Abstract
Neuromodulation technologies are crucial for investigating neuronal connectivity and brain function. Magnetic neuromodulation offers wireless and remote deep brain stimulations that are lacking in optogenetic- and wired-electrode-based tools. However, due to the limited understanding of working principles and poorly designed magnetic operating systems, earlier magnetic approaches have yet to be utilized. Furthermore, despite its importance in neuroscience research, cell-type-specific magnetic neuromodulation has remained elusive. Here we present a nanomaterials-based magnetogenetic toolbox, in conjunction with Cre-loxP technology, to selectively activate genetically encoded Piezo1 ion channels in targeted neuronal populations via torque generated by the nanomagnetic actuators in vitro and in vivo. We demonstrate this cell-type-targeting magnetic approach for remote and spatiotemporal precise control of deep brain neural activity in multiple behavioural models, such as bidirectional feeding control, long-term neuromodulation for weight control in obese mice and wireless modulation of social behaviours in multiple mice in the same physical space. Our study demonstrates the potential of cell-type-specific magnetogenetics as an effective and reliable research tool for life sciences, especially in wireless, long-term and freely behaving animals.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Previously published genomic sequence data that were re-analysed here are available from Ensembl for the Piezo1 protein from Mus musculus (gene ID ENSMUSG00000014444, GenBank: HQ215520.1). All raw unprocessed videos are available via figshare at https://doi.org/10.6084/m9.figshare.26021482 (ref. 60). All raw images acquired using confocal and IVIS optical imaging and additional data that support the findings of this study are available from the corresponding authors upon reasonable request. Additional information is available from the corresponding authors upon reasonable request. Source data are provided with this paper.
Code availability
Custom Python code used for analysing the behavioural tests is available via GitHub at https://github.com/DHSHINN/Magnetogenetics.
References
Deisseroth, K. Optogenetics: 10 years of microbial opsins in neuroscience. Nat. Neurosci. 18, 1213–1225 (2015).
Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005).
Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M. & Deisseroth, K. Optogenetics in neural systems. Neuron 71, 9–34 (2011).
Rabut, C. et al. Ultrasound technologies for imaging and modulating neural activity. Neuron 108, 93–110 (2020).
Won, S. M., Song, E., Reeder, J. T. & Rogers, J. A. Emerging modalities and implantable technologies for neuromodulation. Cell 181, 115–135 (2020).
Yang, Y. et al. Wireless multilateral devices for optogenetic studies of individual and social behaviors. Nat. Neurosci. 24, 1035–1045 (2021).
Walsh, V. & Cowey, A. Transcranial magnetic stimulation and cognitive neuroscience. Nat. Rev. Neurosci. 1, 73–79 (2000).
Christiansen, M. G., Senko, A. W. & Anikeeva, P. Magnetic strategies for nervous system control. Annu. Rev. Neurosci. 42, 271–293 (2019).
Gregurec, D. et al. Magnetic vortex nanodiscs enable remote magnetomechanical neural stimulation. ACS Nano 14, 8036–8045 (2020).
Chen, R., Romero, G., Christiansen, M. G., Mohr, A. & Anikeeva, P. Wireless magnetothermal deep brain stimulation. Science 347, 1477–1480 (2015).
Munshi, R. et al. Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice. eLife 6, e27069 (2017).
Del Sol-Fernandez, S. et al. Magnetogenetics: remote activation of cellular functions triggered by magnetic switches. Nanoscale 14, 2091–2118 (2022).
Tay, A., Sohrabi, A., Poole, K., Seidlits, S. & Di Carlo, D. A 3D magnetic hyaluronic acid hydrogel for magnetomechanical neuromodulation of primary dorsal root ganglion neurons. Adv. Mater. 10, e1800927 (2018).
Stanley, S. A. et al. Bidirectional electromagnetic control of the hypothalamus regulates feeding and metabolism. Nature 531, 647–650 (2016).
Tay, A. & Di Carlo, D. Magnetic nanoparticle-based mechanical stimulation for restoration of mechano-sensitive ion channel equilibrium in neural networks. Nano Lett. 17, 886–892 (2017).
Sebesta, C. et al. Subsecond multichannel magnetic control of select neural circuits in freely moving flies. Nat. Mater. 21, 951–958 (2022).
Lee, J. U. et al. Non-contact long-range magnetic stimulation of mechanosensitive ion channels in freely moving animals. Nat. Mater. 20, 1029–1036 (2021).
Xu, F. X. et al. Magneto is ineffective in controlling electrical properties of cerebellar Purkinje cells. Nat. Neurosci. 23, 1041–1043 (2020).
Wang, G. et al. Revaluation of magnetic properties of Magneto. Nat. Neurosci. 23, 1047–1050 (2020).
Kole, K. et al. Assessing the utility of Magneto to control neuronal excitability in the somatosensory cortex. Nat. Neurosci. 23, 1044–1046 (2020).
Wheeler, M. A. et al. Genetically targeted magnetic control of the nervous system. Nat. Neurosci. 19, 756–761 (2016).
Meister, M. Physical limits to magnetogenetics. eLife 5, e17210 (2016).
Shin, W. et al. Magnetogenetics with Piezo1 mechanosensitive ion channel for CRISPR gene editing. Nano Lett. 22, 7415–7422 (2022).
Madisen, L. et al. A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing. Nat. Neurosci. 15, 793–802 (2012).
Zhang, F., Aravanis, A. M., Adamantidis, A., de Lecea, L. & Deisseroth, K. Circuit-breakers: optical technologies for probing neural signals and systems. Nat. Rev. Neurosci. 8, 577–581 (2007).
Taniguchi, H. et al. A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex. Neuron 71, 995–1013 (2011).
Gong, S. et al. Targeting Cre recombinase to specific neuron populations with bacterial artificial chromosome constructs. J. Neurosci. 27, 9817–9823 (2007).
Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010).
Coste, B. et al. Piezo1 ion channel pore properties are dictated by C-terminal region. Nat. Commun. 6, 7223 (2015).
Moroni, M., Servin-Vences, M. R., Fleischer, R., Sanchez-Carranza, O. & Lewin, G. R. Voltage gating of mechanosensitive PIEZO channels. Nat. Commun. 9, 1096 (2018).
Del Marmol, J. I., Touhara, K. K., Croft, G. & MacKinnon, R. Piezo1 forms a slowly-inactivating mechanosensory channel in mouse embryonic stem cells. eLife 7, e33149 (2018).
Bae, C., Gnanasambandam, R., Nicolai, C., Sachs, F. & Gottlieb, P. A. Xerocytosis is caused by mutations that alter the kinetics of the mechanosensitive channel PIEZO1. Proc. Natl Acad. Sci. USA 110, E1162–E1168 (2013).
Wang, L. et al. Structure and mechanogating of the mammalian tactile channel PIEZO2. Nature 573, 225–229 (2019).
Wojcik, S. M. et al. A shared vesicular carrier allows synaptic corelease of GABA and glycine. Neuron 50, 575–587 (2006).
Moechars, D. et al. Vesicular glutamate transporter VGLUT2 expression levels control quantal size and neuropathic pain. J. Neurosci. 26, 12055–12066 (2006).
Stuber, G. D. & Wise, R. A. Lateral hypothalamic circuits for feeding and reward. Nat. Neurosci. 19, 198–205 (2016).
Jennings, J. H., Rizzi, G., Stamatakis, A. M., Ung, R. L. & Stuber, G. D. The inhibitory circuit architecture of the lateral hypothalamus orchestrates feeding. Science 341, 1517–1521 (2013).
Nectow, A. R. et al. Identification of a brainstem circuit controlling feeding. Cell 170, 429–442 e411 (2017).
Jennings, J. H. et al. Visualizing hypothalamic network dynamics for appetitive and consummatory behaviors. Cell 160, 516–527 (2015).
Nieh, E. H. et al. Decoding neural circuits that control compulsive sucrose seeking. Cell 160, 528–541 (2015).
Wu, Z. et al. GABAergic projections from lateral hypothalamus to paraventricular hypothalamic nucleus promote feeding. J. Neurosci. 35, 3312–3318 (2015).
Sidor, M. M. & McClung, C. A. Timing matters: using optogenetics to chronically manipulate neural circuitry and rhythms. Front. Behav. Neurosci. 8, 41 (2014).
Gunaydin, L. A. et al. Natural neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014).
Yizhar, O. Optogenetic insights into social behavior function. Biol. Psychiatry 71, 1075–1080 (2012).
Singer, A. et al. Magnetoelectric materials for miniature, wireless neural stimulation at therapeutic frequencies. Neuron 107, 631–643 e635 (2020).
Huang, W. C., Zucca, A., Levy, J. & Page, D. T. Social behavior is modulated by valence-encoding mPFC-amygdala sub-circuitry. Cell Rep. 32, 107899 (2020).
Wang, J. et al. Basal forebrain mediates prosocial behavior via disinhibition of midbrain dopamine neurons. Proc. Natl Acad. Sci. USA 118, e2019295118 (2021).
Anpilov, S. et al. Wireless optogenetic stimulation of oxytocin neurons in a semi-natural setup dynamically elevates both pro-social and agonistic behaviors. Neuron 107, 644–655 e647 (2020).
Nieh, E. H. et al. Inhibitory input from the lateral hypothalamus to the ventral tegmental area disinhibits dopamine neurons and promotes behavioral activation. Neuron 90, 1286–1298 (2016).
Kohl, J. et al. Functional circuit architecture underlying parental behaviour. Nature 556, 326–331 (2018).
Kohl, J. Parenting—a paradigm for investigating the neural circuit basis of behavior. Curr. Opin. Neurobiol. 60, 84–91 (2020).
Fang, Y. Y., Yamaguchi, T., Song, S. C., Tritsch, N. X. & Lin, D. A hypothalamic midbrain pathway essential for driving maternal behaviors. Neuron 98, 192–207 e110 (2018).
Zhang, G. W. et al. Medial preoptic area antagonistically mediates stress-induced anxiety and parental behavior. Nat. Neurosci. 24, 516–528 (2021).
Sternson, S. M. & Roth, B. L. Chemogenetic tools to interrogate brain functions. Annu. Rev. Neurosci. 37, 387–407 (2014).
Alexander, G. M. et al. Remote control of neuronal activity in transgenic mice expressing evolved G protein-coupled receptors. Neuron 63, 27–39 (2009).
Magnus, C. J. et al. Ultrapotent chemogenetics for research and potential clinical applications. Science 364, eaav5282 (2019).
Jang, J. T. et al. Critical enhancements of MRI contrast and hyperthermic effects by dopant-controlled magnetic nanoparticles. Angew. Chem. Int. Ed. 48, 1234–1238 (2009).
Jewett, J. C. & Bertozzi, C. R. Cu-free click cycloaddition reactions in chemical biology. Chem. Soc. Rev. 39, 1272–1279 (2010).
Borgius, L., Restrepo, C. E., Leao, R. N., Saleh, N. & Kiehn, O. A transgenic mouse line for molecular genetic analysis of excitatory glutamatergic neurons. Mol. Cell. Neurosci. 45, 245–257 (2010).
Choi, S.-H. et al. Animal behavior dataset of magnetogenetics for cell-type specific neuromodulation. figshare, https://doi.org/10.6084/m9.figshare.26021482 (2024).
Acknowledgements
We thank A. Patapoutian (The Scripps Research Institute) for the kind gift of Myc897-Piezo1 in pcDNA3.1 plasmid. This work was supported by the Institute for Basic Science (IBS-R026-D1).
Author information
Authors and Affiliations
Contributions
J.C. supervised the overall project. M.K. and J.C. conceived the project. S.-H.C., J.S., J.-u.L., J.L., R.Y., W.S. and K.N. performed all the in vitro and in vivo MMG experiments. J.-u.L., J.-Y.K., J.D.L. and G.K. provided the m-Torquer and MMG setup. C.P. and Y.A. performed the electrophysiology experiments. W.K. and C.J.L. provided support for the electrophysiology setup. D.S. developed the in vivo behavioural analysis codes. J.-H.L., M.K. and J.C. wrote the manuscript with contributions from all authors.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Nanotechnology thanks Felix Leroy and Andy Tay for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Experimental setup of MMG apparatus and electron microscope image of m-Torquer for wireless neuromodulation in vivo.
(a) General components of MMG apparatus. The system consists of a rotational magnetic force generator (MFG), an Arduino controller, and a user interface system. (b) Photographs showing top and side views of MMG apparatus of different bore diameters. The 16-cm, 35-cm, and 70-cm MMG apparatus are designed for cell-based experiments, in vivo studies of a single mouse, and in vivo large-area behavioral studies of multiple animals, respectively. Scale bars, 5 cm. (c) 3D illustrations of 16-, 35-, and 70-cm MMG apparatus showing the configuration of the magnetic arrays, including the numbers, dimensions, positions, and angles of magnets. (d) Dynamic changes of the magnitudes of x-component (Bx), y-component (By), and combined total (Btotal) magnetic field. (e) SEM image of an m-Torquer. The 200 nm m-Torquer is composed of assembled monolayer octahedral magnetic nanoparticles on spherical support via click chemistry. Scale bar, 100 nm.
Extended Data Fig. 2 In situ calcium influx analysis of neurons with X-Rhod-1.
(a) False-colour coded images of fluorescence of neurons with and without Piezo1 expression, m-Torquer, or rotating magnetic field, respectively. A single magnetic pulse was given at t = 0 s for 0.5 s. (b) Calcium fluorescence intensity plots corresponding to images in (a). Rapid increase of calcium influx was observed only for the m-Torquer-bound Piezo1-expressing neurons in response to magnetic stimulation, while all control neurons without either m-Torquer, Piezo1 expression, or magnetic field showed no calcium response.
Extended Data Fig. 3 Electrophysiological recording of Piezo1-expressing HEK cells in response to MMG stimulation.
(a) Confocal microscope images of a Piezo1-expressing HEK293 cell labeled with 200 nm m-Torquer on the cell surface. (b) Schematic illustration showing a patch-clamp set-up for electrophysiological recording during MMG stimulation. (c) Whole-cell voltage-clamp trace (at −60 mV) from a Piezo1-expressing (black) and an EGFP-transfected (grey) HEK293 cell evoked by a single pulse (180° s-1) MMG stimulation. (right inset) Quantification of peak current amplitudes. Data are the mean ± s.d. of n = 11 for Vehicle; n = 10 for Piezo1 biological independent samples. ***p = 0.0003; two-tailed unpaired Student’s t-test with Welch’s correction. (d) Current traces recorded from a Piezo1- and EGFP-expressing HEK cell in response to a train of 6 repetitive magnetic pulses. Each black bar represents a single magnetic pulse with a 1.0 s duration at 180° s-1 rotating speed.
Extended Data Fig. 4 The expression and activity of Myc897-Piezo1 in the LHA.
(a) Immunohistochemistry images of brain slices showing Piezo1 expression in the LHA region of Vglut2-Piezo1 mouse. Blue, DAPI (nucleus); Green, Piezo1. Scale bar, 200 μm. (b) Membrane expression of Piezo1 in the LHA region of Vgat-Piezo1 mouse. Blue, DAPI (nucleus); Green, Piezo1. Scale bar, 20 μm. (c, d) Fluorescence histology images of brain slices showing Piezo1 (green) and c-Fos expression (red) at the LHA of Vgat- or Vglut2-Piezo1 mouse upon Yoda1 treatment. Blue, DAPI (nucleus). The expression of c-Fos was detected only in the Piezo1-expressing mice upon Yoda1 treatment, confirming the function of Piezo1 ion channels. Scale bars, 50 μm.
Extended Data Fig. 5 Histological analysis against in vivo c-Fos expression in the LHA of Vgat- or Vglut2-Cre mice.
(a, b) Fluorescence histology images against c-Fos (red) to evaluate in vivo neuronal excitation in LHA of (a) Vgat-Cre or (b) Vglut2-Cre mice under various conditions. Extensive MMG-driven c-Fos expression was observed only in the presence of both m-Torquer and Piezo1 with magnetic stimulation. Blue, DAPI (nucleus). (c, d) Quantification of c-Fos-positive cells in the LHA of (c) Vgat-Cre or (d) Vglut2-Cre under the eight conditions. (a, b) Scale bars, 50 µm. (c, d) One-way ANOVA with multiple comparison test; F(7, 16) = 41.42, p < 0.0001 for (c). Data are mean ± s.d. **p = 0.0027; n.s., non-significant; two-tailed unpaired Student’s t-test for (c). One-way ANOVA with multiple comparison test; F(7, 16) = 81.95, p < 0.0001 for (d). Data are mean ± s.d. ***p = 0.0008; n.s., non-significant; two-tailed unpaired Student’s t-test for (d). All data shown are the mean ± s.d. of n = 3 animals.
Extended Data Fig. 6 Long-term, repeatable cell-type specific neuromodulation for modulating intake and fat mass in HFD obese mice.
(a) Statistical analysis of total food intake after long-term MMG stimulation in Vglut2 HFD mice. Food intakes are measured daily. One-way ANOVA with multiple comparison test; F(3, 16) = 4.619, p = 0.0164. Data are mean ± s.d. **p = 0.0045, **p = 0.0049; two-tailed unpaired Student’s t-test; n = 5 (Piezo1-m-Torquer-), 4 (Piezo1-m-Torquer + ), 5 (Piezo1+m-Torquer-) and 6 (Piezo1+m-Torquer + ) animals, respectively. (b) Statistical analysis of total food intake after long-term MMG stimulation in Vgat HFD mice. Food intakes are measured daily. One-way ANOVA with multiple comparison test; F(3, 12) = 8.523, p = 0.0027. Data are mean ± s.d. *p = 0.0220, **p = 0.0022; two-tailed unpaired Student’s t-test; n = 3 (Piezo1-m-Torquer-), 3 (Piezo1-m-Torquer + ), 5 (Piezo1+m-Torquer-) and 5 (Piezo1+m-Torquer + ) animals, respectively. (c, d) Photographs of white adipose tissues acquired from (c) Vglut2 HFD mice and (d) Vgat HFD mice. Scale bars in (c, d), 1 cm.
Extended Data Fig. 7 Assessment of chronic biocompatibility of m-Torquer injection.
(a–c) Fluorescence histology images of brain slices showing (a) astrocytes (GFAP), (b) activated microglia (Iba1), and (c) neurons (NeuN) at the LHA of Vglut2-HFD mice after long-term MMG stimulation. Scale bar, 100 μm, Scale bar, 200 μm,.
Extended Data Fig. 8 Quantification of social preference by discrimination indexes in single and multiple animal during MMG stimulation.
Quantification of the discrimination indexes in (a, c) the sociability test and (b, d) the social novelty test during MMG stimulation. (a, b) Quantification of the discrimination indexes with single animal using MMG. Data are mean ± s.d. ***p = 0.0003 (a), ***p = 0.0004 (b); two-tailed unpaired Student’s t-test; n = 7 for Vgat-Piezo1 mice without m-Torquer; n = 6 for Vgat-Piezo1 mice with m-Torquer animals per group. (c, d) Quantification of the discrimination indexes with multiple animals using MMG. Data are mean ± s.d. **p = 0.0016, ***p = 0.0003; two-tailed unpaired Student’s t-test; n = 6 for Vgat-Piezo1 mice without m-Torquer; n = 6 for Vgat-Piezo1 mice with m-Torquer animals per group for (c). p = 0.0093, p = 0.0016 Quantification of the discrimination indexes with multiple animals using MMG. Data are mean ± s.d. **p = 0.0093 (M1), **p = 0.0016 (M2); two-tailed unpaired Student’s t-test; n = 6 for Vgat-Piezo1 mice without m-Torquer; n = 6 for Vgat-Piezo1 mice with m-Torquer animals per group for (d).
Extended Data Fig. 9 Cre-dependent Piezo1 activation with MMG stimulation in the pseudo primate brain.
(a) Phantom model of a primate brain for long-range stimulation at the magnetically targeted position. (b) 3D printed primate brain phantom. Matrigel-embedded Piezo1 cells are cultured in the 3D large animal brain phantom to make in vivo-comparable conditions. (c) RT-PCR analysis of HEK293 cells co-transfected Cre and FLEX-Piezo1 confirming increased c-Fos expression in response to MMG stimulation. (d) Bioluminescence imaging (BLI) showing a higher luciferase expression in response to Cre-dependent magnetomechanical activation of Piezo1-based transcription in 3D primate brain phantom model. (e) MMG stimulation induces transcription of the intracellular Ca2+ -dependent luciferase reporter. All data are presented as mean ± s.d.; ***p = 0.006; two-tailed unpaired Student’s t-test; n = 3 biological replicates.
Supplementary information
Supplementary Information
Supplementary Figs. 1–12, Notes 1 and 2, captions for Videos 1–9, Methods, references and source data for Fig. 12.
Supplementary Video 1
Rotational MFGs and their real-time magnetic field strength profiles with various sizes of 16, 35 and 70 cm.
Supplementary Video 2
Wireless MMG stimulation of a Vgat-Cre mouse with Piezo1 and m-Torquer in an open-chamber, free-access feeding task. Vgat-specific MMG stimulation of the LHA induced fast and robust feeding behaviours in this freely behaving mouse.
Supplementary Video 3
Reversible control of feeding behaviours in a Vgat-Cre mouse with Piezo1 and m-Torquer. Each video clip shows the behaviours of the same mouse for 3 min during pre-stimulation (left), stimulation (middle) and post-stimulation (right). During the stimulation, the mouse exhibited markedly increased feeding behaviour, whereas the same animal did not during pre- and post-stimulation.
Supplementary Video 4
Reversible control of feeding behaviours in a Vglut2-Cre mouse with Piezo1 and m-Torquer. Each video clip shows the behaviours of the same mouse for 3 min during pre-stimulation (left), stimulation (middle) and post-stimulation (right). During the stimulation, the mouse exhibited markedly reduced feeding behaviour, whereas the same animal tended to show more interest in food.
Supplementary Video 5
A Vgat-Cre mouse with Piezo1 expression and m-Torquer in the LHA during the three-chambered sociability test on MMG stimulation. The mouse showed an increased preference for a novel mouse (right chamber) than empty chamber (left chamber) in response to a magnetic field.
Supplementary Video 6
A Vgat-Cre mouse with Piezo1 expression and m-Torquer in the LHA during the three-chambered sociability novelty test on MMG stimulation. The mouse showed an increased preference for a novel mouse (left chamber) than a familiar mouse (right chamber) in response to a magnetic field.
Supplementary Video 7
Sociality test of two freely moving mice on wireless MMG stimulation. This video highlights that a pair of Vgat-Piezo1 mice with m-Torquer showed synchronized behaviours with increased interactions with a novel mouse than the empty chamber, whereas a pair of control mice without m-Torquer showed random activity without such preference for social interaction.
Supplementary Video 8
Social novelty test of two freely moving mice on wireless MMG stimulation. This video highlights that a pair of Vgat-Piezo1 mice showed increased interactions with a novel mouse than a familiar mouse in a synchronized fashion on MMG stimulation, whereas a pair of control mice without m-Torquer showed random activity without such preference for social novelty.
Supplementary Video 9
Parental behaviour test of two freely moving mice on wireless MMG stimulation in a semi-natural setup. This video highlights increased parental behaviour, such as pup retrieval, of Vgat-Piezo1 mice in response to MMG, whereas the control mice (GFP+ m-Torquer+) did not show any noticeable increase in such behaviour.
Supplementary Data 1
Statistical source data for Supplementary Fig. 1.
Supplementary Data 2
Statistical source data for Supplementary Fig. 2.
Supplementary Data 3
Statistical source data for Supplementary Fig. 3.
Supplementary Data 4
Statistical source data for Supplementary Fig. 4.
Supplementary Data 5
Statistical source data for Supplementary Fig. 5.
Supplementary Data 6
Statistical source data for Supplementary Fig. 6.
Supplementary Data 7
Statistical source data for Supplementary Fig. 7.
Supplementary Data 8
Statistical source data for Supplementary Fig. 8.
Supplementary Data 9
Statistical source data for Supplementary Fig. 9.
Supplementary Data 10
Statistical source data for Supplementary Fig. 10.
Supplementary Data 11
Statistical source data for Supplementary Fig. 11.
Supplementary Data 12
Unprocessed gels for Supplementary Fig. 12.
Source data
Source Data Fig. 1
Statistical source data for Fig. 1.
Source Data Fig. 2
Statistical source data for Fig. 2.
Source Data Fig. 3
Statistical source data for Fig. 3.
Source Data Fig. 4
Statistical source data for Fig. 4.
Source Data Fig. 5
Statistical source data for Fig. 5.
Source Data Extended Data Fig. 1
Statistical source data for Extended Data Fig. 1.
Source Data Extended Data Fig. 2
Statistical source data for Extended Data Fig. 2.
Source Data Extended Data Fig. 3
Statistical source data for Extended Data Fig. 3.
Source Data Extended Data Fig. 5
Statistical source data for Extended Data Fig. 5.
Source Data Extended Data Fig. 6
Statistical source data for Extended Data Fig. 6.
Source Data Extended Data Fig. 8
Statistical source data for Extended Data Fig. 8.
Source Data Extended Data Fig. 9
Statistical source data for Extended Data Fig. 9.
Source Data Extended Data Fig. 9
Unprocessed gels for Extended Data Fig. 9.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Choi, SH., Shin, J., Park, C. et al. In vivo magnetogenetics for cell-type-specific targeting and modulation of brain circuits. Nat. Nanotechnol. 19, 1333–1343 (2024). https://doi.org/10.1038/s41565-024-01694-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41565-024-01694-2
This article is cited by
-
A magneto-mechanical genetics toolbox for in vivo neuromodulation
Nature Nanotechnology (2024)
