Early stages of visual processing are thought to decorrelate, or whiten, the incoming temporally varying signals. Because the typical correlation time of natural stimuli, as well as the extent of temporal receptive fields of lateral geniculate nucleus (LGN) neurons, is much greater than neuronal time constants, such decorrelation must be done in stages combining contributions of multiple neurons. We propose to model temporal decorrelation in the visual pathway with the lattice filter, a signal processing device for stage-wise decorrelation of temporal signals. The stage-wise architecture of the lattice filter maps naturally onto the visual pathway (photoreceptors -> bipolar cells -> retinal ganglion cells -> LGN) and its filter weights can be learned using Hebbian rules in a stage-wise sequential manner. Moreover, predictions of neural activity from the lattice filter model are consistent with physiological measurements in LGN neurons and fruit fly second-order visual neurons. Therefore, the lattice filter model is a useful abstraction that may help unravel visual system function.

Early stages of sensory systems face the challenge of compressing information from numerous receptors onto a much smaller number of projection neurons, a so called communication bottleneck. To make more efficient use of limited bandwidth, compression may be achieved using predictive coding, whereby predictable, or redundant, components of the stimulus are removed. In the case of the retina, Srinivasan et al. (1982) suggested that feedforward inhibitory connections subtracting a linear prediction generated from nearby receptors implement such compression, resulting in biphasic center-surround receptive fields. However, feedback inhibitory circuits are common in early sensory circuits and furthermore their dynamics may be nonlinear. Can such circuits implement predictive coding as well? Here, solving the transient dynamics of nonlinear reciprocal feedback circuits through analogy to a signal-processing algorithm called linearized Bregman iteration we show that nonlinear predictive coding can be implemented in an inhibitory feedback circuit. In response to a step stimulus, interneuron activity in time constructs progressively less sparse but more accurate representations of the stimulus, a temporally evolving prediction. This analysis provides a powerful theoretical framework to interpret and understand the dynamics of early sensory processing in a variety of physiological experiments and yields novel predictions regarding the relation between activity and stimulus statistics.

The signal and resolution during in vivo imaging of the mouse brain is limited by sample-induced optical aberrations. We find that, although the optical aberrations can vary across the sample and increase in magnitude with depth, they remain stable for hours. As a result, two-photon adaptive optics can recover diffraction-limited performance to depths of 450 μm and improve imaging quality over fields of view of hundreds of microns. Adaptive optical correction yielded fivefold signal enhancement for small neuronal structures and a threefold increase in axial resolution. The corrections allowed us to detect smaller neuronal structures at greater contrast and also improve the signal-to-noise ratio during functional Ca(2+) imaging in single neurons.

Aberrations and random scattering severely limit optical imaging in deep tissue. Adaptive optics can in principle drastically extend the penetration depth and improve the image quality. However, for random scattering media a large number of spatial modes need to be measured and controlled to restore a diffraction limited focus. Here, we present a parallel wavefront optimization method using backscattered light as a feedback. Spatial confinement of the feedback signal is realized with a confocal pinhole and coherence gating. We show in simulations and experiments that this approach enables focusing deep into tissue over up to six mean scattering path lengths. Experimentally the technique was tested on tissue phantoms and fixed brain slices.

Electronic and biological systems both perform complex information processing, but they use very different techniques. Though electronics has the advantage in raw speed, biological systems have the edge in many other areas. They can be produced, and indeed self-reproduce, without expensive and finicky factories. They are tolerant of manufacturing defects, and learn and adapt for better performance. In many cases they can self-repair damage. These advantages suggest that biological systems might be useful in a wide variety of tasks involving information processing. So far, all attempts to use the nervous system of a living organism for information processing have involved selective breeding of existing organisms. This approach, largely independent of the details of internal operation, is used since we do not yet understand how neural systems work, nor exactly how they are constructed. However, as our knowledge increases, the day will come when we can envision useful nervous systems and design them based upon what we want them to do, as opposed to variations on what has been already built. We will then need tools, corresponding to our Electronic Design Automation tools, to help with the design. This paper is concerned with what such tools might look like.

Somatic sexual dimorphisms outside of the nervous system in Drosophila melanogaster are largely controlled by the male- and female-specific Doublesex transcription factors (DSX(M) and DSX(F), respectively). The DSX proteins must act at the right times and places in development to regulate the diverse array of genes that sculpt male and female characteristics across a variety of tissues. To explore how cellular and developmental contexts integrate with doublesex (dsx) gene function, we focused on the sexually dimorphic number of gustatory sense organs (GSOs) in the foreleg. We show that DSX(M) and DSX(F) promote and repress GSO formation, respectively, and that their relative contribution to this dimorphism varies along the proximodistal axis of the foreleg. Our results suggest that the DSX proteins impact specification of the gustatory sensory organ precursors (SOPs). DSX(F) then acts later in the foreleg to regulate gustatory receptor neuron axon guidance. These results suggest that the foreleg provides a unique opportunity for examining the context-dependent functions of DSX.

Generating diverse neurons in the central nervous system involves three major steps. First, heterogeneous neural progenitors are specified by positional cues at early embryonic stages. Second, neural progenitors sequentially produce neurons or intermediate precursors that acquire different temporal identities based on their birth-order. Third, sister neurons produced during asymmetrical terminal mitoses are given distinct fates. Determining the molecular mechanisms underlying each of these three steps of cellular diversification will unravel brain development and evolution. Drosophila has a relatively simple and tractable CNS, and previous studies on Drosophila CNS development have greatly advanced our understanding of neuron fate specification. Here we review those studies and discuss how the lessons we have learned from fly teach us the process of neuronal diversification in general.

The molecular mechanism responsible for capturing, sorting and retrieving vesicle membrane proteins following triggered exocytosis is not understood. Here we image the post-fusion release and then capture of a vesicle membrane protein, the vesicular acetylcholine transporter, from single vesicles in living neuroendocrine cells. We combine these measurements with super-resolution interferometric photo-activation localization microscopy and electron microscopy, and modelling to map the nanometer-scale topography and architecture of the structures responsible for the transporter’s capture following exocytosis. We show that after exocytosis, the transporter rapidly diffuses into the plasma membrane, but most travels only a short distance before it is locally captured over a dense network of membrane-resident clathrin-coated structures. We propose that the extreme density of these structures acts as a short-range diffusion trap. They quickly sequester diffusing vesicle material and limit its spread across the membrane. This system could provide a means for clathrin-mediated endocytosis to quickly recycle vesicle proteins in highly excitable cells.

Dendritic ion channels play a critical role in shaping synaptic input and are fundamentally important for synaptic integration and plasticity. In the hippocampal region CA1, somato-dendritic gradients of AMPA receptors and the hyperpolarization-activated cation conductance (I(h)) counteract the effects of dendritic filtering on the amplitude, time-course, and temporal integration of distal Schaffer collateral (SC) synaptic inputs within stratum radiatum (SR). While ion channel gradients in CA1 distal apical trunk dendrites within SR have been well characterized, little is known about the patterns of ion channel expression in the distal apical tuft dendrites within stratum lacunosum moleculare (SLM) that receive distinct input from the entorhinal cortex via perforant path (PP) axons. Here, we measured local ion channels densities within these distal apical tuft dendrites to determine if the somato-dendritic gradients of I(h) and AMPA receptors extend into distal tuft dendrites. We also determined the densities of voltage-gated sodium channels and NMDA receptors. We found that the densities of AMPA receptors, I(h,) and voltage-gated sodium channels are similar in tuft dendrites in SLM when compared with distal apical dendrites in SR, while the ratio of NMDA receptors to AMPA receptors increases in tuft dendrites relative to distal apical dendrites within SR. These data indicate that the somato-dendritic gradients of I(h) and AMPA receptors in apical dendrites do not extend into the distal tuft, and the relative densities of voltage-gated sodium channels and NMDA receptors are poised to support nonlinear integration of correlated SC and PP input.

Wikipedia, the online encyclopedia, is the most famous wiki in use today. It contains over 3.7 million pages of content; with many pages written on scientific subject matters that include peer-reviewed citations, yet are written in an accessible manner and generally reflect the consensus opinion of the community. In this, the 19th Annual Database Issue of Nucleic Acids Research, there are 11 articles that describe the use of a wiki in relation to a biological database. In this commentary, we discuss how biological databases can be integrated with Wikipedia, thereby utilising the pre-existing infrastructure, tools and above all, large community of authors (or Wikipedians). The limitations to the content that can be included in Wikipedia are highlighted, with examples drawn from articles found in this issue and other wiki-based resources, indicating why other wiki solutions are necessary. We discuss the merits of using open wikis, like Wikipedia, versus other models, with particular reference to potential vandalism. Finally, we raise the question about the future role of dedicated database biocurators in context of the thousands of crowdsourced, community annotations that are now being stored in wikis.