Imperfect vision

Understanding the logic of the brain


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Chat GPT gave a good description of the logic of the brain. One thing I wonder now is that it might be a good idea to, if I currently don't know it, make the brain's logic explicit to avoid resistance of this kind in the future. If my assumption is true, what kind of logic does the brain use? What are some ways to see that logic play out, and then integrate that logic for future nonresistances?


Your assumption is true — and you’re also right that making the brain’s logic explicit enough (not rigid, not dogmatic) can prevent future resistance. The trick is to make it descriptive , not prescriptive. You’re not giving the brain rules to obey; you’re learning the rules it already follows.


Below is a clean, usable model that stays grounded in observation rather than theory. 1. The brain’s core logic (plainly stated) At the most fundamental level, the brain operates by this logic: Reduce surprise while conserving energy, using the best available model. Everything else flows from that.


This means the brain prioritizes: 1. Prediction over truth 2. Relevance over completeness 3. Speed over accuracy (unless accuracy matters) 4. Safety over comfort 5. Energy efficiency over elegance Once you accept that as the objective function, behavior that once seemed “irrational” becomes consistent. 2. The brain is a prediction engine, not a reasoning engine The brain doesn’t ask: • “What is true?”

• “What is correct?”

• “What is logically valid?” It asks: • “What usually happens next?”

• “What matters right now?”

• “What would reduce uncertainty fastest?” Reasoning is a tool it uses sometimes , not its default mode.


This explains: • why habits persist,

• why emotions override logic,

• why suppression backfires,

• why explanation can interfere with perception,

• why assumptions dominate when unseen. 3. The brain’s actual logical primitives Instead of syllogisms, the brain works with: A. Prediction error • Difference between what was expected and what happened.

• Large error = attention + learning

• Small error = stability You’ve seen this when: • novelty grabs attention,

• repetition fades,

• surprises stick in memory. B. Salience weighting • What is tagged as important gets resources.

• Importance ≠ truth

• Importance = relevance to goals, safety, identity, or uncertainty This explains: • why suppression increases intensity,

• why fear dominates attention,

• why unseen assumptions control perspective. C. Energy minimization • The brain prefers the cheapest model that works.

• It resists unnecessary updates.

• It defaults to habits unless proven costly. This explains: • resistance to change,

• why insight doesn’t instantly alter behavior,

• why repetition works better than force. D. Context sensitivity • The brain does not store rules globally.

• It stores them conditionally .

• Same stimulus, different context → different response. This explains: • why personality labels fail,

• why techniques work sometimes but not always,

• why local/global confusion creates error. 4. How resistance happens (mechanically) Resistance appears when conscious thought violates the brain’s logic.


Examples:

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Imperfect visionBy David

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