UC Berkeley Intracranial EEG Methods Symposium

Hosted by Mattia F. Pagnotta & Sigurd L. Alnes

The UC Berkeley Intracranial EEG Methods Symposium was hosted from February 10 to February 14, 2025, by the Knight Lab at UC Berkeley. The aim was to provide training and methodological foundations in human intracranial electroencephalography (iEEG) for those new to the field.

All lectures were recorded and made available on this page, along with associated resources.

Lectures

Insights on brain function from intracranial recordings

Introduction to EEG analysis

Spectral analysis

Periodic (oscillatory) and aperiodic components of the neural power spectra

HFA and decoding

OFC and decoding of iEEG signals

Reconstruction, co-registration, and localization

Effects of anatomy

An overview of connectivity analyses

Single-unit recordings and analysis

Statistical analysis of iEEG data

Hyperscanning with iEEG

Insights on brain function from intracranial recordings

Bob presents an overview of the range of cognitive areas that can be investigated with intracranial EEG recordings.

Resources

Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M. & Knight, R. T. (2006). High gamma is phase-locked to theta oscillations in human neocortex. Science, 313(5793). doi: 10.1126/science.1128115

Introduction to EEG analysis

Intracranial EEG is a powerful method for understanding neural activity in humans. Brooke provides an overview of the conceptual approaches to iEEG research, especially in comparison to other human neuroscience methods, and reviews basic terminology and preprocessing steps.

Resources

Mercier M. R., Dubarry A. S., Tadel F.  et al. (2022). Advances in human intracranial electroencephalography research, guidelines and good practices. Neuroimage, 260:119438. doi: 10.1016/j.neuroimage.2022.119438

McCarty, M. J., Woolnough, O., Mosher, J. C., Seymour, J., & Tandon, N. (2022). The listening zone of human Electrocorticographic Field potential recordings. eneuro, 9(2), ENEURO.0492-21.2022. doi: 10.1523/eneuro.0492-21.2022

Spectral analysis

Tamas provides a broad overview of the principles behind time frequency analysis in electrophysiology with a focus on amplitude and phase information. He covers the Discrete Fourier Transform, Complex Morlet Wavelet, filtering, tapering and more.

Periodic (oscillatory) and aperiodic components of the neural power spectra

Neural power spectra consist of two main components: oscillatory (or periodic) activity, and an aperiodic component that follows a 1/f-like distribution. Changes in aperiodic activity can be misinterpreted as oscillatory power changes when using traditional analysis methods. Rebecca gives an overview of a method developed by the Voytek lab (SpecParam) to address this issue and gives an example of how she incorporates this method into her own analyses.

Resources

Donoghue, T., Haller, M., Peterson, E. J., Varma, P., Sebastian, P., Gao, R., Noto, T., Lara, A. H., Wallis, J. D., Knight, R. T., Shestyuk, A., & Voytek, B. (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience, 23, 1655-1665. DOI: 10.1038/s41593-020-00744-x

High frequency activity and decoding

Bob discusses the use of iEEG in decoding with examples including speech and music decoding.

OFC and decoding of iEEG signals

Decoding approaches are widely used in neuroscience to study the information content in various brain regions. Clara provides an overview of how decoding approaches have been used in human intracranial electrophysiology studies.

Resources

Mathis M. W., Rotondo A. P., Chang E. F. et al. (2024). Decoding the brain: From neural representations to mechanistic models. Cell, 187, 21. doi: 10.1016/j.cell.2024.08.051

Reconstruction, co-registration, and localization of electrodes

Michael explores the significance of generating 3D brain reconstructions from 2D preoperative MRI and postoperative CT imaging, enabling researchers to accurately correlate iEEG signals with specific brain regions for improved functional mapping. He also introduces key software used in the reconstruction pipeline and demonstrates the lab's approach to localizing intracranial electrodes.

Resources

Stolk, A., Griffin, S., van der Meij, R. et al. (2018). Integrated analysis of anatomical and electrophysiological human intracranial data. Nat Protoc 13, 1699–1723. doi: 10.1038/s41596-018-0009-6

Effects of Anatomy

Anatomically accurate localization of electrodes is a critical first step in intracranial electrophysiology studies. Clara presents a case study in the human orbitofrontal cortex arguing why accurate localization, and in this particular case, granular localization within brain subregions, is critical for the interpretation of intracranial electrophysiology data.

An overview of connectivity analyses

In neuroscience research, several methods have been used to study and quantify the dynamic interactions between neuronal populations. Mattia provides an overview of some of the most widely used metrics to quantify functional connectivity in electrophysiological recordings.

Resources

Bastos, A. M., & Schoffelen, J. M. (2016). A tutorial review of functional connectivity analysis methods and their interpretational pitfalls. Frontiers in systems neuroscience, 9, 175. doi: 10.3389/fnsys.2015.00175

Single-unit recordings and analysis

Electrophysiological recordings are widely used in neuroscience, but differences in hardware and electrode contacts lead to differences in the underlying signal measured. Eduardo reviews the origin of the local field potential, compares and contrasts the spatial scales measured by different recording electrodes, and summarizes the methodology behind recovering single unit activity in high impedance microwire recordings.

Resources

Lewicki, M. S. (1998). A review of methods for spike sorting: the detection and classification of neural action potentials. Network 9(4): R53-78. doi: 10.1088/0954-898X_9_4_001

Schevon C. A., Ng S. K., Cappell J. et al. (2008). Microphysiology of epileptiform activity in human neocortex. Journal of Clinical Neurophysiology 25(6):321-30. doi: 10.1097/WNP.0b013e31818e8010

Statistical analysis of iEEG data

Due to the complexity of intracranial data, statistical analyses can be challenging. In this presentation, David summarizes and gives examples of some of the statistical approaches used in the field, including channel-based testing, shuffling, and mixed-effects models.

Hyperscanning with iEEG

Simultaneous iEEG recordings in multiple participants can provide novel insight into the neural dynamics of communication. Sigurd covers recent findings, methodological considerations, challenges, and potential applications of iEEG hyperscanning.

Resources

Wang, J., Meng, F., Xu, C. et al. (2025). Simultaneous intracranial recordings of interacting brains reveal neurocognitive dynamics of human cooperation. Nature Neuroscience 28, 161–173. doi: 10.1038/s41593-024-01824-y