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.V4-rdm-pearson")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_huge_clip336_laion	.256
2	custom_model_cv_18_dagger_408	.240
3	ReAlnet07_cornet	.239
4	cvt_cvt-13-224-in1k_4_LucyV4	.236
5	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.235
6	resnet152_imagenet_full	.235
7	ReAlnet10_cornet	.233
8	ReAlnet08_cornet	.233
9	ReAlnet06_cornet	.232
10	ReAlnet01_cornet	.232
11	ReAlnet02_cornet	.230
12	pnasnet_large_halfPrecision	.229
13	resnet101_imagenet_full	.228
14	ReAlnet04_cornet	.227
15	resnet152_ecoset_full	.227
16	ReAlnet03_cornet	.227
17	ReAlnet05_cornet	.226
18	cvt_cvt-21-224-in1k_4_LucyV4	.226
19	ReAlnet09_cornet	.225
20	effnetb1_272x240	.224
21	vit_relpos_base_patch16_clsgap_224:sw_in1k	.220
22	ijepa_vith14_linhead	.218
23	resnet101_ecoset_full	.216
24	mehrer2020_alexnet_training_seed_05	.217
25	mehrer2020_alexnet_training_seed_04	.216
26	mehrer2020_alexnet_training_seed_01	.214
27	mehrer2020_alexnet_training_seed_03	.214
28	mehrer2020_alexnet_training_seed_02	.213
29	AdvProp_efficientnet-b2	.212
30	AT_efficientnet-b2	.212
31	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.212
32	vit_large_clip336_openai	.212
33	convnext_large:fb_in22k_ft_in1k	.211
34	mehrer2020_alexnet_training_seed_06	.210
35	mehrer2020_alexnet_training_seed_07	.209
36	mehrer2020_alexnet_training_seed_09	.209
37	alexnet	.208
38	mehrer2020_alexnet_training_seed_08	.207
39	efficientnet_b0	.207
40	resnet50-SIN	.205
41	AdvProp_efficientnet-b4	.205
42	resnet50_ewconplus_wzc	.203
43	voneresnet-50	.203
44	resnet50_byol_linhead	.200
45	AlexNet_SIN	.200
46	vit_large_patch14_clip_224:openai_ft_in1k	.200
47	deit_small_imagenet_full_seed-0	.200
48	deit_base_imagenet_full_seed-0	.199
49	vit_large_patch14_clip_336:laion2b_ft_in1k	.199
50	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.198
51	ReAlnet01_cornet_fov12	.197
52	vit_base_patch16_clip_224:openai_ft_in1k	.195
53	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.193
54	focalnet_tiny_lrf_in1k	.192
55	AdvProp_efficientnet-b8	.190
56	convnext_tiny_imagenet_full_seed-0	.190
57	ReAlnet01_cornet_fov16	.190
58	AdvProp_efficientnet-b7	.189
59	dinov2_vitl14_lc_res336	.189
60	ReAlnet01_cornet_fov4	.187
61	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.187
62	resnet50-moclr8deg	.187
63	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.186
64	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.182
65	mehrer2020_alexnet_training_seed_01_fov4	.182
66	AdvProp_efficientnet-b6	.181
67	convnext_tiny_sup	.182
68	convnext_xlarge:fb_in22k_ft_in1k	.181
69	VOneCORnet-S	.180
70	gabor_filter_entropy_4x4_v2	.179
71	dinov2_vitg14_lc	.179
72	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.178
73	convnext_base_imagenet_full_seed-0	.178
74	convnext_large_imagenet_full_seed-0	.175
75	cvt_cvt-13-384-in1k_4_LucyV4	.174
76	efficientnet_b0_imagenet_full	.173
77	resnet34_ecoset_full	.168
78	convnext_small_imagenet_full_seed-0	.168
79	resnet50-vitoimagevidnet8	.165
80	resnet50-VITO-8deg-cc	.165
81	cvt_cvt-21-384-in1k_4_LucyV4	.165
82	Res2Net50_26w_4s	.164
83	AlexNet_SIN_fov4	.159
84	resnet18_ecoset_full	.160
85	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.160
86	convnext_femto_ols:d1_in1k	.159
87	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.159
88	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.157
89	resnet50-SIN_IN	.156
90	grcnn	.152
91	vit_large_patch14_clip_224:laion2b_ft_in1k	.151
92	AlexNet_SIN_fov12	.152
93	resnet50_simclr_linhead_01norm	.150
94	mehrer2020_alexnet_training_seed_10	.150
95	eicircuit_resnet18_bn_20260919	.148
96	gabor_filter_entropy_4x4	.147
97	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.147
98	resnet50_simsiam_linhead	.143
99	resnet18_imagenet_full	.143
100	convnext_base:clip_laiona_augreg_ft_in1k_384	.143
101	resnet34_imagenet_full	.142
102	efficientnet_b1_imagenet_full	.141
103	efficientnet_b2_imagenet_full	.141
104	convnext_small_imagenet_100_seed-0	.137
105	antialiased-r50	.135
106	deit_large_imagenet_full_seed-0	.131
107	resnet50_barlowtwins_linhead	.130
108	AlexNet_SIN_fov16	.130
109	resnet50_vicreg_linhead	.129
110	resnet-50-robust	.129
111	resnet50_imagenet_full	.128
112	seresnext50_32x4d	.128
113	mobilenet_v2_1_4_224	.124
114	ViT_L_32_imagenet1k	.121
115	dinov2_vitl14_lc	.122
116	resnet_SIN_IN_FT_IN	.118
117	resnet50-SIN_IN_IN	.118
118	voneresnet-50-non_stochastic	.117
119	mehrer2020_alexnet_training_seed_01_fov16	.116
120	mehrer2020_alexnet_training_seed_01_fov12	.114
121	resnet_50_v1_spiking	.111
122	resnet_50_v1	.111
123	resnet50_tutorial	.111
124	resnet50-sup	.111
125	gabor_filter_entropy_4x4_v2_forcedCosine	.108
126	resnet50_ecoset_full	.105
127	deit_small_imagenet_100_seed-0	.101
128	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.098
129	resnet50_robust_l2_eps1	.095
130	shufflenet_v2_x1_0	.094
131	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.087
132	convnext_tiny:in12k_ft_in1k	.086
133	resnext101_32x32d_wsl	.085
134	regnety_032	.083
135	resnext101_32x8d_wsl	.081
136	dinov2_vitl14_reg_lc	.081
137	convnext_xxlarge_clip	.080
138	resnext101_32x48d_wsl	.079
139	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.078
140	densenet-121	.078
141	alexnet_training_seed_06	.073
142	gabor_filter_mean_abs_4x4_v2	.073
143	alexnet_training_seed_02	.071
144	resnext101_32x16d_wsl	.069
145	alexnet_training_seed_03	.065
146	alexnet_training_seed_01	.064
147	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.061
148	alexnet_training_seed_09	.058
149	alexnet_training_seed_07	.056
150	resnet_50_v2	.055
151	compact_resnet50_robust_V4	.053
152	hmax	.053
153	dinov2_vitg14_reg_lc	.051
154	alexnet_training_seed_10	.042
155	resnet50_imagenet_100_seed-0
156	dinov2_vitl14_reg_lc_featread
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

0.77.

Note that scores are relative to this ceiling.

Data: Zerbe2026_fmri.V4-rdm

Metric: pearson