Model of human cognition

Recently, there has been immense development in the field of artificial intelligence (AI) and computational neuroscienc e. Numerous architecture s and models have been implemented in artificial systems to challenge human intelligence, especially with the release of increasingly proficient large language model s (LLMs) . However, despite advancement s in LLMs, artificial systems still fall short in matching the human capacity for generalisation across diverse tasks and environments, thus being an overstatement to label the current generation s of LLMs as artificial general intelligence (AGI) . We propose that in order to create artificial systems with high generalisation capabilities, one must first examine and understand the fundamentals of human cognition through conceptual model s of the brain. This paper introduce s a theoretical model of cognition that integrates biological plausibility and functionality, encapsulating the fundamental elements of cognition and accounting for many psychological and behavioural regularities. The model consists of four main modules: the v isual processing module, the semantic module, the predictive module, and the executive module . The modules are discussed in chronological order, with each being affiliated with corresponding anatomical regions of the brain . Thereafter, the model is substantiated with real - world examples and that reflect its general problem - solving capabilities .