Abstract
Recent AI advances achieve remarkable performance, yet modeling the human brain remains a crucial challenge. The Whole Brain Architecture Approach utilizes the Brain Reference Architecture (BRA) to integrate major brain regions but struggles with building large-scale brain-inspired systems. This paper introduces the Brain-morphic software Implementation & Testing System (BITS), a framework guiding developers from design to multi-faceted evaluation. BITS implements Hypothetical Component Diagram (HCD) components as Uniform Circuits (UC). Each UC can adopt either a Biophysically Constrained Model (BCM), which captures neuronal dynamics through spike-based architectures for higher biological fidelity, or a Biophysically Agnostic Model (BAM), relying on more abstract neural networks for computational efficiency. Leveraging the Function Realization Graph (FRG), BITS assesses task performance, alignment with neural activity, structural adherence to BRA, and lesion-based abnormal-condition simulations. Through iterative refinement, this approach balances biological plausibility with practical performance, thereby contributing to the advancement of robust, brain-inspired AGI.
