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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Li2026.V2-ridgecv")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	mehrer2020_alexnet_training_seed_01_fov4	.439
2	AlexNet_SIN_fov4	.432
3	ReAlnet01_cornet_fov4	.425
4	ReAlnet06_cornet	.348
5	ReAlnet08_cornet	.345
6	ReAlnet07_cornet	.345
7	ReAlnet09_cornet	.345
8	ReAlnet05_cornet	.344
9	ReAlnet02_cornet	.343
10	ReAlnet10_cornet	.343
11	ReAlnet03_cornet	.341
12	ReAlnet01_cornet	.341
13	ReAlnet04_cornet	.340
14	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.339
15	resnet50_tutorial	.337
16	VOneCORnet-S	.337
17	efficientnet_b1_imagenet_full	.335
18	dinov2_vitl14_reg_lc	.334
19	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.334
20	cvt_cvt-13-224-in1k_4_LucyV4	.331
21	compact_resnet50_robust_V4	.328
22	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.324
23	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.319
24	resnet50_barlowtwins_linhead	.319
25	resnet50_byol_linhead	.319
26	ijepa_vith14_linhead	.315
27	regnety_032	.314
28	resnet18_ecoset_full	.313
29	resnet50_vicreg_linhead	.313
30	cvt_cvt-21-384-in1k_4_LucyV4	.313
31	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.312
32	resnet50_simsiam_linhead	.311
33	resnet50_robust_l2_eps1	.310
34	effnetb1_272x240	.310
35	resnet50_ewconplus_wzc	.308
36	deit_small_imagenet_full_seed-0	.306
37	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.306
38	resnet152_ecoset_full	.304
39	mehrer2020_alexnet_training_seed_09	.303
40	mehrer2020_alexnet_training_seed_06	.303
41	mehrer2020_alexnet_training_seed_05	.302
42	resnet34_imagenet_full	.302
43	mehrer2020_alexnet_training_seed_10	.302
44	mehrer2020_alexnet_training_seed_07	.300
45	mehrer2020_alexnet_training_seed_03	.300
46	mehrer2020_alexnet_training_seed_02	.300
47	mehrer2020_alexnet_training_seed_08	.298
48	AlexNet_SIN	.297
49	mehrer2020_alexnet_training_seed_04	.297
50	resnet152_imagenet_full	.297
51	resnet101_ecoset_full	.297
52	cvt_cvt-13-384-in1k_4_LucyV4	.296
53	resnet34_ecoset_full	.296
54	dinov2_vitl14_lc	.296
55	mobilenet_v2_1_4_224	.295
56	resnet50-SIN_IN	.295
57	seresnext50_32x4d	.295
58	mehrer2020_alexnet_training_seed_01	.294
59	focalnet_tiny_lrf_in1k	.294
60	voneresnet-50-non_stochastic	.293
61	resnet50-SIN	.290
62	resnet_50_v1_spiking	.287
63	resnet_50_v1	.287
64	resnet50-sup	.287
65	cvt_cvt-21-224-in1k_4_LucyV4	.287
66	vit_large_patch14_clip_336:laion2b_ft_in1k	.287
67	ReAlnet01_cornet_fov12	.287
68	deit_small_imagenet_100_seed-0	.286
69	resnet50-VITO-8deg-cc	.285
70	resnet50-vitoimagevidnet8	.285
71	eicircuit_resnet18_bn_20260919	.285
72	AdvProp_efficientnet-b4	.285
73	deit_base_imagenet_full_seed-0	.283
74	efficientnet_b0_imagenet_full	.282
75	resnet50-SIN_IN_IN	.281
76	resnet_SIN_IN_FT_IN	.281
77	resnet_50_v2	.280
78	antialiased-r50	.276
79	alexnet	.276
80	voneresnet-50	.273
81	AdvProp_efficientnet-b8	.273
82	densenet-121	.272
83	Res2Net50_26w_4s	.272
84	resnet18_imagenet_full	.270
85	ReAlnet01_cornet_fov16	.270
86	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.269
87	custom_model_cv_18_dagger_408	.267
88	AdvProp_efficientnet-b6	.267
89	pnasnet_large_halfPrecision	.266
90	grcnn	.265
91	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.265
92	resnet50-moclr8deg	.263
93	resnet50_imagenet_100_seed-0	.260
94	convnext_large_imagenet_full_seed-0	.260
95	shufflenet_v2_x1_0	.259
96	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.259
97	convnext_femto_ols:d1_in1k	.256
98	convnext_large:fb_in22k_ft_in1k	.251
99	efficientnet_b2_imagenet_full	.250
100	convnext_tiny_sup	.249
101	vit_relpos_base_patch16_clsgap_224:sw_in1k	.247
102	convnext_tiny_imagenet_full_seed-0	.246
103	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.244
104	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.243
105	AdvProp_efficientnet-b7	.241
106	resnet50_imagenet_full	.239
107	deit_large_imagenet_full_seed-0	.239
108	resnext101_32x8d_wsl	.237
109	AlexNet_SIN_fov12	.234
110	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.234
111	resnext101_32x16d_wsl	.228
112	vit_large_patch14_clip_224:openai_ft_in1k	.228
113	mehrer2020_alexnet_training_seed_01_fov12	.224
114	gabor_filter_entropy_4x4_v2_forcedCosine	.223
115	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.223
116	gabor_filter_entropy_4x4_v2	.221
117	alexnet_training_seed_10	.217
118	alexnet_training_seed_01	.216
119	resnet-50-robust	.216
120	alexnet_training_seed_07	.216
121	resnext101_32x32d_wsl	.212
122	convnext_small_imagenet_100_seed-0	.211
123	alexnet_training_seed_03	.208
124	resnext101_32x48d_wsl	.204
125	mehrer2020_alexnet_training_seed_01_fov16	.204
126	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.203
127	alexnet_training_seed_02	.201
128	convnext_base_imagenet_full_seed-0	.200
129	vit_large_patch14_clip_224:laion2b_ft_in1k	.199
130	convnext_xlarge:fb_in22k_ft_in1k	.197
131	AlexNet_SIN_fov16	.197
132	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.190
133	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.189
134	alexnet_training_seed_09	.188
135	alexnet_training_seed_06	.186
136	convnext_small_imagenet_full_seed-0	.184
137	AT_efficientnet-b2	.180
138	AdvProp_efficientnet-b2	.180
139	convnext_tiny:in12k_ft_in1k	.171
140	convnext_base:clip_laiona_augreg_ft_in1k_384	.169
141	resnet50_ecoset_full	.166
142	vit_base_patch16_clip_224:openai_ft_in1k	.162
143	efficientnet_b0	.162
144	resnet101_imagenet_full	.160
145	gabor_filter_entropy_4x4	.141
146	ViT_L_32_imagenet1k	.060
147	gabor_filter_mean_abs_4x4_v2	.051
148	hmax	.036
149	resnet50_simclr_linhead_01norm

Benchmark bibtex

@article{li2026triplen,
    title = {Triple-N dataset: large-scale fMRI-guided dense recordings of nonhuman
             primate neural responses to natural scenes},
    author = {Li, Yipeng and Liu, Xieyi and Li, Wanru and Yang, Jia and Gong, Baoqi
              and Jin, Wei and Gong, Zhengxin and Wang, Kesheng and Luo, Jingqiu
              and Zhao, Zishuo and Bao, Pinglei},
    journal = {Nature Neuroscience},
    year = {2026},
    doi = {10.1038/s41593-026-02322-z},
    url = {https://doi.org/10.1038/s41593-026-02322-z},
}

Ceiling

0.75.

Note that scores are relative to this ceiling.

Data: Li2026.V2

Metric: ridgecv