# Citation

Arjen Stolk, Sandon Griffin, Roemer van der Meij, Callum Dewar, Ignacio Saez, Jack J. Lin, Giovanni Piantoni, Jan-Mathijs Schoffelen, Robert T. Knight, Robert Oostenveld (2018).
Integrated analysis of anatomical and electrophysiological human intracranial data [Data set].
http://hdl.handle.net/11633/di.dccn.DSC_3015000.00_734.

# Abstract

The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI.  However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges.  Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software.  Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations.  The protocol is directly integrated with an open source toolbox for electrophysiological data analysis (FieldTrip).  This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and employed by a large research community.  We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets.  We explain how the protocol can be largely automated and readily adjusted to iEEG data sets with other characteristics.  The protocol can be implemented by a graduate student or post-doctoral fellow with minimal MATLAB experience and takes approximately an hour, excluding the automated cortical surface extraction.

This collection contains the data described in the protocol and that can be used to replicate all results.

# Background information

You can find more information, including relevant publications pertaining to this dataset on the collection overview page at http://hdl.handle.net/11633/di.dccn.DSC_3015000.00_734.

A complete list of files that are part of this dataset can be found in the file MANIFEST.txt, including a SHA256 hash for each file to allow verification of correct data transfer.

# Restrictions on data access and reuse 

The access to and use of this dataset is only allowed under the conditions listed in the data use agreement, as detailed in the file LICENSE.txt. 

Neither the Donders Institute or Radboud University, nor the researchers that provide this dataset should be included as an author of publications or presentations if this authorship would be based solely on the use of this data. 

However, we ask you to acknowledge the use of the data and data derived from the data when publicly presenting any results or algorithms that benefitted from their use:

    1) Papers, book chapters, books, posters, oral presentations, and all other presentations of results derived from the data should acknowledge the origin of the data as follows: "Data were provided (in part) by the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen".
    2) Authors of publications or presentations using the data should cite relevant publications describing the methods developed and used by the Donders Institute to acquire and process the data. The specific publications that are appropriate to cite in any given study will depend on what the data were used for and for what purposes. When applicable, a list of publications will be specified on the collection overview page.