Publications by Ekansh Sareen | EPFL Graph Search

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The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

The Graph Laplacian Mixture Model (GLMM) allows to infer multiple underlying graph structures from multivariate time series data. Given its effectiveness in identifying brain states from brain activity measured by functional magnetic resonance imaging (fMR ...

The spinal cord plays a central role in regulating sensorimotor functions through complex neural pathways. However, detailed investigation of these mechanisms remains a developing field. In this study, we propose a multimodal approach combining transcrania ...

Functional connectivity (FC) between brain regions as manifested via fMRI entails signatures that can be used to differentiate individuals and decode cognitive tasks. In this work, we use methods from graph structure inference to estimate FC, which is in c ...

Ekansh Sareen

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Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

Revealing Brain and Spinal Cord Functional Networks by Block-Structured Graph Laplacian Mixture Models

Improved Spinal Cord FMRI Activation Mapping Using Regularized Hemodynamic Deconvolution

Joint Subject-Identification and Task-Decoding From Inferred Functional Brain Graphs Via a Multi-Task Neural Network