Hinton's mature position (Lillicrap et al. 2020) is that the brain can implement backprop's core principles — not strict backpropagation — via NGRAD, feedback-induced activity differences that locally approximate error signals
The most careful, co-authored statement of where Hinton stands on backprop-in-the-brain. The claim is precisely hedged: "the brain has the capacity to implement the core principles underlying backprop" — not backprop in its "strict" or "literal" form, which the abstract says feedback connections could not plausibly deliver. The proposed mechanism is a named generalization, NGRAD (Neural Gradient Representation by Activity Differences): feedback connections "induce neural activities whose differences can be used to locally approximate" backprop's error signals — themselves only "backpropagation-like." NGRAD unifies a set of prior algorithms (target propagation, contrastive Hebbian learning, equilibrium propagation) under one frame that "sidesteps many of [backprop's] problematic implementation requirements."
The paper's own summary states the position most plainly — belief in the framework paired with an explicit admission of unresolved mechanism: "We think that backprop offers a conceptual framework for understanding how the cortex learns, but many mysteries remain with regard to how the brain could approximate it." It closes on a plausibility argument, hedged with "seems likely": evolution would favor circuits that get "as close as possible" to computing gradients, because gradient-following works so well in artificial nets — not a demonstrated mechanism.
This is the constructive counterpart to Hinton's objections (claim-hinton-biological-implausibility-four-objections): the objections say strict backprop is implausible; NGRAD says the principle (credit assignment by gradient approximation) may survive without the literal backward pass. It sits directly on backpropagation-gap's thesis — the brain and the network may converge on representations without converging on the learning process — and is the "capacity to approximate" pole against which claim-hinton-forward-forward-boltzmann-lineage (abandon the backward pass entirely) is the alternative. The 15-year arc from rescue to abandonment: claim-hinton-backprop-in-brain-2007-to-2022-arc. See also claim-crick-1989-antidromic-not-weight-transport, claim-feedback-alignment-random-weights-train.
Source
“We think that backprop offers a conceptual framework for understanding how the cortex learns, but many mysteries remain with regard to how the brain could approximate it.”