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("FreemanZiemba2013.V2-pls")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.402
2
.402
3
.397
4
.393
5
.391
6
.384
7
.380
8
.373
9
.369
10
.365
11
.364
12
.362
13
.361
14
.360
15
.360
16
.360
17
.360
18
.357
19
.356
20
.356
21
.356
22
.353
23
.353
24
.353
25
.353
26
.353
27
.353
28
.353
29
.353
30
.353
31
.353
32
.353
33
.353
34
.353
35
.349
36
.346
37
.346
38
.345
39
.342
40
.342
41
.341
42
.341
43
.341
44
.341
45
.340
46
.340
47
.339
48
.339
49
.339
50
.339
51
.339
52
.338
53
.337
54
.337
55
.336
56
.336
57
.336
58
.335
59
.335
60
.335
61
.334
62
.334
63
.334
64
.334
65
.333
66
.333
67
.332
68
.332
69
.332
70
.332
71
.332
72
.332
73
.331
74
.331
75
.330
76
.330
77
.329
78
.329
79
.329
80
.328
81
.328
82
.328
83
.327
84
.327
85
.327
86
.326
87
.326
88
.325
89
.325
90
.324
91
.324
92
.324
93
.324
94
.323
95
.323
96
.323
97
.322
98
.322
99
.322
100
.322
101
.322
102
.321
103
.321
104
.321
105
.321
106
.321
107
.321
108
.320
109
.320
110
.320
111
.320
112
.320
113
.320
114
.320
115
.320
116
.319
117
.319
118
.319
119
.318
120
.318
121
.318
122
.318
123
.318
124
.318
125
.317
126
.317
127
.317
128
.317
129
.317
130
.317
131
.316
132
.316
133
.315
134
.315
135
.315
136
.314
137
.313
138
.313
139
.313
140
.313
141
.312
142
.312
143
.312
144
.312
145
.312
146
.312
147
.311
148
.311
149
.311
150
.311
151
.311
152
.311
153
.311
154
.311
155
.310
156
.310
157
.309
158
.309
159
.309
160
.309
161
.308
162
.308
163
.308
164
.308
165
.308
166
.308
167
.307
168
.307
169
.307
170
.307
171
.307
172
.307
173
.307
174
.306
175
.306
176
.306
177
.306
178
.306
179
.306
180
.306
181
.306
182
.306
183
.306
184
.306
185
.305
186
.305
187
.305
188
.305
189
.305
190
.305
191
.304
192
.304
193
.304
194
.304
195
.304
196
.304
197
.304
198
.304
199
.303
200
.303
201
.303
202
.302
203
.302
204
.302
205
.302
206
.302
207
.301
208
.301
209
.301
210
.301
211
.301
212
.301
213
.301
214
.300
215
.300
216
.300
217
.299
218
.299
219
.299
220
.299
221
.299
222
.298
223
.298
224
.298
225
.298
226
.297
227
.297
228
.296
229
.296
230
.296
231
.295
232
.295
233
.295
234
.295
235
.295
236
.295
237
.295
238
.295
239
.295
240
.295
241
.295
242
.294
243
.294
244
.294
245
.294
246
.294
247
.293
248
.293
249
.293
250
.293
251
.293
252
.293
253
.293
254
.293
255
.292
256
.291
257
.291
258
.291
259
.291
260
.291
261
.290
262
.290
263
.290
264
.289
265
.289
266
.289
267
.288
268
.288
269
.288
270
.288
271
.287
272
.287
273
.287
274
.287
275
.286
276
.286
277
.286
278
.286
279
.285
280
.285
281
.285
282
.285
283
.285
284
.284
285
.284
286
.284
287
.283
288
.283
289
.282
290
.282
291
.281
292
.281
293
.280
294
.279
295
.278
296
.278
297
.278
298
.278
299
.276
300
.275
301
.275
302
.274
303
.274
304
.273
305
.273
306
.272
307
.272
308
.272
309
.271
310
.270
311
.270
312
.270
313
.269
314
.269
315
.267
316
.267
317
.266
318
.265
319
.265
320
.265
321
.265
322
.263
323
.263
324
.262
325
.262
326
.261
327
.261
328
.261
329
.260
330
.260
331
.260
332
.259
333
.259
334
.258
335
.257
336
.257
337
.256
338
.255
339
.255
340
.255
341
.254
342
.254
343
.252
344
.252
345
.251
346
.251
347
.250
348
.249
349
.249
350
.249
351
.248
352
.248
353
.248
354
.247
355
.246
356
.246
357
.246
358
.246
359
.243
360
.243
361
.243
362
.242
363
.238
364
.238
365
.238
366
.238
367
.238
368
.238
369
.238
370
.238
371
.238
372
.238
373
.238
374
.237
375
.237
376
.234
377
.234
378
.233
379
.232
380
.232
381
.232
382
.231
383
.231
384
.230
385
.230
386
.230
387
.229
388
.229
389
.228
390
.227
391
.226
392
.226
393
.223
394
.222
395
.218
396
.218
397
.217
398
.216
399
.215
400
.204
401
.202
402
.201
403
.200
404
.198
405
.193
406
.189
407
.182
408
.180
409
.176
410
.174
411
.165
412
.165
413
.150
414
.132
415
.130
416
.128
417
.126
418
.126
419
.120
420
.116
421
.111
422
.107
423
.056
424
.029
425
.024
426
.008
427
.007
428
.005
429
.003
430
X
431
X
432
X
433
X
434
X
435
X
436
X
437
X
438
X
439
X
440
X
441
X
442
X
443
X
444
X

Benchmark bibtex

@Article{Freeman2013,
                author={Freeman, Jeremy
                and Ziemba, Corey M.
                and Heeger, David J.
                and Simoncelli, Eero P.
                and Movshon, J. Anthony},
                title={A functional and perceptual signature of the second visual area in primates},
                journal={Nature Neuroscience},
                year={2013},
                month={Jul},
                day={01},
                volume={16},
                number={7},
                pages={974-981},
                abstract={The authors examined neuronal responses in V1 and V2 to synthetic texture stimuli that replicate higher-order statistical dependencies found in natural images. V2, but not V1, responded differentially to these textures, in both macaque (single neurons) and human (fMRI). Human detection of naturalistic structure in the same images was predicted by V2 responses, suggesting a role for V2 in representing natural image structure.},
                issn={1546-1726},
                doi={10.1038/nn.3402},
                url={https://doi.org/10.1038/nn.3402}
                }
            

Ceiling

0.82.

Note that scores are relative to this ceiling.

Data: FreemanZiemba2013.V2

315 stimuli recordings from 103 sites in V2

Metric: pls