Reverse enginering the brain will require a deep understanding of how information is represented and how computation is performed in the brain. What are the functional operations? What are the knowledge data structures? How are messages encoded? How are relationships established and broken? How are images processed? How does the brain transform signals into symbols? How does the brain generate the incredibly complex, colorfu, dynamic internal representation that we consciously perceive as external reality? The model presented here hypothesizes that each cortical hypercolumn together with its underlying thalamic nuclei performs as a Cortical Computational Unit (CCU) consisting of a frame-like data structure (containing attributes, state, and pointers) plus the computational processes and mechanisms required to build and maintain it. In sensory-processing aras of the brain, CCUs enable segmentation, grouping, and classification. Pointers stored in CCUframes link pixels and signals to objects and events in situations and episodes that are overlaid with meaning and emotioonal values. In behavior-generating areas of the brain, CCUs make decisions, set goals and priorities, generate plans, and control behavior. Poiinters are used to define rules, grammars, procedures, plans, and behaviors. It is suggested that it may be possible to reverse engineer the human brain at the CCU level of fidelity using next-generation massively parallel computer hardware and software.