Supplementary Materials

Altered Topological Organization of High-Level Visual Networks in Alzheimer’s

Disease and Mild Cognitive Impairment

Yanjia Deng1, Lin Shi2,4, Defeng Wang1,3,#, for the Alzheimer’s Disease Neuroimaging

Initiative*

# Corresponding author: Defeng Wang; Tel: +852- 26975027; Fax: +852- 26493761;

Email: dfwang@cuhk.edu.hk

I．ALE analysis for locating “what” and “where” visual cortices

1) Literature selection criteria

We searched the studies that investigated HLV functions in the Web of Pubmed

database (http://www.ncbi.nlm.nih.gov/pubmed). For more specific and effective

search, the MeSH (medical subject headings) entry terms [1] were used, including

"Visual Perception", "Color Perception", "Motion Perception", "Space Perception",

"Depth Perception", "Form Perception", "Size Perception" and "Magnetic Resonance

Imaging".

Until February 2015, this search revealed 3095 published, peer reviewed papers.

Finally, 74 studies matched the following criteria and were included for ALE

analysis: (1) Papers were published in English and in which subjects were healthy

adults; (2) fMRI was adopted as image modality; (3) The whole brain was scanned

and the coordinates of the activation clusters were reported in Talairach and Tournoux

(1988) or Montreal Neurological Institute (MNI) space; (4) Only one visual functions

was tested in one task; (5) Results were obtained results by using low level contrasts

(target vision vs. baseline, noise or scrambled meaningless images).

2) Data analysis

Among the included 74 studies, studies on recognition perception (including face,

object, alphabetic word/ letter, scene, and body vision) were grouped into “what”

vision, and those focused on motion or spatial vision were categorized into “where”

vision (Supplementary Table 1). The meta-analyses were performed using the revised

algorithm of the ALE implemented in the Ginger ALE software, version 2.0

(available at www.brainmap.org/ale). Coordinates reported in the Talairach space

were transformed into the MNI space using the Lancaster transform [2]. Foci from

each individual study were smoothed by a full width half maximum (FWHM) value

scaled by the study’s sample size to model the uncertainty in spatial location of the

activations [3]. The statistical level to determine the null distribution of the ALE value

was at p < 0.01 (multiple comparisons corrected by false discovery rate (FDR pN)

method) [3].

II. Subjects and neuropsychological tests

A total of 162 subjects, including 44 normal controls (CN), 52 early MCI (EMCI), 35

late MCI (LMCI), 31 AD, were included in this study. Briefly, the cognitive level (i.e.

CN, EMCI, LMCI or AD) was judged by combining the memory complaints of

patients or their families, the Wechsler Memory Scale - Logical Memory II

(Wechsler, 1987), the Mini-Mental State Exam (MMSE) scores, and the Clinical

Dementia Rating (CDR) of subjects. Specifically, the major difference of the

diagnostic criteria for EMCI and LMCI is in the score of Logical Memory II subscale.

The score of Logical Memory II subscale for defining EMCI is: a. 9-11 for 16 or more

years of education; b. 5-9 for 8-15 years of education; c. 3-6 for 0-7 years of

education, which is between the scale for CN and LMCI. Therefore, the EMCI and

LMCI refer to the severity of cognitive impairments. The detailed inclusion and

exclusion criteria were found in the ADNI2 and ADNI GO protocol

(http://adni.loni.usc.edu/methods/documents/). For the current study, subjects with

glaucoma or congenital blindness were further excluded. Besides, one AD subjects

was excluded due to excessive head motion during acquisition of rs-fMRI (see data

preprocess section). Finally, there were 44 CN, 52 EMCI, 35 LMCI and 30 AD

subjects.

All participants were administered the Mini Mental State Examination (MMSE) [4].

The MMSE is a widely used general cognitive screening test. In the ADNI database,

the clock drawing test was performed through the ADNI program, which has two

components: a command condition in which the participant draws a clock to verbal

instructions, and a copy condition in which the participant copies a model clock

drawn at the top of response form. This test, especially the copy condition, is

considered correlated with the visuospatial perception [5]. Thus, we included the

results of copy conditions of clock drawing test for further analysis.

III. Network construction and calculations

Previously established network quantification method based on graph theory was used

in this study to calculate the network parameters [6]. Firstly, the association matrices

based on the pair-wise interregional RSFC at 0.021-0.045Hz were created

respectively for “what” (29 × 29) and “where” (25 × 25) vision networks of each

subject. Then the matrices were thresholded into binary matrices. Here, a range of

network densities (0.06 – 0.40, with an interval of 0.01) were used to binarize the

matrics to ensure that the resultant networks of different subject could have the same

number of edges thus to make the networks comparable. Therefore, the binarized

matrix was recognized as a graph, each ROI as a node, and the RSFC between two

nodes as an edge.

Two fundamental quantities, the characteristic path length (L) and clustering

coefficient (C), were used in this study to respectively quantify the capability of

integrated and segregated information processing of the brain network. The L is

defined as the average of the shortest path lengths between nodes [7].

Here N represents the total number of the nodes, i and j stand for two generic nodes,

and Lij is the shortest path length between i and j. Thus a shorter path length

represents greater network integration. The C is the average of the local clustering

coefficients of all nodes which are calculated by dividing the number of existing

connections among the node and its neighbors by all the possible connections.

,

Here G and Gi respectively represent the whole network and the sub-network which is

composed of a node i and its nearest neighbors (e.g., node j and k). Thus the C

quantifies the extent to which neighboring brain regions are connected with each

other, i.e. the network segregation [8].

IV. ADNI dataset

The ADNI was launched in 2003 as a public-private partnership, led by Principal

Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test

whether serial MRI, positron emission tomography (PET), other biological markers,

and clinical and neuropsychological assessment can be combined to measure the

progression of MCI and AD.

ADNI is funded by the National Institute on Aging, the National Institute of

Biomedical Imaging and Bioengineering, and through generous contributions from

the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery

Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb

Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and

Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company

Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer

Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical

Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso

Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis

Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda

Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of

Health Research is providing funds to support ADNI clinical sites in Canada. Private

sector contributions are facilitated by the Foundation for the National Institutes of

Health (www.fnih.org). The grantee organization is the Northern California Institute

for Research and Education, and the study is coordinated by the Alzheimer's Disease

Cooperative Study at the University of California, San Diego. ADNI data are

disseminated by the Laboratory for Neuro Imaging at the University of Southern

California.

Supplementary Tables

Supplementary Table 1 Summary of studies selected for the ALE analysis of

"what" and "where" vision

Category/study(author) Year No. of

Subjects

Contrast No. of

Foci

“What” vision

Leube et al. [9] 2003 13 Face > baseline 5

Badzakova-Trajkov et al. [10] 2010 155 Face > baseline 18

Love et al. [11] 2011 20 Face > baseline 10

Vuilleumier et al. [12] 2003 13 Face > baseline 11

Henson et al. [13] 2003 21 Face > scrambled image 4

Furl et al. [14] 2007 12 Face > baseline 7

Fruhholz et al. [15] 2011 24 Face > scrambled image 21

Platek et al. [16] 2009 12 Face > baseline 1

Schwartz et al. [17] 2013 8 Face > baseline 3

Joseph et al. [18] 2011 43 Face > baseline 11

Jehna et al. [19] 2011 30 Face > scrambled image 5

Benuzzi et al. [20] 2007 24 Face > noise 36

Rossion et al. [21] (2003) 2003 11 Face > baseline 4

Rossion et al. [22] 2012 40 Face > scrambled 12

Gobbini et al. [23] 2011 12 Face > baseline 30

Hoffman et al. [24] 2000 9 Face > baseline 8

Pagliaccio et al. [25] 2013 52 Face > baseline 1

Ramon et al. [26] 2010 13 Face > scrambled image 13

Blonder et al. [27] 2004 14 Face > baseline 6

Liu et al. [28] 2009 17 Face > baseline 11

Orlov et al. [29] 2010 12 Face > baseline 10

Olulade et al. [30] 2013 15 Word> baseline 8

Joseph et al. [31] 2006 11 Word > baseline 7

Minati et al. [32] 2008 10 Word > baseline 15

Szwed et al. [33] 2011 16 Word > scrambled image 9

Longcamp et al. [34] 2011 10 Word > baseline 1

Pegado et al. [35] 2011 14 Letter > baseline 4

Dehaene et al. [36] 2001 15 Word > noise 6

Dehaene et al. [37] 2004 26 Word > noise 6

Casarotto et al. [38] 2006 8 Word > baseline 4

Peng et al. [39] (2003) 2003 8 Word > baseline 34

Gold et al. [40] 2007 16 Word > baseline 2

Gros et al. [41] 2001 6 Letter > baseline 2

James et al. [42] 2009 19 Letter > baseline 12

Thoma et al. [43] 2011 17 Object > scrambled image 8

Pegado et al. [35] 2011 14 Object > baseline 6

Yamamoto et al. [44] 2008 6 Object > baseline 3

Podzebenko et al. [45] 2005 16 Object > baseline 13

Minati et al. [32] 2008 10 Object > baseline 23

Szwed et al. [33] 2011 16 Object > scrambled image 7

Creem-Regehr et al. [46] 2007 23 Object > scrambled image 10

Durand et al. [47] 2009 17 Object > scrambled image 6

Cardin et al. [48] 2011 14 Object > baseline 9

Valyear et al. [49] 2006 7 Object > baseline 1

Niemeier et al. [50] 2005 10 Object > baseline 2

Casarotto et al. [38] 2006 8 Object > baseline 1

Peelen et al. [51] 2012 26 Object > baseline 2

Bucher et al. [52] 2006 16 Object > baseline 7

Blonder et al. [27] 2004 14 Object > baseline 6

Amemiya et al. [53] 2012 27 Scene > baseline 10

Jehna et al. [19] 2011 30 Scene > baseline 4

Blonder et al. [27] 2004 14 Scene > baseline

Claeys et al. [54] 2004 16 Color > baseline 10

Leh et al. [55] 2009 1 Color > baseline 4

Kaufmann et al. [56] 2008 12 Color > baseline 1

Orlov et al. [29] 2010 12 Body > baseline 18

“Where” vision

Homola et al. [57] 2012 24 Motion > baseline 2

Schraa-Tam et al. [58] 2008 22 Motion > baseline 12

Morito, Tanabe et al. [59] 2009 28 Motion > baseline 17

Caplan et al. [60] 2006 12 Motion > baseline 16

Katsuyama et al. [61] 2011 31 Motion > baseline 3

Podzebenko et al. [45] 2005 16 Motion > baseline 9

Braddick et al. [62] 2001 3 Motion > noise 14

Braddick et al. [63] 2000 4 Motion > baseline 4

Oreja-Guevara et al. [64] 2004 9 Motion > baseline 61

Bucher et al. [52] 2006 16 Motion > baseline 12

Santi et al. [65] 2003 10 Motion > baseline 14

Aso et al. [66] 2007 12 Motion > baseline 5

Iwami et al. [67] 2002 10 Spatial > baseline 11

Grady et al. [68] 2014 14 Spatial > baseline 11

Joseph et al. [69] 2003 10 Spatial > baseline 4

Joseph et al. [69] 2003 11 Spatial > baseline 5

Joseph et al. [69] 2003 10 Spatial > baseline 3

Joseph et al. [69] 2003 11 Spatial > baseline 3

Zeidman et al. [70] 2012 19 Spatial > baseline 2

Yamamoto et al. [44] 2008 13 Spatial > baseline 30

Katsuyama et al. [61] 2011 31 Spatial > baseline 7

Fraedrich et al. [71] 2010 18 Spatial > baseline 6

Georgieva et al. [72] 2008 18 Spatial > scrambled image 12

Creem-Regehr et al. [46] 2007 23 Spatial > scrambled image 6

Kana et al. [73] 2013 14 Spatial > baseline 11

Wu et al. [74] 2012 19 Spatial > baseline 9

Valyear et al. [49] 2006 3 Spatial > baseline 1

Braddick et al. [63] 2000 4 Spatial > baseline 8

Kaufmann et al. [56] 2008 12 Spatial > baseline 3

Sterzer et al. [75] 2005 12 Spatial > baseline 4

Brouwer et al. [76] 2005 7 Spatial > baseline 7

Cant et al. [77] 2007 9 Spatial > baseline 10

Schoth et al. [78] 2007 22 Spatial > baseline 12

Dumoulin et al. [79] 2004 4 Spatial > noise 2

Baecke et al. [80] 2009 26 Spatial > baseline 6

Gros et al. [41] 2001 6 Spatial > baseline 2

Ritzl et al. [81] 2003 11 Spatial > baseline 10

Negawa et al. [82] 2003 13 Spatial > scrambled image 13

Supplementary Table 2 Activation likelihood estimation results of “what” vision

Cluster

No.

x y z Anatomic region (AAL) Broadmann area

1 -40 -52 -20 Fusiform_L* 37

-44 -76 -6 Occipital_Mid_L* 19

-46 -68 -14 Temporal_Inf_L 19

-28 -84 -16 Occipital_Inf_L* 18

-30 -96 6 Occipital_Mid_L* 17

2 40 -48 -22 Fusiform_R* 37

48 -74 -6 Temporal_Mid_R* 19

42 -62 -14 Temporal_Inf_R 37

26 -66 -10 Fusiform_R 19

52 -64 6 Temporal_Mid_R 37

3 44 10 28 Frontal_Inf_Tri_R* 44

4 52 -40 8 Temporal_Sup_R* 21

5 30 -92 2 Occipital_Mid_R* 18

6 20 -6 -16 Hippocampus_R* -

7 -46 4 30 Frontal_Inf_Oper_L* 44

8 -32 24 0 Insula_L* 47

9 -20 -8 -14 Amygdala_L* -

10 12 -92 6 Occipital_Sup_L* 17

11 -56 -46 10 Temporal_Sup_L* 22

12 -10 -96 2 Occipital_Sup_L* 17

13 -26 -70 -10 Fusiform_L* 18

14 -22 -100 -2 Occipital_Mid_L* 17

15 22 -30 0 Thalamus_R* -

16 -38 -46 48 Parietal_Inf_L* 40

17 32 24 -2 Frontal_Inf_Orb_R* 47

18 48 2 52 Precentral_R* 6

19 -42 18 22 Frontal_Inf_Tri_L* 48

20 -26 -62 62 Parietal_Sup_L* 7

21 32 -56 52 Parietal_Inf_R* 7

22 -28 -70 46 Parietal_Sup_L* 7

23 56 -52 14 Temporal_Sup_R* 21

24 0 22 44 Frontal_Sup_Medial_L

*

32

25 -18 -68 -16 Lingual_L* 18

Statistical level: p< 0.01; coordinates are in MNI spaces

* coordinate chosen for defining the nodes of “where” vision.

L: left; R: right; Inf: inferior; Mid: middle; Sup: superior.

Supplementary Table 3 Activation likelihood estimation results of “where” vision

Cluster

No.

x y z Anatomical region (AAL) Broadmann area

1 -44 -72 -12 Occipital_Inf_L* 19

-46 -72 4 Temporal_Mid_L* 37

-42 -84 4 Occipital_Mid_L 19

-38 -60 -12 Occipital_Inf_L 37

2 52 -68 4 Temporal_Mid_R* 37

44 -70 -12 Temporal_Inf_R* 19

42 -74 -4 Occipital_Mid_R 19

42 -84 2 Occipital_Mid_R 19

36 -84 -14 Occipital_Inf_R 19

3 30 -86 8 Occipital_Mid_R* 18

26 -76 34 Occipital_Sup_R* 19

34 -78 28 Occipital_Mid_R 19

36 -88 14 Occipital_Mid_R 19

32 -78 12 Occipital_Mid_R 19

26 -92 24 Occipital_Sup_R 18

4 22 -62 58 Parietal_Sup_R* 7

10 -62 60 Precuneus_R 7

28 -54 54 Parietal_Sup_R 7

5 -26 -56 60 Parietal_Sup_L* 7

6 30 4 60 Frontal_Mid_R* 8

7 40 -34 46 Postcentral_R* 2

8 -20 -96 12 Occipital_Sup_L* 17

9 -44 -48 56 Postcentral_L* 40

10 -44 -14 56 Precentral_L* 6

-36 -16 62 Precenral_L* 6

11 -26 -88 28 Occipital_Mid_L* 18

12 -42 -32 58 Postcentral_L* 3

13 -10 -22 46 Cingulum_Mid_L*

14 -38 -48 -22 Fusiform_L* 37

15 30 -58 -20 Fusiform_R* 37

16 -28 -70 42 Parietal_Sup_L* 7

17 40 -46 -26 Fusiform_R* 37

18 -24 -2 52 Frontal_Mid_L* 6

19 38 -44 60 Hippocampus_R* 2

20 20 -28 0 Thalamus_R*

21 -22 -8 58 Frontal_Sup_L* 6

22 -34 -44 52 Postcentral_L* 40

Statistical level: p< 0.01; coordinates are in MNI spaces

* coordinate chosen for defining the nodes of “where” vision.

L: left; R: right; Inf: inferior; Mid: middle; Sup: superior.

Supplementary figures

Supplementary figure 1. The ALE map of “what” vision (L, left; R, right).

Supplementary figure 2. The ALE map of “where” vision (L, left; R, right).

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