A modeling approach of the influence of local hydrodynamic conditions on larval dispersal at hydrothermal vents.

Deep-sea hydrothermal vent animal communities along oceanic ridges are both patchy and transient. Larval dispersal is a key factor in understanding how these communities function and are maintained over generations. To date, numerical approaches simulating larval dispersal considered the effect of oceanic currents on larval transportation over hundreds of kilometers but very seldom looked at the effect of local conditions within meters around chimneys. However, small scale significant variations in the hydrodynamics may influence larval fate in its early stages after release, and hence have a knock-on effect on both dispersal and colonization processes. Here we present a new numerical approach to the study of larval dispersal, considering small scales within the range of the biological communities, called "bio-hydrodynamical" scale, and ranging from a few centimeters to a few meters around hydrothermal sources. We use a physical model for the vent based on jet theory and compute the turbulent velocity field around the smoker. Larvae are considered as passive particles whose trajectories are affected by hydrodynamics, topography of the vent chimney and larval biological properties. Our model predicts that bottom currents often dominate all other factors either by entraining all larvae away from the vent or enforcing strong colonization rates. When bottom currents are very slow (<1 mms(-1)), general larvae motion is upwards due to entrainment by the main smoker jet. In this context, smokers with vertical slopes favor retention of larvae because larval initial trajectory is nearly parallel to the smoker wall, which increases the chances to settle. This retention phenomenon is intensified with increasing velocity of the main smoker jet because entrainment in the high velocity plume is preceded by a phase when larvae are attracted towards the smoker wall, which occurs earlier with higher velocity of the main jet. Finally, the buoyancy rate of the larvae, measured to be in the range of 0.01 mms(-1), is generally irrelevant unless hydrodynamic conditions are balanced, i.e. if the buoyancy rate is comparable to both the bottom current speed and the local water velocity due to entrainment by close smokers. Overall, our model evidences the strong effect of the release point of larvae on their future entrainment within local fluxes. Larvae released from smoker walls might have an entirely different fate than those released further away in the water column. The latter are not, or less, affected by near-chimney hydrodynamics.

Modeling polarity buildup and cell fate decision in the fly eye: insight into the connection between the PCP and Notch pathways.

Metazoan development critically depends on a surprisingly short list of conserved pathways. How can such ubiquitous systems regulate a variety of cell-biological events at various developmental stages in different tissues and in different organisms? In the fruit fly, the planar cell polarity (PCP) pathway regulates widely different processes. It is known to be involved in the correct alignment of hairs on the wing and in the determination of R3/R4 photoreceptor cell fates in the eye. In the wing, PCP regulates the spatial structure of cells sharing the same transcriptional fate, while in the eye the Notch signaling pathway has been recruited to additionally transduce the PCP signal to the nuclei in the two differentiating members of a photoreceptor pair. We have recently proposed a computational model for PCP in the wing; this model posited, on the basis of all known data, that planar polarity buildup is driven by asymmetric molecular complexes constructed around the cadherin Flamingo and spanning the space between two cells. In this paper, we show that the same model, combined with a novel Notch module, equally applies in the eye. The model provides insight into the crosstalk between the PCP and Notch modules in development and illustrates the ability of signaling modules to robustly maintain vital phenotypes in a noisy environment.

Modeling Hox gene regulation in digits: reverse collinearity and the molecular origin of thumbness.

During the development of mammalian digits, clustered Hoxd genes are expressed following a collinear regulatory strategy, leading to both the growth of digits and their morphological identities. Because gene dosage is a key parameter in this system, we used a quantitative approach, associated with a collection of mutant stocks, to investigate the nature of the underlying regulatory mechanism(s). In parallel, we elaborated a mathematical model of quantitative collinearity, which was progressively challenged and validated by the experimental approach. This combined effort suggested a two-step mechanism, which involves initially the looping and recognition of the cluster by a complex including two enhancer sequences, followed by a second step of microscanning of genes located nearby. In this scenario, the respective rank of the genes, with respect to the 5' extremity of the cluster, is primordial, as well as different gene-specific affinities. This model accounts for the quantitative variations observed in our many mutant strains, and reveals the molecular constraint leading to thumbness; i.e., why a morphological difference must occur between the most anterior digit and the others. We also show that the same model applies to the collinear regulation of Hox genes during the emergence of external genitalia, though with some differences likely illustrating the distinct functionalities of these structures in adults.

From a representation of behavior to the concept of cognitive syntax: a theoretical framework.

Before we do anything, our brain must first construct a neural correlate of the various mental operations needed. Imaging and recording techniques have vastly improved our understanding of this process by providing detailed insight into how different regions of the brain contribute to behavior. However, exactly how these regions collaborate with each other to form the brain-scale activity necessary to generate even the simplest task remains elusive. Here we present a neural network model based on the hypothesis of a modular organization of brain activity, where basic neural functions useful to the current task are recruited and integrated into actual behavior. At the heart of this mechanism are regulating structures that restrain activity from flowing freely between the different cortical areas involved, releasing it instead in a controlled fashion designed to produce the different mental operations required by the task at hand. The resulting dynamics enables the network to perform the delayed-matching to sample and delayed-pair association tasks. The model suggests that brain activity coding for elementary tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia. We also argue that such an integration process might take place through an iterative process, by piecing together previously validated behavioral chunks, while creating new ones under the guidance of a partially innate cognitive syntax.

Specifying positional information in the embryo: looking beyond morphogens.

Concentration gradients of small diffusible molecules called morphogens are key regulators of development, specifying position during pattern formation in the embryo. It is now becoming clear that additional or alternative mechanisms involving interactions among cells are also crucial for positional specification.

A model for integrating elementary neural functions into delayed-response behavior.

It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

Establishment and maintenance of planar epithelial cell polarity by asymmetric cadherin bridges: a computer model.

Animal scales, hairs, feathers, and cilia are oriented due to cell polarization in the epithelial plane. Genes involved have been identified, but the signal and mechanism remain unknown. In Drosophila wing polarization, the action of a gradient of Frizzled activity is widely assumed; and cell-cell signalling by cadherins such as Flamingo surely plays a major role. We present a computer model where reading the Frizzled gradient occurs through biased, feedback-reinforced formation of Flamingo-based asymmetric intercellular complexes. Through these complexes neighboring cells are able to compare their Frizzled activity levels. Our computations are highly noise-resistant and reproduce both wild-type and all known mutant wing phenotypes; other phenotypes are predicted. The model puts stringent limits on a Frizzled activation signal, which should exhibit unusual properties: (1) the extracellular Frizzled signalling gradient should be counterdirectional--decreasing from proximal (P) to distal (D), whereas during polarization, the intracellular Frizzled gradient builds up from P to D; (2) the external gradient should be relatively weak and short-lived, lest it prevent inversion of intracellular Frizzled. These features, largely independent of model details, may provide useful clues for future experimental efforts.

Acquisition and performance of delayed-response tasks: a neural network model.

We study the time evolution of a neural network model as it learns the three stages of a visual delayed-matching-to-sample (DMS) task: identification of the sample, retention during delay, and matching of sample and target, ignoring distractors. We introduce a neurobiologically plausible, uncommitted architecture, comprising an "executive" subnetwork gating connections to and from a "working" layer. The network learns DMS by reinforcement: reward-dependent synaptic plasticity generates task-dependent behaviour. During learning, working layer cells exhibit stimulus specialization and increased tuning of their firing. The emergence of top-down activity is observed, reproducing aspects of prefrontal cortex control on activity in the visual areas of inferior temporal cortex. We observe a lability of neural systems during learning, with a tendency to encode spurious associations. Executive areas are instrumental during learning to prevent such associations; they are also fundamental for the "mature" network to keep passing DMS. In the mature model, the working layer functions as a short-term memory. The mature system is remarkably robust against cell damage and its performance degrades gracefully as damage increases. The model underlines that executive systems, which regulate the flow of information between working memory and sensory areas, are required for passing tests such as DMS. At the behavioural level, the model makes testable predictions about the errors expected from subjects learning the DMS.

Noise, delays, robustness, canalization and all that.

A biological system such as a developing embryo can withstand many perturbations. What is the basis of this robustness both against noise and mutation? Recent advances in modeling may throw new light on this old problem. First, recent theoretical and experimental work clearly demonstrates the importance of noise and time delays for the proper functioning of genetic networks: noise and delays are simply part of the normal operating constraints. By contrast, sweeping statements have been made recently about a so-called 'robustness' of biological processes, based on work that neglects noise and delays completely. I submit that studying the stability of complex biological systems with such omissions is an unnecessary, inadequate and potentially disastrous simplification. I review the existing alternatives and propose using them to construct a modeling framework that overcomes all serious limitations.

Oriented clonal cell growth in the developing mouse myocardium underlies cardiac morphogenesis.

During heart morphogenesis, cardiac chambers arise by differential expansion of regions of the primitive cardiac tube. This process is under the control of specific transcription factors such as Tbx5 and dHAND. To gain insight into the cellular mechanisms that underlie cardiogenesis, we have used a retrospective clonal approach based on the spontaneous recombination of an nlaacZ reporter gene targeted to the murine alpha-cardiac actin locus. We show that clonal growth of myocardial cells is oriented. At embryonic day (E) 10.5, the shape of clones is characteristic of a given cardiac region and reflects its morphology. This is already detectable in the primitive cardiac tube at E8.5, and is maintained after septation at E14.5 with additional modulations. The clonal analysis reveals new subdivisions of the myocardium, including an interventricular boundary region. Our results show that the myocardium, from the time of its formation, is a polarized and regionalized tissue and point to the role of oriented clonal cell growth in cardiac chamber morphogenesis.

Genes, neurons and codes: remarks on biological communication.

I examine critically the application of information-theoretic ideas to biological communication during embryonic development and in the functioning central nervous system (CNS). I show that intercellular communication relies mostly on simple signals whose role is to effect a selection among predetermined cellular states. Hence, a crucial role is played by cellular memory, which stabilizes such states. Memory in cells is partly located in the nuclear DNA; no less important however is (phenotypic) memory lying in the cell's organelles and compartments. Because of combinatorial effects in gene expression patterns, cell memory is an enormously powerful mechanism, which also underlies plasticity, and thus constitutes the factor unifying genetic determination, plasticity and learning. Communication in the CNS is analyzed in some detail: here, cellular memory is embodied in anatomy (i.e., cell shape) and neurochemistry. These are the major, relatively "static" factors affecting the routing of neural impulses in the adult CNS. In addition, however, faster channeling is also required: action potentials must be directed to their targets along a few of exponentially many paths, and this dynamic routing is crucial for proper operation. I suggest that collective oscillatory modes may play a role in solving this addressing problem, in the same way that the clock signal gates the operation of man-made computers.