Department of Computer Science & Engineering

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IIT Jodhpur

School of Artificial Intelligence and Data Science (AIDE)

An analysis of Pradhan Mantri Bhartiya Janaushadhi Parijoyana, a Government of India scheme which aims to provide quality generic medicines at affordable prices, is performed using a stylized model. There is distrust on the quality of generic medicines provided by the government and the government is taking enough measures to counter this perception. However, this distrust ensures that adverse selection is avoided wherein the poor patients become the scheme's beneficiaries and the wealthy patients don't intend to get generic medicines from this scheme. Hence, it is rational for the government to expend limited effort in creating awareness on the high quality of generic medicines so as to screen the wealthy patients from the poor patients. However, the government should exert maximum effort possible in ensuring the availability of generic medicines so that the search cost is minimized. It is surprisingly found that the government's effort required to screen the wealthy patients from the poor patients decreases with the availability of generic medicines. © 2021 Elsevier Ltd

World University root node

Socio-Economic Planning Sciences

Averting adverse selection: The Government of India's scheme to distribute affordable medicines

Our aim in this article is two-fold. We use the Charnes–Cooper scalarization technique to develop KKT type conditions to completely characterize Pareto minimizers of convex vector optimization problems and further, we use that scalarization technique to develop a simple and efficient algorithm for convex vector optimization problems. Numerical examples are presented to illustrate the use of our algorithm. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Fulltext

Optimization Letters

Charnes–Cooper scalarization and convex vector optimization

This article presents behavior and EEG dataset collected from 19 healthy human volunteers (10 females) in the age group of 21–29 (mean = 26.9, SD = ±2.15) years at National Brain Research Centre, India during a psychophysical paradigm customized to characterize the brain network interactions during saliency processing. We provide all the raw stimulus files used in developing the experimental paradigm of the linked research article “Organization of directed functional connectivity among nodes of ventral attention network reveals the common network mechanisms underlying saliency processing across distinct spatial and spatio-temporal scales” [1] for replication and use by researchers across various cohorts of the population. Pre-processed EEG time-series segmented into epochs corresponding to three experimental trial conditions, across two visual attention tasks testing the effect of salient distractors on goal-driven tasks are provided. The dataset also includes reaction times corresponding to individual trials. Additionally, structural MRI files corresponding to each individual and 3D EEG sensor locations of all volunteers are provided to assist in accurate source localization. Therefore, the presented dataset will not only facilitate the conventional time resolved EEG analysis like evoked activity and time-frequency analysis at the sensor level but will also facilitate the investigation of source level analysis like global coherence or phase-amplitude coupling within selected regions of the brain. © 2021 The Authors

Data in Brief

Psychophysical data to study the brain network mechanisms involved in reorienting attention to salient events during goal-directed visual discrimination and search tasks

Previous neuroimaging studies have extensively evaluated the structural and functional connectivity of the Ventral Attention Network (VAN) and its role in reorienting attention in the presence of a salient (pop-out) stimulus. However, a detailed understanding of the “directed” functional connectivity within the VAN during the process of reorientation remains elusive. Functional magnetic resonance imaging (fMRI) studies have not adequately addressed this issue due to a lack of appropriate temporal resolution required to capture this dynamic process. The present study investigates the neural changes associated with processing salient distractors operating at a slow and a fast time scale using custom-designed experiment involving visual search on static images and dynamic motion tracking, respectively. We recorded high-density scalp electroencephalography (EEG) from healthy human volunteers, obtained saliency-specific behavioral and spectral changes during the tasks, localized the sources underlying the spectral power modulations with individual-specific structural MRI scans, reconstructed the waveforms of the sources and finally, investigated the causal relationships between the sources using spectral Granger-Geweke Causality (GGC). We found that salient stimuli processing, across tasks with varying spatio-temporal complexities, involves a characteristic modulation in the alpha frequency band which is executed primarily by the nodes of the VAN constituting the temporo-parietal junction (TPJ), the insula and the lateral prefrontal cortex (lPFC). The directed functional connectivity results further revealed the presence of bidirectional interactions among prominent nodes of right-lateralized VAN, corresponding only to the trials with saliency. Thus, our study elucidates the invariant network mechanisms for processing saliency in visual attention tasks across diverse time-scales. © 2021 The Author(s)

NeuroImage

Organization of directed functional connectivity among nodes of ventral attention network reveals the common network mechanisms underlying saliency processing across distinct spatial and spatio-temporal scales

We use a debiased Machine Learning technique to explore causes behind infant malnutrition for households below-poverty-line in India and examine effectiveness of various government interventions along with other factors. Our analysis reveals that access to clean water is one of the most crucial issues to focus on. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Applied Economics Letters

Infant malnutrition, clean-water access and government interventions in India: a machine learning approach towards causal inference

The sensorimotor beta rhythm (∼13–30 Hz) is commonly seen in relation to movement. It is important to understand its functional/ behavioral significance in both health and disease. Sorting out competing theories of sensorimotor beta is hampered by a paucity of experimental protocols in humans that manipulate/induce beta oscillations and test their putative effects on concurrent behavior. Here, we developed a novel behavioral paradigm to generate beta and then test its functional relevance. In two human experiments with scalp EEG (n = 11 and 15), we show that a movement instruction generates a high beta state (postmovement beta rebound), which then slows down subsequent movements required during that state. We also show that this high initial beta rebound related to reduced mu–beta desynchronization for the subsequent movement and, further, that the temporal features of the beta state, that is, the beta bursts, related to the degree of slowing. These results suggest that increased sensorimotor beta in the postmovement period corresponds to an inhibitory state—insofar as it retards subsequent movement. By demonstrating a behavioral method by which people can proactively create a high beta state, our paradigm provides opportunities to test the effect of this state on sensations and affordances. It also suggests related experiments using motor imagery rather than actual movement, and this could later be clinically relevant, for example, in tic disorder. © 2021 Massachusetts Institute of Technology.

Journal of Cognitive Neuroscience

Behavioral induction of a high beta state in sensorimotor cortex leads to movement slowing

We consider an M/M/1 high-contact service queue with unknown service rates. Two types of customers, informed and uninformed, making strategic balking decisions, queue at the facility. We find that informed customers follow a threshold strategy and uninformed customers follow a non-threshold strategy in equilibrium. We suggest that the firm should incentivize the fast server such that the quality of service is not compromised. © 2021 Elsevier B.V.

Operations Research Letters

To incentivize the fast server or not? Firm's dilemma when queue signals service rate in high-contact services

A general entropy framework is proposed, which could lead to intuitive, interpretable and comparable entropy functions in both probabilistic or fuzzy domain, alike. Based on the proposed general entropy framework, the existing fuzzy entropy functions are redefined. The proposed entropy functions are also extended to the probabilistic-fuzzy domain. The usefulness of the work is shown in a real world case-study. © 2020 Elsevier Ltd

Expert Systems with Applications

Redefining fuzzy entropy with a general framework

A complete picture of how subcortical nodes, such as the thalamus, exert directional influence on large-scale brain network interactions across age remains elusive. Using directed functional connectivity and weighted net causal outflow on resting-state fMRI data, we provide evidence of a comprehensive reorganization within and between neurocognitive networks (default mode: DMN, salience: SN, and central executive: CEN) associated with age and thalamocortical interactions. We hypothesize that thalamus subserves both modality-specific and integrative hub role in organizing causal weighted outflow among large-scale neurocognitive networks. To this end, we observe that within-network directed functional connectivity is driven by thalamus and progressively weakens with age. Secondly, we find that age-associated increase in between CEN- and DMN-directed functional connectivity is driven by both the SN and the thalamus. Furthermore, left and right thalami act as a causal integrative hub exhibiting substantial interactions with neurocognitive networks with aging and play a crucial role in reconfiguring network outflow. Notably, these results were largely replicated on an independent dataset of matched young and old individuals. Our findings strengthen the hypothesis that the thalamus is a key causal hub balancing both within- and between-network connectivity associated with age and maintenance of cognitive functioning with aging. © 2020 The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Cerebral Cortex

Reconfiguration of Directed Functional Connectivity among Neurocognitive Networks with Aging: Considering the Role of Thalamo-Cortical Interactions

This article uses a nation-wide household survey data from India and identifies important predictors of neonatal and infant mortality using multiple machine learning (ML) techniques. The consensus on the leading predictors from the interpretable ML algorithms (that we use) serve as early warning signs of neonatal and infant mortality. This enables us to identify a ‘high-mortality risk’ group of mothers and infants–an important goal of India’s ‘India Newborn Action Plan’. This high-risk group comprises firstborns, mothers with prior deaths or several previous births, newborns suffering from complicated deliveries, small size at birth and unvaccinated infants. We identify early newborn care, folic acid supplements and conditional cash transfer (Janani Suraksha Yojana) as the most effective policy interventions. Given the imbalanced nature of the dependent variable (‘events’ being rarer than ‘non-events’) we use additional ML methods (along with the commonly used ones) that are tailor-made for ‘rare-event’ prediction for robustness checks. We also use an evaluation measure called Area under Precision Recall Curve that is tailored for measuring prediction accuracy with imbalanced data. Our analysis sheds light on policy relevance and suggests some new policy prescriptions such as close monitoring of at-risks babies including females and those with small birth-size. © 2021 Informa UK Limited, trading as Taylor & Francis Group.