The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations.

Continuous attractor networks are used to model the storage and representation of analog quantities, such as position of a visual stimulus. The storage of multiple continuous attractors in the same network has previously been studied in the context of self-position coding. Several uncorrelated maps of environments are stored in the synaptic connections, and a position in a given environment is represented by a localized pattern of neural activity in the corresponding map, driven by a spatially tuned input. Here we analyze networks storing a pair of correlated maps, or a morph sequence between two uncorrelated maps. We find a novel state in which the network activity is simultaneously localized in both maps. In this state, a fixed cue presented to the network does not determine uniquely the location of the bump, i.e. the response is unreliable, with neurons not always responding when their preferred input is present. When the tuned input varies smoothly in time, the neuronal responses become reliable and selective for the environment: the subset of neurons responsive to a moving input in one map changes almost completely in the other map. This form of remapping is a non-trivial transformation between the tuned input to the network and the resulting tuning curves of the neurons. The new state of the network could be related to the formation of direction selectivity in one-dimensional environments and hippocampal remapping. The applicability of the model is not confined to self-position representations; we show an instance of the network solving a simple delayed discrimination task.

The brain is an organ of immense complexity. Next-generation RNA sequencing (RNA-seq) is becoming increasingly popular in the deconstruction of this complexity into distinct classes of 'cell types'. Notably, in addition to revealing the organization of this distinct cell-type landscape, the technology has also begun to illustrate that continuous variation can be found within narrowly defined cell types. Here we summarize the evidence for graded transcriptomic heterogeneity being present, widespread, and functionally relevant in the nervous system. We explain how these graded differences can map onto higher-order organizational features and how they may reframe existing interpretations of higher-order heterogeneity. Ultimately, a multimodal approach incorporating continuously variable cell types will facilitate an accurate reductionist interpretation of the nervous system.

In vivo imaging at high spatiotemporal resolution is key to the understanding of complex biological systems. We integrated an optical phase-locked ultrasound lens into a two-photon fluorescence microscope and achieved microsecond-scale axial scanning, thus enabling volumetric imaging at tens of hertz. We applied this system to multicolor volumetric imaging of processes sensitive to motion artifacts, including calcium dynamics in behaving mouse brain and transient morphology changes and trafficking of immune cells.

Mechano-transduction is an emerging but still poorly understood component of T cell activation. Here we investigated the ligand-dependent contribution made by contractile actomyosin arcs populating the peripheral supramolecular activation cluster (pSMAC) region of the immunological synapse (IS) to T cell receptor (TCR) microcluster transport and proximal signaling in primary mouse T cells. Using super resolution microscopy, OT1-CD8+ mouse T cells, and two ovalbumin (OVA) peptides with different affinities for the TCR, we show that the generation of organized actomyosin arcs depends on ligand potency and the ability of myosin 2 to contract actin filaments. While weak ligands induce disorganized actomyosin arcs, strong ligands result in organized actomyosin arcs that correlate well with tension-sensitive CasL phosphorylation and the accumulation of ligands at the IS center. Blocking myosin 2 contractility greatly reduces the difference in the extent of Src and LAT phosphorylation observed between the strong and the weak ligand, arguing that myosin 2-dependent force generation within actin arcs contributes to ligand discrimination. Together, our data are consistent with the idea that actomyosin arcs in the pSMAC region of the IS promote a mechano-chemical feedback mechanism that amplifies the accumulation of critical signaling molecules at the IS.

Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes.

The Drosophila insulin receptor (dInR) regulates cell growth and proliferation through the dPI3K/dAkt pathway, which is conserved in metazoan organisms. Here we report the identification and functional characterization of the Drosophila forkhead-related transcription factor dFOXO, a key component of the insulin signaling cascade. dFOXO is phosphorylated by dAkt upon insulin treatment, leading to cytoplasmic retention and inhibition of its transcriptional activity. Mutant dFOXO lacking dAkt phosphorylation sites no longer responds to insulin inhibition, remains in the nucleus, and is constitutively active. dFOXO activation in S2 cells induces growth arrest and activates two key players of the dInR/dPI3K/dAkt pathway: the translational regulator d4EBP and the dInR itself. Induction of d4EBP likely leads to growth inhibition by dFOXO, whereas activation of dInR provides a novel transcriptionally induced feedback control mechanism. Targeted expression of dFOXO in fly tissues regulates organ size by specifying cell number with no effect on cell size. Our results establish dFOXO as a key transcriptional regulator of the insulin pathway that modulates growth and proliferation.

Deciphering the molecular basis of pluripotency is fundamental to our understanding of development and embryonic stem cell function. Here, we report that TAF3, a TBP-associated core promoter factor, is highly enriched in ES cells. In this context, TAF3 is required for endoderm lineage differentiation and prevents premature specification of neuroectoderm and mesoderm. In addition to its role in the core promoter recognition complex TFIID, genome-wide binding studies reveal that TAF3 localizes to a subset of chromosomal regions bound by CTCF/cohesin that are selectively associated with genes upregulated by TAF3. Notably, CTCF directly recruits TAF3 to promoter distal sites and TAF3-dependent DNA looping is observed between the promoter distal sites and core promoters occupied by TAF3/CTCF/cohesin. Together, our findings support a new role of TAF3 in mediating long-range chromatin regulatory interactions that safeguard the finely-balanced transcriptional programs underlying pluripotency.

Sexual orientation and courtship behavior in Drosophila are regulated by fruitless (fru), the first gene in a branch of the sex-determination hierarchy functioning specifically in the central nervous system (CNS). The phenotypes of new fru mutants encompass nearly all aspects of male sexual behavior. Alternative splicing of fru transcripts produces sex-specific proteins belonging to the BTB-ZF family of transcriptional regulators. The sex-specific fru products are produced in only about 500 of the 10(5) neurons that comprise the CNS. The properties of neurons expressing these fru products suggest that fru specifies the fates or activities of neurons that carry out higher order control functions to elicit and coordinate the activities comprising male courtship behavior.

The Drosophila mushroom body (MB) is an associative learning network that is important for the control of sleep. We have recently identified particular intrinsic MB Kenyon cell (KC) classes that regulate sleep through synaptic activation of particular MB output neurons (MBONs) whose axons convey sleep control signals out of the MB to downstream target regions. Specifically, we found that sleep-promoting KCs increase sleep by preferentially activating cholinergic sleep-promoting MBONs, while wake-promoting KCs decrease sleep by preferentially activating glutamatergic wake-promoting MBONs. Here we use a combination of genetic and physiological approaches to identify wake-promoting dopaminergic neurons (DANs) that innervate the MB, and show that they activate wake-promoting MBONs. These studies reveal a dopaminergic sleep control mechanism that likely operates by modulation of KC-MBON microcircuits.