The Artificial Brain: A Neuroscience Inspired Architecture for Multimodal AI Systems

Abstract

Current AI models process input through a single lens. The human brain never does this—it cross-references every sense against every other sense, flags conflicts, and only calls on expensive conscious reasoning when something doesn't add up. We present a complete architecture for an artificial brain that mirrors this design: specialized Small Language Models (SLMs) as parallel sensory cortices, a lightweight conflict detector as the anterior cingulate cortex, an expensive reasoning model as the prefrontal cortex activated only on demand, a streaming identity core as the default mode network, episodic memory via vector databases, slow knowledge consolidation via sleep-cycle fine-tuning, and a neuromodulator reward system that shapes all behavior over time. The system is born when started, develops personality through experience, sleeps to consolidate, and dies when stopped. Every component maps to a specific brain structure. Every design decision is grounded in neuroscience research. The architecture is implementable today on consumer hardware (RTX 4050, 6GB VRAM).