We introduce Net2Brain, a graphical and command-line user interface toolbox
for comparing the representational spaces of artificial deep neural networks
(DNNs) and human brain recordings. While different toolboxes facilitate only
single functionalities or only focus on a small subset of supervised image
classification models, Net2Brain allows the extraction of activations of more
than 600 DNNs trained to perform a diverse range of vision-related tasks (e.g
semantic segmentation, depth estimation, action recognition, etc.), over both
image and video datasets. The toolbox computes the representational
dissimilarity matrices (RDMs) over those activations and compares them to brain
recordings using representational similarity analysis (RSA), weighted RSA, both
in specific ROIs and with searchlight search. In addition, it is possible to
add a new data set of stimuli and brain recordings to the toolbox for
evaluation. We demonstrate the functionality and advantages of Net2Brain with
an example showcasing how it can be used to test hypotheses of cognitive
computational neuroscience.

Net2Brain 是一个用于比较深度神经网络（DNN）和人脑记录的表征空间的图形和命令行用户界面工具箱，可以提取超过 600 个 DNN 的激活，计算代表性的差异矩阵（RDMs）并将其与大脑记录进行比较，从而测试认知神经科学的假设。