Page 76 - AN-1-1
P. 76

Advanced Neurology                                         Cortical thickness and regional homogeneity in CSVD



               https://doi.org/10.1006/nimg.1998.0395             memory clinic setting. Intern Med, 54: 1027–1033.
            22.  Fischl B, Liu A, Dale AM, 2011, Automated manifold      https://doi.org/10.2169/internalmedicine.54.3747
               surgery:  Constructing  geometrically  accurate  and  33.  Makin  SD,  Turpin  S,  Dennis  MS,  et al.,  2013,  Cognitive
               topologically correct models of the human cerebral cortex.
               IEEE Trans Med Imaging, 20: 70–80.                 impairment after lacunar stroke:  Systematic  review  and
                                                                  meta-analysis of incidence, prevalence and comparison
               https://doi.org/10.1109/42.906426                  with other stroke subtypes. J Neurol Neurosurg Psychiatry,
            23.  Fischl  B,  Sereno MI,  Dale AM,  1999,  Cortical surface-  84: 893–900.
               based analysis. II: Inflation, flattening, and a surface-based      https://doi.org/10.1136/jnnp-2012-303645
               coordinate system. Neuroimage, 9(2): 195–207.
                                                               34.  Chen L, Song J, Cheng R,  et al., 2020, Cortical thinning
               https://doi.org/10.1006/nimg.1998.0396             in the medial temporal lobe and precuneus is related to
            24.  Fischl B, Sereno MI, Tootell RB, et al., 1999, High-resolution   cognitive deficits in patients with subcortical ischemic
               intersubject  averaging  and  a  coordinate  system  for  the   vascular disease. Front Aging Neurosci, 12: 614833.
               cortical surface. Hum Brain Mapp, 8: 272–284.      https://doi.org/10.3389/fnagi.2020.614833
               https://doi.org/10.1002/(sici)1097-0193(1999)8:4<272::aid-  35.  Ni L, Liu R, Yin Z, et al., 2016, Aberrant spontaneous brain
               hbm10>3.0.co;2-4                                   activity in patients with mild cognitive impairment and
            25.  Fischl  B, van  der  Kouwe A,  Destrieux  C,  et al., 2004,   concomitant lacunar infarction: A resting-state functional
               Automatically parcellating the human cerebral cortex. Cereb   MRI study. J Alzheimers Dis, 50: 1243–1254.
               Cortex, 14: 11–22.                                 https://doi.org/10.3233/JAD-150622
               https://doi.org/10.1093/cercor/bhg087           36.  Gasquoine PG, 2013, Localization of function in anterior
            26.  Desikan RS, Segonne F, Fischl B, et al., 2006, An automated   cingulate cortex: from psychosurgery to functional
               labeling system for subdividing the human cerebral cortex on   neuroimaging. Neurosci Biobehav Rev, 37: 340–348.
               MRI scans into gyral based regions of interest. Neuroimage,      https://doi.org/10.1016/j.neubiorev.2013.01.002
               31: 968–980.
                                                               37.  Chen Y, Wang J, Zhang J, et al., 2014, Aberrant functional
               https://doi.org/10.1016/j.neuroimage.2006.01.021   networks connectivity and structural atrophy in silent
            27.  Fischl B, Dale AM, 2000, Measuring the thickness of the   lacunar infarcts: Relationship with cognitive impairments.
               human cerebral cortex from magnetic resonance images.   J Alzheimers Dis, 42: 841–850.
               Proc Natl Acad Sci U S A, 97: 11050–11055.         https://doi.org/10.3233/JAD-140948
               https://doi.org/10.1073/pnas.200033797          38.  Cabeza R, Nyberg L, 2000, Imaging cognition II: An
            28.  Klein A, Tourville J, 2012, 101 labeled brain images and a   empirical review of 275 PET  and fMRI studies.  J  Cogn
               consistent human cortical labeling protocol. Front Neurosci,   Neurosci, 12: 1–47.
               6: 171.                                            https://doi.org/10.1162/08989290051137585
               https://doi.org/10.3389/fnins.2012.00171        39.  Kobayashi Y, Morizumi T, Nagamatsu K,  et al., 2021,
            29.  Kloppenborg RP, Nederkoorn PJ, Geerlings MI, et al., 2014,   Persistent  working  memory  impairment  associated  with
               Presence and progression of white matter hyperintensities   cerebral infarction in the anterior cingulate cortex: A case
               and cognition: A meta-analysis. Neurology, 82: 2127–38.  report and a literature review. Intern Med, 60: 3473–3476.
               https://doi.org/10.1212/WNL.0000000000000505       https://doi.org/10.2169/internalmedicine.6927-20
            30.  Alber  J, Alladi S, Bae HJ,  et al., 2019, White matter   40.  Abd Razak MA, Ahmad NA, Chan YY, et al., 2019, Validity of
               hyperintensities in vascular contributions to cognitive   screening tools for dementia and mild cognitive impairment
               impairment and  dementia (VCID):  Knowledge gaps  and   among the elderly in primary health care: A  systematic
               opportunities. Alzheimers Dement (NY) 5: 107–117.  review. Public Health, 169: 84–92.
               https://doi.org/10.1016/j.trci.2019.02.001         https://doi.org/10.1016/j.puhe.2019.01.001
            31.  Brundel M, Kwa VI, Bouvy WH,  et al., 2014, Cerebral   41.  Zhuang L, Yang Y, Gao J, 2021, Cognitive assessment
               microbleeds are not associated with long-term cognitive   tools for mild cognitive impairment screening.  J  Neurol,
               outcome in patients with transient ischemic attack or minor   268: 1615–1622.
               stroke. Cerebrovasc Dis, 37: 195–202.              https://doi.org/10.1007/s00415-019-09506-7
               https://doi.org/10.1159/000358119
                                                               42.  Tallarita GM, Parente A, Giovagnoli AR, 2019, The
            32.  Doi H, Inamizu S, Saito BY, et al., 2015, Analysis of cerebral   visuospatial pattern of temporal lobe epilepsy.  Epilepsy
               lobar microbleeds and a decreased cerebral blood flow in a   Behav, 101: 106582.


            Volume 1 Issue 1 (2022)                         11                       https://doi.org/10.36922/an.v1i1.48
   71   72   73   74   75   76   77   78   79   80   81