Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Zerbe2026_fmri.V1-rdm-pearson")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_large_clip336_openai	.330
2	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.329
3	AdvProp_efficientnet-b7	.325
4	AdvProp_efficientnet-b6	.323
5	convnext_femto_ols:d1_in1k	.322
6	vit_large_patch14_clip_224:openai_ft_in1k	.319
7	efficientnet_b0	.319
8	AdvProp_efficientnet-b4	.314
9	convnext_xlarge:fb_in22k_ft_in1k	.306
10	AdvProp_efficientnet-b8	.303
11	AT_efficientnet-b2	.303
12	AdvProp_efficientnet-b2	.303
13	alexnet	.300
14	vit_large_patch14_clip_224:laion2b_ft_in1k	.301
15	convnext_small_imagenet_full_seed-0	.301
16	effnetb1_272x240	.299
17	resnet_SIN_IN_FT_IN	.296
18	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.295
19	AlexNet_SIN	.294
20	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.294
21	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.291
22	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.291
23	gabor_filter_entropy_4x4_v2	.289
24	vit_large_patch14_clip_336:laion2b_ft_in1k	.288
25	convnext_tiny_sup	.281
26	deit_base_imagenet_full_seed-0	.278
27	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.277
28	AlexNet_SIN_fov12	.275
29	convnext_large:fb_in22k_ft_in1k	.271
30	voneresnet-50	.270
31	antialiased-r50	.268
32	mehrer2020_alexnet_training_seed_02	.268
33	custom_model_cv_18_dagger_408	.268
34	pnasnet_large_halfPrecision	.265
35	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.264
36	cvt_cvt-13-384-in1k_4_LucyV4	.262
37	grcnn	.263
38	AlexNet_SIN_fov16	.263
39	mehrer2020_alexnet_training_seed_04	.261
40	mehrer2020_alexnet_training_seed_01	.261
41	mehrer2020_alexnet_training_seed_03	.260
42	mehrer2020_alexnet_training_seed_08	.259
43	mehrer2020_alexnet_training_seed_09	.259
44	mehrer2020_alexnet_training_seed_06	.259
45	mehrer2020_alexnet_training_seed_10	.259
46	mehrer2020_alexnet_training_seed_07	.257
47	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.255
48	vit_relpos_base_patch16_clsgap_224:sw_in1k	.254
49	gabor_filter_entropy_4x4	.253
50	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.253
51	resnet50-SIN	.252
52	vit_base_patch16_clip_224:openai_ft_in1k	.245
53	resnet-50-robust	.245
54	convnext_base:clip_laiona_augreg_ft_in1k_384	.243
55	convnext_base_imagenet_full_seed-0	.240
56	ReAlnet08_cornet	.239
57	deit_large_imagenet_full_seed-0	.238
58	mehrer2020_alexnet_training_seed_01_fov16	.238
59	ReAlnet06_cornet	.237
60	ReAlnet10_cornet	.237
61	ReAlnet07_cornet	.230
62	dinov2_vitl14_lc	.230
63	cvt_cvt-13-224-in1k_4_LucyV4	.229
64	ReAlnet05_cornet	.228
65	ReAlnet02_cornet	.227
66	ReAlnet03_cornet	.225
67	mehrer2020_alexnet_training_seed_01_fov12	.225
68	ReAlnet09_cornet	.223
69	compact_resnet50_robust_V4	.223
70	ReAlnet04_cornet	.222
71	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.218
72	efficientnet_b1_imagenet_full	.217
73	ReAlnet01_cornet	.218
74	efficientnet_b2_imagenet_full	.213
75	deit_small_imagenet_full_seed-0	.208
76	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.204
77	convnext_tiny_imagenet_full_seed-0	.200
78	convnext_small_imagenet_100_seed-0	.196
79	ijepa_vith14_linhead	.194
80	mobilenet_v2_1_4_224	.194
81	gabor_filter_entropy_4x4_v2_forcedCosine	.193
82	resnet50-SIN_IN	.191
83	ReAlnet01_cornet_fov12	.191
84	convnext_large_imagenet_full_seed-0	.191
85	dinov2_vitl14_lc_res336	.186
86	AlexNet_SIN_fov4	.186
87	resnet50_ewconplus_wzc	.184
88	resnet50-SIN_IN_IN	.181
89	mehrer2020_alexnet_training_seed_01_fov4	.179
90	seresnext50_32x4d	.178
91	alexnet_training_seed_06	.177
92	efficientnet_b0_imagenet_full	.175
93	resnet101_imagenet_full	.174
94	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.172
95	convnext_tiny:in12k_ft_in1k	.172
96	resnet152_imagenet_full	.171
97	resnet_50_v1_spiking	.170
98	resnet50_tutorial	.170
99	resnet_50_v1	.170
100	resnet50-sup	.170
101	deit_small_imagenet_100_seed-0	.169
102	cvt_cvt-21-224-in1k_4_LucyV4	.168
103	cvt_cvt-21-384-in1k_4_LucyV4	.165
104	focalnet_tiny_lrf_in1k	.163
105	alexnet_training_seed_03	.164
106	ReAlnet01_cornet_fov16	.163
107	resnet50_ecoset_full	.159
108	Res2Net50_26w_4s	.156
109	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.154
110	resnet50-vitoimagevidnet8	.150
111	resnet50-VITO-8deg-cc	.150
112	alexnet_training_seed_02	.150
113	resnet34_imagenet_full	.142
114	ReAlnet01_cornet_fov4	.141
115	resnet152_ecoset_full	.141
116	alexnet_training_seed_01	.142
117	dinov2_vitg14_lc	.139
118	resnet50_imagenet_full	.136
119	resnet34_ecoset_full	.136
120	ViT_L_32_imagenet1k	.131
121	alexnet_training_seed_07	.131
122	densenet-121	.129
123	alexnet_training_seed_09	.130
124	resnet50_imagenet_100_seed-0	.120
125	shufflenet_v2_x1_0	.118
126	resnet50_simsiam_linhead	.117
127	resnet50_robust_l2_eps1	.115
128	convnext_xxlarge_clip	.114
129	gabor_filter_mean_abs_4x4_v2	.114
130	alexnet_training_seed_10	.113
131	resnet18_imagenet_full	.110
132	regnety_032	.108
133	eicircuit_resnet18_bn_20260919	.107
134	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.099
135	resnet18_ecoset_full	.092
136	resnext101_32x16d_wsl	.084
137	resnext101_32x8d_wsl	.083
138	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.082
139	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.082
140	voneresnet-50-non_stochastic	.074
141	resnet50-moclr8deg	.071
142	resnet_50_v2	.065
143	resnext101_32x48d_wsl	.063
144	VOneCORnet-S	.063
145	resnet50_byol_linhead	.060
146	dinov2_vitl14_reg_lc_featread	.054
147	dinov2_vitl14_reg_lc	.054
148	resnext101_32x32d_wsl	.052
149	resnet50_barlowtwins_linhead	.051
150	resnet50_vicreg_linhead	.051
151	dinov2_vitg14_reg_lc	.048
152	hmax	.044
153	resnet50_simclr_linhead_01norm	.038
154	mehrer2020_alexnet_training_seed_05
155	resnet101_ecoset_full
156	vit_huge_clip336_laion
157	eva02_large_in22k

Benchmark bibtex

@inproceedings{zerbe_laion-fmri_2026,
      title = {{LAION}-{fMRI}: A densely sampled 7T-fMRI dataset providing broad coverage of natural image diversity},
      author = {Zerbe, Josefine and Roth, Johannes and Mell, Maggie Mae and Herholz, Peer and Knapen, Tomas and Hebart, Martin N.},
      year = {2026},
      booktitle = {Vision Sciences Society Annual Meeting},
  }

Ceiling

0.79.

Note that scores are relative to this ceiling.

Data: Zerbe2026_fmri.V1-rdm

Metric: pearson