"Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe." - Information and Links:

Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe. - Info and Reading Options

"Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe." and the language of the book is English.


“Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” Metadata:

  • Title: ➤  Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.
  • Authors:
  • Language: English

Edition Identifiers:

  • Internet Archive ID: pubmed-PMC4131428

AI-generated Review of “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.”:


"Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe." Description:

The Internet Archive:

This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28Frontiers%20in%20Computational%20Neuroscience%29" rel="nofollow">Frontiers in Computational Neuroscience</a>, <a href="//archive.org/search.php?query=journaltitle%3A%28Frontiers%20in%20Computational%20Neuroscience%29%20AND%20volume%3A%288%29" rel="nofollow">volume 8</a>.<h2>Abstract</h2>The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

Read “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.”:

Read “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” by choosing from the options below.

Available Downloads for “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.”:

"Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe." is available for download from The Internet Archive in "texts" format, the size of the file-s is: 17.71 Mbs, and the file-s went public at Mon Oct 06 2014.

Legal and Safety Notes

Copyright Disclaimer and Liability Limitation:

A. Automated Content Display
The creation of this page is fully automated. All data, including text, images, and links, is displayed exactly as received from its original source, without any modification, alteration, or verification. We do not claim ownership of, nor assume any responsibility for, the accuracy or legality of this content.

B. Liability Disclaimer for External Content
The files provided below are solely the responsibility of their respective originators. We disclaim any and all liability, whether direct or indirect, for the content, accuracy, legality, or any other aspect of these files. By using this website, you acknowledge that we have no control over, nor endorse, the content hosted by external sources.

C. Inquiries and Disputes
For any inquiries, concerns, or issues related to the content displayed, including potential copyright claims, please contact the original source or provider of the files directly. We are not responsible for resolving any content-related disputes or claims of intellectual property infringement.

D. No Copyright Ownership
We do not claim ownership of any intellectual property contained in the files or data displayed on this website. All copyrights, trademarks, and other intellectual property rights remain the sole property of their respective owners. If you believe that content displayed on this website infringes upon your intellectual property rights, please contact the original content provider directly.

E. Fair Use Notice
Some content displayed on this website may fall under the "fair use" provisions of copyright law for purposes such as commentary, criticism, news reporting, research, or educational purposes. If you believe any content violates fair use guidelines, please reach out directly to the original source of the content for resolution.

Virus Scanning for Your Peace of Mind:

The files provided below have already been scanned for viruses by their original source. However, if you’d like to double-check before downloading, you can easily scan them yourself using the following steps:

How to scan a direct download link for viruses:

  • 1- Copy the direct link to the file you want to download (don’t open it yet).
    • (a free online tool) and paste the direct link into the provided field to start the scan.
  • 2- Visit VirusTotal (a free online tool) and paste the direct link into the provided field to start the scan.
  • 3- VirusTotal will scan the file using multiple antivirus vendors to detect any potential threats.
  • 4- Once the scan confirms the file is safe, you can proceed to download it with confidence and enjoy your content.

Available Downloads

  • Source: Internet Archive
  • Internet Archive Link: Archive.org page
  • All Files are Available: Yes
  • Number of Files: 14
  • Number of Available Files: 14
  • Added Date: 2014-10-06 20:51:05
  • Scanner: Internet Archive Python library 0.7.2
  • PPI (Pixels Per Inch): 300
  • OCR: ABBYY FineReader 9.0

Available Files:

1- Text PDF

  • File origin: original
  • File Format: Text PDF
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070.pdf
  • Direct Link: Click here

2- Item Tile

  • File origin: original
  • File Format: Item Tile
  • File Size: 0.00 Mbs
  • File Name: __ia_thumb.jpg
  • Direct Link: Click here

3- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4131428_files.xml
  • Direct Link: Click here

4- JSON

  • File origin: original
  • File Format: JSON
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4131428_medline.json
  • Direct Link: Click here

5- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4131428_meta.sqlite
  • Direct Link: Click here

6- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4131428_meta.xml
  • Direct Link: Click here

7- DjVu

  • File origin: derivative
  • File Format: DjVu
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070.djvu
  • Direct Link: Click here

8- Animated GIF

  • File origin: derivative
  • File Format: Animated GIF
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070.gif
  • Direct Link: Click here

9- Abbyy GZ

  • File origin: derivative
  • File Format: Abbyy GZ
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070_abbyy.gz
  • Direct Link: Click here

10- DjVuTXT

  • File origin: derivative
  • File Format: DjVuTXT
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070_djvu.txt
  • Direct Link: Click here

11- Djvu XML

  • File origin: derivative
  • File Format: Djvu XML
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070_djvu.xml
  • Direct Link: Click here

12- Single Page Processed JP2 ZIP

  • File origin: derivative
  • File Format: Single Page Processed JP2 ZIP
  • File Size: 0.01 Mbs
  • File Name: PMC4131428-fncom.2014.00070_jp2.zip
  • Direct Link: Click here

13- Scandata

  • File origin: derivative
  • File Format: Scandata
  • File Size: 0.00 Mbs
  • File Name: PMC4131428-fncom.2014.00070_scandata.xml
  • Direct Link: Click here

14- Archive BitTorrent

  • File origin: metadata
  • File Format: Archive BitTorrent
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4131428_archive.torrent
  • Direct Link: Click here

Search for “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” in Libraries Near You:

Read or borrow “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” from your local library.

Buy “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” online:

Shop for “Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe.” on popular online marketplaces.



Find "Data-driven Inference Of Network Connectivity For Modeling The Dynamics Of Neural Codes In The Insect Antennal Lobe." in Wikipdedia