arXiv subjects

Varsha Singh

Publications and source records attributed to Varsha Singh.

7 recordsLinked to original sources

arXiv2026

Structural Brain Predictors of Visual Attention Gradient Modulated by Trait Anxiety

Dynamic allocation of attention across the visual field, quantified as a visuospatial attention gradient, is essential for maintaining perceptual breadth. Disruptions to this flexibility may contribute to altered spatial attentional bias and may be influenced by trait anxiety. We investigated whether individual differences in structural brain morphology predict spatial attentional deployment as a function of trait anxiety. Sixty participants, recruited based on an a priori sample size calculation, completed a visuospatial attention gradient task incorporating brief partial facial emotion cues. Although discrete emotional cues did not significantly modulate attention gradients, structural neuroimaging analyses revealed that greater grey matter volume in bilateral cerebellar lobule VI and increased cortical thickness in the left precentral gyrus and paracentral lobule were associated with reduced interaction between the magnitude of the spatial attention gradient (averaged across emotions) and trait anxiety. Machine-learning models further predicted individual attention-anxiety profiles from these neuroanatomical features. These findings suggest that greater structural integrity in cerebellar and sensorimotor regions is associated with more flexible spatial attentional deployment in individuals with lower trait anxiety. Together, the results highlight the contribution of cerebellar and sensorimotor regions, beyond their traditional motor functions, to individual differences in visual spatial attention and cognitive-affective interactions, while demonstrating the predictive utility of structural brain markers.

q-bio.NC↗

arXiv2023

A dynamic fluid landscape mediates the spread of bacteria

Microbial interactions regulate their spread and survival in competitive environments. It is not clear if the physical parameters of the environment regulate the outcome of these interactions. In this work, we show that the opportunistic pathogen Pseudomonas aeruginosa occupies a larger area on the substratum in the presence of yeast such as Cryptococcus neoformans , than without it. At the microscopic level, bacterial cells show an enhanced activity in the vicinity of yeast cells. We observe this behaviour even when the live yeast cells are replaced with heat-killed cells or with spherical glass beads of similar morphology, which suggests that the observed behaviour is not specific to the biology of microbes. Upon careful investigation, we find that a fluid pool is formed around yeast cells which facilitates the swimming of the flagellated P. aeruginosa , causing their enhanced motility. Using mathematical modeling we demonstrate how this local enhancement of bacterial motility leads to the enhanced spread observed at the level of the plate. We find that the dynamics of the fluid landscape around the bacteria, mediated by the growing yeast lawn, affects the spreading. For instance, when the yeast lawn grows faster, a bacterial colony prefers a lower initial loading of yeast cells for optimum enhancement in the spread. We confirm our predictions using Candida albicans and C. neoformans, at different initial compositions. In summary, our work shows the importance of considering the dynamically changing physical environment while studying bacterial motility in complex environments.

q-bio.CB↗

arXiv2021

Real-time Emotion and Gender Classification using Ensemble CNN

Analysing expressions on the person's face plays a very vital role in identifying emotions and behavior of a person. Recognizing these expressions automatically results in a crucial component of natural human-machine interfaces. Therefore research in this field has a wide range of applications in bio-metric authentication, surveillance systems , emotion to emoticons in various social media platforms. Another application includes conducting customer satisfaction surveys. As we know that the large corporations made huge investments to get feedback and do surveys but fail to get equitable responses. Emotion & Gender recognition through facial gestures is a technology that aims to improve product and services performance by monitoring customer behavior to specific products or service staff by their evaluation. In the past few years there have been a wide variety of advances performed in terms of feature extraction mechanisms , detection of face and also expression classification techniques. This paper is the implementation of an Ensemble CNN for building a real-time system that can detect emotion and gender of the person. The experimental results shows accuracy of 68% for Emotion classification into 7 classes (angry, fear , sad , happy , surprise , neutral , disgust) on FER-2013 dataset and 95% for Gender classification (Male or Female) on IMDB dataset. Our work can predict emotion and gender on single face images as well as multiple face images. Also when input is given through webcam our complete pipeline of this real-time system can take less than 0.5 seconds to generate results.

cs.CV↗

arXiv2019

Tuning the torque-speed characteristics of bacterial flagellar motor to enhance the swimming speed

In a classic paper, Edward Purcell analysed the dynamics of flagellated bacterial swimmers and derived a geometrical relationship which optimizes the propulsion efficiency. Experimental measurements for wild-type bacterial species E. coli have revealed that they closely satisfy this geometric optimality. However, the dependence of the flagellar motor speed on the load and more generally the role of the torque-speed characteristics of the flagellar motor is not considered in Purcell's original analysis. Here we derive a tuned condition representing a match between the flagella geometry and the torque-speed characteristics of the flagellar motor to maximize the bacterial swimming speed for a given load. This condition is independent of the geometric optimality condition derived by Purcell and interestingly this condition is not satisfied by wild-type E. coli which swim 2-3 times slower than the maximum possible speed given the amount of available motor torque. Our analysis also reveals the existence of an anomalous propulsion regime, where the swim speed increases with increasing load (drag). Finally, we present experimental data which supports our analysis.

physics.bio-ph↗

arXiv2019

Active modulation of surfactant driven flow instabilities by swarming bacteria

Models based on surfactant driven instabilities have been employed to describe pattern formation by swarming bacteria. However, by definition, such models cannot account for the effect of bacterial sensing and decision making. Here we present a more complete model for bacterial pattern formation which accounts for these effects by coupling active bacterial motility to the passive fluid dynamics. We experimentally identify behaviours which cannot be captured by previous models based on passive population dispersal and show that a more accurate description is provided by our model. It is seen that the coupling of bacterial motility to the fluid dynamics significantly alters the phase space of surfactant driven pattern formation. We also show that our formalism is applicable across bacterial species.

physics.bio-ph↗

arXiv2018

A Null-model Exhibiting Synchronized Dynamics in Uncoupled Oscillators

The phenomenon of phase synchronization of oscillatory systems arising out of feedback coupling is ubiquitous across physics and biology. In noisy, complex systems, one generally observes transient epochs of synchronization followed by non-synchronous dynamics. How does one guarantee that the observed transient epochs of synchronization are arising from an underlying feedback mechanism and not from some peculiar statistical properties of the system? This question is particularly important for complex biological systems where the search for a non-existent feedback mechanism may turn out be an enormous waste of resources. In this article, we propose a null model for synchronization motivated by expectations on the dynamical behaviour of biological systems to provide a quantitative measure of the confidence with which one can infer the existence of a feedback mechanism based on observation of transient synchronized behaviour. We demonstrate the application of our null model to the phenomenon of gait synchronization in free-swimming nematodes, C. elegans.

physics.bio-ph↗

arXiv2018

Spatial Awareness of a Bacterial Swarm

Bacteria are perhaps the simplest living systems capable of complex behaviour involving sensing and coherent, collective behaviour an example of which is the phenomena of swarming on agar surfaces. Two fundamental questions in bacterial swarming is how the information gathered by individual members of the swarm is shared across the swarm leading to coordinated swarm behaviour and what specific advantages does membership of the swarm provide its members in learning about their environment. In this article, we show a remarkable example of the collective advantage of a bacterial swarm which enables it to sense inert obstacles along its path. Agent based computational model of swarming revealed that independent individual behaviour in response to a two-component signalling mechanism could produce such behaviour. This is striking because independent individual behaviour without any explicit communication between agents was found to be sufficient for the swarm to effectively compute the gradient of signalling molecule concentration across the swarm and respond to it.

physics.bio-ph↗