Attention, Uncertainty, and Free-Energy.¶
Feldman, H., & Friston, K. J. (2010). Attention, Uncertainty, and Free-Energy. Frontiers in Human Neuroscience, 4.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Precision Weighting
- In neural predictive processing the brain is hypothesized to weight prediction errors by context-estimated precision, with attention as one modulation mechanism.
This sourceModels attention as inferring and weighting by the precision of prediction errors in predictive processing.
Supported in partVerified against the work's full text
Feldman and Friston hold that optimal inference “involves weighting data in proportion to their estimated precision”, with prediction error standing in for sensory data in predictive coding and the weighting implemented by synaptic gain. They tie this to attentional gain, where the responsiveness of prediction-error units “is modulated by attentional mechanisms”. That pairing of precision-weighted prediction error with attention as a gain mechanism is the hypothesis the sentence reports. The passage speaks of estimated precision without saying what the estimate is derived from, so the sentence's context-estimated qualifier goes beyond it.
“it may be the case that attention is the process of optimizing synaptic gain to represent the precision of sensory information (prediction error) during hierarchical inference.”
- In neural predictive processing the brain is hypothesized to weight prediction errors by context-estimated precision, with attention as one modulation mechanism.
Mechanisms¶
- Precision-Weighted Error Gate
- … defining idea, borrowed from precision-weighting in predictive coding, is that a large error from an untrustworthy source can matter less than a small error from a trusted one: it is the uncertainty-weighted, cost-aware rationer that keeps a finite channel pointed at the surprises that are both real and important.
This sourceExplains predictive coding as weighting prediction errors by estimated precision, so errors from less precise signals exert less influence.
- … defining idea, borrowed from precision-weighting in predictive coding, is that a large error from an untrustworthy source can matter less than a small error from a trusted one: it is the uncertainty-weighted, cost-aware rationer that keeps a finite channel pointed at the surprises that are both real and important.
Verification¶
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