Satrajit Ghosh

This study identifies and characterizes fifteen subnetworks within subcortical brain regions, revealing their functional organization and potential applications in understanding neuropsychiatric disorders.

The paper identifies recurring brain states during longitudinal viewing of a TV series, showing that the repertoire is individual-specific and adapts to narrative content.

This paper introduces a standards framework for integrating single-cell and spatial omics data into brain cell atlases, enabling interoperable and reusable knowledge-ready resources.

The paper presents a multimodal imaging pipeline that combines diffusion MRI and high-resolution X-ray microscopy to map the human connectome across multiple scales.

This paper presents the first extensive reconstruction of human subcortical fiber pathways using ultra-high-resolution dMRI, providing a high-definition atlas with clinical applications.

This paper presents high-resolution diffusion MRI data from macaque and human brains, enabling detailed mapping of axonal architecture and microstructure.

The paper uses preregistered movie-fMRI analyses to show reduced high-level visual representations and a shift toward low-level encoding in autism, particularly in the pSTS and social brain regions.

This study uses fMRI and HMM to show that narrative context modulates brain state dynamics and behavioral responses during story comprehension.

This study introduces a naturalistic reinforcement learning task to investigate neural representations during exploration, finding robust feedback history encoding in specific brain regions across two participant groups.

The paper defines AI-readiness criteria for biomedical data, encompassing seven dimensions, and evaluates them across flagship datasets to ensure ethical and explainable AI practices.

Neurodesk provides a portable and reproducible neuroimaging analysis platform using software containers to enable accessible and flexible data analysis pipelines.

The paper introduces BABS, a Python package for reproducible and scalable neuroimaging data processing using BIDS Apps and HPC systems.

This paper describes OME-Zarr, a cloud-optimized bioimaging file format developed through community collaboration to improve scalability and data access.

TemplateFlow provides a FAIR framework for sharing and managing multi-scale, multi-species brain models to improve reproducibility in neuroimaging.

The paper provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

Neuroscout provides an automated platform for analyzing naturalistic fMRI data, enabling reproducible and generalizable research through machine learning and open tools.

The paper describes the Neurodata Without Borders (NWB) ecosystem, which enables FAIR neurophysiological data management and analysis across species and modalities.

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.

The paper introduces MindLogger, an open-source platform for creating mobile mental health assessments and interventions, demonstrating its use in a large-scale study.

The paper investigates interhemispheric functional symmetry in human subcortical structures using fMRI data, finding that direct cortical connectivity correlates with stronger subcortical symmetry in some regions, while connectivity to symmetric cortical areas correlates with symmetry in others.

This paper introduces fMRIPrep, a tool for preprocessing task-based fMRI data, and demonstrates its integration into a workflow for statistical analysis.

The paper maps the human subcortical auditory system using histology, post mortem MRI, and in vivo 7T MRI, creating atlases and connectivity maps with high-resolution data.

LittleBrain visualizes cerebellar neuroimaging data along newly identified functional gradients to enhance topographical interpretation.

fMRIPrep, a BIDS-driven, self-adapting fMRI preprocessing pipeline, earned above-acceptable expert quality ratings on 50 of 54 OpenfMRI datasets and introduced less smoothing than FSL feat.

The paper identifies two functional gradients in the cerebellum using diffusion map embedding on resting-state data, revealing a progression from motor to transmodal regions and task-unfocused to task-focused processing.

This paper introduces BIDS Apps, a framework for creating portable neuroimaging analysis tools compatible with BIDS data, improving reproducibility and ease of use.

Open source Mindboggle pipeline extracts cortical folds, sulci and fundi and computes diverse shape measures, yielding normative morphometry for 101 manually labeled healthy human brains.

The paper provides a resource to evaluate test-retest reliability of functional connectivity across different scan conditions and sessions in a healthy brain network.

This paper introduces NIDM-Results, a standardized format for sharing neuroimaging statistical results, enabling reproducibility and meta-analysis.

This paper reviews the application of Linked Data principles in neuroscience to organize data, enhance credibility, and improve data reuse.