arXiv subjects

Sitabhra Sinha

Publications and source records attributed to Sitabhra Sinha.

At least 19 recordsLinked to original sources

arXiv2026

Environmental and cell-cell signaling shape developmental trajectories across morphogenetic landscapes

Despite the variability in gene regulation and environmental conditions, development of an organism occurs through a sequence of highly coordinated patterning processes. Cells integrate different signals to accurately infer their position in order to adopt an appropriate identity. Using a model of epigenetic landscape originally proposed by Waddington to describe cell-fate determination, we establish the critical role played by juxtacrine signaling between cells in determining tissue patterns. Subsequently we systematically coarse-grain the model at the tissue scale to map its patterning to transition between states in a binary spin model having a free energy landscape. We show that such landscapes serve as a powerful unifying framework for describing development of biological systems across distinct spatio-temporal scales.

q-bio.TO↗

arXiv2025

Broken Symmetries, Information and Emergence: What is theory, that biology should be mindful of it?

The discipline of `theoretical biology' has been developing from its inception several decades ago almost in parallel with the advances in biology, so much so that the latter is often considered to be almost exclusively an empirical science. However, the scenario has been changing in recent years with statistical mechanics, nonlinear dynamics and soft-matter physics being more and more frequently invoked to explain various biological observations. As distinct from computational biology, theoretical biology is not just an attempt to reproduce in-silico experimental phenomena, but asks more general and abstract questions. It strives to attain a more fundamental understanding of the mechanisms underlying biological phenomena, ranging from oscillations to strategic actions, that can be unified through the perspective that views organisms as processing information to respond appropriately despite the noise in their environment. We show through a number of investigations carried out by our group, on the emergence of systems-level phenomena through interactions between components, how an approach melding physics, and the theory of information & computation can act as an unifying framework for biological processes across a wide range of temporal and spatial scales.

physics.bio-ph↗

arXiv2024

Mechanics promotes coherence in heterogeneous active media

Synchronization of activity among myocytes constituting vital organs, e.g., the heart, is crucial for physiological functions. Self-organized coordination in such heterogeneous ensemble of excitable and oscillatory cells is therefore of clinical importance. We show by varying the strength of intercellular coupling and the electrophysiological diversity, a wide range of collective behavior emerges including clusters of synchronized activity. Strikingly, stretch-activated currents allow waves of mechanical deformation to alter the activity of neighboring cells, promoting robust global coherence.

q-bio.TO↗

arXiv2023

A hierarchy index for networks in the brain reveals a complex entangled organizational structure

Networks involved in information processing often have their nodes arranged hierarchically, with the majority of connections occurring in adjacent levels. However, despite being an intuitively appealing concept, the hierarchical organization of large networks, such as those in the brain, are difficult to identify, especially in absence of additional information beyond that provided by the connectome. In this paper, we propose a framework to uncover the hierarchical structure of a given network, that identifies the nodes occupying each level as well as the sequential order of the levels. It involves optimizing a metric that we use to quantify the extent of hierarchy present in a network. Applying this measure to various brain networks, ranging from the nervous system of the nematode Caenorhabditis elegans to the human connectome, we unexpectedly find that they exhibit a common network architectural motif intertwining hierarchy and modularity. This suggests that brain networks may have evolved to simultaneously exploit the functional advantages of these two types of organizations, viz., relatively independent modules performing distributed processing in parallel and a hierarchical structure that allows sequential pooling of these multiple processing streams. An intriguing possibility is that this property we report may be common to information processing networks in general.

q-bio.NC↗

arXiv2022

Lateral inhibition in relaxation oscillators provides a basis for computation

Coupled relaxation oscillators, realized via chemical or other means, can exhibit a multiplicity of steady states, characterized by spatial patterns resulting from lateral inhibition. We show that perturbation-initiated transformations between these configurations, mapped to binary strings via coarse-graining, provide a basis for computation. The rules governing these transitions emerge from an underlying effective energy landscape shaped by the global and local stabilities of these states. Our results suggest a framework by which far-from-equilibrium systems may encode a computational logic.

nlin.PS↗

arXiv2022

Modeling-informed policy, policy evaluated by modeling: Evolution of mathematical epidemiology in the context of society and economy

The COronaVIrus Disease 2019 (COVID-19) pandemic that has had the world in its grip from the beginning of 2020, has resulted in an unprecedented level of public interest and media attention on the field of mathematical epidemiology. Ever since the disease came to worldwide attention, numerous models with varying levels of sophistication have been proposed; many of these have tried to predict the course of the disease over different time-scales. Other models have examined the efficacy of various policy measures that have been adopted (including the unparalleled use of "lockdowns") to contain and combat the disease. This multiplicity of models may have led to bewilderment in many quarters about the true capabilities and utility of mathematical modeling. Here we provide a brief guide to epidemiological modeling, focusing on how it has emerged as a tool for informed public-health policy-making and has in turn, influenced the design of interventions aimed at preventing disease outbreaks from turning into raging epidemics. We show that the diversity of models is somewhat illusory, as the bulk of them are rooted in the compartmental modeling framework that we describe here. While their basic structure may appear to be a highly idealized description of the processes at work, we show that features that provide more realism, such as the community organization of populations or strategic decision-making by individuals, can be incorporated into such models. We conclude with the argument that the true value of models lies in their ability to test in silico the consequences of different policy choices in the course of an epidemic, a much superior alternative to trial-and-error approaches that are highly costly in terms of both lives and socio-economic disruption.

q-bio.OT↗

arXiv2022

Flags, Landscapes and Signaling: Contact-mediated inter-cellular interactions enable plasticity in fate determination driven by positional information

Multicellular organisms exhibit a high degree of structural organization with specific cell types always occurring in characteristic locations. The conventional framework for describing the emergence of such consistent spatial patterns is provided by Wolpert's "French flag" paradigm. According to this view, intra-cellular genetic regulatory mechanisms use positional information provided by morphogen concentration gradients to differentially express distinct fates, resulting in a characteristic pattern of differentiated cells. However, recent experiments have shown that suppression of inter-cellular interactions can alter these spatial patterns, suggesting that cell fates are not exclusively determined by the regulation of gene expression by local morphogen concentration. Using an explicit model where adjacent cells communicate by Notch signaling, we provide a mechanistic description of how contact-mediated interactions allow information from the cellular environment to be incorporated into cell fate decisions. Viewing cellular differentiation in terms of trajectories along an epigenetic landscape (as first enunciated by Waddington), our results suggest that the contours of the landscape are moulded differently in a cell position-dependent manner, not only by the global signal provided by the morphogen but also by the local environment via cell-cell interactions. We show that our results are robust with respect to different choices of coupling between the inter-cellular signaling apparatus and the intra-cellular gene regulatory dynamics. Indeed, we show that the broad features can be observed even in abstract spin models. Our work reconciles interaction-mediated self-organized pattern formation with boundary-organized mechanisms involving signals that break symmetry.

q-bio.TO↗

arXiv2022

Contact-mediated signaling enables disorder-driven transitions in cellular assemblies

We show that when cells communicate by contact-mediated interactions, heterogeneity in cell shapes and sizes leads to qualitatively distinct collective behavior in the tissue. For inter-cellular coupling that implements lateral inhibition, such disorder-driven transitions can substantially alter the asymptotic pattern of differentiated cells by modulating their fate choice through changes in the neighborhood geometry. In addition, when contact-induced signals influence inherent cellular oscillations, disorder leads to the emergence of functionally relevant partially-ordered dynamical states.

q-bio.TO↗

arXiv2021

Precision of morphogen-driven tissue patterning during development is enhanced through contact-mediated cellular interactions

Embryonic development involves pattern formation characterized by the emergence of spatially localized domains characterized by distinct cell fates resulting from differential gene expression. The boundaries demarcating these domains are precise and consistent within a species despite stochastic fluctuations in the morphogen molecular concentration that provides positional information to the cells, as well as, the intrinsic noise in molecular processes that interpret this information to guide fate determination. We show that local interactions between physically adjacent cells mediated by receptor-ligand binding utilizes the asymmetry between the fate-determining genes to yield a switch-like response to the global signal provided by the morphogen. This results in robust developmental outcomes with a consistent identity of the gene that is dominantly expressed at each cellular location, thereby substantially reducing the uncertainty in the location of the boundary between distinct fates.

q-bio.TO↗

arXiv2021

Disorder in cellular packing can alter proliferation dynamics to regulate growth

Controlling growth via cell division is crucial in the development of higher organisms, and yet the mechanisms through which this is achieved, e.g., in epithelial tissue, is not yet fully understood. We show that by coupling the cell cycle oscillator governing cell division to signals that encode inter-cellular contacts, this phenomenon can be seen as a collective dynamical transition in a system of coupled oscillators in lattices with changing degree of disorder. As the distribution of cellular morphological characteristics become more homogeneous over the course of development, the contact-induced signals to the cells increase beyond a critical value to trigger coordinated cessation of oscillations, eventually leading to growth arrest. Our results suggest that the global phenomenon of growth rate reduction as a tissue approaches its appropriate size is causally related to the increasingly regular geometry of local cell-cell contact interfaces.

q-bio.TO↗

arXiv2021

Contact-mediated cellular communication supplements positional information to regulate spatial patterning during development

Development in multi-cellular organisms is marked by a high degree of spatial organization of the cells attaining distinct fates in the embryo. We show that receptor-ligand interaction between cells in close physical proximity adaptively regulates the local process of selective gene expression in the presence of a global field set up by a diffusing morphogen that provides positional cues. This allows information from the cellular neighborhood to be incorporated into the emergent thresholds of morphogen concentration that dictate cell fate, consistent with recent experiments.

q-bio.TO↗

arXiv2020

Uncovering the invariant structural organization of the human connectome

In order to understand the complex cognitive functions of the human brain, it is essential to study the structural connectome, i.e., the wiring of different brain regions to each other through axonal pathways. However, the high degree of plasticity and cross-population variability in human brains makes it difficult to relate structure to function, motivating a search for invariant patterns in the connectivity. At the same time, variability within a population can provide information about generative mechanisms. In this paper we analyze the connection topology and link-weight distribution of human structural connectomes obtained from a database comprising 196 subjects. By demonstrating a correspondence between the occurrence frequency of individual links and their average weight across the population, we show that the process by which the brain is wired is not independent of the process by which the link weights of the connectome are determined. Furthermore, using the specific distribution of the weights associated with each link over the entire population, we show that a single parameter that is specific to a link can account for its frequency of occurrence, as well as, the variation in its weight across different subjects. This parameter provides a basis for ``rescaling'' the link weights in each connectome, allowing us to obtain a generic network representative of the human brain, distinct from a simple average over the connectomes. We obtain functional connectomes by implementing a neural mass model on each of the vertices of the corresponding structural connectomes. By comparing with the empirical functional brain networks, we demonstrate that the rescaling procedure yields a closer structure-function correspondence. Finally, we show that the representative network can be decomposed into a basal component that is stable across the population and a highly variable superstructure.

q-bio.NC↗

arXiv2020

The nonlinearity of interactions drives networks of neural oscillators to decoherence at strong coupling

While phase oscillators are often used to model neuronal populations, in contrast to the Kuramoto paradigm, strong interactions between brain areas can be associated with loss of synchrony. Using networks of coupled oscillators described by neural mass models, we find that a transition to decoherence at increased coupling strength results from the fundamental nonlinearity, e.g., arising from refractoriness, of the interactions between the nodes. The nonlinearity-driven transition also depends on the connection topology, underlining the role of network structure in shaping brain activity.

q-bio.NC↗

arXiv2020

Mesoscopic architecture enhances communication across the Macaque connectome revealing structure-function correspondence in the brain

Analyzing the brain in terms of organizational structures at intermediate scales provides an approach to negotiate the complexity arising from interactions between its large number of components. Focusing on a wiring diagram that spans the cortex, basal ganglia and thalamus of the Macaque brain, we provide a mesoscopic-level description of the topological architecture of one of the most well-studied mammalian connectomes. The robust modules we identify each comprise densely inter-connected cortical and sub-cortical areas that play complementary roles in executing specific cognitive functions. We find that physical proximity between areas is insufficient to explain the modular organization, as similar mesoscopic structures can be obtained even after factoring out the effect of distance constraints on the connectivity. We observe that the distribution profile of brain areas, classified in terms of their intra- and inter-modular connectivity, is conserved across the principal cortical subdivisions, as well as, sub-cortical structures. In particular provincial hubs, which have significantly higher number of connections with members of their module, but relatively less well-connected to other modules, are the only class that exhibits homophily, i.e., a discernible preference to connect to each other. By considering a process of diffusive propagation we demonstrate that this architecture, instead of localizing the activity, facilitates rapid communication across the connectome. By supplementing the topological information about the Macaque connectome with physical locations, volumes and functions of the constituent areas and analyzing this augmented dataset, we reveal a counter-intuitive role played by the modular architecture of the brain in promoting global interaction.

q-bio.NC↗

arXiv2020

Uncovering the hierarchical structure of the international FOREX market by using similarity metric between the fluctuation distributions of currencies

The decentralized international market of currency trading is a prototypical complex system having a highly heterogeneous composition. To understand the hierarchical structure relating the price movement of different currencies in the market, we have focused on quantifying the degree of similarity between the distributions of exchange rate fluctuations. For this purpose we use a metric constructed using the Jensen-Shannon divergence between the normalized logarithmic return distributions of the different currencies. This provides a novel method for revealing associations between currencies in terms of the statistical nature of their rate fluctuations, which is distinct from the conventional correlation-based methods. The resulting clusters are consistent with the nature of the underlying economies but also show striking divergences during periods of major international crises.

q-fin.ST↗

arXiv2020

Morphogen-regulated contact-mediated signaling between cells can drive the transitions underlying body segmentation in vertebrates

We propose a unified mechanism that reproduces the sequence of dynamical transitions observed during somitogenesis, the process of body segmentation during embryonic development, that is invariant across all vertebrate species. This is achieved by combining inter-cellular interactions mediated via receptor-ligand coupling with global spatial heterogeneity introduced through a morphogen gradient known to occur along the anteroposterior axis. Our model reproduces synchronized oscillations in the gene expression in cells at the anterior of the presomitic mesoderm (PSM) as it grows by adding new cells at its posterior, followed by traveling waves and subsequent arrest of activity, with the eventual appearance of somite-like patterns. This framework integrates a boundary-organized pattern formation mechanism, which uses positional information provided by a morphogen gradient, with the coupling-mediated self-organized emergence of collective dynamics, to explain the processes that lead to segmentation.

q-bio.TO↗

arXiv2019

Frequency gradients in heterogeneous oscillatory media can spatially localize self-organized wave sources that coordinate system-wide activity

Rhythmogenesis, which is critical for many biological functions, involves a transition to coherent activity through cell-cell communication. In the absence of centralized coordination by specialized cells (pacemakers), competing oscillating clusters impede this global synchrony. We show that spatial symmetry-breaking through a frequency gradient results in the emergence of localized wave sources driving system-wide activity. Such gradients, arising through heterogeneous inter-cellular coupling, may explain directed rhythmic activity during labor in the uterus despite the absence of pacemakers.

nlin.AO↗

arXiv2019

Is Life (or at least socio-economic aspects of it) just Spin and Games?

The enterprise of trying to explain different social and economic phenomena using concepts and ideas drawn from physics has a long history. Statistical mechanics, in particular, has been often seen as most likely to provide the means to achieve this, because it provides a lucid and concrete framework for describing the collective behavior of systems comprising large numbers of interacting entities. Several physicists have, in recent years, attempted to use such tools to throw light on the mechanisms underlying a plethora of socio-economic phenomena. These endeavors have led them to develop a community identity - with their academic enterprise being dubbed as "econophysics" by some. However, the emergence of this field has also exposed several academic fault-lines. Social scientists often regard physics-inspired models, such as those involving spins coupled to each other, as over-simplifications of empirical phenomena. At the same time, while models of rational agents who strategically make choices based on complete information so as to maximize their utility are commonly used in economics, many physicists consider them to be caricatures of reality. We show here that while these contrasting approaches may seem irreconcilable there are in fact many parallels and analogies between them. In addition, we suggest that a new formulation of statistical mechanics may be necessary to permit a complete mapping of the game-theoretic formalism to a statistical physics framework. This may indeed turn out to be the most significant contribution of econophysics.

physics.soc-ph↗