# Connectivity Inference from Neural Recording Data: Challenges, Mathematical Bases and Research Directions

arXiv: https://arxiv.org/abs/1708.01888 · HTML: https://mlsanity.com/paper/1708.01888/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Aug 2017.

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## Abstract (arXiv)

This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further identify critical open issues and possible research directions.