Alex Spaeth

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.

SpikeLab is a text-to-analysis framework for neural spike data that ensures correct and reproducible results using agentic systems, outperforming other models in a controlled benchmark.

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

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.

The paper uses high-density electrophysiology to study epileptiform activity in human hippocampal slices from epilepsy patients, revealing unexpected network oscillations in dentate gyrus slices.

The paper introduces a new transfer function called Refractory SoftPlus to improve mean-field models of neuronal networks, enabling accurate predictions of network responses and bifurcation analysis without restrictive assumptions.