= Feedback alignment
{title2=$\delta^{h}=(B\delta^{o})\odot\sigma^{\prime}$}
A learning scheme replacing a transposed forward-weight matrix in the teaching signal with a separate fixed random matrix. Simulations show that adaptation of the forward weights can make this feedback useful on tested tasks. It need not equal the exact loss <gradient>, and successful simulations alone do not establish the mechanism in the brain.<Random synaptic feedback weights support error backpropagation for deep learning by Timothy P. Lillicrap and others>[Results, Figure 1 and Figure 2; Discussion: random feedback, learning performance and biological limitations]{ref}
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