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Full-Text Articles in Life Sciences
Ultrastructural Correlates Of Axons And Synapses Belonging To Different Circuits In Ferret Primary Visual Cortex, Anjelique Sawh
Ultrastructural Correlates Of Axons And Synapses Belonging To Different Circuits In Ferret Primary Visual Cortex, Anjelique Sawh
Dissertations and Theses
The goal of this study was to determine differences in distinctive layers of mammalian primary visual cortex through analysis of their ultrastructural characteristics. Characterizing brain circuitry using 3-dimensional reconstruction of electron microscopy images, and subsequent ultrastructural analysis of axonal populations provides us with a better understanding of the connectivity of the neural circuits. By quantifying ultrastructural differences in axonal processes such as synaptic densities, types of synapses and their post-synaptic densities (PSDs), mitochondrial volumes, synaptic vesicle aggregates, dendritic targets, and bouton volumes, we aimed to understand whether differences in anatomical specializations among different cortical layers could underlie differences in function …
Variance Predicts Salience In Central Sensory Processing, Ann M. Hermundstad, John J. Briguglio, Mary M. Conte, Jonathan D. Victor, Vijay Balasubramanian, Gašper Tkačik
Variance Predicts Salience In Central Sensory Processing, Ann M. Hermundstad, John J. Briguglio, Mary M. Conte, Jonathan D. Victor, Vijay Balasubramanian, Gašper Tkačik
Publications and Research
Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range should be compressed. In a different regime—when sampling limitations constrain performance—efficient coding implies that more resources should be allocated to informative features that are more variable. We propose that this regime is relevant for sensory cortex when it extracts complex features from limited numbers of sensory samples. To test this prediction, we use central visual processing as a model: we show that visual sensitivity for local multi-point …