Abstract
Perceiving substrate-borne vibrations is a fundamental component of tactile perception. How location (somatotopy) and frequency tuning (tonotopy) of vibrations are integratively processed is poorly understood. Here we addressed this question using in vivo electrophysiology and two-photon calcium imaging along the dorsal column–medial lemniscal pathway. We found that both frequency and location are organized into structured maps in the dorsal column nuclei (DCN). Both maps are intimately related at the fine spatial scale, with parallel map gradients that are consistent across the depth of the DCN and preserved along the ascending pathway. The tonotopic map only partially reflects the distribution of end organs in the skin and deep tissue; instead, the emergence of the fine-scale tonotopy is due to the selective dendritic sampling from axonal afferents, already at the first synaptic relay. We conclude that DCN neural circuits are key to the emergence of these two fine-scale topographical organizations in early somatosensory pathways.
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Data availability
The data for this study are available at https://github.com/leeku2013/Lee-2023-tonotopy. Imaging data are available from the corresponding author upon request. Source data are provided with this paper.
Code availability
The custom code used for this study is available at https://github.com/leeku2013/Lee-2023-tonotopy.
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Acknowledgements
We thank M. Prsa, G. Galiñanes, A. Novozhilova and J. Marozeau for advice and comments on the paper; G. Cuenu for help with histological techniques; R. Vickery for advice on electrophysiology experiments; C. Dürst for the assist on iGluSnFR3 experiments; M. Prsa for the assist on experimental setup; and G. Cuenu for help with breeding mice. This work was supported by the Swiss National Science Foundation (310030_184829), the European Research Council (OPTOMOT), the International Foundation for Research in Paraplegia, and the National Science and Technology Council (113-2628-B-001-012-). K.-S.L. is a EMBO Postdoctoral Fellow (ALTF_816-2020).
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K.-S.L. and D.H. conceptualized the study. K.-S.L. and D.H. designed the experiments. K.-S.L. ran the experiments and analyzed the data. M.S. helped with GRIN lens implantation. D.d.T.W. helped with the hindlimb dissections. A.J.L. performed immunohistochemistry. K.-S.L. and D.H. wrote the paper with assistance from D.d.T.W. and A.J.L.
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Extended data
Extended Data Fig. 1 Spectral analysis of vibrations stimulus measured with a laser doppler vibrometer.
a, Example of a displacement measured by the laser doppler vibrometer of a single 400-Hz vibration. The middle-half interval of spectral analysis was highlighted in red. b, Amplitude spectrum of the displacement produced by 10 trials of 400-Hz stimuli indicates that the physical vibration consisted of a single frequency component (nearly a pure sinusoid). Components apparent at the distant frequencies were highly attenuated relative to the stimulation frequency, similar to the background noise. c, Amplitude spectra were obtained for stimuli at all tested frequencies and four representative amplitudes from two different piezo actuators.
Extended Data Fig. 2 Transmission of vibration within the hindlimb tissue.
a, Amplitude spectra measurement of transmitted vibration along the 7 locations of the hindlimb of an anaesthetized mouse with a laser doppler vibrometer. From the bottom right to the top left, stimulation was placed at the 7 locations of the hindlimb, from the toe to the thigh. b, Amplitude spectra measurement of transmitted vibration with higher amplitude along the 7 locations of the hindlimb of an anaesthetized mouse. Top, stimulation was placed at the toe. Bottom, stimulation was placed at the heel. c, Amplitude spectra measurement of transmitted vibration along the 5 along the fibula freshly dissected from an euthanized mouse. Top, stimulation was placed at the toe. Bottom, stimulation was placed at the heel. d, Signal intensity of different frequency components were obtained ex vivo at the base of fibula in the dissected hindlimb, where the Pacinian corpuscle mainly located. Top, stimulation was placed at the toe. Bottom, stimulation was placed at the heel. Data were from 2 animals and the trials were repeated 5 times. Error bars represent S.E.M.
Extended Data Fig. 3 Complete DCN preference maps, invariance of the receptive field properties and the interaction between frequency, location and amplitude.
a, Joint selectivity of the vibration frequency and the amplitude from two DCN neurons, with stimulation applied to the receptive field center. Note, that the high frequency stimulation of pure sinusoidal vibration can not be generated at the high amplitude due to the technical limits of the actuator. b, The correlation of the frequency preference of individual neurons measured with highest and lowest vibration amplitudes, which yielded a completed tuning curve. c, Joint selectivity of the frequency and the location from the two neurons, with the highest stimulation amplitude that yielded a completed tuning curve. d, Left, the correlation of the frequency preference of individual neurons measured at different body locations, one at the receptive field and one at a nearby location with the second best responses. Right, the correlation of the location preference of individual neurons measured with different frequencies, one with the preferred frequency and one with the second-best preferred frequency. e, Joint selectivity of the location and the amplitude from two DCN neurons, with two frequencies that highly activated the neurons. f, The correlation of the location preference of individual neurons measured with highest and lowest vibration amplitudes, which yielded a completed tuning curve. g, Top, experimental schematic for receptive field mapping with stroke and the example tuning curves of a DCN neuron with either vibration or stroke. Bottom left, the correlation of the location preference of individual neurons measured with vibration or stroke. Bottom right, the correlation of the receptive field (RF) width of individual neurons measured with vibration or stroke. h, Top, experimental schematic for receptive field mapping with indentation and the example tuning curves of a DCN neuron with either vibration or indentation. Bottom left, the correlation of the location preference of individual neurons measured with vibration or indentation. Bottom right, the correlation of the RF width of individual neurons measured with vibration or indentation. i, Top, experimental schematic for receptive field mapping with optogenetic mapping and the example tuning curves of a DCN neuron with either vibration or blue laser in Etv1-Cre × ChR2-EYFP (Ai32) mice. Bottom left, the correlation of the location preference of individual neurons measured with vibration or optogenetic mapping. In the current study, we did not attempt to activate Pacinian corpuscle afferents in the deep tissue with optogenetics. Bottom right, the correlation of the RF width of individual neurons measured with vibration or optogenetic mapping. It is likely that the strong stimulations such as high amplitude vibrations (100 Hz, 400 µm), stroke, indentation, and optogenetic stimulation, used for receptive field mapping, activated multiple LTMR afferent types to some degree. j, Top, experimental schematic for 2D receptive field mapping with indentation and optogenetic mapping, and the example RFs of a DCN neuron with both methods. Bottom, the correlation of the RF size of individual neurons measured with both methods. k-l, The DCN preference maps of somatotopy (k) and tonotopy (l) from all seven animals. The first one is the same as the example in Fig. 1.
Extended Data Fig. 4 Comparing different generations of GCaMP imaging and electrophysiology.
a, The example tuning curve of a DCN neuron across different vibration frequencies at the vibration amplitudes of 3 µm: grey dots, individual stimulus responses; grey trace, mean values; black trace, polynomial curve fit; vertical green dashed line, preferred frequencies; red horizontal lines, the half-width at the half-maximum of the curve. b, Left, the distribution of the tuning preference from the DCN imaging experiments performed with different generations of calcium indicator, GCaMP. Right, the distribution of the tuning width measured in the different imaging experiments. c, Left, the distribution of the tuning preference measured from the calcium imaging at the DRG (top) or electrophysiology recording at the nerve fibers (bottom). Right, the distribution of the tuning width measured from the calcium imaging (top) or electrophysiology experiments (bottom). d, Left, the distribution of tuning preferences from individual DCN neurons measured using calcium imaging from the population of thalamic projection neurons (top) or inferior colliculus projection neurons (bottom). Right, the distribution of the tuning width from the population of thalamic projection neurons (top) or inferior colliculus projection neurons (bottom). No significant difference was found in any comparison within DCN or DRG with the Kolmogorov-Smirnov test, two-sided. e, Left, example fields-of-view of thalamic projection neurons in DCN (top) and each neuron's preference for location and frequency colour-coded (bottom). Right, the relationship of horizontal distance between neurons in a pair and their difference in location (top) and frequency (bottom) is calculated (*P < 0.01, permutation test). The slope of the linear fit (SLF, italic) of the first 5 data points from the original data (black line) is shown. Error bars represent S.E.M. f, Left, example fields-of-view of inferior collicular projection neurons in DCN (top) and each neuron's preference for location and frequency colour-coded (bottom). Right, the relationship of horizontal distance between neurons in a pair and their difference in location (top) and frequency (bottom) is calculated (*P < 0.01, permutation test). The slope of the linear fit (SLF, italic) of the first 5 data points from the original data (black line) is shown. Error bars represent S.E.M. n/N = number of neurons and mice.
Extended Data Fig. 5 Anatomical distribution of mechanosensitive end organs in hindlimb.
a, Summary of the distribution of the three main mechanosensitive end-organs in the mouse hindlimb. Data of Merkel cell and Meissner corpuscle distribution in the paw area was interpreted from the literature23. There was no quantitative data for the distribution of the Merkel cells and Meissner corpuscles beyond the hindpaw. b, Top, a Pacinian corpuscle from a wild-type mouse under the confocal imaging after dissection ex vivo. The denser autofluorescence signals from the inner core cells and the onion-like layers of outer core cells could be visualised with high laser power and gain of the photon detector. Bottom, the inner core cells of a single Pacinian corpuscle were visualised using a double-transgenic strategy (ETV1-Cre x tdTomato) under in situ two-photon imaging at the hindlimb. c, Example plantar field of view of the toe with removed skin, where two tdTomato-positive Pacinian corpuscles are found close to the phalange. d, Six example hindlimbs with skin and muscle removed to expose the distal tibiofibular joint, and they consistently showed many tdTomato-positive Pacinian corpuscles (each bright spot is ETV1+ cells in the inner core area of one Pacinian corpuscle) wrapping around the fibula bone. e, Seven example confocal fields of view show that Troma1+ Merkel cells (arrowhead) and S100+ Meissner corpuscles (arrow) can be found in the foot. S100+ lanceolate endings are frequently spotted around the hair follicles of the hindlimb (bottom right). However, there was no Troma1+ signal observed in the hairy skin of the hindlimb across all 37 pieces of longitudinal skin samples from toe to thigh. f, Six example cross sections of hair follicles in the hindlimb stained using hematoxylin and eosin. There is no cytokeratin 20+ signal observed in the hairy skin of the hindlimb from ankle to thigh.
Extended Data Fig. 6 Details of the threshold mapping of mechanosensitive afferents.
a-c, Mechanosensitive afferents were stimulated by applying a series of sinusoidal mechanical stimuli. These were presented at the receptive field center of individual units,at linearly increasing amplitude and with increasing frequencies (0.3–1600 Hz). Examples of responses evoked by full range of the stimulation of mechanosensitive afferents potentially innervating Merkel cells (a) and Meissner (b) and Pacinian corpuscles (c), respectively. The threshold was determined by the first spike. d, Frequency dependent threshold curves (mechanical activation threshold versus stimulation frequency) of the three mechanosensitive afferents above. Data represent the mean ± S.E.M. Trials were repeated for 5 times. The grey lines show the mean threshold curve of other nerve fibres. e, The threshold curves of all different groups of nerve fibres with a logarithmic scale. We found that mechanical thresholds were highly consistent within the groups, regardless of the receptive field of the afferent within the hindlimb. Plus signs (+) indicate the stimulation parameter specific to preferentially activate only one defined group of mechanosensitive end-organs: Merkel cell-like (MERK), 1 Hz, 300 μm; Meissner-like (MEIS), 30 Hz, 100 μm; Pacinian-like (PACI), 600 Hz, 3μm. Note that they were below the threshold of all the mechanosensitive afferents which were identified as hair follicles-like (HAIR) or proprioceptors (PROP), most likely muscle spindles. Hair follicle-like afferents can be identified by air puff and hair deflection, while proprioceptive afferents can be identified by moving the joints without touching the skin. Though our physiological recordings suggested our stimulation is not ideal to activate hair follicle afferents, we cannot fully rule out the possibility that hair follicle afferents were activated. For proprioceptive afferents with spontaneous firing rates, threshold was determined by the moment that the firing rate within 0.5 s bins exceeded 2 standard deviations above the spontaneous firing rate. Note that the frequency used for threshold mapping was sometimes different even within the same types of afferents, but the results were consistent. f, Functional clusters shown in a t-SNE space. g, Adaptation characteristics were defined by the rate of action potentials in response to a static indentation. The number of the mechanosensitive afferents or neurons is indicated on the bars. Middle groups of bars show the DCN neurons responding to only one of the stimuli defined in e.
Extended Data Fig. 7 Details about dendritic spine calcium and glutamate imaging.
a, Convergence between different end-organ types in the dendrites of single DCN neurons. In vivo two-photon calcium imaging of a DCN neuron with its dendritic field (top left). An example field of view with the soma of the targeted cell (top right). Nice example fields of view covering a part of the dendritic arbour (bottom right). Functional organisation of various submodalities in the dendritic field of the targeted cell (bottom left). b, Left, the percentage of the seven classified groups of dendritic spines in the DCN, defined by three mechanosensitive end-organ-specific stimuli. Right, the percentage of DCN neurons receiving synaptic inputs from one, two, or all three of the unimodal afferent input categories (that is MERK, MEIS, or PACI). c, Top, the distribution of different frequency preferences (tonotopy organisation) on a dendritic segment of the DCN neuron labelled with GCaMP8s. Bottom, postsynaptic activity from a single example spine was isolated by subtracting the component of the signal from the dendritic shaft. Red line: Duration of light stimulus. d, The relationship of distance between spines in a pair and frequency preference was calculated and it revealed that spines with a similar orientation preference were more likely to cluster. Error bars represent S.E.M. ∗p < 0.001, permutation test (n/N = 205 spines and 5 cells from 5 mice). e, Top, the distribution of the tuning preference of spines measured from the GCaMP8s calcium imaging or iGluSnFR3 glutamate imaging. bottom, the distribution of the tuning width measured from the calcium or glutamate imaging. No significant difference was found in any comparison (permutation test). f, The probability to find a responsive spine in iGluSnFR3 (n/N = 102 spines and 3 cells) is three times more than in GCaMP8s imaging (n/N = 246 spines and 4 cells). Error bars represent S.E.M. g, After alignment of the soma across multiple cells (N = 21), the centroid of the distribution of spines receiving the inputs from the information likely supplied by different mechanosensitive end-organs reveals the similar rostral-caudal bias of the end-organ types.
Extended Data Fig. 8 Details about tagging first-order somatosensory neurons and axonal bouton imaging.
a, Expression of GCaMP6s in the first-order somatosensory neurons in DRG was achieved by viral injection at the dorsal horn of lumbar enlargement. b, The two photon imaging of the brainstem (top left) and a whole-mount skin sample from the toe tip (top right) showed the two extreme terminals of the first-order somatosensory neurons. Bottom, three example fields of view at the DRG level, showing the labelling of the cell bodies. c, Four example images of dissected spinal cord revealed the heterogeneity of the viral injection and expression. d, Top, the percentage of different groups of DRG neurons defined by three mechanosensitive end-organs-specific stimulation. Bottom, the percentage of seven classified groups of axonal boutons in DCN defined by three mechanosensitive end-organs-specific stimulation. Those multimodal boutons in DCN are likely from the indirect pathway through the spinal cord dorsal horn.
Extended Data Fig. 9 Histology and illustration of imaging in the complete somatosensory pathway for touch.
a, Left, schematic representation of the ascending pathway of the somatosensory system. Right, the example photos of each location where the imaging windows were installed. b-c, The anatomical-defined receptive fields of lumbar DRG cells were mapped by injecting fluorescent lipophilic dye DiI, DiO and DiD into different locations of the hindlimb. d, Example photos of five DCN windows. White dashed lines marked the right gracile nucleus. e, Overlaying of the gracile nuclei across 24 animals yielded a template for alignment. f, Three tangential serial sections (100 μm apart) of the DCN showing the viral expression covered the complete right gracile nucleus. White dashed lines marked the right gracile nucleus. g, Four example post hoc histological verification of the GRIN lens implantation above the thalamus (VPL) after the viral expression of GCaMP7b. h, Example epifluorescence imaging of the brain showing the GCaMP expression at the injection site at S1 and the projections at the contralateral DCN.
Extended Data Fig. 10 A model for emergence of tonotopic representation in the hindlimb dorsal column–medial lemniscal pathway.
a, Top, experimental schematic for blocking the signal transmission by the indirect dorsal column pathway through the spinal cord dorsal horn neurons (pink). Bottom, the frequency preference of neurons are colour-coded before (left) and after (right) the application of synaptic inhibitors (MK-801 and NBQX) of excitatory synaptic transmission to the spinal cord. b, Example tuning curves of nine DCN neurons showing various changes in response amplitude after application of blocking the signal transmission by the indirect dorsal column pathway. c, Left, the correlation of the frequency preference of individual neurons measured before and after the inactivation of the synaptic activity within the spinal cord (linear regression, P = 0.00007). Right, the change of the calcium response amplitude of individual neurons in three different groups, categorized by their preferred frequency, before and after the inactivation (paired-sample t-test, two-sided, *P < 0.001). d, An example photo of the imaging window over the spinal cord. e, Left, schematic of the clusters of neuronal cell bodies (top) and example fields-of-view under two-photon microscope (bottom). Right, each neuron's preference for location and frequency is colour-coded. f, The relationship of horizontal distances between neurons in a pair and their difference in location (top) and frequency (bottom) is calculated (*P < 0.01, permutation test). The slope of the linear fit (SLF, italic) of the first 5 data points from the original data (black line) is shown. Error bars represent S.E.M. g, An example photo of the imaging window over the inferior colliculus. h, Left, schematic of the clusters of neuronal cell bodies (top) and example fields-of-view (bottom). Right, each neuron's preference for location and frequency is colour-coded. i, The relationship of horizontal distance between neurons in a pair and their difference in location (top) and frequency (bottom) is calculated (*P < 0.01, permutation test). The slope of the linear fit (SLF, italic) of the first 5 data points from the original data (black line) is shown. Error bars represent S.E.M. All the neurons shown here did not respond to auditory stimulation with the hindlimb off the stimulator. This suggests they are a specific population in inferior colliculus that only responds to tactile stimulation. n/N = number of neurons and mice. j, Mechanosensitive end-organs and their LTMR afferents - Merkel cells (blue), Meissner corpuscles (yellow) and Pacinian corpuscles (red) - detect a wide frequency spectrum of vibrations (0.1 – 2000 Hz) in the periphery. The end-organs are distributed throughout the hindlimb, but each is most densely found in one area: Merkel cells in the toes, Meissner corpuscles in the foot pads and Pacinian corpuscles along the fibula. At the cell bodies of the LTMRs in the dorsal root ganglia no tonotopic organisation is observed. However, at their central projections in the gracile nucleus of the brainstem, but not in the spinal cord dorsal horn, fine-scale topographic organisation arises. Furthermore, inputs from the same end-organ group are found projecting onto the gracile nucleus with a rostrocaudal bias. Each colour-coded circle illustrates a synaptic connection. The selective dendritic sampling of the gracile nucleus neurons (black) is the basis for the emergence of a topographic map in the brainstem. Along the ascending pathway, the tonotopic map found in the gracile nucleus is partially preserved in the midbrain, thalamus and hindlimb somatosensory cortex.
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Lee, KS., Loutit, A.J., de Thomas Wagner, D. et al. Emergence of a brainstem somatosensory tonotopic map for substrate vibration. Nat Neurosci 28, 97–104 (2025). https://doi.org/10.1038/s41593-024-01821-1
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DOI: https://doi.org/10.1038/s41593-024-01821-1
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