Visual target processing in high- and low-performing older subjects indexed by P3 component

VISUAL TARGET PROCESSING IN HIGHAND LOW PERFORMING OLDER SUBJECTS INDEXED BY P3 COMPONENT LE P3 EN TANT QU’INDEX DU NIVEAU DE PERFORMANCE DE SUJETS ÂGÉS IMPLIQUÉS DANS UNE TÂCHE VISUELLE Authors: L. Lorenzo-López∗, E. Amenedo, P. Pazo-Álvarez, F. Cadaveira This is the peer reviewed version of the following article: Lorenzo-López, L., Amenedo, E., PazoÁlvarez, P., Cadaveira, F. (2007). Visual target processing in highand low-performing older subjects indexed by P3 component. Neurophysiologie Clinique / Clinical Neurophysiology, 37, 53-61. doi: 10.1016/j.neucli.2007.01.008 This article may be used for non-commercial purposes in accordance with Elsevier, International Federation of Clinical Neurophysiology, Italian Clinical Neurophysiology Society, Japanese Society of Clinical Neurophysiology, Brazilian Society of Clinical Neurophysiology terms and conditions for use of self-archived versions. Post-print (final draft post-refereeing) 2 Visual target processing in highand low-performing older subjects indexed by P3 component Le P3 en tant qu’index du niveau de performance de sujets âgés impliqués dans une tâche visuelle Authors:L. Lorenzo-López∗, E. Amenedo, P. Pazo-Álvarez, F. Cadaveira Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Santiago de Compostela, Galicia, Spain *Corresponding author: laura[email protected] (L. Lorenzo-López). Post-print (final draft post-refereeing) 3 Abstract Aim. — To explore the possible changes in the parameters of the P3 event-related potential (ERP) component among groups of young and older healthy subjects characterized as either highor low-performers in a visual attention task. Methods. — Both conventional and single-trial analyses of the visual P3 component were performed on each group of subjects. Results. — P3 component significantly increased in latency as a function of age. The high performing older subjects showed the posterior predominance of P3, as in young subjects. However, the low-performing older subjects showed a significant P3 amplitude reduction at posterior locations and topographically more widespread activity. Furthermore, single-trial analysis showed that low-performing older subjects presented higher intertrial variability in P3 latency, few trials with P3 generation, and a reduced P3 amplitude in these trials in whom P3 was generated. Conclusion. — These data suggest a specific decline in visual target processing in the low performing older subjects, which would imply a reduction in these attentional brain resources that are allocated to correctly select the relevant stimuli. The implications of this finding for the actual compensation versus dedifferentiation debate in normal aging are discussed. Résumé But. — Comparer les paramàtres du composant P3 des potentiels évoqués dans un groupe de sujets jeunes en bonne santé et dans un groupe de sujets âgés classifiés en fonction de leur niveau d’exécution d’une tâche d’attention visuelle (meilleurs et moins bons exécuteurs). Méthodes. — Des analyses conventionnelles et des analyses « en sweep unique » du composant P3 ont été réalisées dans chaque groupe de sujets. Résultats. — Le temps de latence du composant P3 augmente de fac¸on significative avec l’âge. Chez les sujets âgés meilleurs exécuteurs le P3 prédominait au niveau des régions postérieures, comme chez les sujets jeunes. Par contre, chez les sujets âgés moins bons exécuteurs, le P3 était significativement moins ample en postérieur et plus diffusément réparti sur le scalp. Les analyses « en sweep unique » ont montré que ces derniers présentaient une plus grande variabilité interessai en ce qui concerne le temps de latence de P3, moins de tests où le P3 était présent, ainsi qu’une réduction de l’amplitude de P3 dans les tests où il était présent. Conclusion. — Ces données suggèrent l’existence d’un déficit du traitement visuel des stimuli chez les sujets âgés moins bons exécuteurs qui pourrait consister en une réduction des ressources Post-print (final draft post-refereeing) 4 cérébrales attentionnelles mobilisées pour sélectionner correctement le stimulus approprié. Nous discutons les implications de ces résultats dans le d´ebat concernant la redistribution des aires corticales actives chez les sujets âgés (hypothèses de compensation versus dédifférentiation). Post-print (final draft post-refereeing) 5 Introduction The P3 component of event-related potentials (ERPs) has demonstrated considerable utility in the study of cognitive life-span changes, since it has been associated with basic informationprocessing mechanisms including attention and memory [33]. P3 is a large positive-going waveform with a posterior-parietal maximum amplitude and a peak latency of about 300—400 ms in young subjects, which has been obtained in the auditory, visual or somatic modality (for a recent review, see [19]). The visual P3 was shown to be significantly larger in amplitude and longer in latency than the auditory P3 [22,32]. In the ERP literature, P3 latency has been considered an indicator of the speed of cognitive processing associated with the selection of relevant stimuli; it is generally unrelated to response selection processes and independent of behavioral measures [26,30]. P3 amplitude has been considered as an index of the allocation of attentional brain resources to the voluntary selection of relevant stimuli (for a review, see [23]). The results of several ERP aging studies employing auditory or visual paradigms demonstrated the existence of age-related changes in the latency, amplitude, and scalp distribution of this component. Specifically, there is general consensus that the peak latency of P3 progressively increases with age [1,20,25,31,32,34,39,40]. However, results on P3 amplitude changes with age are less consistent, especially for visual stimuli, since amplitudes were found to be unaffected by age in some studies [32], but reduced only at some electrode locations in others [31,34]. Other common finding in the literature is an age-related topographic alteration in the scalp distribution of P3, which becomes more anteriorly distributed and, thereby, more diffused or equipotential across the scalp with increasing age [1,10—12,15,17,18,32,40]. These age-related topographical changes have been interpreted as reflecting attentional alterations in older subjects, who would continue to utilize frontal processes for stimuli that have already been well-categorized [1,10], (see [16] for a recent review). In parallel with these age-related changes in P3 scalp distribution, functional neuroimaging studies of aging have shown a paradoxical increase in the brain activation of older subjects during the execution of memory tasks, particularly in prefrontal areas [6,28,35]. It has been suggested that this age-related recruitment of atypical brain pathways might reflect a possible compensatory response (for reviews, see [3—5]). In keeping with this view, the ‘compensation’ hypothesis suggests that, in order to reach an adequate level of behavioral performance in a specific task, high performing older subjects would recruit different and wider areas of the brain, which are not activated by younger subjects (for reviews, see [5,16,36]). Alternatively, it has been suggested that this age-related increase in frontal activation could reflect an inefficient neural distribution of task-relevant cortical networks in older subjects, which was referred to as the ‘dedifferentiation’ hypothesis (see [3—5,28,36] for reviews). Post-print (final draft post-refereeing) 6 In our opinion, a fruitful way to shed new light on this debate would be to differentiate between performance levels in aging studies. Therefore, the aim of this study was to explore whether the P3 latency, amplitude, and scalp distribution differ in young and older subjects characterized as either highor low-performers in a visual attention task. Since the typical oddball task is relatively easy, and performance in older subjects is usually almost perfect, we used a more demanding task. We tried to determine whether possible P3 differences between both subgroups of older subjects should be considered compensatory or inefficient. Indeed, if differences are due to a compensatory mechanism, highperforming older subjects should be expected to present a more widespread scalp distribution of P3 than young subjects. Alternatively, if the differences are due to a deficit or an inefficient neural activation, the scalp distribution changes should be observed in low-performing older subjects. Because the previously described age-related P3 amplitude reductions may actually be due to: (a) the existence of more intertrial variability in P3 latency (i.e. latency jitter effect), (b) reduced P3 amplitudes in all trials, or (c) absence of P3 generation in some trials [26], we used a single-trial method to describe P3 fluctuations in addition to the conventional ERP averaging. Finally, it should be noted that, whereas in most of previous studies the cognitive functioning of older subjects was defined by their performance on standardized neuropsychological tests [7], in our study the older subjects were characterized as either highor low-performers according to their actual behavioral performance in the visual attention task. This allows us comparing these electrophysiological responses that are related to different actual performance levels among groups in the same task. Materials and methods Subjects Ten young (7 females, age range: 22—38, mean: 29.4±6.3 years), and ten older subjects (5 females, age range: 58—67, mean: 62.2±3.2 years) were tested. All were healthy wellfunctioning subjects and had no history of neurological or psychiatric diseases. All subjects had normal or correctedto-normal vision. Older subjects performed the Spanish version (MEC-35) [27] of the Mini-Mental State Exam (MMSE) [13] and had normal scores (> 28). Informed consent was obtained from all subjects. The older subjects were assigned to two groups on the basis of their behavioral performance in the visual attention task that was carried out during the recording of P3: a group of older subjects who performed as well as the young subjects (high-performing, N = 5), and a group of older subjects who performed at a significantly lower level compared to the young subjects (low- Post-print (final draft post-refereeing) 7 performing, N = 5). Reaction times (RTs) and performance levels confirmed that the older subjects assigned to the low-performing group, performed significantly worse than young and high-performing older subjects (see result section). Age and gender distributions were similar in both older groups (see Table 1). Stimuli and procedure Subjects sat in a comfortable armchair in an electrically shielded and sound-attenuated room at 61 cm viewing distance from a computer monitor. All stimuli were created, presented, and controlled using the Presentation software application (Neurobehavioral Systems, Inc., version 0.76). Afixation cross was presented continuously at the center of the monitor. The stimuli consisted of nine possible digits (1, 2, 3, 4, 5, 6, 7, 8 or 9) in three different colors (red, green or blue) subtending 1.04◦ ×0.66◦ of visual angle, which were equiprobably presented for 40 ms over the central fixation cross. Subjects were required to press a mouse button as quickly as possible in response to digits lower than five of any color. Thus, digits 1, 2, 3 and 4 of any color were the target stimuli. Horizontal sinusoidal gratings differing in motion direction (4.13◦ visual angle, 20% contrast, speed 1.95 deg/s, spatial frequency 0.7 cycles/deg) were also presented bilaterally at 10.7◦ to the left and to the right from the fixation cross for 133 ms. These gratings were presented in sequences of repetitive upward-drifting gratings (standard motion, p = 0.8), which were occasionally replaced by downward drifting gratings (deviant motion, p = 0.2) and were followed by a blankscreen ISI of 665 ms. Subjects were presented with a block of 770 trials, from which 500 correspondedto unattended gratings and 270 to attended digits. All stimuli were presented with a stimulus onset asynchrony (SOA) of 798 ms. Subjects were required to fix their gaze on the central cross and to pay attention to the digits, while ignoring the peripheral gratings. In a recent study, we reported the effects of normal aging on the preattentive processing of these unattended peripheral gratings [29] and here we only report the results on the central task. ERP recordings Continuous electroencephalogram (EEG) was recorded (bandpass 0.05—100 Hz, 500 Hz/channel) with a NeuroScan system from 20 active electrodes (Fp1, Fp2, F3, Fz, F4, F7, F8, C3, Cz, C4, P3, Pz, P4, T3, T4, T5, T6, O1, O2, Oz), referred to the nose tip and grounded with an electrode at nasion. Vertical and horizontal eye movements were recorded bipolarly with additional electrodes placed above and below the left eye and at the outer canthi of both eyes, respectively. Electrode impedance was kept below 10 K_. Post-print (final draft post-refereeing) 8 Data analysis Behavioral data analysis RTs were automatically on-line recorded for all subjects, and the performance level was calculated as the percentage of correct responses to target digits in the central visual task. Only RT values associated with correct responses were considered for data analysis. Mean RTs and percentages of correct responses were compared across groups using one-way analysis of variance (ANOVA) with Group (young, high-performing older, lowperforming older) as the between subjects factor. ERP data analysis Two types of analysis were performed on ERP data: conventional analysis of amplitude, latency and scalp distribution, and single-trial analysis. Conventional averaging The EEG was digitally filtered off-line with a 0.1—30 Hz bandpass filter, and epoched into periods of 1000 ms (100 ms pretarget and 900 ms post-target). Epochs exceeding± 100µV and those containing horizontal or vertical eye movements, or incorrect responses were excluded from analysis. The EEG was averaged for the target digits in each group of subjects, separately. The P3 component was then measured as the maximum positive voltage peak between 300 and 600 ms poststimulus relative to the 100 ms baseline in each group of subjects. These amplitude values were subjected to mixed ANOVA with Group (young, high-performing older, low-performing older) as the between-subjects factor, and Localization (anterior, posterior), and Electrode (anterior: Cz, Fz, F3, F4, Fp1, Fp2; posterior: Pz, Oz, P3, P4, O1, O2) as the within-subject factors. The P3 latency values were determined with respect to the largest positive voltage at Pz electrode and compared across groups using one-way ANOVA with Group (young, highperforming older, low-performing older) as the between-subjects factor. Note that, in this study, we explored the age-related differences in P3 parameters along an anterior-posterior axis, so data on specific electrodes are not presented. An alpha level of 0.05 was used for all statistical tests. Degrees of freedom were corrected by the conservative Greenhouse—Geisser estimate when appropriate. Post hoc comparisons were performed using the Bonferroni adjustment for multiple comparisons. Finally, in order to examine the scalp distribution of P3 and to explore in more detail the possible changes in the scalp distribution of P3 amplitude among groups, voltage maps were computed with the EEGLAB program [8], which plots topographic maps of EEG fields as a 2D circular view using cointerpolation on a fine Cartesian grid. Single-trial analysis Post-print (final draft post-refereeing) 9 In order to visualize and describe more accurately the trial-to-trial variability in the amplitude and latency of P3 component during the task, EEG epochs to target digits associated with correct responses were subjected to single-trial analysis using the EEGLAB software [8] at Fz and Pz electrodes in each subject. In a first step, EEG Neuroscan data epoch files including only correct responses were imported via the EEGLAB toolbox under MATLAB environment. The specific channels of interest (Fz and Pz) were then selected. Thereafter, the EEGLAB menu allowed us to sort data trials according to their occurrence in the experiment and, finally, to create ERP-image plots. The computed ERP-images consisted of two-dimensional colored rectangular representations of trial data, in which each horizontal line represents activity occurring in each single experimental trial. In these images the activity values are color-coded in left-to-right straight lines, with the changing color value indicating potential variations at each time point in the trial. Inspecting the adjacent single trials allowed us to explore the trial-by-trial P3 consistency, making possible to determine whether a P3 response was present in each individual trial, and to explore its moment-to-moment fluctuations in each group of subjects. Results of this single-trial analysis were compared with those of the conventional averaging. Results Behavioral data RTs and percentages of correct responses are summarized in Table 1. There was a significant main effect of Group on mean RT (F2,17 = 5.67, P < 0.013). Pairwise comparisons (Bonferroni) revealed that the mean RT of low-performing older subjects was significantly longer than that of young subjects (P < 0.011), with no significant differences between the mean RT of highperforming older and young subjects (P = 1), and between both lowand high-performing older subjects (P = 0.138). There was a significant main effect of Group on percentage of correct responses (F2,17 = 7.74, P < 0.004). Pairwise comparisons revealed that performance accuracy was significantly lower for the low-performing older subjects than for the other two groups (young: P < 0.005; high-performing older: P < 0.017), with no significant differences between the performance levels of the latter two groups (P = 1) (see Table 1). ERP data Figure 1 shows ERPs to targets for young, high-, and lowperforming older subjects at anterior and posterior scalp locations. 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