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Shankar S, Chen Y, Averbeck S, Hendricks Q, Murphy B, Ferleger B, Driscoll N, Shekhirev M, Takano H, Richardson A, Gogotsi Y, Vitale F. Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics. Adv Healthc Mater 2025; 14:e2402576. [PMID: 39328088 PMCID: PMC11804840 DOI: 10.1002/adhm.202402576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 09/11/2024] [Indexed: 09/28/2024]
Abstract
Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.
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Affiliation(s)
- Sneha Shankar
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
| | - Yuzhang Chen
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
| | - Spencer Averbeck
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
| | - Quincy Hendricks
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Brendan Murphy
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Benjamin Ferleger
- Department of NeurosurgeryUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Nicolette Driscoll
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Mikhail Shekhirev
- A. J. Drexel Nanomaterials Instituteand Department of Materials Science and EngineeringDrexel UniversityPhiladelphiaPA19104USA
| | - Hajime Takano
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Division of NeurologyChildren's Hospital of PhiladelphiaPhiladelphiaPA19104USA
| | - Andrew Richardson
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of NeurosurgeryUniversity of PennsylvaniaPhiladelphiaPA19104USA
| | - Yury Gogotsi
- A. J. Drexel Nanomaterials Instituteand Department of Materials Science and EngineeringDrexel UniversityPhiladelphiaPA19104USA
| | - Flavia Vitale
- Center for Neuroengineering & TherapeuticsUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Center for NeurotraumaNeurodegenerationand RestorationCorporal Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPA19104USA
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPA19104USA
- Department of Physical Medicine & RehabilitationUniversity of PennsylvaniaPhiladelphiaPA19104USA
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Erickson B, Kim B, Sabes P, Rich R, Hatcher A, Fernandez-Nuñez G, Mentzelopoulos G, Vitale F, Medaglia J. TMS-induced phase resets depend on TMS intensity and EEG phase. J Neural Eng 2024; 21:056035. [PMID: 39321851 PMCID: PMC11500019 DOI: 10.1088/1741-2552/ad7f87] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 07/26/2024] [Accepted: 09/23/2024] [Indexed: 09/27/2024]
Abstract
Objective. The phase of the electroencephalographic (EEG) signal predicts performance in motor, somatosensory, and cognitive functions. Studies suggest that brain phase resets align neural oscillations with external stimuli, or couple oscillations across frequency bands and brain regions. Transcranial Magnetic Stimulation (TMS) can cause phase resets noninvasively in the cortex, thus providing the potential to control phase-sensitive cognitive functions. However, the relationship between TMS parameters and phase resetting is not fully understood. This is especially true of TMS intensity, which may be crucial to enabling precise control over the amount of phase resetting that is induced. Additionally, TMS phase resetting may interact with the instantaneous phase of the brain. Understanding these relationships is crucial to the development of more powerful and controllable stimulation protocols.Approach.To test these relationships, we conducted a TMS-EEG study. We applied single-pulse TMS at varying degrees of stimulation intensity to the motor area in an open loop. Offline, we used an autoregressive algorithm to estimate the phase of the intrinsicµ-Alpha rhythm of the motor cortex at the moment each TMS pulse was delivered.Main results. We identified post-stimulation epochs whereµ-Alpha phase resetting and N100 amplitude depend parametrically on TMS intensity and are significantversusperipheral auditory sham stimulation. We observedµ-Alpha phase inversion after stimulations near peaks but not troughs in the endogenousµ-Alpha rhythm.Significance. These data suggest that low-intensity TMS primarily resets existing oscillations, while at higher intensities TMS may activate previously silent neurons, but only when endogenous oscillations are near the peak phase. These data can guide future studies that seek to induce phase resetting, and point to a way to manipulate the phase resetting effect of TMS by varying only the timing of the pulse with respect to ongoing brain activity.
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Affiliation(s)
- Brian Erickson
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Brian Kim
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Philip Sabes
- Starfish Neuroscience, Bellevue, WA 98004, United States of America
- Department of Physiology, University of California, San Francisco, CA 94143, United States of America
| | - Ryan Rich
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Abigail Hatcher
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Guadalupe Fernandez-Nuñez
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Georgios Mentzelopoulos
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
| | - Flavia Vitale
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - John Medaglia
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Drexel University, Philadelphia, PA 19104, United States of America
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Erickson B, Rich R, Shankar S, Kim B, Driscoll N, Mentzelopoulos G, Fernandez-Nuñez G, Vitale F, Medaglia JD. Evaluating and benchmarking the EEG signal quality of high-density, dry MXene-based electrode arrays against gelled Ag/AgCl electrodes. J Neural Eng 2024; 21:016005. [PMID: 38081060 PMCID: PMC10788783 DOI: 10.1088/1741-2552/ad141e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/17/2023] [Accepted: 12/11/2023] [Indexed: 01/13/2024]
Abstract
Objective.To evaluate the signal quality of dry MXene-based electrode arrays (also termed 'MXtrodes') for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard.Approach.We placed 4 × 4 MXtrode arrays and gelled Ag/AgCl electrodes on different scalp locations. The scalp was cleaned with alcohol and rewetted with saline before application. We recorded from both electrode types simultaneously while participants performed a vigilance task.Main results.The root mean squared amplitude of MXtrodes was slightly higher than that of Ag/AgCl electrodes (.24-1.94 uV). Most MXtrode pairs had slightly lower broadband spectral coherence (.05 to .1 dB) and Delta- and Theta-band timeseries correlation (.05 to .1 units) compared to the Ag/AgCl pair (p< .001). However, the magnitude of correlation and coherence was high across both electrode types. Beta-band timeseries correlation and spectral coherence were higher between neighboring MXtrodes in the array (.81 to .84 units) than between any other pair (.70 to .75 units). This result suggests the close spacing of the nearest MXtrodes (3 mm) more densely sampled high spatial-frequency topographies. Event-related potentials were more similar between MXtrodes (ρ⩾ .95) than equally spaced Ag/AgCl electrodes (ρ⩽ .77,p< .001). Dry MXtrode impedance (x̄= 5.15 KΩ cm2) was higher and more variable than gelled Ag/AgCl electrodes (x̄= 1.21 KΩ cm2,p< .001). EEG was also recorded on the scalp across diverse hair types.Significance.Dry MXene-based electrodes record EEG at a quality comparable to conventional gelled Ag/AgCl while requiring minimal scalp preparation and no gel. MXtrodes can record independent signals at a spatial density four times higher than conventional electrodes, including through hair, thus opening novel opportunities for research and clinical applications that could benefit from dry and higher-density configurations.
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Affiliation(s)
- Brian Erickson
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Ryan Rich
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Sneha Shankar
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
| | - Brian Kim
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Nicolette Driscoll
- Laboratory of Electronics Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
| | - Georgios Mentzelopoulos
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
| | - Guadalupe Fernandez-Nuñez
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Flavia Vitale
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - John D Medaglia
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Drexel University, Philadelphia, PA 19104, United States of America
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