Many animal embryos face early on in development the problem of having to pull and close an epithelial sheet around the spherical yolk-sac. During this gastrulation process, known as epiboly, the spherical geometry of the egg dictates that the epithelial sheet first expands and subsequently compacts to close around the sphere. While it is well recognized that contractile actomyosin cables can drive epiboly movements, it is unclear how pulling on the leading edge can lead to simultaneous tissue expansion and compaction. Moreover, the epithelial sheet spreading over the sphere is mechanically stressed and this stress needs to be dissipated for seamless closure. While oriented cell division is known to dissipate tissue stresses during epiboly, it is unclear how this can be achieved without cell division. Here we show that during extraembryonic tissue (serosa) epiboly in the red flour beetle Tribolium castaneum, the non-proliferative serosa becomes regionalized into two distinct territories: a dorsal region under higher tension away from the leading edge with larger, isodiametric and non-rearranging cells, and a more fluid ventral region under lower tension surrounding the leading edge with smaller, anisotropic cells undergoing cell intercalation. Our results suggest that fluidization of the leading edge is effected by a heterogeneous actomyosin cable that drives sequential eviction and intercalation of individual cells away from the serosa margin. Since this developmental solution utilized during epiboly resembles the mechanism of wound healing in other systems, we propose actomyosin cable-driven local tissue fluidization as a conserved morphogenetic module for closure of epithelial gaps.

Dendritic spines are the nearly ubiquitous site of excitatory synaptic input onto neurons and as such are critically positioned to influence diverse aspects of neuronal signalling. Decades of theoretical studies have proposed that spines may function as highly effective and modifiable chemical and electrical compartments that regulate synaptic efficacy, integration and plasticity. Experimental studies have confirmed activity-dependent structural dynamics and biochemical compartmentalization by spines. However, there is a longstanding debate over the influence of spines on the electrical aspects of synaptic transmission and dendritic operation. Here we measure the amplitude ratio of spine head to parent dendrite voltage across a range of dendritic compartments and calculate the associated spine neck resistance (R(neck)) for spines at apical trunk dendrites in rat hippocampal CA1 pyramidal neurons. We find that R(neck) is large enough ( 500 MΩ) to amplify substantially the spine head depolarization associated with a unitary synaptic input by  1.5- to  45-fold, depending on parent dendritic impedance. A morphologically realistic compartmental model capable of reproducing the observed spatial profile of the amplitude ratio indicates that spines provide a consistently high-impedance input structure throughout the dendritic arborization. Finally, we demonstrate that the amplification produced by spines encourages electrical interaction among coactive inputs through an R(neck)-dependent increase in spine head voltage-gated conductance activation. We conclude that the electrical properties of spines promote nonlinear dendritic processing and associated forms of plasticity and storage, thus fundamentally enhancing the computational capabilities of neurons.

Phase precession is a well known phenomenon in which a hippocampal place cell will fire action potentials at successively earlier phases (relative to the theta-band oscillations recorded in the local field potential) as an animal moves through the cell’s receptive field (also known as a place field). We present a model in which CA1 pyramidal cell spiking is driven by dual input components arising from CA3 and EC3. The receptive fields of these two input components overlap but are offset in space from each other such that as the animal moves through the model place field, action potentials are driven first by the CA3 input component and then the EC3 input component. As CA3 synaptic input is known to arrive in CA1 at a later theta phase than EC3 input (Mizuseki et al., 2009; Montgomery et al., 2009), CA1 spiking advances in phase as the model transitions from CA3-driven spiking to EC3-driven spiking. Here spike phase is a function of animal location, placing our results in agreement with many experimental observations characterizing CA1 phase precession (O’Keefe and Recce, 1993; Huxter et al., 2003; Geisler et al., 2007). We predict that experimental manipulations that dramatically enhance or disrupt activity in either of these areas should have a significant effect on phase precession observed in CA1.

Relating the function of neuronal cell types to information processing and behavior is a central goal of neuroscience. In the hippocampus, pyramidal cells in CA1 and the subiculum process sensory and motor cues to form a cognitive map encoding spatial, contextual, and emotional information, which they transmit throughout the brain. Do these cells constitute a single class or are there multiple cell types with specialized functions? Using unbiased cluster analysis, we show that there are two morphologically and electrophysiologically distinct principal cell types that carry hippocampal output. We show further that these two cell types are inversely modulated by the synergistic action of glutamate and acetylcholine acting on metabotropic receptors that are central to hippocampal function. Combined with prior connectivity studies, our results support a model of hippocampal processing in which the two pyramidal cell types are predominantly segregated into two parallel pathways that process distinct modalities of information.

Locomotion requires coordinated motor activity throughout an animal's body. In both vertebrates and invertebrates, chains of coupled central pattern generators (CPGs) are commonly evoked to explain local rhythmic behaviors. In C. elegans, we report that proprioception within the motor circuit is responsible for propagating and coordinating rhythmic undulatory waves from head to tail during forward movement. Proprioceptive coupling between adjacent body regions transduces rhythmic movement initiated near the head into bending waves driven along the body by a chain of reflexes. Using optogenetics and calcium imaging to manipulate and monitor motor circuit activity of moving C. elegans held in microfluidic devices, we found that the B-type cholinergic motor neurons transduce the proprioceptive signal. In C. elegans, a sensorimotor feedback loop operating within a specific type of motor neuron both drives and organizes body movement.

Binary cell fate decisions allow the production of distinct sister neurons from an intermediate precursor. Neurons are further diversified based on the birth order of intermediate precursors. Here we examined the interplay between binary cell fate and birth-order-dependent temporal fate in the Drosophila lateral antennal lobe (lAL) neuronal lineage. Single-cell mapping of the lAL lineage by twin-spot mosaic analysis with repressible cell markers (ts-MARCM) revealed that projection neurons (PNs) and local interneurons (LNs) are made in pairs through binary fate decisions. Forty-five types of PNs innervating distinct brain regions arise in a stereotyped sequence; however, the PNs with similar morphologies are not necessarily born in a contiguous window. The LNs are morphologically less diverse than the PNs, and the sequential morphogenetic changes in the two pairs occur independently. Sanpodo-dependent Notch activity promotes and patterns the LN fates. By contrast, Notch diversifies PN temporal fates in a Sanpodo-dispensable manner. These pleiotropic Notch actions underlie the differential temporal fate specification of twin neurons produced by common precursors within a lineage, possibly by modulating postmitotic neurons’ responses to Notch-independent transcriptional cascades.

Our brains are capable of remarkably stable stimulus representations despite time-varying neural activity. For instance, during delay periods in working memory tasks, while stimuli are represented in working memory, neurons in the prefrontal cortex, thought to support the memory representation, exhibit time-varying neuronal activity. Since neuronal activity encodes the stimulus, its time-varying dynamics appears to be paradoxical and incompatible with stable network stimulus representations. Indeed, this finding raises a fundamental question: can stable representations only be encoded with stable neural activity, or, its corollary, is every change in activity a sign of change in stimulus representation?

paradox? You might expect more complex organisms to have progressively larger genomes, but eukaryotic genome size fails to correlate well with apparent complexity, and instead varies wildly over more than a 100,000-fold range. Single-celled amoebae have some of the largest genomes, up to 100-fold larger than the human genome. This variation suggested that genomes can contain a substantial fraction of DNA other than for genes and their regulatory sequences. C.A. Thomas Jr dubbed it the ‘C-value paradox’ in 1971.

Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.