“Cognitive psychologists often use computer as an analogy to explain the relation between cognition and brain.” Discuss.

The Computer Analogy: An Information Processing Approach

The computer analogy, largely influenced by the development of artificial intelligence, views the human mind as an information processor. This perspective breaks down cognitive processes into stages, mirroring the functional components of a computer:

• Input: Sensory receptors act as input devices, receiving information from the environment (similar to a keyboard or mouse).
• Encoding: This information is then encoded into a format the mind can understand (like converting data into binary code).
• Storage: Information is stored in various memory systems (short-term, long-term) analogous to a computer’s RAM and hard drive.
• Retrieval: Accessing stored information is akin to retrieving files from a computer’s memory.
• Processing: Cognitive operations like attention, decision-making, and problem-solving are seen as computational processes.
• Output: Responses, whether behavioral or mental, represent the output of the system (like displaying information on a screen).

Key Models Based on the Analogy

Several influential cognitive models are rooted in the computer analogy:

• Atkinson-Shiffrin Model (1968): This multi-store model of memory proposes three distinct stages – sensory memory, short-term memory, and long-term memory – functioning like different storage systems in a computer.
• Baddeley’s Working Memory Model (1974): This model refines the concept of short-term memory, proposing a central executive and specialized subsystems (phonological loop, visuospatial sketchpad) that actively manipulate information, similar to a computer’s CPU.
• Connectionism (Parallel Distributed Processing): This approach, emerging later, moved away from strict serial processing to emphasize parallel processing, resembling the architecture of neural networks in computers.

Strengths of the Computer Analogy

The computer analogy has been incredibly fruitful for cognitive psychology:

• Precision and Testability: It provided a framework for formulating precise hypotheses and designing experiments to test cognitive processes.
• Development of AI: It spurred the development of artificial intelligence, aiming to create machines that mimic human cognitive abilities.
• Understanding Complex Processes: It allowed researchers to break down complex cognitive functions into smaller, manageable components.

Limitations of the Computer Analogy

Despite its successes, the analogy has limitations:

• Biological Plausibility: The brain is far more complex and dynamic than a computer. Computers operate on a digital, serial basis, while the brain utilizes parallel processing and analog signals.
• Emotional and Motivational Factors: The analogy largely ignores the role of emotions, motivations, and consciousness in cognition. Computers lack subjective experience.
• Creativity and Intuition: Human cognition exhibits creativity and intuition, which are difficult to replicate in computer algorithms.
• Brain Damage & Plasticity: The brain demonstrates remarkable plasticity and can recover from damage, a feature not easily replicated in current computer systems.

Furthermore, the analogy often overlooks the embodied nature of cognition – the idea that cognitive processes are deeply intertwined with the body and its interactions with the environment.