• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Cogn Neurosci. Author manuscript; available in PMC Oct 1, 2009.
Published in final edited form as:
PMCID: PMC2730979
NIHMSID: NIHMS73153

Neural signatures of semantic and phonemic fluency in young and old adults

Abstract

As we age, our ability to select and produce words changes, yet we know little about the underlying neural substrate of word-finding difficulties in old adults. The present study was designed to elucidate changes in specific frontally mediated retrieval processes involved in word-finding difficulties associated with advanced age. We implemented two overt verbal (semantic and phonemic) fluency tasks during functional magnetic resonance imaging and compared brain activity patterns of old and young adults. Performance during the phonemic task was comparable for both age-groups and mirrored by strongly left lateralized (frontal) activity patterns. On the other hand, a significant drop of performance during the semantic task in the older goup was accompanied by additional right (inferior and middle) frontal activity, which was negatively correlated with performance. Moreover, the younger group recruited different subportions of the left inferior frontal gyrus for both fluency tasks, while the older participants failed to show this distinction. Thus, functional integrity and efficient recruitment of left frontal language areas seems to be critical for successful word-retrieval in old age.

Keywords: aging, functional magnetic resonance imaging, higher level cognition, neuropsychology, prefrontal cortex

Introduction

A growing segment of the population is entering old age and likely to suffer some degree of age-related cognitive decline (ARCD), including the most severe cases of dementias such as Alzheimer's disease. Recently considerable attention has been devoted to elucidate the underlying neural substrates of ARCD. Still, research concerning cognitive decline in normal and pathological aging has mainly focused on memory, cognition and perception (Cabeza, Anderson, Locantore, & McIntosh, 2002). On the other hand, age related changes in language functions and their underlying neuronal causes have widely been neglected even though word-retrieval difficulties are frequently observed in old-age (Burke & Shafto, 2008) and are among the earliest signs of pathological aging (e.g., Henry, Crawford, & Phillips, 2004). In particular, while certain aspects of language, like semantic knowledge, increases across the lifespan with little decline even in very old age (Burke & Shafto, 2008; Verhaeghen, 2003), others have been found to be heavily affected by aging. For example, access to and integration of information at multiple levels during real time language processing seems to be affected, especially when processing resources are taxed (e.g., by increased cognitive load) and older adults may be less able to inhibit competing or irrelevant information. Even during non-challenging language comprehension tasks where older and younger adults perform similarly, changes in brain activity patterns have recently been confirmed (for review see Federmeier, 2007). Moreover, during language production tasks the retrieval of lexical-semantic knowledge from memory stores may be impaired (Ivnik, Malek, Smith, Tangolos, & Petersen, 1996), and errors accessing phonological word forms, like tip-of-the tongue phenomena, occur more frequently in old than in young persons (Shafto, Burke, Stamatakis, Tam, & Tyler, 2007). These findings may point to a specific compromise of executive language functions.

Such a conclusion is in line with current theories of cognitive aging that focus on the frontal and medial temporal lobes as a major source of age related disruptions in cognitive performance (Craik & Bialystok, 2006; Raz, Gunning-Dixon, Head, Rodrigue, Williamson, & Acker, 2004; West, 1996). For example, recent research in animals and humans revealed subtle region-specific alterations in dendritic morphology, cellular connectivity, gene expression and other factors that affect plasticity and ultimately alter the network dynamics of neuronal ensembles that support cognition (Burke & Barnes, 2006). Moreover, functional imaging studies of aging have consistently confirmed that older adults tend to recruit regions in the contralateral non-task dominant (prefrontal) cortex when performing various cognitive tasks (e.g. episodic memory, semantic memory retrieval, working memory, perception and inhibitory control). This has been described as hemispheric asymmetry reduction in older adults (HAROLD, Cabeza et al., 2002). The functional relevance of this reduced asymmetry for cognition in old age has been controversial: For example, a beneficial role has been suggested by studies that found additional (bilateral) activity in high but not in low performing old adults during a variety of cognitive tasks (Cabeza et al., 2002; Daselaar, Veltman, Rombouts, Raaijmakers, & Jonker, 2003; Davis, Dennis, Daselaar, Fleck, & Cabeza, 2008; Reuter-Lorenz, 2002; Reuter-Lorenz, Jonides, Smith, Hartley, Miller, Marshuetz, & Koeppe, 2000; Rosen, Prull, O'Hara, Race, Desmond, Glover, Yesavage, & Gabrieli, 2002). Still, others have suggested that the more bilateral activity pattern observed in older individuals may only reflect increased task demands in older adults as young adults tend to recruit the non task-dominant hemisphere more when difficulty levels are raised (e.g., Braver, Barch, Kelley, Buckner, Cohen, Miezin, Snyder, Ollinger, Akbudak, Conturo, & Petersen, 2001; Grady, McIntosh, Bookstein, Horwitz, Rapoport, & Haxby, 1998), inefficient recruitment of specialized brain regions in the dominant hemisphere, disinhibition of nonspecialized networks, or dedifferentiation of function (Li & Lindenberger, 1999; Rajah & D'Esposito, 2005).

So far, little is known about word retrieval difficulties in healthy old adults and only one study has directly compared the neural substrates of word-retrieval in healthy younger and older adults during an overt picture naming task (Wierenga, Benjamin, Gopinath, Perlstein, Leonard, Rothi, Conway, Cato, Briggs, & Crosson, 2008). While naming accuracy was comparable between younger and older participants (age range 68-84 years) on average, fMRI in the old participants revealed a larger frontal network during word-retrieval not only in left-hemisphere areas but also less lateralization compared to younger adults as evident by increased right frontal activation (homologue of Broca's area, BA45; anterior inferior frontal gyrus, IFG; anterior cingulate). Notably, frontal brain regions that showed a correlation with performance in older adults were not similar compared to the group of younger adults with one exception: in young adults and low performing old adults activity in the right IFG was negatively correlated with performance. Moreover, the older group scored significantly worse in tests that placed demands on executive language functions as assessed outside of the scanner (i.e., selection, retrieval and manipulation of semantic information). In sum, even though naming performance in (healthy) older adults activated a larger bilateral frontal network, including additional right inferior frontal areas not activated by younger participants, this activation pattern was not beneficial for performance in all of the participants. Taking into account the above mentioned results, further research is needed to elucidate the specific frontally mediated retrieval processes involved in word finding difficulties in older adults.

Hence, in the present study we used functional magnetic resonance imaging (fMRI) and two different overt verbal fluency paradigms to investigate frontally mediated language functions in healthy young and old participants. In particular, we assessed brain activity patterns during semantic (category based) and phonemic (letter based) fluency tasks. Several previous functional imaging studies have demonstrated that both tasks draw heavily on frontally mediated processes and mainly activate dorsolateral frontal cortices. Activity patterns have been found to be strongly left lateralized in younger participants, and it has been suggested that different subportions in the left inferior frontal gyrus (IFG) are differentially activated during both tasks (i.e., more dorsal peak of activity for phonemic fluency, for a recent review of functional imaging during verbal fluency tasks see Costafreda, Fu, Lee, Everitt, Brammer, & David, 2006). Moreover, semantic fluency has been shown to be affected by age more strongly than phonemic fluency (e.g., Brickman, Paul, Cohen, Williams, MacGregor, Jefferson, Tate, Gunstad, & Gordon, 2005), replicating findings in Mild Cognitive Impairment (MCI, Murphy, Rich, & Troyer, 2006) and in AD (Monsch, Bondi, Butters, Salmon, Katzman, & Thal, 1992), even though in pathological aging this pattern is relatively more pronounced. Therefore, both tasks are well suited to compare neural activity in young and old participants to assess (a) potentially different patterns of activity either in left or right frontal regions, (b) the impact of different performance levels on brain activity, and (c) the differential contribution of different subportions of the IFG in each group. Moreover, by implementing an overt language design we were able to relate the respective differential activity pattern to the actual behavioural performance during scanning.

Methods

Participants

Sixteen healthy older participants [mean age 69.3 ± 5.6 years, range 64-88 years; 8 females] were recruited for the study. Another 16 younger participants [mean age 26.1 ± 3.7, range 20-33] served as a control group and was matched to the older participants for gender and education (years of education: old group 13.3 ± 3.0, range 8-19 years, young group: 14.8 ± 2.6, range 10-19; F(1,30)=2.4, p= .12). All participants were native speakers of the German language. Written informed consent was obtained from the participants prior to the fMRI scanning, participants were briefed on scanner security and paid a compensation of 20 Euros for participation. The ethics committee of the University of Konstanz had approved the study protocol and the study was conducted in accordance with the Helsinki Declaration.

Psychometric assessment

Dementia screening

Prior to the fMRI session, each old subject completed a standard health questionnaire to exclude any previous or current neurological or psychiatric condition, the Mini-Mental Status Exam (MMSE, Folstein, Folstein, & McHugh, 1975) and the neuropsychological test battery established by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-Plus, www.memoryclinic.ch). The CERAD-Plus is a well established screening tool that comes along with an online database including age- and gender-adjusted norms (z-scores) to differentiate normal aging from dementia and its precursors (i.e., amnestic Mild Cognitive Impairment, aMCI, Petersen, 2004). The CERAD is comprised of several subtests to assess semantic (animals) and phonemic fluency (words beginning with S), naming (short version of the Boston Naming Test, BNT), constructional praxis, verbal memory (three immediate recall trials of a 10 word list, delayed recall and discrimination) and executive functioning (Trail Making Test A/B). In particular, the word list test has been shown to be sensitive to MCI (c.f. Shankle, Romney, Hara, Fortier, Dick, Chen, Chan, & Sun, 2005). Even though the CERAD does not provide norms for younger participants, the younger group completed the test to assure similar testing conditions.

Additionally, all participants were screened for depression by using the Beck Depression Inventory (Beck, Steer, & Garbin, 1988) and found to score within normal ranges. None of the old participants reported subjective memory complaints in everyday life or had an MMSE score below 27 (mean 29.1. ± 1.8). All participants scored within ± 1.5 standard deviations (SD) of the mean for the CERAD normative sample in all subtests. In particular, none was more than 1 SD below age norms in the word list test. Average scores for all CERAD subtests are provided in Table 1.

Table 1
Results of the young and old group in the CERAD test battery (raw scores)

Additional neuropsychological language tests

To assess executive language functions outside of the scanner, old and young participants completed the Regensburger verbal fluency test (RWT, Aschenbrenner, Tucha, & Lange, 2000). The RWT comprises semantic and phonemic fluency trials. Two 1-minute trials of semantic fluency (food, surnames) and phonemic fluency (letters M, B) were administered. Two additional language tests were completed prior to scanning to assess semantic processing (synonym test of the synonym-antonym-selection-classification test, SASKA, Riegel, 1967) and a standardized German vocabulary test (Wortschatztest, WST, Schmidt & Metzler, 1992).

Functional Magnetic Resonance Imaging (fMRI)

Experimental task and stimulus characteristics

We implemented an overt verbal fluency task and participants were instructed that they would see different categories and initial letters at the centre of a video screen. The participants' task was to generate different exemplars of the respective category (semantic fluency) or words beginning with a particular letter (phonemic fluency). During the phonemic fluency task, production of words from all word classes were allowed (with the exception of names, brandnames and repeated use of composita that share the same stem; e.g., tennis-court, tennis-player).

The functional MRI tasks consisted of two blocked conditions of category or phonemic generation, which alternated with a control condition [reading the German word “Pause” (engl. “rest”) aloud]. A complex baseline condition was chosen to control for activity associated with (a) basic visual processing, (b) articulation and, (c) hearing of the subject's own voice. Each category/letter or rest-condition was preceded by a speech bubble (5.5 seconds) introducing the respective condition, afterwards the first category/initial letter or the word “Pause” was displayed.

The same four different categories and initial letters were used for all participants with order of presentation randomized across subjects. For half of the participants the stimulation started with category fluency condition, for the other half with a letter fluency trial. Categories were selected to comprise a large range of category exemplars (sports/fruits/body parts/musical instruments) according to a German norming study (Mannhaupt, 1983). Initial letters (H, F, N, A) were chosen because of the large number of legal German words beginning with these letters according to the Simplex Celex Database [http://iona.sprachwiss.uni-konstanz.de/simplex.html].

A total of 4 blocks for each condition were collected (i.e., 40 trials for category and phonemic fluency). Both experimental conditions (category and phonemic fluency) were presented in blocks of 10 consecutive trials (block duration 55 seconds, the same category/letter was repeated 10 times within each block). The baseline blocks (5 consecutive trials) were interspersed between category and letter fluency trials (block length 27.5 seconds, 8 blocks), therefore, resulting in a balanced number of trials for each fluency condition and the baseline condition.

fMRI-setup and acquisition parameters

The fMRI paradigm employed a temporal sparse-sampling design (Hall, Haggard, Akeroyd, Palmer, Summerfield, Elliott, Gurney, & Bowtell, 1999), in which the overt verbal response is assessed in the scanner during an off-phase, and the hemodynamic response is acquired after a short time delay; thereby movement artifacts due to the articulation process are avoided. Scanning was conducted using a 1.5 Tesla Philips Intera MR-System equipped with Power Gradients. For functional scanning, a T2*-weighted Fast-Field Echo, Echo-Planer-Imaging (FFE-EPI) sequence utilizing a parallel scanning technique (SENSE, Pruessmann, Weiger, Scheidegger, & Boesiger, 1999, SENSE factor 2) was used. Stimuli were presented by a visor (VisuaStim, Resonance Technology, Inc.) for 3 seconds, overt responding was required during this interval. After a delay of 0.27 seconds a whole-brain functional MR volume was acquired (temporal sparse sampling). Functional MR was performed with the following acquisition parameters: Repetition time TR=5.5 sec.; acquisition time TA=2.23 sec.; TE=40 msec.; 34 transversal slices, slice-thickness: 3 mm; in-plane resolution: 3×3 mm; interslice gap: 0.5 mm; Field of View=192, acquisition matrix 64×64. A total of 120 functional whole brain volumes were acquired, and the entire experiment had a duration of 12.5 minutes. Verbal responses were transmitted from the scanner to a microphone and transcribed. Prior to the first scan, a training session outside of the scanner was performed to familiarize the participants with the experimental design. A different set of categories and letters was used for this training session.

Functional MRI pre-processing

Functional MRI post-processing was performed using Statistical Parametric Mapping (SPM5, Wellcome Department of Cognitive Neurology, London, UK). Preprocessing included correction for slice-time differences and spatial alignment to the first volume in the image series to adjust for head movements during the course of the experiment. Afterwards, functional volumes were normalized to MNI standard stereotactic space and smoothed with a Gaussian Kernel of 9×9×11 mm full-width-at-half-maximum (FWHM). Data was modeled using a finite impulse response function (Gaab, Gabrieli, & Glover, 2007).

After preprocessing, the data was submitted to statistical analysis implementing the General linear Model (GLM). The corresponding design matrix was comprised by the 3 covariates-of-interest representing the experimental conditions' onsets as well as covariates-of-no-interest (the six movement parameters obtained during realignment). The covariates-of-no-interest were included to improve overall model fit to the empirical data and to reduce residual error variance. Before estimating the modeled regressors, a high-pass filter with a cut-off period of 128 sec. was applied to the data. Following estimation of the overall model, planned contrasts-of-interest were calculated for each subject. These included separate comparisons of category and phonemic fluency runs with the baseline condition for both age groups. Additional contrasts included the direct comparison of (a) category and phonemic fluency trials between the two age groups and (b) the within group comparison of activity patterns associated with category and phonemic fluency trials.

For the group analysis a random effect model was calculated that included the above mentioned contrasts of all participants for each age group. Maximally activated voxels within significant clusters for the comparison of both fluency conditions with the baseline are reported at a voxel threshold of p<.01 FDR-corrected (false discovery rate, Genovese, Lazar, & Nichols, 2002) and a cluster extent of k≥20 voxels. Comparison of activity patterns within each age group (category vs. phonemic fluency) and between groups (category/phonemic fluency old vs. young) are thresholded with p< .05 FDR-corrected, k≥10. Anatomic localization of significant voxels within clusters was conducted using the Talairach Daemon software (Lancaster, Woldorff, Parsons, Liotti, Freitas, Rainey, Kochunov, Nickerson, Mikiten, & Fox, 2000) with the nearest grey matter option enabled. For presentation of the results the data is superimposed on a standard brain template (Montreal Brain).

To explore the functional relevance of increased activity in brain regions that were more strongly activated by old than young adults, a region-of-interest (ROI) analysis was performed that correlated the averaged z-transformed activity in differentially activated clusters with the individual behavioral performance in the scanner. [Note: younger participants did not evidence increased activity compared to the older participants in both fluency tasks, see results]. Due to the limited behavioral variance during both word generation tasks a correlation analysis between activity patterns and performance was not feasible in the younger participants.

Results

Behavioral language testing

Participants of the young group outperformed the old group during both semantic fluency trials outside of the scanner (sum of words produced during the two one minute trials; young: 59.1 ± 9.9, old: 46.1 ± 6.7; F(1,30)=18.6, p= .0002; same scores expressed as a function of the maximum number of correct responses attained (N/73): young: 0.40 ± 07, old: 0.31 ± 0.04), while performance in the two phonemic trials was comparable in both groups (young: 22.6 ± 6.1 old: 29.8 ± 7.0; F(1,30)=1.7, p= .2; (N/73): young: 0.22 ± 0.04, old: 0.20 ± 0.04). Even though both groups generated significantly more words during the semantic compared to the phonemic fluency task (young: F(1,30)=83.4, p< .0001; old: F(1,30)=45.5, p< .0001), this difference was more pronounced in the younger participants (Interaction Group × Condition: F(1,30)=6.1, p= .02). Comparison of the old subjects with their respective norm group (age-corrected z-scores are provided for the RWT) revealed that they performed within the 78-94th percentile for all subtests, i.e., 1.0-1.7 z-scores above age-norms. The younger subjects scored between the 56-78th percentile of their age group, 0.2-1.1 z-scores. Therefore, even though absolute performance levels of the old group were lower compared to the young participants in the semantic task, the old participants were indeed rather high functioning for their age [Note: at least with respect to age-corrected scores the older participants performed better than the younger participants. Therefore, differences between the two groups during functional imaging (see below) might even have been more pronounced if the subjects had been more closely matched with regard to age-corrected scores]. No differences were found in the synonym and vocabulary tasks [synonym test (SASKA) young: 48.1 ± 3.8 old: 50.7 ± 6.4, p= .2; vocabulary (WST) young: 35.8 ± 1.3 old: 34.9 ± 4.9, p= .5].

Functional magnetic resonance imaging

Fluency scores in the scanner

During scanning, the younger participants generated significantly more words during the semantic fluency task than the old participants (see Figure 1, scores expressed as a function of the maximum number of correct responses (N/40): young: 0.96 ± 0.02, old: 0.88 ± 0.03; F(1,30)=9.1, p= .005), while no differences were found during the phonemic fluency task (N/40: young: 0.92 ± 0.07, old: 0.89 ± 0.07; F(1,30)=1.3, p= .3). Only the younger participants generated more exemplars during the semantic fluency task than in the phonemic task (young F(1,30)=4.3, p= .04, old (F(1,30)=0.2, p= .6). For the performance obtained in the scanner, the Group × Condition interaction only approached significance (F(1,30)=3.6, p= .069).

Figure 1
Number of correct responses during the semantic and phonemic fluency task for young and old subjects as obtained in the scanner (maximum score 40).

Activity patterns (young group)

Figure 2 shows the activity pattern elicited during semantic and phonemic fluency trials for the younger participants. Notably, for both fluency tasks, activity was strongly left lateralized.

Figure 2
Shows the activity pattern elicited during the semantic and phonemic fluency tasks during fMRI for young and old participants compared to the baseline condition (p< .01 FDR-corrected; k≥20). Right column=left hemisphere, left column=right ...

When comparing the semantic fluency task with the complex baseline in the younger group, peak activity was centered at the junction of the left anterior superior temporal gyrus (STG, BA 22) and the inferior frontal gyrus (IFG, BA 9). Additional activity was found in the left cuneate gyrus (BA 17) and in the medial and middle frontal gyri (BA 6). Activity in the right hemisphere was confined to the caudate nucleus. In general, a very similar pattern of activity was observed during the phonemic fluency task, even though a larger network of brain regions appeared to be activated and peak activity in several regions was more pronounced. In particular, a large anterior cluster was activated in the left hemisphere that included the left STG and IFG (BAs 22/9) and also encompassed pars triangularis (BA 45). Additionally, the superior frontal gyrus (SFG, BA 6), cuneate gyrus and the caudate nucleus were activated. As for the category fluency condition right hemispheric activity was found only in the caudate nucleus (see Table 2 for details).

Table 2
Activity patterns of young and old participants during semantic and phonemic fluency tasks

The direct comparison of the two fluency tasks yielded two significant clusters with peak activity in BA 45 (k=47, Z=5.5, -56/24/4) and BAs 9/44 (k=39, Z= 4.3, -56/13/24 and -50/13/19) of the left IFG that were more strongly activated for the phonemic task. Naming of category exemplars resulted in more pronounced activity in medial frontal structures only (right medial frontal gyrus, BA 11, k=17, Z=4.6, 3/37/-17; left anterior rostral cingulate zone, BA 32, Z=4.3, -9/31/-12).

Activity patterns (old group)

As can be seen in Figure 2, when compared to the younger group a more extensive pattern of activity was observed in the old participants for the semantic fluency task. The generation of category exemplars yielded significant activity in a large left-hemisphere cluster with peak activity being located in superior temporal and superior/middle/inferior frontal areas (BAs 22/46/10/6). Additional left-hemisphere regions included medial frontal areas, the precuneus (BA 7), the inferior and middle temporal gyri (BAs 20/21) and the thalamus. Right-hemispere activity was located in the middle and inferior frontal gyri (BAs 47/10/9), the lingual gyrus (BA 18) and premotor cortex (BA6). Phonemic generation yielded only one significant cluster in the right hemisphere (middle frontal gyrus, BA 10). Significantly activated clusters in the left hemisphere for this condition were located in the inferior (BA 44) and medial frontal (BAs 9/32) gyrus and in posterior parietal regions (for details see Table 2).

Even though the activity patterns of the two fluency tasks against the baseline suggested more pronounced differences between the two conditions, only one small cluster was significantly more activated for the category fluency than the phonemic fluency task and was located in the right medial frontal cortex (BA 11, Z=5.5, k=26, 6/39/-14). Inspection of the activity pattern elicited during phonemic fluency compared to the baseline at a lower threshold (p< .05 FDR-corrected) revealed a very similar pattern of activity compared to the category fluency task, in particular in the right IFG, which explains the minimal differences between the tasks.

Differences between groups for both fluency tasks

The comparison of activity patterns of the two age groups revealed more pronounced activity in the old participants only for the category fluency condition. Significant clusters were found in the left paracentral lobe (BA 31, k=30, Z=5.2, -3/-30/43) and the cingulate gyrus (BA 23, k=13, Z=4.5, 0/-28/26). In the right hemisphere, the pars triangularis in the inferior frontal gyrus (BA 45, k=16, 4.7, 59/21/4), the anterior and inferior most portion of the middle frontal gyrus (BA 47, k=15, Z=4.6, 36/43/-5) and superior temporal gyrus (BA 42, k=11, Z=4.0, 68/-17/9) were more strongly activated in the old group.

Correlation analysis between activity in differentially activated clusters in the old subgroup and performance

To explore the functional relevance of clusters that were more strongly activated in the old participants during the category fluency task we correlated individual performance and activity within these clusters. There was a strong negative correlation between behavioral performance and activity in the right inferior frontal gyrus ROI (r= -.63, p= .01) and the right middle frontal gyrus ROI (r= -.62, p= .009; see Figure 3 A+B). Activity in the left paracentral and cingulate gyrus and the right superior temporal gyrus was not correlated with behavioral performance.

Figure 3
A +B Shows the negative correlation between task performance during the semantic fluency task in the aged group (number of correct respones) and activity within the (A) right middle frontal gyrus (R MFG; 36/43/-5) and (B) the right inferior frontal gyrus ...

To further qualify the role of left frontal activity patterns in the older participants we performed two additional analyses: (1) for the semantic fluency condition correlation coefficients were calculated between performance and left-hemisphere areas of activity homologous to the active right IFG and MFG ROIs. The correlation for the left MFG ROI was not significant (r= -.3, p= .2). A marginally significant (negative) correlation in the left IFG was driven by one participant (r= -.4, p= .1, 33 correct responses, z=2.97), when we removed this outlier, the correlation dropped to r= -.05 (p= .9). (2) To assess the functional significance of left frontal activity during the phonemic task we calculated correlation coefficients between performance and the left frontal cluster that was activated by the older participants when compared to the baseline condition (see Table 2). Activity in this cluster (BA 44, left IFG) was positively correlated with the behavioral performance in the scanner (r= .56, p= .02). A similar analysis that included the large left fronto-temporal cluster obtained during the semantic fluency task (see Table 2) confirmed the previous ROI analysis (which only included the homologous area of the right IFG) and yielded a non-significant correlation (r= -.03, p= .2).

Because fluency scores were at ceiling for most young participants, there was little variance in their fluency scores; therefore, correlation analysis would not have yielded meaningful statistics for the young group.

Discussion

In the present study, we used fMRI to compare activity patterns elicited by two different verbal fluency tasks (semantic and phonemic fluency) in healthy young and old adults. The main findings of our study can be summarized as follows: (1) In the young adults, a strongly left lateralized (frontal) pattern of activity was evident during both tasks. A more bilateral pattern was found in the old group during semantic fluency. While performance during the phonemic fluency task was comparable between young and old participants, a selective drop of performance was observed in the old compared to the young group during the semantic task. The latter difference was accompanied by greater activity in the old than the young group mainly in right inferior and middle frontal regions. (2) This additional right frontal activity pattern was not beneficial to performance, as participants with more pronounced right frontal activity produced less correct words during the semantic task. (3) Only during the phonemic task, when performance levels were comparable between old and young adults a positive correlation between left frontal activity and behavioral performance could be substantiated (4) While in the younger participants the activity pattern was larger and more pronounced for the phonemic compared to the semantic fluency task in anterior ventral (BA 45) and posterior dorsal (BA 44/9) portion of the IFG, the old participants' activity pattern failed to show this distinction. We will comment on these findings in more detail below.

Previous studies have suggested a positive effect of additional activity in the non-task dominant hemisphere in particular for high-functioning healthy old adults across a variety of cognitive tasks (for review see Cabeza, 2002). Moreover, recently Davis and colleagues (2008) compared fMRI activity patterns in old and young participants during an episodic retrieval and visual perceptual task. These authors convincingly demonstrated that this pattern may not solely be explained by increased task demands in the older subjects as they controlled for task difficulty and matched their young and old subjects according to performance levels and confidence to master the task. Concerning language functions, little is known about the neural concomitants of word-retrieval processes in older adults and only one study employed a language production task to scrutinize the neural concomitants word-retrieval processes in old age (Wierenga et al., 2008). In this latter study, compared to previous non-language tasks a slightly different picture emerged: Not only did older adults recruit a larger network in left frontal brain regions, it was also suggested that during language tasks right-hemisphere activity might not be universally beneficial to performance. In particular, even though across the group naming accuracy was similar in old and young adults, when the authors only considered the lower functioning old participants, a negative correlation with performance was found in the posterior ventral portion of the right IFG (BA 45). This result is in line with our findings. As suggested by previous reports (e.g., Brickman et al., 2005), during the semantic task, performance levels of our old participants were reduced compared to the young group in- and outside (RWT) of the scanner. Moreover, only during the semantic task, the older adults (a) recruited additional right (inferior and middle) frontal areas and (b) this activity pattern was negatively correlated with performance. These findings contrast with those of Wierenga et al. (2008), who found a positive correlation in the right IFG (BAs 47) with picture-naming performance in neurologically normal old adults. However, a closer inspection of the positive correlation between performance of old adults and activity in the right IFG as reported by Wierenga et al. (2008) reveals that it was largely driven by three of 20 participants who had both low performance on picture naming and reduced activity in the IFG.

It also is worth noting that in the picture-naming task of Wierenga et al., performance was strongly determined by an external stimulus (i.e., the picture). Crosson et al. (2001) demonstrated differences in extent of activity in the IFG for externally driven vs. internally driven tasks like the verbal fluency task we used. Thus, this difference between tasks in the two studies may be of some importance in correlations between performance and IFG activity.

For the phonemic fluency task, the older participants performed on the same level as their younger counterparts and the direct comparison of the activity patterns of young and old adults revealed no statistically significant differences in the left or the right hemisphere. Moreover, a positive correlation between activity in the task-dominant left hemisphere and performance in the older adults was found only during the phonemic task. These results are similar to previous reports that investigated other types of language tasks (non-expressive). For example, in a study by Rotte (2005) old and young subjects performed simple synonym or letter identity judgements. Here, similar performance of both groups was accompanied by a strongly left lateralized activity pattern in old and young participants. Moreover, Daselaar, Veltman, Rombouts, Raaijmakers, & Jonker (2005) investigated priming effects during a word-stem completion task using event-related fMRI and observed similar priming-related activity reductions in the left IFG. It was noteworthy that no differences were found in the right IFG but rather confined to areas in the left hemisphere (e.g., the anterior superior temporal lobe).

Moreover, two recent studies investigated the influence of difficulty levels on phonemic word-retrieval tasks in younger subjects (to mimic word-retrieval difficulties in aphasia) by means of fMRI (Drager, Jansen, Bruchmann, Forster, Pleger, Zwitserlood, & Knecht, 2004) and functional transcranial Doppler sonography (fTCD, Drager & Knecht, 2002). In both studies the subjects' task was to generate words beginning with a single letter (T….; simple condition) or up to three letters (TEN….; difficult condition due to the limited search volume). Therefore, the difficulty levels were increased, but the fundamental phonological nature of the task was unaltered. (Such alterations could have lead to recruitment of different neural resources). Both studies found no additional activity in right hemisphere regions or no increased blood flow in the right middle cerebral artery subserving homologous right-hemisphere areas of the classical perisylvian language cortex of the dominant hemisphere.

The pattern of activity observed in semantic fluency task of our study is strongly reminescent of that seen in patients with acquired language disorders after cerebrovascular stroke (i.e., aphasia). Even though effective takeover of functions by the right hemisphere has convincingly been demonstrated for language comprehension tasks (e.g., Crinion & Price, 2005) this has not universally been shown for language production tasks. Rather, increased activity in the contralesional (right) hemisphere has usually been linked to a less favourable outcome in most studies (Cao, Vikingstad, George, Johnson, & Welch, 1999; Heiss & Thiel, 2006; Winhuisen, Thiel, Schumacher, Kessler, Rudolf, Haupt, & Heiss, 2007) and seems to be related to larger lesions when less language eloquent cortex in the left hemisphere is preserved (Heiss, Karbe, Weber-Luxenburger, Herholz, Kessler, Pietrzyk, & Pawlik, 1997). Further, it is important to note that right frontal lesions rarely cause aphasia in older adults, even though older adults demonstrate right frontal activity during word finding tasks such as in the current study or that of Wierenga et al. (2008). Given these facts, it cannot be assumed that right frontal activity in patients with aphasia necessarily represents language production (unless there is no left frontal activity to support production).

Based on the presently available data on language (production) tasks in old age it seems premature to exclude a potentially beneficial role of the right hemisphere in aging (i.e., the participants could even be more impaired without additional right-hemisphere activity, which could be addressed in future studies by means of repetitive transcranial magnetic stimulation, rTMS). Still, as summarized above previous studies in healthy subjects and aphasia patients pointed to a crucial role of the dominant left hemisphere. Even though correlations between performance scores and increased right hemispheric (frontal) activity have been found in some studies involving patients with aphasia, which points to effective compensation of these areas, in general, re-recruitment of left hemispheric brain areas, when intact, usually leads to a better outcome in aphasia than compensatory right-hemisphere involvement (for review see Heiss & Thiel, 2006). Moreover, suppression of additional activity in the pars triangularis of the right IFG by means of repetitive transcranial magnetic stimulation (rTMS) may improve word-retrieval in stroke sufferers (Naeser, Martin, Nicholas, Baker, Seekins, Kobayashi, Theoret, Fregni, Maria-Tormos, Kurland, Doron, & Pascual-Leone, 2005). Notably, this is exactly the area that was negatively correlated with performance in our sample of old participants.

At present, we can only speculate about the mechanism that may be responsible for the additional right frontal activity pattern in old adults during the semantic task. For example, in aphasia right hemispheric activity has been explained by decreased transcallossal inhibition that might even interfere with task performance in the dominant hemisphere (Heiss & Thiel, 2006). This might be related to inefficient recruitment of the left hemisphere during word-retrieval (Li & Lindenberger, 1999), which would also be in line with the rather extended pattern that was evident during the semantic task in the left hemisphere in the old participants. Additionally, in line with previous studies (Costafreda et al., 2006; Gourovitch, Kirkby, Goldberg, Weinberger, Gold, Esposito, Van Horn, & Berman, 2000; Mummery, Patterson, Hodges, & Wise, 1996) in the young participants, we observed more pronounced activity in the posterior dorsal part of the IFG (BAs 44/9) as well as in the more ventral and anterior portion (BA 45) for the phonemic task. This was not the case for the old group. Here, no statistically significant differences were found between the two tasks.

As mentioned earlier in the introduction, recent electrophysiological studies indicated changed brain activity patterns during language comprehension tasks across the lifespan (e.g., changed amplitude and latency of the N400 component indicating processing of potentially relevant information like words or other meaningful stimuli; for review see Federmeier, 2007). In particular, older adults may be specifically compromised when they must use highly constrained contextual information to generate information about upcoming events (e.g., Federmeier, McLennon, DeOchoa, & Kutas, 2002). Moreover, in this study a subset of the older participants continued to show a young like activity pattern which was best predicted by high working memory resources and verbal fluency scores. The latter was interpreted as reflecting a link between (internal or covert) language production processes and predictive processing during language comprehension tasks (Federmeier, 2007). Tentatively, it might be speculated whether the more constrained character of the semantic fluency task (i.e., the limited number of category exemplars, while a larger number of items can be selected during the letter fluency task) might be an explanation for the selective impairment during the semantic task in our study. Moreover, it has been shown that (a) the use of contextual information and preactivation of likely upcoming events during language comprehension tasks (at least on a sentential level) might be most efficiently executed by the left hemisphere and (b) that the left hemisphere is more tuned to make use of controlled processes to select word meaning (Federmeier, 2007). Integrity and effective use this left (frontal-temporal) network may even be more important during language production tasks. Therefore, in line with our findings, additional activity in the right hemisphere in older adults may not be efficient or functionally compensatory at least with regard to selective cognitive processes, like in the context of the (more constrained) semantic fluency task.

A note of caution should be made concerning the task choice in our study: In the present study, we chose to compare two different fluency tasks, as we expected a selective impairment of one task (the semantic) and similar performance in the other (the phonemic task). Still, the direct comparison of the two tasks we used in the present study is difficult to interpret as the two tasks may require different cognitive operations and involve different neural resources. For example, even though both tasks require a strategic search and retrieval of information from semantic memory, previous studies found phonemic fluency to be more strongly affected by left frontal damage, while semantic fluency is affected by left frontal and (medial/inferior) temporal damage (e.g., Stuss, Alexander, Hamer, Palumbo, Dempster, Binns, Levine, & Izukawa, 1998). This pattern might be explained by the fact that semantic fluency requires a rather constrained search of exemplars from a superordinate category and strongly relies on semantic associations, while phonemic fluency can be accomplished within a relatively less constrained search volume (Murphy et al., 2006). Moreover, two previous studies (Gourovitch et al., 2000; Mummery et al., 1996) that used positron emission tomography (PET) directly compared semantic and phonemic fluency tasks within the same (healthy young) subjects. Similar to our own study, both found increased activity in several subportions of the IFG for the phonemic task (including BAs 44/9). For the inverse contrast, increased activity was observed mainly in inferior and middle temporal areas and the hippocampus. In our study, no difference between the two tasks was found in temporal areas, which may be related to greater sensitivity of PET for functional activity in temporal brain regions, the sparse sampling procedure that we used or/and the difference in baseline tasks [Mummery et al., 1996: null-baseline; Gourovitch et al., 2000: generation of days of the week or months of the year]. Therefore, to directly assess the impact of difficulty on the neural concomitants of verbal fluency measures in old adults, future studies should also consider varying the level of difficulty within each task (e.g., by comparing activity elicited by superordinate categories that comprise a different number of possible exemplars).

Despite these potential differences between the two fluency tasks, the engagement of comparable brain regions in old and young participants during the phonemic task was consistent with the equal performance levels of the young and old groups, while reduced task performance in the semantic task for old adults resulted in an inefficient recruitment of homologous brain areas. Thus, functional integrity and recruitment of left frontal language areas in the task dominant hemisphere seems to be crucial for successful word-retrieval in old age. If the negative correlation found in our own study and in the subgroup of low performing old adults of Wierenga et al. (2008) will be replicated it might be worth exploring strategies to counteract these processes. Here, to confirm the non-beneficial role of additional right hemisphere activity, two strategies are conceivable: The first might involve the active suppression of right frontal activity by means of rTMS, as has successfully been demonstrated in stroke patients suffering from aphasia (e.g., Naeser et al., 2005). A potentially complementary approach may involve facilitation of left-frontal activity by behavioral training as has been suggested for right-frontal activity in aphasia treatment by Crosson et al. (2007;, 2005).

Acknowledgments

This study was supported by: a grant from the German Foundation for Science (DFG) awarded to MM (ME 3161/2-1) and CE (SFB 471; FOR 341); grants from the US Department of Veterans Affairs Rehabilitation Research and Development service to BC (Research Career Scientist Award B3470S), to LGR (Center of Excellence Grant B3149C, Research Career Scientist Award B5083S), and to TC (Career Development Award B3992V); and a grant from the National Institute on Deafness and other Communication Disorders to BC (R01 DC007387) and. All authors declare that they have no competing financial interests.

References

  • Aschenbrenner S, Tucha O, Lange KW. Regensburger Wortflüssigkeitstest. Göttingen: Hogrefe; 2000.
  • Beck A, Steer P, Garbin M. Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review. 1988;8:122–132.
  • Braver TS, Barch DM, Kelley WM, Buckner RL, Cohen NJ, Miezin FM, et al. Direct comparison of prefrontal cortex regions engaged by working and long-term memory tasks. Neuroimage. 2001;14:48–59. [PubMed]
  • Brickman AM, Paul RH, Cohen RA, Williams LM, MacGregor KL, Jefferson AL, et al. Category and letter verbal fluency across the adult lifespan: relationship to EEG theta power. Archives of Clinincal Neuropsychology. 2005;20:561–573. [PMC free article] [PubMed]
  • Burke DM, Shafto MA. Language and aging. In: Salthouse TA, editor. The handbook of aging and cognition. New York: Psychology Press; 2008. pp. 373–443.
  • Burke SN, Barnes CA. Neural plasticity in the ageing brain. Nature Reviews Neuroscience. 2006;7:30–40. [PubMed]
  • Cabeza R. Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychology and Aging. 2002;17:85–100. [PubMed]
  • Cabeza R, Anderson ND, Locantore JK, McIntosh AR. Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage. 2002;17:1394–1402. [PubMed]
  • Cao Y, Vikingstad EM, George KP, Johnson AF, Welch KM. Cortical language activation in stroke patients recovering from aphasia with functional MRI. Stroke. 1999;30:2331–2340. [PubMed]
  • Costafreda SG, Fu CH, Lee L, Everitt B, Brammer MJ, David AS. A systematic review and quantitative appraisal of fMRI studies of verbal fluency: role of the left inferior frontal gyrus. Human Brain Mapping. 2006;27:799–810. [PubMed]
  • Craik FI, Bialystok E. Cognition through the lifespan: mechanisms of change. Trends in Cognitive Sciences. 2006;10:131–138. [PubMed]
  • Crinion J, Price CJ. Right anterior superior temporal activation predicts auditory sentence comprehension following aphasic stroke. Brain. 2005;128:2858–2871. [PubMed]
  • Crosson B, McGregor K, Gopinath KS, Conway TW, Benjamin M, Chang YL, et al. Functional MRI of language in aphasia: a review of the literature and the methodological challenges. Neuropsychology Review. 2007;17:157–177. [PMC free article] [PubMed]
  • Crosson B, Moore AB, Gopinath K, White KD, Wierenga CE, Gaiefsky ME, et al. Role of the right and left hemispheres in recovery of function during treatment of intention in aphasia. Journal of Cognitive Neuroscience. 2005;17:392–406. [PubMed]
  • Crosson B, Sadek JR, Maron L, Gokcay D, Mohr CM, Auerbach EJ, et al. Relative shift in activity from medial to lateral frontal cortex during internally versus externally guided word generation. Journal of Cognitive Neuroscience. 2001;13:272–283. [PubMed]
  • Daselaar SM, Veltman DJ, Rombouts SA, Raaijmakers JG, Jonker C. Neuroanatomical correlates of episodic encoding and retrieval in young and elderly subjects. Brain. 2003;126:43–56. [PubMed]
  • Daselaar SM, Veltman DJ, Rombouts SA, Raaijmakers JG, Jonker C. Aging affects both perceptual and lexical/semantic components of word stem priming: An event-related fMRI study. Neurobiology of Learning and Memory. 2005;83:251–262. [PubMed]
  • Davis SW, Dennis NA, Daselaar SM, Fleck MS, Cabeza R. Que PASA? The posterior-anterior shift in aging. Cerebral Cortex. 2008;18:1201–1209. [PMC free article] [PubMed]
  • Drager B, Jansen A, Bruchmann S, Forster AF, Pleger B, Zwitserlood P, et al. How does the brain accommodate to increased task difficulty in word finding? A functional MRI study. Neuroimage. 2004;23:1152–1160. [PubMed]
  • Drager B, Knecht S. When finding words becomes difficult: is there activation of the subdominant hemisphere? Neuroimage. 2002;16:794–800. [PubMed]
  • Federmeier KD. Thinking ahead: the role and roots of prediction in language comprehension. Psychophysiology. 2007;44:491–505. [PMC free article] [PubMed]
  • Federmeier KD, McLennon DB, DeOchoa E, Kutas M. The impact of semantic memory organization and sentence context information on spoken language processing by younger and older adults: An ERP study. Psychophysiology. 2002;39:133–146. [PubMed]
  • Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatry Research. 1975;12:189–198. [PubMed]
  • Gaab N, Gabrieli JD, Glover GH. Assessing the influence of scanner background noise on auditory processing. II. An fMRI study comparing auditory processing in the absence and presence of recorded scanner noise using a sparse design. Human Brain Mapping. 2007;28:721–732. [PubMed]
  • Genovese CR, Lazar NA, Nichols T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage. 2002;15:870–878. [PubMed]
  • Gourovitch ML, Kirkby BS, Goldberg TE, Weinberger DR, Gold JM, Esposito G, et al. A comparison of rCBF patterns during letter and semantic fluency. Neuropsychology. 2000;14:353–360. [PubMed]
  • Grady CL, McIntosh AR, Bookstein F, Horwitz B, Rapoport SI, Haxby JV. Age-related changes in regional cerebral blood flow during working memory for faces. Neuroimage. 1998;8:409–425. [PubMed]
  • Hall DA, Haggard MP, Akeroyd MA, Palmer AR, Summerfield AQ, Elliott MR, et al. “Sparse” temporal sampling in auditory fMRI. Human Brain Mapping. 1999;7:213–223. [PubMed]
  • Heiss WD, Karbe H, Weber-Luxenburger G, Herholz K, Kessler J, Pietrzyk U, et al. Speech-induced cerebral metabolic activation reflects recovery from aphasia. Journal of the Neurological Sciences. 1997;145:213–217. [PubMed]
  • Heiss WD, Thiel A. A proposed regional hierarchy in recovery of post-stroke aphasia. Brain and Language. 2006;98:118–123. [PubMed]
  • Henry JD, Crawford JR, Phillips LH. Verbal fluency performance in dementia of the Alzheimer's type: a meta-analysis. Neuropsychologia. 2004;42:1212–1222. [PubMed]
  • Ivnik RJ, Malek JF, Smith GE, Tangolos EG, Petersen RC. Neuropsychological norms above age 55: COWA, BNT, MAE Token, WRAT-R Reading, AMNART, Stroop, TMT, and JLO. Clinical Neuropsychology. 1996;10:262–278.
  • Lancaster JL, Woldorff MG, Parsons LM, Liotti M, Freitas CS, Rainey L, et al. Automated Talairach atlas labels for functional brain mapping. Human Brain Mapping. 2000;10:120–131. [PubMed]
  • Li SC, Lindenberger U. Cross-level unification: a computational exploration of the link between deterioration of neurotransmitter systems dedifferentation of cognitiveabilities in old age. In: O'Connor D, editor. Dementia and normal aging. Cambridge: University Press; 1999. pp. 331–365.
  • Mannhaupt HR. Produktionsnormen für verbale Reaktionen zu 40 geläufigen Kategorien. Sprache und Kognition. 1983;4:264–278.
  • Monsch AU, Bondi MW, Butters N, Salmon DP, Katzman R, Thal LJ. Comparisons of verbal fluency tasks in the detection of dementia of the Alzheimer type. Archives of Neurology. 1992;49:1253–1258. [PubMed]
  • Mummery CJ, Patterson K, Hodges JR, Wise RJ. Generating ‘tiger’ as an animal name or a word beginning with T: differences in brain activation. Proceedings of the Biological Sciences. 1996;263:989–995. [PubMed]
  • Murphy KJ, Rich JB, Troyer AK. Verbal fluency patterns in amnestic mild cognitive impairment are characteristic of Alzheimer's type dementia. Journal of the International Neuropsychological Society. 2006;12:570–574. [PubMed]
  • Naeser MA, Martin PI, Nicholas M, Baker EH, Seekins H, Kobayashi M, et al. Improved picture naming in chronic aphasia after TMS to part of right Broca's area: an open-protocol study. Brain and Language. 2005;93:95–105. [PubMed]
  • Petersen RC. Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine. 2004;256:183–194. [PubMed]
  • Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magnetic Resonance Medicine. 1999;42:952–962. [PubMed]
  • Rajah MN, D'Esposito M. Region-specific changes in prefrontal function with age: a review of PET and fMRI studies on working and episodic memory. Brain. 2005;128:1964–1983. [PubMed]
  • Raz N, Gunning-Dixon F, Head D, Rodrigue KM, Williamson A, Acker JD. Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: replicability of regional differences in volume. Neurobiology of Aging. 2004;25:377–396. [PubMed]
  • Reuter-Lorenz P. New visions of the aging mind and brain. Trends in Cognitive Sciences. 2002;6:394. [PubMed]
  • Reuter-Lorenz PA, Jonides J, Smith EE, Hartley A, Miller A, Marshuetz C, et al. Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. Journal of Cognitive Neuroscience. 2000;12:174–187. [PubMed]
  • Riegel KF. Der sprachliche Leistungstest SASKA: Synonym-Antonym-Selektions-Klassifikations-Analogietest. Göttingen: Hogrefe; 1967.
  • Rosen AC, Prull MW, O'Hara R, Race EA, Desmond JE, Glover GH, et al. Variable effects of aging on frontal lobe contributions to memory. Neuroreport. 2002;13:2425–2428. [PubMed]
  • Rotte M. Age-related differences in the areas of Broca and Wernicke using functional magnetic resonance imaging. Age and Ageing. 2005;34:609–613. [PubMed]
  • Schmidt KH, Metzler P. Wortschatztest. Göttingen: Hogrefe; 1992.
  • Shafto MA, Burke DM, Stamatakis EA, Tam PP, Tyler LK. On the Tip-of-the-Tongue: Neural Correlates of Increased Word-finding Failures in Normal Aging. Journal of Cognitive Neuroscience 2007 [PMC free article] [PubMed]
  • Shankle WR, Romney AK, Hara J, Fortier D, Dick MB, Chen JM, et al. Methods to improve the detection of mild cognitive impairment. Proceedings of the National Academy of Sciences U S A. 2005;102:4919–4924. [PMC free article] [PubMed]
  • Stuss DT, Alexander MP, Hamer L, Palumbo C, Dempster R, Binns M, et al. The effects of focal anterior and posterior brain lesions on verbal fluency. Journal of the International Neuropsychological Society. 1998;4:265–278. [PubMed]
  • Verhaeghen P. Aging and vocabulary scores: a meta-analysis. Psychology and Aging. 2003;18:332–339. [PubMed]
  • West RL. An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin. 1996;120:272–292. [PubMed]
  • Wierenga CE, Benjamin M, Gopinath K, Perlstein WM, Leonard CM, Rothi LJ, et al. Age-related changes in word retrieval: role of bilateral frontal and subcortical networks. Neurobiology of Aging. 2008;29:436–451. [PubMed]
  • Winhuisen L, Thiel A, Schumacher B, Kessler J, Rudolf J, Haupt WF, et al. The right inferior frontal gyrus and poststroke aphasia: a follow-up investigation. Stroke. 2007;38:1286–1292. [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...