4, 5]. The primary visual processing area (striate cortex, Brodmann area 17) appears relatively unaffected by typical microscopic level AD pathology, i.e., the deposition of amyloid plaques and neurofibrillary tangles. However, the visual association areas (e.g., extrastriate cortex, Brodmann areas 18 and 19) show significant microscopic pathology with aggregations of amyloid plaques and neurofibrillary tangles of up to 20 times that observed in the primary visual areas [6–9]. McKee and colleagues [10] proposed that this is due to the high synaptic complexity of the association cortices, compared to the primary sensory cortices, which may amplify the impact of disease pathology. The occurrence of such microscopic pathology in the absence of the macroscopic change (such as the cortical atrophy typically observed in the hippocampal pathway [3, 11]) suggests that examining the functional integrity of visual association areas may prove a novel and sensitive marker of early cortical pathology in AD. By broadening the scope of brain function and integrity that is examined in early AD, there is the potential to better characterize the disease process, and develop more sensitive early disease markers than those currently available. To increase the potential efficacy of treatment and intervention in AD, one needs to apply them at the earliest possible stage. Consequently, there has been a substantial increase in the study of amnestic mild cognitive impairment (aMCI); characterized by the presence of acquired cognitive, specifically memory, dysfunction in the absence of both dementia and a significant change in activities of daily living, in relation to an individual’s age and educational level. Although etiologically heterogeneous, a substantial proportion of individuals diagnosed with aMCI will develop AD. Importantly, as in AD, a multidisciplinary research approach to aMCI continues to reveal group-level evidence of substantial deficits in many aspects and levels of visual and visual attention-related processing compared to cognitively healthy aging, with the inherent potential therefore for AD-specific changes in a proportion of such patients [4, 12]. Here we examine the integrity of early visual information processing using objective, neurophysiological measures, i.e., visual evoked potentials (VEPs). The aim was to further characterize the functional abnormalities in AD and in aMCI, specifically with regards to visual information processing, and to inform the development of early disease markers.

Visual evoked potentials Recorded at the scalp, evoked potentials reflect the voltage change in the ongoing electroencephalogram (EEG) associated with particular neural processes. The VEPs described below are those that occur with the onset of a visual stimulus and are comprised of three components, the C1, P1, and N1. The first cortical VEP, C1, typically peaks between 60–90 ms, and represents the processing of basic stimulus characteristics, with neural generators located in the primary visual cortex [13, 14]. The P1, typically peaking between 100–130 ms, has neural generators in the dorsal and ventral extrastriate cortex, and is considered to represent the processing of stimulus characteristics and visuo-spatial selection [15–17]. The N1 peaks between 150–200 ms and is considered to represent object categorization, with multiple neural generators in the occipito-parietal, occipito-temporal, and possibly frontal cortex [18, 19]. The C1-P1-N1 transition reflects the information flow from striate to extra-striate/parietal processing, pre-attentive to attentionally mediated processing, and the building of visual processing from the simplest physical properties to coherent recognizable objects. P1 latencies have been shown to be significantly delayed [20] and the motion-onset N2 (originating in the dorsal extrastriate pathway) reduced in amplitude in AD [21], both pointing to abnormality in visual extrastriate processing. Using flash stimuli, delays have been demonstrated in AD in the extrastriate cortex generated “flash-P2” component, but no change in the earlier striate cortex generated “flash-P1” (n.b., the specific nomenclature for flash VEPs), reinforcing the assertion that primary visual processing is spared while association area processing is impacted in AD [22–26]. Studies examining early VEPs in MCI patients are scarce. Irimajiri and colleagues demonstrated no difference between MCI and healthy controls in VEPs (C1, P1, and N1) elicited in response to chequerboard reversal stimuli [27], while Saavedra and colleagues [46] demonstrated reduced N1 amplitudes but maintained P1 amplitudes in response to more complex visual stimuli, i.e., faces. In addition to the VEPs described above, the Mismatch Negativity (MMN) provides an additional measure of change detection, discriminative processing of stimuli, and therefore a proxy measure of the integrity of early sensory processing during oddball paradigm detection tasks. It is measured as the difference in response following the N1 peak to a frequently presented standard stimulus from that of a rare deviant

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Table 1 Participant demographics for healthy older adults, aMCI, and AD patients Gender Old aMCI AD

Age

MMSE

n

Male

Female

Mean

Range

Mean

Range

26 25 20

14 16 7

12 9 13

76.0 (±7.0) 77.3 (±7.4) 79.2 (±8.8)

62–88 62–91 60–91

28.5 (±1.2) 25.9 (±1.9) 22.9 (±2.5)

25–30 21–29 17–29

stimulus and has been comprehensively documented in the auditory [see 28 for a review] and visual modalities [see 29–31 for reviews]. As well as reflecting early sensory processing, MMN may also be indicative of more generalized cognitive function. Auditory MMN (aMMN) has also been proposed to be a marker of cognitive decline, with reduced aMMN responses observed across a wide range of pathologies associated with cognitive impairments [32]. As previous findings have demonstrated that the visual MMN (vMMN) response is maintained in healthy aging [33], it may represent a valuable tool by which to examine cognitive decline in aging populations. Early and preliminary research by Tales and colleagues was indicative of some abnormality in vMMN in AD and aMCI, namely a possibly delayed but then over-reactive response to novel information [34, 35]. These were, however, preliminary studies with relatively few participants, differences in the treatment status of the AD patients and no analysis of the VEPs that precede the vMMN. Thus the aims of the present study were to examine in more detail the impact of AD and aMCI on vMMN and the preceding VEPs, i.e., P1 and N1. In summary, there is a great need for more sensitive diagnostic tools in AD and MCI clinical research, with growing evidence to support looking beyond medial temporal lobe atrophy and its associated episodic memory impairments. Visual association areas have been demonstrated to be highly vulnerable to AD microscopic pathology and VEPs provide an objective, cost-effective, non-invasive and reliable tool for measuring the functional integrity of such areas. The aims of the present study were therefore to examine the VEP responses of healthy older adults, AD, and aMCI patients during a vMMN oddball paradigm. Specifically we predicted that P1 and N1 VEPs generated in the extrastriate cortex would be impaired in AD, and that vMMN amplitude would be correlated with cognitive impairment. Our prediction for the aMCI group was for greater group heterogeneity in early VEPs and vMMN due to the range of etiologies underlying their cognitive impairment, but given the high risk of conversion to AD, a trend toward the pattern of results observed in AD patients.

MATERIALS AND METHODS Participants Participant demographics are presented in Table 1. The groups differed significantly in Mini-Mental State Examination (MMSE) scores (F 2,70 = 49.2, p < 0.001), with Gabriel post-hoc comparisons indicating healthy older adults > aMCI (mean difference = 2.54, p < 0.001), and aMCI > AD (mean difference = 3.06, p < 0.001). The groups did not differ significantly in age (F 2,70 = 0.96, p = 0.38), or gender (χ2 (2) = 3.74, p = 0.15). AD and aMCI patients were recruited from memory clinics in the South West of England on a consecutive incident patient basis. The diagnosis of AD and aMCI was determined by clinical staff using neurological, neuroimaging, physical, and biochemical examination together with the results of family interview, neuropsychological, and daily living skills assessment according to DSM-IV [36] and NINCDS-ADRDA guidelines [37]. The diagnosis of aMCI was given to individuals who had made a formal, corroborated complaint of cognitive, specifically memory impairment, and who, on examination, were not demented, had preserved functions of daily living and general intellect but exhibited abnormal cognitive function, namely objective memory decline greater than at least one SD and typically greater than 1.5 SDs from age and education-appropriate norms. All patients were free from dementia-related medication and had normal or corrected-to-normal visual function. The older adults control group was recruited from the memory clinics’ volunteer research panels and were in normal general health, had normal or correctedto-normal visual function, and had no evidence of a dementing or other neuropsychological disorder, according to NINCDS-ADRDA guidelines [37]. Exclusion criteria for all groups included poor general health or a history of transient ischemic attack or stroke, significant head injury, and any other significant psychiatric disorder or neurological disease. All appropriate approvals for our procedures were obtained from the National Research Ethics Service

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Fig. 1. Stimuli used to elicit visual evoked potentials. a) inter-stimulus screen; b) attended target; c) unattended standard; d) unattended deviant.

Stimuli

dards, 38 ± 2 for deviants, and 37 ± 3 for targets. Epochs from −100 to 500 ms were defined around stimulus onset and baseline corrected using the prestimulus interval (−100 to 0 ms). A 40 Hz low-pass filter was applied.

Stimuli were presented using Presentation software version 12.2 (Neurobehavioral Systems, Inc).

ERP analysis

Committee South West – Bristol, Ref. 09/H0106/90. Participants provided written informed consent before participating and were free to withdraw at any time.

Procedure Participants were instructed to fixate and attend exclusively to a small blue frame (1.3 cm × 1.3 cm) at the center of a monitor situated 0.5 m in front of them (Fig. 1a) and to respond to a red target stimulus (Fig. 1b) by pressing a hand-held button. The standards, single white bars (3.9 cm × 1.2 cm) were presented simultaneously above and below the central blue square (Fig. 1c); deviants, double white bars equal to the standards in total area (3.9 cm × 0.6 cm × 2) and brightness, were presented in the same locations (Fig. 1d). The target, standard, and deviant stimuli were presented with a randomized stimulus onset asynchrony of 612–642 ms for 200 ms with at least two standards preceding each deviant. The ratio of standards:deviants:targets was 16:1:1. The stimuli were shown in one block containing 640 standards, 40 deviants, and 40 targets. EEG recording EEG signals were sampled at 1000 Hz from 64 Ag/AgCl electrodes fitted on a standard electrode layout elasticized cap using a BrainAmp DC amplifier (Brain Products GmbH) with a common FCz reference and online low-pass filtered at 250 Hz. Impedances were below 5k. Recordings were analyzed offline using Brain Electrical Source Analysis software v5.3 (BESA GmbH). Artifacts including blinks and eye movements were corrected using BESA automatic artifact correction [38] and any remaining epochs containing artifacts > ±100 ␮V were rejected. The rejection rate never exceeded 10% of trials for each participant and stimulus, the mean number of epochs comprising individual averages was 590 ± 31 for stan-

The values of seven electrodes, O1, Oz, O2, PO9, PO10, PO7, PO8, were averaged to form an occipital region of interest. Examination of the grand average evoked responses re-referenced to a common average reference confirmed that the electrode selection was appropriate, that neural activity was highly consistent across the seven electrodes, and that there were no significant differences between electrodes in either hemisphere. Averaging across electrodes that show consistent and comparable activity has also been demonstrated to be more reliable than using single electrodes [39] and has previously been adopted using an identical paradigm [33]. Grand average waveforms were used to select the point at which voltage was at 0 ␮V before and after the peak; peak latency was measured as the time of the greatest positive or negative peak during this epoch. Peak magnitude was measured as the mean amplitude during epochs defined by one SD around the mean peak latency. To calculate the vMMN the averaged response to the standard stimuli was subtracted from the deviant stimuli to create a difference waveform. Sequential one sample t-tests were then applied to the difference waveforms for each group using the method outlined by Guthrie and Buchwald [40]. The consecutive time points necessary to indicate an epoch of significant difference between the standard and deviant responses were obtained from a simulation using an autocorrelation estimated from the data. Intervals with values of p < 0.05 that lasted for the required duration (14 consecutive time points (i.e., 14 ms) for the healthy older adults, 26 for the AD patients, and 9 for the aMCI patients) were accepted as significantly different epochs. vMMN amplitude was then calculated as the mean amplitude of any negative deflection in the difference waveform following the N1 peak.

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Fig. 2. Grand average responses to standard, deviant, and target stimuli and difference waveforms (i.e., deviant minus standard) for healthy older adults, AD, and aMCI patients for the occipital region of interest (average of electrodes O1, Oz, O2, PO9, PO10, PO7, and PO8). Shaded areas on the difference waveforms illustrate epochs of significant difference (p < 0.05) between responses to standard and deviant stimuli throughout the epoch; pink shaded areas indicate the vMMN.

Statistical analysis Effects of group (older adults versus aMCI versus AD) and stimulus (standard versus deviant) on P1, N1 amplitudes and latencies were examined in a 3 × 2 mixed ANOVA, and the effect of group on vMMN amplitude was examined in a one-way ANOVA. Gabriel’s pairwise post hoc comparisons, the most appropriate post-hoc test for unequal group sample sizes, were performed to further explore group differences. Given the considerable physical differ-

ences in stimuli between targets and the standard and deviants, group differences in neurophysiological and behavioral responses to targets were analyzed separately in a one-way ANOVA. P3 amplitude and latency in response to target stimuli was also measured in addition to P1 and N1. Behavioral measures were median reaction time to target stimuli and the percentage of targets correctly responded to. Finally, VEP amplitudes and latencies were entered into a stepwise regression model in order to assess their relationship to MMSE score. Bootstrapped 95% confidence intervals were

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Table 2 Peak latencies (ms) and mean (SD) amplitudes (␮V) of P1, N1 P3, and vMMN in response to standard, deviant, and target stimuli, measured at the occipital region of interest (mean value of electrodes O1, Oz, O2, PO9, PO10, PO7, PO8) in healthy older adults, aMCI, and AD patients P1 Standard Lat

Amp

N1

Deviant Lat

Amp

Target Lat

Amp

Standard Lat

Amp

Deviant Lat

Amp

P3 Target Lat

Amp

vMMN

Target Lat

Amp

Duration

Amp

128 1.9 122 1.9 125 0.8 201 −1.7 202 −2.7 237 −3.1 374 −0.6 146–234 −1.1 (±22) (±1.4) (±25) (±1.4) (±21) (±1.7) (±28) (±2.1) (±32) (±2.9) (±18) (±3.3) (±76) (±3.9) (±1.0) aMCI 129 1.4 125 1.4 126 0.6 204 −0.7 200 −0.8 228 −2.2 362 1.8 – – (±26) (±1.3) (±25) (±1.3) (±27) (±1.5) (±22) (±1.4) (±21) (±1.9) (±28) (±2.8) (±62) (±4.0) AD 138 0.8 115 0.8 118 0.0 208 −0.4 203 −1.0 231 −2.2 372 1.1 147–213 −0.7 (±22) (±0.8) (±27) (±0.8) (±34) (±0.9) (±26) (±0.8) (±25) (±2.0) (±26) (±3.7) (±75) (±2.5) (±0.8) Old

Peak latencies were measured during the following epochs: P1 – largest positive value between 75–170 ms, N1 - largest negative value between 160–260 ms, P3 – largest positive value between 230–500 ms. All three groups showed a double peaked P1 rather than the typical single peak observed in healthy younger adults. P1 latency was measured as the largest positive peak during an epoch that encompassed both peaks; typically the second peak was the largest for all groups.

calculated for all behavioral means and regression beta values. RESULTS Grand average waveforms are presented on the left and the vMMN response on the right of Fig. 2. Mean amplitudes and latencies for P1, N1, P3, and vMMN are presented in Table 2. P1 was reduced in AD patients, and N1 amplitude appeared reduced in aMCI and AD patients compared to healthy older adults. A vMMN response was observable in the healthy older adult and AD group but not in the aMCI grand averages. P1 Figure 3 shows amplitudes of P1, N1, and vMMN in healthy older adults and AD patients. A 3 (group:

Old versus aMCI versus AD) × 2 (stimulus: standard versus deviant) ANOVA revealed a main effect of group on P1 amplitude (F 2,68 = 7.65, p = 0.001). Posthoc comparisons showed AD patients had significantly reduced P1 amplitudes compared to healthy older adults (Mean difference −1.52 ␮V, p = 0.001, (95% CI −2.46, −0.56)) and to aMCI patients (Mean difference −0.97 ␮V, p = 0.046, (95% CI −1.93, −0.014)). There was no significant difference between aMCI patients and healthy older adults (Mean difference −0.54 ␮V, p = 0.367, (95% CI −1.44, 0.35)). A double-peaked P1 was observed across groups; this double peaked morphology of the P1 has previously been highlighted as a potential consequence of healthy aging [see 41]. There was no effect of stimulus on P1 amplitude (F 1,68 = 1.16, p = 0.286) however there was a significant interaction between group and stimulus (F 2,68 = 3.49, p = 0.036) reflecting an increased P1 to deviant stimuli in the healthy older adults. There were no significant effects of group on P1 latencies.

N1

Fig. 3. P1, N1, and vMMN mean amplitudes in response to standard, deviant, and target stimuli in healthy older adults, aMCI, and AD patients. Error bars indicate standard error of the mean. Brackets indicate significant differences between groups. ∗ p < 0.05, ∗∗ p < 0.01.

A 3 (group: Old versus aMCI versus AD) × 2 (stimulus: standard versus deviant) ANOVA revealed a main effect of group on N1 amplitude (F 2,68 = 5.50, p = 0.006). Post-hoc comparisons showed AD patients had significantly reduced N1 amplitudes compared to healthy older adults (Mean difference 1.54 ␮V, p = 0.020, (95% CI 0.19, 2.89)). aMCI patients also demonstrated significantly reduced N1 amplitudes compared to healthy older adults (Mean difference 1.50 ␮V, p = 0.016, (95% CI 0.23, 2.78)). There was no significant difference between AD and aMCI patients (Mean difference 0.03 ␮V, p = 1.0, (95% CI −1.32, 1.40)).

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Fig. 4. Scatter plot and linear regression lines for the two individual predictors in the stepwise regression model, P1 amplitude in response to deviant stimuli and vMMN amplitude, and MMSE score across all participants.

N1 amplitudes were significantly increased in response to deviant compared to standard stimuli (F 1,68 = 12.61, p = 0.001) which was likely due to the temporally overlapping vMMN response. There were no significant effects of group on N1 latencies. vMMN Healthy older adults’ vMMN response lasted for 89 ms (146– 234 ms), resulting in a mean amplitude of −1.10 ␮V (±1.01). AD patients’ vMMN response was split between two epochs of 147–184 ms and 189–213 ms intervals; the intervals were combined for the calculation of mean amplitude given their close temporal proximity, resulting in a mean amplitude of −0.75 ␮V (±0.76). There was no observable vMMN response in the aMCI patients’ data at a group level as indicated by the sequential t-tests (see Fig. 2). Given the absence of an observable vMMN in aMCI patients at the group level, a mean amplitude of the difference waveform was calculated based on the healthy older adults’ vMMN epoch (146–234 ms) for each aMCI patient. This revealed that rather than vMMN being absent from the aMCI group entirely, a significant number of aMCI patients did show a vMMN response. Critically a subset of the aMCI patients showed a positive rather than negative deflection of the difference wave during the critical vMMN epoch; this subset can be clearly seen in Fig. 4. Further examination of the individual subject waveforms revealed that these individuals showed a larger P1 amplitude to deviant stimuli prior to the anticipated vMMN response, i.e., the preceding VEP activity influenced the amplitude of components in the subsequent epoch. Such posi-

tive deflection was not observed in any healthy older adults or AD participants. This explains the absence of an observable vMMN response in the aMCI grand average waveform, as the positive deflection in the difference wave from this subset weakened or cancelled out the remaining aMCI patients’ typical negative deflection. A one-way ANOVA revealed a main effect of group (Old versus aMCI versus AD) on vMMN amplitude (F 2,68 = 6.31, p = 0.003). aMCI patients showed a significantly reduced vMMN amplitude compared to healthy older adults (Mean difference 0.88 ␮V, p = 0.002, (95% CI 0.27, 1.49)), but not compared to AD patients (Mean difference 0.58 ␮V, p = 0.094, (95% CI −0.07, 1.24)). There was no significant difference between AD patients and healthy older adults in vMMN amplitude (Mean difference 0.29 ␮V, p = 0.61, (95% CI −0.35, 0.94)). Behavioral and neurophysiological responses to targets P1, N1, and P3 amplitudes and latencies in response to target stimuli are reported in Table 2. There was no effect of group on P1 amplitudes (F 2,68 = 1.77, p = 0.178) or latencies (F 2,68 = 0.52, p = 0.595), or N1 amplitudes (F 2,68 = 0.62, p = 0.542) or latencies (F 2,68 = 1.03, p = 0.363). There was also no effect of group on P3 amplitude (F 2,68 = 2.87, p = 0.064) or latency (F 2,68 = 0.19, p = 0.827). Mean reaction times and response accuracies are presented for each group in Table 3. One-way ANOVA (group: Old versus aMCI versus AD) revealed no significant effects of group on the number of targets

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Table 3 Mean accuracy and mean (median) reaction times to target stimuli for healthy older adults, aMCI, and AD patients Accuracy (%)

Old aMCI AD

Reaction time (ms)

Mean (SD)

Bootstrap 95% CI

Mean (SD)

Bootstrap 95% CI

97.8 (±3.3) 93.2 (±11.1) 93.1 (±9.5)

96.4 – 99.0 88.2 – 96.9 88.3 – 96.7

417 (±38) 438 (±63) 456 (±62)

403–432 413–463 429–484

detected (F 2,68 = 2.48, p = 0.092) or mean reaction times (F 2,68 = 2.89, p = 0.062). VEPs as predictors of impairment Stepwise multiple regression analysis was performed to evaluate the relationship between VEPs and MMSE score across all participants. Predictor variables were the amplitudes and latencies of P1 and N1 in response to standard and deviant stimuli; P3 amplitude and latency in response to target stimuli and vMMN amplitude. P1 amplitude in response to deviant stimuli and vMMN amplitude emerged as significant predictors of MMSE score, i.e., lower MMSE scores were associated with lower vMMN amplitudes and lower P1 amplitudes in response to deviant stimuli. See Table 4 for the regression model statistics and Fig. 4 for scatter plots illustrating the relationship between MMSE and the predictors. DISCUSSION The study investigated early VEPs and vMMN in AD and in aMCI compared to cognitively healthy aging. Our results demonstrated that early VEP amplitudes (P1 and N1) were significantly reduced in AD, highlighting the sensitivity of VEPs to the functional disruption of visual extrastriate processing in AD. N1, but not P1, amplitudes were significantly reduced in aMCI patients compared to healthy older adults, possibly representing an interim stage between healthy aging and AD. vMMN amplitude was not significantly reduced in AD patients at group level compared to healthy older adults, however stepwise regression analysis demonstrated that vMMN amplitude was a significant predictor of MMSE score along with P1 amplitude to deviants, i.e., the lower the vMMN/P1 amplitude the lower the MMSE score. aMCI patients did not show a vMMN response at a group level due to the distortion of the group mean by a subset of aMCI patients who showed an abnormal mismatch “posi-

tivity”. There were no differences between groups in the behavioral responses to targets, i.e., reaction time and accuracy, highlighting how objective neurophysiological measures are sensitive to changes in brain function long before those changes are severe enough to manifest themselves behaviorally. The reduction of P1 and N1 in AD patients is in line with earlier research on flash, pattern, and motion onset VEPs [e.g., 22–26, 42, 43] and indicative of an AD-specific deficit in early visual association area processing, an area highlighted as highly vulnerable to AD pathology [8–10, 27]. We propose that the reduction in P1 and N1 amplitude in AD shown in the present study may reflect this pathology and provides a potential marker of early AD, although without postmortem assessment of extrastriate integrity any link between VEP change and microscopic pathology is inferential. Crucially atrophy in the early stages of AD are rarely demonstrated in this cortical area [7, 10], highlighting EEG’s potential to complement and broaden the assessment and characterization of brain function beyond that currently available using behavioral, imaging, and biochemical tools. More generally, synaptic dysfunction (i.e., reduced long-term potentiation and synaptic transmission) has been demonstrated to be a significant consequence of AD and one that occurs to a significant degree prior to the emergence of classic AD pathology, e.g., amyloid plaque deposits and neurofibrillary tangles [see 44 for a summary of AD related synaptic dysfunction]. The high synaptic complexity of the sensory association areas may make them functionally highly vulnerable to such dysfunction. P1 amplitude in response to deviant stimuli, but interestingly not in response to standard stimuli, emerged as a significant predictor of MMSE score in a stepwise regression analysis. The difference in the predictive value of responses to standard and deviant stimuli may be due to the large differences in the number of trials contributing to an individual’s average VEP (590 ± 31 for standards, 38 ± 2 for deviants). It may be that impaired extrastriate processing, as a consequence of pathology, results in a weaker or more unstable P1, consequently more trials are required in the averaging process in order for a stable peak to establish itself. Clearly in the case of the AD group, there was still a significant reduction in P1 amplitude regardless of stimulus. Nevertheless, the reduction was greater in the P1 to deviant stimuli, and it was this measure that emerged as a significant predictor of MMSE score. The number of trials has been clearly demonstrated to be important in the elicitation of another evoked potential, the feedback related negativity

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Table 4 Stepwise multiple regression analysis of VEP predictors of MMSE across participants Model

Predictors

Beta (Bootstrapped 95% CI)

SE

Standardized Beta

P

F (2,70) = 5.70, p = 0.005 R2 = 0.14

P1 deviant amplitude

0.50 (0.25 – 0.81)

0.18

0.31

0.008

vMMN amplitude

−0.70 (−1.19 – −0.25)

0.33

−0.24

0.039

Variables entered into the initial model were P1 and N1 amplitudes and latencies in response to standard and deviant stimuli, P3 amplitude and latency in response to target stimuli, and vMMN amplitude. The table indicates the final model indicating P1 amplitude to deviant stimuli and vMMN amplitude as significant predictors of MMSE score.

component. Marco-Pallares and colleagues demonstrated that healthy older adults needed more than double the number of trials than younger adults before a reliable feedback related negativity component emerged [45] and suggest that the number of trials needed in clinical or cognitively impaired samples might be much larger. Differences in the number of presentations necessary to elicit a VEP may prove to be a sensitive way in which to assess the functional integrity of a sensory processing area The reduction in the aMCI patients of N1 but not P1 amplitudes matches the findings of Saavedra and colleagues [46] who demonstrated reduced N1 amplitudes but maintained P1 amplitudes in response to faces. Given that conversion to AD is expected in a substantial proportion of aMCI patients over a 5-year period [47], the reduced N1 amplitude in the absence of significant reduction of P1 amplitude in our aMCI at group level may reflect the presence of prodromal AD in some individuals. Surprisingly, given the clear reduction in both patient groups, N1 amplitude did not emerge as a significant predictor of MMSE score in the stepwise regression analysis. Planned longitudinal follow up of the aMCI patients will help to establish if reduced N1 amplitude did indeed reflect an interim stage between healthy aging and AD. vMMN amplitude was not significantly reduced in AD. A clear delineation of AD patients from healthy aging was not observed, possibly due to some healthy older adults showing vMMN amplitudes close to zero. Overall, inter-individual variability had a significant impact on between group comparisons of vMMN amplitude, and further development of vMMN paradigms is needed in order to consistently elicit stable vMMN responses in control populations. Previous findings by Tales and colleagues [34, 35] demonstrated an increased vMMN response in AD patients compared to healthy older adult controls, but to only the second half of stimuli presented. The current data was examined for differences in responses to the first and second halves of stimuli presentation, as in the previous stud-

ies, and there were no significant differences in any of the participant groups. As previously discussed, Tales and colleagues’ sample sizes were smaller than the current study and in the later study [35]. AD patients were taking cholinergic medication, and cumulatively these factors may explain the difference in findings between the initial studies and the current study. Additionally the measurement of the vMMN differed in the current study, i.e., the duration of the vMMN was measured in order to accurately measure the mean amplitude, as opposed to as opposed to Tales and colleagues’ measurement of the mean vMMN amplitude across a pre-selected fixed epoch. These discrepancies further highlight the need for reliable measurement of the vMMN response at the level of the individual participant. It should also be noted that the current study did not include a rigorous assessment of visual function beyond the clinicians’ assessment of patients showing normal or corrected to normal visual function. Future work should include such an assessment of visual function (e.g. contrast sensitivity, flicker fusion thresholds) in order to dissociate striate and extrastriate cortical processing changes. The absence of a vMMN response in the aMCI group grand average waveform was due to a subset of aMCI patients who showed an abnormal mismatch “positivity”. This subset of patients did not differ in any characteristic (e.g., age, gender, MMSE, VEPs), from the other aMCI patients, however it was observed that their P1 amplitudes in response to deviant stimuli were larger compared to standard stimuli, suggesting differences in early visual processing of this subset of MCI patients. Recent studies have demonstrated a reduced aMMN in aMCI patients but only in novel minus standard comparisons, not the typical deviant minus standard comparison [48], and reduced aMMN that correlated with self-reported disability, but only observed at mastoid and not the typical fronto-central electrode sites [49]. The inconsistency of findings may be due to the inherent pathological heterogeneity of groups of aMCI patients that make clear findings

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harder to detect than in groups with a common pathology. Future work should focus on establishing a reliable normative range of vMMN in healthy individuals, and optimizing the reliable measurement of vMMN in healthy individuals in order that an altered vMMN response can be attributed to pathology and not inter-individual variability. Additionally, it may be that changes in vMMN over time may predict outcome more accurately than a single assessment. A recent study of comatose patients highlighted this issue by demonstrating that although baseline differences in aMMN were present between patients and controls, it was the deterioration in aMMN between two separate measurements that was the most predictive of clinical outcome [50]. A recent proposal by N¨aa¨ t¨anen and colleagues [32] is that MMN is a marker of cognitive decline across etiologies including AD [e.g., 51, 52], with the majority of evidence derived from aMMN studies. Despite the absence of a significant difference between AD patients and healthy older adults and the high inter-individual variability in aMCI patients, vMMN amplitude emerged as a significant predictor of MMSE score, along with P1 amplitude in response to deviant stimuli. With improvements in the measurement of vMMN and a wider range of cognitive assessment, further similarities with the aMMN and its relationship to cognitive impairment may emerge, and is a clear avenue for future work. In summary, we have demonstrated a clear reduction in the early P1 and N1 VEPs in AD patients, which may serve as a biomarker of extrastriate cortex microstructural pathology. aMCI patients showed a maintained P1 but a subsequently reduced N1, which may represent an interim stage between healthy aging and AD for some individuals within this group. vMMN was not significantly reduced in the early stages of AD, but along with P1 amplitude to deviant stimuli, did prove to be a significant predictor of MMSE score across participants. It was absent at a group level in aMCI patients, but further examination revealed a high level of heterogeneity in vMMN responses. The results highlight the need for reliable individual level measurement and analysis of vMMN in order to optimize its clinical potential as an early diagnosis tool and marker of disease progression.

memory service clinics at the BRACE Centre, Frenchay Hospital and Abi Wright, Dr Krist Noonan and Prof. Roy Jones at the Research Institute, for Care of the Elderly and BRACE-Alzheimer’s research registered charity no. 297965 for their invaluable and continued support with patient recruitment, equipment funding and publishing costs. This work was supported by the Biotechnology and Biosciences Research Council. Prof. N¨aa¨ t¨anen acknowledges the Institutional Research Grant IUT 02–13 to Juri Allik from the Estonian Ministry of Education and Research. Authors’ disclosures available online (http://www.jalz.com/disclosures/view.php?id=2529). REFERENCES [1] [2]

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