@misc{10481/105402,
year = {2025},
month = {1},
url = {https://hdl.handle.net/10481/105402},
abstract = {Sensory systems use context to infer meaning. Accordingly, context profoundly influences neural responses to sensory stimuli. However, a cohesive understanding of the circuit mechanisms governing contextual effects across different stimulus conditions is still lacking. Here we present a unified circuit model of mouse visual cortex that accounts for the main standard forms of contextual modulation. This data-driven and biologically realistic circuit, including three primary inhibitory cell types, sheds light on how bottom-up, top-down, and recurrent inputs are integrated across retinotopic space to generate contextual effects in layer 2/3. We establish causal relationships between neural responses, geometrical features of the inputs, and the connectivity patterns. The model not only reveals how a single canonical cortical circuit differently modulates sensory response depending on context but also generates multiple testable predictions, offering insights that apply to broader neural circuitry.},
organization = {NIH U01NS108683, NIH R01EY029999, NIH U19NS107613, NSF 1707398},
organization = {Gatsby Charitable Foundation GAT3708},
organization = {Kavli Foundation, grant no. IJC2020-044517-I},
organization = {Agencia Estatal de Investigación de España (grant no. PID2023-149174NB-I00)},
publisher = {Elsevier},
keywords = {contextual modulation},
keywords = {visual cortex},
keywords = {feedback},
keywords = {higher visual areas},
keywords = {inhibitory subclasses},
title = {Contextual modulation emerges by integrating feedforward and feedback processing in mouse visual cortex},
doi = {10.1016/j.celrep.2024.115088},
author = {Di Santo, Serena and Dipoppa, Mario and Keller, Andreas and Roth, Morgane and Scanziani, Massimo and Miller, Kenneth D.},
}