Shyam Diwakar
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Community-Based Action Research Approaches, Environmental Conservation, Economic Development, and Ethical Tensions: Reflections on Work in Peru and India Open
Community-based action research (CBAR) is designed to facilitate community members’ identification of challenges in their lives, as well as to collaboratively develop ways to confront those challenges. It is also designed to be an inherent…
Interconnections and global transitions among functional states encode activity-related dynamics as brain topology changes after yoga training Open
With the emphasis on sustainable health, understanding the neural dynamics associated with sustainable practices such as widely practiced yoga has gained significant importance. In this work, we explored the underlying neural mechanisms of…
View article: Predicting Markers of Cognitive Decline within Small Population Samples of Daily Life Activities
Predicting Markers of Cognitive Decline within Small Population Samples of Daily Life Activities Open
Lifestyle markers associated with health can be used to predict decline in cognitive function among individuals. The objective of this study was to investigate how lifestyle factors assessed from data surveys impact decline in cognitive fu…
Enhanced Spin Pumping and Magnetization dynamics in Ni$_{80}$Fe$_{20}$/MoS$_2$ stack via interface modification Open
Materials with strong spin orbit coupling (SOC) are essential for realizing spin orbit torque (SOT) based magnetic memory devices. Transition metal dichalcogenides (TMDs) are promising candidates for such appli cations because of their inh…
View article: DiversityOne: A Multi-Country Smartphone Sensor Dataset for Everyday Life Behavior Modeling
DiversityOne: A Multi-Country Smartphone Sensor Dataset for Everyday Life Behavior Modeling Open
Understanding everyday life behavior of young adults through personal devices, e.g., smartphones and smartwatches, is key for various applications, from enhancing the user experience in mobile apps to enabling appropriate interventions in …
Early Research Trends on ChatGPT: Insights from Altmetrics and Science Mapping Analysis Open
In the four months following its launch in December 2022, ChatGPT, the LLM bot employing deep learning algorithms to generate human-like responses, has been the subject of numerous research articles. Identifying early attention to this res…
View article: Diversity and neocolonialism in Big Data research: Avoiding extractivism while struggling with paternalism
Diversity and neocolonialism in Big Data research: Avoiding extractivism while struggling with paternalism Open
The extractive logic of Big Data-driven technology and knowledge production has raised serious concerns. While most criticism initially focused on the impacts on Western societies, attention is now increasingly turning to the consequences …
Early research trends on ChatGPT: a review based on Altmetrics and science mapping analysis Open
In the three months following its launch in November 2022, ChatGPT, the LLM bot employing deep learning algorithms to generate human-like responses, has been the subject of numerous research articles (n=385). Identifying early attention to…
View article: LEVERAGING OR EXPLOITING? BREAKING THROUGH DATA COLONIALISM AND ETHNOCENTRISM WHEN BUILDING A DIVERSITY-AWARE SOCIAL PLATFORM.
LEVERAGING OR EXPLOITING? BREAKING THROUGH DATA COLONIALISM AND ETHNOCENTRISM WHEN BUILDING A DIVERSITY-AWARE SOCIAL PLATFORM. Open
The extractive logic of data-driven technology and knowledge production has raised serious concerns. While this discourse initially focused on the impact on Western societies, attention is increasingly turning to the consequences for count…
View article: Generalization and Personalization of Mobile Sensing-Based Mood Inference Models
Generalization and Personalization of Mobile Sensing-Based Mood Inference Models Open
Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in m…
A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction Open
Spiking neural networks were introduced to understand spatiotemporal information processing in neurons and have found their application in pattern encoding, data discrimination, and classification. Bioinspired network architectures are con…
View article: A multi-class logistic regression algorithm to reliably infer network connectivity from cell membrane potentials
A multi-class logistic regression algorithm to reliably infer network connectivity from cell membrane potentials Open
In neuroscience, the structural connectivity matrix of synaptic weights between neurons is one of the critical factors that determine the overall function of a network of neurons. The mechanisms of signal transduction have been intensively…
Exploring EEG spectral and temporal dynamics underlying a hand grasp movement Open
For brain-computer interfaces, resolving the differences between pre-movement and movement requires decoding neural ensemble activity in the motor cortex’s functional regions and behavioural patterns. Here, we explored the underlying neura…
Quantification of Epileptogenic Network From Stereo EEG Recordings Using Epileptogenicity Ranking Method Open
Introduction: Precise localization of the epileptogenic zone is very essential for the success of epilepsy surgery. Epileptogenicity index (EI) computationally estimates epileptogenicity of brain structures based on the temporal domain par…
Computational modelling of TNFα related pathways regulated by neuroinflammation, oxidative stress and insulin resistance in neurodegeneration Open
Computational and mathematical modelling towards understanding the structure and dynamics of biological systems has significantly impacted on translational neuroscience to face novel approaches toward neurological disorders such as Alzheim…
Correlations of Gait Phase Kinematics and Cortical EEG: Modelling Human Gait with Data from Sensors Open
Neural coding of gait intent and continuous gait kinematics have advanced brain computer interface (BCI) technology for detection and predicting human upright walking movement. However, the dynamics of cortical involvement in upright walki…
Innovation Adoption and Diffusion of Virtual Laboratories Open
Educational technology such as Virtual laboratories (VLs) are being perceived as sustainable solutions to growing concerns related to laboratory skill training i.e. delivering quality laboratory education to a large number of students due …
ReConvPy: Modeling Local Field Potentials of Cerebellum Granule Neurons using Repetitive Convolutions in Python Open
One of the main goals in today's computational neuroscience laboratories is the ability to construct ensemble population responses from bottom-up reconstructions that involve computationally-detailed single neuron models. As a modeler's to…
Computational analysis of EEG activity during stance and swing gait phases Open
Analysis of cortical electroencephalography (EEG) patterns may suggest novel neural dynamics related to healthy and diseased gait which could be critical for assessing neurological disorders. However, the dynamics of cortical involvement i…
Classification of Human Gait: Swing and Stance Phases using Sum-Vector Analysis Open
Recent advances in low-cost wearable sensors with methodologies, have opened up a promising future for gait analysis. By providing patient analysis with gait disorders from clinics to common people the analysis requires some form of précis…
Computational Exploration of Neural Dynamics Underlying Music Cues Among Trained and Amateur Subjects Open
Exploring the neural basis of music perception and processing has become relevant in neuroscience research for studying human cognition and emotion. Recently many neuroimaging studies have seen brain structure differences in responses to v…
Mathematical Modeling of fMRI BOLD responses related Nitric Oxide Production-Consumption and in the Cerebellum Granule Layer Open
Brain imaging techniques such as functional magnetic resonance imaging (fMRI) have allowed to study changes in neural circuit activity and behavioral functioning. Nitric Oxide (NO) production, consumption and diffusion define changes in ne…