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Średniawa W, Borzymowska Z, Kondrakiewicz K, Jurgielewicz P, Mindur B, Hottowy P, Wójcik DK, Kublik E. Local contribution to the somatosensory evoked potentials in rat's thalamus. PLoS One 2024; 19:e0301713. [PMID: 38593141 PMCID: PMC11003638 DOI: 10.1371/journal.pone.0301713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/19/2024] [Indexed: 04/11/2024] Open
Abstract
Local Field Potential (LFP), despite its name, often reflects remote activity. Depending on the orientation and synchrony of their sources, both oscillations and more complex waves may passively spread in brain tissue over long distances and be falsely interpreted as local activity at such distant recording sites. Here we show that the whisker-evoked potentials in the thalamic nuclei are of local origin up to around 6 ms post stimulus, but the later (7-15 ms) wave is overshadowed by a negative component reaching from cortex. This component can be analytically removed and local thalamic LFP can be recovered reliably using Current Source Density analysis. We used model-based kernel CSD (kCSD) method which allowed us to study the contribution of local and distant currents to LFP from rat thalamic nuclei and barrel cortex recorded with multiple, non-linear and non-regular multichannel probes. Importantly, we verified that concurrent recordings from the cortex are not essential for reliable thalamic CSD estimation. The proposed framework can be used to analyze LFP from other brain areas and has consequences for general LFP interpretation and analysis.
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Affiliation(s)
- Władysław Średniawa
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Zuzanna Borzymowska
- Neurobiology of Emotions Laboratory, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Kacper Kondrakiewicz
- Neurobiology of Emotions Laboratory, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Paweł Jurgielewicz
- AGH University of Science and Technology in Kraków, Faculty of Physics and Applied Computer Science, Krakow, Poland
| | - Bartosz Mindur
- AGH University of Science and Technology in Kraków, Faculty of Physics and Applied Computer Science, Krakow, Poland
| | - Paweł Hottowy
- AGH University of Science and Technology in Kraków, Faculty of Physics and Applied Computer Science, Krakow, Poland
| | - Daniel K. Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- Jagiellonian University, Faculty of Management and Social Communication, Jagiellonian University, Krakow, Poland
| | - Ewa Kublik
- Neurobiology of Emotions Laboratory, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
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Shokri M, Gogliettino AR, Hottowy P, Sher A, Litke AM, Chichilnisky EJ, Pequito S, Muratore D. Spike sorting in the presence of stimulation artifacts: a dynamical control systems approach. J Neural Eng 2024; 21:016022. [PMID: 38271715 PMCID: PMC10853761 DOI: 10.1088/1741-2552/ad228f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 11/08/2023] [Accepted: 01/25/2024] [Indexed: 01/27/2024]
Abstract
Objective. Bi-directional electronic neural interfaces, capable of both electrical recording and stimulation, communicate with the nervous system to permit precise calibration of electrical inputs by capturing the evoked neural responses. However, one significant challenge is that stimulation artifacts often mask the actual neural signals. To address this issue, we introduce a novel approach that employs dynamical control systems to detect and decipher electrically evoked neural activity despite the presence of electrical artifacts.Approach. Our proposed method leverages the unique spatiotemporal patterns of neural activity and electrical artifacts to distinguish and identify individual neural spikes. We designed distinctive dynamical models for both the stimulation artifact and each neuron observed during spontaneous neural activity. We can estimate which neurons were active by analyzing the recorded voltage responses across multiple electrodes post-stimulation. This technique also allows us to exclude signals from electrodes heavily affected by stimulation artifacts, such as the stimulating electrode itself, yet still accurately differentiate between evoked spikes and electrical artifacts.Main results. We applied our method to high-density multi-electrode recordings from the primate retina in anex vivosetup, using a grid of 512 electrodes. Through repeated electrical stimulations at varying amplitudes, we were able to construct activation curves for each neuron. The curves obtained with our method closely resembled those derived from manual spike sorting. Additionally, the stimulation thresholds we estimated strongly agreed with those determined through manual analysis, demonstrating high reliability (R2=0.951for human 1 andR2=0.944for human 2).Significance. Our method can effectively separate evoked neural spikes from stimulation artifacts by exploiting the distinct spatiotemporal propagation patterns captured by a dense, large-scale multi-electrode array. This technique holds promise for future applications in real-time closed-loop stimulation systems and for managing multi-channel stimulation strategies.
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Affiliation(s)
- Mohammad Shokri
- Delft Center for Systems and Control, Delft University of Technology, Delft 2628 CN, The Netherlands
| | - Alex R Gogliettino
- Neurosciences PhD Program, Stanford University, Stanford, CA 94305, United States of America
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA 94305, United States of America
| | - Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA, United States of America
| | - Alan M Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA, United States of America
| | - E J Chichilnisky
- Departments of Neurosurgery and Ophthalmology, Stanford University, Stanford, CA 94305, United States of America
| | - Sérgio Pequito
- Division of Systems and Control, Department of Information Technology, Uppsala University, 751 05 Uppsala, Sweden
| | - Dante Muratore
- Microelectronics Department, Delft University of Technology, Delft 2628 CN, The Netherlands
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Madugula SS, Vilkhu R, Shah NP, Grosberg LE, Kling A, Gogliettino AR, Nguyen H, Hottowy P, Sher A, Litke AM, Chichilnisky EJ. Inference of Electrical Stimulation Sensitivity from Recorded Activity of Primate Retinal Ganglion Cells. J Neurosci 2023; 43:4808-4820. [PMID: 37268418 PMCID: PMC10312054 DOI: 10.1523/jneurosci.1023-22.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 06/04/2023] Open
Abstract
High-fidelity electronic implants can in principle restore the function of neural circuits by precisely activating neurons via extracellular stimulation. However, direct characterization of the individual electrical sensitivity of a large population of target neurons, to precisely control their activity, can be difficult or impossible. A potential solution is to leverage biophysical principles to infer sensitivity to electrical stimulation from features of spontaneous electrical activity, which can be recorded relatively easily. Here, this approach is developed and its potential value for vision restoration is tested quantitatively using large-scale multielectrode stimulation and recording from retinal ganglion cells (RGCs) of male and female macaque monkeys ex vivo Electrodes recording larger spikes from a given cell exhibited lower stimulation thresholds across cell types, retinas, and eccentricities, with systematic and distinct trends for somas and axons. Thresholds for somatic stimulation increased with distance from the axon initial segment. The dependence of spike probability on injected current was inversely related to threshold, and was substantially steeper for axonal than somatic compartments, which could be identified by their recorded electrical signatures. Dendritic stimulation was largely ineffective for eliciting spikes. These trends were quantitatively reproduced with biophysical simulations. Results from human RGCs were broadly similar. The inference of stimulation sensitivity from recorded electrical features was tested in a data-driven simulation of visual reconstruction, revealing that the approach could significantly improve the function of future high-fidelity retinal implants.SIGNIFICANCE STATEMENT This study demonstrates that individual in situ primate retinal ganglion cells of different types respond to artificially generated, external electrical fields in a systematic manner, in accordance with theoretical predictions, that allows for prediction of electrical stimulus sensitivity from recorded spontaneous activity. It also provides evidence that such an approach could be immensely helpful in the calibration of clinical retinal implants.
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Affiliation(s)
- Sasidhar S Madugula
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- School of Medicine, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Ramandeep Vilkhu
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Nishal P Shah
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Lauren E Grosberg
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Facebook Reality Labs, Facebook, Mountain View, California 94040
| | - Alexandra Kling
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Alex R Gogliettino
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Huy Nguyen
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland 30-059
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, California 95064
| | - Alan M Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, California 95064
| | - E J Chichilnisky
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Ophthalmology, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
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Gogliettino AR, Madugula SS, Grosberg LE, Vilkhu RS, Brown J, Nguyen H, Kling A, Hottowy P, Dąbrowski W, Sher A, Litke AM, Chichilnisky EJ. High-Fidelity Reproduction of Visual Signals by Electrical Stimulation in the Central Primate Retina. J Neurosci 2023; 43:4625-4641. [PMID: 37188516 PMCID: PMC10286946 DOI: 10.1523/jneurosci.1091-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 05/17/2023] Open
Abstract
Electrical stimulation of retinal ganglion cells (RGCs) with electronic implants provides rudimentary artificial vision to people blinded by retinal degeneration. However, current devices stimulate indiscriminately and therefore cannot reproduce the intricate neural code of the retina. Recent work has demonstrated more precise activation of RGCs using focal electrical stimulation with multielectrode arrays in the peripheral macaque retina, but it is unclear how effective this can be in the central retina, which is required for high-resolution vision. This work probes the neural code and effectiveness of focal epiretinal stimulation in the central macaque retina, using large-scale electrical recording and stimulation ex vivo The functional organization, light response properties, and electrical properties of the major RGC types in the central retina were mostly similar to the peripheral retina, with some notable differences in density, kinetics, linearity, spiking statistics, and correlations. The major RGC types could be distinguished by their intrinsic electrical properties. Electrical stimulation targeting parasol cells revealed similar activation thresholds and reduced axon bundle activation in the central retina, but lower stimulation selectivity. Quantitative evaluation of the potential for image reconstruction from electrically evoked parasol cell signals revealed higher overall expected image quality in the central retina. An exploration of inadvertent midget cell activation suggested that it could contribute high spatial frequency noise to the visual signal carried by parasol cells. These results support the possibility of reproducing high-acuity visual signals in the central retina with an epiretinal implant.SIGNIFICANCE STATEMENT Artificial restoration of vision with retinal implants is a major treatment for blindness. However, present-day implants do not provide high-resolution visual perception, in part because they do not reproduce the natural neural code of the retina. Here, we demonstrate the level of visual signal reproduction that is possible with a future implant by examining how accurately responses to electrical stimulation of parasol retinal ganglion cells can convey visual signals. Although the precision of electrical stimulation in the central retina was diminished relative to the peripheral retina, the quality of expected visual signal reconstruction in parasol cells was greater. These findings suggest that visual signals could be restored with high fidelity in the central retina using a future retinal implant.
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Affiliation(s)
- Alex R Gogliettino
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Sasidhar S Madugula
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Stanford School of Medicine, Stanford University, Stanford, California 94305
| | - Lauren E Grosberg
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Ramandeep S Vilkhu
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Jeff Brown
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Huy Nguyen
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Alexandra Kling
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059, Kraków, Poland
| | - Władysław Dąbrowski
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059, Kraków, Poland
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California 95064
| | - Alan M Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California 95064
| | - E J Chichilnisky
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
- Department of Ophthalmology, Stanford University, Stanford, California 94305
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Kołodziej K, Dąbrowski W, Hottowy P. Cancellation of the stimulation artifacts by stimulus-dependent nanoampere correction pulses. Front Cell Neurosci 2018. [DOI: 10.3389/conf.fncel.2018.38.00122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Mena GE, Grosberg LE, Madugula S, Hottowy P, Litke A, Cunningham J, Chichilnisky EJ, Paninski L. Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays. PLoS Comput Biol 2017; 13:e1005842. [PMID: 29131818 PMCID: PMC5703587 DOI: 10.1371/journal.pcbi.1005842] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Revised: 11/27/2017] [Accepted: 10/20/2017] [Indexed: 11/18/2022] Open
Abstract
Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.
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Affiliation(s)
- Gonzalo E. Mena
- Statistics Department, Columbia University, New York, New York, United States of America
| | - Lauren E. Grosberg
- Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America
| | - Sasidhar Madugula
- Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America
| | - Paweł Hottowy
- Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland
| | - Alan Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California, United States of America
| | - John Cunningham
- Statistics Department, Columbia University, New York, New York, United States of America
- Grossman Center for the Statistics of Mind and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America
| | - E. J. Chichilnisky
- Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America
| | - Liam Paninski
- Statistics Department, Columbia University, New York, New York, United States of America
- Grossman Center for the Statistics of Mind and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America
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Gunning DE, Beggs JM, Dabrowski W, Hottowy P, Kenney CJ, Sher A, Litke AM, Mathieson K. Dense arrays of micro-needles for recording and electrical stimulation of neural activity in acute brain slices. J Neural Eng 2012; 10:016007. [PMID: 23234809 DOI: 10.1088/1741-2560/10/1/016007] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE This paper describes the design, microfabrication, electrical characterization and biological evaluation of a high-density micro-needle array. The array records from and electrically stimulates individual neurons simultaneously in acute slices of brain tissue. APPROACH Acute slices, arguably the closest in-vitro model of the brain, have a damaged surface layer. Since electrophysiological recording methods rely heavily on electrode-cell proximity, this layer significantly attenuates the signal amplitude making the use of traditional planar electrodes unsuitable. To penetrate into the tissue, bypassing the tissue surface, and to record and stimulate neural activity in the healthy interior volume of the slice, an array of 61 micro-needles was fabricated. MAIN RESULTS This device is shown to record extracellular action potentials from individual neurons in acute cortical slices with a signal to noise ratio of up to ∼15:1. Electrical stimulation of individual neurons is achieved with stimulation thresholds of 1.1-2.9 µA. SIGNIFICANCE The novelty of this system is the combination of close needle spacing (60 µm), needle heights of up to 250 µm and small (5-10 µm diameter) electrodes allowing the recording of single unit activity. The array is coupled to a custom-designed readout system forming a powerful electrophysiological tool that permits two-way electrode-cell communication with populations of neurons in acute brain slices.
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Affiliation(s)
- D E Gunning
- IOP, University of Strathclyde, Glasgow G4 0NW, UK.
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Hottowy P, Skoczeń A, Gunning DE, Kachiguine S, Mathieson K, Sher A, Wiącek P, Litke AM, Dąbrowski W. Properties and application of a multichannel integrated circuit for low-artifact, patterned electrical stimulation of neural tissue. J Neural Eng 2012; 9:066005. [PMID: 23160018 DOI: 10.1088/1741-2560/9/6/066005] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Modern multielectrode array (MEA) systems can record the neuronal activity from thousands of electrodes, but their ability to provide spatio-temporal patterns of electrical stimulation is very limited. Furthermore, the stimulus-related artifacts significantly limit the ability to record the neuronal responses to the stimulation. To address these issues, we designed a multichannel integrated circuit for a patterned MEA-based electrical stimulation and evaluated its performance in experiments with isolated mouse and rat retina. APPROACH The Stimchip includes 64 independent stimulation channels. Each channel comprises an internal digital-to-analogue converter that can be configured as a current or voltage source. The shape of the stimulation waveform is defined independently for each channel by the real-time data stream. In addition, each channel is equipped with circuitry for reduction of the stimulus artifact. MAIN RESULTS Using a high-density MEA stimulation/recording system, we effectively stimulated individual retinal ganglion cells (RGCs) and recorded the neuronal responses with minimal distortion, even on the stimulating electrodes. We independently stimulated a population of RGCs in rat retina, and using a complex spatio-temporal pattern of electrical stimulation pulses, we replicated visually evoked spiking activity of a subset of these cells with high fidelity. Significance. Compared with current state-of-the-art MEA systems, the Stimchip is able to stimulate neuronal cells with much more complex sequences of electrical pulses and with significantly reduced artifacts. This opens up new possibilities for studies of neuronal responses to electrical stimulation, both in the context of neuroscience research and in the development of neuroprosthetic devices.
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Affiliation(s)
- Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland.
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