Finger somatotopy is preserved after tetraplegia but deteriorates over time

Sanne Kikkert, Dario Pfyffer, Michaela Verling, Patrick Freund, Nicole Wenderoth, Sanne Kikkert, Dario Pfyffer, Michaela Verling, Patrick Freund, Nicole Wenderoth

Abstract

Previous studies showed reorganised and/or altered activity in the primary sensorimotor cortex after a spinal cord injury (SCI), suggested to reflect abnormal processing. However, little is known about whether somatotopically specific representations can be activated despite reduced or absent afferent hand inputs. In this observational study, we used functional MRI and a (attempted) finger movement task in tetraplegic patients to characterise the somatotopic hand layout in primary somatosensory cortex. We further used structural MRI to assess spared spinal tissue bridges. We found that somatotopic hand representations can be activated through attempted finger movements in the absence of sensory and motor hand functioning, and no spared spinal tissue bridges. Such preserved hand somatotopy could be exploited by rehabilitation approaches that aim to establish new hand-brain functional connections after SCI (e.g. neuroprosthetics). However, over years since SCI the hand representation somatotopy deteriorated, suggesting that somatotopic hand representations are more easily targeted within the first years after SCI.

Trial registration: ClinicalTrials.gov NCT03772548.

Keywords: functional MRI; hand; human; neuroscience; plasticity; somatotopy; spinal cord injury; tetraplegia.

Conflict of interest statement

SK, DP, MV, PF, NW No competing interests declared

© 2021, Kikkert et al.

Figures

Figure 1.. Inter-participant somatotopic finger-specific probability maps…
Figure 1.. Inter-participant somatotopic finger-specific probability maps of the control and tetraplegic patient groups.
Colours indicate the number of participants (ranging from 1 [red] till 18 and 13 [blue] participants for the control and SCI patient group, respectively) who demonstrated finger selectivity for a given vertex. Characteristic finger selectivity is characterised by a progression of finger selectivity from the thumb (laterally) to the little finger (medially). These characteristic finger progressions can be observed in both the control (top) and the tetraplegic patient (bottom) group’s probability maps. Qualitative inspection suggests that inter-participant consistency was lowest for the little finger representation in both groups. It further appears that overall inter-participant consistency was reduced in the patient group compared to the control group. White arrows indicate the central sulcus. A: anterior; P: posterior.
Figure 2.. Finger selectivity is preserved in…
Figure 2.. Finger selectivity is preserved in tetraplegic patients.
Colours indicate selectivity for the thumb (finger 1, red), index finger (finger 2, yellow), middle finger (finger 3, green), ring finger (finger 4, blue), and little finger (finger 5, purple). Maps of participants for whom the left hand was tested are horizontally mirrored for visualisation purposes. Typical finger selectivity is characterised by a gradient of finger preference, progressing from the thumb (laterally) to the little finger (medially). These characteristic gradients of finger selectivity can be observed in both the able-bodied controls (A) and the tetraplegic patients (B). Despite most maps (except patient map 3) displaying aspects of characteristic finger maps, some finger representations were not visible in the thresholded patient and control maps. Patients’ hand maps are sorted according to their overall upper-limb impairments (assessed using the Graded Redefined Assessment of Strength, Sensibility and Prehension test [GRASSP]): from most to least impaired – as indicated by the white numbers. Black numbers indicate the years since spinal cord injury (SCI). Multiple comparisons were adjusted using a false discovery rate (FDR) with q < 0.05. Other figure annotations are as in Figure 1. (C) To ensure that the observed clusters were not representing noise, but rather true finger selectivity, we calculated split-half consistency between two halves of the minimally thresholded (Z > 2) travelling wave dataset (see Figure 2—figure supplement 1 for the travelling wave maps used to calculate split-half consistency). Both controls and patients showed higher split-half consistency (assessed using the Dice overlap coefficient) for comparison of the same fingers between two halves of the travelling wave dataset (light blue), compared to neighbouring (blue), and non-neighbouring fingers (dark blue). Moreover, neighbouring fingers showed greater overlap across the split-halves of the dataset then non-neighbouring fingers for both patients and controls. The same results were obtained when calculating split-half consistency on maps thresholded using FDR q < 0.05 (as was used for the maps in A, B; see Figure 2—figure supplement 2). Error bars show the standard error of the mean. *** = corrected p≤0.001, ns: non-significant.
Figure 2—figure supplement 1.. Hard-edged split-half travelling…
Figure 2—figure supplement 1.. Hard-edged split-half travelling wave maps used to calculate the intra-participant spatial consistency reported in Figure 2C.
Control (A) and patient maps (B) are ordered as in Figure 2. Colours indicate selectivity for the thumb (finger 1, red), index finger (finger 2, yellow), middle finger (finger 3, green), ring finger (finger 4, blue), and little finger (finger 5, purple). Maps of participants for whom the left hand was tested are horizontally mirrored for visualisation purposes. We used minimally thresholded finger-specific clusters (Z > 2) for the Dice overlap coefficient (DOC) spatial consistency analysis to ensure we were sensitive to overlaps that would be missed when using high thresholds. A: anterior; P: posterior. Multiple comparisons were adjusted using a false discovery rate (FDR) with q < 0.05.
Figure 2—figure supplement 2.. Spatial consistency of…
Figure 2—figure supplement 2.. Spatial consistency of false discovery rate (FDR)-thresholded finger maps.
We repeated the split-half consistency analysis using an q 2: overall, split-half consistency was not significantly different between patients and controls, as tested using a robust mixed ANOVA (F(1,17.69) = 0.08, p=0.79). There was a significant difference in split-half consistency between pairs of same, neighbouring, and non-neighbouring fingers (F(2,14.77) = 38.80, p<0.001). This neighbourhood relationship was not significantly different between the control and patient groups (i.e. there was no significant interaction; F(2,14.77) = 0.12, p=0.89). *** = corrected p≤0.001, ns: non-significant.
Figure 3.. Typical multivariate hand somatotopy is…
Figure 3.. Typical multivariate hand somatotopy is preserved following tetraplegia.
(A) Percent signal change in the S1 hand area during finger movement for able-bodied controls (grey) and tetraplegic patients (orange). Similar results were found in the M1 hand ROI (see Figure 3—figure supplement 1). (B, C) Two-dimensional projection of the representational structure of inter-finger distances in the control (B) and tetraplegic patient groups (C). Inter-finger distance is reflected by the distance in the two dimensions. Individual fingers are represented by different colours: thumb, red; index finger, yellow; middle finger, green; ring finger, blue; little finger, purple. Ellipses represent the between-participants’ standard error after Procrustes alignment. Inter-finger distances across finger pairs were significantly different across finger pairs (as would be expected based on somatotopic mapping), but not between controls and tetraplegic patients (see Figure 3—figure supplement 2). Individual participant inter-finger distance patterns are visualised in Figure 3—figure supplement 3 and Figure 3—figure supplement 4 for the controls and patients, respectively. (D) Separability, measured as mean inter-finger distance, of the representational structure in the S1 hand area of controls and patients. Patients are presented on a colour scale representing the sensory and motor functioning of their tested upper limb, measured using the Graded Redefined Assessment of Strength, Sensibility and Prehension test (GRASSP) (0 = no upper limb function, 116 = normal upper limb function). (E) Typicality of the representational structure in controls, patients, and congenital one-handers (Cong. in the figure). *** p<0.001; ns: non-significant; Dim: dimension; a.u.: arbitrary unit; Cong: congenital one-handers.
Figure 3—figure supplement 1.. Percent signal change…
Figure 3—figure supplement 1.. Percent signal change in the M1 hand area during finger movement.
Overall, all tetraplegic patients were able to engage their M1 hand area by moving (or attempting to move) individual fingers (t(13) = 6.44, p<0.001; BF10 = 1.09 e + 3), as did controls (t(17) = 9.73, p<0.001; BF10 = 5.65 e + 5). Furthermore, patients’ task-related activity was not significantly different from controls (t(30) = –0.66, p=0.52; BF10 = 0.40), with the Bayes factor (BF) showing anecdotal evidence in favour of the null hypothesis.
Figure 3—figure supplement 2.. Inter-finger distances across…
Figure 3—figure supplement 2.. Inter-finger distances across finger pairs for controls and tetraplegic patients.
A robust mixed ANOVA with a within-participants factor for finger pair (10 levels) and a between-participants factor for group (two levels: controls and tetraplegic patients) revealed a significant main effect for finger pair, as would be expected based on somatotopic mapping (F(9,15.38) = 27.22, p<0.001). We did not find a significant group (F(1,21.66) = 1.50, p=0.23) or finger pair by group interaction (F(9,15.38) = 1.05, p=0.45). When testing for group differences per finger pair, the Bayes factor (BF) only revealed inconclusive evidence (BF >0.37 and < 1.11; note that we could not run a Bayesian ANOVA due to normality violations). Crossval.: crossvalidated; F: finger; F1: thumb; F2: index finger; F3: middle finger; F4: ring finger; F5: little finger.
Figure 3—figure supplement 3.. Individual control participant’s…
Figure 3—figure supplement 3.. Individual control participant’s inter-finger distance patterns.
Annotations are as in Figure 3. The order of participants is as in Figure 2.
Figure 3—figure supplement 4.. Individual tetraplegic patient’s…
Figure 3—figure supplement 4.. Individual tetraplegic patient’s inter-finger distance patterns.
Annotations are as in Figure 3. The order of participants is as in Figure 2 (note that patient S02 did not undergo the travelling wave paradigm due to time constraints).
Figure 4.. Years since spinal cord injury…
Figure 4.. Years since spinal cord injury and retained motor function correlate with hand representation typicality in the primary somatosensory cortex (S1).
We examined clinical, behavioural, and spinal cord structural correlates for hand representation typicality. Increasing marker sizes represent increasing years since spinal cord injury (SCI) in graphs A–E. (A) There was a negative correlation between years since SCI and hand representation typicality. (B) We found a positive correlation between motor function of the tested upper limb (measured using the Graded Redefined Assessment of Strength, Sensibility and Prehension test [GRASSP]) and hand representation typicality. There was no significant correlation between hand representation typicality and sensory function of the tested upper limb (C; measured using the GRASSP), spared midsagittal spinal tissue bridges (D), and cross-sectional spinal cord area (E). (F) Bootstrapped distribution of controls’ and congenital one-handers’ mean S1 hand representation typicality. Dark grey bars indicate the distribution of congenital one-handers (data taken from an independent study; Wesselink et al., 2019), and light grey bars indicate the distribution of the able-bodied controls (tested for this study). The typicality scores of the SCI patients are plotted as orange lines. Increasing line thickness represent increasing years since SCI. Grey shaded areas indicate the 95% confidence intervals of the mean for congenital one-handers and able-bodied controls.
Appendix 1—figure 1.. Finger-specific activity levels in…
Appendix 1—figure 1.. Finger-specific activity levels in finger-specific regions of interest (ROIs).
(A) Finger-specific ROIs were based on the control group’s binarised 25% probability travelling wave finger selectivity maps. White arrows indicate the central sulcus. A: anterior; P: posterior. (B) Finger movement activity levels in the corresponding finger-specific ROIs. There were no significant differences in activity levels between thetetraplegic patient and control groups. Controls are projected in grey; patients are projected in orange. Error bars show the standard error of the mean.
Appendix 1—figure 2.. Geodesic distance between each…
Appendix 1—figure 2.. Geodesic distance between each finger’s peak activated vertex and a cortical anchor.
Cortical geodesic distances were calculated between a reference anchor in the S1 foot cortex (MNI coordinates: −16.93, –32.06, 73.80) and the peak activated vertex per finger movement for each participant. Controls are projected in grey; spinal cord injury (SCI) patients are projected in orange. Error bars show the standard error of the mean.

References

    1. Adams RA, Shipp S, Friston KJ. Predictions not commands: Active inference in the motor system. Brain Structure & Function. 2013;218:611–643. doi: 10.1007/s00429-012-0475-5.
    1. Ajiboye AB, Willett FR, Young DR, Memberg WD, Murphy BA, Miller JP, Walter BL, Sweet JA, Hoyen HA, Keith MW, Peckham PH, Simeral JD, Donoghue JP, Hochberg LR, Kirsch RF. Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration. Lancet. 2017;389:1821–1830. doi: 10.1016/S0140-6736(17)30601-3.
    1. Akselrod M, Martuzzi R, Serino A, van der Zwaag W, Gassert R, Blanke O. Anatomical and functional properties of the foot and leg representation in areas 3b, 1 and 2 of primary somatosensory cortex in humans: A 7T fMRI study. NeuroImage. 2017;159:473–487. doi: 10.1016/j.neuroimage.2017.06.021.
    1. Ariani G, Pruszynski JA, Diedrichsen J. Motor Planning Brings Human Primary Somatosensory Cortex into Movement-Specific Preparatory States. bioRxiv. 2020 doi: 10.1101/2020.12.17.423254.
    1. Armenta Salas M, Bashford L, Kellis S, Jafari M, Jo H, Kramer D, Shanfield K, Pejsa K, Lee B, Liu CY, Andersen RA. Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation. eLife. 2018;7:e32904. doi: 10.7554/eLife.32904.
    1. Besle J, Sánchez-Panchuelo RM, Bowtell R, Francis S, Schluppeck D. Single-subject fMRI mapping at 7 T of the representation of fingertips in S1: a comparison of event-related and phase-encoding designs. Journal of Neurophysiology. 2013;109:2293–2305. doi: 10.1152/jn.00499.2012.
    1. Borg I, Groenen PJF. Modern Multidimensional Scaling: Theory and Applications. Springer; 2005.
    1. Bouton CE, Shaikhouni A, Annetta NV, Bockbrader MA, Friedenberg DA, Nielson DM, Sharma G, Sederberg PB, Glenn BC, Mysiw WJ, Morgan AG, Deogaonkar M, Rezai AR. Restoring cortical control of functional movement in a human with quadriplegia. Nature. 2016;533:247–250. doi: 10.1038/nature17435.
    1. Bruurmijn MLCM, Pereboom IPL, Vansteensel MJ, Raemaekers MAH, Ramsey NF. Preservation of hand movement representation in the sensorimotor areas of amputees. Brain. 2017;140:3166–3178. doi: 10.1093/brain/awx274.
    1. Burman DD, Lie-Nemeth T, Brandfonbrener AG, Parisi T, Meyer JR. Altered finger representations in sensorimotor cortex of musicians with focal dystonia: Precentral cortex. Brain Imaging and Behavior. 2008;3:10–23. doi: 10.1007/s11682-008-9046-z.
    1. Chand P, Jain N. Intracortical and thalamocortical connections of the hand and face representations in somatosensory area 3b of macaque monkeys and effects of chronic spinal cord injuries. The Journal of Neuroscience. 2015;35:13475–13486. doi: 10.1523/JNEUROSCI.2069-15.2015.
    1. Corballis MC. Comparing a single case with a control sample: Refinements and extensions. Neuropsychologia. 2009;47:2687–2689. doi: 10.1016/j.neuropsychologia.2009.04.007.
    1. Cramer SC, Lastra L, Lacourse MG, Cohen MJ. Brain motor system function after chronic, complete spinal cord injury. Brain: A Journal of Neurology. 2005;128:2941–2950. doi: 10.1093/brain/awh648.
    1. Curt A, Keck ME, Dietz V. Functional outcome following spinal cord injury: significance of motor-evoked potentials and ASIA scores. Archives of Physical Medicine and Rehabilitation. 1998;79:81–86. doi: 10.1016/S0003-9993(98)90213-1.
    1. Da Costa S, Saenz M, Clarke S, van der Zwaag W. Tonotopic Gradients in Human Primary Auditory Cortex: Concurring Evidence From High-Resolution 7 T and 3 T fMRI. Brain Topography. 2015;28:66–69. doi: 10.1007/s10548-014-0388-0.
    1. Da Rocha Amaral S, Sanchez Panchuelo RM, Francis S. A Data-Driven Multi-scale Technique for fMRI Mapping of the Human Somatosensory Cortex. Brain Topography. 2020;33:22–36. doi: 10.1007/s10548-019-00728-6.
    1. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. NeuroImage. 1999;9:179–194. doi: 10.1006/nimg.1998.0395.
    1. Delhaye BP, Long KH, Bensmaia SJ. Neural basis of touch and proprioception in primate cortex. Comprehensive Physiology. 2018;8:1575–1602. doi: 10.1002/cphy.c170033.
    1. Dempsey-Jones H, Wesselink DB, Friedman J, Makin TR. Organized Toe Maps in Extreme Foot Users. Cell Reports. 2019;28:2748–2756. doi: 10.1016/j.celrep.2019.08.027.
    1. DeYoe EA, Carman GJ, Bandettini P, Glickman S, Wieser J, Cox R, Miller D, Neitz J. Mapping striate and extrastriate visual areas in human cerebral cortex. PNAS. 1996;93:2382–2386. doi: 10.1073/pnas.93.6.2382.
    1. Dice LR. Measures of the amount of ecologic association between species. Ecology. 1945;26:297–302. doi: 10.2307/1932409.
    1. Dienes Z. Using Bayes to get the most out of non-significant results. Frontiers in Psychology. 2014;5:1–17. doi: 10.3389/fpsyg.2014.00781.
    1. Ejaz N, Hamada M, Diedrichsen J. Hand use predicts the structure of representations in sensorimotor cortex. Nature Neuroscience. 2015;18:1034–1040. doi: 10.1038/nn.4038.
    1. Ejaz N, Sadnicka A, Wiestler T, Butler K, Edwards M, Diedrichsen J. Finger Representations in Sensorimotor Cortex Are Not Disrupted in Musicians’ DystoniaSociety for Neuroscience Annual Meeting. San Diego, USA: Society for Neuroscience Annual Meeting; 2016.
    1. Elbert T, Candia V, Altenmüller E, Rau H, Sterr A, Rockstroh B, Pantev C, Taub E. Alteration of digital representations in somatosensory cortex in focal hand dystonia. Neuroreport. 1998;9:3571–3575. doi: 10.1097/00001756-199811160-00006.
    1. Engel SA, Glover GH, Wandell BA. Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cerebral Cortex. 1997;7:181–192. doi: 10.1093/cercor/7.2.181.
    1. Fassett HJ, Turco CV, El-Sayes J, Nelson AJ. Alterations in motor cortical representation of muscles following incomplete spinal cord injury in humans. Brain Sciences. 2018;8:E225. doi: 10.3390/brainsci8120225.
    1. Fifer MS, McMullen DP, Thomas TM, Osborn LE, Nickl RW, Candrea DN, Pohlmeyer EA, Thompson MC, Anaya M, Schellekens W, Ramsey NF, Bensmaia SJ, Anderson WS, Wester BA, Crone NE, Celnik PA, Cantarero GL, Tenore F. Intracortical Microstimulation Elicits Human Fingertip Sensations. medRxiv. 2020
    1. Fischl B, Liu A, Dale AM. Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Transactions on Medical Imaging. 2001;20:70–80. doi: 10.1109/42.906426.
    1. Flesher SN, Collinger JL, Foldes ST, Weiss JM, Downey JE, Tyler-Kabara EC, Bensmaia SJ, Schwartz AB, Boninger ML, Gaunt RA. Intracortical microstimulation of human somatosensory cortex. Science Translational Medicine. 2016;8:1–11. doi: 10.1126/scitranslmed.aaf8083.
    1. Freund P, Rothwell J, Craggs M, Thompson AJ, Bestmann S. Corticomotor representation to a human forearm muscle changes following cervical spinal cord injury. European Journal of Neuroscience. 2011a;34:1839–1846. doi: 10.1111/j.1460-9568.2011.07895.x.
    1. Freund P, Weiskopf N, Ward NS, Hutton C, Gall A, Ciccarelli O, Craggs M, Friston K, Thompson AJ. Disability, atrophy and cortical reorganization following spinal cord injury. Brain: A Journal of Neurology. 2011b;134:1610–1622. doi: 10.1093/brain/awr093.
    1. Gooijers J, Chalavi S, Roebroeck A, Kaas S, Swinnen SP. Representational similarity scores of digits in the sensorimotor cortex are associated with behavioral performance. bioRxiv. 2021 doi: 10.1101/2021.06.18.448803.
    1. Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. NeuroImage. 2009;48:63–72. doi: 10.1016/j.neuroimage.2009.06.060.
    1. Halder P, Kambi N, Chand P, Jain N. Altered Expression of Reorganized Inputs as They Ascend From the Cuneate Nucleus to Cortical Area 3b in Monkeys With Long-Term Spinal Cord Injuries. Cerebral Cortex. 2018;28:3922–3938. doi: 10.1093/cercor/bhx256.
    1. Henderson LA, Gustin SM, Macey PM, Wrigley PJ, Siddall PJ. Functional reorganization of the brain in humans following spinal cord injury: Evidence for underlying changes in cortical anatomy. The Journal of Neuroscience. 2011;31:2630–2637. doi: 10.1523/JNEUROSCI.2717-10.2011.
    1. Horsfield MA, Sala S, Neema M, Absinta M, Bakshi A, Sormani MP, Rocca MA, Bakshi R, Filippi M. Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: Application in multiple sclerosis. NeuroImage. 2010;50:446–455. doi: 10.1016/j.neuroimage.2009.12.121.
    1. Hotz-Boendermaker S, Funk M, Summers P, Brugger P, Hepp-Reymond MC, Curt A, Kollias SS. Preservation of motor programs in paraplegics as demonstrated by attempted and imagined foot movements. NeuroImage. 2008;39:383–394. doi: 10.1016/j.neuroimage.2007.07.065.
    1. Huber E, Lachappelle P, Sutter R, Curt A, Freund P. Are midsagittal tissue bridges predictive of outcome after cervical spinal cord injury? Annals of Neurology. 2017;81:740–748. doi: 10.1002/ana.24932.
    1. Jain N, Catania KC, Kaas JH. A histologically visible representation of the fingers and palm in primate area 3b and its immutability following long-term deafferentations. Cerebral Cortex. 1998;8:227–236. doi: 10.1093/cercor/8.3.227.
    1. Jain N, Qi HX, Collins CE, Kaas JH. Large-scale reorganization in the somatosensory cortex and thalamus after sensory loss in macaque monkeys. The Journal of Neuroscience. 2008;28:11042–11060. doi: 10.1523/JNEUROSCI.2334-08.2008.
    1. Jenkinson M, Bannister P, Brady M, Smith SM. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage. 2002;17:825–841. doi: 10.1016/S1053-8119(02)91132-8.
    1. Jutzeler CR, Freund P, Huber E, Curt A, Kramer JLK. Neuropathic pain and functional reorganization in the primary sensorimotor cortex after spinal cord injury. The Journal of Pain. 2015;16:1256–1267. doi: 10.1016/j.jpain.2015.08.008.
    1. Kalsi-Ryan S, Beaton D, Curt A, Duff S, Popovic MR, Rudhe C, Fehlings MG, Verrier MC. The Graded Redefined Assessment of Strength Sensibility and Prehension: Reliability and Validity. Journal of Neurotrauma. 2012;29:905–914. doi: 10.1089/neu.2010.1504.
    1. Kalsi-Ryan S, Beaton D, Curt A, Popovic MR, Verrier MC, Fehlings MG. Outcome of the upper limb in cervical spinal cord injury: Profiles of recovery and insights for clinical studies. The Journal of Spinal Cord Medicine. 2014;37:503–510. doi: 10.1179/2045772314Y.0000000252.
    1. Kambi N, Halder P, Rajan R, Arora V, Chand P, Arora M, Jain N. Large-scale reorganization of the somatosensory cortex following spinal cord injuries is due to brainstem plasticity. Nature Communications. 2014;5:3602. doi: 10.1038/ncomms4602.
    1. Kass RE, Raftery AE. Bayes Factors. Journal of the American Statistical Association. 1995;90:773–795. doi: 10.1080/01621459.1995.10476572.
    1. Kieliba P, Clode D, Maimon-Mor RO, Makin TR. Robotic hand augmentation drives changes in neural body representation. Science Robotics. 2021;6:eabd7935. doi: 10.1126/scirobotics.abd7935.
    1. Kikkert S, Kolasinski J, Jbabdi S, Tracey I, Beckmann CF, Johansen-Berg H, Makin TR. Revealing the neural fingerprints of a missing hand. eLife. 2016;5:e15292. doi: 10.7554/eLife.15292.
    1. Kikkert S, Johansen-Berg H, Tracey I, Makin TR. Reaffirming the link between chronic phantom limb pain and maintained missing hand representation. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior. 2018;106:174–184. doi: 10.1016/j.cortex.2018.05.013.
    1. Kikkert S, Mezue M, O’Shea J, Henderson Slater D, Johansen-Berg H, Tracey I, Makin TR. Neural basis of induced phantom limb pain relief. Annals of Neurology. 2019;85:59–73. doi: 10.1002/ana.25371.
    1. Kokotilo KJ, Eng JJ, Curt A. Reorganization and preservation of motor control of the brain in spinal cord injury: a systematic review. Journal of Neurotrauma. 2009;26:2113–2126. doi: 10.1089/neu.2008.0688.
    1. Kolasinski J, Makin TR, Jbabdi S, Clare S, Stagg CJ, Johansen-Berg H. Investigating the stability of fine-grain digit somatotopy in individual human participants. The Journal of Neuroscience. 2016a;36:1113–1127. doi: 10.1523/JNEUROSCI.1742-15.2016.
    1. Kolasinski J, Makin TR, Logan JP, Jbabdi S, Clare S, Stagg CJ, Johansen-Berg H. Perceptually relevant remapping of human somatotopy in 24 hours. eLife. 2016b;5:e17280. doi: 10.7554/eLife.17280.
    1. Kriegeskorte N, Mur M, Bandettini P. Representational similarity analysis - connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience. 2008;2:1–28. doi: 10.3389/neuro.06.004.2008.
    1. Kuehn E, Haggard P, Villringer A, Pleger B, Sereno MI. Visually-driven maps in area 3b. The Journal of Neuroscience. 2018;38:1295–1310. doi: 10.1523/JNEUROSCI.0491-17.2017.
    1. Lebedev MA, Nicolelis MAL. Brain-machine interfaces: From basic science to neuroprostheses and neurorehabilitation. Physiological Reviews. 2017;97:767–837. doi: 10.1152/physrev.00027.2016.
    1. Levy WJ, Amassian VE, Traad M, Cadwell J. Focal magnetic coil stimulation reveals motor cortical system reorganized in humans after traumatic quadriplegia. Brain Research. 1990;510:130–134. doi: 10.1016/0006-8993(90)90738-W.
    1. Liao C-C, Qi H-X, Reed JL, Jeoung H-S, Kaas JH. Corticocuneate projections are altered after spinal cord dorsal column lesions in New World monkeys. The Journal of Comparative Neurology. 2021;529:1669–1702. doi: 10.1002/cne.25050.
    1. Liu P, Chrysidou A, Doehler J, Hebart MN, Wolbers T, Kuehn E. The organizational principles of de-differentiated topographic maps in somatosensory cortex. eLife. 2021;10:e60090. doi: 10.7554/eLife.60090.
    1. London BM, Miller LE. Responses of somatosensory area 2 neurons to actively and passively generated limb movements. Journal of Neurophysiology. 2013;109:1505–1513. doi: 10.1152/jn.00372.2012.
    1. Losseff NA, Webb SL, O’Riordan JI, Page R, Wang L, Barker GJ, Tofts PS, McDonald WI, Miller DH, Thompson AJ. Spinal cord atrophy and disability in multiple sclerosis A new reproducible and sensitive MRI method with potential to monitor disease progression. Brain: A Journal of Neurology. 1996;119:701–708. doi: 10.1093/brain/119.3.701.
    1. Mair P, Wilcox R. Robust statistical methods in R using the WRS2 package. Behavior Research Methods. 2020;52:464–488. doi: 10.3758/s13428-019-01246-w.
    1. Makin TR, Scholz J, Filippini N, Henderson Slater D, Tracey I, Johansen-Berg H. Phantom pain is associated with preserved structure and function in the former hand area. Nature Communications. 2013;4:1570. doi: 10.1038/ncomms2571.
    1. Mancini F, Haggard P, Iannetti GD, Longo MR, Sereno MI. Fine-grained nociceptive maps in primary somatosensory cortex. The Journal of Neuroscience. 2012;32:17155–17162. doi: 10.1523/JNEUROSCI.3059-12.2012.
    1. Mancini F, Wang AP, Schira MM, Isherwood ZJ, McAuley JH, Iannetti GD, Sereno MI, Moseley GL, Rae CD. Fine-Grained Mapping of Cortical Somatotopies in Chronic Complex Regional Pain Syndrome. The Journal of Neuroscience. 2019;39:9185–9196. doi: 10.1523/JNEUROSCI.2005-18.2019.
    1. Nili H, Wingfield C, Walther A, Su L, Marslen-Wilson W, Kriegeskorte N. A Toolbox for Representational Similarity Analysis. PLOS Computational Biology. 2014;10:e1003553. doi: 10.1371/journal.pcbi.1003553.
    1. Nyström B, Hagbarth KE. Microelectrode recordings from transected nerves in amputees with phantom limb pain. Neuroscience Letters. 1981;27:211–216. doi: 10.1016/0304-3940(81)90270-6.
    1. Ozdemir RA, Perez MA. Afferent Input and Sensory Function after Human Spinal Cord Injury. Journal of Neurophysiology. 2018;119:134–144. doi: 10.1152/jn.00354.2017.
    1. Petersen JA, Wilm BJ, von Meyenburg J, Schubert M, Seifert B, Najafi Y, Dietz V, Kollias S. Chronic Cervical Spinal Cord Injury: DTI Correlates with Clinical and Electrophysiological Measures. Journal of Neurotrauma. 2012;29:1556–1566. doi: 10.1089/neu.2011.2027.
    1. Pfyffer D, Huber E, Sutter R, Curt A, Freund P. Tissue bridges predict recovery after traumatic and ischemic thoracic spinal cord injury. Neurology. 2019;93:e1550–e1560. doi: 10.1212/WNL.0000000000008318.
    1. Pfyffer D, Vallotton K, Curt A, Freund P. Predictive Value of Midsagittal Tissue Bridges on Functional Recovery After Spinal Cord Injury. Neurorehabilitation and Neural Repair. 2021;35:33–43. doi: 10.1177/1545968320971787.
    1. Puckett AM, Bollmann S, Barth M, Cunnington R. Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI. NeuroImage. 2017;161:179–187. doi: 10.1016/j.neuroimage.2017.08.014.
    1. Puckett AM, Bollmann S, Junday K, Barth M, Cunnington R. Bayesian population receptive field modeling in human somatosensory cortex. NeuroImage. 2020;208:116465. doi: 10.1016/j.neuroimage.2019.116465.
    1. Sabbah P, de SS, Leveque C, Gay S, Pfefer F, Nioche C, Sarrazin JL, Barouti H, Tadie M, Cordoliani YS. Sensorimotor cortical activity in patients with complete spinal cord injury: A functional magnetic resonance imaging study. Journal of Neurotrauma. 2002;19:53–60. doi: 10.1089/089771502753460231.
    1. Sanders ZB, Wesselink DB, Dempsey-Jones H, Makin TR. Similar somatotopy for active and passive digit representation in primary somatosensory cortex. bioRxiv. 2019 doi: 10.1101/754648.
    1. Sereno MI, Dale AM, Reppas JB, Kwong KK, Belliveau JW, Brady TJ, Rosen BR, Tootell RBH. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science. 1995;268:889–893. doi: 10.1126/science.7754376.
    1. Smith SM. Fast robust automated brain extraction. Human Brain Mapping. 2002;17:143–155. doi: 10.1002/hbm.10062.
    1. Solstrand Dahlberg L, Becerra L, Borsook D, Linnman C. Brain changes after spinal cord injury, a quantitative meta-analysis and review. Neuroscience and Biobehavioral Reviews. 2018;90:272–293. doi: 10.1016/j.neubiorev.2018.04.018.
    1. Streletz LJ, Belevich JKS, Jones SM, Bhushan A, Shah SH, Herbison GJ. Transcranial magnetic stimulation: Cortical motor maps in acute spinal cord injury. Brain Topography. 1995;7:245–250. doi: 10.1007/BF01202383.
    1. Talavage TM, Sereno MI, Melcher JR, Ledden PJ, Rosen BR, Dale AM. Tonotopic Organization in Human Auditory Cortex Revealed by Progressions of Frequency Sensitivity. Journal of Neurophysiology. 2004;91:1282–1296. doi: 10.1152/jn.01125.2002.
    1. Topka H, Cohen LG, Cole RA, Hallett M. Reorganization of corticospinal pathways following spinal cord injury. Neurology. 1991;41:1276–1283. doi: 10.1212/wnl.41.8.1276.
    1. Urbin MA, Royston DA, Weber DJ, Boninger ML, Collinger JL. What is the functional relevance of reorganization in primary motor cortex after spinal cord injury? Neurobiology of Disease. 2019;121:286–295. doi: 10.1016/j.nbd.2018.09.009.
    1. Vallotton K, Huber E, Sutter R, Curt A, Hupp M, Freund P. Width and neurophysiologic properties of tissue bridges predict recovery after cervical injury. Neurology. 2019;92:E2793–E2802. doi: 10.1212/WNL.0000000000007642.
    1. Vaso A, Adahan HM, Gjika A, Zahaj S, Zhurda T, Vyshka G, Devor M. Peripheral nervous system origin of phantom limb pain. Pain. 2014;155:1384–1391. doi: 10.1016/j.pain.2014.04.018.
    1. Wesselink DB, Maimon-Mor R. rsatoolbox. Github. 2017
    1. Wesselink DB, van den Heiligenberg FM, Ejaz N, Dempsey-Jones H, Cardinali L, Tarall-Jozwiak A, Diedrichsen J, Makin TR. Obtaining and maintaining cortical hand representation as evidenced from acquired and congenital handlessness. eLife. 2019;8:e37227. doi: 10.7554/eLife.37227.
    1. Wesselink DB, Kolasinski J, Kikkert S, Hurley SA, Bridge H, Makin TR. Finger representation in the cortex of the congenitally blind. bioRxiv. 2021 doi: 10.1101/2021.03.16.435392.
    1. Wrigley PJ, Press SR, Gustin SM, Macefield VG, Gandevia SC, Cousins MJ, Middleton JW, Henderson LA, Siddall PJ. Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury. Pain. 2009;141:52–59. doi: 10.1016/j.pain.2008.10.007.
    1. Wrigley PJ, Siddall PJ, Gustin SM. New evidence for preserved somatosensory pathways in complete spinal cord injury: A fMRI study. Human Brain Mapping. 2018;39:588–598. doi: 10.1002/hbm.23868.
    1. Yousry TA, Schmid UD, Alkadhi H, Schmidt D, Peraud A, Buettner A, Winkler P. Localization of the motor hand area to a knob on the precentral gyrus A new landmark. Brain: A Journal of Neurology. 1997;120:141–157. doi: 10.1093/brain/120.1.141.
    1. Zeharia N, Hertz U, Flash T, Amedi A. New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity. The Journal of Neuroscience. 2015;35:2845–2859. doi: 10.1523/Jneurosci.4246-14.2015.

Source: PubMed

3
Iratkozz fel