2.1 The Brain Is an Inference Machine

Our brains are constantly making inferences about reality, filling in gaps and resolving ambiguities using prior knowledge. This process involves both bottom-up sensory input and top-down cognitive influences, shaping our perception of the world around us.

Emotions and rational thought both play crucial roles in decision-making. While emotions provide quick, intuitive evaluations, rational thought allows for deliberate analysis. Balancing these processes is key to effective decision-making in various aspects of life.

Perception and Inference

Brain's inference of reality

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• Brain actively interprets sensory input to create a coherent model of the world
  • Sensory information often ambiguous or incomplete (partially obscured objects, noisy environments)
  • Brain fills in gaps and resolves ambiguities using prior knowledge and expectations (assuming a partially hidden object is complete, interpreting speech sounds based on context)
• Perception involves both bottom-up (sensory) and top-down (cognitive) influences
  • Bottom-up processing: Sensory information from environment enters nervous system (light hitting retina, sound waves activating hair cells in ear)
  • Top-down processing: Higher-level cognitive processes shape sensory information interpretation (attention focusing on specific visual features, memory providing context for interpreting a scene)
• Brain generates hypotheses or predictions about causes of sensory input based on prior experience and knowledge
  • Predictions compared with actual sensory input
  • Discrepancies between predictions and input lead to updating brain's model of world (seeing an unexpected object causes surprise and prompts closer examination)
• Optical illusions demonstrate brain's inferences can be misleading when sensory information ambiguous or contradicts expectations (Müller-Lyer illusion, Necker cube)
• Perceptual learning allows the brain to improve its inference abilities through experience and practice

Neural basis of inference

• Neural networks in the brain play a crucial role in sensory processing and inference
• Cognitive neuroscience investigates how these neural processes give rise to perception and decision-making
• Karl Friston's theory of predictive coding suggests the brain constantly generates and updates predictions to minimize prediction errors

Emotion, Cognition, and Decision-Making

Emotions vs rational thought

• Emotions and rational thought interconnected and both play important roles in decision-making
• Emotions influence decision-making by:
  1. Providing quick, intuitive evaluations of options based on past experiences (feeling of unease about a risky investment)
  2. Motivating behavior towards rewarding stimuli and away from aversive stimuli (desire for tasty food, fear of dangerous animals)
  3. Modulating attention and memory to prioritize relevant information (enhanced memory for emotionally charged events)
• Rational thought influences decision-making by:
  1. Allowing for deliberate, logical analysis of options and consequences (calculating expected utility of different choices)
  2. Enabling consideration of long-term goals and values (deciding to save money for retirement despite short-term desires)
  3. Providing means to override emotional impulses when necessary (resisting temptation to engage in unhealthy behaviors)
• Effective decision-making often involves balance between emotional and rational processes
  • Emotions provide valuable information and guide decisions, but unchecked emotions lead to impulsive or irrational choices (making a large purchase on impulse)
  • Rational deliberation evaluates options objectively, but overreliance on logic leads to suboptimal decisions neglecting important emotional and social factors (choosing a higher-paying job despite poor work-life balance)
• Somatic marker hypothesis proposes emotions guide decision-making by associating physiological states with potential outcomes, biasing decisions towards favorable options (gut feelings about a decision based on past experiences)

Heuristics and Biases

Heuristics and cognitive biases

• Heuristics are simple, efficient rules or mental shortcuts brain uses to make judgments and decisions quickly
  • Often based on limited information and rely on general principles or past experiences
  • Examples: availability heuristic (judging likelihood based on ease of recall), representativeness heuristic (judging probability based on resemblance to stereotypes)
• Heuristics can be useful for making fast decisions with minimal cognitive effort, but can also lead to systematic errors or cognitive biases
• Common cognitive biases resulting from heuristics:
  1. Confirmation bias: Tendency to seek out and interpret information in way that confirms pre-existing beliefs, while ignoring contradictory evidence (selectively reading articles that support one's political views)
  2. Anchoring bias: Tendency to rely too heavily on first piece of information encountered (the "anchor") when making estimates or judgments (estimating a car's value based on the initial asking price)
  3. Framing effect: Tendency to make different decisions based on how a problem or situation is presented or framed (choosing a medical treatment described in terms of survival rates vs. mortality rates)
• Cognitive biases lead to suboptimal decision-making and judgments in various domains (finance, health, social interactions)
• Awareness of common heuristics and biases helps individuals recognize and mitigate their influence on thinking and decision-making (considering alternative perspectives, seeking disconfirming evidence, being mindful of framing effects)