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Abnormal Functional Connectivity of Hippocampus During Episodic Memory Retrieval Processing Network in Amnestic Mild Cognitive Impairment
Abnormal Functional Connectivity of Hippocampus During Episodic Memory Retrieval Processing Network in Amnestic Mild Cognitive Impairment Feng Bai, Zhijun Zhang, David R. Watson, Hui Yu, Yongmei Shi, Yonggui Yuan, Yufeng Zang, Chaozhe Zhu, and Yun Qian Background: Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. Methods: Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. Results: Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. Conclusions: aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer’s disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD. Key Words: Functional connectivity, functional magnetic resonance imaging, mild cognitive impairment
A
mnestic mild cognitive impairment (aMCI) (1) is believed to be an intermediate state between normal aging and dementia, which is at present the most valid conceptual indicator of incipient or early Alzheimer’s disease (AD) (2). The predominant cognitive deficits present in aMCI are related to learning and memory function. The first pathological changes that appear as AD develops are in hippocampus areas, and at the end stage of the disease these regions are also the ones most severely affected (3). Previous studies suggested that reduction in hippocampal volume represents the most important structural hallmark of conversion from mild cognitive impairment (MCI) to AD (4 –7). Neuroimaging techniques for assessing hippocampal function may be extremely useful in the evaluation of disease development and trajectory and its related pathology (8). In general, episodic memory is a typical impairment in AD (9) and refers to the ability to retain, recall, and encode information related to personal events and experiences occurring at specific From the School of Clinical Medicine (FB, ZZ, HY, YS, YY, YQ), Southeast University, and Department of Neurology (FB, ZZ, HY, YS, YQ), Affiliated ZhongDa Hospital of Southeast University, Nanjing, China; Psychiatry and Neuroscience (DRW), School of Medicine and Dentistry, Queen’s University Belfast, United Kingdom; Department of Psychiatry (YY), Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China; and State Key Laboratory of Cognitive Neuroscience and Learning (YZ, CZ), Beijing Normal University, Beijing, China. Address reprint requests to Zhijun Zhang, Ph.D., M.D., The Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, No. 87 DingJiaQiao, Nanjing, Jiangsu 210009 China; E-mail: zhijunzhang838@yahoo. com.cn. Received June 3, 2008; revised October 9, 2008; accepted October 9, 2008.
0006-3223/09/$36.00 doi:10.1016/j.biopsych.2008.10.017
times and places (10). Human studies have demonstrated that the hippocampus has a key role in episodic memory processing (11). Therefore, it is reasonable that structural and functional changes in the hippocampus are likely to be important in understanding the origins of impaired memory function in AD. Functional neuroimaging studies have shown abnormal activation of hippocampus during episodic memory tasks in both AD (12) and MCI patients (8,13,14). However, the processes involved in all forms of higher cognitive function are not isolated to specific brain regions but instead result from highly interconnected neural circuits encompassing often remote brain regions. Therefore, it is important to explore the connections among neural circuits underpinning episodic memory function if we are to better understand how they may differ between sufferers of AD or aMCI and normal subjects. Functional connectivity analysis is a technique for the in vivo examination of brain regions cooperating during rest or task performance and provides a measure of the temporal correlation between neurophysiological activities in different brain regions (15,16). Two recent AD-related studies reported decreased functional connectivity in the resting-state between the hippocampus and diffuse cortical, subcortical, and cerebellar sites (17,18). In addition, Grady et al. (19), using a face memory task, concluded that AD patients had a functional disconnection between hippocampus and prefrontal cortex and suggested that memory breakdown is related to a reduction in the integrated activity within a distributed network that includes these two areas. However, the state of functional connectivity between hippocampus and other regions of the brain remains unclear in aMCI patients. This study examined functional connectivity between hippocampus and other regions during an episodic memory retrieval task. Investigations of episodic memory retrieval in AD BIOL PSYCHIATRY 2009;65:951–958 © 2009 Society of Biological Psychiatry
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patients using the same task (8,13) showed that although task performance ability was unimpaired in such groups compared with normally aging control subjects, their retrieval capacity was significantly reduced. Given the key role of the hippocampus in AD-related pathology, it is reasonable to expect aMCI patients to be able to perform the task without difficulty but also display retrieval dysfunction. We predict that, compared with normal aging subjects, this retrieval difficulty will be associated with differences in hippocampus connectivity measures. To our knowledge, this is the first study of hippocampus connectivity under episodic memory retrieval task conditions in aMCI patients.
Methods and Materials Subjects We recruited 59 elderly individuals (all Chinese Han and right-handed) made up of 34 aMCI patients and 25 healthy control subjects through normal community health screening and newspaper advertisements. All aMCI patients met the diagnostic criteria proposed by Petersen et al. (1) including 1) subjective memory impairment corroborated by subject and an informant; 2) objective memory performances documented by the Auditory Verbal Learning Test—Delayed Recall score that is ⱕ 1.5 SD of age-adjusted and education-adjusted norms (the cutoff was ⱕ 4 correct responses on 12 items for ⱖ 8 years of education); 3) normal general cognitive functioning evaluated by a Mini-Mental State Exam (MMSE) score of 24 or higher; 4) a Clinical Dementia Rating of .5, with at least a .5 in the memory domain; 5) no or minimal impairment in activities of daily living; 6) absence of dementia or insufficient level to meet the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association criteria for AD. The inclusion assessment was performed by an experienced neuropsychiatrist who administered a structured interview to subjects and their informants. Participants were excluded from the study if they had a past history of known stroke (modified Hachinski score ⬎ 4), alcoholism, head injury, Parkinson’s Table 1. Demographic and Neuropsychological Data Between Groups aMCI Subjects (n ⫽ 28)
Normal Aging (n ⫽ 23)
Items
Mean
SD
Mean
SD
p
Age (Years) Education Level (Years) Sex (Male:Female) Clinical Dementia Rating Mini-Mental State Exam Auditory Verbal Memory Test— Delayed Recall Rey-Osterrieth Complex Figure Test—Delayed Recall Trail Making Test—A Trail Making Test—B Symbol Digit Modalities Test Clock Drawing Test Digit Span Test
72.5 14.7 17:11 .5 27.1b
4.3 2.4 — — 1.6
70.4 14.7 13:10 0 28.4
5.3 3.4 — — 1.4
ns ns ns .005
2.8b
1.9
8.3
2.0
.000
10.8a 95.8a 183.4a 28.5 8.7 12.3
7.7 35.2 71.1 10.6 1.2 1.6
17.0 72.9 134.3 33.3 8.8 12.9
7.1 25.7 34.8 8.0 1.1 2.1
.018 .021 .024 ns ns .012
Values are mean (SD); p ⬍ .05. aMCI, amnestic mild cognitive impairment. a p ⬍ .05 statistical difference between groups. b p ⬍ .01 statistical difference between groups.
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Table 2. Comparison of the Behavioral Data of Episodic Memory Retrieval Task Between and Within Groups Items
Reaction Time (msec)—Old Reaction Time (msec)—New Accuracy
aMCI Subjects
Control Subjects
Mean (msec)
SD
Mean (msec)
SD
958.7
126.8
804.2
119.4
1113.4 96.1%
207.1 .03
895.2 96.7%
159.7 .04
Between groups and within groups, there were significant differences between response times to old pictures and new pictures, p ⬍ .001. There was no significant difference in accuracy between groups, p ⬎ .05. aMCI, amnestic mild cognitive impairment.
disease, epilepsy, major depression (excluded by Self-Rating Depression Scale) or other neurological or psychiatric illness (excluded by clinical assessment and case history), major medical illness (e.g., cancer, anemia, thyroid dysfunction), or severe visual or hearing loss. In addition, none of aMCI subjects was on cognitive enhancing therapies. Control subjects were required to have a Clinical Dementia Rating of 0, a MMSE score ⱖ 26, and a Delayed Recall score ⬎ 4 for those with 8 or more years of education. The study was approved by the Research Ethics Committee of Affiliated ZhongDa Hospital, Southeast University, and written informed consent was obtained from all participants. Functional Magnetic Resonance Imaging (fMRI) Activation Task The associative episodic recognition task involved serial presentation of color photographs with neutral mood, which were obtained from the International Affective Picture System (20). This task consisted of two identical training sessions and one scanning session. The first training session was carried out 45 min before the scanning session, and the second training session was performed 15 min before the scanning session. Each training session consisted of five pictures and each picture was presented repeatedly 15 times in a pseudorandom pattern. Participants were asked to view the training pictures and try to remember them. The pictures presented in the training sessions were designated as “old” pictures in the test session. The scanning session consisted of 90 exposures, including 45 “old” pictures that appeared pseudorandomly as one, two, three, four, or five consecutive items and 45 “new” pictures that were presented once each, pseudorandomly. The “old” pictures were intermixed with the “new” pictures pseudorandomly. Every picture was presented for 2800 msec with 200-msec interstimulus interval. During scanning the participants had to judge whether the presented picture was “old” or “new.” To indicate their choice they used a two-bottom fiber-optic box held in the right hand: the index finger was used to respond to “old” pictures and the middle finger to respond to “new” pictures. The Presentation application recorded these button responses. The scanning session duration was 4 min and 36 sec, and the first 6 sec contained word cues to ready the participants. Magnetic Resonance Imaging Procedures Subjects were scanned using a 1.5-Tesla scanner (General Electric Medical Systems, Milwaukee, Wisconsin) with a homogeneous birdcage head coil. High-resolution T1-weighted axial images covering the whole brain were acquired using a three-dimensional spoiled gradient echo sequence: repetition time (TR) ⫽ 9.9 msec; echo time (TE) ⫽ 2.1 msec; flip angle
F. Bai et al. (FA) ⫽ 150°; acquisition matrix ⫽ 256 ⫻ 192; field of view (FOV) ⫽ 240 ⫻ 240 mm; thickness ⫽2.0 mm; gap ⫽ 0 mm; number of excitations (NEX) ⫽ 1.0. Functional scans (T2 images) involved the acquisition of 30 contiguous axial slices using a gradient-recalled echo-planar imaging pulse sequence: TR ⫽ 3000 msec; TE ⫽ 40 msec; FA ⫽ 90°; acquisition matrix ⫽ 64 ⫻ 64; FOV ⫽ 240 ⫻ 240 mm; thickness ⫽ 4.0 mm; gap ⫽ 0 mm and 3.75 ⫻ 3.75 mm2 in-plane resolution; NEX ⫽ 1.0. All present subjects with good compliance were scanned in the daytime, while none of subjects without upset before and during scan. Image Data Analysis Structural Data Analysis. Anatomic guidelines for the hippocampus were based on the work of Watson et al. (21) with a standard neuroanatomic atlas (22) as a guide and manually outlining the periphery of the regions of interest (ROI), delineated using a mouse-driven cursor separately for the left and right hemispheres from T1-weighted coronal images on a plane perpendicular to hippocampal major axis. The MRIcro software, version 3.9 (C. Rorden, www.mricro.com) was employed to draw the ROIs. MATLAB software, version 7.0 (Mathworks,
BIOL PSYCHIATRY 2009;65:951–958 953 Sherborn, Massachusetts) calculated the ROI volume by multiplying the number of voxels in the ROI by the size of each voxel.
Functional Data Analysis Image Preprocessing. Analyses were conducted with Statistical Parametric Mapping software (www.fil.ion.ucl.ac.uk/spm). The first two volumes of the scanning session were discarded to allow for T1 equilibration effects. The remaining images were corrected for the timing differences between each slice and motion effects (six-parameter rigid body). Participants with head motion greater than 2.5-mm maximum displacement in any direction or 2.5° of angular motion during the scan were excluded from final analysis. The remaining images were spatially normalized into a standard stereotaxic space using a 12-parameter affine approach and an echo planar image template image and resampled to 3 ⫻ 3 ⫻ 3 mm3 voxels, and smoothed with a Gaussian kernel of 4 ⫻ 4 ⫻ 4 mm (full-width half-maximum [FWHM]). Linear trends were removed from the image time series and the time series was high pass filtered with a filter cutoff of .01 Hz (23).
Figure 1. Brain regions show significant connectivity to the bilateral hippocampus in amnestic mild cognitive impairment (aMCI) and control group. Voxels with p ⬍ 1 ⫻ 10– 6 and cluster size 432 mm3. (Note: use of threshold for the two groups was for visual purposes only.)
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Figure 2. Distribution of decreased functional connectivity of left hippocampus (A) and right hippocampus (B) in amnestic mild cognitive impairment patients compared with healthy control subjects. Voxels with p ⬍ .05 and cluster size 432 mm3.
Figure 3. Distribution of increased functional connectivity of left hippocampus and right hippocampus in amnestic mild cognitive impairment (aMCI) patients compared with healthy control subjects. L, left; R, right; 1. R cerebellum/declive; 2. R inferior temporal gyrus; 3. L subcallosal gyrus; 4. L anterior cingulated; 5. R inferior frontal gyrus; 6. L inferior frontal gyrus; 7. R insula; 8. R parahippocampal gyrus; 9. L parahippocampal gyrus; 10. R middle occipital gyrus; 11. bilateral cingulated gyrus; 12. L superior frontal gyrus; 13. R precuneus; 14. L precuneus; 15. L medial frontal gyrus; 16. L superior temporal gyrus; 17. L anterior cingulated; 18. R parahippocampal gyrus; 19. L middle temporal gyrus; 20. R inferior frontal gyrus; 21. L inferior frontal gyrus; 22. R putamen; 23. L insula; 24.R insula/ R superior temporal gyrus; 25. R cerebellum/ culmen; 26. R superior frontal gyrus; 27. R cuneus; 28. L cingulated gyrus; 29. L medial frontal gyrus. Voxels with p ⬍ .005 and cluster size 432 mm3 were taken as being significantly connected to the hippocampus. These criteria met corrected threshold of p ⬍ .0004.
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F. Bai et al. Finally, seven participants (five aMCI patients and two control subjects) with major head motion and one aMCI participant with poor quality of image were excluded from study. Functional Connectivity Analyses. For each subject, a mean time series for hippocampal formation (left and right separately) was computed for each subject. This region of interest, using automated anatomic labeling (24) implemented with wfu_PickAtlas software (25,26), was used to test our a priori hypothesis regarding the hippocampus. The cross-correlation analysis was then carried out between mean signal change and the time series of all other voxels in the whole brain. Six motion parameters were included as regressors of no interest. Finally, a Fisher’s z transform was applied to improve the normality of the correlation coefficients (18,27). To determine brain regions showing significant connectivity to the left and right hippocampus within each group, the individual z value was entered into a random effect, one-sample t test in a voxelwise manner. To remove possible effects of hippocampal atrophy on the results, “normalized” hippocampal volume, namely (raw hippocampal volume / total intracranial volume) ⫻ 1000 (28), obtained from the structural scan ROI data, was introduced as a covariate into a random effects, two-sample t test in a voxelwise manner to identify the regions showing significant differences in connectivity to the left and right hippocampus between the groups. Group Statistical Maps. Within experimental groups (aMCI patients ⫽ 28; control subjects ⫽ 23), voxels with p ⬍ 1 ⫻ 10– 6 and cluster size ⬎ 432 mm3 was used to show significant connectivity to the left and right hippocampus. These differences were still significant after correction for multiple comparisons. Between experimental groups a single voxel threshold was set at p ⬍ .005, and a minimum cluster size of 432 mm3 was used to correct for multiple comparisons. This yielded a corrected threshold of p ⬍ .0004, determined by Monte Carlo simulation (see program AlphaSim by D. Ward. Parameters were: single voxel p value ⫽ .005, FWHM ⫽ 4 mm, with mask. Also see http:// afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf). Statistical Analysis Nonparametric Mann-Whitney U tests were used for group comparisons of demographic, neuropsychological performances and hippocampal volume (statistical significance was set at p ⬍ .05). A further correlation analysis between fMRI data and neuropsychological performances was performed: masks were created for the regions where significant differences in functional connectivity between groups were found. Second, mean z values of abnormal functional connectivity were calculated for these cluster masks within every aMCI patient. These analyses were performed using a semiautomated imaging analysis program developed at Institute of Automation, Chinese Academy of Sciences (WL Zhu). Finally, correlative analyses were performed to examine relationships between these connectivity z values and neuropsychological performance using SPSS 11.5 software (SPSS, Chicago, Illinois).
Results Demographic and Neuropsychological Data Demographic characteristics and neuropsychological scores are shown in Table 1. Compared with healthy aging subjects, aMCI patients had poor performances in Auditory Verbal Memory Test, Rey-Osterrieth Complex Figure Test, Trail Making Test—A and B, and Digit Span Test; other test battery indices showed no significant differences between groups.
Behavioral Data There were no significant differences in the performance of the memory task between the two groups. Both groups demonstrated better than 96% average accuracy for recognition of the pictures following their scanning session, whereas aMCI patients showed increased reaction time than control subjects (Table 2). Structural Data-Group Comparison The volumes extracted from the manual segmentation of hippocampus for the groups show that hippocampal volumes of aMCI patients group were 15.8% smaller on the left side (p ⬍ .004) and 18.2% smaller on the right side (p ⬍ .001) than their normal aging peers. Functional Connectivity Data-Within Group Comparison In the normal aging group, the left and right hippocampus showed significant connectivity to the medial temporal lobe, Table 3. Increased Functional Connectivity of Hippocampus in aMCI Patients Compared with Healthy Control Subjects
Brain Region
BA
Peak Talairach Coordiates x, y, z (mm)
L Hippocampus Increased Functional Connectivity L Superior Frontal Gyrus 9 ⫺18 37 34 L Medial Frontal Gyrus 6 ⫺12 ⫺9 53 L Subcallosal Gyrus 25 ⫺3 14 ⫺13 L Inferior Frontal Gyrus 47 ⫺30 20 ⫺4 R Inferior Frontal Gyrus 47 48 17 ⫺6 R Inferior Temporal Gyrus 20 39 ⫺16 ⫺27 R Parahippocampal Gyrus 27 15 ⫺32 ⫺1 L Parahippocampal Gyrus 30 ⫺3 ⫺41 2 R Insula 13 39 ⫺3 ⫺5 R Precuneus 7 6 ⫺33 46 L Precuneus 7 ⫺3 ⫺35 49 L Anterior Cingulate 32 ⫺12 41 ⫺5 Bilateral Cingulated Gyrus 31 0 ⫺36 29 R Middle Occipital Gyrus 19 39 ⫺78 15 R Cerebellum/Declive — 21 ⫺80 ⫺21 R Hippocampus Increased Functional Connectivity R Superior Frontal Gyrus 10 12 70 1 L Medial Frontal Gyrus 6 ⫺12 ⫺9 53 L Inferior Frontal Gyrus 47 ⫺30 20 ⫺9 R Inferior Frontal Gyrus 47 33 23 ⫺4 L Superior Temporal 38 ⫺50 2 ⫺10 Gyrus L Middle Temporal Gyrus 21 ⫺45 ⫺29 ⫺4 L Insula 13 ⫺36 ⫺15 ⫺7 R Parahippocampal Gyrus 28 27 ⫺24 ⫺6 R Putamen — 30 ⫺6 ⫺2 R Insula 13 42 ⫺17 1 R Superior Temporal Gyrus 41 45 ⫺29 4 L Anterior Cingulate 32 ⫺5 46 ⫺5 L Cingulated Gyrus 31 ⫺15 ⫺39 32 R Cuneus 18 24 ⫺80 23 R Cerebellum/Culmen — ⫺3 ⫺49 2
Peak T Score
Cluster Size
3.40 3.65 3.90 3.48 3.81 4.26 3.77 3.64 3.86 3.90 3.57 3.64 3.63 3.70 3.78
567 729 459 1836 2349 810 3159
4.16 3.31 3.50 4.11 3.56
486 513 1350 972 864
4.19 4.07 3.65 3.67 4.13 3.63 3.14 3.96 4.61 4.28
1674
1188 783 891 486 783 756
918 1080 1917 621 621 945 459
a MCI, amnestic mild cognitive impairment; BA, Brodmann’s area; L, left; R, right. Secondary peaks are italic; cluster size is in mm3. Voxels with p ⬍ .005 and cluster size 432 mm3 were considered to be significantly connected to the hippocampus. These criteria met corrected threshold of p ⬍ .0004.
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956 BIOL PSYCHIATRY 2009;65:951–958 posterior cingulated gyrus, basal ganglia, temporal lobe, and frontal lobe. These regions overlap with regions known to contribute to the episodic memory network. A similar pattern was noted in the aMCI group, but visual comparison of the maps suggested that the magnitude and extent of hippocampal connectivity to frontal lobe, temporal lobe, parietal lobe, and cerebellum in these patients was greater than observed in the control group data. (Figure 1). Functional Connectivity Data-Between Group Comparisons After correction for multiple comparisons, aMCI patients showed a trend toward impaired functional connectivity in prefrontal lobe, temporal lobe, parietal lobe, and cerebellum (voxels with p ⬍ .05 and cluster size 432 mm3; Figure 2). The functional connectivity analysis of the left and right hippocampus revealed extensive regions with significantly higher functional connectivity in the aMCI patients compared with their control subjects, mainly in diffuse areas of prefrontal lobe, temporal lobe, parietal lobe, and cerebellum (corrected threshold of p ⬍ .0004 by multiple comparisons; Figure 3, Table 3). In addition, significant correlations between neuropsychological performance on the memory task and increased functional connectivity were found in aMCI patients (Table 4).
Discussion In normal aging individuals, the episodic memory network includes a tight complex of interconnections with the hippocam-
F. Bai et al. pus, including medial temporal lobe, posterior cingulate, basal ganglia, frontal lobe, cerebellum, and temporal lobe. This is consistent with previous episodic memory-related studies (10,29,30). Three main findings are noted in this study: first, in aMCI a tendency of decreased functional connectivity in prefrontal lobe, temporal lobe, parietal lobe, and cerebellum is noted; second, increased functional connectivity was observed in an abnormally diffuse or loosened distributed network of connections within these same brain regions; finally, the degree of divergence of hippocampal connectivity patterns within the episodic memory network is significantly related to the cognitive impairment noted in the aMCI group. These changes in connectivity would be consistent with evidence of early functional abnormalities within the episodic memory system in aMCI patients. Compared with their normal aging peers, aMCI patients displayed loosened connectivity between the prefrontal lobe, temporal lobe, parietal lobe and cerebellum, and hippocampal structures bilaterally. This is consistent with previous episodic memory task-related studies, which showed hypoactivity in these brain regions in MCI subjects, compared with healthy subjects (31,32). However, this functional connectivity study confirms that the episodic memory retrieval process relies on a highly interconnected neural circuit. This is consistent with existing models that propose a complicated distributed network underpinning episodic memory function (29). In addition, this study
Table 4. Significant Correlations Between Neuropsychological Data and Increased Functional Connectivity in aMCI Subjects Neuropsychological Scale L Hippocampus
MMSE Auditory Verbal Memory Test—Delayed Recall
R Hippocampus
Trail Making Test—A Auditory Verbal Memory Test—delayed recall
Trail Making Test—A Trail Making Test—B
Rey-Osterrieth Complex Figure Test—delayed recall
Increased Functional Connectivity
Spearman’s Correlation Coefficient
p Values
L superior frontal gyrus L subcallosal gyrus L superior frontal gyrus L medial frontal gyrus L subcallosal gyrus L inferior frontal gyrus R inferior frontal gyrus R inferior temporal gyrus Bilateral parahippocampal gyrus R insula L anterior cingulate Bilateral cingulated gyrus R middle occipital gyrus R cerebellum/declive L subcallosal gyrus R superior frontal gyrus R inferior frontal gyrus L middle temporal gyrus/insual R insula/R superior temporal gyrus R putamen L anterior cingulate L cingulated gyrus R cerebellum/culmen R insula/R superior temporal gyrus L superior temporal gyrus L middle temporal gyrus/insual R insula/R superior temporal gyrus R putamen R insula/R superior temporal gyrus L anterior cingulate
⫺.307 ⫺.288 ⫺.391 ⫺.308 ⫺.454 ⫺.311 ⫺.479 ⫺.435 ⫺.415 ⫺.436 ⫺.379 ⫺.339 ⫺.313 ⫺.386 .336 ⫺.402 ⫺.406 ⫺.401 ⫺.431 ⫺.353 ⫺.386 ⫺.328 ⫺.338 .298 .310 .414 .415 .355 ⫺.381 ⫺.354
.034a .047a .006b .033a .001b .031a .001b .002b .003b .002b .008b .018a .030a .007b .021a .005b .004b .005b .002b .014a .007b .023a .019a .042a .034a .004b .004b .014a .008b .015a
aMCI, amnestic mild cognitive impairment; L, left; MMSE, Mini-Mental State Examination; R, right. a p ⬍ .05 statistical significance between neuropsychological data and increased functional connectivity. b p ⬍ .01 statistical significance between neuropsychological data and increased functional connectivity.
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F. Bai et al. noted significantly increased functional connectivity in those brain regions associated with normal episodic memory function in aMCI patients and more extensive subregions compared with control subjects. This study confirms and extends previous findings identifying functional brain abnormalities associated with memory deficits in aMCI and AD patients. Previous studies in AD patients showed increased activation in prefrontal cortex (33,34) and parietal-temporal border (34) and increased activation in left frontal lobe (35) and medial temporal lobe (32) during episodic memory tasks. In addition, a recent AD resting-state study observed increased functional connectivity between hippocampus and prefrontal cortex (18). This discrepancy in findings may partly be related to the degree of cognitive decline and diagnostic criteria for patients and to different fMRI designs. In addition, our study suggests brain regions recruited to compensate for impairments brought about by the functional and structural changes occurring as aMCI progresses are close to these impaired regions. Interestingly, aMCI patients showed a decrease of more than 15% in hippocampal volume and significantly impaired neuropsychological performance compared with control subjects. This is consonant with the observed memory deficits in the aMCI population and the critical role the hippocampus is known to play in episodic memory (3). However, because the patients had the same task accuracy levels as healthy control subjects, there is support for the idea that at the aMCI stage of AD, the compensatory mechanisms are capable of maintaining near-normal performance in many high-level cognitive tasks. A novel finding in this study was the identification of a negative correlation between brain regions with increased functional connectivity and the performance of neuropsychological tests, especially episodic memory (Auditory Verbal Memory Test—Delayed Recall and Rey-Osterrieth Complex Figure Test— Delayed Recall). Whereas the hippocampus seems to play a major role for episodic memory, which is substantially impaired in AD, prefrontal cortex (29), parietal cortex (36), lateral temporal cortex (37), and cerebellum (38) are also subsumed in the neuronal substrate of episodic memory. This study confirms a clinically relevant role for the hippocampus in how this neuronal substrate breaks down in the course of AD. The established negative correlation shows that as hippocampal changes induce increased cognitive impairment functional connectivity is loosened and increasingly diffuse connections are established in an attempt to counter the induced functional decline. It appears that in the early stages of AD, as seen in aMCI, this process is partially successful. Thus, on the basis of the interaction of this distributed network of brain regions, it was not surprising to find that the successful task performance was found in aMCI patients. The study has several limitations. First, it was cross-sectional and a small sample size, so it remains to be seen whether the functional connectivity findings here in aMCI are in any way related to a progression to AD. Further studies are necessary to follow-up such patients and examine whether disturbed functional connectivity can act as a biomarker for cognitive dysfunction in AD-related illness progression. Second, given that a previous study reported close links between the “default mode” (resting) network and episodic memory function (39), it would have been useful have taken into account group differences in resting cerebral blood flow in our study. In the future, it is reasonable to explore brain functional changes through multimodality approaches. In summary, this study augments current data available on functional connectivity in episodic memory networks and offers
BIOL PSYCHIATRY 2009;65:951–958 957 clues to the pattern of abnormal integrity of these networks in aMCI patients and their relationship to hippocampal structure and function. In addition, the identification of regions of higher functional connectivity would be consistent with the idea of active compensatory processes being engaged in these subjects to compensate for the mounting neuropathologic changes involving memory mechanisms. Thus, the connectivity approach may be able to assist with the objective of early detection of disease processes that presage the development of AD.
This research was supported in part by the National Basic Research Program of China (973 Program; Grant No. 2007CB512308 to ZZ), National Hi-Tech Research and Development Program of China (863 Program; Grant No. 2007AA0200Z435 to ZZ), National Natural Science Foundation of China (No. 300770779 to ZZ), and Chinese-Finnish NEURO program from Natural Science Foundation of China (Grant No. 30621130074 to YZ). We thank Professor Jiang Tian-Zi and Dr. Liu Yong, Institute of Automation, Chinese Academy of Sciences, for technical support and advice. The authors reported no biomedical financial interests or potential conflicts of interest. 1. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E (1999): Mild cognitive impairment, clinical characterization and outcome. Arch Neurol 56:303–308. 2. Morris JC, Storandt M, Miller JP, McKeel DW, Price JL, Rubin EH, et al. (2001): Mild cognitive impairment represents early-stage Alzheimer disease. Arch Neurol 58:397– 405. 3. Braak H, Braak E (1995): Staging of Alzheimer’s disease-related neurofibrillary tangles. Neurobiol Aging 16:271–284. 4. Dickerson BC, Goncharova I, Sullivan MP, Forchetti C, Wilson RS, Bennett DA, et al. (2001): MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol Aging 22: 747–754. 5. Bottino CM, Castro CC, Gomes RL, Buchpiguel CA, Marchetti RL, Neto MR (2002): Volumetric MRI measurements can differentiate Alzheimer’s disease, mild cognitive impairment, and normal aging. Int Psychogeriatr 14:59 –72. 6. Chetelat G, Baron JC (2003): Early diagnosis of Alzheimer’s disease: Contribution of structural neuroimaging. Neuroimage 18:525–541. 7. Pennanen C, Kivipelto M, Tuomainen S, Hartikainen P, Hänninen T, Laakso MP, et al. (2004): Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging 25:303–310. 8. Johnson SC, Schmitz TW, Moritz CH, Meyerand ME, Rowley HA, Alexander AL, et al. (2006): Activation of brain regions vulnerable to Alzheimer’s disease: The effect of mild cognitive impairment. Neurobiol Aging 27:1604 –1612. 9. Gainotti G, Marra C, Villa G, Parlato V, Chiarotti F (1998): Sensitivity and specificity of some neuropsychological markers of Alzheimer dementia. Alzheimer Dis Assoc Disord 12:152–162. 10. Budson AE, Price BH (2005): Memory Dysfunction. N Engl J Med 352:692– 699. 11. Cabeza R, Nyberg L (2000): Neural bases of learning and memory: functional neuroimaging evidence. Curr Opin Neurol 13:415– 421. 12. Remy F, Mirrashed F, Campbell B, Richter W (2005): Verbal episodic memory impairment in Alzheimer’s disease: A combined structural and functional MRI study. Neuroimage 25:253–266. 13. Ries ML, Schmitz TW, Kawahara TN, Torgerson BM, Trivedi MA, Johnson SC (2006): Task-dependent posterior cingulate activation in mild cognitive impairment. Neuroimage 29:485– 492. 14. Kircher TT, Weis S, Freymann K, Erb M, Jessen F, Grodd W, et al. (2007): Hippocampal activation in patients with mild cognitive impairment is necessary for successful memory encoding. J Neurol Neurosurg Psychiatry 78:812– 818. 15. Friston KJ, Frith CD, Fletcher P, Liddle PF, Frackowiak RS (1996): Functional topography: Multidimensional scaling and functional connectivity in the brain. Cereb Cortex 6:156 –164.
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958 BIOL PSYCHIATRY 2009;65:951–958 16. Friston KJ, Frith CD, Liddle PF, Frackowiak RS (1993): Functional connectivity: The principalcomponent analysis of large (PET) data sets. J Cereb Blood Flow Metab 13:5–14. 17. Allen G, Barnard H, McColl R, Hester AL, Fields JA, Weiner MF, et al. (2007): Reduced hippocampal functional connectivity in Alzheimer disease. Arch Neurol 64:1482–1487. 18. Wang L, Zang YF, He Y, Liang M, Zhang X, Tian L, et al. (2006): Changes in hippocampal connectivity in the early stages of Alzheimer’s disease: Evidence from resting state fMRI. Neuroimage 31:496 –504. 19. Grady CL, Furey ML, Pietrini P, Horwitz B, Rapoport SI (2001): Altered brain functional connectivity and impaired short-term memory in Alzheimer’s disease. Brain 124:739 –756. 20. Lang PJ, Bradley MM, Cuthbert BN (2005): International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual (Technical Report A-6). University of Florida, Gainesville, FL. 21. Watson C, Andermann F, Gloor P, Jones-Gotman M, Peters A, Evans A, et al. (1992): Anatomic basis of amygdaloid and hippocampal volume measurement by magnetic resonance imaging. Neurology 42:1743– 1750. 22. Duvernoy HM (1998): The Human Hippocampus: Functional Anatomy, Vascularization and Series Sections with MRI, 2nd ed. Berlin: SpringerVerlag. 23. Bokde ALW, Lopez-Bayo P, Meindl T, Pechler S, Born C, Faltraco F, et al. (2006): Functional connectivity of the fusiform gyrus during a facematching task in subjects with mild cognitive impairment. Brain 129: 1113–1124. 24. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. (2002): Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI singlesubject brain. Neuroimage 15:273–289. 25. Maldjian JA, Laurienti PJ, Burdette JH (2004): Precentral gyrus discrepancy in electronic versions of the Talairach atlas. Neuroimage 21:450 – 455. 26. Maldjian JA, Laurienti PJ, Kraft RA, Burdette JB (2003): An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19:1233–1239.
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F. Bai et al. 27. Lowe MJ, Mock BJ, Sorenson JA (1998): Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7:119 –132. 28. Fischer P, Jungwirth S, Zehetmayer S, Weissgram S, Hoenigschnabl S, Gelpi E, et al. (2007): Conversion from subtypes of mild cognitive impairment to Alzheimer dementia. Neurology 68:288 –289. 29. Simons JS, Spies HJ (2003): Prefrontal and medial temporal lobe interactions in long-term memory. Nature 4:637– 648. 30. Wagner AD, Shannon BJ, Kahn I, Buckner RL (2005): Parietal lobe contributions to episodic memory retrieval. Trends Cogn Sci 9:445– 453. 31. Machulda MM, Ward HA, Borowski B, Gunter JL, Cha RH, O’Brien PC, et al. (2003): Comparison of memory fMRI response among normal, MCI, and Alzheimer’s patients. Neurology 61:500 –506. 32. Dickerson BC, Salat DH, Greve DN, Chua EF, Rand-Giovannetti E, Rentz DM, et al. (2005): Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD. Neurology 65:404 – 411. 33. Becker JT, Mintun MA, Aleva K, Wiseman MB, Nichols T, Dekosky ST (1996): Compensatory reallocation of brain resources supporting verbal episodic memory in Alzheimer’s disease. Neurology 46:692–700. 34. Grady CL, McIntosh AR, Beig S, Keightley ML, Burian H, Black SE (2003): Evidence from functional neuroimaging of a compensatory prefrontal network in Alzheimer’s disease. J Neurosci 23:986 –993. 35. Moulin CJ, Laine M, Rinne JO, Kaasinen V, SipilŠ H, Hiltunen J, et al. (2007): Brain function during multi-trial learning in mild cognitive impairment: A PET activation study. Brain Res 1136:132–141. 36. Cabeza R (2008): Role of parietal regions in episodic memory retrieval: The dual attentional processes hypothesis. Neuropsychologia 46:1813– 1827. 37. Kirchoff BA, Wagner AD, Maril A, Stern CE (2000): Prefrontal-temporal circuitry for episodic encoding and subsequent memory. J Neurosci 20:6173– 6180. 38. Fliessbach K, Trautner P, Quesada CM, Elger CE, Weber B (2007): Cerebellar contributions to episodic memory encoding as revealed by fMRI. Neuroimage 36:1361–1373. 39. Greicius MD, Srivastava G, Reiss AL, Menon V (2004): Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proc Natl Acad Sci 101:4637– 4642.
A
mnestic mild cognitive impairment (aMCI) (1) is believed to be an intermediate state between normal aging and dementia, which is at present the most valid conceptual indicator of incipient or early Alzheimer’s disease (AD) (2). The predominant cognitive deficits present in aMCI are related to learning and memory function. The first pathological changes that appear as AD develops are in hippocampus areas, and at the end stage of the disease these regions are also the ones most severely affected (3). Previous studies suggested that reduction in hippocampal volume represents the most important structural hallmark of conversion from mild cognitive impairment (MCI) to AD (4 –7). Neuroimaging techniques for assessing hippocampal function may be extremely useful in the evaluation of disease development and trajectory and its related pathology (8). In general, episodic memory is a typical impairment in AD (9) and refers to the ability to retain, recall, and encode information related to personal events and experiences occurring at specific From the School of Clinical Medicine (FB, ZZ, HY, YS, YY, YQ), Southeast University, and Department of Neurology (FB, ZZ, HY, YS, YQ), Affiliated ZhongDa Hospital of Southeast University, Nanjing, China; Psychiatry and Neuroscience (DRW), School of Medicine and Dentistry, Queen’s University Belfast, United Kingdom; Department of Psychiatry (YY), Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China; and State Key Laboratory of Cognitive Neuroscience and Learning (YZ, CZ), Beijing Normal University, Beijing, China. Address reprint requests to Zhijun Zhang, Ph.D., M.D., The Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, No. 87 DingJiaQiao, Nanjing, Jiangsu 210009 China; E-mail: zhijunzhang838@yahoo. com.cn. Received June 3, 2008; revised October 9, 2008; accepted October 9, 2008.
0006-3223/09/$36.00 doi:10.1016/j.biopsych.2008.10.017
times and places (10). Human studies have demonstrated that the hippocampus has a key role in episodic memory processing (11). Therefore, it is reasonable that structural and functional changes in the hippocampus are likely to be important in understanding the origins of impaired memory function in AD. Functional neuroimaging studies have shown abnormal activation of hippocampus during episodic memory tasks in both AD (12) and MCI patients (8,13,14). However, the processes involved in all forms of higher cognitive function are not isolated to specific brain regions but instead result from highly interconnected neural circuits encompassing often remote brain regions. Therefore, it is important to explore the connections among neural circuits underpinning episodic memory function if we are to better understand how they may differ between sufferers of AD or aMCI and normal subjects. Functional connectivity analysis is a technique for the in vivo examination of brain regions cooperating during rest or task performance and provides a measure of the temporal correlation between neurophysiological activities in different brain regions (15,16). Two recent AD-related studies reported decreased functional connectivity in the resting-state between the hippocampus and diffuse cortical, subcortical, and cerebellar sites (17,18). In addition, Grady et al. (19), using a face memory task, concluded that AD patients had a functional disconnection between hippocampus and prefrontal cortex and suggested that memory breakdown is related to a reduction in the integrated activity within a distributed network that includes these two areas. However, the state of functional connectivity between hippocampus and other regions of the brain remains unclear in aMCI patients. This study examined functional connectivity between hippocampus and other regions during an episodic memory retrieval task. Investigations of episodic memory retrieval in AD BIOL PSYCHIATRY 2009;65:951–958 © 2009 Society of Biological Psychiatry
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patients using the same task (8,13) showed that although task performance ability was unimpaired in such groups compared with normally aging control subjects, their retrieval capacity was significantly reduced. Given the key role of the hippocampus in AD-related pathology, it is reasonable to expect aMCI patients to be able to perform the task without difficulty but also display retrieval dysfunction. We predict that, compared with normal aging subjects, this retrieval difficulty will be associated with differences in hippocampus connectivity measures. To our knowledge, this is the first study of hippocampus connectivity under episodic memory retrieval task conditions in aMCI patients.
Methods and Materials Subjects We recruited 59 elderly individuals (all Chinese Han and right-handed) made up of 34 aMCI patients and 25 healthy control subjects through normal community health screening and newspaper advertisements. All aMCI patients met the diagnostic criteria proposed by Petersen et al. (1) including 1) subjective memory impairment corroborated by subject and an informant; 2) objective memory performances documented by the Auditory Verbal Learning Test—Delayed Recall score that is ⱕ 1.5 SD of age-adjusted and education-adjusted norms (the cutoff was ⱕ 4 correct responses on 12 items for ⱖ 8 years of education); 3) normal general cognitive functioning evaluated by a Mini-Mental State Exam (MMSE) score of 24 or higher; 4) a Clinical Dementia Rating of .5, with at least a .5 in the memory domain; 5) no or minimal impairment in activities of daily living; 6) absence of dementia or insufficient level to meet the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association criteria for AD. The inclusion assessment was performed by an experienced neuropsychiatrist who administered a structured interview to subjects and their informants. Participants were excluded from the study if they had a past history of known stroke (modified Hachinski score ⬎ 4), alcoholism, head injury, Parkinson’s Table 1. Demographic and Neuropsychological Data Between Groups aMCI Subjects (n ⫽ 28)
Normal Aging (n ⫽ 23)
Items
Mean
SD
Mean
SD
p
Age (Years) Education Level (Years) Sex (Male:Female) Clinical Dementia Rating Mini-Mental State Exam Auditory Verbal Memory Test— Delayed Recall Rey-Osterrieth Complex Figure Test—Delayed Recall Trail Making Test—A Trail Making Test—B Symbol Digit Modalities Test Clock Drawing Test Digit Span Test
72.5 14.7 17:11 .5 27.1b
4.3 2.4 — — 1.6
70.4 14.7 13:10 0 28.4
5.3 3.4 — — 1.4
ns ns ns .005
2.8b
1.9
8.3
2.0
.000
10.8a 95.8a 183.4a 28.5 8.7 12.3
7.7 35.2 71.1 10.6 1.2 1.6
17.0 72.9 134.3 33.3 8.8 12.9
7.1 25.7 34.8 8.0 1.1 2.1
.018 .021 .024 ns ns .012
Values are mean (SD); p ⬍ .05. aMCI, amnestic mild cognitive impairment. a p ⬍ .05 statistical difference between groups. b p ⬍ .01 statistical difference between groups.
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Table 2. Comparison of the Behavioral Data of Episodic Memory Retrieval Task Between and Within Groups Items
Reaction Time (msec)—Old Reaction Time (msec)—New Accuracy
aMCI Subjects
Control Subjects
Mean (msec)
SD
Mean (msec)
SD
958.7
126.8
804.2
119.4
1113.4 96.1%
207.1 .03
895.2 96.7%
159.7 .04
Between groups and within groups, there were significant differences between response times to old pictures and new pictures, p ⬍ .001. There was no significant difference in accuracy between groups, p ⬎ .05. aMCI, amnestic mild cognitive impairment.
disease, epilepsy, major depression (excluded by Self-Rating Depression Scale) or other neurological or psychiatric illness (excluded by clinical assessment and case history), major medical illness (e.g., cancer, anemia, thyroid dysfunction), or severe visual or hearing loss. In addition, none of aMCI subjects was on cognitive enhancing therapies. Control subjects were required to have a Clinical Dementia Rating of 0, a MMSE score ⱖ 26, and a Delayed Recall score ⬎ 4 for those with 8 or more years of education. The study was approved by the Research Ethics Committee of Affiliated ZhongDa Hospital, Southeast University, and written informed consent was obtained from all participants. Functional Magnetic Resonance Imaging (fMRI) Activation Task The associative episodic recognition task involved serial presentation of color photographs with neutral mood, which were obtained from the International Affective Picture System (20). This task consisted of two identical training sessions and one scanning session. The first training session was carried out 45 min before the scanning session, and the second training session was performed 15 min before the scanning session. Each training session consisted of five pictures and each picture was presented repeatedly 15 times in a pseudorandom pattern. Participants were asked to view the training pictures and try to remember them. The pictures presented in the training sessions were designated as “old” pictures in the test session. The scanning session consisted of 90 exposures, including 45 “old” pictures that appeared pseudorandomly as one, two, three, four, or five consecutive items and 45 “new” pictures that were presented once each, pseudorandomly. The “old” pictures were intermixed with the “new” pictures pseudorandomly. Every picture was presented for 2800 msec with 200-msec interstimulus interval. During scanning the participants had to judge whether the presented picture was “old” or “new.” To indicate their choice they used a two-bottom fiber-optic box held in the right hand: the index finger was used to respond to “old” pictures and the middle finger to respond to “new” pictures. The Presentation application recorded these button responses. The scanning session duration was 4 min and 36 sec, and the first 6 sec contained word cues to ready the participants. Magnetic Resonance Imaging Procedures Subjects were scanned using a 1.5-Tesla scanner (General Electric Medical Systems, Milwaukee, Wisconsin) with a homogeneous birdcage head coil. High-resolution T1-weighted axial images covering the whole brain were acquired using a three-dimensional spoiled gradient echo sequence: repetition time (TR) ⫽ 9.9 msec; echo time (TE) ⫽ 2.1 msec; flip angle
F. Bai et al. (FA) ⫽ 150°; acquisition matrix ⫽ 256 ⫻ 192; field of view (FOV) ⫽ 240 ⫻ 240 mm; thickness ⫽2.0 mm; gap ⫽ 0 mm; number of excitations (NEX) ⫽ 1.0. Functional scans (T2 images) involved the acquisition of 30 contiguous axial slices using a gradient-recalled echo-planar imaging pulse sequence: TR ⫽ 3000 msec; TE ⫽ 40 msec; FA ⫽ 90°; acquisition matrix ⫽ 64 ⫻ 64; FOV ⫽ 240 ⫻ 240 mm; thickness ⫽ 4.0 mm; gap ⫽ 0 mm and 3.75 ⫻ 3.75 mm2 in-plane resolution; NEX ⫽ 1.0. All present subjects with good compliance were scanned in the daytime, while none of subjects without upset before and during scan. Image Data Analysis Structural Data Analysis. Anatomic guidelines for the hippocampus were based on the work of Watson et al. (21) with a standard neuroanatomic atlas (22) as a guide and manually outlining the periphery of the regions of interest (ROI), delineated using a mouse-driven cursor separately for the left and right hemispheres from T1-weighted coronal images on a plane perpendicular to hippocampal major axis. The MRIcro software, version 3.9 (C. Rorden, www.mricro.com) was employed to draw the ROIs. MATLAB software, version 7.0 (Mathworks,
BIOL PSYCHIATRY 2009;65:951–958 953 Sherborn, Massachusetts) calculated the ROI volume by multiplying the number of voxels in the ROI by the size of each voxel.
Functional Data Analysis Image Preprocessing. Analyses were conducted with Statistical Parametric Mapping software (www.fil.ion.ucl.ac.uk/spm). The first two volumes of the scanning session were discarded to allow for T1 equilibration effects. The remaining images were corrected for the timing differences between each slice and motion effects (six-parameter rigid body). Participants with head motion greater than 2.5-mm maximum displacement in any direction or 2.5° of angular motion during the scan were excluded from final analysis. The remaining images were spatially normalized into a standard stereotaxic space using a 12-parameter affine approach and an echo planar image template image and resampled to 3 ⫻ 3 ⫻ 3 mm3 voxels, and smoothed with a Gaussian kernel of 4 ⫻ 4 ⫻ 4 mm (full-width half-maximum [FWHM]). Linear trends were removed from the image time series and the time series was high pass filtered with a filter cutoff of .01 Hz (23).
Figure 1. Brain regions show significant connectivity to the bilateral hippocampus in amnestic mild cognitive impairment (aMCI) and control group. Voxels with p ⬍ 1 ⫻ 10– 6 and cluster size 432 mm3. (Note: use of threshold for the two groups was for visual purposes only.)
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Figure 2. Distribution of decreased functional connectivity of left hippocampus (A) and right hippocampus (B) in amnestic mild cognitive impairment patients compared with healthy control subjects. Voxels with p ⬍ .05 and cluster size 432 mm3.
Figure 3. Distribution of increased functional connectivity of left hippocampus and right hippocampus in amnestic mild cognitive impairment (aMCI) patients compared with healthy control subjects. L, left; R, right; 1. R cerebellum/declive; 2. R inferior temporal gyrus; 3. L subcallosal gyrus; 4. L anterior cingulated; 5. R inferior frontal gyrus; 6. L inferior frontal gyrus; 7. R insula; 8. R parahippocampal gyrus; 9. L parahippocampal gyrus; 10. R middle occipital gyrus; 11. bilateral cingulated gyrus; 12. L superior frontal gyrus; 13. R precuneus; 14. L precuneus; 15. L medial frontal gyrus; 16. L superior temporal gyrus; 17. L anterior cingulated; 18. R parahippocampal gyrus; 19. L middle temporal gyrus; 20. R inferior frontal gyrus; 21. L inferior frontal gyrus; 22. R putamen; 23. L insula; 24.R insula/ R superior temporal gyrus; 25. R cerebellum/ culmen; 26. R superior frontal gyrus; 27. R cuneus; 28. L cingulated gyrus; 29. L medial frontal gyrus. Voxels with p ⬍ .005 and cluster size 432 mm3 were taken as being significantly connected to the hippocampus. These criteria met corrected threshold of p ⬍ .0004.
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F. Bai et al. Finally, seven participants (five aMCI patients and two control subjects) with major head motion and one aMCI participant with poor quality of image were excluded from study. Functional Connectivity Analyses. For each subject, a mean time series for hippocampal formation (left and right separately) was computed for each subject. This region of interest, using automated anatomic labeling (24) implemented with wfu_PickAtlas software (25,26), was used to test our a priori hypothesis regarding the hippocampus. The cross-correlation analysis was then carried out between mean signal change and the time series of all other voxels in the whole brain. Six motion parameters were included as regressors of no interest. Finally, a Fisher’s z transform was applied to improve the normality of the correlation coefficients (18,27). To determine brain regions showing significant connectivity to the left and right hippocampus within each group, the individual z value was entered into a random effect, one-sample t test in a voxelwise manner. To remove possible effects of hippocampal atrophy on the results, “normalized” hippocampal volume, namely (raw hippocampal volume / total intracranial volume) ⫻ 1000 (28), obtained from the structural scan ROI data, was introduced as a covariate into a random effects, two-sample t test in a voxelwise manner to identify the regions showing significant differences in connectivity to the left and right hippocampus between the groups. Group Statistical Maps. Within experimental groups (aMCI patients ⫽ 28; control subjects ⫽ 23), voxels with p ⬍ 1 ⫻ 10– 6 and cluster size ⬎ 432 mm3 was used to show significant connectivity to the left and right hippocampus. These differences were still significant after correction for multiple comparisons. Between experimental groups a single voxel threshold was set at p ⬍ .005, and a minimum cluster size of 432 mm3 was used to correct for multiple comparisons. This yielded a corrected threshold of p ⬍ .0004, determined by Monte Carlo simulation (see program AlphaSim by D. Ward. Parameters were: single voxel p value ⫽ .005, FWHM ⫽ 4 mm, with mask. Also see http:// afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf). Statistical Analysis Nonparametric Mann-Whitney U tests were used for group comparisons of demographic, neuropsychological performances and hippocampal volume (statistical significance was set at p ⬍ .05). A further correlation analysis between fMRI data and neuropsychological performances was performed: masks were created for the regions where significant differences in functional connectivity between groups were found. Second, mean z values of abnormal functional connectivity were calculated for these cluster masks within every aMCI patient. These analyses were performed using a semiautomated imaging analysis program developed at Institute of Automation, Chinese Academy of Sciences (WL Zhu). Finally, correlative analyses were performed to examine relationships between these connectivity z values and neuropsychological performance using SPSS 11.5 software (SPSS, Chicago, Illinois).
Results Demographic and Neuropsychological Data Demographic characteristics and neuropsychological scores are shown in Table 1. Compared with healthy aging subjects, aMCI patients had poor performances in Auditory Verbal Memory Test, Rey-Osterrieth Complex Figure Test, Trail Making Test—A and B, and Digit Span Test; other test battery indices showed no significant differences between groups.
Behavioral Data There were no significant differences in the performance of the memory task between the two groups. Both groups demonstrated better than 96% average accuracy for recognition of the pictures following their scanning session, whereas aMCI patients showed increased reaction time than control subjects (Table 2). Structural Data-Group Comparison The volumes extracted from the manual segmentation of hippocampus for the groups show that hippocampal volumes of aMCI patients group were 15.8% smaller on the left side (p ⬍ .004) and 18.2% smaller on the right side (p ⬍ .001) than their normal aging peers. Functional Connectivity Data-Within Group Comparison In the normal aging group, the left and right hippocampus showed significant connectivity to the medial temporal lobe, Table 3. Increased Functional Connectivity of Hippocampus in aMCI Patients Compared with Healthy Control Subjects
Brain Region
BA
Peak Talairach Coordiates x, y, z (mm)
L Hippocampus Increased Functional Connectivity L Superior Frontal Gyrus 9 ⫺18 37 34 L Medial Frontal Gyrus 6 ⫺12 ⫺9 53 L Subcallosal Gyrus 25 ⫺3 14 ⫺13 L Inferior Frontal Gyrus 47 ⫺30 20 ⫺4 R Inferior Frontal Gyrus 47 48 17 ⫺6 R Inferior Temporal Gyrus 20 39 ⫺16 ⫺27 R Parahippocampal Gyrus 27 15 ⫺32 ⫺1 L Parahippocampal Gyrus 30 ⫺3 ⫺41 2 R Insula 13 39 ⫺3 ⫺5 R Precuneus 7 6 ⫺33 46 L Precuneus 7 ⫺3 ⫺35 49 L Anterior Cingulate 32 ⫺12 41 ⫺5 Bilateral Cingulated Gyrus 31 0 ⫺36 29 R Middle Occipital Gyrus 19 39 ⫺78 15 R Cerebellum/Declive — 21 ⫺80 ⫺21 R Hippocampus Increased Functional Connectivity R Superior Frontal Gyrus 10 12 70 1 L Medial Frontal Gyrus 6 ⫺12 ⫺9 53 L Inferior Frontal Gyrus 47 ⫺30 20 ⫺9 R Inferior Frontal Gyrus 47 33 23 ⫺4 L Superior Temporal 38 ⫺50 2 ⫺10 Gyrus L Middle Temporal Gyrus 21 ⫺45 ⫺29 ⫺4 L Insula 13 ⫺36 ⫺15 ⫺7 R Parahippocampal Gyrus 28 27 ⫺24 ⫺6 R Putamen — 30 ⫺6 ⫺2 R Insula 13 42 ⫺17 1 R Superior Temporal Gyrus 41 45 ⫺29 4 L Anterior Cingulate 32 ⫺5 46 ⫺5 L Cingulated Gyrus 31 ⫺15 ⫺39 32 R Cuneus 18 24 ⫺80 23 R Cerebellum/Culmen — ⫺3 ⫺49 2
Peak T Score
Cluster Size
3.40 3.65 3.90 3.48 3.81 4.26 3.77 3.64 3.86 3.90 3.57 3.64 3.63 3.70 3.78
567 729 459 1836 2349 810 3159
4.16 3.31 3.50 4.11 3.56
486 513 1350 972 864
4.19 4.07 3.65 3.67 4.13 3.63 3.14 3.96 4.61 4.28
1674
1188 783 891 486 783 756
918 1080 1917 621 621 945 459
a MCI, amnestic mild cognitive impairment; BA, Brodmann’s area; L, left; R, right. Secondary peaks are italic; cluster size is in mm3. Voxels with p ⬍ .005 and cluster size 432 mm3 were considered to be significantly connected to the hippocampus. These criteria met corrected threshold of p ⬍ .0004.
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956 BIOL PSYCHIATRY 2009;65:951–958 posterior cingulated gyrus, basal ganglia, temporal lobe, and frontal lobe. These regions overlap with regions known to contribute to the episodic memory network. A similar pattern was noted in the aMCI group, but visual comparison of the maps suggested that the magnitude and extent of hippocampal connectivity to frontal lobe, temporal lobe, parietal lobe, and cerebellum in these patients was greater than observed in the control group data. (Figure 1). Functional Connectivity Data-Between Group Comparisons After correction for multiple comparisons, aMCI patients showed a trend toward impaired functional connectivity in prefrontal lobe, temporal lobe, parietal lobe, and cerebellum (voxels with p ⬍ .05 and cluster size 432 mm3; Figure 2). The functional connectivity analysis of the left and right hippocampus revealed extensive regions with significantly higher functional connectivity in the aMCI patients compared with their control subjects, mainly in diffuse areas of prefrontal lobe, temporal lobe, parietal lobe, and cerebellum (corrected threshold of p ⬍ .0004 by multiple comparisons; Figure 3, Table 3). In addition, significant correlations between neuropsychological performance on the memory task and increased functional connectivity were found in aMCI patients (Table 4).
Discussion In normal aging individuals, the episodic memory network includes a tight complex of interconnections with the hippocam-
F. Bai et al. pus, including medial temporal lobe, posterior cingulate, basal ganglia, frontal lobe, cerebellum, and temporal lobe. This is consistent with previous episodic memory-related studies (10,29,30). Three main findings are noted in this study: first, in aMCI a tendency of decreased functional connectivity in prefrontal lobe, temporal lobe, parietal lobe, and cerebellum is noted; second, increased functional connectivity was observed in an abnormally diffuse or loosened distributed network of connections within these same brain regions; finally, the degree of divergence of hippocampal connectivity patterns within the episodic memory network is significantly related to the cognitive impairment noted in the aMCI group. These changes in connectivity would be consistent with evidence of early functional abnormalities within the episodic memory system in aMCI patients. Compared with their normal aging peers, aMCI patients displayed loosened connectivity between the prefrontal lobe, temporal lobe, parietal lobe and cerebellum, and hippocampal structures bilaterally. This is consistent with previous episodic memory task-related studies, which showed hypoactivity in these brain regions in MCI subjects, compared with healthy subjects (31,32). However, this functional connectivity study confirms that the episodic memory retrieval process relies on a highly interconnected neural circuit. This is consistent with existing models that propose a complicated distributed network underpinning episodic memory function (29). In addition, this study
Table 4. Significant Correlations Between Neuropsychological Data and Increased Functional Connectivity in aMCI Subjects Neuropsychological Scale L Hippocampus
MMSE Auditory Verbal Memory Test—Delayed Recall
R Hippocampus
Trail Making Test—A Auditory Verbal Memory Test—delayed recall
Trail Making Test—A Trail Making Test—B
Rey-Osterrieth Complex Figure Test—delayed recall
Increased Functional Connectivity
Spearman’s Correlation Coefficient
p Values
L superior frontal gyrus L subcallosal gyrus L superior frontal gyrus L medial frontal gyrus L subcallosal gyrus L inferior frontal gyrus R inferior frontal gyrus R inferior temporal gyrus Bilateral parahippocampal gyrus R insula L anterior cingulate Bilateral cingulated gyrus R middle occipital gyrus R cerebellum/declive L subcallosal gyrus R superior frontal gyrus R inferior frontal gyrus L middle temporal gyrus/insual R insula/R superior temporal gyrus R putamen L anterior cingulate L cingulated gyrus R cerebellum/culmen R insula/R superior temporal gyrus L superior temporal gyrus L middle temporal gyrus/insual R insula/R superior temporal gyrus R putamen R insula/R superior temporal gyrus L anterior cingulate
⫺.307 ⫺.288 ⫺.391 ⫺.308 ⫺.454 ⫺.311 ⫺.479 ⫺.435 ⫺.415 ⫺.436 ⫺.379 ⫺.339 ⫺.313 ⫺.386 .336 ⫺.402 ⫺.406 ⫺.401 ⫺.431 ⫺.353 ⫺.386 ⫺.328 ⫺.338 .298 .310 .414 .415 .355 ⫺.381 ⫺.354
.034a .047a .006b .033a .001b .031a .001b .002b .003b .002b .008b .018a .030a .007b .021a .005b .004b .005b .002b .014a .007b .023a .019a .042a .034a .004b .004b .014a .008b .015a
aMCI, amnestic mild cognitive impairment; L, left; MMSE, Mini-Mental State Examination; R, right. a p ⬍ .05 statistical significance between neuropsychological data and increased functional connectivity. b p ⬍ .01 statistical significance between neuropsychological data and increased functional connectivity.
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F. Bai et al. noted significantly increased functional connectivity in those brain regions associated with normal episodic memory function in aMCI patients and more extensive subregions compared with control subjects. This study confirms and extends previous findings identifying functional brain abnormalities associated with memory deficits in aMCI and AD patients. Previous studies in AD patients showed increased activation in prefrontal cortex (33,34) and parietal-temporal border (34) and increased activation in left frontal lobe (35) and medial temporal lobe (32) during episodic memory tasks. In addition, a recent AD resting-state study observed increased functional connectivity between hippocampus and prefrontal cortex (18). This discrepancy in findings may partly be related to the degree of cognitive decline and diagnostic criteria for patients and to different fMRI designs. In addition, our study suggests brain regions recruited to compensate for impairments brought about by the functional and structural changes occurring as aMCI progresses are close to these impaired regions. Interestingly, aMCI patients showed a decrease of more than 15% in hippocampal volume and significantly impaired neuropsychological performance compared with control subjects. This is consonant with the observed memory deficits in the aMCI population and the critical role the hippocampus is known to play in episodic memory (3). However, because the patients had the same task accuracy levels as healthy control subjects, there is support for the idea that at the aMCI stage of AD, the compensatory mechanisms are capable of maintaining near-normal performance in many high-level cognitive tasks. A novel finding in this study was the identification of a negative correlation between brain regions with increased functional connectivity and the performance of neuropsychological tests, especially episodic memory (Auditory Verbal Memory Test—Delayed Recall and Rey-Osterrieth Complex Figure Test— Delayed Recall). Whereas the hippocampus seems to play a major role for episodic memory, which is substantially impaired in AD, prefrontal cortex (29), parietal cortex (36), lateral temporal cortex (37), and cerebellum (38) are also subsumed in the neuronal substrate of episodic memory. This study confirms a clinically relevant role for the hippocampus in how this neuronal substrate breaks down in the course of AD. The established negative correlation shows that as hippocampal changes induce increased cognitive impairment functional connectivity is loosened and increasingly diffuse connections are established in an attempt to counter the induced functional decline. It appears that in the early stages of AD, as seen in aMCI, this process is partially successful. Thus, on the basis of the interaction of this distributed network of brain regions, it was not surprising to find that the successful task performance was found in aMCI patients. The study has several limitations. First, it was cross-sectional and a small sample size, so it remains to be seen whether the functional connectivity findings here in aMCI are in any way related to a progression to AD. Further studies are necessary to follow-up such patients and examine whether disturbed functional connectivity can act as a biomarker for cognitive dysfunction in AD-related illness progression. Second, given that a previous study reported close links between the “default mode” (resting) network and episodic memory function (39), it would have been useful have taken into account group differences in resting cerebral blood flow in our study. In the future, it is reasonable to explore brain functional changes through multimodality approaches. In summary, this study augments current data available on functional connectivity in episodic memory networks and offers
BIOL PSYCHIATRY 2009;65:951–958 957 clues to the pattern of abnormal integrity of these networks in aMCI patients and their relationship to hippocampal structure and function. In addition, the identification of regions of higher functional connectivity would be consistent with the idea of active compensatory processes being engaged in these subjects to compensate for the mounting neuropathologic changes involving memory mechanisms. Thus, the connectivity approach may be able to assist with the objective of early detection of disease processes that presage the development of AD.
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