Resources

Epylib

Epylib is an open-source Python software for exploring, visualizing, and analyzing human intracranial EEG recordings from drug-resistant epilepsy patients. Epylib is available on GitHub and is distributed under the General Public License version 2. When citing, please use:

If you use Epylib, please reference the following research paper:

  • Vila-Vidal, Manel, Alessandro Principe, Miguel Ley, Gustavo Deco, Adrià Tauste Campo, and Rodrigo Rocamora. “Detection of Recurrent Activation Patterns across Focal Seizures: Application to Seizure Onset Zone Identification.” Clinical Neurophysiology, vol. 128, no. 6, Jun. 2017, pp. 977-985, doi:10.1016/j.clinph.2017.03.040.

We also provide broadband and band-limited power time courses of 8 different seizures from an exemplary patient. Each file contains the instantaneous power time courses at different recording sites during an ictal event. Recordings comprise the ictal epoch along with 60 seconds of pre- and post-ictal activity shown for comparison. Each seizure is represented in 5 different frequency bands. The data can be downloaded from OSF and is distributed under the terms and conditions of license CC BY 4.0. When citing, please use:

DI-Inference for Python

Python software for the Detection of Non-linear Directional Couplings between Discrete Time Series. DI-Inference for Python is available on Github and is distributed under the General Public License version 2. When citing, please use:

This software is a translation of the DI-Inference software for Matlab by Adrià Tauste Campo. Reference publication:

  • Tauste Campo, Adrià, Yuriria Vázquez, Manuel Álvarez, Antonio Zainos, Román Rossi-Pool, Gustavo Deco, Ranulfo Romo. “Feed-forward information and zero-lag synchronization in the sensory thalamo-cortical circuit are modulated during stimulus perception.” PNAS, vol. 116, no. 15, Apr. 2019, pp. 7513-22, doi:10.1073/pnas.1819095116.

MUST Set and Toolbox

The MUST Toolbox is a MATLAB toolbox containing a set of functions to analyze the computational properties of musical stimuli saved in MIDI format. Functions to assess Balance, Contour, Symmetry and Complexity are provided. The MUST Toolbox is available on GitHub and is distributed under the General Public License version 3. When citing, please use:

A set of musical stimuli to be used together with the measures is accessible on OSF and is distributed under the General Public License version 3. When citing, please use:

  • Clemente, Ana, Manel Vila-Vidal, Marcos Nadal, Marcus T. Pearce, Guido Corradi, and Germán Aguiló. “MUST Set”. OSF, 2020, doi:10.17605/OSF.IO/73MNE.

If you use the MUST Toolbox or the stimuli, please make sure to reference the following research article:

  • Clemente, Ana, Manel Vila-Vidal, Marcus T. Pearce, Germán Aguiló, Guido Corradi, and Marcos Nadal. “A Set of 200 Musical Stimuli Varying in Balance, Contour, Symmetry, and Complexity: Behavioral and Computational Assessments.” Behavior Research Methods, Feb. 2020, doi:10.3758/s13428-019-01329-8.

Geoloc

Geoloc is a python package that identifies the geolocalizable entities that appear in a text. Geoloc is available on GitHub. Additional information and examples of use can be found here: geoloc.github.io/geoloc/. Geoloc is distributed under Apache License 2.0.

When citing, please use:

  • Guigó Corminas, Roderic, Jorge L. Salcedo, Adrià San José Plana, Manel Vila-Vidal, and Josep Zapata García. Geoloc. v1.0. GitHub, 2015, github.com/GEOLOC/geoloc.