Standards for data acquisition and software‐based analysis of in vivo electroencephalography recordings from animals. A TASK1‐WG5 report of the AES/ILAE Translational Task Force of the ILAE

Electroencephalography (EEG)—the direct recording of the electrical activity of populations of neurons—is a tremendously important tool for diagnosing, treating, and researching epilepsy. Although standard procedures for recording and analyzing human EEG exist and are broadly accepted, there are no such standards for research in animal models of seizures and epilepsy—recording montages, acquisition systems, and processing algorithms may differ substantially among investigators and laboratories. The lack of standard procedures for acquiring and analyzing EEG from animal models of epilepsy hinders the interpretation of experimental results and reduces the ability of the scientific community to efficiently translate new experimental findings into clinical practice. Accordingly, the intention of this report is twofold: (1) to review current techniques for the collection and software‐based analysis of neural field recordings in animal models of epilepsy, and (2) to offer pertinent standards and reporting guidelines for this research. Specifically, we review current techniques for signal acquisition, signal conditioning, signal processing, data storage, and data sharing, and include applicable recommendations to standardize collection and reporting. We close with a discussion of challenges and future opportunities, and include a supplemental report of currently available acquisition systems and analysis tools. This work represents a collaboration on behalf of the American Epilepsy Society/International League Against Epilepsy (AES/ILAE) Translational Task Force (TASK1‐Workgroup 5), and is part of a larger effort to harmonize video‐EEG interpretation and analysis methods across studies using in vivo and in vitro seizure and epilepsy models.

[1]  Michael Norris,et al.  Design and development of medical electronic instrumentation : a practical perspective of the design, construction, and test of medical devices , 2004 .

[2]  Benjamin H. Brinkmann,et al.  Multiscale electrophysiology format: An open-source electrophysiology format using data compression, encryption, and cyclic redundancy check , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  E. Bertram CHAPTER 46 – Monitoring for Seizures in Rodents , 2006 .

[4]  M. Nuwer,et al.  American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2012 version. , 2013, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[5]  S. Qian,et al.  Joint time-frequency analysis : methods and applications , 1996 .

[6]  C. Martín del Campo,et al.  EEG Recording in Rodents, with a Focus on Epilepsy , 2009, Current protocols in neuroscience.

[7]  X. Wei,et al.  Infraslow EEG Changes in Infantile Spasms , 2014, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[8]  James S. Walker,et al.  A Primer on Wavelets and Their Scientific Applications, Second Edition , 2008 .

[9]  Emmanuel Ifeachor,et al.  Digital Signal Processing: A Practical Approach , 1993 .

[10]  H. Nyquist,et al.  Certain Topics in Telegraph Transmission Theory , 1928, Transactions of the American Institute of Electrical Engineers.

[11]  C. Binnie,et al.  Glossar der meistgebrauchten Begriffe in der klinischen Elektroenzephalographie und Vorschläge für die EEG-Befunderstellung , 2004 .

[12]  Christof Koch,et al.  Neurodata Without Borders: Creating a Common Data Format for Neurophysiology , 2015, Neuron.

[13]  N. Rensing,et al.  Video-EEG monitoring methods for characterizing rodent models of tuberous sclerosis and epilepsy. , 2012, Methods in molecular biology.

[14]  R. B. Reilly,et al.  FASTER: Fully Automated Statistical Thresholding for EEG artifact Rejection , 2010, Journal of Neuroscience Methods.

[15]  Bruce J. West,et al.  Wavelet analysis of epileptic spikes. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Guideline 6: A Proposal for Standard Montages to Be Used in Clinical EEG , 2006, American journal of electroneurodiagnostic technology.

[17]  Benjamin H. Brinkmann,et al.  Large-scale electrophysiology: Acquisition, compression, encryption, and storage of big data , 2009, Journal of Neuroscience Methods.

[18]  T. Lucas,et al.  Transparent and flexible low noise graphene electrodes for simultaneous electrophysiology and neuroimaging , 2014, Nature Communications.

[19]  G. Flint,et al.  Seizures and epilepsy. , 1988, British journal of neurosurgery.

[20]  Steven W. Smith,et al.  The Scientist and Engineer's Guide to Digital Signal Processing , 1997 .

[21]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[22]  Sergio Cerutti,et al.  Digital biomedical signal acquisition and processing , 2006 .

[23]  A. Verma Very Slow EEG Responses Lateralize Temporal Lobe Seizures: An Evaluation of Noninvasive DC-EEG , 2006 .

[24]  James S. Walker,et al.  A Primer on Wavelets and Their Scientific Applications , 1999 .

[25]  Sampsa Vanhatalo,et al.  Slow endogenous activity transients and developmental expression of K+–Cl− cotransporter 2 in the immature human cortex , 2005, The European journal of neuroscience.

[26]  F. L. D. Silva,et al.  EEG analysis: Theory and Practice , 1998 .

[27]  Dorothy V. M. Bishop,et al.  Journal of Neuroscience Methods , 2015 .

[28]  VERSION , 1922 .

[29]  Erich Schröger,et al.  Digital filter design for electrophysiological data – a practical approach , 2015, Journal of Neuroscience Methods.

[30]  Brian Litt,et al.  Collaborating and sharing data in epilepsy research. , 2015, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[31]  W. Stacey,et al.  Effect of sampling rate and filter settings on High Frequency Oscillation detections , 2016, Clinical Neurophysiology.

[32]  Bob Kemp,et al.  European data format ‘plus’ (EDF+), an EDF alike standard format for the exchange of physiological data , 2003, Clinical Neurophysiology.

[33]  Anthony N. Burkitt,et al.  Closed-Loop Seizure Control with Very High Frequency Electrical Stimulation at Seizure Onset in the Gaers Model of Absence Epilepsy , 2011, Int. J. Neural Syst..

[34]  J. Gotman,et al.  A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification , 2006, Clinical Neurophysiology.

[35]  A Värri,et al.  A simple format for exchange of digitized polygraphic recordings. , 1992, Electroencephalography and clinical neurophysiology.

[36]  F. Edward Dudek,et al.  Long-term Continuous EEG Monitoring in Small Rodent Models of Human Disease Using the Epoch Wireless Transmitter System , 2015, Journal of visualized experiments : JoVE.

[37]  A. Nehlig,et al.  Epilepsy therapy development: Technical and methodologic issues in studies with animal models , 2013, Epilepsia.

[38]  L. Skoog,et al.  Historical aspects. , 2009, Monographs in clinical cytology.

[39]  V. A. Makarov,et al.  Recovering EEG brain signals: Artifact suppression with wavelet enhanced independent component analysis , 2006, Journal of Neuroscience Methods.

[40]  E. Bertram Monitoring for Seizures in Rodents , 2017 .

[41]  Matt Stead,et al.  Proposal for a Standard Format for Neurophysiology Data Recording and Exchange , 2016, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[42]  Ankit N Khambhati,et al.  Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings , 2017, Brain : a journal of neurology.

[43]  Akio Ikeda,et al.  Methodological standards and interpretation of video‐electroencephalography in adult control rodents. A TASK1‐WG1 report of the AES/ILAE Translational Task Force of the ILAE , 2017, Epilepsia.

[44]  A. Flisberg,et al.  Infraslow EEG activity in burst periods from post asphyctic full term neonates , 2005, Clinical Neurophysiology.

[45]  Jerome Engel,et al.  High-frequency oscillations in epileptic brain , 2010, Current opinion in neurology.

[46]  Terrence J. Sejnowski,et al.  Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis , 2007, NeuroImage.

[47]  R. Northrop Signals and Systems Analysis In Biomedical Engineering , 2003 .

[48]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[49]  William P. Marnane,et al.  Parallel artefact rejection for epileptiform activity detection in routine EEG , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[50]  Scott B. Wilson,et al.  Spike detection: a review and comparison of algorithms , 2002, Clinical Neurophysiology.

[51]  Wim van Drongelen,et al.  Signal processing for Neuroscientists : introduction to the analysis of physiological signals , 2007 .

[52]  Sheng-Fu Liang,et al.  A closed-loop brain computer interface for real-time seizure detection and control , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[53]  Kenneth A. Loparo,et al.  Automated Removal of EKG Artifact From EEG Data Using Independent Component Analysis and Continuous Wavelet Transformation , 2014, IEEE Transactions on Biomedical Engineering.