Sample stimuli

sample 0 sample 1 sample 2 sample 3 sample 4 sample 5 sample 6 sample 7 sample 8 sample 9

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Ferguson2024half-value_delta")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
1.0
2
1.0
3
1.0
4
1.0
5
1.0
6
1.0
7
1.0
8
1.0
9
1.0
10
1.0
11
1.0
12
1.0
13
1.0
14
1.0
15
1.0
16
1.0
17
1.0
18
1.0
19
1.0
20
1.0
21
1.0
22
1.0
23
1.0
24
1.0
25
1.0
26
.975
27
.975
28
.975
29
.975
30
.975
31
.975
32
.942
33
.942
34
.942
35
.942
36
.942
37
.942
38
.942
39
.942
40
.942
41
.942
42
.942
43
.882
44
.882
45
.882
46
.882
47
.882
48
.882
49
.882
50
.882
51
.852
52
.852
53
.852
54
.852
55
.852
56
.852
57
.798
58
.798
59
.798
60
.798
61
.798
62
.771
63
.771
64
.771
65
.771
66
.771
67
.771
68
.771
69
.771
70
.771
71
.771
72
.771
73
.771
74
.771
75
.771
76
.771
77
.771
78
.722
79
.722
80
.722
81
.722
82
.722
83
.722
84
.722
85
.722
86
.698
87
.698
88
.698
89
.698
90
.698
91
.698
92
.698
93
.698
94
.698
95
.653
96
.653
97
.653
98
.631
99
.631
100
.631
101
.631
102
.631
103
.631
104
.631
105
.631
106
.631
107
.631
108
.631
109
.591
110
.591
111
.591
112
.591
113
.591
114
.591
115
.591
116
.571
117
.571
118
.571
119
.571
120
.571
121
.571
122
.571
123
.571
124
.571
125
.571
126
.571
127
.571
128
.571
129
.571
130
.571
131
.535
132
.535
133
.535
134
.517
135
.517
136
.517
137
.517
138
.517
139
.517
140
.517
141
.517
142
.517
143
.517
144
.484
145
.484
146
.484
147
.484
148
.484
149
.484
150
.467
151
.467
152
.467
153
.467
154
.467
155
.467
156
.438
157
.438
158
.423
159
.423
160
.423
161
.423
162
.423
163
.423
164
.423
165
.423
166
.423
167
.423
168
.396
169
.383
170
.383
171
.383
172
.383
173
.383
174
.383
175
.383
176
.383
177
.383
178
.358
179
.358
180
.346
181
.346
182
.346
183
.346
184
.324
185
.324
186
.324
187
.324
188
.324
189
.324
190
.324
191
.313
192
.313
193
.313
194
.313
195
.313
196
.313
197
.313
198
.293
199
.293
200
.293
201
.293
202
.283
203
.283
204
.283
205
.283
206
.283
207
.283
208
.283
209
.283
210
.283
211
.283
212
.283
213
.256
214
.256
215
.256
216
.240
217
.240
218
.232
219
.232
220
.232
221
.232
222
.232
223
.232
224
.217
225
.217
226
.217
227
.210
228
.196
229
.196
230
.190
231
.172
232
.172
233
.172
234
.172
235
.172
236
.172
237
.172
238
.172
239
.155
240
.155
241
.155
242
.155
243
.155
244
.155
245
.155
246
.145
247
.141
248
.141
249
.132
250
.132
251
.127
252
.127
253
.115
254
.115
255
.115
256
.115
257
.115
258
.115
259
.108
260
.104
261
.104
262
.094
263
.094
264
.085
265
.077
266
.077
267
.077
268
.072
269
270
271
272

Benchmark bibtex

        @misc{ferguson_ngo_lee_dicarlo_schrimpf_2024,
         title={How Well is Visual Search Asymmetry predicted by a Binary-Choice, Rapid, Accuracy-based Visual-search, Oddball-detection (BRAVO) task?},
         url={osf.io/5ba3n},
         DOI={10.17605/OSF.IO/5BA3N},
         publisher={OSF},
         author={Ferguson, Michael E, Jr and Ngo, Jerry and Lee, Michael and DiCarlo, James and Schrimpf, Martin},
         year={2024},
         month={Jun}
}

Ceiling

0.90.

Note that scores are relative to this ceiling.

Data: Ferguson2024half

Metric: value_delta