Maximum-entropy and representative samples of neuronal activity: a dilemma
PierGianLuca Porta ManaiD, Vahid RostamiiD, Emiliano TorreiD, Yasser RoudiiD
Abstract
The present work shows that the maximum-entropy method can be applied to a sample of neuronal recordings along two different routes: (1) apply to the sample; or (2) apply to a larger, unsampled neuronal population from which the sample is drawn, and then marginalize to the sample. These two routes give inequivalent results. The second route can be further generalized to the case where the size of the larger population is unknown. Which route should be chosen? Some arguments are presented in favour of the second. This work also presents and discusses probability formulae that relate states of knowledge about a population and its samples, and that may be useful for sampling problems in neuroscience.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Random versus maximum entropy models of neural population activity
Ulisse Ferrari, Tomoyuki Obuchi, Thierry Mora·Physical review. EPeer-reviewed·Apr 27, 2017
- Natural gradient enables fast sampling in spiking neural networks
Paul Masset, Jacob A. Zavatone-Veth, … Cengiz Pehlevan·neural information processing systemsPeer-reviewed·Jan 1, 2022
- Quantifying the information about uncertainty in neural population codes
Xiaolu Wang, Peter Dayan, Paul M. Bays·bioRxiv·Jul 20, 2026
- A quick and easy way to estimate entropy and mutual information for neuroscience
Mickaël Zbili, Sylvain Rama·Frontiers in NeuroinformaticsPeer-reviewed·Jun 15, 2021
- Thermodynamic analog of integrate-and-fire neuronal networks by maximum entropy modelling
Tiago da Silva Alves de Nogueira Simões, Cesar I. N. Sampaio Filho, … L. de Arcangelis·Scientific ReportsPeer-reviewed·Apr 25, 2024
- Consistent estimation of complete neuronal connectivity in large neuronal populations using sparse "shotgun" neuronal activity sampling
Yuriy Mishchenko·bioRxiv·Nov 20, 2015