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("Marques2020_Ringach2002-or_selective")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
1.0
2
1.0
3
1.0
4
1.000
5
1.0
6
1.000
7
1.0
8
1.0
9
1.000
10
1.0
11
1.000
12
1.000
13
1.000
14
1.000
15
1.000
16
.999
17
.999
18
1.000
19
.999
20
.999
21
.999
22
.999
23
.999
24
.999
25
.999
26
.999
27
.999
28
.999
29
.999
30
.999
31
.999
32
.999
33
.999
34
.998
35
.998
36
.999
37
.999
38
.998
39
.998
40
.998
41
.998
42
.997
43
.997
44
.997
45
.996
46
.996
47
.996
48
.996
49
.996
50
.996
51
.996
52
.996
53
.996
54
.995
55
.996
56
.995
57
.995
58
.995
59
.995
60
.995
61
.995
62
.994
63
.995
64
.994
65
.994
66
.994
67
.993
68
.993
69
.992
70
.992
71
.991
72
.991
73
.991
74
.990
75
.990
76
.989
77
.988
78
.988
79
.986
80
.986
81
.986
82
.986
83
.986
84
.986
85
.986
86
.986
87
.986
88
.986
89
.986
90
.986
91
.986
92
.986
93
.986
94
.986
95
.986
96
.986
97
.986
98
.986
99
.986
100
.986
101
.986
102
.986
103
.986
104
.986
105
.986
106
.986
107
.986
108
.986
109
.985
110
.984
111
.984
112
.984
113
.984
114
.983
115
.982
116
.982
117
.981
118
.981
119
.981
120
.981
121
.980
122
.978
123
.977
124
.975
125
.975
126
.975
127
.975
128
.974
129
.974
130
.971
131
.971
132
.970
133
.970
134
.968
135
.966
136
.966
137
.965
138
.965
139
.963
140
.964
141
.964
142
.963
143
.962
144
.958
145
.958
146
.956
147
.954
148
.953
149
.952
150
.951
151
.949
152
.948
153
.946
154
.946
155
.945
156
.945
157
.942
158
.941
159
.941
160
.940
161
.939
162
.939
163
.939
164
.939
165
.937
166
.937
167
.936
168
.935
169
.935
170
.933
171
.933
172
.933
173
.931
174
.931
175
.931
176
.929
177
.928
178
.927
179
.927
180
.927
181
.925
182
.925
183
.925
184
.925
185
.924
186
.923
187
.921
188
.919
189
.919
190
.917
191
.915
192
.914
193
.913
194
.912
195
.911
196
.911
197
.909
198
.909
199
.908
200
.907
201
.907
202
.906
203
.905
204
.905
205
.905
206
.901
207
.901
208
.901
209
.900
210
.900
211
.900
212
.900
213
.900
214
.900
215
.900
216
.898
217
.898
218
.897
219
.897
220
.897
221
.897
222
.896
223
.895
224
.895
225
.894
226
.893
227
.893
228
.892
229
.891
230
.890
231
.889
232
.889
233
.888
234
.886
235
.885
236
.884
237
.884
238
.883
239
.883
240
.880
241
.880
242
.879
243
.878
244
.877
245
.877
246
.876
247
.876
248
.873
249
.873
250
.871
251
.871
252
.870
253
.868
254
.868
255
.865
256
.862
257
.860
258
.860
259
.857
260
.855
261
.848
262
.846
263
.846
264
.846
265
.845
266
.844
267
.839
268
.839
269
.838
270
.838
271
.838
272
.835
273
.834
274
.834
275
.828
276
.828
277
.828
278
.827
279
.826
280
.826
281
.823
282
.821
283
.820
284
.820
285
.813
286
.813
287
.812
288
.805
289
.800
290
.797
291
.797
292
.797
293
.795
294
.795
295
.795
296
.795
297
.795
298
.793
299
.793
300
.787
301
.786
302
.782
303
.781
304
.780
305
.774
306
.771
307
.765
308
.754
309
.754
310
.748
311
.748
312
.747
313
.742
314
.736
315
.735
316
.734
317
.733
318
.718
319
.718
320
.711
321
.694
322
.692
323
.686
324
.681
325
.676
326
.672
327
.662
328
.648
329
.643
330
.628
331
.607
332
.601
333
.557
334
.513
335
.481
336
.370
337
.322
338
.321
339
.274
340
.138
341
.052
342
X
343
X
344
X
345
X
346
X
347
X
348
X
349
X
350
X
351
X
352
X
353
X
354
X
355
X
356
X
357
X
358
X
359
X
360
X
361
X
362
X
363
X
364
X
365
X

Benchmark bibtex

None

Ceiling

0.99.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: or_selective