What Is Cognition?

Cognition is the set of mental processes by which an organism acquires, represents, stores, transforms, and uses information to produce adaptive behavior. It encompasses perception, attention, memory, language comprehension and production, reasoning, decision-making, and problem-solving. In engineering and computational contexts, cognition is studied both as a biological phenomenon to be understood and as a design target to be modeled or replicated in artificial systems. The related_topics for this entry include active perception, brain, cognitive systems, digital intelligence, and psychology, reflecting cognition's position at the junction of neuroscience, computer science, and psychology.

The modern scientific study of cognition took shape in the mid-1950s as researchers applied formal models from computation and information theory to mental processes. Pioneers including Herbert Simon, Allen Newell, Noam Chomsky, and George Miller argued that human thought could be described in terms of symbol manipulation, setting the foundation for cognitive science as an interdisciplinary field encompassing philosophy, linguistics, neuroscience, and artificial intelligence.

Perception and Active Sensing

Perception is the process by which sensory data, visual, auditory, somatosensory, olfactory, and vestibular, is transduced and interpreted to form a representation of the environment. Active perception extends this concept to systems, biological or artificial, that direct sensors to acquire information strategically rather than passively receiving whatever arrives. In biological vision, saccadic eye movements redirect the fovea to regions of interest, compressing the effective information load. In robotics and autonomous systems, analogous active perception frameworks govern how sensors are pointed, when to gather new data, and how uncertainty is reduced through directed action. Research published in PMC on cognitive perception explores how higher-order cognitive states such as expectations and goals exert top-down influence on early perceptual processing, blurring the boundary between perception and cognition proper.

Memory and Learning

Memory, the capacity to encode, consolidate, store, and retrieve information, is the mechanism by which experience shapes future behavior. Cognitive science distinguishes working memory, the short-duration, limited-capacity buffer where information is actively manipulated, from long-term memory, which is further divided into declarative memory for facts and events and procedural memory for skills and habits. Learning is the process that updates memory representations in response to experience, whether through associative conditioning, statistical regularization, or explicit instruction. These distinctions inform the design of artificial neural networks, where architectural choices about memory and learning rate directly parallel the cognitive concepts they are inspired by. The UCSB Cognition, Perception, and Cognitive Neuroscience research group documents work on the neural substrates of working memory and attention that connects cognitive theory to brain measurement.

Cognitive Systems and Digital Intelligence

Cognitive systems are engineered systems designed to perform some subset of cognitive functions, including perception, language understanding, planning, or learning, at a level useful for practical tasks. Digital intelligence, a broader term covering software agents, AI systems, and hybrid human-machine systems, builds on cognitive science research to define how machines should represent knowledge and reason under uncertainty. Bayesian inference frameworks, reinforcement learning algorithms, and transformer-based language models all draw from cognitive and neural inspiration, though their internal representations differ from biological cognition in important ways. Research across IEEE Xplore in areas including human-robot interaction, cognitive radio, and adaptive systems reflects how cognitive principles are operationalized in engineering design.

Applications

Cognition has applications in a wide range of disciplines, including:

• Human-robot interaction and socially intelligent robotics
• Brain-computer interface design and assistive neurotechnology
• Educational technology and adaptive learning systems
• Cognitive radio and autonomous spectrum management
• Autonomous vehicle perception and decision-making
• Ergonomics and human factors engineering