Data · dataset · 2026
<p>Criticality after development.</p>
Listed in UCL Research Data Repository
Description
<p><b>(A)</b> Spike raster plots showing the firing patterns of a sample network prototype across the grid of and after 15 hours of development. <b>(B)</b> Frequency of avalanches plotted against their respective size (blue points: evenly spaced binning, red points: 20 log binning) along with the corresponding power-law fit (solid line), illustrating the calculation of , which is the mean error between the observed frequencies and the power-law fit.
The three plots correspond to the highlighted raster plots in panel A and summarize the final 5 minutes of activity in each of these networks. Inset: Exponent <i>𝛼</i> and criticality outcome . <b>(C)</b> Distribution of across the grid of and . was calculated in each run of each network from activity between 13 and 15 hours. Boxes show quartiles, with whiskers extending to points within 1.5 times the interquartile range.
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Boxes are clustered by the (categorical) value of and color-coded by . Each box summarizes 5 runs 10 networks created from a pair of r_inh and . <b>(D)</b> The mean of across all runs in each grid cell in two sample networks. <b>(E)</b> The criticality relation plotted against , with color indicating individual network prototypes. Connected stars: median trace of criticality relation plotted at 20 linearly spaced bin centers with black stars. <b>(F, G)</b> Fano factors plot. <b>F</b>: 𝐹(𝑇) calculated across a range of 1 to 100 ms. 𝐹(𝑇) plotted against bin size 𝑇, showing power-law scaling up to about 30-40 ms.
Each line corresponds to a network instantiation, colors are arbitrary. Inset plots normalizing each curve to the minimum (upper left, 1 ms) and maximum (lower right, 99 ms) interval investigated. <b>G</b>: Exponents of the power-law fit across the parameter space (color-coded by in the same style as panel <b>C)</b>, showing a clear progression towards lower exponents with increased inhibitory density and radius.</p>
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Where it is published
- DOI doi.org/10.1371/journal.pcbi.1014798.g004 ↗
DOI / persistent id · from rdr ucl ac uk
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from rdr ucl ac uk
Topics
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| UCL Research Data Repository | oai:figshare.com:article/34049623 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:320211 | mapping · rdr ucl ac uk | vocabulary-mapper@1.0.0 | keywords['Infectious Diseases'] |
| concepts[field].local:field:earth-environmental | mapping · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| description | source · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| title | source · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | /metadata/dc/title |