Neurophysiology has long progressed through exploratory experiments and chance discoveries. Anecdotes abound of researchers listening to spikes in real time and noticing patterns of activity related to ongoing stimuli or behaviors. With the advent of large-scale recordings, such close observation of data has become difficult. To find patterns in large-scale neural data, we developed 'Rastermap', a visualization method that displays neurons as a raster plot after sorting them along a one-dimensional axis based on their activity patterns. We benchmarked Rastermap on realistic simulations and then used it to explore recordings of tens of thousands of neurons from mouse cortex during spontaneous, stimulus-evoked and task-evoked epochs. We also applied Rastermap to whole-brain zebrafish recordings; to wide-field imaging data; to electrophysiological recordings in rat hippocampus, monkey frontal cortex and various cortical and subcortical regions in mice; and to artificial neural networks. Finally, we illustrate high-dimensional scenarios where Rastermap and similar algorithms cannot be used effectively.

We investigate a practical approach to solving one instantiation of a distributed hypothesis testing problem under severe rate constraints that shows up in a wide variety of applications such as camera calibration, biometric authentication and video hashing: given two distributed continuous-valued random sources, determine if they satisfy a certain Euclidean distance criterion. We show a way to convert the problem from continuous-valued to binary-valued using binarized random projections and obtain rate savings by applying a linear syndrome code. In finding visual correspondences, our approach uses just 49% of the rate of scalar quantization to achieve the same level of retrieval performance. To perform video hashing, our approach requires only a hash rate of 0.0142 bpp to identify corresponding groups of pictures correctly.

Light-mediated chemical reactions are powerful methods for manipulating and interrogating biological systems. Photosensitizers, compounds that generate reactive oxygen species upon excitation with light, can be utilized for numerous biological experiments, but the repertoire of bioavailable photosensitizers is limited. Here, we describe the synthesis, characterization, and utility of two photosensitizers based upon the widely used rhodamine scaffold and demonstrate their efficacy for chromophore-assisted light inactivation, cell ablation in culture and in vivo, and photopolymerization of diaminobenzidine for electron microscopy. These chemical tools will facilitate a broad range of applications spanning from targeted destruction of proteins to high-resolution imaging.

Rhodamine dyes exist in equilibrium between a fluorescent zwitterion and a nonfluorescent lactone. Tuning this equilibrium toward the nonfluorescent lactone form can improve cell-permeability and allow creation of "fluorogenic" compounds-ligands that shift to the fluorescent zwitterion upon binding a biomolecular target. An archetype fluorogenic dye is the far-red tetramethyl-Si-rhodamine (SiR), which has been used to create exceptionally useful labels for advanced microscopy. Here, we develop a quantitative framework for the development of new fluorogenic dyes, determining that the lactone-zwitterion equilibrium constant () is sufficient to predict fluorogenicity. This rubric emerged from our analysis of known fluorophores and yielded new fluorescent and fluorogenic labels with improved performance in cellular imaging experiments. We then designed a novel fluorophore-Janelia Fluor 526 (JF)-with SiR-like properties but shorter fluorescence excitation and emission wavelengths. JF is a versatile scaffold for fluorogenic probes including ligands for self-labeling tags, stains for endogenous structures, and spontaneously blinking labels for super-resolution immunofluorescence. JF constitutes a new label for advanced microscopy experiments, and our quantitative framework will enable the rational design of other fluorogenic probes for bioimaging.

Genetically encoded pH sensors based on fluorescent proteins are valuable tools for the imaging of cellular events that are associated with pH changes, such as exocytosis and endocytosis. Superecliptic pHluorin (SEP) is a pH-sensitive green fluorescent protein (GFP) variant widely used for such applications. Here, we report the rational design, development, structure, and applications of Lime, an improved SEP variant with higher fluorescence brightness and greater pH sensitivity. The X-ray crystal structure of Lime supports the mechanistic rationale that guided the introduction of beneficial mutations. Lime provides substantial improvements relative to SEP for imaging of endocytosis and exocytosis. Furthermore, Lime and its variants are advantageous for a broader range of applications including the detection of synaptic release and neuronal voltage changes.

Green-to-red photoconvertible fluorescent proteins (pcFPs) are powerful tools for super-resolution localization microscopy and protein tagging. Recently, they have been found to undergo efficient photoconversion not only by the traditional 400-nm illumination but also by an alternative method termed primed conversion, employing dual wavelength illumination with blue and far-red/near-infrared light. Primed conversion has been reported only for Dendra2 and its mechanism has remained elusive. Here, we uncover the molecular mechanism of primed conversion by reporting the intermediate "primed" state to be a triplet dark state formed by intersystem crossing. We show that formation of this state can be influenced by the introduction of serine or threonine at sequence position 69 (Eos notation) and use this knowledge to create "pr"- (for primed convertible) variants of most known green-to-red pcFPs.

The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal information with the least invasiveness. Deep neural networks have substantially improved optical microscopy, including image super-resolution and restoration, but still have substantial potential for artifacts. In this study, we developed rationalized deep learning (rDL) for structured illumination microscopy and lattice light sheet microscopy (LLSM) by incorporating prior knowledge of illumination patterns and, thereby, rationally guiding the network to denoise raw images. Here we demonstrate that rDL structured illumination microscopy eliminates spectral bias-induced resolution degradation and reduces model uncertainty by five-fold, improving the super-resolution information by more than ten-fold over other computational approaches. Moreover, rDL applied to LLSM enables self-supervised training by using the spatial or temporal continuity of noisy data itself, yielding results similar to those of supervised methods. We demonstrate the utility of rDL by imaging the rapid kinetics of motile cilia, nucleolar protein condensation during light-sensitive mitosis and long-term interactions between membranous and membrane-less organelles.

The ability to image and manipulate specific cell populations in Drosophila enables the investigation of how neural circuits develop and coordinate appropriate motor behaviors. Gal4 lines give genetic access to many types of neurons, but the expression patterns of these reagents are often complex. Here, we present the generation and expression patterns of LexA lines based on the vesicular neurotransmitter transporters and Hox transcription factors. Intersections between these LexA lines and existing Gal4 collections provide a strategy for rationally subdividing complex expression patterns based on neurotransmitter or segmental identity.

Distal enhancers commonly contact target promoters via chromatin looping. In erythroid cells, the locus control region (LCR) contacts β-type globin genes in a developmental stage-specific manner to stimulate transcription. Previously, we induced LCR-promoter looping by tethering the self-association domain (SA) of Ldb1 to the β-globin promoter via artificial zinc fingers. Here, we show that targeting the SA to a developmentally silenced embryonic globin gene in adult murine erythroblasts triggers its transcriptional reactivation. This activity depends on the LCR, consistent with an LCR-promoter looping mechanism. Strikingly, targeting the SA to the fetal γ-globin promoter in primary adult human erythroblasts increases γ-globin promoter-LCR contacts, stimulating transcription to approximately 85% of total β-globin synthesis, with a reciprocal reduction in adult β-globin expression. Our findings demonstrate that forced chromatin looping can override a stringent developmental gene expression program and suggest a novel approach to control the balance of globin gene transcription for therapeutic applications.

Neurons are inherently plastic, adjusting their structure, connectivity and excitability in response to changes in activity. How neurons sense changes in their activity level and then transduce these to structural changes remains to be fully elucidated. Working with the Drosophila larval locomotor network, we show that neurons use reactive oxygen species (ROS), metabolic byproducts, to monitor their activity. ROS signals are both necessary and sufficient for activity-dependent structural adjustments of both pre- and postsynaptic terminals and for network output, as measured by larval crawling behavior. We find the highly conserved Parkinsons disease-linked protein DJ-1b acts as a redox sensor in neurons where it regulates pre- and postsynaptic structural plasticity, in part via modulation of the PTEN-PI3Kinase pathway. Neuronal ROS thus play an important physiological role as second messengers required for neuronal and network tuning, whose dysregulation in the ageing brain and under neurodegenerative conditions may contribute to synaptic dysfunction.