The “Complete” Perspective on Meditation According to Research, #2

In our last post, we explored a groundbreaking theory on meditation. Its researchers linked meditation to the brain’s predictive processing system. If you haven’t read that article yet, I recommend it to understand the foundation of this series.

The study From Many to None: Meditation and the Plasticity of the Predictive Mind clarifies how meditation changes the brain. It proposes that meditation disrupts habitual mental patterns, increasing flexibility and awareness.

This process unfolds in three states: Focused Attention, Open Monitoring, and Non-Dual Awareness. These techniques exist on a spectrum. Each step reduces distractions and brings the mind into the present moment.

At the core of this research is predictive processing, a model of how the brain interprets the world. The brain constantly predicts what will happen based on past experiences. Then it accordingly adjusts its understanding using sensory input.

This system helps us survive, but it also reinforces biases and automatic responses. Meditation challenges this cycle. By interrupting rigid thought patterns, mindfulness opens up new ways of experiencing reality.

Self-Sustaining Based on Predictions

What does the brain do? What is the basic goal of a living organism?

Biology explains how life adapts over time through natural selection. Yet, it does not fully explain how organisms survive and change in their lifetimes. Living beings do more than reproduce—they think, feel, and behave to stay alive. What drives this compulsion?

The free energy principle shows survival entails more than seeking pleasure or avoiding pain. Instead, organisms must maintain a boundary between themselves and the world. If this boundary dissolves, they lose stability and become disordered.

The brain prevents this by making predictions to keep the body within safe limits. These self-sustaining actions keep the organism in familiar, life-supporting states.

The Purpose of Prediction Error Minimization

The ability to survive depends on accurate predictions. But the brain does not have direct access to the outside world. It only receives sensory signals, which are often noisy or incomplete.

For example, in vision, the size of an object on the retina depends on both the object’s size and its distance. How does the brain know an object’s true size from this limited information?

The solution is prediction error minimization. The brain compares predictions to sensory input and updates models when errors occur. This process helps refine how it interprets the world.

The brain cannot analyze every tiny detail of sensory input. It relies on efficient, experience-based predictions to guide behavior.

Imagine drinking a glass of water. This action requires predicting how to move the hand, avoid obstacles, and swallow. If the expected taste or texture is wrong, the brain registers a prediction error.

If the liquid is dangerous, the brain signals a warning, possibly triggering a spit or gag reflex. Even thirst itself is a prediction error, signaling the need for water based on fluid levels. Organisms that fail to minimize prediction errors will not survive for long.

The relationship between predictive processing and meditation has five key features:

1. Hierarchical Predictions – The brain organizes predictions at different levels.
2. Active Inference – The brain doesn’t just react; it also acts to confirm or change predictions.
3. Precision-Weighting (Attention) – The brain assigns importance to some signals over others.
4. The Hierarchical Self – The sense of self emerges from predictive models.
5. Fact-Free Learning and Insight – The brain refines models even without new sensory input.

1. The Brain’s Hierarchy of Predictions

The brain organizes information in layers. Lower levels process raw sensory input. Higher levels handle complex thoughts and ideas. Each level makes predictions about the one below it. When a prediction error occurs, it moves up the hierarchy for further analysis.

This hierarchical structure allows the brain to simplify complex information. Simple sensory data feeds into abstract concepts, shaping thoughts and beliefs. If prediction errors occur often, the brain must adjust its assumptions.

The brain follows Bayesian inference, meaning it updates beliefs based on new information. Experiences create priors, or expectations, which influence perception. Some priors are deeply ingrained, such as maintaining a stable body temperature. Other priors, shaped by personal experience, can change over time.

The question remains: How flexible are these priors? Can long-held assumptions be revised? Meditation may play a role in shifting stubborn biases. It can train the brain to observe rather than react to repetitive prediction errors.

2. Perceptual and Active Inference

The brain minimizes prediction errors in two ways:

• Perceptual Inference – Updating beliefs based on new sensory input.
• Active Inference – Acting in ways that confirm existing predictions.

For example, if you are thirsty, your brain predicts the experience of drinking water. If the actual sensation of drinking matches expectations, the brain reduces prediction error.

However, sometimes active inference overrides perception. Instead of changing beliefs, the brain takes actions that confirm its expectations. A scientist may ignore unexpected results and keep trying to prove a hypothesis. Similarly, people often seek information that supports their beliefs, rather than challenging them.

Meditation may interrupt active inference, allowing the brain to observe rather than react. This opens space for deep learning, curiosity, and cognitive flexibility.

3. Attention and Precision-Weighting

Not all sensory input is reliable. The brain must decide which signals to trust and which to ignore. This process, called precision-weighting, is how the brain assigns importance to different stimuli.

Attention plays a key role in this process. When the brain expects a signal to be clear and reliable, it increases attention to that input. In a well-lit room, even small visual changes are noticed. But, in darkness, the brain downplays unreliable signals.

By controlling precision-weighting, attention shapes perception. The more attention something receives, the more real it feels. This could explain why meditation emphasizes focused attention—it amplifies present experience.

In some meditation practices, attention is later released, moving toward non-preferential awareness. In advanced non-dual practices, attention dissolves completely, allowing perception to unfold without resistance.

4. The Hierarchical Self

Predictive processing suggests that the self is also a construction. Like everything else in the brain, it emerges from hierarchical models shaped by experience.

To act in the world, the brain must model itself. If you reach for a glass of water, your brain predicts your body’s movements as part of the action. It also predicts your need for water, your agency in reaching for it, and the expected sensory outcome.

This self-model allows counterfactual thinking—imagining possible future scenarios. While useful, this ability can also create suffering. The brain can dwell on negative hypothetical situations, generating stress and anxiety.

Some theories propose a layered sense of self:

1. Experiencing Self – Direct awareness of bodily sensations.
2. Narrative Self – The story we tell ourselves about who we are.
3. Minimal Self – A basic first-person awareness.

Meditation often weakens the narrative self, shifting attention to direct experience. Some advanced states, such as those reached in deep meditation, may even lead to a temporary loss of self.

5. Fact-Free Learning and Insight

The brain can refine its models without new sensory input. This process is called fact-free learning. It occurs when insights emerge from within rather than from external experiences.

For example, a solution to a problem may suddenly appear while taking a shower or resting. The brain is constantly refining its models, even in stillness.

Meditation may enhance fact-free learning by reducing external distractions and encouraging inner processing. Some researchers compare deep meditation to sleep. While the body rests, the brain reorganizes itself and eliminates unnecessary connections.

Classical meditation traditions, such as Vipassanā, emphasize insight as a key outcome. Meditation may allow the brain to strip away unnecessary assumptions. The process mirrors a sculptor revealing a statue by selectively, delicately removing stone.

Final Thoughts

Predictive processing suggests that the brain creates reality through prediction. These predictions shape perception, emotions, and even the sense of self. Meditation may offer a way to interrupt, observe, and refine these processes.

What’s Next?

The next post will even more closely explore how meditation interacts with predictive processing.

This blog series will follow the structure of the study:

1. Introduction to the Study
2. Predictive Processing
3. Meditation and Predictive Processing
4. The Unifying Framework of the Many-to-None Model
5. Key Empirical Predictions and Support
6. Final Discussion

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