> Synaptic connections mediate classical intercellular communication in the brain. However, recent data have demonstrated the existence of noncanonical routes of interneuronal communication mediating the transport of materials including calcium, mitochondria, and pathogenic proteins such as amyloid beta (Aβ). Using super-resolution and electron microscopy, Chang et al. identified and characterized structures called nanotubular bridges that connect dendrites in the brain (see the Perspective by Budinger and Heneka). These bridges mediate the transport of calcium ions, small molecules, and Aβ peptides, and may contribute to the spreading and accumulation of pathological Aβ in Alzheimer’s disease. —Mattia Maroso
does super-resolution refer to the image processing technique of interpolating/hallucinating higher resolutions? if so, is this a common/respected part of evidence gathering?
Super resolution refers to imaging below the refraction limit, more or less by having the receiving sensor within a wavelength or two of the material being imaged, allowing you to use the nearfield (which doesn't have a diffraction limit, but which also doesn't propagate beyond a couple wavelengths) instead of the farfield (which does, and does).
It's unrelated to the nvidia marketing term for ai filtering of images.
Nvidia's DLSS Super Resolution doesn't do anything with bypassing the diffraction limit, but does go beyond the single image nyquist limit by undersampling the input render, jittering the projection matrix each frame, and reconstructing higher resolution with frame history. It's reconstructing real extra detail. Some parts of it like handling disocclusion areas between frames etc. are fully hallucinated though.
With camera movement and things like gaps between camera sensor elements acting as the undersampling, their video super resolution may be learning similar ways of legitimately reconstructing at a higher res from temporal data, though it also hallucinates some in and is dealing with already compressed video where a lot of that might be lost.
I'm not sure if their video super resolution actually does this kind of temporal stuff though or it is just a repeated image upscale, but some of the AI video upscalers do and get much better upscaling on longer windows of frames than when run frame by frame without context.
But they say they used ML analysis too in the abstract
> Using super-resolution microscopy,25
we characterized their unique molecular composition and dynamics in dissociated neurons,26
enabling Ca 2+ propagation over distances. Utilizing imaging and machine-learning-based27
analysis, we confirmed the in situ presence of DNTs connecting dendrites to other dendrites28
whose anatomical features are distinguished from synaptic dendritic spines
> Synaptic connections mediate classical intercellular communication in the brain. However, recent data have demonstrated the existence of noncanonical routes of interneuronal communication mediating the transport of materials including calcium, mitochondria, and pathogenic proteins such as amyloid beta (Aβ). Using super-resolution and electron microscopy, Chang et al. identified and characterized structures called nanotubular bridges that connect dendrites in the brain (see the Perspective by Budinger and Heneka). These bridges mediate the transport of calcium ions, small molecules, and Aβ peptides, and may contribute to the spreading and accumulation of pathological Aβ in Alzheimer’s disease. —Mattia Maroso