Vnd/nkx, ind/gsh, and msh/msx: conserved regulators of dorsoventral neural patterning?

Expression of vnd in ventral, ind in intermediate, and msh in dorsal columns of fly neurectoderm, and of homologous gene families in corresponding domains of vertebrate neurectoderm, suggests that elements of dorsoventral neural patterning have been evolutionarily conserved. However, upstream signaling pathways regulating this columnar gene expression pattern appear to have diverged significantly throughout evolution. In addition, while recent loss-of-function studies in flies and mice indicate that these three genes may have a conserved role in regional specification, there is no obvious conservation of the particular cell fates deriving from corresponding domains. The three-column expression pattern may thus represent a developmental mechanism that is more resistant to evolutionary changes than genetic events upstream or downstream of it.     

Relationships between Nest Architecture and Behavior in <Emphasis Type="Italic">Xylocopa virginica</Emphasis> (Hymenoptera: Apidae)

The large carpenter bees nest in reeds, stems and wood. Many other Hymenoptera, including many wasps and some bees, have strong associations between the physical elements of their nests and behavior. Nests of the North American carpenter bee, Xylocopa virginica, were collected in southern Ontario. Nest architecture elements were examined with respect to their impact on life-history elements. In particular, it was determined that the brood cells are provisioned sequentially both within and among branches. There was also no detectable pattern of sex allocation in broods. Nests with branched architecture contained more foundresses, but these foundresses did not appear to contribute in the construction of larger nests. These findings are discussed with respect to other bees, and to the social structure of Xylocopa virginica.     

Synchronization of neural activity is a promising mechanism of memory information processing in networks of columns

Synchronization of the oscillatory discharge of cortical neurons could be a part of the mechanism that is involved in cortical information processing. On the assumption that the basic functional unit is the column composed of local excitatory and inhibitory cells and generating oscillatory neural activity, a network model that attains associative memory function is proposed. The synchronization of oscillation in the model is studied analytically using a sublattice analysis. In particular, the retrieval of a single memory pattern can be studied in the system, which can be derived from the original network model of interacting columns and is formally equivalent to a system of an isolated column. The network model simulated numerically shows a remarkable performance in which retrieval is achieved simultaneously for more than one memory pattern. The manifestations of this simultaneous retrieval in the network dynamics are successive transitions of the network state from a synchronized oscillation for a memory pattern to that for another memory pattern.     

Spatially constrained adaptive rewiring in cortical networks creates spatially modular small world architectures

A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture.     

Modelling of syntactical processing in the cortex

Probably the hardest test for a theory of brain function is the explanation of language processing in the human brain, in particular the interplay of syntax and semantics. Clearly such an explanation can only be very speculative, because there are essentially no animal models and it is hard to study detailed neural processing in humans. The approach presented in this paper uses well established basic neural mechanisms in a plausible global network architecture that is formulated essentially in terms of cortical areas and their intracortical and corticocortical interconnections. The neural implementation of this system shows that the comparatively intricate logical task of understanding semantico-syntactical structures can be mastered by a neural network architecture. The system presented also shows additional context awareness, in particular the model is able to correct ambiguous input to a certain degree, e.g. the input "bot show/lift green wall" with an artificial ambiguity between "show" and "lift" is correctly interpreted as "bot show green wall" since a wall is not liftable. Furthermore, the system is able to learn new object words during runtime.     

On how network architecture determines the dominant patterns of spontaneous neural activity

In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks.     

Development of the swimbladder in the European eel (Anguilla anguilla)

The swimbladder of the adult eel, Anguilla anguilla, with its bipolar countercurrent system, the rete mirabile, is a widely used model for swimbladder function, but very little is known about the development of this swimbladder. Our histological studies on the developing swimbladder revealed that during metamorphosis the swimbladder becomes present as a dorsal outgrowth of the esophagus. It is filled with surfactant, and gas was not detected in the swimbladder. In the young glass-eel, the epithelial (gas gland) cells of the swimbladder are columnar, but do not yet have the typical basolateral labyrinth established in adult animals. Few blood vessels are found in the swimbladder tissue, and the submucosa is present as a thick layer of connective tissue, giving a large diffusion distance between blood vessel and swimbladder lumen. Within the next 2 or 3 months of development, gas gland cells develop their typical basolateral labyrinth, and the thickness of the submucosa is significantly reduced, resulting in a short diffusion distance between blood vessels and the swimbladder lumen. The first filling of the swimbladder with gas is observed while the gas gland cells are still in a poorly differentiated status and it appears unlikely that these cells can accomplish their typical role in gas deposition. The presence of small gas bubbles in the swimbladder as well as in the ductus pneumaticus at the time of initial swimbladder inflation suggests that the swimbladder is filled by air gulping or possibly by taking up gas bubbles from the water.     

三角帆蚌外套膜细胞的超微结构

用透射电镜观察了三角帆蚌(Hyriopsis cumingii Lea)外套膜细胞的超徽结构。外套膜内表皮细胞中,有具纤毛的柱状细胞,顶端具小分泌泡的杯状细胞,胞质中含大分泌泡以及线粒体聚集成群的柱状细胞四类。各类表皮细胞的细胞质电子密度和内含物均有差异。细胞核呈椭圆或棒形。线粒体和高尔基体多分布在细胞核上方细胞的游离端。各类细胞游离表面都密生微绒毛,其中内表皮的柱状细胞还着生有纤毛,但无分泌泡。其余几种表皮细胞在细胞顶部都具有大小不等,电子密度不同的分泌泡。在外表皮中只观察到一般的柱状表皮细胞和胞质中具有成群线粒体的细胞两类。另外,外表皮细胞中具有较多的溶酶体。从三角帆蚌外套膜表皮细胞超微结构来看,内、外表皮都具有分泌和吸收机能。内表皮的纤毛柱状细胞有运动功能,而外表皮细胞有较强的消化吸收功能。     

Growth and differentiation of the larval midgut epithelium during molting in the moth, Manduca sexta

The number of epithelial cells comprising larval midgut of the tobacco hornworm moth, Manduca sexta increases 200-fold in development from the first to the fifth instar. We have examined larvae periodically before and during molting to follow epithelial cell proliferation and differentiation. The midgut epithelium in Manduca sexta consists predominantly of columnar and goblet cells. These are arranged in a characteristic pattern with each goblet cell surrounded by a single layer of 4-6 columnar cells (Hakim et al., (1988)). While undifferentiated basal stem cells are infrequently seen in intermolt larvae, just prior to the period when external signs of molting are visible, their number increases and mitotic figures become common. Proliferation continues for several hours and then these stem cells differentiate following a pattern similar to that seen during embryogenesis (Hakim et al., (1988)). Here, however, the newly differentiating cells become intercalated among the mature differentiated cells already present in the epithelium. Since the pattern of individual goblet cells surrounded by a reticulum of columnar cells is maintained after the addition of new cells, the midgut epithelium of molting larvae appears to be a useful model for studying pattern formation in development.     

Genetic structure of Rhododendron ferrugineum at a wide range of spatial scales

Rhododendron ferrugineum L. (Ericaceae) is a subalpine shrub found throughout the Pyrenees and Alps at elevations of 1600-2200 m. We examined relationships between genetic and geographic distance, using 115 dominant amplified fragment length polymorphism (AFLP) markers to assess genetic structure over a wide range of spatial scales. We sampled 17 sites with distances of 4 km to more than 1000 km between them. At these scales we detected no association between geographic distance and genetic distance between populations. This suggests that genetic drift and gene flow are not in equilibrium for these populations. This pattern could have resulted from recent and rapid postglacial colonization, from more recent human disturbance, or as a function of frequent and random "natural" long-distance colonization. At two of our sites we used transects (two horizontal and two vertical with respect to slope at each site) to sample at distances ranging from 10 m to more than 5000 m. At this scale we observed a positive relationship between genetic and spatial distance along two vertical transects, one at each site. We hypothesize that isolation-by-distance at this smaller scale is a function of restricted gene flow via seed dispersal.     

At the nexus between pattern formation and cell-type specification: the generation of individual neuroblast fates in the Drosophila embryonic central nervous system.

The specification of specific and often unique fates to individual cells as a function of their position within a developing organism is a fundamental process during the development of multicellular organisms. The development of the Drosophila embryonic central nervous system serves as an excellent model system in which to clarify the developmental mechanisms that link pattern formation to cell-type specification. The Drosophila embryonic central nervous system develops from a set of neural stem cells termed neuroblasts. Neuroblasts arise from the ectoderm in an invariant pattern, and each neuroblast acquires a unique fate based on its position within this pattern. Two groups of genes recently have been demonstrated to govern the individual fate specification of neuroblasts. One group, the segment polarity genes, enables neuroblasts that develop in different anteroposterior positions to acquire different fates. The second group, referred to as the columnar genes, ensures that neuroblasts that develop in different dorsoventral domains assume different fates. When integrated, the activities of the segment polarity and columnar genes create a Cartesian coordinate system that bestows unique fates to individual neuroblasts as a function of their position of formation within the ectoderm. BioEssays 1999;21:922-931.     

A checkerboard pattern manifested by the oviduct epithelium of the Japanese quail.

The oviduct epithelium of the Japanese quail is a monolayered epithelium consisting of two types of columnar cells, goblet type gland (G-) cells and ciliated (C-) cells. We found these cells to be arranged in a checkerboard pattern. Three types of cell boundaries formed between the two different types of cells were examined statistically at various levels of the columnar cells. There was a tendency on the part of the cells to form boundaries between G- and C- cells rather than between two C- cells or between two G- cells. We therefore propose that the pattern is constructed under a rule of maximizing the length of boundaries of two different types of cells owing to the fact that theirs is the greatest adhesion capacity. The role of microfilament bundles running along the apical cell boundaries is also discussed. It is suggested that they are in a tense state so as to shorten total length by contraction.     

Flow cytometric analysis and sorting of human endometrial cells after immunocytochemical labeling for cytokeratin using a monoclonal antibody

Endometrial cells in suspension were stained with propidium iodide and a monoclonal antibody against a cytokeratin intermediate filament protein specific for glandular and columnar cells (RGE 53). In this way columnar epithelial cells of the normal endometrium and of adenocarcinomas can be distinguished and separated by flow cytometry from non-epithelial cells (fibroblasts and inflammatory cells) and squamous epithelial cells, all of which are negative for RGE 53. This makes it possible to analyse and also sort pure fractions of this particular tissue type for further studies. The use of propidium iodide allows simultaneous DNA flow cytometry of these columnar epithelial cells. Therefore, the use of antibodies to cytokeratin in combination with propidium iodide can be of help in analyzing and sorting pure fractions of both normal and malignant cells. This allows a more refined examination of complex cell mixtures using flow cytometry.     

Correlations and Functional Connections in a Population of Grid Cells

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern.     

Extremely Dilute Modular Neuronal Networks: Neocortical Memory Retrieval Dynamics

A model of columnar networks of neocortical association areas is studied. The neuronal network is composed of many Hebbian autoassociators, or modules, each of which interacts with a relatively small number of the others, randomly chosen. Any module encodes and stores a number of elementary percepts, or features. Memory items, or patterns, are peculiar combinations of features sparsely distributed over the multi-modular network. Any feature stored in any module can be involved in several of the stored patterns; feature-sharing is in fact source of local ambiguities and, consequently, a potential cause of erroneous memory retrieval spreading through the model network in pattern completion tasks.The memory retrieval dynamics of the large modular autoassociator is investigated by combining mathematical analysis and numerical simulations. An oscillatory retrieval process is proposed that is very efficient in overcoming feature-sharing drawbacks; it requires a mechanism that modulates the robustness of local attractors to noise, and neuronal activity sparseness such that quiescent and active modules are about equally noisy to any post-synaptic module.Moreover, it is shown that statistical correlation between 'kinds' of features across the set of memory patterns can be exploited to obtain a more efficient achievement of memory retrieval capabilities.It is also shown that some spots of the network cannot be reached by retrieval activity spread if they are not directly cued by the stimulus. The locations of these activity isles depend on the pattern to retrieve, while their extension only depends (in large networks) on statistics of inter-modular connections and stored patterns. The existence of activity isles determines an upper-bound to retrieval quality that does not depend on the specific retrieval dynamics adopted, nor on whether feature-sharing is permitted. The oscillatory retrieval process nearly saturates this bound.     

A biogeographic genetic approach for testing the role of reinforcement: the case of Drosophila pseudoobscura and D. persimilis

Abstract.— The role of reinforcement in speciation can be explained by two distinct models. In model I, two diverged populations hybridize and produce fertile hybrids that successfully backcross (hybridization with gene flow). In model II, two populations hybridize but succeeding backcrosses are unproductive (hybridization without gene flow). Using Drosophila persimilis and D. pseudoobscura , we have tested model I by comparing the extent of heterospecific introgression in sympatric versus allopatric populations. We show that certain expectations of this particular model of reinforcement, which is based on hybridization and gene flow between divergent populations after secondary contact, are not realized in these two species. The evidence consists of the similarity of genetic distances as well as proportions of unique/rare alleles between sympatric and allopatric heterospecific populations and a negative correlation between genetic distance and geographical distance between heterospecific populations, which suggests ecological differentiation. This approach in quantifying differential gene flow has important consequences to studies that compare sympatric and allopatric isolation using genetic distance. Following model I, one would expect a pattern of higher prezygotic isolation in sympatric species compared to allopatric species of the same genetic distance simply as a result of an underestimation of genetic distance due to introgression between sympatric populations. We suggest more parsimonious explanations such as reinforcement without genetic exchange (model II) and ecological differentiation, which require high levels of preexisting reproductive isolation between populations.     

Perspective: network-guided pattern formation of neural dynamics

The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain''s network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs or hierarchical network organization) are derived from these deviations. An alternative strategy could be to study deviations of network architectures from regular graphs (rings and lattices) and consider the implications of such deviations for self-organized dynamic patterns on the network. Following this strategy, we draw on the theory of spatio-temporal pattern formation and propose a novel perspective for analysing dynamics on networks, by evaluating how the self-organized dynamics are confined by network architecture to a small set of permissible collective states. In particular, we discuss the role of prominent topological features of brain connectivity, such as hubs, modules and hierarchy, in shaping activity patterns. We illustrate the notion of network-guided pattern formation with numerical simulations and outline how it can facilitate the understanding of neural dynamics.     

Feedforward neural network with adaptive reference pattern layer.

A hybrid neural network architecture is investigated for modeling purposes. The proposed hybrid is based on the multilayer perceptron (MLP) network. In addition to the usual hidden layers, the first hidden layer is selected to be an adaptive reference pattern layer. Each unit in this new layer incorporates a reference pattern that is located somewhere in the space spanned by the input variables. The outputs of these units are the component wise-squared differences between the elements of a reference pattern and the inputs. The reference pattern layer has some resemblance to the hidden layer of the radial basis function (RBF) networks. Therefore the proposed design can be regarded as a sort of hybrid of MLP and RBF networks. The presented benchmark experiments show that the proposed hybrid can provide significant advantages over standard MLPs and RBFs in terms of fast and efficient learning, and compact network structure.