Visualizing Morphogenesis with the Processing Programming Language

Abstract

We used Processing, a visual artists' programming language developed at MIT Media Lab, to IntroductionProcessing is a Java based software language and environment created at MIT Media Laboratory in 2001 for visual modeling (www.processing.org). Processing has grown into a popular tool and online community for programming within the visual arts and data visualization fields. Several artists have used Processing to model or simulate various biological phenomena. One artist animated a matrix of biological cells switching between two states (Polyptic by George Legrady), while another simulated fungal hyphae growth using images as food (Mycelium by Ryan Alexander). A textbook further describes how Processing can animate dynamic processes in nature using diverse underlying theoretical models (Shiffman 2012). However, Processing has yet to make its full mark in modeling of biological phenomena. One potential area of application for Processing is computational visualization of morphogenesis in developmental biology.Morphogenesis -the generation of shape and form in embryonic tissues -is a critical process in developmental biology (Gilbert 2013). Morphogenesis is responsible for elongating the body axis, forming the organs in the body, and establishing neuronal circuitry in the brain, among other processes. A central issue in the study of morphogenesis is determining the cell behaviors (e.g. motility, rearrangement, shape change, and division) that are responsible for changing tissue shapes. A powerful technique for elucidating the dynamic cellular mechanisms of morphogenesis is time-lapse videomicroscopic imaging of cells in embryonic tissues undergoing morphogenesis (Elul and Keller 2000;Elul et al., 1997;Harris et al., 1987). The mechanisms underlying morphogenetic processes can be clarified by observation of cell dynamics from these time-lapse video sequences.Morphometric measurement further defines the quantitative and statistical relationships between the cell dynamics that underlie morphogenesis (Kim and Davidson 2011;Marshak et al., 2007;Elul et al., 1997;Witte et al., 1996). Mathematical decomposition of cell dynamics additionally facilitates the computational modeling of cellular mechanisms that drive morphogenesis (Satulovsky et al., 2008). MethodsIn this paper, we use the Processing programming language to visualize dynamic cell behaviors driving morphogenesis in the developing nervous system. Based on in vivo time-lapse image sequences, we created models of cell dynamics underlying two morphogenetic processes in the developing nervous system. We first computationally modeled the cell motility that drives neural tube formation and spinal cord elongation in vertebrate embryos. The terminal branching of optic axonal arbors that establish synaptic connectivity in the primary visual projection was then simulated. These visualizations highlight the process of computational decomposition of the dynamic cell behaviors that shape the developing nervous system, which may be useful for artists seeking to illustrate ...

N-terminal and central domains of APC function to regulate branch number, length and angle in developing optic axonal arbors in vivo

“…3C). Quantitative measurements further showed that control optic axonal arbors had a mean branching angle of 68° (SE = 2.7, n = 91 angles in 10 control GFP arbors; also see Patel et al, 2017). However, for APCNTERM optic axonal arbors, we measured an average bifurcation angle of 75° (SE =2.9, 93 angles in 16 APCNTERM arbors).…”

Quantifying patterns in art and nature

“…In addition to our watercolour paintings, we have developed computational visualizations that mimic the temporal patterns in changes of cellular morphologies. These animations were developed using the Processing programming language (www.processing.org), based on observations of time lapse microscopic sequences of cells captured in living embryonic tissues (Patel et al, 2017). To best simulate the fractal patterns in the dynamic cell contours, we incorporated both deterministic (repetitive) and random (variable) number parameters into each of the programmes.…”

Exploring Connections Between Cosmos & Mind Through Six Interactive Art Installations in "As Above As Below"

“…This leads to neurons that develop morphologies that approximate minimal spanning trees that contain a set of nodes that are branch points and/or synapse locations (Cuntz, 2012). Neurons have also inspired many artistic interpretations and visualizations (Kim, 2015;Patel et al, 2017).…”