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.V1-pls")
score = benchmark(my_model)

Model scores

Min Alignment Max Alignment

Rank

Model

Score

1
.430
2
.409
3
.407
4
.394
5
.394
6
.392
7
.389
8
.387
9
.385
10
.379
11
.379
12
.379
13
.379
14
.379
15
.379
16
.378
17
.376
18
.375
19
.375
20
.374
21
.374
22
.370
23
.365
24
.358
25
.355
26
.353
27
.347
28
.344
29
.343
30
.343
31
.341
32
.338
33
.338
34
.334
35
.329
36
.327
37
.326
38
.325
39
.324
40
.322
41
.322
42
.318
43
.318
44
.317
45
.316
46
.316
47
.316
48
.316
49
.316
50
.316
51
.316
52
.316
53
.316
54
.316
55
.316
56
.316
57
.314
58
.313
59
.311
60
.310
61
.310
62
.309
63
.308
64
.305
65
.305
66
.304
67
.303
68
.301
69
.301
70
.301
71
.301
72
.301
73
.301
74
.301
75
.301
76
.301
77
.301
78
.301
79
.300
80
.300
81
.300
82
.300
83
.300
84
.299
85
.299
86
.299
87
.299
88
.299
89
.298
90
.298
91
.298
92
.298
93
.297
94
.297
95
.296
96
.295
97
.295
98
.294
99
.294
100
.293
101
.291
102
.290
103
.290
104
.290
105
.290
106
.290
107
.289
108
.289
109
.289
110
.289
111
.289
112
.289
113
.288
114
.288
115
.287
116
.287
117
.287
118
.286
119
.286
120
.285
121
.285
122
.285
123
.285
124
.284
125
.284
126
.283
127
.283
128
.283
129
.283
130
.282
131
.282
132
.282
133
.282
134
.282
135
.282
136
.282
137
.281
138
.281
139
.281
140
.279
141
.279
142
.279
143
.279
144
.279
145
.278
146
.278
147
.278
148
.278
149
.278
150
.278
151
.278
152
.278
153
.278
154
.278
155
.278
156
.278
157
.278
158
.278
159
.278
160
.278
161
.277
162
.277
163
.277
164
.277
165
.277
166
.277
167
.276
168
.276
169
.276
170
.275
171
.275
172
.275
173
.275
174
.275
175
.274
176
.274
177
.274
178
.274
179
.274
180
.274
181
.274
182
.274
183
.273
184
.273
185
.273
186
.273
187
.272
188
.272
189
.272
190
.271
191
.271
192
.271
193
.271
194
.271
195
.271
196
.270
197
.270
198
.270
199
.270
200
.270
201
.269
202
.269
203
.269
204
.269
205
.268
206
.268
207
.267
208
.267
209
.267
210
.267
211
.267
212
.266
213
.266
214
.266
215
.265
216
.265
217
.265
218
.264
219
.264
220
.264
221
.264
222
.264
223
.263
224
.263
225
.263
226
.263
227
.263
228
.263
229
.262
230
.262
231
.262
232
.262
233
.261
234
.261
235
.260
236
.260
237
.259
238
.259
239
.258
240
.258
241
.258
242
.258
243
.258
244
.258
245
.257
246
.257
247
.256
248
.256
249
.256
250
.256
251
.255
252
.255
253
.254
254
.254
255
.254
256
.254
257
.254
258
.253
259
.253
260
.253
261
.253
262
.252
263
.252
264
.251
265
.251
266
.251
267
.250
268
.249
269
.249
270
.248
271
.248
272
.248
273
.248
274
.248
275
.247
276
.247
277
.247
278
.247
279
.247
280
.246
281
.246
282
.246
283
.246
284
.246
285
.246
286
.245
287
.245
288
.245
289
.245
290
.245
291
.245
292
.244
293
.244
294
.244
295
.244
296
.243
297
.243
298
.243
299
.242
300
.242
301
.242
302
.242
303
.242
304
.242
305
.242
306
.241
307
.241
308
.241
309
.241
310
.241
311
.241
312
.240
313
.239
314
.239
315
.239
316
.239
317
.238
318
.238
319
.238
320
.238
321
.238
322
.237
323
.237
324
.236
325
.236
326
.236
327
.235
328
.235
329
.235
330
.235
331
.234
332
.234
333
.234
334
.233
335
.233
336
.233
337
.233
338
.233
339
.232
340
.232
341
.231
342
.231
343
.230
344
.229
345
.229
346
.228
347
.228
348
.227
349
.227
350
.227
351
.226
352
.225
353
.224
354
.223
355
.223
356
.223
357
.223
358
.223
359
.223
360
.222
361
.222
362
.222
363
.221
364
.221
365
.221
366
.220
367
.220
368
.220
369
.220
370
.219
371
.219
372
.218
373
.217
374
.217
375
.217
376
.217
377
.216
378
.215
379
.215
380
.215
381
.215
382
.215
383
.213
384
.213
385
.212
386
.210
387
.210
388
.209
389
.208
390
.208
391
.207
392
.206
393
.206
394
.206
395
.206
396
.206
397
.206
398
.206
399
.206
400
.206
401
.206
402
.206
403
.205
404
.200
405
.198
406
.198
407
.193
408
.191
409
.190
410
.184
411
.183
412
.183
413
.183
414
.182
415
.175
416
.173
417
.160
418
.133
419
.129
420
.114
421
.089
422
.061
423
.053
424
.048
425
.047
426
.043
427
X
428
X
429
X
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

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

0.87.

Note that scores are relative to this ceiling.

Data: FreemanZiemba2013.V1

315 stimuli recordings from 102 sites in V1

Metric: pls