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Ramezani M, Kim JH, Liu X, Ren C, Alothman A, De-Eknamkul C, Wilson MN, Cubukcu E, Gilja V, Komiyama T, Kuzum D. High-density transparent graphene arrays for predicting cellular calcium activity at depth from surface potential recordings. NATURE NANOTECHNOLOGY 2024; 19:504-513. [PMID: 38212523 DOI: 10.1038/s41565-023-01576-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 11/16/2023] [Indexed: 01/13/2024]
Abstract
Optically transparent neural microelectrodes have facilitated simultaneous electrophysiological recordings from the brain surface with the optical imaging and stimulation of neural activity. A remaining challenge is to scale down the electrode dimensions to the single-cell size and increase the density to record neural activity with high spatial resolution across large areas to capture nonlinear neural dynamics. Here we developed transparent graphene microelectrodes with ultrasmall openings and a large, transparent recording area without any gold extensions in the field of view with high-density microelectrode arrays up to 256 channels. We used platinum nanoparticles to overcome the quantum capacitance limit of graphene and to scale down the microelectrode diameter to 20 µm. An interlayer-doped double-layer graphene was introduced to prevent open-circuit failures. We conducted multimodal experiments, combining the recordings of cortical potentials of microelectrode arrays with two-photon calcium imaging of the mouse visual cortex. Our results revealed that visually evoked responses are spatially localized for high-frequency bands, particularly for the multiunit activity band. The multiunit activity power was found to be correlated with cellular calcium activity. Leveraging this, we employed dimensionality reduction techniques and neural networks to demonstrate that single-cell and average calcium activities can be decoded from surface potentials recorded by high-density transparent graphene arrays.
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Affiliation(s)
- Mehrdad Ramezani
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jeong-Hoon Kim
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Xin Liu
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Chi Ren
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Abdullah Alothman
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Chawina De-Eknamkul
- Department of NanoEngineering, University of California San Diego, La Jolla, CA, USA
| | - Madison N Wilson
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Ertugrul Cubukcu
- Department of NanoEngineering, University of California San Diego, La Jolla, CA, USA
| | - Vikash Gilja
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Takaki Komiyama
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Duygu Kuzum
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
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Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders. BRAIN MULTIPHYSICS 2022. [DOI: 10.1016/j.brain.2022.100058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Schwalm M, Tabuena DR, Easton C, Richner TJ, Mourad P, Watari H, Moody WJ, Stroh A. Functional States Shape the Spatiotemporal Representation of Local and Cortex-wide Neural Activity in Mouse Sensory Cortex. J Neurophysiol 2022; 128:763-777. [PMID: 35975935 DOI: 10.1152/jn.00424.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The spatiotemporal representation of neural activity during rest and upon sensory stimulation in cortical areas is highly dynamic, and may be predominantly governed by cortical state. On the mesoscale level, intrinsic neuronal activity ranges from a persistent state, generally associated with a sustained depolarization of neurons, to a bimodal, slow-wave like state with bursts of neuronal activation, alternating with silent periods. These different activity states are prevalent under certain types of sedatives, or are associated with specific behavioral or vigilance conditions. Neurophysiological experiments assessing circuit activity, usually assume a constant underlying state, yet reports of variability of neuronal responses under seemingly constant conditions are common in the field. Even when a certain type of neural activity or cortical state can stably be maintained over time, the associated response properties are highly relevant for explaining experimental outcomes. Here we describe the spatiotemporal characteristics of ongoing activity and sensory evoked responses under two predominant functional states in the sensory cortices of mice: persistent activity (PA) and slow wave activity (SWA). Using electrophysiological recordings, and local and wide-field calcium recordings, we examine whether spontaneous and sensory evoked neuronal activity propagate throughout the cortex in a state dependent manner. We find that PA and SWA differ in their spatiotemporal characteristics which determine the cortical network's response to a sensory stimulus. During PA state, sensory stimulation elicits gamma-based short-latency responses which precisely follow each stimulation pulse and are prone to adaptation upon higher stimulation frequencies. Sensory responses during SWA are more variable, dependent on refractory periods following spontaneous slow waves. While spontaneous slow waves propagated in anterior-posterior direction in a majority of observations, the direction of propagation of stimulus-elicited wave depends on the sensory modality. These findings suggest that cortical state explains variance and should be considered when investigating multi-scale correlates of functional neurocircuit activity.
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Affiliation(s)
- Miriam Schwalm
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Dennis R Tabuena
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Curtis Easton
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Thomas J Richner
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Pierre Mourad
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Hirofumi Watari
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Department of Biology, University of Washington, Seattle, WA, United States
| | - William J Moody
- Department of Biology, University of Washington, Seattle, WA, United States
| | - Albrecht Stroh
- Institute of Pathophysiology, University Medical Center Mainz, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
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Shi Y, Ananthakrishnan A, Oh S, Liu X, Hota G, Cauwenberghs G, Kuzum D. A Neuromorphic Brain Interface based on RRAM Crossbar Arrays for High Throughput Real-time Spike Sorting. IEEE TRANSACTIONS ON ELECTRON DEVICES 2022; 69:2137-2144. [PMID: 37168652 PMCID: PMC10168101 DOI: 10.1109/ted.2021.3131116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Real-time spike sorting and processing are crucial for closed-loop brain-machine interfaces and neural prosthetics. Recent developments in high-density multi-electrode arrays with hundreds of electrodes have enabled simultaneous recordings of spikes from a large number of neurons. However, the high channel count imposes stringent demands on real-time spike sorting hardware regarding data transmission bandwidth and computation complexity. Thus, it is necessary to develop a specialized real-time hardware that can sort neural spikes on the fly with high throughputs while consuming minimal power. Here, we present a real-time, low latency spike sorting processor that utilizes high-density CuOx resistive crossbars to implement in-memory spike sorting in a massively parallel manner. We developed a fabrication process which is compatible with CMOS BEOL integration. We extensively characterized switching characteristics and statistical variations of the CuOx memory devices. In order to implement spike sorting with crossbar arrays, we developed a template matching-based spike sorting algorithm that can be directly mapped onto RRAM crossbars. By using synthetic and in vivo recordings of extracellular spikes, we experimentally demonstrated energy efficient spike sorting with high accuracy. Our neuromorphic interface offers substantial improvements in area (~1000× less area), power (~200× less power), and latency (4.8μs latency for sorting 100 channels) for real-time spike sorting compared to other hardware implementations based on FPGAs and microcontrollers.
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Affiliation(s)
- Yuhan Shi
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Akshay Ananthakrishnan
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Sangheon Oh
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Xin Liu
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Gopabandhu Hota
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Gert Cauwenberghs
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
| | - Duygu Kuzum
- Electrical and Computer Engineering Department. G. Cauwenberghs is with Bioengineering Department, University of California at San Diego, San Diego, CA 92093, USA
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