Modified Neuropixels probes for recording human neurophysiology in the operating room

Sydney S. Cash, Angelique C. Paulk, Brian Coughlin, William Muñoz, Yoav Kfir, Michael J. Young, Domokos Meszéna, Mohsen Jamali, Irene Caprara, Richard Hardstone, Arjun Khanna, Martina L. Mustroph, Eric M. Trautmann, Charlie Windolf, Erdem Varol, Dan J. Soper, Sergey D. Stavisky, Marleen Welkenhuysen, Barundeb Dutta, Krishna V. Shenoy, Leigh R. Hochberg, R. Mark Richardson, Ziv M. Williams

Published: 2023-09-10 DOI: 10.1038/s41596-023-00871-2

Neuropixels

Human Neurophysiology

Electrophysiology

Perioperative Procedures

Sterile Conditions

AI 解读

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Comprehensive multi-attribute method workflow for biotherapeutic characterization and current good manufacturing practices testing

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Introduction
Materials
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Troubleshooting
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Anticipated results
- Reporting summary
Acknowledgements

Khodagholy, D. et al. Organic electronics for high-resolution electrocorticography of the human brain. Sci. Adv. 2, e1601027 (2016).
Jun, J. J. et al. Fully integrated silicon probes for high-density recording of neural activity. Nature 551, 232–236 (2017).
Steinmetz, N. A. et al. Neuropixels 2.0: a miniaturized high-density probe for stable, long-term brain recordings. Science 372, eabf4588 (2021).
Dutta, B. et al. The Neuropixels probe: a CMOS based integrated microsystems platform for neuroscience and brain-computer interfaces. In 2019 IEEE International Electron Devices Meeting (IEDM) 10.1.1–10.1.4 https://doi.org/10.1109/IEDM19573.2019.8993611 (2019).
Steinmetz, N. A., Zatka-Haas, P., Carandini, M. & Harris, K. D. Distributed coding of choice, action and engagement across the mouse brain. Nature 576, 266–273 (2019).
Siegle, J. H. et al. Survey of spiking in the mouse visual system reveals functional hierarchy. Nature 592, 86–92 (2021).
Jia, X. et al. High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification. J. Neurophysiol. 121, 1831–1847 (2019).
Trautmann, E. M. et al. Large-scale brain-wide neural recording in nonhuman primates. Preprint at bioRxiv https://doi.org/10.1101/2023.02.01.526664 (2023).
Durand, S. et al. Acute head-fixed recordings in awake mice with multiple Neuropixels probes. Nat. Protoc. 18, 424–457 (2023).
Trepka, E. B., Zhu, S., Xia, R., Chen, X. & Moore, T. Functional interactions among neurons within single columns of macaque V1. eLife 11, e79322 (2022).
Pachitariu, M., Steinmetz, N., Kadir, S., Carandini, M. & Harris, K. Fast and accurate spike sorting of high-channel count probes with KiloSort. Adv. Neural Inf. Process. Syst. 2016, 1–9 (2016).
Siegle, J. H. et al. Open Ephys: an open-source, plugin-based platform for multichannel electrophysiology. J. Neural Eng. 14, 045003 (2017).
Pachitariu, M., Sridhar, S. & Stringer, C. Solving the spike sorting problem with Kilosort. Preprint at bioRxiv https://doi.org/10.1101/2023.01.07.523036 (2023).
Paulk, A. C. et al. Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex. Nat. Neurosci. 25, 252–263 (2022).
Chung, J. E. et al. High-density single-unit human cortical recordings using the Neuropixels probe. Neuron 110, 2409–2421.e3 (2022).
Chari, A., Thornton, R. C., Tisdall, M. M. & Scott, R. C. Microelectrode recordings in human epilepsy: a case for clinical translation. Brain Commun. 2, fcaa082 (2020).
Cash, S. S. & Hochberg, L. R. The emergence of single neurons in clinical neurology. Neuron 86, 79–91 (2015).
Amirnovin, R., Williams, Z. M., Cosgrove, G. R. & Eskandar, E. N. Experience with microelectrode guided subthalamic nucleus deep brain stimulation. Neurosurgery 58, ONS96–ONS102 (2006).
Jamali, M. et al. Dorsolateral prefrontal neurons mediate subjective decisions and their variation in humans. Nat. Neurosci. 22, 1010–1020 (2019).
Sheth, S. A. et al. Human dorsal anterior cingulate cortex neurons mediate ongoing behavioural adaptation. Nature 488, 218–221 (2012).
Feinsinger, A. et al. Ethical commitments, principles, and practices guiding intracranial neuroscientific research in humans. Neuron 110, 188–194 (2022).
Greely, H. T. et al. Neuroethics Guiding Principles for the NIH BRAIN Initiative. J. Neurosci. 38, 10586–10588 (2018).
Young, M. J. & Bernat, J. L. Emerging subspecialties in neurology: neuroethics: an emerging career path in neurology. Neurology 98, 505–508 (2022).
Goering, S. et al. Recommendations for responsible development and application of neurotechnologies. Neuroethics 14, 365–386 (2021).
Windolf, C. et al. Robust online multiband drift estimation in electrophysiology data. Preprint at bioRxiv https://doi.org/10.1101/2022.12.04.519043 (2022).
Windolf, C. et al. Robust online multiband drift estimation in electrophysiology data. In ICASSP 2023 IEEE International Conference on Acoustics, Speech and Signal Processing https://doi.org/10.1109/ICASSP49357.2023.10095487 (2023).
Allen, W. E. et al. Thirst regulates motivated behavior through modulation of brainwide neural population dynamics. Science 364, 0–10 (2019).
Trautmann, E. M. et al. Accurate estimation of neural population dynamics without spike sorting. Neuron 103, 292–308.e4 (2019).
Juavinett, A. L., Bekheet, G. & Churchland, A. K. Chronically implanted Neuropixels probes enable high-yield recordings in freely moving mice. eLife 8, e47188 (2019).
Aguillon-Rodriguez, V. et al. Standardized and reproducible measurement of decision-making in mice. eLife 10, 1–28 (2021).
Barack, D. & Krakauer, J. W. Two views on the cognitive brain. Nat. Rev. Neurosci. 22, 359–371 (2021).
Yuste, R. From the neuron doctrine to neural networks. Nat. Rev. Neurosci. 16, 487–497 (2015).
Hesse, J. K. & Tsao, D. Y. A new no-report paradigm reveals that face cells encode both consciously perceived and suppressed stimuli. eLife 9, e58360 (2020).
van Daal, R. J. J. et al. Implantation of Neuropixels probes for chronic recording of neuronal activity in freely behaving mice and rats. Nat. Protoc. 16, 3322–3347 (2021).
Siegle, J. H. et al. Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology. eLife 10, 1–35 (2021).
Zatka-Haas, P., Steinmetz, N. A., Carandini, M. & Harris, K. D. Sensory coding and the causal impact of mouse cortex in a visual decision. eLife 10, 1–25 (2021).
Truccolo, W. et al. Single-neuron dynamics in human focal epilepsy. Nat. Neurosci. 14, 635–641 (2011).
Truccolo, W. et al. Neuronal ensemble synchrony during human focal seizures. J. Neurosci. 34, 9927–9944 (2014).
Jamali, M. et al. Single-neuronal predictions of others’ beliefs in humans. Nature 591, 610–614 (2021).
Mian, M. K. et al. Encoding of rules by neurons in the human dorsolateral prefrontal cortex. Cereb. Cortex 24, 807–816 (2014).
Patel, S. R. et al. Studying task-related activity of individual neurons in the human brain. Nat. Protoc. 8, 949–957 (2013).
Aabedi, A. A. et al. Functional alterations in cortical processing of speech in glioma-infiltrated cortex. Proc. Natl Acad. Sci. USA. 118, e2108959118 (2021).
Ulbert, I., Halgren, E., Heit, G. & Karmos, G. Multiple microelectrode-recording system for human intracortical applications. J. Neurosci. Methods 106, 69–79 (2001).
Maynard, E. M., Nordhausen, C. T. & Normann, R. A. The Utah Intracortical Electrode Array: a recording structure for potential brain-computer interfaces. Electroencephalogr. Clin. Neurophysiol. 102, 228–239 (1997).
Nordhausen, C. T., Rousche, P. J. & Normann, R. A. Optimizing recording capabilities of the Utah Intracortical Electrode Array. Brain Res. 637, 27–36 (1994).
Nordhausen, C. T., Maynard, E. M. & Normann, R. A. Single unit recording capabilities of a 100 microelectrode array. Brain Res. 726, 129–140 (1996).
Hochberg, L. R. et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485, 372–375 (2012).
Hochberg, L. R. et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442, 164–171 (2006).
Willett, F. R. et al. Hand knob area of premotor cortex represents the whole body in a compositional way. Cell 181, 1–14 (2020).
Slutzky, M. W. Brain–machine interfaces: powerful tools for clinical treatment and neuroscientific investigations. Neuroscientist 25, 139–154 (2019).
Lebedev, M. A. & Nicolelis, M. A. L. Brain-machine interfaces: past, present and future. Trends Neurosci. 29, 536–546 (2006).
Saha, S. et al. Progress in brain computer interface: challenges and opportunities. Front. Syst. Neurosci. 15, 1–20 (2021).
Tchoe, Y. et al. Human brain mapping with multi-thousand channel PtNRGrids resolves novel spatiotemporal dynamics. Sci. Transl. Med. 14, eabj1441 (2022).
Paulk, A. C. et al. Microscale physiological events on the human cortical surface. Cereb. Cortex 31, 3678–3700 (2021).
Yang, J. C. et al. Microscale dynamics of electrophysiological markers of epilepsy. Clin. Neurophysiol. 32, 2916–2931 (2021).
Khodagholy, D. et al. NeuroGrid: recording action potentials from the surface of the brain. Nat. Neurosci. 18, 310–315 (2015).
Viventi, J. et al. Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nat. Neurosci. 14, 1599–1605 (2011).
Sun, J. et al. Intraoperative microseizure detection using a high-density micro-electrocorticography electrode array. Brain Commun. 4, fcac122 (2022).
Hassan, A. R. et al. Translational organic neural interface devices at single neuron resolution. Adv. Sci. (Weinh.) 9, e2202306 (2022).
Ward, A. A. & Thomas, L. B. The electrical activity of single units in the cerebral cortex of man. Electroencephalogr. Clin. Neurophysiol. 7, 135–136 (1955).
Verzeano, M., Crandall, P. H. & Dymond, A. Neuronal activity of the amygdala in patients with psychomotor epilepsy. Neuropsychologia 9, 331–344 (1971).
Fried, I. et al. Cerebral microdialysis combined with single-neuron and electroencephalographic recording in neurosurgical patients: technical note. J. Neurosurg. 91, 697–705 (1999).
Fried, I., Cameron, K. A., Yashar, S., Fong, R. & Morrow, J. W. Inhibitory and excitatory responses of single neurons in the human medial temporal lobe during recognition of faces and objects. Cereb. Cortex 12, 575–584 (2002).
Worrell, G. A. et al. High-frequency oscillations in human temporal lobe: simultaneous microwire and clinical macroelectrode recordings. Brain 131, 928–937 (2008).
Kleen, J. K. et al. Bidirectional propagation of low frequency oscillations over the human hippocampal surface. Nat. Commun. 12, 2764 (2021).
Musk, E. An integrated brain-machine interface platform with thousands of channels. Preprint at bioRxiv https://doi.org/10.1101/703801 (2019).
Sahasrabuddhe, K. et al. The Argo: a high channel count recording system for neural recording in vivo. J. Neural Eng. 18, 015002 (2021).
Fiáth, R. et al. Slow insertion of silicon probes improves the quality of acute neuronal recordings. Sci. Rep. 9, 1–17 (2019).
Wang, Q., Yin, J. & Cui, H. Reinforcement of Neuropixels probes for high-density neural recording in non-human primates. In 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER) 128–131 (IEEE, 2021).
Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
Mercier, M. R. et al. Advances in human intracranial electroencephalography research, guidelines and good practices. Neuroimage 260, 119438 (2022).
Duncan, D. et al. Data Archive for the BRAIN Initiative (DABI). Sci. Data 10, 83 (2023).
Oostenveld, R., Fries, P., Maris, E. & Schoffelen, J.-M. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869 (2011).
Bischoff-Grethe, A. et al. A technique for the deidentification of structural brain MR images. Hum. Brain Mapp. 28, 892–903 (2007).
Buimer, E. E. L. et al. De-identification procedures for magnetic resonance images and the impact on structural brain measures at different ages. Hum. Brain Mapp. 42, 3643–3655 (2021).
Holdgraf, C. et al. iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. Sci. Data 6, 102 (2019).
Investigational Device Exemptions. 21 CFR § 812. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfCFR/CFRSearch.cfm?CFRPart=812 (2023).
U.S. Department of Health and Human Services Food and Drug Administration Center for Devices and Radiological Health (CDRH). Information Sheet Guidance for IRBs, Clinical Investigators, and Sponsors. Significant Risk and Nonsignificant Risk Medical Device Studies https://www.fda.gov/regulatory-information/search-fda-guidance-documents/significant-risk-and-nonsignificant-risk-medical-device-studies (2006).
Kalb, S. IDE Basics. Investigational Device Exemption (IDE) Program Office of Device Evaluation, Center for Devices and Radiological Health U.S. Food and Drug Administration. https://www.fda.gov/media/127955/download (2014).
Kleiner, M., Brainard, D. H. & Pelli, D. What’s new in Psychtoolbox-3? Perception 36, 1–16 (ECVP Abstract Supplement) (2007).
Buccino, A. P. et al. SpikeInterface, a unified framework for spike sorting. eLife 9, e61834 (2020).
Williams, Z. M., Bush, G., Rauch, S. L., Cosgrove, G. R. & Eskandar, E. N. Human anterior cingulate neurons and the integration of monetary reward with motor responses. Nat. Neurosci. 7, 1370–1375 (2004).
Felsenstein, O. & Peled, N. MMVT—multi-modality visualization tool. GitHub https://doi.org/10.5281/zenodo.438343 (2017).
Reuter, M., Rosas, H. D. & Fischl, B. Highly accurate inverse consistent registration: a robust approach. Neuroimage 53, 1181–1196 (2010).
Reuter, M., Schmansky, N. J., Rosas, H. D. & Fischl, B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 61, 1402–1418 (2012).
Holmes, C. J. et al. Enhancement of MR images using registration for signal averaging. J. Comput. Assist. Tomogr. 22, 324–333 (1998).
Community, B. O. Blender—a 3D Modelling and Rendering Package (Blender Foundation, 2018).
Chan, A. M. et al. Speech-specific tuning of neurons in human superior temporal gyrus. Cereb. Cortex 24, 2679–2693 (2014).
Schevon, C. A., Goodman, R. R., McKhann, G. & Emerson, R. G. Propagation of epileptiform activity on a submillimeter scale. J. Clin. Neurophysiol. 27, 406–411 (2010).
Koch, C. & Jones, A. Big science, team science, and open science for neuroscience. Neuron 92, 612–616 (2016).
Ascoli, G. A. Mobilizing the base of neuroscience data: the case of neuronal morphologies. Nat. Rev. Neurosci. 7, 318–324 (2006).
Ascoli, G. A., Donohue, D. E. & Halavi, M. NeuroMorpho.Org: a central resource for neuronal morphologies. J. Neurosci. 27, 9247–9251 (2007).
Tóth, K. et al. Hyperexcitability of the network contributes to synchronization processes in the human epileptic neocortex. J. Physiol. 596, 317–342 (2018).
Lancaster, J. L. et al. Automated analysis of fundamental features of brain structures. Neuroinformatics 9, 371–380 (2011).
Lancaster, J. L. et al. Anatomical global spatial normalization. Neuroinformatics 8, 171–182 (2010).
Lancaster, J. L. et al. Automated regional behavioral analysis for human brain images. Front. Neuroinform. 6, 1–12 (2012).

Modified Neuropixels probes for recording human neurophysiology in the operating room

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