Map of spiking activity underlying change detection in the mouse visual system
Corbett BennettiD, Samuel D. Gale, Greggory R. HelleriD, Tamina K. RamireziD, Hannah BelskiiD, Alex T. PietiD, Omid A. ZobeiriiD, Adam AmsteriD, Anton S. ArkhipoviD, Alex CahooniD, Shiella CaldejoniD, Mikayla CarlsoniD, Linzy Casal, Scott F. DanieliD, Colin FarrelliD, Marina GarrettiD, Ryan GillisiD, Conor GrassoiD, Ben HardcastleiD, Ross Hytnen, Tye JohnsoniD, Peter LedochowitschiD, Quinn L’HeureuxiD, Dana MastrovitoiD, Ethan G. McBrideiD, , Shawn R. OlseniD
Abstract
Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here we present a database of spiking activity across the mouse visual system--including thalamus, cortex, and midbrain--while mice perform an image change detection task. Using Neuropixels probes, we record from >75,000 high-quality units in 54 mice, mapping area-, cortical layer-, and cell type-specific coding of sensory and motor information. Modulation by task-engagement increased across the thalamocortical hierarchy but was strongest in the midbrain. Novel images modulated cortical (but not thalamic) responses through delayed recurrent activity. Population decoding and optogenetics identified a critical decision window for change detection and revealed that mice use an adaptation-based rather than image-comparison strategy. This comprehensive resource provides a valuable substrate for understanding sensorimotor computations in neural networks.
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