Inducible and reversible perturbation of the activity of selected neurons in vivo is critical to understanding the dynamics of brain circuits. Several genetically encoded systems for rapid inducible neuronal silencing have been developed in the past few years offering an arsenal of tools for in vivo experiments. Some systems are based on ion-channels or pumps, others on G protein coupled receptors, and yet others on modified presynaptic proteins. Inducers range from light to small molecules to peptides. This diversity results in differences in the various parameters that may determine the applicability of each tool to a particular biological question. Although further development would be beneficial, the current silencing tool kit already provides the ability to make specific perturbations of circuit function in behaving animals.

Cell and tissue specific gene expression is a defining feature of embryonic development in multi-cellular organisms. However, the range of gene expression patterns, the extent of the correlation of expression with function, and the classes of genes whose spatial expression are tightly regulated have been unclear due to the lack of an unbiased, genome-wide survey of gene expression patterns.

Staining the mRNA of a gene via in situ hybridization (ISH) during the development of a D. melanogaster embryo delivers the detailed spatio-temporal pattern of expression of the gene. Many biological problems such as the detection of co-expressed genes, co-regulated genes, and transcription factor binding motifs rely heavily on the analyses of these image patterns. The increasing availability of ISH image data motivates the development of automated computational approaches to the analysis of gene expression patterns.

Cortical maps, consisting of orderly arrangements of functional columns, are a hallmark of the organization of the cerebral cortex. However, the microorganization of cortical maps at the level of single neurons is not known, mainly because of the limitations of available mapping techniques. Here, we used bulk loading of Ca(2+) indicators combined with two-photon microscopy to image the activity of multiple single neurons in layer (L) 2/3 of the mouse barrel cortex in vivo. We developed methods that reliably detect single action potentials in approximately half of the imaged neurons in L2/3. This allowed us to measure the spiking probability following whisker deflection and thus map the whisker selectivity for multiple neurons with known spatial relationships. At the level of neuronal populations, the whisker map varied smoothly across the surface of the cortex, within and between the barrels. However, the whisker selectivity of individual neurons recorded simultaneously differed greatly, even for nearest neighbors. Trial-to-trial correlations between pairs of neurons were high over distances spanning multiple cortical columns. Our data suggest that the response properties of individual neurons are shaped by highly specific subcolumnar circuits and the momentary intrinsic state of the neocortex.

This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Correcting Output Coding (ECOC), which uses a code matrix to decompose a multi-class problem into multiple binary problems. ECOC for multi-class classification hinges on the design of the code matrix. We propose to explore the distribution of data classes and optimize both the composition and the number of base learners to design an effective and compact code matrix. Two real world applications are studied: (1) the holistic recognition (i.e., recognition without segmentation) of touching handwritten numeral pairs and (2) the classification of cancer tissue types based on microarray gene expression data. The results show that the proposed DECOC is able to deliver competitive accuracy compared with other ECOC methods, using parsimonious base learners than the pairwise coupling (one-vs-one) decomposition scheme. With a rejection scheme defined by a simple robustness measure, high reliabilities of around 98% are achieved in both applications.

In CA1 pyramidal neurons, burst firing is correlated with hippocampally dependent behaviours and modulation of synaptic strength. One of the mechanisms underlying burst firing in these cells is the afterdepolarization (ADP) that follows each action potential. Previous work has shown that the ADP results from the interaction of several depolarizing and hyperpolarizing conductances located in the soma and the dendrites. By using patch-clamp recordings from acute rat hippocampal slices we show that D-type potassium current modulates the size of the ADP and the bursting of CA1 pyramidal neurons. Sensitivity to alpha-dendrotoxin suggests that Kv1-containing potassium channels mediate this current. Dual somato-dendritic recording, outside-out dendritic recordings, and focal application of dendrotoxin together indicate that the channels mediating this current are located in the apical dendrites. Thus, our data present evidence for a dendritic segregation of Kv1-like channels in CA1 pyramidal neurons and identify a novel action for these channels, showing that they inhibit action potential bursting by restricting the size of the ADP.

The functions of cortical areas depend on their inputs and outputs, but the detailed circuits made by long-range projections are unknown. We show that the light-gated channel channelrhodopsin-2 (ChR2) is delivered to axons in pyramidal neurons in vivo. In brain slices from ChR2-expressing mice, photostimulation of ChR2-positive axons can be transduced reliably into single action potentials. Combining photostimulation with whole-cell recordings of synaptic currents makes it possible to map circuits between presynaptic neurons, defined by ChR2 expression, and postsynaptic neurons, defined by targeted patching. We applied this technique, ChR2-assisted circuit mapping (CRACM), to map long-range callosal projections from layer (L) 2/3 of the somatosensory cortex. L2/3 axons connect with neurons in L5, L2/3 and L6, but not L4, in both ipsilateral and contralateral cortex. In both hemispheres the L2/3-to-L5 projection is stronger than the L2/3-to-L2/3 projection. Our results suggest that laminar specificity may be identical for local and long-range cortical projections.

On August 1, 2006 the Howard Hughes Medical Institute's first stand-alone research campus opened at Janelia Farm, near Washington DC. Our mission at Janelia is to do exceptional fundamental research. Our two scientific foci are to understand the function of neural circuits and to develop synergistic imaging technologies. To achieve this we have changed many of the conventions of academic and/or industrial science. The founding director at Janelia is the well-known Drosophilist Gerry Rubin, who has been a central figure in fly molecular, developmental and genomic biology in recent decades. Not coincidentally, we at Janelia fully appreciate the potential of flies to contribute to an understanding of neuronal circuits. Our objectives are ambitious, and in the first ten months of operations at Janelia we have made some good beginnings.

In conventional biological imaging, diffraction places a limit on the minimal xy distance at which two marked objects can be discerned. Consequently, resolution of target molecules within cells is typically coarser by two orders of magnitude than the molecular scale at which the proteins are spatially distributed. Photoactivated localization microscopy (PALM) optically resolves selected subsets of protect fluorescent probes within cells at mean separations of <25 nanometers. It involves serial photoactivation and subsequent photobleaching of numerous sparse subsets of photoactivated fluorescent protein molecules. Individual molecules are localized at near molecular resolution by determining their centers of fluorescent emission via a statistical fit of their point-spread-function. The position information from all subsets is then assembled into a super-resolution image, in which individual fluorescent molecules are isolated at high molecular densities. In this paper, some of the limitations for PALM imaging under current experimental conditions are discussed.

Automatic segmentation of nuclei in 3D microscopy images is essential for many biological studies including high throughput analysis of gene expression level, morphology, and phenotypes in single cell level. The complexity and variability of the microscopy images present many difficulties to the traditional image segmentation methods. In this paper, we present a new method based on 3D watershed algorithm to segment such images. By using both the intensity information of the image and the geometry information of the appropriately detected foreground mask, our method is robust to intensity fluctuation within nuclei and at the same time sensitive to the intensity and geometrical cues between nuclei. Besides, the method can automatically correct potential segmentation errors by using several post-processing steps. We tested this algorithm on the 3D confocal images of C.elegans, an organism that has been widely used in biological studies. Our results show that the algorithm can segment nuclei in high accuracy despite the non-uniform background, tightly clustered nuclei with different sizes and shapes, fluctuated intensities, and hollow-shaped staining patterns in the images.