Human brain local field potential recordings during a battery of multilingual cognitive and eye-tracking tasks
Language English Country Great Britain, England Media electronic
Document type Journal Article, Dataset
Grant support
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
2021/03/Y/NZ4/00082
Narodowe Centrum Nauki (National Science Centre)
22-28594K
Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
22-28594K
Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
22-28594K
Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
22-28594K
Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
PubMed
40436877
PubMed Central
PMC12119873
DOI
10.1038/s41597-025-05222-2
PII: 10.1038/s41597-025-05222-2
Knihovny.cz E-resources
- MeSH
- Electroencephalography MeSH
- Language MeSH
- Cognition * MeSH
- Humans MeSH
- Brain * physiology MeSH
- Eye Movements MeSH
- Eye-Tracking Technology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
Intracranial human brain recordings from multiple implanted depth electrodes using stereo-EEG (sEEG) technology for seizure localization provide unique local field potential signals (LFP) sampled with standard macro- and special micro-electrode contacts. Over one hundred macro- and micro-contact LFP signals localized in particular brain regions were recorded from each sEEG monitoring case as patients engaged in an automated battery of verbal memory and non-verbal gaze movement tasks. Subject eye and vocal responses in both visual and auditory task versions were automatically detected in Polish, Czech, and Slovak languages with accurate timing of the correct and incorrect verbal responses using our web-based transcription tool. The behavioral events, LFP and pupillometric signals were synchronized and stored in a standard BIDS data structure with corresponding metadata. Each dataset contains recordings from at least one battery task performed over at least one day. The same set of 180 common nouns in the three languages was used across different battery tasks and recording days to enable the analysis of selective responses to specific word stimuli.
Central European Institute of Technology Masaryk University Brno Czech Republic
Department of Neurology Wroclaw Medical University Wroclaw Poland
Department of Neurosurgery Wroclaw Medical University Wroclaw Poland
Department of Physiology and Biomedical Engineering Mayo Clinic Rochester MN USA
See more in PubMed
Fried, I., Rutishauser, U., Cerf, M. & Kreiman, G. Single Neuron Studies of the Human Brain: Probing Cognition. (MIT Press, 2014).
Engel, A. K., Moll, C. K., Fried, I. & Ojemann, G. A. Invasive recordings from the human brain: clinical insights and beyond. Nat Rev Neurosci.6(1), 35–47, 10.1038/nrn1585 (2005). PubMed
Jacobs, J. & Kahana, M. J. Direct brain recordings fuel advances in cognitive electrophysiology. Trends Cogn. Sci.14, 162–171 (2010). PubMed PMC
Parvizi, J. & Kastner, S. Promises and limitations of human intracranial electroencephalography. Nat. Neurosci.21, 474–483 (2018). PubMed PMC
Axmacher, N. Intracranial EEG. (Springer International Publishing).
Johnson, E. L. & Knight, R. T. Intracranial recordings and human memory. Curr. Opin. Neurobiol.31, 18–25 (2015). PubMed PMC
Lhatoo, S. D., Kahane, P. & Luders, H. O. Invasive Studies of the Human Epileptic Brain: Principles and Practice. (Oxford University Press, USA, 2019).
Hardesty, D. E. & Sackeim, H. A. Deep brain stimulation in movement and psychiatric disorders. Biol. Psychiatry61, 831–835 (2007). PubMed
Buzsáki, G., Anastassiou, C. A. & Koch, C. The origin of extracellular fields and currents–EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci.13, 407–420 (2012). PubMed PMC
Buzsaki, G. Rhythms of the Brain. (Oxford University Press, 2006).
Fried, I. Neurons as will and representation. Nat. Rev. Neurosci.23, 104–114 (2022). PubMed PMC
Alagapan, S. et al. Cingulate dynamics track depression recovery with deep brain stimulation. Nature622, 130–138 (2023). PubMed PMC
Marks, V. S. et al. bioRxiv 12.21.521275 10.1101/2022.12.21.521275 (2022).
Gilron, R. et al. Long-term wireless streaming of neural recordings for circuit discovery and adaptive stimulation in individuals with Parkinson’s disease. Nat. Biotechnol.39, 1078–1085 (2021). PubMed PMC
Marks, V. S. et al. Deep Brain Stimulation of Anterior Nuclei of the Thalamus and Hippocampal Seizure Rate Modulate Verbal Memory Performance, IEEE International Conference on Electro Information Technology (eIT), Mankato, MN, USA, 2022, pp. 1-4, 10.1109/eIT53891.2022.9813930 (2022).
Cimbalnik, J. et al. Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry. EBRAINS, 10.25493/GKNT-T3X (2021). PubMed PMC
Kahana, M. J. Foundations of Human Memory. (Oxford University Press, 2014).
Quiroga, R. Q. Concept cells: the building blocks of declarative memory functions. Nat. Rev. Neurosci.13, 587–597 (2012). PubMed
Kubska, Z. R. & Kamiński, J. How Human Single-Neuron Recordings Can Help Us Understand Cognition: Insights from Memory Studies. Brain Sci11, (2021). PubMed PMC
Vaz, A. P., Wittig, J. H. Jr, Inati, S. K. & Zaghloul, K. A. Replay of cortical spiking sequences during human memory retrieval. Science367, 1131–1134 (2020). PubMed PMC
Norman, Y. et al. Hippocampal sharp-wave ripples linked to visual episodic recollection in humans. Science365, (2019). PubMed
Kucewicz, M. T., Cimbalnik, J., Garcia, J. S. S., Brazdil, M. & Worrell, G. A. High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams? Brain awae159 (2024). PubMed PMC
Lech, M., Czyżewski, A. & Kucewicz, M. T. CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain. Sensors21, (2021). PubMed PMC
Lech, M., Kucewicz, M. T. & Czyżewski, A. Human Computer Interface for Tracking Eye Movements Improves Assessment and Diagnosis of Patients With Acquired Brain Injuries. Front. Neurol.10, 6 (2019). PubMed PMC
Kucewicz, M. T. et al. Pupil size reflects successful encoding and recall of memory in humans. Sci. Rep.8, 4949 (2018). PubMed PMC
Keles, U. et al. Multimodal single-neuron, intracranial EEG, and fMRI brain responses during movie watching in human patients. Sci Data11, 214 (2024). PubMed PMC
Doležal, J. & Fabian, V. 41. Application of eye tracking in neuroscience. Clinical Neurophysiology126, e44 10.1016/j.clinph.2014.10.200 (2015).
Deman, P. et al. IntrAnat Electrodes: A Free Database and Visualization Software for Intracranial Electroencephalographic Data Processed for Case and Group Studies. Front Neuroinform12, 40 (2018). PubMed PMC
Radford, A & Kim, J Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya. Robust Speech Recognition via Large-Scale Weak Supervision. arXiv10.48550/ARXIV.2212.04356 (2022).
Rosana Ardila, Megan Branson, Kelly Davis, Michael Henretty, Michael Kohler, Josh Meyer, Reuben Morais, Lindsay Saunders, Francis M. Tyers, Gregor Weber. Common Voice: A Massively-Multilingual Speech Corpus. arXiv10.48550/arXiv.1912.06670.
Stead, M. & Halford, J. J. Proposal for a Standard Format for Neurophysiology Data Recording and Exchange. J. Clin. Neurophysiol.33, 403–413 (2016). PubMed PMC
Cimbalnik, J. et al. EBRAINS10.25493/4FZH-ZCG (2024).
Holdgraf, C. et al. iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. Sci Data6, 102 (2019). PubMed PMC
Nejedly, P. et al. Intracerebral EEG Artifact Identification Using Convolutional Neural Networks. Neuroinformatics17, 225–234 (2019). PubMed PMC
Kucewicz, M. T. et al. Dissecting gamma frequency activity during human memory processing. Brain140, 1337–1350 (2017). PubMed
Kucewicz, M. T. et al. High frequency oscillations are associated with cognitive processing in human recognition memory. Brain137, 2231–2244 (2014). PubMed PMC
Kucewicz, M. T. et al. Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task. IEEE Trans. Biomed. Eng.63, 67–75 (2016). PubMed
Rutishauser, U., Schuman, E. M. & Mamelak, A. N. Online detection and sorting of extracellularly recorded action potentials in human medial temporal lobe recordings, in vivo. J Neurosci Methods154, 204–224 (2006). PubMed
Yarkoni, T., et al. PyBIDS: Python tools for BIDS datasets. J Open Source Softw4(40), 1294, 10.21105/joss.01294 (2019). PubMed PMC
Mathôt, S., Fabius, J., Van Heusden, E. & Van der Stigchel, S. Safe and sensible preprocessing and baseline correction of pupil-size data. Behav. Res. Methods50, 94–106 (2018). PubMed PMC
Cimbalnik, J. Python Signal Viewer (PySigView). 10.5281/zenodo.2590814 (Zenodo, 2019).
Plesinger, F., Jurco, J., Halamek, J. & Jurak, P. SignalPlant: an open signal processing software platform. Physiol. Meas.37, N38–48 (2016). PubMed
Schwarz, C. G. et al. Identification of Anonymous MRI Research Participants with Face-Recognition Software. N. Engl. J. Med.381, 1684–1686 (2019). PubMed PMC
Cimbalnik, J., Klimes, P. & Travnicek, V. ElectroPhYsiology COmputational Module (EPYCOM). 10.5281/zenodo.4030570 (Zenodo, 2020).
Cimbálník, J., Hewitt, A., Worrell, G. & Stead, M. The CS algorithm: A novel method for high frequency oscillation detection in EEG. J. Neurosci. Methods293, 6–16 (2018). PubMed PMC
Gardner, A. B., Worrell, G. A., Marsh, E., Dlugos, D. & Litt, B. Human and automated detection of high-frequency oscillations in clinical intracranial EEG recordings. Clin. Neurophysiol.118, 1134–1143 (2007). PubMed PMC
Barkmeier, D. T. et al. High inter-reviewer variability of spike detection on intracranial EEG addressed by an automated multi-channel algorithm. Clin Neurophysiol.123(6), 1088–95, 10.1016/j.clinph.2011.09.023 (2012). PubMed PMC
Cimbalnik, J. et al. Multi-feature localization of epileptic foci from interictal, intracranial EEG. Clin. Neurophysiol.130, 1945–1953 (2019). PubMed PMC
Klimes, P. et al. NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram. Epilepsia60, 2404–2415 (2019). PubMed