Deciphering the underlying mechanisms of the pharyngeal pumping motions in Caenorhabditis elegans.

The pharynx of the nematode Caenorhabditis elegans is a neuromuscular organ that exhibits typical pumping motions, which result in the intake of food particles from the environment. In-depth inspection reveals slightly different dynamics at the various pharyngeal areas, rather than synchronous pumping motions of the whole organ, which are important for its effective functioning. While the different pumping dynamics are well characterized, the underlying mechanisms that generate them are not known. In this study, the C. elegans pharynx was modeled in a bottom-up fashion, including all of the underlying biological processes that lead to, and including, its end function, food intake. The mathematical modeling of all processes allowed performing comprehensive, quantitative analyses of the system as a whole. Our analyses provided detailed explanations for the various pumping dynamics generated at the different pharyngeal areas; a fine-resolution description of muscle dynamics, both between and within different pharyngeal areas; a quantitative assessment of the values of many parameters of the system that are unavailable in the literature; and support for a functional role of the marginal cells, which are currently assumed to mainly have a structural role in the pharynx. In addition, our model predicted that in tiny organisms such as C. elegans, the generation of long-lasting action potentials must involve ions other than calcium. Our study exemplifies the power of mathematical models, which allow a more accurate, higher-resolution inspection of the studied system, and an easier and faster execution of in silico experiments than feasible in the lab.

Measurement of the Anisotropic Dynamic Elastic Constants of Additive Manufactured and Wrought Ti6Al4V Alloys.

Additively manufactured (AM) materials and hot rolled materials are typically orthotropic, and exhibit anisotropic elastic properties. This paper elucidates the anisotropic elastic properties (Young's modulus, shear modulus, and Poisson's ratio) of Ti6Al4V alloy in four different conditions: three AM (by selective laser melting, SLM, electron beam melting, EBM, and directed energy deposition, DED, processes) and one wrought alloy (for comparison). A specially designed polygon sample allowed measurement of 12 sound wave velocities (SWVs), employing the dynamic pulse-echo ultrasonic technique. In conjunction with the measured density values, these SWVs enabled deriving of the tensor of elastic constants (Cij) and the three-dimensional (3D) Young's moduli maps. Electron backscatter diffraction (EBSD) and micro-computed tomography (µCT) were employed to characterize the grain size and orientation as well as porosity and other defects which could explain the difference in the measured elastic constants of the four materials. All three types of AM materials showed only minor anisotropy. The wrought (hot rolled) alloy exhibited the highest density, virtually pore-free µCT images, and the highest ultrasonic anisotropy and polarity behavior. EBSD analysis revealed that a thin ß-phase layer that formed along the elongated grain boundaries caused the ultrasonic polarity behavior. The finding that the elastic properties depend on the manufacturing process and on the angle relative to either the rolling direction or the AM build direction should be taken into account in the design of products. The data reported herein is valuable for materials selection and finite element analyses in mechanical design. The pulse-echo measurement procedure employed in this study may be further adapted and used for quality control of AM materials and parts.

A measure of smell enables the creation of olfactory metamers.

Wavelength is a physical measure of light, and the intricate understanding of its link to perceived colour enables the creation of perceptual entities such as metamers-non-overlapping spectral compositions that generate identical colour percepts1. By contrast, scientists have been unable to develop a physical measure linked to perceived smell, even one that merely reflects the extent of perceptual similarity between odorants2. Here, to generate such a measure, we collected perceptual similarity estimates of 49,788 pairwise odorants from 199 participants who smelled 242 different multicomponent odorants and used these data to refine a predictive model that links odorant structure to odorant perception3. The resulting measure combines 21 physicochemical features of the odorants into a single number-expressed in radians-that accurately predicts the extent of perceptual similarity between multicomponent odorant pairs. To assess the usefulness of this measure, we investigated whether we could use it to create olfactory metamers. To this end, we first identified a cut-off in the measure: pairs of multicomponent odorants that were within 0.05 radians of each other or less were very difficult to discriminate. Using this cut-off, we were able to design olfactory metamers-pairs of non-overlapping molecular compositions that generated identical odour percepts. The accurate predictions of perceptual similarity, and the ensuing creation of olfactory metamers, suggest that we have obtained a valid olfactory measure, one that may enable the digitization of smell.

Autonomics: In search of a foundation for next-generation autonomous systems.

The potential benefits of autonomous systems are obvious. However, there are still major issues to be dealt with before developing such systems becomes a commonplace engineering practice, with accepted and trustworthy deliverables. We argue that a solid, evolving, publicly available, community-controlled foundation for developing next-generation autonomous systems is a must, and term the desired foundation "autonomics." We focus on three main challenges: 1) how to specify autonomous system behavior in the face of unpredictability; 2) how to carry out faithful analysis of system behavior with respect to rich environments that include humans, physical artifacts, and other systems; and 3) how to build such systems by combining executable modeling techniques from software engineering with artificial intelligence and machine learning.

Computational Paradigm to Elucidate the Effects of Arts-Based Approaches: Art and Music Studies and Implications for Research and Therapy.

Art therapy and music therapy, as well as other arts-based approaches and interventions, help to mitigate symptoms in serious and chronic diseases and to improve the well-being and quality of life for both healthy individuals and patients. Artistic creation is also researched and practiced intending to empower and understand individuals, groups, and communities. However, much research is required in order to learn how arts-based approaches operate and to enhance their effectivity. The complex and simultaneous occurrences involving the dynamics of the creation work, the client, and the therapist in a typical arts setting are difficult to grasp, consequently affecting their objective analyses. Here we employ our Computational Paradigm which enables the quantitative and rigorous tracking, analyzing, and documenting of the underlying dynamic processes, and describe its application in recent past and current real-world art and music studies with human participants. We aim to study emergent artistic behaviors of individuals and collectives in response to art and music making. Significant insights obtained include demographic variation factors such as gender and age, empirical behavioral patterns, and quantitative expressiveness and its change. We discuss the implications of the findings for therapy and research, such as causality for behavioral diversification and audio-visual cross-modality, and also offer directions for future applications and technology enhancements.

Computational elucidation of the effects induced by music making.

Music making, in the form of free improvisations, is a common technique in music therapy, used to express one's feelings or ideas in the non-verbal language of music. In the broader sense, arts therapies, and music therapy in particular, are used to induce therapeutic and psychosocial effects, and to help mitigate symptoms in serious and chronic diseases. They are also used to empower the wellbeing and quality of life for both healthy individuals and patients. However, much research is still required to understand how music-based and arts-based approaches work, and to eventually enhance their effectivity. The clinical setting employing the arts constitutes a rich dynamic environment of occurrences that is difficult to capture, being driven by complex, simultaneous, and interwoven behavioral processes. Our computational paradigm is designed to allow substantial barriers in the arts-based fields to be overcome by enabling the rigorous and quantitative tracking, analyzing and documenting of the underlying dynamic processes. Here we expand the method for the music modality and apply it in a proof of principle experimentation to study expressive behavioral effects of diverse musical improvisation tasks on individuals and collectives. We have obtained statistically significant results that include empirical expressive patterns of feelings, as well as proficiency, gender and age behavioral differences, which point to variation factors of these categorized collectives in music making. Our results also suggest that males are more exploratory than females (e.g., they exhibit a larger range of octaves and intensity) and that the older people express musical characterized negativity more than younger ones (e.g., exhibiting larger note clusters and more chromatic transitions). We discuss implications of these findings to music therapy, such as behavioral diversity causality in treatment, as well as future scientific and clinical applications of the methodology.

Attention Robustly Gates a Closed-Loop Touch Reflex.

Rats' large whiskers (macrovibrissae) are used to explore their nearby environment, typically using repetitive protraction-retraction "whisking" motions that are coordinated with head and body movements [1-8]. Once objects are detected, the rat can further explore the object tactually by using both the macrovibrissae and an array of shorter, stationary microvibrissae on the chin, as well as by using the lips [9-11]. When touch occurs during whisking, a fast reflexive response, termed a touch-induced pump (TIP), may be triggered. During a TIP, the whisker slightly retracts and protracts again, doubling the number of pressure onsets per contact. In head-fixed rats, TIPs occur in ∼25% of the contacts [12]. Here we report that the occurrence of TIPs depends strongly on attention, indicated by head-turning toward an object: when rats intended to explore an object, either after encountering it during free exploration or when expecting its existence, the probability of a TIP increased from <30% to >65% without an increase in TIP latency. TIP regulation was unilateral and specific to the attended object; when two objects were palpated bilaterally simultaneously, TIP probability increased to >65% and decreased to <20% for contacts with the apparently-attended and apparently-unattended object, respectively. A data-driven computational model indicates that attentional gating could not be triggered by object contact, due to temporal constraints; rather, it could be based on a normally enabled or whisking-triggered scheme. Taken together, our results suggest that object-related attention regulates contact dynamics by gating the operation of a brainstem motor-sensory-motor loop and that this regulation is optimized for fast reaction.

Niépce-Bell or Turing: how to test odour reproduction.

Decades before the existence of anything resembling an artificial intelligence system, Alan Turing raised the question of how to test whether machines can think, or, in modern terminology, whether a computer claimed to exhibit intelligence indeed does so. This paper raises the analogous issue for olfaction: how to test the validity of a system claimed to reproduce arbitrary odours artificially, in a way recognizable to humans. Although odour reproduction systems are still far from being viable, the question of how to test candidates thereof is claimed to be interesting and non-trivial, and a novel method is proposed. Despite the similarity between the two questions and their surfacing long before the tested systems exist, the present question cannot be answered adequately by a Turing-like method. Instead, our test is very different: it is conditional, requiring from the artificial no more than is required from the original, and it employs a novel method of immersion that takes advantage of the availability of easily recognizable reproduction methods for sight and sound, a la Nicéphore Niépce and Alexander Graham Bell.

The tumor as an organ: comprehensive spatial and temporal modeling of the tumor and its microenvironment.

BACKGROUND: Research related to cancer is vast, and continues in earnest in many directions. Due to the complexity of cancer, a better understanding of tumor growth dynamics can be gleaned from a dynamic computational model. We present a comprehensive, fully executable, spatial and temporal 3D computational model of the development of a cancerous tumor together with its environment. RESULTS: The model was created using Statecharts, which were then connected to an interactive animation front-end that we developed especially for this work, making it possible to visualize on the fly the on-going events of the system's execution, as well as the effect of various input parameters. We were thus able to gain a better understanding of, e.g., how different amounts or thresholds of oxygen and VEGF (vascular endothelial growth factor) affect the progression of the tumor. We found that the tumor has a critical turning point, where it either dies or recovers. If minimum conditions are met at that time, it eventually develops into a full, active, growing tumor, regardless of the actual amount; otherwise it dies. CONCLUSIONS: This brings us to the conclusion that the tumor is in fact a very robust system: changing initial values of VEGF and oxygen can increase the time it takes to become fully developed, but will not necessarily completely eliminate it.

An Interactive Tool for Animating Biology, and Its Use in Spatial and Temporal Modeling of a Cancerous Tumor and Its Microenvironment.

The ability to visualize the ongoing events of a computational model of biology is critical, both in order to see the dynamics of the biological system in action and to enable interaction with the model from which one can observe the resulting behavior. To this end, we have built a new interactive animation tool, SimuLife, for visualizing reactive models of cellular biology. SimuLife is web-based, and is freely accessible at http://simulife.weizmann.ac.il/. We have used SimuLife to animate a model that describes the development of a cancerous tumor, based on the individual components of the system and its environment. This has helped in understanding the dynamics of the tumor and its surrounding blood vessels, and in verifying the behavior, fine-tuning the model accordingly, and learning in which way different factors affect the tumor.

Computational Paradigm to Elucidate the Effects of Arts-Based Approaches and Interventions: Individual and Collective Emerging Behaviors in Artwork Construction.

Art therapy, as well as other arts-based therapies and interventions, is used to reduce pain, stress, depression, breathlessness and other symptoms in a wide variety of serious and chronic diseases, such as cancer, Alzheimer and schizophrenia. Arts-based approaches are also known to contribute to one's well-being and quality of life. However, much research is required, since the mechanisms by which these non-pharmacological treatments exert their therapeutic and psychosocial effects are not adequately understood. A typical clinical setting utilizing the arts consists of the creation work itself, such as the artwork, as well as the therapist and the patient, all of which constitute a rich and dynamic environment of occurrences. The underlying complex, simultaneous and interwoven processes of this setting are often considered intractable to human observers, and as a consequence are usually interpreted subjectively and described verbally, which affect their subsequent analyses and understanding. We introduce a computational research method for elucidating and analyzing emergent expressive and social behaviors, aiming to understand how arts-based approaches operate. Our methodology, which centers on the visual language of Statecharts and tools for its execution, enables rigorous qualitative and quantitative tracking, analysis and documentation of the underlying creation and interaction processes. Also, it enables one to carry out exploratory, hypotheses-generating and knowledge discovery investigations, which are empirical-based. Furthermore, we illustrate our method's use in a proof-of-principle study, applying it to a real-world artwork investigation with human participants. We explore individual and collective emergent behaviors impacted by diverse drawing tasks, yielding significant gender and age hypotheses, which may account for variation factors in response to art use. We also discuss how to gear our research method to systematic and mechanistic investigations, as we wish to provide a broad empirical evidence for the uptake of arts-based approaches, also aiming to ameliorate their use in clinical settings.

Tactile modulation of whisking via the brainstem loop: statechart modeling and experimental validation.

Rats repeatedly sweep their facial whiskers back and forth in order to explore their environment. Such explorative whisking appears to be driven by central pattern generators (CPGs) that operate independently of direct sensory feedback. Nevertheless, whisking can be modulated by sensory feedback, and it has been hypothesized that some of this modulation already occurs within the brainstem. However, the interaction between sensory feedback and CPG activity is poorly understood. Using the visual language of statecharts, a dynamic, bottom-up computerized model of the brainstem loop of the whisking system was built in order to investigate the interaction between sensory feedback and CPG activity during whisking behavior. As a benchmark, we used a previously quantified closed-loop phenomenon of the whisking system, touched-induced pump (TIP), which is thought to be mediated by the brainstem loop. First, we showed that TIPs depend on sensory feedback, by comparing TIP occurrence in intact rats with that in rats whose sensory nerve was experimentally cut. We then inspected several possible feedback mechanisms of TIPs using our model. The model ruled out all hypothesized mechanisms but one, which adequately simulated the corresponding motion observed in the rat. Results of the simulations suggest that TIPs are generated via sensory feedback that activates extrinsic retractor muscles in the mystacial pad. The model further predicted that in addition to the touching whisker, all whiskers found on the same side of the snout should exhibit a TIP. We present experimental results that confirm the predicted movements in behaving rats, establishing the validity of the hypothesized interaction between sensory feedback and CPG activity we suggest here for the generation of TIPs in the whisking system.

Reactive animation: from piecemeal experimentation to reactive biological systems.

Over the past decade, multi-level complex behavior and reactive nature of biological systems, has been a focus point for the biomedical community. We have developed a computational approach, termed Reactive Animation (RA) for simulating such complex biological systems. RA is an approach for describing the dynamic characteristics of biological systems based on facts collected from experiments. These data are integrated bottom-up by computational tools and methods for reactive systems development and are simulated concomitantly to a front-end user friendly visualization and reporting systems. Using RA, the experimenter may intervene mid-simulation, suggest new hypotheses for cellular and molecular interactions, apply them to the simulation and observe their resulting outcomes "on-line". Several RA models have been developed including models of T cell activation, thymocyte development and pancreatic organogenesis, which are describe in the in this review.

Predicting odor pleasantness with an electronic nose.

A primary goal for artificial nose (eNose) technology is to report perceptual qualities of novel odors. Currently, however, eNoses primarily detect and discriminate between odorants they previously "learned". We tuned an eNose to human odor pleasantness estimates. We then used the eNose to predict the pleasantness of novel odorants, and tested these predictions in naïve subjects who had not participated in the tuning procedure. We found that our apparatus generated odorant pleasantness ratings with above 80% similarity to average human ratings, and with above 90% accuracy at discriminating between categorically pleasant or unpleasant odorants. Similar results were obtained in two cultures, native Israeli and native Ethiopian, without retuning of the apparatus. These findings suggest that unlike in vision and audition, in olfaction there is a systematic predictable link between stimulus structure and stimulus pleasantness. This goes in contrast to the popular notion that odorant pleasantness is completely subjective, and may provide a new method for odor screening and environmental monitoring, as well as a critical building block for digital transmission of smell.

Biocharts: a visual formalism for complex biological systems.

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis.

Odorant concentration dependence in electroolfactograms recorded from the human olfactory epithelium.

Electroolfactograms (EOGs) are the summated generator potentials of olfactory receptor neurons measured directly from the olfactory epithelium. To validate the sensory origin of the human EOG, we set out to ask whether EOGs measured in humans were odorant concentration dependent. Each of 22 subjects (12 women, mean age = 23.3 yr) was tested with two odorants, either valeric acid and linalool (n = 12) or isovaleric acid and l-carvone (n = 10), each delivered at four concentrations diluted with warm (37 degrees C) and humidified (80%) odorless air. In behavior, increased odorant concentration was associated with increased perceived intensity (all F > 5, all P < 0.001). In EOG, increased odorant concentration was associated with increased area under the EOG curve (all F > 8, all P < 0.001). These findings substantiate EOG as a tool for probing olfactory coding directly at the level of olfactory receptor neurons in humans.

Four-dimensional realistic modeling of pancreatic organogenesis.

Organogenesis, the process by which organs develop from individual precursor stem cells, requires that the precursor cells proliferate, differentiate, and aggregate to form a functioning structure. This process progresses through changes in 4 dimensions: time and 3 dimensions of space-4D. Experimental analysis of organogenesis, by its nature, cuts the 4D developmental process into static, 2D histological images or into molecular or cellular markers and interactions with little or no spatial dimensionality and minimal dynamics. Understanding organogenesis requires integration of the piecemeal experimental data into a running, realistic and interactive 4D simulation that allows experimentation and hypothesis testing in silico. Here, we describe a fully executable, interactive, visual model for 4D simulation of organogenic development using the mouse pancreas as a representative case. Execution of the model provided a dynamic description of pancreas development, culminating in a structure that remarkably recapitulated morphologic features seen in the embryonic pancreas. In silico mutations in key signaling molecules resulted in altered patterning of the developing pancreas that were in general agreement with in vivo data. The modeling approach described here thus typifies a useful platform for studying organogenesis as a phenomenon in 4 dimensions.

Measuring smells.

Olfaction consists of a set of transforms from a physical space of odorant molecules, through a neural space of information processing, and into a perceptual space of smell. Elucidating the rules governing these transforms depends on establishing valid metrics for each of the three spaces. Here we first briefly review the perceptual and neural spaces, and then concentrate on the physical space of odorant molecules. We argue that the lack of an agreed-upon odor metric poses a significant obstacle toward understanding the neurobiology of olfaction, and suggest two alternative odor metrics as possible solutions.

A scenario-based approach to modeling development: a prototype model of C. elegans vulval fate specification.

Studies of developmental biology are often facilitated by diagram "models" that summarize the current understanding of underlying mechanisms. The increasing complexity of our understanding of development necessitates computational models that can extend these representations to include their dynamic behavior. Here we present a prototype model of Caenorhabditis elegans vulval precursor cell fate specification that represents many processes crucial for this developmental event but that are hard to integrate using other modeling methodologies. We demonstrate the integrative capabilities of our methodology by comprehensively incorporating the contents of three seminal papers, showing that this methodology can lead to comprehensive models of developmental biology. The prototype computational model was built and is run using a language (Live Sequence Charts) and tool (the Play-Engine) that facilitate the same conceptual processes biologists use to construct and probe diagram-type models. We demonstrate that this modeling approach permits rigorous tests of mutual consistency between experimental data and mechanistic hypotheses and can identify specific conflicting results, providing a useful approach to probe developmental systems.

Prediction models for the pleasantness of binary mixtures in olfaction.

Whereas the rules underlying the perceived intensity of binary mixtures have been investigated, minimal efforts have been directed at elucidating the rules underlying the perceived pleasantness of such mixtures. To address this, 84 subjects ranked the pleasantness and intensity of 5 distinct binary mixtures (15 pairs, inter-stimulus interval = 4 s, inter-trial interval = 30 s, flow = 6 l/min, pulse = 2 s) constructed from different ratios (0:100%, 25:75%, 50:50%, 75:25%, and 100:0%, olfactometer-generated vapor phase). We found that in the majority of cases, the pleasantness of the mixture fell between the pleasantness values of its separated constituents and that it was strongly influenced by the relative intensities of the constituents. Based on these results, we proposed a prediction paradigm for the pleasantness of binary mixtures from the pleasantness of their separated constituents weighted by their respective perceived intensities. The uniqueness of the proposed paradigm is that it neither requires presetting an interaction constant between the mixture components nor require any factorization of the pleasantness weights. It does, nonetheless, require solid psychophysical data on the separated components at their different concentrations, and currently it can only explain the behavior of intermediate pleasantness of mixtures.