Volume 10 Issue 6, June 2013

New features are added to a neuron-painting toolbox that could contribute to the recently announced US brain-mapping initiative.

Choose distinct symbols that overlap without ambiguity and communicate relationships in data.

Two independent groups identify factors that drive direct conversion to oligodendrocyte precursor cells in the rodent.

Two independently controlled regulators modulate the output in amplifying Boolean logic gates.

Researchers use networked porous metal complexes as crystalline 'sponges' that absorb and orient small molecules for X-ray crystallography.

Machine learning and imaging show what the dreaming brain sees.

A polymer 'nano-suit' allows living organisms to survive the harsh conditions of scanning electron microscopy.

Locating the final oxidation products of methylated cytosine by enrichment and sequencing reveals that DNA demethylation is common across the genome.

Two reports demonstrate further advances in the use of nitrogen vacancies for very different imaging applications.

Progress in genomics offers researchers many new reasons to expand the universe of organisms they study.

Two reports describing the use of direct-conversion electron detectors and algorithms that correct for beam-induced sample motion in single-particle electron cryomicroscopy demonstrate that this technique can solve structures of macromolecules at near-atomic resolution.

An approach for analyzing gene expression data identifies putative lineage-specifying transcription factors that may prove useful in cellular reprogramming.

In this Historical Perspective, we ask what information is needed beyond connectivity diagrams to understand the function of nervous systems. Informed by invertebrate circuits whose connectivities are known, we highlight the importance of neuronal dynamics and neuromodulation, and the existence of parallel circuits. The vertebrate retina has these features in common with invertebrate circuits, suggesting that they are general across animals. Comparisons across these systems suggest approaches to study the functional organization of large circuits based on existing knowledge of small circuits.

New methods for mapping synaptic connections and recording neural signals generate rich and complex data on the structure and dynamics of brain networks. Making sense of these data will require a concerted effort directed at data analysis and reduction as well as computational modeling.

Opinions diverge on whether mapping the synaptic connectivity of the brain is a good idea. Here we argue that albeit their limitations, such maps will reveal essential characteristics of neural circuits that would otherwise be inaccessible.

Neuronal networks are high-dimensional graphs that are packed into three-dimensional nervous tissue at extremely high density. Comprehensively mapping these networks is therefore a major challenge. Although recent developments in volume electron microscopy imaging have made data acquisition feasible for circuits comprising a few hundreds to a few thousands of neurons, data analysis is massively lagging behind. The aim of this Perspective is to summarize and quantify the challenges for data analysis in cellular-resolution connectomics and describe current solutions involving online crowd-sourcing and machine-learning approaches.

With potential relevance for brain-mapping work, hydrogel-based structures can now be built from within biological tissue to allow subsequent removal of lipids without mechanical disassembly of the tissue. This process creates a tissue-hydrogel hybrid that is physically stable, that preserves fine structure, proteins and nucleic acids, and that is permeable to both visible-spectrum photons and exogenous macromolecules. Here we highlight relevant challenges and opportunities of this approach, especially with regard to integration with complementary methodologies for brain-mapping studies.

The beginning of the 21st century has seen a renaissance in light microscopy and anatomical tract tracing that together are rapidly advancing our understanding of the form and function of neuronal circuits. The introduction of instruments for automated imaging of whole mouse brains, new cell type–specific and trans-synaptic tracers, and computational methods for handling the whole-brain data sets has opened the door to neuroanatomical studies at an unprecedented scale. We present an overview of the present state and future opportunities in charting long-range and local connectivity in the entire mouse brain and in linking brain circuits to function.

At macroscopic scales, the human connectome comprises anatomically distinct brain areas, the structural pathways connecting them and their functional interactions. Annotation of phenotypic associations with variation in the connectome and cataloging of neurophenotypes promise to transform our understanding of the human brain. In this Review, we provide a survey of magnetic resonance imaging–based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry and emphasize the importance of integrating structural and functional perspectives on brain architecture.

An improved Brainbow toolbox for expression in the mouse is presented in this Resource. The collection includes transgenic lines, plasmids and viral vectors with improved performance and added capabilities relative to the original Brainbow constructs.

Contact spotting with standard microarray printing tools can be used to generate high-density arrays of living mammalian cells, permitting the arraying of cell libraries without complex fluid manipulation.

Treatment with DMSO improves the differentiation of multiple human pluripotent stem cell lines into cells of all three germ layers.

A method for computing the intrinsic resolution of a super-resolution image that accounts for localization uncertainty, labeling density and image anisotropy is described. This work extends and builds on the Fourier ring correlation method used in cryoelectron microscopy.

Unlike hybrid approaches that use multiple libraries for de novo assembly, the hierarchical genome-assembly process uses data from only a single long-read SMRT sequencing library to produce high-quality finished microbial genome or BAC assemblies in an automated workflow.

With a multiplexed, sensitive, selected reaction monitoring–based mass spectrometry approach, transcription factor copy numbers can be accurately quantified during terminal fat cell differentiation.

A method to measure reversals in gene expression between cell types is used to identify transcriptional regulators important for lineage specification. The approach should help identify putative factors for direct fate conversion.

The combination of a direct electron-detection camera that can count individual electrons and an algorithm for correcting for beam-induced motion in cryo-EM will facilitate determination of three-dimensional structures of smaller, lower-symmetry macromolecular complexes to higher resolution than previously possible.

We are entering a new era in the neurosciences, in which development of technology will be in the spotlight. In this Focus, experts outline the different technologies needed to obtain anatomical and functional brain maps across species, and discuss the importance of assembling these maps and what will be needed beyond them, to understand the functioning of the brain.