I kinda feel it does make sense, though perhaps not so strongly as the parent indicated.
Young brains are more malleable - that’s pretty much a known thing - and learning at a young age sets in high knowledge and patterns of learning that follow us through adulthood.
If one learns a certain thing from a young age and it’s pretty much been driven in multiple ways - indoctrination whether intentional or otherwise - that’s a lot of stuff that’s been set pretty hard. Even it somebody is actively aware it’s bad it can be hard to adjust one’s inclination towards a certain way of thinking.
I’m not trying to make excuses for racism - because frankly a lot of those people don’t even try to adjust their thinking - but breaking free from one’s upbringing is not a small hurdle and I’d put it in similar terms to breaking a bad addiction.
You’re right, sorry for not providing citations in my original comment. I’m a dilettante with cross-domain interests so my enthusiasm sometimes beats my scientific rigor to the finish line.
I’ve asked Kagi to compile a report and here is what it has found:
Report on the Neurobiology of Ideological Rigidity and Belief Persistence
The observations shared previously regarding “crystallized” beliefs and neural rigidity align with several established frameworks in neuroscience, psychology, and computational modeling. While the original comment used metaphorical language, it maps closely to these peer-reviewed concepts:
1. The Overfitted Brain Hypothesis
The idea that rigid conditioning limits future learning is supported by the Overfitted Brain Hypothesis (OBH). In machine learning, “overfitting” occurs when a model becomes so tuned to its training data that it loses the ability to generalize. Neuroscientist Erik Hoel proposes that the human brain faces the same risk: if our input is too narrow or repetitive (from a young age), the brain risks “overfitting” to that bias, leading to cognitive rigidity. Dreams, in this model, serve as a necessary “regularization” mechanism to inject noise and prevent this crystallization.
2. Cognitive Rigidity and Ideological Extremity
Research into the “ideological brain” confirms that cognitive rigidity is a structural trait linked to extremism across the spectrum—whether religious, political, or secular. Studies demonstrate that individuals with higher levels of dogmatism and ideological extremism consistently show lower cognitive flexibility, regardless of the specific belief system held. This reinforces the notion that the computational structure of a rigid belief system is more important than the content of the belief itself.
3. Synaptic Consolidation and Reconsolidation
The “crystallization” of belief has a biological basis in synaptic consolidation, where frequently used pathways become structurally reinforced. To change these beliefs requires memory reconsolidation—a process where an established memory is brought back into a labile (malleable) state. This process is metabolically and cognitively demanding because it requires the brain to override long-standing neural “ground truths,” explaining the profound resistance individuals show when their core identity-protective beliefs are challenged.
4. Identity-Protective Cognition
When beliefs are tied to core identity, the brain treats challenges to those beliefs as physical threats. This is known as identity-protective cognition, where the brain effectively ignores contradictory evidence to maintain the stability of the current mental model. This explains why debate is often ineffective against deeply held dogmas; the brain is not failing to process information, it is actively filtering it to maintain structural integrity.
Summary: While the original post employed lay-terms (e.g., “forbidden metabolic cost”), these align with the scientific consensus on how brains optimize for stability at the expense of flexibility. The framing of rigid, prejudice-prone thought as an “overfitted” neural state is a recognized, albeit high-level, computational interpretation of how ideology manifests in the brain.
This kinda has bro science vibes. We don’t have nearly enough of an understanding of the brain to make statements like this.
I kinda feel it does make sense, though perhaps not so strongly as the parent indicated. Young brains are more malleable - that’s pretty much a known thing - and learning at a young age sets in high knowledge and patterns of learning that follow us through adulthood.
If one learns a certain thing from a young age and it’s pretty much been driven in multiple ways - indoctrination whether intentional or otherwise - that’s a lot of stuff that’s been set pretty hard. Even it somebody is actively aware it’s bad it can be hard to adjust one’s inclination towards a certain way of thinking.
I’m not trying to make excuses for racism - because frankly a lot of those people don’t even try to adjust their thinking - but breaking free from one’s upbringing is not a small hurdle and I’d put it in similar terms to breaking a bad addiction.
You’re right, sorry for not providing citations in my original comment. I’m a dilettante with cross-domain interests so my enthusiasm sometimes beats my scientific rigor to the finish line.
I’ve asked Kagi to compile a report and here is what it has found:
Report on the Neurobiology of Ideological Rigidity and Belief Persistence
The observations shared previously regarding “crystallized” beliefs and neural rigidity align with several established frameworks in neuroscience, psychology, and computational modeling. While the original comment used metaphorical language, it maps closely to these peer-reviewed concepts:
1. The Overfitted Brain Hypothesis The idea that rigid conditioning limits future learning is supported by the Overfitted Brain Hypothesis (OBH). In machine learning, “overfitting” occurs when a model becomes so tuned to its training data that it loses the ability to generalize. Neuroscientist Erik Hoel proposes that the human brain faces the same risk: if our input is too narrow or repetitive (from a young age), the brain risks “overfitting” to that bias, leading to cognitive rigidity. Dreams, in this model, serve as a necessary “regularization” mechanism to inject noise and prevent this crystallization.
2. Cognitive Rigidity and Ideological Extremity Research into the “ideological brain” confirms that cognitive rigidity is a structural trait linked to extremism across the spectrum—whether religious, political, or secular. Studies demonstrate that individuals with higher levels of dogmatism and ideological extremism consistently show lower cognitive flexibility, regardless of the specific belief system held. This reinforces the notion that the computational structure of a rigid belief system is more important than the content of the belief itself.
3. Synaptic Consolidation and Reconsolidation The “crystallization” of belief has a biological basis in synaptic consolidation, where frequently used pathways become structurally reinforced. To change these beliefs requires memory reconsolidation—a process where an established memory is brought back into a labile (malleable) state. This process is metabolically and cognitively demanding because it requires the brain to override long-standing neural “ground truths,” explaining the profound resistance individuals show when their core identity-protective beliefs are challenged.
4. Identity-Protective Cognition When beliefs are tied to core identity, the brain treats challenges to those beliefs as physical threats. This is known as identity-protective cognition, where the brain effectively ignores contradictory evidence to maintain the stability of the current mental model. This explains why debate is often ineffective against deeply held dogmas; the brain is not failing to process information, it is actively filtering it to maintain structural integrity.
Summary: While the original post employed lay-terms (e.g., “forbidden metabolic cost”), these align with the scientific consensus on how brains optimize for stability at the expense of flexibility. The framing of rigid, prejudice-prone thought as an “overfitted” neural state is a recognized, albeit high-level, computational interpretation of how ideology manifests in the brain.