GP Kernels for Cross-Spectrum Analysis
Authors: Kyle R. Ulrich, David E. Carlson, Kafui Dzirasa, Lawrence Carin
NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Results are presented for measured multi-region electrophysiological data. Section 6 analyzes the performance of this approximation and presents results for the CSM kernel in the neuroscience application, considering measured multi-region LFP data from the brain of a mouse. |
| Researcher Affiliation | Academia | 1Department of Electrical and Computer Engineering, Duke University 2Department of Psychiatry and Behavioral Sciences, Duke University 3Department of Statistics, Columbia University |
| Pseudocode | No | The paper describes the mathematical formulations and inference steps but does not include explicit pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide a statement about releasing code or a link to a code repository. |
| Open Datasets | No | The paper mentions 'measured multi-region electrophysiological data' and '12 hours of LFP data of a mouse transitioning between different stages of sleep [7, 21]', citing previous works, but does not provide concrete access information (link, DOI, or explicit statement of public availability) for the dataset used in this paper's experiments. |
| Dataset Splits | No | The paper describes the data and its processing (e.g., 'Using 3 second windows provides N = 600 and W = 14, 400'), but does not specify any train/validation/test splits for reproducibility. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | Observations were recorded simultaneously from 4 channels [6], high-pass filtered at 1.5 Hz, and subsampled to 200 Hz. Using 3 second windows provides N = 600 and W = 14, 400. The HMM was implemented with the number of kernel components Q = 15 and the number of states L = 7. A CSM kernel is defined for two outputs with a single Gaussian component, Q = 1. The mean frequency and variance for this component are set to push the limits of the application. For example, with LFP data, low frequency content is of interest, namely greater than 1 Hz; therefore, we test values of eµ1 { 1 2, 1, 3} Hz. We anticipate variances at these frequencies to be around eν1 = 1 Hz2. A conversion to angular frequency gives µ1 = 2πeµ1 and ν1 = 4π2eν1. The covariance matrix Γ in (3) is formed using these parameters, a fixed noise variance, and N observations on a time grid with sampling rate of 200 Hz. |