SUPPLEMENTARY MATERIAL
Inferring a dual-stream model of mentalizing from the disconnection
of white matter fibres
Guillaume Herbet, Gilles Lafargue, François Bonnetblanc, Sylvie Moritz-Gasser, Nicolas Manjot de
Champfleur and Hugues Duffau
This file contains two supplementary tables:
-
Table S1: Sociodemographic and clinical data for all patients
Table S2: descriptive statistics of mentalizing data
Table S3: Summary of multiple regression analyses
Supplementary Table 1: Sociodemographic and clinical data for all patients
Sociodemographic variables
Clinical Variables
ID
Gend.
Age
Handedness
Educ.
level
IQ
Time
Side
Grade
Rec.
Surg.
Pre.
CT
% of
LR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
37
50
51
52
53
54
55
56
57
58
59
60
61
62
M
M
F
F
F
F
F
F
F
M
M
F
M
M
F
F
M
F
F
M
M
M
M
F
F
F
M
M
M
M
F
F
M
M
M
M
F
F
F
F
F
M
M
M
F
M
M
M
F
F
F
M
F
M
M
F
F
M
M
F
M
M
27
32
55
34
22
29
41
24
53
32
36
39
54
40
35
34
37
35
31
26
47
41
31
44
53
38
21
34
34
53
46
39
26
41
18
27
36
47
65
41
41
43
27
63
53
33
51
29
37
24
41
34
62
37
48
38
46
32
40
41
31
49
R
R
R
R
R
R
R
R
R
R
R
L
R
L
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
L
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
L
R
R
R
R
R
9
9
26
15
9
9
16
14
16
12
12
14
9
12
14
15
9
12
17
14
9
9
17
12
14
17
9
12
22
12
18
17
17
17
12
12
17
22
17
9
14
12
17
14
17
12
17
15
17
12
14
15
16
17
17
12
17
14
17
12
17
17
106
113
106
101
113
100
100
103
107
100
101
101
90
94
106
111
102
113
113
100
90
90
111
106
104
110
109
111
123
110
117
118
108
117
110
113
109
115
113
107
115
103
118
115
113
112
110
115
110
106
110
114
110
108
115
110
106
105
108
110
106
114
3
9
26
23
3
3
3
3
3
21
18
3
12
3
25
25
3
9
3
20
6
12
3
3
3
3
27
3
3
3
26
6
3
3
3
32
3
6
9
12
3
24
10
6
54
3
22
6
3
3
3
3
24
6
3
3
9
12
3
27
3
12
L
L
R
R
R
L
R
R
R
L
L
R
R
R
R
R
R
R
R
R
R
L
R
R
L
R
L
R
R
L
L
R
R
L
R
R
R
R
R
R
R
L
L
R
R
R
R
R
L
R
R
R
R
R
R
R
R
R
R
L
R
L
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
1
1
1
1
1
1
1
1
1
1
2
1
1
2
2
1
2
1
1
1
1
2
2
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
2
2
1
1
1
1
1
3
2
2
2
1
1
2
1
1
1
1
1
2
1
2
2
1
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
no
no
no
no
no
no
yes
no
no
no
no
no
yes
no
yes
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
yes
no
no
NO
no
no
no
no
no
no
yes
no
no
no
no
no
no
no
no
no
no
no
no
no
100
70
93
94
95
97
93
100
100
100
100
90
98
95
85
88
95
95
100
90
85
95
100
98
96
80
85
80
96
79
97
100
98
100
100
94
90
95
95
93
89
98
100
89
100
97
100
98
95
95
95
93
95
95
100
95
95
90
90
95
94
95
Volume of
RC (1*1*1
voxels)
8974
15506
6138
92238
28885
140568
18818
24870
14727
17230
126854
27614
162570
69565
65306
199071
23363
9790
51263
163810
41536
13063
9078
146713
113049
159860
24103
17508
95361
29609
188978
43543
129233
22795
4411
7440
84306
89245
109483
123944
49299
5863
92574
111695
30230
26014
99494
239138
155666
60817
52317
145928
50701
98464
11499
100057
23844
71389
7857
141065
75346
11012
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
M
M
M
M
F
F
M
F
M
F
M
M
F
F
F
M
M
M
F
M
M
F
F
M
F
F
F
M
F
F
F
27
25
28
50
47
62
27
25
22
31
23
46
36
43
53
38
53
41
36
34
28
31
34
41
32
53
42
38
42
39
42
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
12
12
12
17
17
9
17
17
12
14
12
9
17
12
14
17
12
17
17
9
14
14
17
17
9
17
12
14
14
17
9
97
110
100
105
117
94
120
100
114
94
100
114
106
115
108
113
101
md
110
104
100
108
106
115
94
110
101
103
108
118
103
3
24
3
9
23
27
3
3
9
11
26
84
3
6
36
3
13
3
3
36
9
26
3
36
3
96
3
12
3
9
15
R
L
R
R
R
R
R
R
R
L
L
R
R
R
L
R
L
R
R
L
R
L
R
R
L
R
R
R
R
R
R
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
II
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
3
1
1
1
1
3
1
1
1
1
1
1
2
1
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
AW
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
97
76
80
95
95
96
90
100
95
90
100
100
98
97
91
100
90
100
100
95
97
100
95
100
95
98
83
94
95
100
100
148922
289947
115085
183722
55759
14854
141253
155851
24183
75407
89450
76036
103987
153304
5552
7212
12266
45980
13905
7373
16641
117038
138563
18764
63864
10388
104898
47065
33833
39109
28127
Gend. = gender, M = male, F = female, Educ. = educational, Rec. = Recurrence, Surg. = surgery, pre CT =
preoperative chemotherapy, LR = lesion resection, RC = resective cavity, md = missing data.
Supplementary Table 2: Descriptive statistics of mentalizing data
n
Mean
SD
Min
Max
% of CR
90
61.67
11
36.11
83.33
HLMT (Comic strips Task)
Attribution of intentions (AI) - % of CR
84
84.69
13.34
39.9
100
Physical Causality (PhC) - % of CR
84
93.75
7.29
42.9
100
Differential error rate (DER) - % of CR
84
-9.05
9.95
-35.71
7.14
LLMT (RME task)
LLMT = low-level mentalizing task; HHLT = high-level mentalizing task; CR = correct responses
Supplementary Table 3: Summary of multiple regression analyses
Global model
Age
Premorbid IQ
Resective
Volume
Time elapsed
since surgery
R2
P
β
P
β
P
β
P
β
P
0.082
0.11
-0.24
0.03
-0.14
0.17
-0.05
0.6
-0.075
0.49
0.23
0.0003
-0.23
0.032
0.4
0.0001
-0.037
0.71
-0.11
0.26
PhC
0.225
0.0004
-0.26
0.018
0.31
0.002
-0.12
0.23
-0.21
0.05
DER
0.11
0.04
-0.12
0.28
0.32
0.004
-0.038
0.72
-0.003
0.97
LLMT (RME
task)
HLMT (Comic
strips task)
AI
LLMT = low-level mentalizing task; HHLT = high-level mentalizing task; AI = Attribution of Intentions condition;
PhC = Physical Causality condition; DER= Differential error rate between AI and PhC conditions