Visual receptive field properties of feature detecting neurons in the dragonfly

The dragonfly, (Aeshna, Anax) which feeds on small flying insects, requires a visual system capable of signaling the movements of airborne prey. A group of 8 descending feature detectors in the dragonfly are tuned exclusively to moving contrasting objects. These target-selective descending neurons project from the brain to the thoracic ganglia. Their activity drives steering movement of the wings.In this study, we recorded target-selective descending neuron activity intracellularly.To define their receptive fields, we recorded responses to the movement of black square targets projected onto a screen in front of the animal. Each neuron was identified by dye injection.Target-selective descending neurons exhibit several receptive field properties. Our results show that they are strongly directionally selective. Two TSDNs, exclusively tuned to small targets, have receptive fields restricted to visual midline. Others, which are not selective for target size, have asymmetric receptive fields centered laterally.We suggest that the behavioral function of these specialized feature detectors is to steer the dragonfly during prey-tracking so as to fix the position of the prey image on the retina. If the dragonfly maintains a constant visual bearing to its prey over time it will intercept its prey.Abbreviations TSDN target-selective descending neuron - DCMD descending contralateral movement detector - MDT median dorsal tract - DIT dorsal intermediate tract - VNC ventral nerve cord     

Chromosomal regions in prostatic carcinomas studied by comparative genomic hybridization, hierarchical cluster analysis and self-organizing feature maps.

Comparative genomic hybridization (CGH) is an established genetic method which enables a genome-wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that place. Therefore, large amounts of data quickly accumulate which must be put into a logical order. Cluster analysis can be used to assign individual cases (samples) to different clusters of cases, which are similar and where each cluster may be related to a different tumour biology. Another approach consists in a clustering of chromosomal regions by rewriting the original data matrix, where the cases are written as rows and the chromosomal regions as columns, in a transposed form. In this paper we applied hierarchical cluster analysis as well as two implementations of self-organizing feature maps as classical and neuronal tools for cluster analysis of CGH data from prostatic carcinomas to such transposed data sets. Self-organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule. We studied a group of 48 cases of incidental carcinomas, a tumour category which has not been evaluated by CGH before. In addition we studied a group of 50 cases of pT2N0-tumours and a group of 20 pT3N0-carcinomas. The results show in all case groups three clusters of chromosomal regions, which are (i) normal or minimally affected by losses and gains, (ii) regions with many losses and few gains and (iii) regions with many gains and few losses. Moreover, for the pT2N0- and pT3N0-groups, it could be shown that the regions 6q, 8p and 13q lay all on the same cluster (associated with losses), and that the regions 9q and 20q belonged to the same cluster (associated with gains). For the incidental cancers such clear correlations could not be demonstrated.     

A theory for the development of feature detecting cells in visual cortex

Passive modification of the strength of synaptic junctions that results in the construction of internal mappings with some of the properties of memory is shown to lead to the development of Hubel-Wiesel type feature detectors in visual cortex. With such synaptic modification a cortical cell can become committed to an arbitrary but repeated external pattern, and thus fire every time the pattern is presented even if that cell has no genetic pre-disposition to respond to the particular pattern. The additional assumption of lateral inhibition between cortical cells severely limits the number of cells which respond to one pattern as well as the number of patterns that are picked up by a cell. The introduction of a simple neural mapping from the visual field to the lateral geniculate leads to an interaction between patterns which, combined with our assumptions above, seems to lead to a progression of patterns from column to column of the type observed by Hubel and Wiesel in monkey.     

Mathematical theory on formation of category detecting nerve cells

The nerve cells are believed to have such ability of self-organization that, given a number of input patterns, each cell tunes itself to become responsive to only one of the patterns, or to one subset of patterns having some features in common. The detectors of patterns or pattern subsets are formed in this manner. A simple but plausible mechanism of self-organization is proposed based on the two hypotheses: 1) Synaptic modification process is non-linear, activated when the output of a cell is positive. 2) Not only excitatory but also inhibitory synapses are modifiable. A rigorous mathematical analysis is given to elucidate the characteristics of modifiable synapses to form these detectors. The present model fits well most of the experiments on the developmental plasticity of the visual cortex such as the formation of orientation detecting cells, monocular and alternate monocular deprivation in normal and abnormal environments.     

Spatially segregated SNARE protein interactions in living fungal cells

The machinery for trafficking proteins through the secretory pathway is well conserved in eukaryotes, from fungi to mammals. We describe the isolation of the snc1, sso1, and sso2 genes encoding exocytic SNARE proteins from the filamentous fungus Trichoderma reesei. The localization and interactions of the T. reesei SNARE proteins were studied with advanced fluorescence imaging methods. The SSOI and SNCI proteins co-localized in sterol-independent clusters on the plasma membrane in subapical but not apical hyphal regions. The vesicle SNARE SNCI also localized to the apical vesicle cluster within the Spitzenk?rper of the growing hyphal tips. Using fluorescence lifetime imaging microscopy and Foerster resonance energy transfer analysis, we quantified the interactions between these proteins with high spatial resolution in living cells. Our data showed that the site of ternary SNARE complex formation between SNCI and SSOI or SSOII, respectively, is spatially segregated. SNARE complex formation could be detected between SNCI and SSOI in subapical hyphal compartments along the plasma membrane, but surprisingly, not in growing hyphal tips, previously thought to be the main site of exocytosis. In contrast, SNCI.SSOII complexes were found exclusively in growing apical hyphal compartments. These findings demonstrate spatially distinct sites of plasma membrane SNARE complex formation in fungi and the existence of multiple exocytic SNAREs, which are functionally and spatially segregated. This is the first demonstration of spatially regulated SNARE interactions within the same membrane.     

Merging regions across feature maps in texture segmentation

This paper describes segmentation phenomena of superimposed textures and the Linking phenomena. These phenomena provide us with information about the mechanism of a late stage of segmenting textures. The late stage takes place after the segmentation process forms regions in feature maps such that parameter values in one region are substantially different from those in the neighboring regions. At the stage, the segmentation process merges the regions across the feature maps to determine output regions by integrating information about how the regions occupy two-dimensional space. The segmentation process gets such information both from local areas and from areas far away from the local areas where it determines the output regions and boundaries.     

Modelling of batch fermentation and estimation of state variables using self-organizing feature maps

Summary A self-organizing feature map was used for modelling of batch yeast cultures. The model was constructed by training the neural network with experimental data of the specific rates. Estimates of state variables were obtained from the neural network model and differential mass balance equations via integration. They were compared with the experimental data. The neural network model showed a good modelling accuracy and interpolation capability.     

Potentially functional regions of nucleic acids recognized by a Kohonen's self-organizing map

Computer recognition of short frnctional sites on DNA, suchas promoter regions or intron—exon boundaries, has recentlyattracted much interest. In this paper we have focused our attentionon the automatic recognition of relevant features of human nucleicacid sequences by means of an unsupervised artificial neuralnetwork model. Sixty messenger RNA and 31 genomic DNA sequenceswere analysed. The results showed that in mRNA, the minimalsimilarity 60 base pattern was guanine-and cytosine-rich andlocated in most sequences in a range of 250 bases from eitherthe middle point of the signal peptide coding region or fromthe start of the coding region. On DNA sequences a region definedby a cluster of minimal similarity patterns was present in manyof the analysed genes. This zone may be related to alternativesplicing and DNA methylation.     

Model of neural visual system with self-organizing cells

This paper describes a model of a neural visual system of a higher animal, in which the capability of pattern recognition develops adaptively. To produce the adaptability, we adopted self-organizing cells, and with them modeled feature-detecting cells which were discovered by Hubel and Wiesel and whose plasticity was found by Blakemore and Cooper. Combining the self-organizing cells and the learning principle of a Perceptron-type system, we constructed a model of the whole visual system. The model is also equipped with an eye movement control mechanism for gazing, which reduces the number of selforganizing cells required for pattern recognition, thus contributing to their quick self-organization. Computer simulation and an experiment using a hardware simulator showed that self-organizing cells quickly become sensitive to the features often seen and that the resulted system can classify patterns with a rather small number of feature-detecting cells.     

Formation of the transverse nerve in moth embryos : I. A scaffold of nonneuronal cells prefigures the nerve

We have studied the embryonic development of the transverse nerve (TN), an unpaired segmental nerve of the moth Manduca sexta. Two identified motor neurons and 16 identified neuroendocrine neurons project axons within the larval TN; therefore, the TN is both a peripheral nerve and a neurohaemal organ. At 33% of embryogenesis, and prior to the arrival of any neuronal growth cones, the position, shape, and trajectory of the TN are anticipated by two groups of nonneuronal cells that we call the strap and the bridge. At this time the strap and the bridge together consist of approximately 100 cells, all of which express a cell surface epitope recognized by the monoclonal antibody TN-1. As development proceeds, both the number of nonneuronal cells within the strap and the bridge and the fraction that expresses the TN-1 antigen(s) decrease. Moreover, individual cells within the strap become morphologically identifiable before the arrival of the neuronal growth cones. Most of the axons that project to the TN also express the TN-1 antigen(s) during their period of outgrowth. The two motor neuron growth cones are the first to reach the environment of the strap and the bridge, doing so at approximately 37%; having encountered these cellular structures, the growth cones restrict their navigation to this preexisting scaffolding, until they reach their muscle target. The neuroendocrine growth cones arrive later and also grow within the confines of the strap and the bridge (J.N. Carr and P.H. Taghert, 1988, Dev. Biol, 130, 500-512). In this first paper we describe the development of the strap and the bridge, and the interactions of the motor neuron growth cones with these structures. The observations are novel in documenting the extent and precision to which a peripheral nerve pathway is prefigured by a contiguous assemblage of nonneuronal cells.     

Application of Kohonen's self-organizing feature map algorithm to cortical maps of orientation and direction preference

Cortical maps of orientation preference in cats, ferrets and monkeys contain numerous half-rotation point singularities. Experimental data have shown that direction preference also has a smooth representation in these maps, with preferences being for the most part orthogonal to the axis of preferred orientation. As a result, the orientation singularities induce an extensive set of linear fractures in the direction map. These fractures run between and connect nearby point orientation singularities. Their existence appears to pose a puzzle for theories that postulate that cortical maps maximize continuity of representation, because the fractures could be avoided if the orientation map contained full-rotation singularities. Here we show that a dimension-reduction model of cortical map formation, which implements principles of continuity and completeness, produces an arrangement of linear direction fractures connecting point orientation singularities which is similar to that observed experimentally. We analyse the behaviour of this model and suggest reasons why the model maps contain half-rotation rather than full-rotation orientation singularities.     

A new algorithm for detecting low-complexity regions in protein sequences

MOTIVATION: Pair-wise alignment of protein sequences and local similarity searches produce many false positives because of compositionally biased regions, also called low-complexity regions (LCRs), of amino acid residues. Masking and filtering such regions significantly improves the reliability of homology searches and, consequently, functional predictions. Most of the available algorithms are based on a statistical approach. We wished to investigate the structural properties of LCRs in biological sequences and develop an algorithm for filtering them. RESULTS: We present an algorithm for detecting and masking LCRs in protein sequences to improve the quality of database searches. We developed the algorithm based on the complexity analysis of subsequences delimited by a pair of identical, repeating subsequences. Given a protein sequence, the algorithm first computes the suffix tree of the sequence. It then collects repeating subsequences from the tree. Finally, the algorithm iteratively tests whether each subsequence delimited by a pair of repeating subsequences meets a given criteria. Test results with 1000 proteins from 20 families in Pfam show that the repeating subsequences are a good indicator for the low-complexity regions, and the algorithm based on such structural information strongly compete with others. AVAILABILITY: http://bioinfo.knu.ac.kr/research/CARD/ CONTACT: swshin@bioinfo.knu.ac.kr     

Chromosome constitution of in vitro segregated haploid and diploid cells of the mouse

The composition in segregated haploid sets of paternal and maternal chromosomes has been studied in order to verify whether their composition is uniparental of mixed, fixed or variable. Primary cultures where prepared using kidneys from hybrids of strains of Mus musculus in which the parental chromosomes are distinguishable; the maternal set consists of 20 teleocentric chromosomes, the paternal set of 9 metacentric chromosomes, derived by Robertsonian fusion and 2 telocentrics. Applying Seabright's banding technique, an analysis of segregated haploid and diploid cells, which have originated spontaneously through polyploidisation-segregation processes was carried out. It was concluded that the haploid sets have a variable composition of paternal and maternal chromosomes.     

Cytochemical and ultrastructural studies on normal and segregated nucleoli in meristematic cells

Summary The location of the two nucleolar components, in meristematic root tip cells ofAllium cepa has been studied. The segregation of granular and fibrous components of the nucleoli was induced by adenosine-3deoxyriboside. The relationship between the ultrastructure and the stain affinities of both nucleolar regions has been determined by using different selective nucleolar stains.The pars fibrosa appears positive in the silver, lead, zinc, and methylen blue stains and shows a high ATPase activity.     

Molecular feature of the nerve growth factor in human serum

High molecular weight binding components which bind [¹²⁵I] mouse β nerve growth factor exist in human serum. The binding of β nerve growth factor to the serum components was inhibited at alkaline condition. After gel filtration of human serum on a Sephadex G-150 column at neutral condition, the nerve growth factor-like immunoreactivity was observed in only one peak, differing from the high molecular weight serum components. However, at alkaline condition two peaks with nerve growth factor-like immunoreactivity appeared; one was almost at the position observed at neutral pH, and the other was a new peak eluted approximately to the column volume. these results suggest that there are at least two nerve growth factor-like molecules in human serum and most of the nerve growth factor in the serum exists in a complex form associated with serum components with high molecular weight.