Mohammed A. Mostajo-Radji

PULSE, a foundation model trained on neural recordings, reveals how disease variants affect network development and how circuits encode information in brain organoids.

The paper introduces MYCEL, a graph neural network that improves decoding of brain anatomy from neuronal neighborhoods by learning local pooling, outperforming fixed aggregation on multiple datasets.

HIPPIE is a deep learning model that classifies neurons from electrophysiological recordings by combining self-supervised pretraining and supervised fine-tuning, showing better performance than unsupervised methods.

The paper presents a cloud-based pipeline for analyzing and visualizing neuronal electrophysiology data from HD-MEAs, demonstrating its utility in simplifying data analysis and understanding neural activity.

This paper develops a cloud-connected stem cell platform to enhance scientific identity in underrepresented students, showing improved outcomes in competence and research readiness.

This paper develops a 3D-printed, servo-actuated microvalve system for automated organoid culture, validated in mouse and human models with comparable viability and gene expression to manual methods.

This study develops a microfluidic platform to induce spatially segregated ventral and dorsal domains in mouse forebrain organoids without fusion, enabling study of tissue regionalization.

This study uses mouse forebrain organoids to show how variations in cellular composition influence the self-organization of neural circuits, revealing intrinsic principles of forebrain circuit assembly.

This paper introduces an automated in-incubator microscope for long-term live cell imaging, enabling high-frequency, continuous data collection with improved thermal stability and operational reliability.

This study demonstrates goal-directed learning in cortical organoids using a closed-loop electrophysiology framework and artificial reinforcement learning.

CytoVerse enables browser-based single-cell analysis using Foundation Models by deploying models in ONNX, compressed indexing, and secure embedding sharing.

This study shows that structured firing sequences emerge in human and murine brain organoids and neonatal brain slices, suggesting innate rather than experience-dependent neural coding.

This paper introduces a sealed recirculatory system for organoid culture that eliminates the need for CO2 incubators and enables continuous live imaging and metabolic viability.

This paper introduces an automated brain organoid platform with IoT integration for continuous monitoring and control, showing increased neural activity and stable firing rates during automated media exchange.

This study shows that the identity of MGE-derived cortical interneurons can be dynamically influenced by their environment, with human 3D models promoting Pvalb expression over Sst.

SIMS is a deep learning tool for single-cell RNA sequencing classification that outperforms existing methods in accuracy and versatility across complex tissues and developmental stages.

The paper introduces Piphys, an open-source platform for neural recording that enables remote control and scalability through cloud-based software and low-cost hardware.

In primary human cortical tissue and stem cell-derived organoids, SARS-CoV-2 infects astrocytes almost exclusively, apparently through DPP4 rather than ACE2, leaving them reactive and stressed.

The paper develops all-optical electrophysiology tools to record subthreshold dynamics and excitability in mouse hippocampus during behavior, revealing brain-state dependent changes in neuronal activity.

The paper uses chimpanzee cerebral organoids to identify human-specific genes in cortical development and finds increased PI3K/AKT/mTOR activation in human outer radial glia.