Data for: Emergence of the consonance pattern within synaptic weights of a neural network featuring Hebbian neuroplasticity

Published: 4 Oct 2017 | Version 1 | DOI: 10.17632/db8ncd664m.1
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Description of this data

MATLAB program code:

  • SweepHighToLow5Harmonics.m — Performs neural network training, sweeping the stimulus frequency from the highest to the lowest frequencies.
  • SweepLowToHigh5Harmonics.m — Performs neural network training, sweeping the stimulus frequency from the lowest to the highest frequencies.
  • Random5Harmonics.m — Performs neural network training with random stimulus frequency, which has a quasi-uniform probability distribution across the whole auditory spectrum.

Experiment data files

peer reviewed

This data is associated with the following peer reviewed publication:

Emergence of the consonance pattern within synaptic weights of a neural network featuring Hebbian neuroplasticity

Published in: Biologically Inspired Cognitive Architectures

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Previous versions

  • Version 1

    2017-10-04

    Published: 2017-10-04

    DOI: 10.17632/db8ncd664m.1

    Cite this dataset

    Pankovski, Toso; Pankovska, Eva (2017), “Data for: Emergence of the consonance pattern within synaptic weights of a neural network featuring Hebbian neuroplasticity”, Mendeley Data, v1 http://dx.doi.org/10.17632/db8ncd664m.1

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Categories

Computational Neuroscience

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Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?

This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.