Short-term Hebbian learning can implement transformer-like attention.

Transformers have revolutionized machine learning models of language and vision, but their connection with neuroscience remains tenuous. Built from attention layers, they require a mass comparison of queries and keys that is difficult to perform using traditional neural circuits. Here, we show that neurons can implement attention-like computations using short-term, Hebbian synaptic potentiation.

Tonic or Phasic Stimulation of Dopaminergic Projections to Prefrontal Cortex Causes Mice to Maintain or Deviate from Previously Learned Behavioral Strategies.

Dopamine neurons in the ventral tegmental area (VTA) encode reward prediction errors and can drive reinforcement learning through their projections to striatum, but much less is known about their projections to prefrontal cortex (PFC). Here, we studied these projections and observed phasic VTA-PFC fiber photometry signals after the delivery of rewards. Next, we studied how optogenetic stimulation of these projections affects behavior using conditioned place preference and a task in which mice learn associations between cues and food rewards and then use those associations to make choices.