The brain is tasked with choosing actions that maximize an animal's chances of survival and reproduction. These choices must be flexible and informed by the current state of the environment, the needs of the body, and the outcomes of past actions. This information is physiologically encoded and processed across different brain regions on a wide range of spatial scales, from molecules in single synapses to networks of brain areas. Uncovering these spatially distributed neural interactions underlying behavior requires investigations that span a similar range of spatial scales. Larval zebrafish, given their small size, transparency, and ease of genetic access, are a good model organism for such investigations, allowing the use of modern microscopy, molecular biology, and computational techniques. These approaches are yielding new insights into the mechanistic basis of behavioral states, which we review here and compare to related studies in mammalian species.

Analyzing Drosophila melanogaster neural expression patterns in thousands of three-dimensional image stacks of individual brains requires registering them into a canonical framework based on a fiducial reference of neuropil morphology. Given a target brain labeled with predefined landmarks, the BrainAligner program automatically finds the corresponding landmarks in a subject brain and maps it to the coordinate system of the target brain via a deformable warp. Using a neuropil marker (the antibody nc82) as a reference of the brain morphology and a target brain that is itself a statistical average of data for 295 brains, we achieved a registration accuracy of 2 μm on average, permitting assessment of stereotypy, potential connectivity and functional mapping of the adult fruit fly brain. We used BrainAligner to generate an image pattern atlas of 2954 registered brains containing 470 different expression patterns that cover all the major compartments of the fly brain.

Mammalian chromosomes are organized into megabase-sized compartments that are further subdivided into topologically associating domains (TADs). While the formation of TADs is dependent on cohesin, the mechanism behind compartmentalization remains enigmatic. Here, we show that the bromodomain and extraterminal (BET) family scaffold protein BRD2 promotes spatial mixing and compartmentalization of active chromatin after cohesin loss. This activity is independent of transcription but requires BRD2 to recognize acetylated targets through its double bromodomain and interact with binding partners with its low-complexity domain. Notably, genome compartmentalization mediated by BRD2 is antagonized on the one hand by cohesin and on the other hand by the BET homolog protein BRD4, both of which inhibit BRD2 binding to chromatin. Polymer simulation of our data supports a BRD2-cohesin interplay model of nuclear topology, in which genome compartmentalization results from a competition between loop extrusion and chromatin-state-specific affinity interactions.

In near-field scanning optical microscopy, a light source or detector with dimensions less than the wavelength (lambda) is placed in close proximity (lambda/50) to a sample to generate images with resolution better than the diffraction limit. A near-field probe has been developed that yields a resolution of approximately 12 nm ( approximately lambda/43) and signals approximately 10(4)- to 10(6)-fold larger than those reported previously. In addition, image contrast is demonstrated to be highly polarization dependent. With these probes, near-field microscopy appears poised to fulfill its promise by combining the power of optical characterization methods with nanometric spatial resolution.

In near-field scanning optical microscopy, a light source or detector with dimensions less than the wavelength (lambda) is placed in close proximity (lambda/50) to a sample to generate images with resolution better than the diffraction limit. A near-field probe has been developed that yields a resolution of approximately 12 nm ( approximately lambda/43) and signals approximately 10(4)- to 10(6)-fold larger than those reported previously. In addition, image contrast is demonstrated to be highly polarization dependent. With these probes, near-field microscopy appears poised to fulfill its promise by combining the power of optical characterization methods with nanometric spatial resolution.

Commentary: Introduced the adiabatically tapered single mode fiber probe to near-field scanning optical microscopy which, together with shear force feedback, made the technique a practical reality. Although earlier claims of superresolution via near-field microscopy existed for nearly a decade, this paper was the first to convincingly break Abbe’s limit with visible light, as demonstrated by reproducibly resolving known, complex nanoscale patterns having features separated by much less than the wavelength. Whereas our fiber probe and shear force technologies were soon widely adopted and key to many novel applications (see above), the earlier methods proved to be technological dead ends, never achieving the results of their original claims. This experience taught me the most valuable lesson of my career: while it’s bad to bullshit others, it’s even worse to bullshit yourself. It’s a lesson sadly unheeded by many current practitioners of superresolution microscopy.

The performance of mass spectrometers with limited pumping capacity is shown to be improved through use of a discontinuous atmospheric pressure interface (DAPI). A proof-of-concept DAPI interface was designed and characterized using a miniature rectilinear ion trap mass spectrometer. The interface consists of a simple capillary directly connecting the atmospheric pressure ion source to the vacuum mass analyzer region; it has no ion optical elements and no differential pumping stages. Gases carrying ionized analytes were pulsed into the mass analyzer for short periods at high flow rates rather than being continuously introduced at lower flow rates; this procedure maximized ion transfer. The use of DAPI provides a simple solution to the problem of coupling an atmospheric pressure ionization source to a miniature instrument with limited pumping capacity. Data were recorded using various atmospheric pressure ionization sources, including electrospray ionization (ESI), nano-ESI, atmospheric pressure chemical ionization (APCI), and desorption electrospray ionization (DESI) sources. The interface was opened briefly for ion introduction during each scan. With the use of the 18 W pumping system of the Mini 10, limits of detection in the low part-per-billion levels were achieved and unit resolution mass spectra were recorded.

Optical microscopy has so far been restricted to superficial layers, leaving many important biological questions unanswered. Random scattering causes the ballistic focus, which is conventionally used for image formation, to decay exponentially with depth. Optical imaging beyond the ballistic regime has been demonstrated by hybrid techniques that combine light with the deeper penetration capability of sound waves. Deep inside highly scattering media, the sound focus dimensions restrict the imaging resolutions. Here we show that by iteratively focusing light into an ultrasound focus via phase conjugation, we can fundamentally overcome this resolution barrier in deep tissues and at the same time increase the focus to background ratio. We demonstrate fluorescence microscopy beyond the ballistic regime of light with a threefold improved resolution and a fivefold increase in contrast. This development opens up practical high resolution fluorescence imaging in deep tissues.

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Many unexpected discoveries in developmental biology have depended on advancement of imaging technologies to visualize developmental processes as they unfold across multiple spatial and temporal scales. This essay surveys the recent advances in imaging, highlighting emerging capabilities with an eye toward those poised to have the greatest impact on developmental biology.

As we move through the world, we see the same visual scenes from different perspectives. Although we experience perspective deformations, our perception of a scene remains stable. This raises the question of which neuronal representations in visual brain areas are perspective-tuned and which are invariant. Focusing on planar rotations, we introduce a mathematical framework based on the principle of equivariance, which asserts that an image rotation results in a corresponding rotation of neuronal representations, to explain how the same representation can range from being fully tuned to fully invariant. We applied this framework to large-scale simultaneous neuronal recordings from four visual cortical areas in mice, where we found that representations are both tuned and invariant but become more invariant across higher-order areas. While common deep convolutional neural networks show similar trends in orientation-invariance across layers, they are not rotation-equivariant. We propose that equivariance is a prevalent computation of populations of biological neurons to gradually achieve invariance through structured tuning.