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
.293
102
.291
103
.290
104
.290
105
.290
106
.290
107
.290
108
.289
109
.289
110
.289
111
.289
112
.289
113
.289
114
.288
115
.288
116
.287
117
.287
118
.287
119
.286
120
.286
121
.285
122
.285
123
.285
124
.285
125
.284
126
.284
127
.283
128
.283
129
.283
130
.283
131
.282
132
.282
133
.282
134
.282
135
.282
136
.282
137
.282
138
.281
139
.281
140
.281
141
.279
142
.279
143
.279
144
.279
145
.279
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
.278
162
.277
163
.277
164
.277
165
.277
166
.277
167
.277
168
.276
169
.276
170
.276
171
.275
172
.275
173
.275
174
.275
175
.275
176
.274
177
.274
178
.274
179
.274
180
.274
181
.274
182
.274
183
.274
184
.273
185
.273
186
.273
187
.273
188
.272
189
.272
190
.272
191
.271
192
.271
193
.271
194
.271
195
.271
196
.271
197
.270
198
.270
199
.270
200
.270
201
.270
202
.269
203
.269
204
.269
205
.269
206
.268
207
.268
208
.267
209
.267
210
.267
211
.267
212
.267
213
.266
214
.266
215
.266
216
.265
217
.265
218
.265
219
.264
220
.264
221
.264
222
.264
223
.264
224
.263
225
.263
226
.263
227
.263
228
.263
229
.263
230
.262
231
.262
232
.262
233
.262
234
.261
235
.261
236
.260
237
.260
238
.259
239
.259
240
.258
241
.258
242
.258
243
.258
244
.258
245
.258
246
.257
247
.257
248
.256
249
.256
250
.256
251
.256
252
.255
253
.255
254
.254
255
.254
256
.254
257
.254
258
.254
259
.253
260
.253
261
.253
262
.253
263
.252
264
.252
265
.251
266
.251
267
.251
268
.250
269
.249
270
.249
271
.248
272
.248
273
.248
274
.248
275
.248
276
.247
277
.247
278
.247
279
.247
280
.247
281
.246
282
.246
283
.246
284
.246
285
.246
286
.246
287
.245
288
.245
289
.245
290
.245
291
.245
292
.245
293
.244
294
.244
295
.244
296
.244
297
.243
298
.243
299
.243
300
.242
301
.242
302
.242
303
.242
304
.242
305
.242
306
.242
307
.241
308
.241
309
.241
310
.241
311
.241
312
.241
313
.240
314
.239
315
.239
316
.239
317
.239
318
.238
319
.238
320
.238
321
.238
322
.238
323
.238
324
.237
325
.237
326
.236
327
.236
328
.236
329
.235
330
.235
331
.235
332
.235
333
.234
334
.234
335
.234
336
.233
337
.233
338
.233
339
.233
340
.233
341
.232
342
.232
343
.231
344
.231
345
.230
346
.229
347
.229
348
.228
349
.228
350
.227
351
.227
352
.227
353
.226
354
.225
355
.224
356
.223
357
.223
358
.223
359
.223
360
.223
361
.223
362
.222
363
.222
364
.222
365
.221
366
.221
367
.221
368
.220
369
.220
370
.220
371
.220
372
.219
373
.219
374
.218
375
.217
376
.217
377
.217
378
.217
379
.216
380
.215
381
.215
382
.215
383
.215
384
.215
385
.213
386
.213
387
.212
388
.210
389
.210
390
.209
391
.208
392
.208
393
.207
394
.206
395
.206
396
.206
397
.206
398
.206
399
.206
400
.206
401
.206
402
.206
403
.206
404
.206
405
.205
406
.200
407
.198
408
.198
409
.193
410
.191
411
.190
412
.184
413
.183
414
.183
415
.183
416
.182
417
.175
418
.173
419
.160
420
.133
421
.129
422
.114
423
.089
424
.061
425
.053
426
.048
427
.047
428
.043
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
444
X
445
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