Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2017 Oct 18;37(42):10114–10124. doi: 10.1523/JNEUROSCI.0448-17.2017

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Copyright © 2017 the authors 0270-6474/17/3710114-11$15.00/0

PMC Copyright notice

Figure 4. — Neuron network model with the ability of neurons to go offline captures the differential decline of long-range temporal correlations. The network was instantiated at a connectivity K = 1 and with different probablities p_OFFLINE for neurons to go offline for a brief amount of time in an asynchronous (a–f) or synchronous (g–i) manner. a, Raster plot without the presence of offline periods. b, Raster plot with asynchronous offline periods (p_OFFLINE = 0.1, gray shaded areas). c, Autocorrelation functions for spiking activity in a network without offline periods (p_OFFLINE = 0, blue) and in a network with asynchronous offline periods (p_OFFLINE = 0.1, red) in neuron activity. d, Autocorrelation decay rates increase with higher probability for asynchronous offline periods. e, Recovery from intrinsic fluctuations (p_OFFLINE = 0, blue; p_OFFLINE = 0.1, red). f, Recovery rates from intrinsic fluctuations increase with higher probability for asynchrnous offline periods. g, Raster plot with synchronous offline periods (gray shaded areas). h, i, Autocorrelation decay and recovery rates from intrinsic fluctuations increase with higher probability for synchronous offline periods.