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.

C. elegans, a roundworm in soil is widely used in studying animal development and aging, cell differentiation, etc. Recentlv, high-resolution fluorescence images of C. elegans have become available, introducing several new image analysis applications. One problem is that worm bodies usually curve greatly in images, thus it is highly desired to straighten worms so that they can be compared easily under the same canonical coordinate system. We develop a worm straightening algorithm (WSA) using a cutting-plane restacking method, which aggregates the linear rotation transforms of a continuous sequence of cutting lines/planes orthogonal to the "backbone" of a worm to best approximate the nonlinearly bended worm body. We formulate the backbone as a parametric form of cubic spline of a series of control points. We develop two minimum-spanning-tree based methods to automatically determine the locations of control points. Our experimental methods show that our approach can effectively straighten both 2D and 3D worm images.

When searching sequence databases for RNAs, it is desirable to score both primary sequence and RNA secondary structure similarity. Covariance models (CMs) are probabilistic models well-suited for RNA similarity search applications. However, the computational complexity of CM dynamic programming alignment algorithms has limited their practical application. Here we describe an acceleration method called query-dependent banding (QDB), which uses the probabilistic query CM to precalculate regions of the dynamic programming lattice that have negligible probability, independently of the target database. We have implemented QDB in the freely available Infernal software package. QDB reduces the average case time complexity of CM alignment from LN(2.4) to LN(1.3) for a query RNA of N residues and a target database of L residues, resulting in a 4-fold speedup for typical RNA queries. Combined with other improvements to Infernal, including informative mixture Dirichlet priors on model parameters, benchmarks also show increased sensitivity and specificity resulting from improved parameterization.

Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.

CA1 pyramidal neurons from animals that have acquired hippocampal tasks show increased neuronal excitability, as evidenced by a reduction in the postburst afterhyperpolarization (AHP). Studies of AHP plasticity require stable long-term recordings, which are affected by the intracellular solutions potassium methylsulphate (KMeth) or potassium gluconate (KGluc). Here we show immediate and gradual effects of these intracellular solutions on measurement of the AHP and basic membrane properties, and on the induction of AHP plasticity in CA1 pyramidal neurons from rat hippocampal slices. The AHP measured immediately after establishing whole-cell recordings was larger with KMeth than with KGluc. In general, the AHP in KMeth was comparable to the AHP measured in the perforated-patch configuration. However, KMeth induced time-dependent changes in the intrinsic membrane properties of CA1 pyramidal neurons. Specifically, input resistance progressively increased by 70% after 50 min; correspondingly, the current required to trigger an action potential and the fast afterdepolarization following action potentials gradually decreased by about 50%. Conversely, these measures were stable in KGluc. We also demonstrate that activity-dependent plasticity of the AHP occurs with physiologically relevant stimuli in KGluc. AHPs triggered with theta-burst firing every 30 s were progressively reduced, whereas AHPs elicited every 150 s were stable. Blockade of the apamin-sensitive AHP current (I(AHP)) was insufficient to block AHP plasticity, suggesting that plasticity is manifested through changes in the apamin-insensitive slow AHP current (sI(AHP)). These changes were observed in the presence of synaptic blockers, and therefore reflect changes in the intrinsic properties of the neurons. However, no AHP plasticity was observed using KMeth. In summary, these data show that KMeth produces time-dependent changes in basic membrane properties and prevents or obscures activity-dependent reduction of the AHP. In whole-cell recordings using KGluc, repetitive theta-burst firing induced AHP plasticity that mimics learning-related reduction in the AHP.