The male-specific Fruitless proteins (Fru(M)) act to establish the potential for male courtship behavior in Drosophila melanogaster and are expressed in small groups of neurons throughout the nervous system. We screened  1000 GAL4 lines, using assays for general courtship, male-male interactions, and male fertility to determine the phenotypes resulting from the GAL4 driven inhibition of Fru(M) expression in subsets of these neurons. A battery of secondary assays showed that the phenotypic classes of GAL4 lines could be divided into subgroups based on additional neurobiological and behavioral criteria. For example, in some lines restoration of Fru(M) expression in cholinergic neurons restores fertility or reduces male-male courtship. Persistent chains of males courting each other in some lines results from males courting both sexes indiscriminately whereas in other lines this phenotype result from apparent habituation deficits. Inhibition of ectopic Fru(M) expression in females, in populations of neurons where Fru(M) is necessary for male fertility, can rescue female infertility. To identify the neurons responsible for some of the observed behavioral alterations, we determined the overlap between the identified GAL4 lines and endogenous Fru(M) expression in lines with fertility defects. The GAL4 lines causing fertility defects generally had widespread overlap with Fru(M) expression in many regions of the nervous system suggesting likely redundant Fru(M)-expressing neuronal pathways capable of conferring male fertility. From associations between the screened behaviors, we propose a functional model for courtship initiation.

Understanding how activity patterns in specific neural circuits coordinate an animal's behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light.

Spatial navigation is often used as a behavioral task in studies of the neuronal circuits that underlie cognition, learning and memory in rodents. The combination of in vivo microscopy with genetically encoded indicators has provided an important new tool for studying neuronal circuits, but has been technically difficult to apply during navigation. Here we describe methods for imaging the activity of neurons in the CA1 region of the hippocampus with subcellular resolution in behaving mice. Neurons that expressed the genetically encoded calcium indicator GCaMP3 were imaged through a chronic hippocampal window. Head-restrained mice performed spatial behaviors in a setup combining a virtual reality system and a custom-built two-photon microscope. We optically identified populations of place cells and determined the correlation between the location of their place fields in the virtual environment and their anatomical location in the local circuit. The combination of virtual reality and high-resolution functional imaging should allow a new generation of studies to investigate neuronal circuit dynamics during behavior.

Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. While many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called "minimal" enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster (1). However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor binding sites that drive patterning.

Individual neurons in prefrontal cortex – a key brain area involved in cognitive functions – are selective for variables such as space or time, as well as more cognitive aspects of tasks, such as learned categories. Many neurons exhibit mixed selectivity, that is, they show selectivity for multiple variables. A fundamental question is whether neurons are functionally specialized for particular variables and how selectivity for different variables intersects across the population. Here, we analyzed neural correlates of space and time in rats performing a navigational task with two behaviorally important categories – starts and goals. Using simultaneous recordings of many medial prefrontal cortex (mPFC) neurons during behavior, we found that population codes for elapsed time were invariant to different locations within categories, and subsets of neurons had functional preferences for time or space across categories. Thus, mPFC exhibits structured selectivity, which may facilitate complex behaviors by efficiently generating informative representations of multiple variables.

Small unilamellar vesicles (SUVs) are indispensable model membranes, organelle mimics, and drug and vaccine carriers. However, the lack of robust techniques to functionalize or organize preformed SUVs limits their applications. Here we use DNA nanostructures to coat, cluster, and pattern sub-100-nm liposomes, generating distance-controlled vesicle networks, strings and dimers, among other configurations. The DNA coating also enables attachment of proteins to liposomes, and temporal control of membrane fusion driven by SNARE protein complexes. Such a convenient and versatile method of engineering premade vesicles both structurally and functionally is highly relevant to bottom-up biology and targeted delivery.

Processing bodies (p-bodies) are a prototypical phase-separated RNA-containing granule. Their abundance is highly dynamic and has been linked to translation. Yet, the molecular mechanisms responsible for coordinate control of the two processes are unclear. Here, we uncover key roles for eEF2 kinase (eEF2K) in the control of ribosome availability and p-body abundance. eEF2K acts on a sole known substrate, eEF2, to inhibit translation. We find that the eEF2K agonist nelfinavir abolishes p-bodies in sensory neurons and impairs translation. To probe the latter, we used cryo-electron microscopy. Nelfinavir stabilizes vacant 80S ribosomes. They contain SERBP1 in place of mRNA and eEF2 in the acceptor site. Phosphorylated eEF2 associates with inactive ribosomes that resist splitting in vitro. Collectively, the data suggest that eEF2K defines a population of inactive ribosomes resistant to recycling and protected from degradation. Thus, eEF2K activity is central to both p-body abundance and ribosome availability in sensory neurons.

Human memory appears to be fragile and unpredictable. Free recall of random lists of words is a standard paradigm used to probe episodic memory. We proposed an associative search process that can be reduced to a deterministic walk on random graphs defined by the structure of memory representations. The corresponding graph model can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled (R) out of M items in memory: R=sqrt[3πM/2]. This prediction was verified with a specially designed experimental protocol combining large-scale crowd-sourced free recall and recognition experiments with randomly assembled lists of words or common facts. Our results show that human memory can be described by universal laws derived from first principles.

Predictive remapping (PRE )—the ability of cells in retinotopic brain structures to transiently exhibit spatiotemporal shifts beyond the spatial extent of their classical anatomical receptive fields—has been proposed as a primary mechanism that stabilizes an organism’s percept of the visual world around the time of a saccadic eye movement. Despite the well-documented effects of PRE , a biologically plausible mathematical framework that specifies a fundamental law and the functional neural architecture that actively mediates this ubiquitous phenomenon does not exist. We introduce the Newtonian model of PRE , where each modular component of PRE manifests as three temporally overlapping forces: centripetal ( fC ), convergent ( fP ), and translational ( fT ), that perturb retinotopic cells from their equilibrium extent. The resultant and transient influences of these forces fC + fP + fT gives rise to a neuronal force field that governs the spatiotemporal dynamics of PRE . This neuronal force field fundamentally obeys an inverse-distance law PRE ∝ 1 r1.6 , akin to Newton’s law of universal gravitation [I. Newton, Newton’s Principia: The Mathematical Principles of Natural Philosophy (Geo. P. Putnam, New-York, 1850)] and activates retinotopic elastic fields elϕ’s. We posit that elϕ’s are transient functional neural structures that are self-generated by visual systems during active vision and approximate the sloppiness (or degrees of spatial freedom) within which receptive fields are allowed to shift, while ensuring that retinotopic organization does not collapse. The predictions of this general model are borne out by the spatiotemporal changes in visual sensitivity to probe stimuli in human subjects around the time of an eye movement and qualitatively match neural sensitivity signatures associated with predictive shifts in the receptive fields of cells in premotor and higher-order retinotopic brain structures. The introduction of this general model opens the search for possible biophysical implementations and provides experimentalists with a simple, elegant, yet powerful mathematical framework they can now use to generate experimentally testable predictions across a range of biological systems.