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Open-source · MIT · Peer-reviewed

Theplatformforbrain organoid analysis

Open-source analysis platform for brain organoid electrophysiology. 9 peer-reviewed methods — from spike sorting to criticality assessment.

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Peer-Reviewed Methods
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Literature References

Capabilities

Everything you need to work with organoid electrophysiology

Visualization

Visualize spike activity

Interactive raster plots, firing rate heatmaps, and spike waveforms across all electrodes and time ranges.

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Analysis

Characterize neural dynamics

Burst detection (Bakkum 2013), criticality assessment (Clauset et al. 2009), and IIT Phi computation — in one click.

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Connectivity

Map functional connectivity

Cross-correlation, transfer entropy (Schreiber 2000), Granger causality, and graph-theoretic metrics. All with significance testing.

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Workflow

From zero to neural experiments

01

Upload

Load spike data from any MEA system — CSV, HDF5, NWB, or Parquet. Or use our FinalSpark demo dataset.

02

Analyze

9 analysis modules run automatically: bursts, connectivity, criticality, emergence, metastability, and more.

03

Compare

Stage your organoid against 10 reference neural systems across 15 electrophysiological metrics.

04

Publish

Export JSON reports and analysis parameters. All methods fully cited for reproducibility.

Methods

Every module grounded in peer-reviewed literature

Burst Detection
MaxInterval (Bakkum 2013), Rank Surprise (Legendy & Salcman 1985), Poisson Surprise
Connectivity
Cross-correlation, Transfer Entropy (Schreiber 2000), Granger causality, PLV, Mutual Information
Criticality
Power-law fitting (Clauset et al. 2009), Branching ratio, DFA (Beggs & Plenz 2003)
Emergence
IIT Phi (Tononi 2004), Queyranne MIP, PID (Williams & Beer 2010), Causal Emergence (Hoel 2013)
Metastability
Kuramoto order parameter (Shanahan 2010), FCD (Deco & Kringelbach 2016)
Temporal Prediction
Differential response analysis: Markov transitions, prediction error signals, Bayesian surprise. Bonferroni correction + Cohen's d. Speculative without closed-loop
State Transitions
HMM Baum-Welch for bistable dynamics, Lomb-Scargle periodogram, Cosinor (Sokolove & Bushell 1983). Detects network bistability, not sleep physiology
Complexity Index
6-dimension composite: signal quality, network complexity, information processing, temporal organization, adaptability, learning potential. Heuristic weights, not externally validated
Comparative
15 metrics × 10 reference systems (C. elegans, mouse hippocampus, rat cortex, DishBrain, and 6 others)
How to cite
Britikov, N. (2026). NeuroBridge: An Open-Source Platform for Multi-Dimensional Analysis of Brain Organoid Electrophysiology. GitHub. https://github.com/Luckyguybiz/neurobridge-api

Ready to analyze your organoid data?

Upload your MEA recordings or explore the FinalSpark demo dataset.