Skip to main content Accessibility help

Diffusion Tensor Imaging Predictors of Episodic Memory Decline in Healthy Elders at Genetic Risk for Alzheimer’s Disease

  • Melissa A. Lancaster (a1), Michael Seidenberg (a1), J. Carson Smith (a2), Kristy A. Nielson (a3) (a4), John L. Woodard (a5), Sally Durgerian (a4) and Stephen M. Rao (a6)...


Objectives: White matter (WM) integrity within the mesial temporal lobe (MTL) is important for episodic memory (EM) functioning. The current study investigated the ability of diffusion tensor imaging (DTI) in MTL WM tracts to predict 3-year changes in EM performance in healthy elders at disproportionately higher genetic risk for Alzheimer’s disease (AD). Methods: Fifty-one cognitively intact elders (52% with family history (FH) of dementia and 33% possessing an Apolipoprotein E ε4 allelle) were administered the Rey Auditory Verbal Learning Test (RAVLT) at study entry and at 3-year follow-up. DTI scanning, conducted at study entry, examined fractional anisotropy and mean, radial and axial diffusion within three MTL WM tracts: uncinate fasciculus (UNC), cingulate-hippocampal (CHG), and fornix-stria terminalis (FxS). Correlations were performed between residualized change scores computed from RAVLT trials 1–5, immediate recall, and delayed recall scores and baseline DTI measures; MTL gray matter (GM) and WM volumes; demographics; and AD genetic and metabolic risk factors. Results: Higher MTL mean and axial diffusivity at baseline significantly predicted 3-year changes in EM, whereas baseline MTL GM and WM volumes, FH, and metabolic risk factors did not. Both ε4 status and DTI correlated with change in immediate recall. Conclusions: Longitudinal EM changes in cognitively intact, healthy elders can be predicted by disruption of the MTL WM microstructure. These results are derived from a sample with a disproportionately higher genetic risk for AD, suggesting that the observed WM disruption in MTL pathways may be related to early neuropathological changes associated with the preclinical stage of AD. (JINS, 2016, 22, 1005–1015)


Corresponding author

Correspondence and reprint requests to: Stephen M. Rao, Schey Center for Cognitive Neuroimaging, Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, 9500 Euclid Avenue / U10, Cleveland, OH 44195. E-mail:


Hide All
Acosta-Cabronero, J., Williams, G.B., Pengas, G., & Nestor, P.J. (2010). Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease. Brain, 133, 529539.
Agosta, F., Pievani, M., Sala, S., Geroldi, C., Galluzzi, S., Frisoni, G.B., & Filippi, M. (2011). White matter damage in Alzheimer disease and its relationship to gray matter atrophy. Radiology, 258(3), 853863. doi: 10.1148/radiol.10101284
Albert, M.S., Moss, M.B., Tanzi, R., & Jones, K. (2001). Preclinical prediction of AD using neuropsychological tests. Journal of the International Neuropsychological Society, 7(5), 631639.
Alves, G.S., O’Dwyer, L., Jurcoane, A., Oertel-Knochel, V., Knochel, C., Prvulovic, D., & Laks, J. (2012). Different patterns of white matter degeneration using multiple diffusion indices and volumetric data in mild cognitive impairment and Alzheimer patients. PLoS One, 7(12), e52859. doi: 10.1371/journal.pone.0052859
Backman, L., Small, B.J., & Fratiglioni, L. (2001). Stability of the preclinical episodic memory deficit in Alzheimer’s disease. Brain, 124(Pt 1), 96102.
Balthazar, M.L., Yasuda, C.L., Cendes, F., & Damasceno, B.P. (2010). Learning, retrieval, and recognition are compromised in aMCI and mild AD: Are distinct episodic memory processes mediated by the same anatomical structures? Journal of the International Neuropsychological Society, 16(1), 205209. doi: 10.1017/s1355617709990956
Bartzokis, G., Sultzer, D., Lu, P.H., Nuechterlein, K.H., Mintz, J., & Cummings, J.L. (2004). Heterogeneous age-related breakdown of white matter structural integrity: Implications for cortical “disconnection” in aging and Alzheimer’s disease. Neurobiology of Aging, 25, 843851.
Behrens, M.W., Woolrich, M., Jenkinson, H., Johansen-Berg, R.G., Nunes, S., & Clare, P.M. (2003). Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magnetic Resonance in Medicine, 50, 10771088.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 57, 289300.
Bennett, I.J., & Madden, D.J. (2014). Disconnected aging: Cerebral white matter integrity and age-related differences in cognition. Neuroscience, 276, 187205. doi: 10.1016/j.neuroscience.2013.11.026
Blacker, D., Lee, H., Muzikansky, A., Martin, E.C., Tanzi, R., McArdle, J.J., & Albert, M. (2007). Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Archives of Neurology, 64(6), 862871. doi: 10.1001/archneur.64.6.862
Bondi, M.W., Salmon, D.P., Galasko, D., Thomas, R.G., & Thal, L.J. (1999). Neuropsychological function and apolipoprotein E genotype in the preclinical detection of Alzheimer’s disease. Psychology and Aging, 14(2), 295303.
Canu, E., McLaren, D.G., Fitzgerald, M.E., Bendlin, B.B., Zoccatelli, G., Alessandrini, F., & Frisoni, G.B. (2010). Microstructural diffusion changes are independent of macrostructural volume loss in moderate to severe Alzheimer’s disease. Journal of Alzheimer’s Disease, 19(3), 963976. doi: 10.3233/jad-2010-1295
Cardenas, V.A., Chao, L.L., Studholme, C., Yaffe, K., Miller, B.L., Madison, C., & Weiner, M.W. (2011). Brain atrophy associated with baseline and longitudinal measures of cognition. Neurobiology of Aging, 32(4), 572580. doi: 10.1016/j.neurobiolaging.2009.04.011
Caselli, R.J., Reiman, E.M., Osborne, D., Hentz, J.G., Baxter, L.C., Hernandez, J.L., & Alexander, G.G. (2004). Longitudinal changes in cognition and behavior in asymptomatic carriers of the APOE e4 allele. Neurology, 62(11), 19901995.
Christidi, F., Zalonis, I., Kyriazi, S., Rentzos, M., Karavasilis, E., Wilde, E.A., & Evdokimidis, I. (2014). Uncinate fasciculus microstructure and verbal episodic memory in amyotrophic lateral sclerosis: A diffusion tensor imaging and neuropsychological study. Brain Imaging and Behavior, 8(4), 497505. doi: 10.1007/s11682-013-9271-y
Cox, R. (1996). AFNI: Sotware for analysis and visualization of functional magnetic resonance images. Computers and Biomedical Research, 29, 162173.
den Heijer, T., Geerlings, M.I., Hoebeek, F.E., Hofman, A., Koudstaal, P.J., & Breteler, M.M. (2006). Use of hippocampal and amygdalar volumes on magnetic resonance imaging to predict dementia in cognitively intact elderly people. Archives of General Psychiatry, 63(1), 5762. doi: 10.1001/archpsyc.63.1.57
Dickerson, B.C., & Eichenbaum, H. (2010). The episodic memory system: Neurocircuitry and disorders. Neuropsychopharmacology, 35(1), 86104. doi: 10.1038/npp.2009.126
Edmonds, E.C., Delano-Wood, L., Galasko, D.R., Salmon, D.P., & Bondi, M.W. (2015). Subtle cognitive decline and biomarker staging in preclinical Alzheimer’s disease. Journal of Alzheimer’s Disease, 47(1), 231242. doi: 10.3233/jad-150128
Ellis, K.A., Lim, Y.Y., Harrington, K., Ames, D., Bush, A.I., Darby, D., … AIBL Research Group. (2013). Decline in cognitive function over 18 months in healthy older adults with high amyloid-beta. Journal of Alzheimer’s Disease, 34(4), 861871. doi: 10.3233/jad-122170
Ezzati, A., Katz, M.J., Lipton, M.L., Zimmerman, M.E., & Lipton, R.B. (2016). Hippocampal volume and cingulum bundle fractional anisotropy are independently associated with verbal memory in older adults. Brain Imaging and Behavior, 10, 652659. doi: 10.1007/s11682-015-9452-y
Fagan, A.M., Roe, C.M., Xiong, C., Mintun, M.A., Morris, J.C., & Holtzman, D.M. (2007). Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Archives of Neurology, 64(3), 343349. doi: 10.1001/archneur.64.3.noc60123
Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., & Haselgrove, C. (2004). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33, 341355.
Fletcher, E., Raman, M., Huebner, P., Liu, A., Mungas, D., Carmichael, O., & DeCarli, C. (2013). Loss of fornix white matter volume as a predictor of cognitive impairment in cognitively normal elderly individuals. JAMA Neurology, 70(11), 13891395. doi: 10.1001/jamaneurol.2013.3263
Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-Mental State”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatry Research, 12, 189198.
Fu, J.L., Liu, Y., Li, Y.M., Chang, C., & Li, W.B. (2014). Use of diffusion tensor imaging for evaluating changes in the microstructural integrity of white matter over 3 years in patients with amnesic-type mild cognitive impairment converting to Alzheimer’s disease. Journal of Neuroimaging, 24(4), 343348. doi: 10.1111/jon.12061
Geschwind, N. (1965a). Disconnexion syndromes in animals and man. I. Brain, 88(2), 237294.
Geschwind, N. (1965b). Disconnexion syndromes in animals and man. II. Brain, 88(3), 585644.
Golomb, J., Kluger, A., de Leon, M.J., Ferris, S.H., Mittelman, M., Cohen, J., & George, A.E. (1996). Hippocampal formation size predicts declining memory performance in normal aging. Neurology, 47(3), 810813.
Hamel, R., Kohler, S., Sistermans, N., Koene, T., Pijnenburg, Y., van der Flier, W., & Ramakers, I. (2015). The trajectory of cognitive decline in the pre-dementia phase in memory clinic visitors: Findings from the 4C-MCI study. Psychological Medicine, 45(7), 15091519. doi: 10.1017/s0033291714002645
Hiyoshi-Taniguchi, K., Oishi, N., Namiki, C., Miyata, J., Murai, T., Cichocki, A., & Fukuyama, H. (2015). The uncinate fasciculus as a predictor of conversion from aMCI to Alzheimer disease. Journal of Neuroimaging, 25, 748753. doi: 10.1111/jon.12196
Jurica, P.J., Leittten, C.L., & Mattis, S. (2001). Dementia Rating Scale-2 professional manual. Lutz, FL: Psychological Assessment Resources.
Lawton, M.P., & Brody, E.M. (1969). Assessment of older people: Self-maintaining instrumental activities of daily living. Gerontologist, 9, 179186.
Li, W., Muftuler, L.T., Chen, G., Ward, B.D., Budde, M.D., Jones, J.L., & Goveas, J.S. (2014). Effects of the coexistence of late-life depression and mild cognitive impairment on white matter microstructure. Journal of the Neurological Sciences, 338(1-2), 4656. doi: 10.1016/j.jns.2013.12.016
Lim, Y.Y., Pietrzak, R.H., Ellis, K.A., Jaeger, J., Harrington, K., Ashwood, T., & Maruff, P. (2013). Rapid decline in episodic memory in healthy older adults with high amyloid-beta. Journal of Alzheimer’s Disease, 33(3), 675679. doi: 10.3233/jad-2012-121516
Loewenstein, D.A., Barker, W.W., Chang, J.Y., Apicella, A., Yoshii, F., Kothari, P., & Duara, R. (1989). Predominant left hemisphere metabolic dysfunction in dementia. Archives of Neurology, 46(2), 146152.
Mattsson, P., Forsberg, A., Persson, J., Nyberg, L., Nilsson, L.G., Halldin, C., & Farde, L. (2015). beta-Amyloid binding in elderly subjects with declining or stable episodic memory function measured with PET and [(1)(1)C]AZD2184. European Journal of Nuclear Medicine and Molecular Imaging, 42(10), 15071511. doi: 10.1007/s00259-015-3103-9
McSweeny, A.J., Naugle, R.I., Chelune, G.J., & Luders, H. (1993). “T scores for change”: An illustration of a regression approach to depicting change in clinical neuropsychology. The Clinical Neuropsychologist, 7, 300312.
Mesulam, M.M. (1990). Large-scale neurocognitive networks and distributed processing for attention, language, and memory. Annals of Neurology, 28(5), 597613. doi: 10.1002/ana.410280502
Metzler-Baddeley, C., Hunt, S., Jones, D.K., Leemans, A., Aggleton, J.P., & O’Sullivan, M.J. (2012). Temporal association tracts and the breakdown of episodic memory in mild cognitive impairment. Neurology, 79(23), 22332240. doi: 10.1212/WNL.0b013e31827689e8
Mistridis, P., Krumm, S., Monsch, A.U., Berres, M., & Taylor, K.I. (2015). The 12 years preceding mild cognitive impairment due to Alzheimer’s disease: The temporal emergence of cognitive decline. Journal of Alzheimer’s Disease, 48(4), 10951107. doi: 10.3233/jad-150137
Moghekar, A., Li, S., Lu, Y., Li, M., Wang, M.C., & Albert, M., … Biocard Research Team. (2013). CSF biomarker changes precede symptom onset of mild cognitive impairment. Neurology, 81(20), 17531758. doi: 10.1212/01.wnl.0000435558.98447.17
Mori, S., Oishi, K., Jiang, H., Jiang, L., Li, X., Akhter, K., & Mazziotta, J. (2008). Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. Neuroimage, 40(2), 570582. doi: 10.1016/j.neuroimage.2007.12.035
Nir, T.M., Jahanshad, N., Villalon-Reina, J.E., Toga, A.W., Jack, C.R., & Weiner, M.W., … Alzheimer’s Disease Neuroimaging Initiative. (2013). Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging. Neuroimage: Clinical, 3, 180195. doi: 10.1016/j.nicl.2013.07.006
O’Dwyer, L., Lamberton, F., Bokde, A.L., Ewers, M., Faluyi, Y.O., Tanner, C., & Hampel, H. (2011). Multiple indices of diffusion identifies white matter damage in mild cognitive impairment and Alzheimer’s disease. PLoS One, 6(6), e21745. doi: 10.1371/journal.pone.0021745
Oishi, K., Faria, A., van Zijl, P.C.M., & Mori, S. (2011). MRI atlas of human white matter, (2nd ed.). London: Elsevier.
Papp, K.V., Amariglio, R.E., Mormino, E.C., Hedden, T., Dekhytar, M., Johnson, K.A., & Rentz, D.M. (2015). Free and cued memory in relation to biomarker-defined abnormalities in clinically normal older adults and those at risk for Alzheimer’s disease. Neuropsychologia, 73, 169175. doi: 10.1016/j.neuropsychologia.2015.04.034
Pierpaoli, C., Barnett, A., Pajevic, S., Chen, R., Penix, L.R., Virta, A., & Basser, P. (2001). Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture. Neuroimage, 13(6 Pt 1), 11741185. doi: 10.1006/nimg.2001.0765
Ray, N.J., Metzler-Baddeley, C., Khondoker, M.R., Grothe, M.J., Teipel, S., Wright, P., & O’Sullivan, M.J. (2015). Cholinergic basal forebrain structure influences the reconfiguration of white matter connections to support residual memory in mild cognitive impairment. Journal of Neuroscience, 35(2), 739747. doi: 10.1523/jneurosci.3617-14.2015
Raz, N., & Rodrigue, K.M. (2006). Differential aging of the brain: Patterns, cognitive correlates and modifiers. Neuroscience and Biobehavioral Reviews, 30(6), 730748. doi: 10.1016/j.neubiorev.2006.07.001
Remy, F., Vayssiere, N., Saint-Aubert, L., Barbeau, E., & Pariente, J. (2015). White matter disruption at the prodromal stage of Alzheimer’s disease: Relationships with hippocampal atrophy and episodic memory performance. Neuroimage: Clinical, 7, 482492. doi: 10.1016/j.nicl.2015.01.014
Rey, A. (1958). L’examen clinique en psychologie. Paris: Presses Universitaires de France.
Rosen, A.C., Prull, M.W., Gabrieli, J.D., Stoub, T., O’Hara, R., Friedman, L., & deToledo-Morrell, L. (2003). Differential associations between entorhinal and hippocampal volumes and memory performance in older adults. Behavioral Neuroscience, 117(6), 11501160. doi: 10.1037/0735-7044.117.6.1150
Salat, D.H., Tuch, D.S., van der Kouwe, A.J., Greve, D.N., Pappu, V., & Lee, S.Y. (2010). White matter pathology isolates the hippocampal formation in Alzheimer’s disease. Neurobiology of Aging, 31, 244256.
Saunders, A.M., Hulette, O., Welsh-Bohmer, K.A., Schmechel, D.E., Crain, B., & Burke, J.R. (1996). Specificity, sensitivity, and predictive value of apolipoprotein-E genotyping for sporadic Alzheimer’s disease. Lancet, 348, 9093.
Schaeffer, D.J., Krafft, C.E., Schwarz, N.F., Chi, L., Rodrigue, A.L., Pierce, J.E., & McDowell, J.E. (2014). The relationship between uncinate fasciculus white matter integrity and verbal memory proficiency in children. Neuroreport, 25(12), 921925. doi: 10.1097/wnr.0000000000000204
Seidenberg, M., Guidotti, L., Nielson, K.A., Woodard, J.L., Durgerian, S., Antuono, P., & Rao, S.M. (2009). Semantic memory activation in individuals at risk for developing Alzheimer disease. Neurology, 73(8), 612620. doi: 10.1212/WNL.0b013e3181b389ad
Smith, S.M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17, 143155.
Smith, S.M., Jenkinson, M., Johansen-Berg, H., Ruckert, D., Nichols, T.E., & Mackay, C.E. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage, 31, 14871505.
Song, S.K., Sun, S.W., Ju, W.K., Lin, S.J., Cross, A.H., & Neufeld, A.H. (2003). Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage, 20, 17141722.
Song, S.K., Sun, S.W., Ramsbottom, M.J., Chang, C., Russell, J., & Cross, A.H. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage, 17(3), 14291436.
Sperling, R.A., Aisen, P.S., Beckett, L.A., Bennett, D.A., Craft, S., Fagan, A.M., & Phelps, C.H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers and Dementia, 7(3), 280292. doi: 10.1016/j.jalz.2011.03.003
Thai, C., Lim, Y.Y., Villemagne, V.L., Laws, S.M., Ames, D., & Ellis, K.A., … Australian Imaging, Biomarkers and Lifestyle (AIBL) Research Group. (2015). Amyloid-related memory decline in preclinical Alzheimer’s disease is dependent on APOE epsilon4 and is detectable over 18-months. PLoS One, 10(10), e0139082. doi: 10.1371/journal.pone.0139082
Thompson, P.M., Hayashi, K.M., de Zubicaray, G., Janke, A.L., Rose, S.E., Semple, J., & Toga, A.W. (2003). Dynamics of gray matter loss in Alzheimer’s disease. Journal of Neuroscience, 23(3), 9941005.
Tucker, L.R., Damarin, F., & Messick, S. (1966). A base-free measure of change. Psychometrika, 31(4), 457473.
Von Der Heide, R.J., Skipper, L.M., Klobusicky, E., & Olson, I.R. (2013). Dissecting the uncinate fasciculus: Disorders, controversies and a hypothesis. Brain, 136(6), 16921707. doi: 10.1093/brain/awt094
Vyhnalek, M., Nikolai, T., Andel, R., Nedelska, Z., Rubinova, E., Markova, H., & Hort, J. (2014). Neuropsychological correlates of hippocampal atrophy in memory testing in nondemented older adults. Journal of Alzheimer’s Disease, 42(Suppl 3), S81S90. doi: 10.3233/jad-132642
Wang, R., Fratiglioni, L., Laukka, E.J., Lovden, M., Kalpouzos, G., Keller, L., & Qiu, C. (2015). Effects of vascular risk factors and APOE epsilon4 on white matter integrity and cognitive decline. Neurology, 84(11), 11281135. doi: 10.1212/wnl.0000000000001379
Wheeler-Kingshott, C.A., & Cercignani, M. (2009). About “axial” and “radial” diffusivities. Magnetic Resonance in Medicine, 61(5), 12551260. doi: 10.1002/mrm.21965
Wisse, L.E., Reijmer, Y.D., ter Telgte, A., Kuijf, H.J., Leemans, A., & Luijten, P.R., … Utrecht Vascular Cognitive Impairment Study Group. (2015). Hippocampal disconnection in early Alzheimer’s disease: A 7 tesla MRI study. Journal of Alzheimer’s Disease, 45(4), 12471256. doi: 10.3233/jad-142994
Woodard, J.L., Seidenberg, M., Nielson, K.A., Antuono, P., Guidotti, L., Durgerian, S., & Rao, S.M. (2009). Semantic memory activation in amnestic mild cognitive impairment. Brain, 132(Pt 8), 20682078. doi: 10.1093/brain/awp157
Woodard, J.L., Seidenberg, M., Nielson, K.A., Smith, J.C., Antuono, P., Durgerian, S., & Rao, S.M. (2010). Prediction of cognitive decline in healthy older adults using fMRI. Journal of Alzheimer’s Disease, 21, 871885.
Woodard, J.L., Sugarman, M.A., Nielson, K.A., Smith, J.C., Seidenberg, M., Durgerian, S., & Rao, S.M. (2012). Lifestyle and genetic contributions to cognitive decline and hippocampal structure and function in healthy aging. Current Alzheimer’s Research, 9(4), 436446.
Yasmin, H., Nakata, Y., Aoki, S., Abe, O., Sato, N., Nemoto, K., & Ohtomo, K. (2008). Diffusion abnormalities of the uncinate fasciculus in Alzheimer’s disease: Diffusion tensor tract-specific analysis using a new method to measure the core of the tract. Neuroradiology, 50(4), 293299. doi: 10.1007/s00234-007-0353-7
Yesavage, J.A., Brink, T.L., Rose, T.L., Lum, O., Huang, V., & Adey, M. (1983). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatry Research, 17, 3749.
Zhang, Y., Schuff, N., Jahng, G.H., Bayne, W., Mori, S., Schad, L., & Weiner, M.W. (2007). Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology, 68(1), 1319. doi: 10.1212/01.wnl.0000250326.77323.01
Zhuang, L., Sachdev, P.S., Trollor, J.N., Kochan, N.A., Reppermund, S., Brodaty, H., & Wen, W. (2012). Microstructural white matter changes in cognitively normal individuals at risk of amnestic MCI. Neurology, 79(8), 748754. doi: 10.1212/WNL.0b013e3182661f4d
Zhuang, L., Sachdev, P.S., Trollor, J.N., Reppermund, S., Kochan, N.A., Brodaty, H., & Wen, W. (2013). Microstructural white matter changes, not hippocampal atrophy, detect early amnestic mild cognitive impairment. PLoS One, 8(3), e58887. doi: 10.1371/journal.pone.0058887


Related content

Powered by UNSILO

Diffusion Tensor Imaging Predictors of Episodic Memory Decline in Healthy Elders at Genetic Risk for Alzheimer’s Disease

  • Melissa A. Lancaster (a1), Michael Seidenberg (a1), J. Carson Smith (a2), Kristy A. Nielson (a3) (a4), John L. Woodard (a5), Sally Durgerian (a4) and Stephen M. Rao (a6)...


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.