Mapping neuronal selectivity and invariance in the mammalian visual cortex using digital twins.
1Center for Life Sciences and Artificial Intelligence, School of Life Sciences, Tsinghua University, Beijing, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China; Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, China.
Trends in Neurosciences
|May 5, 2026
Summary
Researchers mapped neuronal responses in the mouse visual cortex using a novel closed-loop system. They discovered specific receptive-field organizations that process visual information, particularly spatial frequencies.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Visual System Research
Background:
- Understanding neuronal coding in the visual cortex is crucial for deciphering brain function.
- Previous methods for mapping neuronal selectivity are often limited in efficiency and scope.
Purpose of the Study:
- To systematically map neuronal selectivity and invariance in the mouse primary visual cortex.
- To investigate the representational geometry and coding schemes within the visual system.
Main Methods:
- Application of model-guided closed-loop physiology.
- Systematic exploration of the high-dimensional visual feature space.
- Analysis of receptive-field properties in the primary visual cortex.
Main Results:
- A spectrum of receptive-field invariances was revealed.
- A bipartite organization tuned to spatial-frequency boundaries was identified.
- Efficient exploration of the visual feature space was achieved.
Conclusions:
- Model-guided closed-loop physiology offers an efficient framework for studying neuronal coding.
- The findings provide insights into how the visual cortex represents complex visual information.
- Neuronal selectivity and invariance are organized in a structured manner within the primary visual cortex.
