Age-Related Differences in Face Processing: A Meta- Analysis of Three Functional Neuroimaging Experiments

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1 Age-Related Differences in Face Processing: A Meta- Analysis of Three Functional Neuroimaging Experiments CHERYL L. GRADY, Rotman Research Institute, Departments of Psychiatry and Psychology, University of Toronto Abstract Differences between young and old adults in brain activity, measured with positron emission tomography, were examined during three face processing experiments: episodic memory, working memory, and degraded face perception. Each experiment contained an easy face matching condition and a more difficult processing condition. Young adults showed greater activity in bilateral prefrontal cortex during the memory tasks, compared to face matching, but no difference in prefrontal activity between degraded and nondegraded perception. Older adults, on the other hand, had greater prefrontal activity in both memory and degraded perceptual tasks compared to matching. This suggests that increased prefrontal activity is task-specific in young adults, but, in old adults, is a more general response to increased cognitive effort or need for resources. These data are consistent with the dedifferentiation hypothesis of aging, and suggest a possible neural mechanism for this dedifferentiation, such that dependence on prefrontal activity across a greater number of tasks could also increase the amount of covariance across these tasks. Aging is associated with changes in the visual system that affect contrast sensitivity and other aspects of vision (e.g., Spear, 1993). These changes, most of which are thought to be of central rather than peripheral origin (Burton, Owsley, & Sloane, 1993; Spear, Moore, Kim, Xue, & Tumosa, 1994), affect older adults' ability to detect or discriminate faces, as indexed by an increase in contrast necessary for discrimination to take place (Owsley, Sekuler, & Boldt, 1981; Sekuler & Owsley, 1982). Older adults also show reduced accuracy or increased reaction times (RTs) on tasks requiring perceptual matching of faces (Grady, McIntosh, Horwitz, & Rapoport, 2000; Grady et al., 1994). However, these perceptual differences are smaller in magnitude than age-related reductions in the ability to remember faces (Bartlett & Leslie, 1986; Bartlett, Leslie, Tubbs, & Fulton, 1989; Grady et al., 1995). Elderly individuals consistently show substantial reductions in recognition memory for unfamiliar faces (Bartlett & Leslie, 1986; Bartlett et al., 1989; Crook & Larrabee, 1992; Smith & Winograd, 1978), unless the faces are retained for very short periods of time, such as a few seconds (Grady et al., 1998). In contrast, recognition of other types of complex visual information, such as pictures of objects or scenes, is often spared or only slightly reduced compared to younger adults (Craik & Jennings, 1992; Grady, McIntosh, Rajah, Beig, & Craik, 1999; Park, Puglisi, & Sovacool, 1983; Smith, Park, Cherry, & Berkovsky, 1990). Recently, functional neuroimaging has been used to examine the brain mechanisms underlying age-related differences in face processing. A particular region in ventral extrastriate cortex, known as the fusiform gyrus, is critically involved in face perception and memory (Andreasen et al., 1996; Bernstein, Beig, Siegenthaler, & Grady, in press; Courtney, Ungerleider, Keil, & Haxby, 1996, 1997; Haxby et al., 1994; Haxby et al., 1996; Kanwisher, McDermott, & Chun, 1997; Kuskowski & Pardo, 1999; McCarthy, Puce, Gore, & Allison, 1997; Moscovitch, Winocur, & Behrmann, 1997; Sergent, Ohta, & MacDonald, 1992), and generally shows larger increases in activity for faces than for other kinds of stimuli (Haxby et al., 1999; Kanwisher, Stanley, & Harris, 1999; Kanwisher et al., 1997). Activation in face-sensitive regions in the fusiform gyrus during face matching in older adults is equivalent to that seen in young adults (Grady et al., 1994; Grady et al., 2000). This indicates that perceptual mechanisms are largely unchanged with age, at least in terms of overall activity levels in this region of the brain. However, older individuals also show greater activation in prefrontal cortex during face perception, particularly in the left hemisphere (Grady et al., 1994; Grady et al., 2000). When working memory for faces is tested over very short time intervals (e.g., several seconds), prefrontal activation becomes more apparent in both young and older adults, but the patterns of activation are different. That Canadian Journal of Experimental Psychology, 2002, 56:3,

2 Age-Related Differences in Face Processing 209 is, both show increased activity in prefrontal and temporal lobe areas (Grady et al., 1998), but older adults have more activation, compared to younger adults, in left dorsolateral prefrontal cortex, similar to that seen during perceptual tasks. When memory for faces is tested over a longer time period (15-20 minutes), activity in older adults is reduced in some memory-related brain areas, such as parietal regions, but similar in magnitude to that seen in young adults in other areas, such as parts of right prefrontal cortex (Grady, Bernstein, Siegenthaler, & Beig, 2002; Grady et al., 1995). Under some conditions, older adults can show greater activation in left prefrontal cortex during face recognition, similar to that seen in perception and working memory (Grady, Bernstein et al., 2002). A consistent finding from these face processing experiments is that left prefrontal cortex is frequently activated more in older adults than in young adults. Greater activation of left prefrontal cortex in older adults also has been found in other task conditions, including verbal recognition and cued recall (Backman et al., 1997; Cabeza et al., 1997; Madden et al., 1999) and during spatial memory tasks (Reuter-Lorenz et al., 2000). This additional activity has been interpreted as an indication of greater demands on the executive functions of the frontal lobes that may reflect a compensatory mechanism, particularly when there are no age-related reductions in performance (Cabeza et al., 1997; Grady et al., 1994). Thus, we have learned a fair amount about how brain activity during face processing does or does not change with age. Some of these changes are similar to those seen using other kinds of task paradigms, raising the question of whether there are any differences that are common across face perception and memory tasks that might reflect more general changes due to aging, rather than task-specific differences. For example, is the particular region of left prefrontal cortex that shows increased activity in older adults the same area across tasks, suggesting a more generalized age effect, or is it task-specific? Are there any other regions of the brain that show consistently reduced or increased activity across different face processing tasks? Differences between young and old adults in how brain activity is related to individual differences in performance also have been reported (Grady, Bernstein et al., 2002; Grady et al., 1998; Madden et al., 1997; McIntosh et al., 1999). For example, in the working memory experiment cited above (Grady et al., 1998), a positive correlation was found between left prefrontal activity and reaction time in older adults, whereas this correlation was reversed in young adults. However, it is not known if such differences are similar across tasks or specific to the particular task demands. The purpose of the present study was to combine data from three face processing experiments, representing episodic memory (Grady et al., 1995), working memory (Grady et al., 1998), and degraded face perception (Grady et al., 2000), to address some of these questions about general versus specific age-related differences. Each of these experiments contained a relatively easy face matching task and a more demanding task, either of face memory or degraded perception. If the greater activity in prefrontal cortex in older adults during face processing is a general aging effect then one would expect to find increased activity in all of the more difficult tasks regardless of the specific task demands, whereas such increases would be task specific in younger adults. Thus, comparison across the three experiments will show whether or not age-related differences in brain activity and in the relation between brain activity and behaviour are characteristic of face processing in general. Method Data from three separate experiments, all using grayscale photographs of faces as stimuli (Haxby et al., 1994) and carried out with positron emission tomography (PET), were used in the current analysis. Participants were screened to rule out trauma, alcohol or other drug abuse, concurrent medication, cerebral abnormalities (using structural MRIs), or medical diseases that could affect brain function (Duara et al., 1984). Demographic information about the participants in these experiments is shown in Table 1. The first experiment examined brain activity during episodic memory for faces and included encoding and recognition conditions (EM, Grady et al., 1995; Haxby et al., 1996). The second examined face working memory using a delayed match-to-sample paradigm from 1 to 21 seconds (WM, Grady et al., 1998; Haxby, Ungerleider, Horwitz, Rapoport, & Grady, 1995). The third study measured brain activity during perception of degraded and nondegraded faces (DF; Grady et al., 1996; Grady et al., 2000). Faces were degraded by replacing a percentage of the pixels in the face with random gray values (the degradation ranged from 20% to 70%). The majority of participants were right-handed; one young participant in the DF experiment and three older participants in the WM experiment were left-handed. All were highly educated, with greater than 12 years of education. Participants with less than 20/20 vision uncorrected wore their corrective lenses/glasses during the experiment. One older female participated in both the EM and DF experiments, and another older female was part of both WM and DF; otherwise the subject samples of the three experiments were unique.

3 210 Grady TABLE 1 Demographic Data on Participants From the Three Experiments Age (yrs) Gender Experiment Y O Y O Episodic memory 25 ± 2 69 ± 6 8M,2F 7M,3F Working memory 25 ± 3 66 ± 4 10M,3F 11M,5F Degraded faces 24 ± 3 66 ± 4 5M,5F 5M,5F Values are mean ± s.d. Y = young adults; O = old adults. For the current analysis, three task conditions from each experiment were used. One condition was a nonface control task and the second was a relatively easy face-matching task, both of which were similar across all three experiments (details of the experimental paradigms can be found in the references listed above). The third task from the EM experiment was a recognition condition that occurred roughly 20 min after a study period. The third task from the WM experiment was the condition utilizing a 6-s delay between the sample and choice faces, and the third DF condition was one in which faces had been degraded by 50%. These latter three conditions were chosen to represent the three processes of interest while attempting to keep the number of faces presented relatively constant and to match behavioural performance where possible (performance in the WM task was higher across all conditions than in the other experiments and so these measures could not be matched, see Table 2). In all experiments, the stimulus array consisted of three squares, one at the top and two at the bottom, and the task format was two-alternative forced choice. In the control tasks, the same nonface stimulus appeared in all three positions of the array and participants alternated right- and left-hand button presses with each presentation of the stimulus. This control stimulus was a black and white nonsense image with similar complexity to the faces but containing no recognizable objects (obtained from a magnetic resonance image of the neck). During the matching tasks, the top face was the sample face and the participants indicated which of the two bottom faces was the same person as seen in the top photograph by pressing the right- or left-hand button. In the recognition condition for the EM experiment, the top square contained the control stimulus and the two bottom squares contained faces. The task was to indicate which face had been seen previously during study. During WM, participants initially saw a single face presented in the top square (with the two bottom squares filled with gray), followed by an array in which all three squares were filled with gray. The trial ended with two choice faces presented in the bottom squares, one of which was the same face as the sample seen at the beginning of the trial. During the DF task, a non-degraded face was seen in the top position and two degraded faces in the bottom positions, and the task was to indicate which of the bottom faces was the same as the top face. In both EM and WM experiments, each stimulus in all tasks was seen for 4 s with a 1-s interstimulus interval. In the DF experiment all tasks were self-paced. PET scans, with injections of 40 mci of H 2 15 O each and separated by 11 minutes, were performed on all participants using a GEMS PC B tomograph, which has a reconstructed resolution of 6.5 mm in both transverse and axial planes. This tomograph allows 15 planes, separated by 6.5 mm (centre to centre), to be acquired simultaneously. Emission data were corrected for attenuation by means of a transmission scan obtained at the same levels as the emission scans. Head movement during the scans was minimized with a thermoplastic mask that was molded to each person's head and attached to the scanner bed. Prior to each scan the instructions for the task to be carried out during that scan were read to the participant. Then the task was begun and 20 s later the isotope was injected. In all experiments the control task was presented during the first scan. For WM and DF, the order of scans (either delay or degradation condition) was counterbalanced across participants, whereas during EM, the recognition scans always occurred after the matching scans (which were interposed between encoding and recognition). Measures of regional cerebral blood flow (rcbf) were calculated using a rapid least squares algorithm (Carson et al., 1987). Data Analysis Accuracy of performance during the tasks (percent correct) and mean reaction times for correct responses (in ms) were analyzed using repeated-measures ANOVA with task as the repeated measure and age and experiment as independent factors. The meta-analysis of brain activity was carried out by entering the rcbf data from all experiments into a multivariate analysis (described below) to determine areas of change common across experiments. Prior to this analysis, each participant's PET scans were registered to the first scan to correct for small movements during the scanning session using AIR (Woods, Cherry, & Mazziotta, 1992). Images were then spatially normalized to the Talairach and Tournoux atlas coordinate system (Talairach & Tournoux, 1988), and smoothed using a 10-mm filter (to increase signal to noise and reduce the effects of individual differences in anatomy) using SPM95 (Frackowiak & Friston, 1994). Ratios of rcbf to global CBF within each scan for each participant were computed and analyzed using Partial Least Squares (for a more complete description of this tech-

4 Age-Related Differences in Face Processing 211 nique, see McIntosh, Bookstein, Haxby, & Grady, 1996). Partial Least Squares (PLS) is a multivariate analysis that identifies groups of brain regions distributed over the entire brain that together covary with some aspect of the experimental design, in contrast to the more typically used univariate analysis that assesses the significance of each region separately. The use of this method is based on the assumption that cognition is the result of the integrated activity of dynamic brain networks rather than the action of any region acting independently. PLS decomposes the covariance between brain voxels and a set of contrasts representing the experimental design to identify a new set of variables (so-called Latent Variables or LVs). Each LV identifies both the pattern of task differences across the experimental conditions and the brain voxels showing that pattern. Each brain voxel has a weight on each LV, known as a salience, which indicates how that voxel is related to the LV. These weights can be positive or negative, depending on whether the voxel shows a positive or negative relation with the pattern identified by the LV. To determine the reliability of the saliences for the brain voxels characterizing each pattern, all saliences in each analysis were submitted to a bootstrap estimation of the standard errors (Efron & Tibshirani, 1986; Sampson, Streissguth, Barr, & Bookstein, 1989). For the purposes of this analysis, a reliable voxel was defined as one whose salience was equal to or greater than 3.3 times the estimated standard error of that salience (p < 0.001; Sampson et al., 1989). Local maxima for the reliable brain areas on each LV were defined as the voxel with a ratio higher than any other voxel in a 2-cm cube centred on that voxel. Locations of these maxima are reported in terms of brain region, or gyrus, and estimated Brodmann area (BA) as defined in the Talairach and Tournoux atlas. To examine the brain areas where activity was modulated across the task conditions, two PLS analyses were carried out. The first analysis compared the control task and both face processing tasks across groups and experiments. This analysis was done to see whether the expected dominant pattern that distinguishing the face tasks from the nonface control task, was the same in both age groups. A second task analysis, which included only the two face processing tasks across experiments and groups, was carried out to isolate differences between these tasks, without the influence of the control task. PLS also was used to examine the relation between activity in all brain voxels during the memory and degraded perception tasks and response times on these tasks (accuracy measures could not be used for this analysis given the restricted range of values on the WM task). This type of analysis is similar to the task analysis except that it calculates the covariance between brain voxels and the behavioural measure, rather than between task contrasts and brain voxels. With this type of analysis, correlations between behaviour and brain activity are computed within each condition and then compared across conditions. This allows the identification of regions that are similarly correlated with behaviour as well as those areas that are differentially correlated across the different task conditions or between groups (Grady, Bernstein et al., 2002; Grady et al., 1998; Schreurs et al., 1997). For all three analyses, the pattern of activity identified by the first LV is reported here, as this LV accounts for the greatest amount of covariance (59% for analysis of face and control tasks; 30% for analysis of face tasks only; 27% for behavioural analysis). Results BEHAVIOUR Performance on the face processing tasks is shown in Table 2. The main effects of Experiment, Age, and Task on accuracy all were significant (experiment, F(2,61) = 50.5, p < 0.001; age, F(1,61) = 41.9, p < 0.001; task, F(1,61) = 231.2, p < 0.001). Thus, performance in WM was better than EM or DF (pairwise post hoc comparisons, p < for both contrasts), younger adults performed better overall than older adults, and both groups performed more accurately on the matching tasks than on the memory or degraded perception tasks. The interaction of Task and Age also was significant, F(1,61) = 6.9, p = 0.011, as was the three-way interaction of Experiment, Age and Task, F(2,61) = 4.08, p = Separate ANOVAs on each experiment showed that the Task x Age interaction was significant for EM, F(1,18) = 7.1, p < 0.05, and DF, F(1,17) = 5.3, p < 0.05, but not WM, F < 1, such that older adults had a larger difference in performance between the two tasks in the former two experiments but not in the latter. In terms of RT, the main effects of Task, F = 45.8 (1,60), p < and Experiment, F = 28.8 (2,60), p < were significant, but not the effect of Age, F < 1. The effect of Experiment was due to longer RTs in the DF experiment compared to both EM and WM (pairwise post hoc comparisons, p < for both contrasts). RT was shorter for the matching tasks compared to the other conditions except in the WM experiment (Task x Experiment interaction, F(2,60) = 28.4, p < 0.001). The interaction of Task and Age also was marginally significant, F = 4.2 (1,60), p = but the three way interaction was not reliable. The Age x Task interaction was due to the fact that the difference in RT between the matching and the memory or degraded perception tasks was smaller in the older adults than in the younger adults (270 ms on average for older adults vs. 617 ms in younger adults).

5 212 Grady TABLE 2 Performance on the Face Processing Tasks Accuracy Reaction Time Task Young Old Young Old Matching 98 ± 2 95 ± 3 1,702 ± 650 1,908 ± 363 Recognition 79 ± 8 67 ± 9 2,105 ± 634 2,276 ± 393 Matching 99 ± 2 96 ± 5 1,478 ± 393 1,851 ± 459 Delayed Match-to-Sample 97 ± 4 96 ± 4 1,493 ± 313 1,637 ± 340 Matching 99 ± 1 90 ± 4 2,503 ± 797 2,681 ± 824 Degraded Matching (50%) 86 ± 8 69 ± 11 4,137 ± ,622 ± 1662 Values are mean ± s.d. Accuracy measures are percent correct and Reaction Times are in ms. TABLE 3 Brain Areas With Differential Activity in the Control and Face Processing Tasks in Both Young and Old Adults Region, Gyrus Hem BA X Y Z Ratio Face > Control 1 Prefrontal (GOb) L Prefrontal (GFi) R Prefrontal (GFm) L Prefrontal (GFm) L Premotor (GPrC) R Occipital (GF) R Occipital (GF) R Occipital (GF) L Control > Face 2 Prefrontal (GFd) L Premotor (GPrC) R Cingulate R Cingulate R Temporal (GTs) R Temporal (GTs) R Temporal (GTs) L Temporal (GTs) L Parietal (LPi) R Red and yellow brain areas in Fig Blue areas in Fig. 1. Coordinates and estimated Brodmann s areas of all maxima are taken from the atlas (Talairach & Tournoux, 1988). X (right/left): Negative values are in the Left Hemisphere; Y (anterior/posterior): Negative values are Posterior to the zero point (located at the anterior commissure); Z (superior/inferior): Negative values are Inferior to the plane defined by the anterior and posterior commissures; Ratio = ratio of salience/s.e. from the bootstrap. Abbreviations: Hem = hemisphere; R = right; L = left; BA = Brodmann s area; GF = fusiform gyrus; GF(i,m,d) = frontal gyrus (inferior, middle, medial); GL = lingual gyrus; GOb = orbitofrontal gyrus; GPrC = precentral gyrus; GTs = superior temporal gyrus; LPi = inferior parietal. BRAIN ACTIVITY CHANGES DUE TO TASK As expected, the first LV in the comparison of the control and face processing tasks identified a set of regions where activity differentiated all face processing tasks from all of the nonface control tasks across experiments and groups (Figure 1, Table 3). Brain regions with increased activity during face processing included bilateral fusiform gyri and bilateral inferior and middle frontal regions. Conversely, areas with greater activity during the control task, compared to face processing, were seen bilaterally in perisylvian regions (i.e., superior temporal and inferior parietal cortices), in medial prefrontal cortex, and the cingulate gyrus. The first LV in the analysis comparing the two face processing tasks across experiments identified a contrasting set of anterior and posterior regions (Figure 2, Table 4). In young adults, widespread bilateral prefrontal regions and smaller areas of right temporal and extrastriate cortex showed increased activity during the two memory tasks, whereas activity was increased in

6 Age-Related Differences in Face Processing 213 Figure 1. The brain areas with differential activity during the face processing and control tasks (reliability ratio > 3.0) are shown on the left of the figure plotted on a standard structural MRI. In this and subsequent figures, the brain slices begin at 28 mm relative to the anterior commissure-posterior commissure line (AC-PC line; top left image) and end at +28 mm (bottom right image) with a 4-mm slice separation. The graph on the right shows the LV scores for young and old adults for each task condition. Positive scores for a condition indicate that activity was increased in the brain regions shown in red and yellow (i.e., those with positive salience on the LV). Negative scores for a condition indicate that activity was increased in the brain regions shown in blue (those with negative salience on the LV). See Table 3 for local maxima of these regions. Abbreviations: EM = episodic memory; WM = working memory; DF = degraded faces; task 1 = face matching; task 2 = memory or degraded perception. Figure 2. On the left of the figure, the brain areas with differential activity during the two face processing tasks are shown on a standard MRI (brain areas with a reliability ratio 2.5). The graph on the right shows the LV scores for young and old adults for each task condition. Positive scores for a condition indicate that activity was increased in the brain regions shown in red and yellow (i.e., those with positive salience on the LV). Negative scores for a condition indicate that activity was increased in the brain regions shown in blue (those with negative salience on the LV). See Table 4 for local maxima of these regions. Abbreviations are the same as in Figure 1. Figure 3. On the left of the figure are the brain areas where activity was correlated with RT during the face memory and degraded tasks. Areas are shown on a standard MRI (brain areas with a reliability ratio > 2.5). The graph on the right shows the LV scores for young adults (black bars) and old adults (gray bars) for each task condition. If the scores are positive for a condition, it indicates that RT was positively correlated with activity in the brain regions shown in yellow and red, and negatively correlated with activity in the blue regions. If the scores are negative for a condition, it indicates that RT was positively correlated with activity in the brain regions shown in blue and negatively correlated with activity in the red regions. See Table 5 for local maxima of these regions. Abbreviations are the same as in Figure 1.

7 214 Grady TABLE 4 Brain Areas With Differential Activity in the Two Face Processing Tasks Region, Gyrus Hem BA X Y Z Ratio Positive LV weights 1 Prefrontal (GFi) R Prefrontal (GFi) L Prefrontal (GFi) L 44/ Prefrontal (GFm) R Prefrontal (GFm) R Prefrontal (GFd) R Cingulate M Temporal (GTi) R Temporal (GTs) R Occipital (GOi) R Thalamus R Negative LV weights 2 Temporal (GTi) R Temporal (GTi) L Temporal (GTi) L Hippocampus L Occipital (GF) R Occipital (GF) L Occipital (Cu) M Parietal (LPi) L Red and yellow brain areas in Fig Blue areas in Fig. 2. M = midline; Cu = cuneus; GOi = inferior occipital gyrus; GTi = inferior temporal gyrus. Other abbreviations can be found in Table 3. the fusiform and inferior temporal gyri, medial occipital regions, and left hippocampus during the matching tasks. This pattern of activity did not characterize the DF experiment in young adults (as indicated by the LV scores near zero for the two conditions from this experiment; see Figure 2). In contrast, this pattern differentiated the perceptual matching tasks from both the memory and the degraded tasks in old adults. That is, older adults had increased prefrontal activity during the more difficult task and increased activity in temporal and occipital regions in the perceptual task across all three experiments (Figure 2). CORRELATIONS BETWEEN BRAIN AND BEHAVIOUR The LV that accounted for the most covariance in the brain and behaviour analysis identified a common set of correlations across the EM, WM, and DF tasks in the young adults that also characterized the degraded faces task in the old adults (Figure 3, Table 5). This pattern was associated with positive correlations between RT and activity in the right lingual and superior temporal gyri and the left parahippocampal gyrus, and negative correlations between RT and activity in left prefrontal and bilateral temporal and occipital regions. That is, increasing activity in prefrontal cortex was found in those participants who were faster to respond, whereas increased activity in sensory cortices was associated with slower responding. In contrast, the older adults showed the opposite pattern on the two memory tasks, such that increased prefrontal activity on these tasks was positively correlated with behaviour and thus was associated with slower RTs but increased activity in sensory areas, and the parahippocampal gyrus was associated with faster responses. Since it appeared that similar prefrontal regions were identified by both the task and behaviour analyses, this was confirmed by calculating the overlap of the bootstrap images seen in Figures 2 and 3 by multiplying them (Grady, McIntosh, Beig, & Craik, 2001; Nyberg et al., 2000). This identified two regions in prefrontal cortex, one in the left middle frontal gyrus (BA 46, X: -36, Y: 42, Z: 12) and one in the right medial frontal gyrus (BA 10, X: 18, Y: 52, Z: 0). Both of these regions had positive weights on the task LV, indicating increased activity during the memory tasks in young adults and during the memory and degraded perception task in old adults. In addition, these regions showed positive weights on the behavioural LV, indicating that activity in these areas was differentially correlated with performance in EM and WM, being negatively correlated with RT in young and positively correlated in old adults. Discussion Data from three face processing experiments, each containing similar face matching tasks and a task tapping either memory or perception of degraded stimuli, were compared in this analysis. Performance on the face

8 Age-Related Differences in Face Processing 215 TABLE 5 Brain Areas Where Activity is Correlated With Reaction Time Region, Gyrus Hem BA X Y Z Ratio Positive LV weights 1 Prefrontal (GFi) L Prefrontal (GFm) L Prefrontal (GFd) R Prefrontal (GFd) L Temporal (GTm) L Temporal (GTs) R Occipital (GF) R Occipital (GOm) R Occipital (GOm) L Thalamus L Negative LV weights 2 Occipital (GL) R Temporal (GH) L Temporal (GTs) R Red and yellow brain areas in Fig Blue areas in Fig. 3. GH = parahippocampal gyrus; GOm = middle occipital gyrus; GTm = middle temporal gyrus. Other abbreviations can be found in Table 3. matching tasks was near ceiling in all three experiments, whereas the episodic memory and degraded perception tasks were more difficult, as indicated by increased RT and decreased accuracy. Older adults showed lower performance overall and larger effects of task difficulty on accuracy of performance, except during the WM experiment in which there was little difference between tasks in either group. The behavioural results are thus consistent with earlier work showing age-related differences in face perception and memory, with larger differences seen during episodic memory or difficult perceptual tasks than during easier perceptual tasks. It was surprising perhaps that RTs were not slower overall in the older group, given that this is commonly found in other types of tasks (e.g., Cerella, 1985). In addition, the difference in RT between the tasks was actually smaller in old adults compared to young adults. Both of these effects may have been due to the strict health criteria that were used in screening the participants in these studies. The brain activity pattern characterizing face processing per se, compared to the nonface control task, was the same across all experiments and showed no differences between young and old adults. Activity during face processing was found in the fusiform gyrus bilaterally, as would be expected from previous work (e.g., Haxby et al., 1994; Kanwisher et al., 1997). Activation also was seen in the frontal lobes, in both hemispheres, which has not been emphasized as a face-processing region in the literature. However, left prefrontal cortex, particularly the inferior portions, is found during both incidental and intentional encoding of faces (Bernstein et al., 2002; Haxby et al., 1996), which probably accounts for its increased activity in these experiments. Right prefrontal activity has been noted during face perception (Haxby et al., 1994) and recognition (Bernstein et al., 2002; Haxby et al., 1996) and occasionally during encoding (Kelley et al., 1998) all of which are conceivably involved in these tasks. The areas of reduced activity during face matching, or increased activity during the nonface control task, which included medial prefrontal and perisylvian regions, also have been previously reported. Reductions in perisylvian regions may reflect reduced activity associated with nonattended sensory regions outside the visual system (i.e., auditory and language areas; Haxby et al., 1994). Reductions in medial prefrontal regions have recently been attributed to differences between a focus on internal states, more likely during low-level baseline states, and a focus on external stimuli necessary during externally driven task conditions (Gusnard, Akbudak, Shulman, & Raichle, 2001). The finding of the same pattern of activity across the three experiments highlights the robust nature of the pattern for basic face processing regardless of other task requirements and supports the earlier conclusion (Grady et al., 1994) that the brain mechanisms for face perception are largely unchanged with age. The second task analysis that compared brain activity on the face processing tasks identified a pattern of activity that characterized both young and old adults in the memory experiments. Bilateral prefrontal and right posterior temporal regions were more active during the memory tasks and occipital regions, including the posterior fusiform bilaterally, and the hippocampus were more active during the perceptual tasks. This pattern is

9 216 Grady consistent with prefrontal activation during both encoding and retrieval and temporoparietal activation reported during retrieval (for a review see Cabeza & Nyberg, 2000). The hippocampal activity noted during the perceptual tasks is of interest given its presumed role in memory formation and retrieval (e.g., Cipolotti et al., 2001; Eichenbaum, Otto, & Cohen, 1992; Nadel & Moscovitch, 1997; Squire, 1992). The activation seen here during face matching could be due to the novelty of the faces in these conditions (Tulving, Markowitsch, Kapur, Habib, & Houle, 1994) and is consistent with the idea that hippocampal activity is more prominent during encoding of complex visual information than during recognition (Haxby et al., 1996; Stern et al., 1996). Importantly, prefrontal activity also was increased in older adults, but not younger adults, during the more difficult degraded perceptual task compared to the nondegraded task. This finding is consistent with other evidence that older adults utilize prefrontal cortex under task conditions not requiring or eliciting this activity in younger adults. For example, older adults have more bilateral prefrontal activity during nonface memory retrieval tasks on which younger adults have mainly or exclusively unilateral prefrontal activity (Backman et al., 1997; Cabeza, 2002; Cabeza et al., 1997; Madden et al., 1999; Reuter-Lorenz et al., 2000). In addition, increased left dorsolateral prefrontal activity was noted in older adults for both WM and DF experiments in the initial analyses of these experiments (Grady et al., 1998; Grady et al., 2000). The new information provided by this meta-analysis is that older adults recruit the same regions of ventral and mid-dorsolateral prefrontal cortex for both face memory and for nonmemory tasks that are difficult. This is consistent with reports of increasing prefrontal activity with increasing task load in young adults (Barch et al., 1997; Braver et al., 1997), and strongly suggests that this response is a general one to increased cognitive effort or need for resources that occurs in older adults at lower levels of load than in young adults. This result also is consistent with the notion of dedifferentiation in older adults (Lindenberger & Baltes, 1994, 1997). This hypothesis has been suggested to explain the finding that a variety of processes, both sensory and cognitive, become more highly correlated and thus less differentiated with age. Although the brain mechanism for such a dedifferentiation is unknown, one possible mechanism could be the increased recruitment of prefrontal cortex in older adults. That is, if more tasks are accompanied by activity in prefrontal cortex then performance on these tasks becomes dependent to some extent on these prefrontal regions and the amount of covariance across these tasks would be increased. The analysis of performance and brain activity showed that increased activity in left prefrontal cortex and bilateral occipitotemporal regions was differentially correlated with RT in young and old adults, but only during the memory experiments. Activity in these areas was negatively correlated with RT in young adults during EM and WM, indicating that an increase was associated with faster responding. Conversely, the correlations were positive in old adults so that increased prefrontal and occipitotemporal activity was associated with slower responding in the memory experiments. Interestingly, this difference in how brain activity was related to RT occurred despite the fact that there was no significant difference in RT between groups. In addition, the left prefrontal areas with different correlations were a subset of the areas that showed increased activity in older adults across all of the more difficult tasks, and thus had age-related task differences as well as correlational differences. This is similar to what we reported previously for WM (Grady et al., 1998), and extends this dissociation to episodic memory as well, indicating that this effect may be specific to memory. This difference in correlation pattern in old adults across the experiments also was distinct from the task effect, in which older adults showed the same pattern across all experiments. The task and behaviour analyses taken together suggest that although young adults show task-specific modulation of brain activity, the brain areas that are associated with rapid performance of these tasks is remarkably similar across experiments and samples of young adults. In contrast, older adults are more variable in how brain activity is expressed in behavioural outcome despite the similarity of brain activity across experiments. Another important aspect of this result is that it shows that using the same network of brain regions can have different consequences for behavioural performance depending on the age of the participants. This complements earlier findings that individuals at different ages can use entirely different networks to facilitate task performance (McIntosh et al., 1999). It also should be noted that the finding presented here of negative correlations between RT and prefrontal activity in the young group and positive correlations in old adults is the opposite of what Rypma and D'Esposito (2000) reported in subjects performing a verbal WM task. Given the many methodological differences between their experiment and the ones described here, it is not possible to ascertain precisely why the results should be different. However, the discrepancy does illustrate how complex the effects of age on brain activity and cognition can be. In conclusion, this meta-analysis has shown that prefrontal activity in young adults during face processing tasks is specific to the type of task, whereas in older adults it appears to be associated with more demand-

10 Age-Related Differences in Face Processing 217 ing tasks, regardless of the specific task requirements. In addition, regions in left prefrontal cortex that differentiate young and old on these task effects also differentiate the groups in terms of the association this activity shows with memory task performance. This provides converging evidence, along with other functional neuroimaging studies, that prefrontal regions, particularly in the left hemisphere, are critically involved in mediating age-related differences in cognitive function. This work was supported in part by the Canadian Institutes of Health Research and the Intramural Research Program of the National Institute on Aging (USA). I would like to thank Dr. Reza Habib for programming assistance and my coauthors on the original papers describing the face processing experiments, in particular Drs. James Haxby, Barry Horwitz, and Randy McIntosh. References Andreasen, N. C., O'Leary, D. 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