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
.320
117
.320
118
.320
119
.319
120
.319
121
.319
122
.318
123
.318
124
.318
125
.318
126
.318
127
.318
128
.317
129
.317
130
.317
131
.317
132
.317
133
.317
134
.316
135
.316
136
.315
137
.315
138
.315
139
.314
140
.313
141
.313
142
.313
143
.313
144
.312
145
.312
146
.312
147
.312
148
.312
149
.312
150
.311
151
.311
152
.311
153
.311
154
.311
155
.311
156
.311
157
.311
158
.310
159
.310
160
.309
161
.309
162
.309
163
.309
164
.308
165
.308
166
.308
167
.308
168
.308
169
.308
170
.307
171
.307
172
.307
173
.307
174
.307
175
.307
176
.307
177
.306
178
.306
179
.306
180
.306
181
.306
182
.306
183
.306
184
.306
185
.306
186
.306
187
.306
188
.305
189
.305
190
.305
191
.305
192
.305
193
.305
194
.304
195
.304
196
.304
197
.304
198
.304
199
.304
200
.304
201
.304
202
.303
203
.303
204
.303
205
.302
206
.302
207
.302
208
.302
209
.302
210
.301
211
.301
212
.301
213
.301
214
.301
215
.301
216
.301
217
.300
218
.300
219
.300
220
.299
221
.299
222
.299
223
.299
224
.299
225
.298
226
.298
227
.298
228
.298
229
.297
230
.297
231
.296
232
.296
233
.296
234
.295
235
.295
236
.295
237
.295
238
.295
239
.295
240
.295
241
.295
242
.295
243
.295
244
.295
245
.294
246
.294
247
.294
248
.294
249
.294
250
.293
251
.293
252
.293
253
.293
254
.293
255
.293
256
.293
257
.293
258
.293
259
.292
260
.291
261
.291
262
.291
263
.291
264
.291
265
.290
266
.290
267
.289
268
.289
269
.289
270
.288
271
.288
272
.288
273
.288
274
.287
275
.287
276
.287
277
.287
278
.286
279
.286
280
.286
281
.286
282
.285
283
.285
284
.285
285
.285
286
.285
287
.284
288
.284
289
.284
290
.283
291
.283
292
.282
293
.282
294
.281
295
.281
296
.280
297
.279
298
.278
299
.278
300
.278
301
.278
302
.276
303
.275
304
.275
305
.274
306
.274
307
.273
308
.273
309
.272
310
.272
311
.272
312
.271
313
.270
314
.270
315
.270
316
.269
317
.269
318
.267
319
.267
320
.266
321
.265
322
.265
323
.265
324
.265
325
.263
326
.263
327
.263
328
.262
329
.262
330
.261
331
.261
332
.261
333
.260
334
.260
335
.260
336
.259
337
.259
338
.258
339
.257
340
.257
341
.256
342
.255
343
.255
344
.255
345
.254
346
.254
347
.252
348
.252
349
.251
350
.251
351
.250
352
.249
353
.249
354
.249
355
.248
356
.248
357
.248
358
.247
359
.246
360
.246
361
.246
362
.246
363
.243
364
.243
365
.243
366
.242
367
.238
368
.238
369
.238
370
.238
371
.238
372
.238
373
.238
374
.238
375
.238
376
.238
377
.238
378
.237
379
.237
380
.234
381
.234
382
.233
383
.232
384
.232
385
.232
386
.231
387
.231
388
.230
389
.230
390
.230
391
.229
392
.229
393
.228
394
.227
395
.226
396
.226
397
.223
398
.222
399
.218
400
.218
401
.217
402
.216
403
.215
404
.204
405
.202
406
.201
407
.200
408
.198
409
.193
410
.189
411
.182
412
.180
413
.176
414
.174
415
.165
416
.165
417
.150
418
.132
419
.130
420
.128
421
.126
422
.126
423
.120
424
.116
425
.111
426
.107
427
.056
428
.029
429
.024
430
.008
431
.007
432
.005
433
.003
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448

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