A potentially organizing goal of the brain and cognitive sciences is to accurately explain domains of human intelligence as executable, neurally mechanistic models. Years of research have led to models that capture experimental results in individual behavioral tasks and individual brain regions. We here advocate for taking the next step: integrating experimental results from many laboratories into suites of benchmarks that, when considered together, push mechanistic models toward explaining entire domains of intelligence, such as vision, language, and motor control. Given recent successes of neurally mechanistic models and the surging availability of neural, anatomical, and behavioral data, we believe that now is the time to create integrative benchmarking platforms that incentivize ambitious, unified models. This perspective discusses the advantages and the challenges of this approach and proposes specific steps to achieve this goal in the domain of visual intelligence with the case study of an integrative benchmarking platform called Brain-Score.

大脑和认知科学的潜在组织目标是将人类智能领域准确地解释为可执行的神经机制模型。多年的研究导致了可以捕获单个行为任务和单个大脑区域中的实验结果的模型。我们在这里提倡采取下一步行动：将来自许多实验室的实验结果整合到一系列基准中，这些基准一起考虑时，会将机械模型推向解释整个智能领域，例如视觉，语言和运动控制。鉴于神经机制模型的最新成功以及神经，解剖学和行为数据的迅猛可用性，我们认为现在是时候创建激励雄心勃勃的统一模型的集成基准测试平台了。