On variability in the density of corticocortical and thalamocortical connections

Variability is an important but neglected aspect of connectional neuroanatomy. The quantitative density of the 'same' corticocortical or thalamocortical connection may vary by over two orders of magnitude between different injections of the same tracer. At present, however, the frequency distribution of connection densities is unknown. Therefore, it is unclear what kind of sampling strategies or statistical methods are appropriate for quantitative studies of connectivity. Nor is it clear if the measured variability represents differences between subjects, or if it is simply a consequence of intra-individual differences resulting from experimental technique and the exact placement of tracers relative to local spatial and laminar variation in connectivity. We used quantitative measurements of the density of a large number of corticocortical and thalamocortical connections from our own laboratories and from the literature. Variability in the density of given corticocortical and thalamocortical connections is high, with the standard deviation of density proportional to the mean. The frequency distribution is close to exponential. Therefore, analysis methods relying on the normal distribution are not appropriate. We provide an appendix that gives simple statistical guidance for samples drawn from exponentially distributed data. For a given corticocortical or thalamocortical connection density, between-individual standard deviation is 0.85 to 1.25 times the within-individual standard deviation. Therefore, much of the variability reported in conventional neuroanatomical studies (with one tracer deposited per animal) is due to within-individual factors. We also find that strong, but not weak, corticocortical connections are substantially more variable than thalamocortical connections. We propose that the near exponential distribution of connection densities is a simple consequence of 'patchy' connectivity. We anticipate that connection data will be well described by the negative binomial, a class of distribution that applies to events occurring in clumped or patchy substrates. Local patchiness may be a feature of all corticocortical connections and could explain why strong corticocortical connections are more variable than strong thalamocortical connections. This idea is supported by the columnar patterns of many corticocortical but few thalamocortical connections in the literature.     

Directed corticocortical functional connectivity at the early stages of serial learning in adults and seven- to eight-year-old children

Serial learning at its earlier stages, presumably involving the working memory, was studied in adults and seven- to eight-year-old children during the reproduction of a sequence of discrete movements following the order specified by a sequence of visual stimuli. In both age groups, the learning curves (latent time vs. trial number) were qualitatively similar in shape. The overall shape of the learning curve depended on the relative proportion of the fast vs. slow phases of latent time reduction. Comparison of the corticocortical functional connectivity patterns in the prestimulus period in the sequence reproduction task vs. the simple visuomotor reaction task showed a general tendency of an increase in the influence of postcentral cortical areas accompanied by the reduced influence of prefrontal and central cortical areas. In particular, it was typical of adults to show an increase in the directed influence of temporo-parieto-occipital (TPO) cortical areas, while the children also showed an increase in the directed influence of the parietal cortex. Comparison of the subgroups with different shapes of learning curves in the prestimulus period has shown the difference in their patterns of directed functional connectivity. The results are discussed with a special emphasis on the role of the working memory retaining the internal representations of sequences being learned.     

Low connectivity and declining genetic variability along a depth gradient in Corallium rubrum populations

This study examines the possible effect of depth on the connectivity and genetic variability in red coral (Corallium rubrum; Octocorallia: Alcyonacea) populations. Patterns of genetic structuring along a depth gradient (from 20 to 70 m) were investigated in two locations of the western Mediterranean coast (northern Catalan and eastern Ligurian Seas) using 10 microsatellite loci. Strong patterns of genetic structuring among the samples were found both within and between the two study sites. In both locations, consistent patterns of reduction in genetic variability along the depth gradient were also observed, suggesting that depth has an important role in determining the patterns of genetic structure in Corallium rubrum. Moreover, a threshold in connectivity was observed among the samples collected across 40–50 m depth, supporting the hypothesis that discrete shallow- and deep-water red coral populations occur. This finding has major implications for management strategies and the conservation of commercially exploited deep red coral populations.     

Proteomics, networks and connectivity indices

Describing the connectivity of chemical and/or biological systems using networks is a straight gate for the introduction of mathematical tools in proteomics. Networks, in some cases even very large ones, are simple objects that are composed at least by nodes and edges. The nodes represent the parts of the system and the edges geometric and/or functional relationships between parts. In proteomics, amino acids, proteins, electrophoresis spots, polypeptidic fragments, or more complex objects can play the role of nodes. All of these networks can be numerically described using the so-called Connectivity Indices (CIs). The transformation of graphs (a picture) into CIs (numbers) facilitates the manipulation of information and the search for structure-function relationships in Proteomics. In this work, we review and comment on the challenges and new trends in the definition and applications of CIs in Proteomics. Emphasis is placed on 1-D-CIs for DNA and protein sequences, 2-D-CIs for RNA secondary structures, 3-D-topographic indices (TPGIs) for protein function annotation without alignment, 2-D-CIs and 3-D-TPGIs for the study of drug-protein or drug-RNA quantitative structure-binding relationships, and pseudo 3-D-CIs for protein surface molecular recognition. We also focus on CIs to describe Protein Interaction Networks or RNA co-expression networks. 2-D-CIs for patient blood proteome 2-DE maps or mass spectra are also covered.     

Uniformity,ideality, and hydrogen bonds in transmembrane alpha-helices

Protein environments substantially influence the balance of molecular interactions that generate structural stability. Transmembrane helices exist in the relatively uniform low dielectric interstices of the lipid bilayer, largely devoid of water and with a very hydrophobic distribution of amino acid residues. Here, through an analysis of bacteriorhodopsin crystal structures and the transmembrane helix structure from M2 protein of influenza A, some helices are shown to be exceptionally uniform in hydrogen bond geometry, peptide plane tilt angle, and backbone torsion angles. Evidence from both the x-ray crystal structures and solid-state NMR structure suggests that the intramolecular backbone hydrogen bonds are shorter than their counterparts in water-soluble proteins. Moreover, the geometry is consistent with a dominance of electrostatic versus covalent contributions to these bonds. A comparison of structure as a function of resolution shows that as the structures become better characterized the helices become much more uniform, suggesting that there is a possibility that many more uniform helices will be observed, even among the moderate resolution membrane protein structures that are currently in the Protein Data Bank that do not show such features.     

Olfactory map formation in the Drosophila brain: genetic specificity and neuronal variability

The development of the Drosophila olfactory system is a striking example of how genetic programs specify a large number of different neuron types and assemble them into functional circuits. To ensure precise odorant perception, each sensory neuron has to not only select a single olfactory receptor (OR) type out of a large genomic repertoire but also segregate its synaptic connections in the brain according to the OR class identity. Specification and patterning of second-order interneurons in the olfactory brain center occur largely independent of sensory input, followed by a precise point-to-point matching of sensory and relay neurons. Here we describe recent progress in the understanding of how cell-intrinsic differentiation programs and context-dependent cellular interactions generate a stereotyped sensory map in the Drosophila brain. Recent findings revealed an astonishing morphological diversity among members of the same interneuron class, suggesting an unexpected variability in local microcircuits involved in insect sensory processing.     

Significance of chronotypic specificity of healthy individuals for the variability of cardiac rhythm

Differences in cardiointervalogram parameters have been revealed in young people with the morning and evening chronotypes. Individuals with the morning chronotype are characterized by a tendency to sympathicotonia in the morning, which decreases towards the end of the day. For individuals with the evening chronotype, a reverse tendency is typical, which is manifested as the appearance of signs of cardiointervalogram sympathization in the evening.     

Ontogeny of corticocortical projections of the rat somatosensory cortex.

Rhodamine-coated microspheres (RCMs) were injected into the primary somatosensory cortex (SI) of rats ranging in age from postnatal (PN) day 1 to adulthood. Ipsilateral corticocortical and callosal projections within the SI were identified as early as PN day 1. At the end of the first PN week, ipsilaterally projecting neurons located in sublayer VIb were the first to assume an adult-like pattern of connectivity. Injections at subsequent postnatal ages revealed that an adult pattern of lamination of ipsilateral corticocortical projections within the SI is established between PN weeks 2 and 3, comprising projection neurons from layers II/III, layer V, and sublayer VIb. Therefore, local interactions in the rat SI are mediated not only by pyramidal neurons of layers III and V, derived from the cortical plate, but also by a subpopulation of ontogenetically older neurons located in the sublayer VIb, which may correspond to the subplate neurons of other species. Overall, these results suggest the existence of three independent short-range corticocortical systems of projections within the rat SI, which differ in terms of the laminar distribution and ontogenetic origin of their cells.     

Systems biology, connectivity and the future of medicine

The concept of systems-based strategies in medicine is emerging, with systems pathology guiding an understanding of the multidimensional aspects of disease system fingerprints and systems pharmacology providing insight into dynamic system responses upon (multiple) drug perturbations. Knowledge of the changes of system characteristics during disease progression creates a framework for the design of novel combinatorial treatment strategies. Such a systems-based, combinatorial-therapies approach readdresses the value of the synergistic actions of components of treatments based on natural products and highlights new methodology to study multidimensional intervention via reversed-pharmacology.     

Changing seascapes, stochastic connectivity, and marine metapopulation dynamics

The probability of dispersal from one habitat patch to another is a key quantity in our efforts to understand and predict the dynamics of natural populations. Unfortunately, an often overlooked property of this potential connectivity is that it may change with time. In the marine realm, transient landscape features, such as mesoscale eddies and alongshore jets, produce potential connectivity that is highly variable in time. We assess the impact of this temporal variability by comparing simulations of nearshore metapopulation dynamics when potential connectivity is constant through time (i.e., when it is deterministic) and when it varies in time (i.e., when it is stochastic). We use mathematical analysis to reach general conclusions and realistic biophysical modeling to determine the actual magnitude of these changes for a specific system: nearshore marine species in the Southern California Bight. We find that in general the temporal variability of potential connectivity affects two important quantities: metapopulation growth rates when the species is rare and equilibrium abundances. Our biophysical models reveal that stochastic outcomes are almost always lower than their deterministic counterparts, sometimes by up to 40%. This has implications for how we use spatial information, such as connectivity, to manage nearshore (and other) systems.     

Sequence variability of the pattern recognition receptor Mermaid mediates specificity of marine nematode symbioses

Selection of a specific microbial partner by the host is an all-important process. It guarantees the persistence of highly specific symbioses throughout host generations. The cuticle of the marine nematode Laxus oneistus is covered by a single phylotype of sulfur-oxidizing bacteria. They are embedded in a layer of host-secreted mucus containing the mannose-binding protein Mermaid. This Ca²⁺-dependent lectin mediates symbiont aggregation and attachment to the nematode. Here, we show that Stilbonema majum—a symbiotic nematode co-occurring with L. oneistus in shallow water sediment—is covered by bacteria phylogenetically distinct to those covering L. oneistus. Mermaid cDNA analysis revealed extensive protein sequence variability in both the nematode species. We expressed three recombinant Mermaid isoforms, which based on the structural predictions display the most different carbohydrate recognition domains (CRDs). We show that the three CRDs (DNT, DDA and GDA types) possess different affinities for L. oneistus and S. majum symbionts. In particular, the GDA type, exclusively expressed by S. majum, displays highest agglutination activity towards its symbionts and lowest towards its L. oneistus symbionts. Moreover, incubation of L. oneistus in the GDA type does not result in complete symbiont detachment, whereas incubation in the other types does. This indicates that the presence of particular Mermaid isoforms on the nematode surface has a role in the attachment of specific symbionts. This is the first report of the functional role of sequence variability in a microbe-associated molecular patterns receptor in a beneficial association.     

Small-world connectivity, motif composition, and complexity of fractal neuronal connections

Connection patterns of the cerebral cortex consist of pathways linking neuronal populations across multiple levels of scale, from whole brain regions to local minicolumns. This nested interconnectivity suggests the hypothesis that cortical connections are arranged in fractal or self-similar patterns. We describe a simple procedure to generate fractal connection patterns that aim at capturing the potential self-similarity and hierarchical ordering of neuronal connections. We examine these connection patterns by calculating a broad range of structural measures, including small-world attributes and motif composition, as well as some global measures of functional connectivity, including complexity. As we vary fractal patterns by changing a critical control parameter, we find strongly correlated changes in several structural and functional measures, suggesting that they emerge together and are mutually linked. Measures obtained from some modeled fractal patterns closely resemble those of real neuroanatomical data sets, supporting the original hypothesis.