Resources
These resources include original and publicly available datasets that were standardised according to the CND data structure, as well as original analysis scripts and links to publicly available toolboxes for the analysis of continuous-event neural data. Note that each dataset should be used according to its own license and should be referenced as indicated by the authors in their original submission.
CNSP2023 lectures and tutorials
CNSP2022 lectures and tutorials
CNSP2021 lectures and tutorials
Continuous-event Neural Data data format
Please check out the CND specifications (Continuous-event Neural Data) and the documentation website. You can also refer to this paper for more detailed insights. Detailed insights on the format can be found in our Resource preparation guidelines and on the BYOData Preparation Guidelines| Datasets | |||
|---|---|---|---|
| Authors | Original Link | Paper | Download CND data |
| Broderick, Andreson, Di Liberto, Crosse and Lalor | EEG: Natural, reverse & cocktail party speech | Current Biology, 2018 | Download natural speech CND *** Download reverse speech CND Download cocktail party CND |
| Di Liberto, Pelofi, Bianco, Patel, Mehta, Herrero, de Cheveigné, Shamma and Mesgarani | EEG: Bach piano melodies | eLife, 2020 | Download CND dataset |
| Marion, Di Liberto, and Shamma | EEG: Music listening & imagery | J Neurosci, 2021 (Part I)
J Neurosci, 2021 (Part II) |
Download CND dataset |
| Brennan and Hale | EEG: Natural speech | PLoS ONE, 2019 | Download CND dataset |
| Das, Francart, Bertrand | EEG: Cocktail party speech | J Neural Eng, 2016 | Download CND dataset |
| Di Liberto, Attaheri, Goswami, et al. | EEG: Baby rhythm speech | Nature Communications, 2023 | Download CND dataset |
| Toolboxes | |||
| Link | Authors | Paper | Description |
| CNSP Resources GitHub and documentation |
Di Liberto, Nidiffer, Crosse, Zuk, Haro, Cantisani et al. | arXiv, 2023 | The CNSP analytic resources and guidelines for relating neural signals to continuous stimuli. |
| CNSP Data Browser (beta) |
Di Liberto et al. | arXiv, 2023 | An interactive MATLAB toolbox for data preprocessing, TRF and cross-correlation analyses, feature design, CND import/export, and data simulation. |
| mTRF-Toolbox (Domain-specific) |
Crosse, Di Liberto, Bednar & Lalor | Front Hum Neurosci, 2016 | A MATLAB toolbox for relating neural signals to continuous stimuli. |
| Eelbrain (Domain-specific) |
Brodbeck et al. | eLife, 2023
CNSP2021 slides |
A Python toolbox for relating neural signals to continuous stimuli. |
| NoiseTools | de Cheveigné et al. | Papers | A MATLAB toolbox for denoising and analysing continuous and event-related neural data. |
| EEGLAB (General purpose) |
Delorme & Makeig | J Neurosci Methods, 2004 | An interactive MATLAB toolbox for processing continuous and event-related neural data. |
| MNE (General purpose) |
Gramfort et al. | Front Neurosci, 2013 | A Python package for exploring, visualizing, and analyzing neural data. |
| PERMUTOOLS (General purpose) |
Crosse et al. | arXiv, 2024 | A MATLAB package for multivariate permutation testing and effect size measurement. |
| Other Useful References | |||
| Link | Authors | Description | Year |
| Front Neurosci paper | Crosse, Zuk, Di Liberto, Nidiffer, Molholm, Lalor | Linear Modeling of Neurophysiological Responses to Naturalistic Stimuli: Methodological Considerations for Applied Research. | 2021 |
| NeuroImage paper | Di Liberto, Nie, Yeaton, Khalighinejad, Shamma, Mesgarani | Neural representation of linguistic feature hierarchy reflects second-language proficiency. | 2021 |
| IEEE Trans Biomed Eng paper | Kulasingham, Simon | Algorithms for estimating time-locked neural response components in cortical processing of continuous speech. | 2022 |
| J Neural Eng paper | Thornton, Mandic, Reichenbach | Robust decoding of the speech envelope from EEG recordings through deep neural networks. | 2022 |
| Computational audiology resources | Barbour, Hohmann, Ntlhakana, Zeng, Buhl, Goehring, Warzybok, Wasmann | This initiative strives to highlight recent examples that illustrate the potential of a computational approach to audiology. computationalaudiology.com aims to become a central hub for sharing resources that are useful for researchers and clinicians. | 2020-present |