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Predictive Processing & Learning
Predictive Processing & Learning
Predictive processing is a broad research framework exploring how prediction may contribute to perception, learning and action. These accounts propose that perception is shaped by an ongoing relationship between what a person expects and what they encounter. Incoming sensory information can confirm or challenge those expectations, helping to shape present experience and future learning.
In Categorization is ‘baked’ into the brain, Lisa Feldman Barrett and Earl K. Miller propose that categorisation is not simply a late stage of perception, after the brain has recognised individual features. They review evidence suggesting that categorisation occurs throughout signal processing, from the beginning.
In their account, categorisation means treating different objects, actions or events as functionally equivalent in a particular situation. For example, different movements, sounds or visual patterns may become meaningful in similar ways when they help a person pursue the same goal. A category is not treated as a fixed label stored in the brain; it is dynamically constructed from past experience, current goals and the demands of the activity.
Barrett and Miller propose that predictive feedback helps create the context in which incoming sensory information is organised. This may help a person select possible actions and respond to the needs and goals of the moment. Their account also connects categorisation with allostasis: the brain’s anticipation and regulation of bodily needs.
Watch this two-minute video that cleverly demonstrates how predictive processing works.
Image courtesy of Greg Dunn
Why it interests us
Why it interests us
Learning Just Became Easier is interested in whether these ideas can help generate useful questions about learning.
What makes it easier or harder to notice something new in a familiar activity?
How might pace, repetition, visual feedback, sensory sequencing and meaningful activity affect learning?
How might a person’s goals and past experience shape what they notice as relevant?
What conditions help someone return to an activity with greater curiosity, confidence or flexibility?
These are research questions. The predictive-processing framework, including Barrett and Miller’s account of categorisation, is not presented here as a proven explanation of how the VLX works, or as proof that the VLX produces a particular health outcome.
Our research approach
Our research approach
The VLX creates a structured learning setting in which the practitioner can adjust visual feedback, task pace, attention and activity design.
We are exploring whether this setting can help participants work with aspects of an activity that are ordinarily difficult to notice or change. The work is practical, participant-led and developmental. It is informed by relevant research, but it does not assume that a scientific theory has already established the mechanism or outcome of the VLX.
What we are developing
What we are developing
Our current work focuses on:
Clearer descriptions of the VLX apparatus and practitioner approach
Safe and consistent setup procedures
Appropriate ways to observe and record learning
Research questions that can be investigated responsibly
Evidence needed before making future outcome claims
We believe careful development matters. Meaningful learning deserves both imagination and evidence.
Dive into the Science
Dive into the Science
This video describes the neurological and physiological processes that affect our mental health. How do antidepressants change the way we perceive the world? How should we use placebos? Is dopamine really just about rewards?
The predictive processing theory frames much of our work. This talk has some useful demos and a good introduction to the theory at the beginning. Watch the whole lecture for a deeper dive into the topic.
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