ABSTRACT
Maps of the nervous system that identify individual cells along with their type, subcellular components and connectivity have the potential to elucidate fundamental organizational principles of neural circuits. Nanometer-resolution imaging of brain tissue provides the necessary raw data, but inferring cellular and subcellular annotation layers is challenging. We present segmentation-guided contrastive learning of representations (SegCLR), a self-supervised machine learning technique that produces representations of cells directly from 3D imagery and segmentations. When applied to volumes of human and mouse cortex, SegCLR enables accurate classification of cellular subcompartments and achieves performance equivalent to a supervised approach while requiring 400-fold fewer labeled examples. SegCLR also enables inference of cell types from fragments as small as 10 µm, which enhances the utility of volumes in which many neurites are truncated at boundaries. Finally, SegCLR enables exploration of layer 5 pyramidal cell subtypes and automated large-scale analysis of synaptic partners in mouse visual cortex.
Subject(s)
Neuropil , Visual Cortex , Humans , Animals , Mice , Neurites , Pyramidal Cells , Supervised Machine Learning , Image Processing, Computer-AssistedABSTRACT
The neural coding of human color vision begins in the retina. The outputs of long (L)-, middle (M)-, and short (S)-wavelength-sensitive cone photoreceptors combine antagonistically to produce "red-green" and "blue-yellow" spectrally opponent signals (Hering, 1878; Hurvich and Jameson, 1957). Spectral opponency is well established in primate retinal ganglion cells (Reid and Shapley, 1992; Dacey and Lee, 1994; Dacey et al., 1996), but the retinal circuitry creating the opponency remains uncertain. Here we find, from whole-cell recordings of photoreceptors in macaque monkey, that "blue-yellow" opponency is already present in the center-surround receptive fields of S cones. The inward current evoked by blue light derives from phototransduction within the outer segment of the S cone. The outward current evoked by yellow light is caused by feedback from horizontal cells that are driven by surrounding L and M cones. Stimulation of the surround modulates calcium conductance in the center S cone.