# Sparse Graphical Models for Functional Connectivity Networks: Best Methods and the Autocorrelation Issue

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/sparse-graphical-models-for-functional-connectivity-networks-best-methods-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yunan Zhu,Ivor Cribben |
| Citations | 39 |
| DOI | 10.1089/brain.2017.0511 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2952839475 |
| PMID | 29634321 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Ivor Cribben](https://scholariq.org/researchers/ivor-cribben/)

## Paper primary topic

- [Functional Brain Connectivity Studies](https://scholariq.org/topics/functional-brain-connectivity-studies/)

## Paper topics

- [Functional Brain Connectivity Studies](https://scholariq.org/topics/functional-brain-connectivity-studies/)
- [Neural dynamics and brain function](https://scholariq.org/topics/neural-dynamics-and-brain-function/)
- [Advanced MRI Techniques and Applications](https://scholariq.org/topics/advanced-mri-techniques-and-applications/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.