0
Original Contribution |

Reduced Hippocampal Functional Connectivity in Alzheimer Disease FREE

Greg Allen, PhD; Holly Barnard, MA; Roderick McColl, PhD; Andrea L. Hester, PhD; Julie A. Fields, BA; Myron F. Weiner, MD; Wendy K. Ringe, PhD; Anne M. Lipton, MD, PhD; Matthew Brooker, BS; Elizabeth McDonald, RN; Craig D. Rubin, MD; C. Munro Cullum, PhD
[+] Author Affiliations

Author Affiliations: Departments of Psychiatry (Drs Allen, Hester, Weiner, Ringe, Lipton, and Cullum, Mss Barnard and Fields, and Mr Brooker), Radiology (Dr McColl), Neurology (Drs Weiner, Lipton, and Cullum), and Internal Medicine (Ms McDonald and Dr Rubin), University of Texas Southwestern Medical Center, Dallas; School of Behavioral and Brain Sciences, The University of Texas at Dallas (Dr Allen); Department of Psychology, University of Denver, Denver, Colorado (Ms Bernard); Presbyterian Hospital of Dallas (Dr Lipton); and University of North Texas Health Sciences Center, Texas College of Osteopathic Medicine, Fort Worth (Mr Brooker).


Arch Neurol. 2007;64(10):1482-1487. doi:10.1001/archneur.64.10.1482.
Text Size: A A A
Published online

Objective  To determine if functional connectivity of the hippocampus is reduced in patients with Alzheimer disease.

Design  Functional connectivity magnetic resonance imaging was used to investigate coherence in the magnetic resonance signal between the hippocampus and all other regions of the brain.

Participants  Eight patients with probable Alzheimer disease and 8 healthy volunteers.

Results  Control subjects showed hippocampal functional connectivity with diffuse cortical, subcortical, and cerebellar sites, while patients demonstrated markedly reduced functional connectivity, including an absence of connectivity with the frontal lobes.

Conclusion  These findings suggest a functional disconnection between the hippocampus and other brain regions in patients with Alzheimer disease.

Figures in this Article

Alzheimer disease (AD) is the most common type of dementia,1,2 characterized by memory impairment progressing to globally impaired cognition.3 As the human lifespan has increased, so too has the prevalence of AD and widespread concern about this disease, encouraging the search for new modes of early identification and intervention. Recently, neuroimaging techniques have proved to be useful disease-monitoring tools,4,5 prompting further research into their utility for early detection.

An extensive review of the neuroimaging literature6 concluded that volume loss within the hippocampus most reliably discriminates between healthy control subjects and patients with early AD. Furthermore, hippocampal atrophy correlates significantly with decline in cognitive status in patients with AD and mild cognitive impairment,7,8 and may in fact be a predictor of conversion from mild cognitive impairment to AD.9,10 This is consistent with the decline in declarative memory characteristic of AD.3 Thus, neuroimaging techniques for assessing and monitoring hippocampal function may be greatly useful in the evaluation of AD. A new approach to investigating brain function that holds promise for the study of AD is functional connectivity magnetic resonance imaging (FCMRI).

Functional connectivity magnetic resonance imaging is a technique that enables the in vivo examination of functional connections in the brain. It is based on the finding that brain regions that are functionally related show correlated low-frequency fluctuations in the MRI signal11 that arise from the same blood oxygenation level–dependent origins as task-related functional magnetic resonance imaging signal changes.12 Functional connectivity magnetic resonance imaging exploits these correlations to create an image of task-independent functional connectivity. This technique has been used to demonstrate connectivity between homologous regions of the right and left hemisphere (eg, motor,11 visual,13 and auditory cortices14) and other functionally related brain regions (eg, thalamus and hippocampus,15 Broca and Wernicke areas,16 and cerebellum, thalamus, and cerebrocortical sites17). When applied to patients, FCMRI can be used to examine dysfunction at the level of neurofunctional networks. For instance, an FCMRI study comparing patients with AD and mild cognitive impairment with healthy age-matched controls demonstrated decreases in the functional synchrony of the right and left hippocampi along the spectrum from healthy to AD.18 However, this investigation was limited to an examination of connections between the two hippocampi. In contrast, FCMRI was used to examine hippocampal connectivity with the rest of the brain in a mixed group of subjects with mild or “very mild” AD.19 This study reported reduced connectivity between the right hippocampus and several brain regions and increased connectivity between the left hippocampus and the right prefrontal cortex in those with AD. The goal of the present study was to examine a more homogeneous group of subjects with mild AD to gain further insight into the effects of the disease on hippocampal functional connectivity. We hypothesized an overall breakdown in the synchronous activity of neural circuits involving the hippocampus.

Eight patients with probable AD (Table 1) were recruited from the Alzheimer’s Disease Center and the Mildred Wyatt and Ivor P. Wold Center for Geriatric Care at the University of Texas Southwestern Medical Center. Alzheimer disease was diagnosed by a neurologist or geriatrician using National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria.20 Eight healthy volunteers (Table 1) with no history of developmental, psychiatric, or neurological disorders were recruited from the community. All subjects were right-handed. Before participation, the study was described to the subjects and their caregivers. Written informed consent was then obtained from subjects and a family member or legal representative. The University of Texas Southwestern Medical Center institutional review board approved the complete experimental protocol.

Table Graphic Jump LocationTable 1. Characteristics of the 8 Subjects With AD and the 8 Healthy Control Subjects

All subjects were administered a brief neurocognitive battery to ensure a mild level of cognitive impairment in the AD group and to rule out impairment in controls (Table 1). This included the Mini-Mental State Examination,21 the Alzheimer Disease Assessment Scale–cognitive subscale,22 and the logical memory subtest of the Wechsler Memory Scale–Third Edition.23

The magnetic resonance images were acquired at 1.5 T using the standard quadrature birdcage RF head coil (GE Medical Systems, Milwaukee, Wisconsin). A time series of 100 echo-planar image volumes was acquired at 16 axial slice locations through the whole brain while subjects were at rest in a darkened scanner room. Sensory stimulation was limited to the noise of the scanner, which was dampened by earplugs and noise-reducing headphones. The echo-planar image data were acquired with a single-shot gradient-recalled pulse sequence (sequential slice acquisition; repetition time, 2000 milliseconds; echo time, 45 milliseconds; flip angle, 90°; matrix, 64 × 64; field of view, 24 cm; thickness, 7 mm; and gap, 0.5 mm). High-resolution images of the entire brain (3-dimensional spoiled grass pulse sequence: repetition time, 30 milliseconds; echo time, 5 milliseconds; flip angle, 45°; matrix, 256 × 256; field of view, 24 cm; and thickness, 2.0 mm) were also acquired.

All analyses were conducted with the use of Analysis of Functional NeuroImages (AFNI) software.24 First, all data were normalized to the Talairach grid,25 which aided in anatomical localization and allowed the combination of data across subjects and comparison between groups. Subsequent preprocessing steps included slice-timing correction, detrending, motion correction,26 and temporal filtering. Early FCMRI studies demonstrated that coherence in blood oxygenation level–dependent signal fluctuations occurs at low frequencies.11,13,27 Thus, a low-pass filter removed all frequencies of greater than 0.08 Hz. The data were then spatially smoothed with a 3-dimensional gaussian tapering function (5-mm full width at half maximum) to increase the signal-noise ratio.

For each subject, right and left hippocampal “seed volumes” were identified. To ensure that seed volumes were restricted to intact hippocampal tissue in each subject, these volumes were defined as 5 contiguous voxels (at echo-planar image resolution) in the body of the hippocampus (Figure 1). Preprocessed time series echo-planar image signal data were then extracted from these voxels. These data were averaged to create left and right hippocampal signal time courses for each subject, which were used as reference functions for correlation with fluctuations in the magnetic resonance signal in all other brain voxels. The least-squares fit coefficients from these calculations were entered into the group analyses. This same procedure was also conducted using a control seed volume placed in the primary visual cortex.

Place holder to copy figure label and caption
Figure 1.

Left hippocampus seed volume from a single subject overlaid on representative coronal slices.

Graphic Jump Location

Within-group 2-tailed t tests identified sites where the AD or control data were significantly different from 0, while unpaired between-group 2-tailed t tests identified sites of significant group difference. The output from these t tests was thresholded using a voxel-cluster-size method. First, all voxels whose t value did not exceed α = .025 were excluded from further analysis. Then, Monte Carlo simulations were used to determine the probability of falsely detecting clusters of various sizes. Our goal was an overall (ie, over the entire 3-dimensional image volume) significance level of P < .01. Thus, we identified the minimum cluster size that occurred with P < .01 for each comparison. For the left hippocampus, the size for controls was 2004 μL; for patients with AD, 1898 μL; and for controls vs those with AD, 2637 μL. For the right hippocampus, the size for controls was 2004 μL; for patients with AD, 2004 μL; and for controls vs those with AD, 2742 μL. Clusters that exceeded this cutoff were retained.

NEUROPSYCHOLOGICAL TESTING

Control subjects performed within normal limits on the Alzheimer Disease Assessment Scale–cognitive subscale28 and the Mini-Mental State Examination, while subjects with AD were mildly impaired (Table 1). On the logical memory subtest from the Wechsler Memory Scale–Third Edition, all controls performed in the average to above average range on immediate and delayed recall trials (mean scaled scores, 11.6 and 12.0, respectively) and all retained more than 60% of learned information (mean, 80%), ruling out the isolated memory deficit characteristic of mild cognitive impairment.29

HIPPOCAMPAL FUNCTIONAL CONNECTIVITY: WITHIN-GROUP FINDINGS

In controls (Figure 2A), both hippocampi showed extensive functional connectivity with frontal, parietal, occipital, and temporal sites. Connectivity with other limbic regions was also observed, as was connectivity with basal ganglia and cerebellum. In contrast, participants with AD (Figure 2B) showed a much more restricted pattern of connectivity, with a complete absence of connectivity with the frontal lobes.

Place holder to copy figure label and caption
Figure 2.

Connectivity with the left hippocampus in control subjects (A) and in subjects with Alzheimer disease (AD) (B), and increased connectivity in controls vs subjects with AD (C).

Graphic Jump Location
REDUCED HIPPOCAMPAL FUNCTIONAL CONNECTIVITY IN AD

Compared with patients with AD, control subjects demonstrated significantly greater connectivity of the hippocampus throughout the cerebral cortex, limbic areas, subcortical regions, and cerebellum (Table 2 and Table 3 and Figure 2C). While the within-group analysis of subjects with AD indicated a lack of hippocampal-frontal connectivity, the group comparison emphasized much more diffuse reductions in connectivity. In contrast, when the FCMRI analyses were conducted with a primary visual cortex seed volume, no group differences were observed. There were no regions of increased hippocampal connectivity in participants with AD.

Table Graphic Jump LocationTable 2. Sites of Reduced Functional Connectivity (Local Maxima) With the Left Hippocampus in Patients With AD
Table Graphic Jump LocationTable 3. Sites of Reduced Functional Connectivity (Local Maxima) With the Right Hippocampus in Patients With AD

The pathway between the hippocampus and neocortical regions includes the entorhinal cortex and other medial temporal lobe structures.30 Because these areas are some of the first affected in AD, this disease has been thought to involve a breakdown in connectivity between the hippocampus and the rest of the brain.31 In recent years, neuroimaging studies have sought to identify such disconnections. The first of these, which examined activation during a facial, delayed, match-to-sample task,32 found reduced functional connectivity between the right prefrontal cortex and hippocampus in patients with AD. Similarly, Wang et al19 found disrupted connectivity between the right hippocampus and several brain regions in subjects with AD, while connectivity between the left hippocampus and the prefrontal cortex was relatively increased. In contrast to the study by Wang et al, our findings indicate a more extensive disruption of hippocampal connectivity in AD, with no regions of increased connectivity and an absence of hippocampal-frontal connectivity. The most likely explanation for this difference is a greater disease severity in our sample, supporting the notion that hippocampal connectivity declines progressively during the disease.18 When we examined functional connectivity with the primary visual cortex, no group differences were observed, lending support to the specificity of the hippocampal connectivity differences. Dysfunctional circuitry connecting the hippocampus with other brain regions is a likely contributor to deficits in learning and memory and other areas of cognition characteristic of AD, and FCMRI of the hippocampus may ultimately provide an in vivo marker of abnormal hippocampal function in this population. If shown to have adequate sensitivity and specificity, hippocampal FCMRI may also prove useful in the diagnosis and monitoring of AD progression.

Correspondence: Greg Allen, PhD, Department of Psychiatry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9127 (Greg.Allen@UTSouthwestern.edu).

Accepted for Publication: April 2, 2007.

Author Contributions: Dr Allen had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Allen and Cullum. Acquisition of data: Allen, McColl, Weiner, Lipton, McDonald, and Rubin. Analysis and interpretation of data: Allen, Barnard, McColl, Hester, Fields, Ringe, Lipton, and Brooker. Drafting of the manuscript: Allen, Hester, Fields, Weiner, Lipton, and Brooker. Critical revision of the manuscript for important intellectual content: Allen, Barnard, McColl, Hester, Fields, Ringe, Lipton, McDonald, Rubin, and Cullum. Statistical analysis: Allen and Ringe. Obtained funding: Rubin and Cullum. Administrative, technical, and material support: Allen, Barnard, McColl, Hester, Fields, Brooker, McDonald, and Rubin.

Financial Disclosure: Dr Lipton has served as a consultant and received honoraria from Pfizer Inc, Novartis, and Forest Pharmaceuticals. Dr Weiner has received honoraria from Pfizer Inc and Forest Pharmaceuticals.

Funding/Support: This study was supported by a grant from the Margaret and Trammell Crow family.

Additional Contributions: The participants and their families made this research possible; and the reviewers of the manuscript provided many helpful comments and suggestions.

American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994
Fromholt  PBruhn  P Cognitive dysfunction and dementia.  In: Nordhus  IH, VandenBos  GR, Berg  S,Fronholt  P, eds. Clinical Geropsychology. Washington, DC: American Psychological Association; 2003:183-189
Cullum  CMRosenberg  RN Memory loss: when is it Alzheimer disease? JAMA 1998;279 (21) 1689- 1690
PubMed
DeCarli  C The role of neuroimaging in dementia. Clin Geriatr Med 2001;17 (2) 255- 279
PubMed
Rombouts  SABarkhof  FGoekoop  RStam  CJScheltens  P Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: an fMRI study. Hum Brain Mapp 2005;26 (4) 231- 239
PubMed
Zakzanis  KKGraham  SJCampbell  Z A meta-analysis of structural and functional brain imaging in dementia of the Alzheimer's type: a neuroimaging profile. Neuropsychol Rev 2003;13 (1) 1- 18
PubMed
Jack  CR  JrPetersen  RCXu  Y  et al.  Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 2000;55 (4) 484- 489
PubMed
Morris  JCStorandt  MMiller  JP  et al.  Mild cognitive impairment represents early-stage Alzheimer disease. Arch Neurol 2001;58 (3) 397- 405
PubMed
Grundman  MSencakova  DJack  CR  Jr  et al.  Brain MRI hippocampal volume and prediction of clinical status in a mild cognitive impairment trial. J Mol Neurosci 2002;19 (1-2) 23- 27
PubMed
Jack  CR  JrPetersen  RCXu  YC  et al.  Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 1999;52 (7) 1397- 1403
PubMed
Biswal  BYetkin  FZHaughton  VMHyde  JS Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34 (4) 537- 541
PubMed
Peltier  SJNoll  DCT T2* dependence of low frequency functional connectivity. Neuroimage 2002;16 (4) 985- 992
PubMed
Lowe  MJMock  BJSorenson  JA Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 1998;7 (2) 119- 132
PubMed
Cordes  DHaughton  VMArfanakis  K  et al.  Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am J Neuroradiol 2000;21 (9) 1636- 1644
PubMed
Stein  TMoritz  CQuigley  MCordes  DHaughton  VMeyerand  E Functional connectivity in the thalamus and hippocampus studied with functional MR imaging. AJNR Am J Neuroradiol 2000;21 (8) 1397- 1401
PubMed
Hampson  MPeterson  BSSkudlarski  PGatenby  JCGore  JC Detection of functional connectivity using temporal correlations in MR images. Hum Brain Mapp 2002;15 (4) 247- 262
PubMed
Allen  GMcColl  RBarnard  HRinge  WKFleckenstein  JCullum  CM Magnetic resonance imaging of cerebellar-prefrontal and cerebellar-parietal functional connectivity. Neuroimage 2005;28 (1) 39- 48
PubMed
Li  SJLi  ZWu  GZhang  MJFranczak  MAntuono  PG Alzheimer disease. Radiology 2002;225 (1) 253- 259
PubMed
Wang  LZang  YHe  Y  et al.  Changes in hippocampal connectivity in the early stages of Alzheimer's disease. Neuroimage 2006;31 (2) 496- 504
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM Clinical diagnosis of Alzheimer's disease. Neurology 1984;34 (7) 939- 944
PubMed
Folstein  MFRobins  LNHelzer  JE The Mini-Mental State Examination. Arch Gen Psychiatry 1983;40 (7) 812
PubMed
Rosen  WGMohs  RCDavis  KL A new rating scale for Alzheimer's disease. Am J Psychiatry 1984;141 (11) 1356- 1364
PubMed
Wechsler  D Wechsler Memory Scale. 3rd ed. San Antonio, TX: Psychological Corp; 1997
Cox  RW AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996;29 (3) 162- 173
PubMed
Talairach  JTournoux  P Co-Planar Stereotaxic Atlas of the Human Brain.  New York, NY: Thieme Medical; 1988
Cox  RWJesmanowicz  A Real-time 3D image registration for functional MRI. Magn Reson Med 1999;42 (6) 1014- 1018
PubMed
Cordes  DHaughton  VMArfanakis  K  et al.  Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR Am J Neuroradiol 2001;22 (7) 1326- 1333
PubMed
Zec  RFLandreth  ESVicari  SK  et al.  Alzheimer disease assessment scale. Alzheimer Dis Assoc Disord 1992;6 (2) 89- 102
PubMed
Petersen  RCSmith  GEWaring  SCIvnik  RJTangalos  EGKokmen  E Mild cognitive impairment. Arch Neurol 1999;56 (3) 303- 308
PubMed
Carpenter  MB Core Text of Neuroanatomy. 4th ed. Baltimore, MD: Williams & Wilkins; 1991
De Lacoste  MCWhite  CL  III The role of cortical connectivity in Alzheimer's disease pathogenesis: a review and model system. Neurobiol Aging 1993;14 (1) 1- 16
PubMed
Grady  CLFurey  MLPietrini  PHorwitz  BRapoport  SI Altered brain functional connectivity and impaired short-term memory in Alzheimer's disease. Brain 2001;124 (4) 739- 756
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Left hippocampus seed volume from a single subject overlaid on representative coronal slices.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Connectivity with the left hippocampus in control subjects (A) and in subjects with Alzheimer disease (AD) (B), and increased connectivity in controls vs subjects with AD (C).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristics of the 8 Subjects With AD and the 8 Healthy Control Subjects
Table Graphic Jump LocationTable 2. Sites of Reduced Functional Connectivity (Local Maxima) With the Left Hippocampus in Patients With AD
Table Graphic Jump LocationTable 3. Sites of Reduced Functional Connectivity (Local Maxima) With the Right Hippocampus in Patients With AD

References

American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994
Fromholt  PBruhn  P Cognitive dysfunction and dementia.  In: Nordhus  IH, VandenBos  GR, Berg  S,Fronholt  P, eds. Clinical Geropsychology. Washington, DC: American Psychological Association; 2003:183-189
Cullum  CMRosenberg  RN Memory loss: when is it Alzheimer disease? JAMA 1998;279 (21) 1689- 1690
PubMed
DeCarli  C The role of neuroimaging in dementia. Clin Geriatr Med 2001;17 (2) 255- 279
PubMed
Rombouts  SABarkhof  FGoekoop  RStam  CJScheltens  P Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: an fMRI study. Hum Brain Mapp 2005;26 (4) 231- 239
PubMed
Zakzanis  KKGraham  SJCampbell  Z A meta-analysis of structural and functional brain imaging in dementia of the Alzheimer's type: a neuroimaging profile. Neuropsychol Rev 2003;13 (1) 1- 18
PubMed
Jack  CR  JrPetersen  RCXu  Y  et al.  Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 2000;55 (4) 484- 489
PubMed
Morris  JCStorandt  MMiller  JP  et al.  Mild cognitive impairment represents early-stage Alzheimer disease. Arch Neurol 2001;58 (3) 397- 405
PubMed
Grundman  MSencakova  DJack  CR  Jr  et al.  Brain MRI hippocampal volume and prediction of clinical status in a mild cognitive impairment trial. J Mol Neurosci 2002;19 (1-2) 23- 27
PubMed
Jack  CR  JrPetersen  RCXu  YC  et al.  Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 1999;52 (7) 1397- 1403
PubMed
Biswal  BYetkin  FZHaughton  VMHyde  JS Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34 (4) 537- 541
PubMed
Peltier  SJNoll  DCT T2* dependence of low frequency functional connectivity. Neuroimage 2002;16 (4) 985- 992
PubMed
Lowe  MJMock  BJSorenson  JA Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 1998;7 (2) 119- 132
PubMed
Cordes  DHaughton  VMArfanakis  K  et al.  Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am J Neuroradiol 2000;21 (9) 1636- 1644
PubMed
Stein  TMoritz  CQuigley  MCordes  DHaughton  VMeyerand  E Functional connectivity in the thalamus and hippocampus studied with functional MR imaging. AJNR Am J Neuroradiol 2000;21 (8) 1397- 1401
PubMed
Hampson  MPeterson  BSSkudlarski  PGatenby  JCGore  JC Detection of functional connectivity using temporal correlations in MR images. Hum Brain Mapp 2002;15 (4) 247- 262
PubMed
Allen  GMcColl  RBarnard  HRinge  WKFleckenstein  JCullum  CM Magnetic resonance imaging of cerebellar-prefrontal and cerebellar-parietal functional connectivity. Neuroimage 2005;28 (1) 39- 48
PubMed
Li  SJLi  ZWu  GZhang  MJFranczak  MAntuono  PG Alzheimer disease. Radiology 2002;225 (1) 253- 259
PubMed
Wang  LZang  YHe  Y  et al.  Changes in hippocampal connectivity in the early stages of Alzheimer's disease. Neuroimage 2006;31 (2) 496- 504
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM Clinical diagnosis of Alzheimer's disease. Neurology 1984;34 (7) 939- 944
PubMed
Folstein  MFRobins  LNHelzer  JE The Mini-Mental State Examination. Arch Gen Psychiatry 1983;40 (7) 812
PubMed
Rosen  WGMohs  RCDavis  KL A new rating scale for Alzheimer's disease. Am J Psychiatry 1984;141 (11) 1356- 1364
PubMed
Wechsler  D Wechsler Memory Scale. 3rd ed. San Antonio, TX: Psychological Corp; 1997
Cox  RW AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996;29 (3) 162- 173
PubMed
Talairach  JTournoux  P Co-Planar Stereotaxic Atlas of the Human Brain.  New York, NY: Thieme Medical; 1988
Cox  RWJesmanowicz  A Real-time 3D image registration for functional MRI. Magn Reson Med 1999;42 (6) 1014- 1018
PubMed
Cordes  DHaughton  VMArfanakis  K  et al.  Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR Am J Neuroradiol 2001;22 (7) 1326- 1333
PubMed
Zec  RFLandreth  ESVicari  SK  et al.  Alzheimer disease assessment scale. Alzheimer Dis Assoc Disord 1992;6 (2) 89- 102
PubMed
Petersen  RCSmith  GEWaring  SCIvnik  RJTangalos  EGKokmen  E Mild cognitive impairment. Arch Neurol 1999;56 (3) 303- 308
PubMed
Carpenter  MB Core Text of Neuroanatomy. 4th ed. Baltimore, MD: Williams & Wilkins; 1991
De Lacoste  MCWhite  CL  III The role of cortical connectivity in Alzheimer's disease pathogenesis: a review and model system. Neurobiol Aging 1993;14 (1) 1- 16
PubMed
Grady  CLFurey  MLPietrini  PHorwitz  BRapoport  SI Altered brain functional connectivity and impaired short-term memory in Alzheimer's disease. Brain 2001;124 (4) 739- 756
PubMed

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Topics
PubMed Articles
JAMAevidence.com

Users' Guides to the Medical Literature
Clinical Resolution

Users' Guides to the Medical Literature
Clinical Scenario