Directed Spectrum Measures Improve Latent Network Models Of Neural Populations
Authors: Neil Gallagher, Kafui Dzirasa, David Carlson
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate that latent linear factor models of DS measures better capture underlying brain networks in both simulated and real neural recording data compared to available alternatives. To test the effectiveness of the Directed Spectrum and LFMs, we generated a dataset of simulated latent networks. We next tested how effectively networks identified by the Directed Spectrum decode behaviorally relevant variables from a dataset of neural recordings. |
| Researcher Affiliation | Academia | Neil M. Gallagher Department of Neurobiology Duke University Durham, NC 27708 neil.gallagher@duke.edu Kafui Dzirasa Howard Hughes Medical Institute Department of Psychiatry and Behavioral Sciences Department of Neurobiology Duke University Durham, NC 27710 kafui.dzirasa@duke.edu David Carlson Department of Biostatistics and Bioinformatics Department of Civil and Environmental Engineering Duke University Durham, NC 27708 david.carlson@duke.edu |
| Pseudocode | No | Additional algorithmic details can be found in Supplemental Section F.1. |
| Open Source Code | Yes | Code for calculating the Directed Spectrum and Pairwise Directed Spectrum is provided in the supplemental material (MATLAB) and at https://github.com/neil-gallagher/directed-spectrum (Python). |
| Open Datasets | No | The dataset consists of local field potentials simultaneously recorded from 11 brain regions in 26 mice (originally published in [27]). |
| Dataset Splits | Yes | In order to obtain estimates of the spread of the decoding performance and choose optimal hyperparameter values, a 5-fold nested cross-validation procedure was used, where each mouse was associated with only one split. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU, GPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | Code for calculating the Directed Spectrum and Pairwise Directed Spectrum is provided in the supplemental material (MATLAB) and at https://github.com/neil-gallagher/directed-spectrum (Python). |
| Experiment Setup | Yes | The hyperparameters tuned during cross-validation were the number of NMF factors (20, 40, 80), NMF regularization strength (1000, 100, 10, 0), and logistic regression regularization strength (10, 1). |