Convolutional spike-triggered covariance analysis for neural subunit models
Authors: Anqi Wu, Il Memming Park, Jonathan W. Pillow
NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we analyze neural data from macaque primary visual cortex and show that our moment-based estimator outperforms a highly regularized generalized quadratic model (GQM), and achieves nearly the same prediction performance as the full maximum-likelihood estimator, yet at substantially lower cost. |
| Researcher Affiliation | Academia | 1 Princeton Neuroscience Institute, Princeton University {anqiw, pillow}@princeton.edu 2 Department of Neurobiology and Behavior, Stony Brook University memming.park@stonybrook.edu |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statements about open-source code availability or links to repositories for the methodology described. |
| Open Datasets | Yes | we applied LS, MELE and MLE estimators to data from a population of 57 V1 simple and complex cells (data published in [11]). [11] Nicole C. Rust, Odelia Schwartz, J. Anthony Movshon, and Eero P. Simoncelli. Spatiotemporal elements of macaque v1 receptive fields. Neuron, 46(6):945 956, Jun 2005. |
| Dataset Splits | No | The paper mentions training and testing data but does not explicitly describe a separate validation set or provide specific split percentages for validation. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used for running experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | Mean firing rate is 0.91 spk/s. In our estimation, each time bin stimulus with 40 dimensions is treated as one sample to generate spike response. The time bin size is 10 ms and the number of bars (d) is 16 in our experiment. Each subunit filter has a length of 5. All hyper parameters are chosen by cross validation. |