Two‐Photon Lithography, thanks to its very high sub‐diffraction resolution, has become the lithographic technique par excellence in applications requiring small feature sizes and complex 3D pattering. Despite this, the fabrication times required for extended structures remain much longer than those of other competing techniques (UV mask lithography, nanoimprinting, etc.). Its low throughput prevents its wide adoption in industrial applications. To increase it, over the years different solutions have been proposed, although their usage is difficult to generalize and may be limited depending on the specific application. A promising strategy to further increase the throughput of Two‐Photon Lithography, opening a concrete window for its adoption in industry, lies in its combination with holography approaches: in this way it is possible to generate dozens of foci from a single laser beam, thus parallelizing the fabrication of periodic structures, or to engineer the intensity distribution on the writing plane in a complex way, obtaining 3D microstructures with a single exposure. Here, the fundamental concepts behind high‐speed Two‐Photon Lithography and its combination with holography are discussed, and the literary production of recent years that exploits such techniques is reviewed, and contextualized according to the topic covered.

Fiber photometry is used to monitor signals from fluorescent indicators in genetically-defined neural populations in behaving animals. Recently, fiber photometry has rapidly expanded and it now provides researchers with increasingly powerful means to record neural dynamics and neuromodulatory action. However, it is not clear how to select the optimal fiber optic given the constraints and goals of a particular experiment. Here, using combined confocal/2-photon microscope, we quantitatively characterize the fluorescence collection properties of various optical fibers in brain tissue. We show that the fiber size plays a major role in defining the volume of the optically sampled brain region, whereas numerical aperture impacts the total amount of collected signal and, marginally, the shape and size of the collection volume. We show that ~80% of the effective signal arises from 10⁵ to 10⁶ μm³ volume extending ~200 μm from the fiber facet for 200 μm core optical fibers. Together with analytical and ray tracing collection maps, our results reveal the light collection properties of different optical fibers in brain tissue, allowing for an accurate selection of the fibers for photometry and helping for a more precise interpretation of measurements in terms of sampled volume.

Integration of plasmonic nanostructures with fiber‐optics‐based neural probes enables label‐free detection of molecular fingerprints via surface‐enhanced Raman spectroscopy (SERS), and it represents a fascinating technological horizon to investigate brain function. However, developing neuroplasmonic probes that can interface with deep brain regions with minimal invasiveness while providing the sensitivity to detect biomolecular signatures in a physiological environment is challenging, in particular because the same waveguide must be employed for both delivering excitation light and collecting the resulting scattered photons. Here, a SERS‐active neural probe based on a tapered optical fiber (TF) decorated with gold nanoislands (NIs) that can detect neurotransmitters down to the micromolar range is presented. To do this, a novel, nonplanar repeated dewetting technique to fabricate gold NIs with sub‐10 nm gaps, uniformly distributed on the wide (square millimeter scale in surface area), highly curved surface of TF is developed. It is experimentally and numerically shown that the amplified broadband near‐field enhancement of the high‐density NIs layer allows for achieving a limit of detection in aqueous solution of 10⁻⁷ m for rhodamine 6G and 10⁻⁵ m for serotonin and dopamine through SERS at near‐infrared wavelengths. The NIs‐TF technology is envisioned as a first step toward the unexplored frontier of in vivo label‐free plasmonic neural interfaces.