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Where is the error? Hierarchical predictive coding through dendritic error computation
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DOI：10.1016/j.tins.2022.09.007.png)
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Abstract
En 中文
Top-down feedback in cortex is critical for guiding sensory processing, which has prominently been formalized in the theory of hierarchical predictive coding (hPC). However, experimental evidence for error units, which are central to the theory, is inconclusive and it remains unclear how hPC can be implemented with spiking neurons. To address this, we connect hPC to existing work on effi- cient coding in balanced networks with lateral inhibition and predictive computation at apical dendrites. Together, this work points to an efficient implementation of hPC with spiking neurons, where prediction errors are computed not in separate units, but locally in dendritic compartments. We then discuss the correspondence of this model to experimentally observed connectivity patterns, plasticity, and dynamics in cortex.
Keywords:
TIMING-DEPENDENT PLASTICITY
LONG-TERM POTENTIATION
VISUAL-CORTEX
BAYESIAN-INFERENCE
NEURONAL CIRCUITS
CELL-TYPE
INHIBITION
FEEDBACK
MODEL
INTERNEURONS
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