| First Author | Christian JA | Year | 2026 |
| Journal | Cereb Cortex | Volume | 36 |
| Issue | 6 | PubMed ID | 42248694 |
| Mgi Jnum | J:389868 | Mgi Id | MGI:8394150 |
| Doi | 10.1093/cercor/bhag047 | Citation | Christian JA, et al. (2026) Association learning drives synaptic plasticity at feedforward synapses in somatosensory cortex. Cereb Cortex 36(6) |
| abstractText | Learning broadly alters neocortical synapses, although the input and target specificity for this plasticity has not been well-defined. Feedforward synapses into sensory cortex have early critical periods for plasticity after which they are resistant to experience-dependent changes. Whether these synapses are altered during learning has not been investigated, particularly in a setting where animals must identify causal relationships between sensory stimuli and rewards. Here, we examined whether these feedforward synapses can be altered by training mice in a freely-moving and whisker-dependent association task. Pathway-specific optogenetic stimulation and analysis of quantal excitatory postsynaptic currents in layer 2/3 (L2/3) pyramidal neurons from barrel cortex revealed a rapid and transient potentiation of layer 4 (L4) inputs at the onset of training, without any change in thalamocortical inputs onto L4 neurons. In contrast, pseudotraining-where stimuli and rewards were decoupled-drove depression of L4-L2/3 quantal excitatory postsynaptic currents. Because environmental enrichment did not influence quantal excitatory postsynaptic current amplitude, these data suggest that reward-prediction accuracy is a key driver of feedforward plasticity in primary sensory cortex. Significance statement Although it is well accepted that sensory learning can alter cortical synapses, the pathways that are modified and the specific cues that drive this synaptic change have not been systematically investigated. By manipulating stimulus-reward probabilities, we identified discrete and opposite changes in the strength of L4-L2/3 synapses depending on the predictive accuracy of the stimulus. These data suggest that feedforward sensory circuits are exquisitely sensitive to the predictive value of sensory input in a goal-directed task. |
