neocortex-learning-predictive-error-driven

name	neocortex-learning-predictive-error-driven
description	Neocortex learning framework via error-driven predictive learning using temporal derivatives, corticothalamic circuits, and competitive kinase synaptic plasticity. Implemented in Axon spiking neural simulation framework. Activation: neocortex learning, predictive coding, error-driven learning, temporal derivatives, corticothalamic circuits, kinase plasticity, spiking neurons, Axon framework, competitive learning
metadata	{"arxiv_id":"2606.08720","submitted":"2026-06-07","authors":"Randall C. O'Reilly","tags":["neuroscience","neocortex","learning","predictive-coding","spiking-neural-network","synaptic-plasticity","thalamus","computational-neuroscience"]}
license	Complete terms in LICENSE.txt

Neocortex Learning via Predictive Error-Driven Temporal Derivatives

Context

A sufficient account of how the neocortex learns must meet three criteria: computational (powerful general-purpose learning algorithm), algorithmic (implementable with known neural circuits), and implementational (detailed neurochemical account). Error-driven predictive learning via temporal derivatives, driven by corticothalamic circuits and competitive kinase synaptic plasticity, is the only framework meeting all three criteria.

Core Methodology

Three-Criterion Framework

1. Computational Criterion: Must approximate a powerful, general-purpose learning algorithm known to scale to human-level intelligence
2. Algorithmic Criterion: Must be implementable using known, well-established neural circuits within neocortex and associated brain structures