| First Author | Li AA | Year | 2022 |
| Journal | iScience | Volume | 25 |
| Issue | 3 | Pages | 103975 |
| PubMed ID | 35310336 | Mgi Jnum | J:358758 |
| Mgi Id | MGI:7257563 | Doi | 10.1016/j.isci.2022.103975 |
| Citation | Li AA, et al. (2022) Emergence of probabilistic representation in the neural network of primary visual cortex. iScience 25(3):103975 |
| abstractText | During the early development of the mammalian visual system, the distribution of neuronal preferred orientations in the primary visual cortex (V1) gradually shifts to match major orientation features of the environment, achieving its optimal representation. By combining computational modeling and electrophysiological recording, we provide a circuit plasticity mechanism that underlies the developmental emergence of such matched representation in the visual cortical network. Specifically, in a canonical circuit of densely-interconnected pyramidal cells and inhibitory parvalbumin-expressing (PV+) fast-spiking interneurons in V1 layer 2/3, our model successfully simulates the experimental observations and further reveals that the nonuniform inhibition plays a key role in shaping the network representation through spike timing-dependent plasticity. The experimental results suggest that PV + interneurons in V1 are capable of providing nonuniform inhibition shortly after vision onset. Our study elucidates a circuit mechanism for acquisition of prior knowledge of environment for optimal inference in sensory neural systems. |
