A spinal cord injury (SCI) refers to damage of the spinal cord caused by a trauma, disease, or degeneration of vertebral discs. SCI mostly results in a partial or complete loss of motor control and sensation. Following a tetraplegia (or cervical SCI), individuals mostly experience a loss of muscle function and sensation in their limbs and torso (Curt et al., 1998; Kalsi-Ryan et al., 2014; Petersen et al., 2012). Accordingly, the primary somatosensory cortex (S1) mostly receives weakened, or is fully deprived of, afferent inputs and is exposed to altered motor behaviour (Ozdemir and Perez, 2018).

Research in non-human primate models of chronic and complete cervical SCI has shown that the S1 hand area becomes largely unresponsive to tactile hand stimulation after the injury (Jain et al., 2008; Kambi et al., 2014; Liao et al., 2021). The surviving finger-related activity became disorganised such that a few somatotopically appropriate sites but also other somatotopically non-matched sites were activated (Liao et al., 2021). Seminal non-human primate research has further demonstrated that SCI leads to extensive cortical reorganisation in S1, such that tactile stimulation of cortically adjacent body parts (e.g. of the face) activated the deprived brain territory (e.g. of the hand; Halder et al., 2018; Jain et al., 2008; Kambi et al., 2014). Although the physiological hand representation appears to largely be altered following a chronic cervical SCI in non-human primates, the anatomical isomorphs of individual fingers are unchanged (Jain et al., 1998). This suggests that while a hand representation can no longer be activated through tactile stimulation after the disruption of afferent spinal pathways, a latent and somatotopic hand representation may be preserved regardless of large-scale physiological reorganisation.

A similar pattern of results has been reported for human SCI patients. Transcranial magnetic stimulation (TMS) studies induced current in localised areas of SCI patients’ primary motor cortex (M1) to induce a peripheral muscle response. They found that representations of more impaired muscles retract or are absent while representations of less impaired muscles shift and expand (Fassett et al., 2018; Freund et al., 2011a; Levy et al., 1990; Streletz et al., 1995; Topka et al., 1991; Urbin et al., 2019). Similarly, human fMRI studies have shown that cortically neighbouring body part representations can shift towards, though do not invade, the deprived M1 and S1 cortex (Freund et al., 2011b; Henderson et al., 2011; Jutzeler et al., 2015; Wrigley et al., 2018; Wrigley et al., 2009). Other human fMRI studies hint at the possibility of latent somatotopic hand representations following SCI by showing that attempted movements with the paralysed and sensory-deprived body part can still evoke signals in the sensorimotor system (Cramer et al., 2005; Freund et al., 2011b; Kokotilo et al., 2009; Solstrand Dahlberg et al., 2018). This attempted ‘net’ movement activity was, however, shown to substantially differ from healthy controls: activity levels have been shown to be increased (Freund et al., 2011b; Kokotilo et al., 2009; Solstrand Dahlberg et al., 2018) or decreased (Hotz-Boendermaker et al., 2008), volumes of activation have been shown to be reduced (Cramer et al., 2005; Hotz-Boendermaker et al., 2008), activation was found in somatotopically non-matched cortical sites (Freund et al., 2011b), and activation was poorly modulated when patients switched from attempted to imagined movements (Cramer et al., 2005). These observations have therefore mostly been attributed to abnormal and/or disorganised processing induced by the SCI. It remains possible though that, despite certain aspects of sensorimotor activity being altered after SCI, somatotopically typical representations of the paralysed and sensory deprived body parts can be preserved (e.g. finger somatotopy of the affected hand(s)). Such preserved representations have the potential to be exploited in a functionally meaningful manner (e.g. via neuroprosthetics).

Case studies using intracortical stimulation in the S1 hand area to elicit finger sensations in tetraplegic patients hint at such preserved somatotopic representations (Fifer et al., 2020; Flesher et al., 2016), with one exception (Armenta Salas et al., 2018). Negative results were suggested to be due to a loss of hand somatotopy and/or reorganisation in S1 of the implanted tetraplegic patient, or due to potential misplacement of the implant (Armenta Salas et al., 2018). Whether fine-grained somatotopy is generally preserved in the tetraplegic patient population remains unknown. It is also unclear what clinical, behavioural, and structural spinal cord determinants may influence such representations to be maintained.

Here we used functional MRI (fMRI) and a visually cued (attempted) finger movement task in tetraplegic patients to examine whether hand somatotopy is preserved following a disconnect between the brain and the periphery. We instructed patients to perform the fMRI tasks with their most impaired upper limb and matched control participants’ tested hands to patients’ tested hands. If a patient was unable to make overt finger movements due to their injury, then we carefully instructed them to make attempted (i.e. not imagined) finger movements. To see whether patient’s maps exhibited characteristics of somatotopy, we visualised finger selectivity in S1 using a travelling wave approach. To investigate whether fine-grained hand somatotopy was preserved and could be activated in S1 following tetraplegia, we assessed inter-finger representational distance patterns using representational similarity analysis (RSA). These inter-finger distance patterns are thought to be shaped by daily life experience such that fingers used more frequently together in daily life have lower representational distances (Ejaz et al., 2015). RSA-based inter-finger distance patterns have been shown to depict the invariant representational structure of fingers in S1 and M1 better than the size, shape, and exact location of the areas activated by finger movements (Ejaz et al., 2015). Over the past years RSA has therefore regularly been used to investigate somatotopy of finger representations both in healthy (e.g. Akselrod et al., 2017; Ariani et al., 2020; Ejaz et al., 2015; Gooijers et al., 2021; Kieliba et al., 2021; Kolasinski et al., 2016b; Liu et al., 2021; Sanders et al., 2019) and patient populations (e.g. Dempsey-Jones et al., 2019; Ejaz et al., 2016; Kikkert et al., 2016; Wesselink et al., 2019). We closely followed procedures that have previously been used to map preserved and typical somatotopic finger selectivity and inter-finger representational distance patterns of amputees’ missing hands in S1 using volitional phantom finger movements (Kikkert et al., 2016; Wesselink et al., 2019). However, in amputees, these movements generally recruit the residual arm muscles that used to control the missing limb via intact connections between the brain and spinal cord. Whether similar preserved somatotopic mapping can be observed in SCI patients with diminished or no connections between the brain and the periphery is unclear. If finger somatotopy is preserved in tetraplegic patients, then we should find typical inter-finger representational distance patterns in the S1 hand area of these patients. By measuring a group of 14 chronic tetraplegic patients with varying amounts of spared spinal cord tissue at the lesion level (quantified by means of midsagittal tissue bridges based on sagittal T2w scans), we uniquely assessed whether preserved connections between the brain and periphery are necessary to preserve fine somatotopic mapping in S1 (Huber et al., 2017; Pfyffer et al., 2019). If spared connections between the periphery and the brain are not necessary for preserving hand somatotopy, then we should find typical inter-finger representational distance patterns even in patients without spared spinal tissue bridges. We also investigated what clinical and behavioural determinants may contribute to preserving S1 hand somatotopy after chronic tetraplegia. If spared sensorimotor hand function is not necessary for preserving hand somatotopy, then we should find typical inter-finger representational distance patterns even in patients who suffer from full sensory loss and paralysis of the hand(s).

In this study, we investigated whether hand somatotopy is preserved and can be activated through attempted movements following tetraplegia. We tested a heterogenous group of SCI patients to examine what clinical, behavioural, and structural spinal cord determinants contribute to preserving S1 somatotopy. Our results revealed that detailed hand somatotopy can be preserved following tetraplegia, even in the absence of sensory and motor hand function and a lack of spared spinal tissue bridges. However, over time since SCI these finger maps deteriorated such that the hand somatotopy became less typical.

Spared spinal cord tissue bridges can be found in most patients with a clinically incomplete injury, their width being predictive of electrophysiological information flow, recovery of sensorimotor function, and neuropathic pain (Huber et al., 2017; Pfyffer et al., 2021; Pfyffer et al., 2019; Vallotton et al., 2019). However, in this study, spared midsagittal spinal tissue bridges at the lesion level and sensorimotor hand function did not seem necessary to maintain and activate a somatotopic hand representation in S1. We found a highly typical hand representation in two patients (S01 and S03) who did not have any spared spinal tissue bridges at the lesion level, a complete (S01) or near complete (S03) hand paralysis, and a complete (S01) or near complete loss (S03) of hand sensory function. Our predictive modelling results were in line with this notion and showed that these behavioural and structural spinal cord determinants were not predictive of hand representation typicality. Note however that our sample size was limited, and it is challenging to draw definite conclusions from non-significant predictive modelling results.

Time since injury was predictive of a deteriorated, or less typical, somatotopic S1 hand representation. In fact, both patients with a typical S1 hand representations but absent spinal tissue bridges suffered their SCI only 4 years ago (the group was on average 12 years since SCI). The hand representation typicality of patients who suffered their SCI further in the past were not similar to congenital one-handers’ nor to controls’ hand representation. Thus, S1 hand representations may deteriorate over time after an SCI, but some weak hand information appears to be maintained in S1 even >30 years after an SCI. This finding complements previous studies in amputees showing that missing hand somatotopy is preserved even decades after arm amputation and that years since injury was not related to missing hand representation typicality (Kikkert et al., 2016; Wesselink et al., 2019). While both amputees and SCI patients suffer from major sensory input loss and changed motor behaviour, their injuries are inherently different. The injured axons within amputees’ residual limb and the remaining part of the peripheral nerves mostly generate some spontaneous (ectopic) activity that is propagated to the brain and could contribute to maintaining S1 representations (Kikkert et al., 2019; Kikkert et al., 2018; Kikkert et al., 2016; Makin et al., 2013; Nyström and Hagbarth, 1981; Vaso et al., 2014). Furthermore, amputees mostly remain able to move and receive afferents from the residual limb muscles that used to control the missing hand as most of their motor system remains intact. Although their hand is missing, amputees’ residual arm muscles are often still used (either to move the residual limb and/or to control a prosthetic arm). Lastly, amputees’ vividness of kinaesthetic sensations during phantom finger movements was found to be predictive of the typicality of the S1 missing hand representation (Wesselink et al., 2019). A continued, though altered, experience relating to the missing hand in amputees may contribute to maintaining the somatotopic missing hand representation in S1. Contrarily, tetraplegic patients mostly have reduced or a complete loss of communication between the brain and periphery. They therefore have problems activating the adequate muscles and will lose orderly afferents from their muscles and the skin. It is possible that this continued disuse causes somatotopic S1 representations to deteriorate after SCI.

How may these representations be preserved over time and activated through attempted movements in the absence of peripheral information? S1 is reciprocally connected with various brain areas, for example,, M1, lateral parietal cortex, posterior parietal area 5, secondary somatosensory cortex, and supplementary motor cortex (Delhaye et al., 2018). After a loss of sensory inputs and paralysis through SCI, S1 representations may be activated and preserved through its interconnections with these areas. Firstly, it is possible that cortico-cortical efference copies may keep a representation ‘alive’ through occasional corollary discharge (London and Miller, 2013). While motor and sensory signals no longer pass through the spinal cord in the absence of spinal tissue bridges, S1 and M1 remain intact. When a motor command is initiated (e.g. in the form of an attempted hand movement), an efference copy is thought to be sent to S1 in the form of corollary discharge. This corollary discharge resembles the expected somatosensory feedback activity pattern and may drive somatotopic S1 activity even in the absence of ascending afferent signals from the hand (Adams et al., 2013; London and Miller, 2013). It is possible that our patients occasionally performed attempted movements which would result in corollary discharge in S1. Second, it is likely that attempting individual finger movements poses high attentional demands on tetraplegic patients. Accordingly, attentional processes might have contributed to eliciting somatotopic S1 activity. Evidence for this account comes from studies showing that it is possible to activate somatotopic S1 hand representations through attending to individual fingers (Puckett et al., 2017) or through touch observation (Kuehn et al., 2018). Attending to fingers during our attempted finger movement task may have been sufficient to elicit somatotopic S1 activity through top-down processes in the tetraplegic patients who lacked motor and sensory hand function. Furthermore, one might speculate that observing others’ or one’s own fingers being touched or directing attention to others’ hand movements or one’s own fingers may help preserve somatotopic representations. Third, it is possible that these somatotopic maps are relatively hardwired, and while they deteriorate over time, they never fully disappear. Indeed, somatotopic mapping of a sensory-deprived body part has been shown to be resilient after dystonia (Ejaz et al., 2016; though see Burman et al., 2008 and Elbert et al., 1998) and arm amputation (Bruurmijn et al., 2017; Kikkert et al., 2016; Wesselink et al., 2019). Fourth, it is possible that even though a patient is clinically assessed to be complete and is unable to perceive sensory stimuli on the deprived body part, there is still some ascending information flow that contributes to preserving somatotopy (Wrigley et al., 2018). A recent study found that although complete paraplegic SCI patients were unable to perceive a brushing stimulus on their toe, 48% of patients activated the location-appropriate S1 area (Wrigley et al., 2018). However, the authors of this study defined the completeness of patients’ injuries via behavioural testing, while we additionally assessed the retained connections passing through the SCI directly via quantification of spared spinal tissue bridges through structural MRI. It is unlikely that spinal tissue carrying somatotopically organised information would be missed by our assessment (Huber et al., 2017; Pfyffer et al., 2019). Our experiment did not allow us to tease apart these potential processes, and it is likely that various processes simultaneously influence the preservation of S1 somatotopy and elicited the observed somatotopic S1 activity.

Our finding of preserved S1 somatotopy may appear inconsistent with the wealth of evidence showing cortical reorganisation in S1 following SCI (Halder et al., 2018; Jain et al., 2008; Kambi et al., 2014). In these studies, experimenters indirectly probed the deprived S1 hand cortex via stimulation of cortically adjacent body parts. Human fMRI studies similarly probed the intact and cortically neighbouring body parts and suggested that their representations shift towards the deprived S1 cortex (Freund et al., 2011b; Freund et al., 2011a; Henderson et al., 2011; Jutzeler et al., 2015; Wrigley et al., 2018; Wrigley et al., 2009). TMS studies similarly induce current in localised areas of M1 to induce a peripheral muscle response of cortically neighbouring body parts. These studies demonstrated that the representations of less impaired muscles shift and expand following a complete or incomplete SCI (Fassett et al., 2018; Freund et al., 2011a; Levy et al., 1990; Streletz et al., 1995; Topka et al., 1991; Urbin et al., 2019). Our fMRI results showed that tetraplegic patients had a preserved somatotopic hand representation in S1, though this deteriorated over time. We did not probe body parts other than the hand and could therefore not investigate whether any remapping of other (neighbouring and/or intact) body part representations towards or into the deprived S1 hand cortex may have taken place. Whether reorganisation and preservation of the original function can simultaneously take place within the same cortical area therefore remains a topic for further investigation. It is possible that reorganisation and preservation of the original function could co-occur within cortical areas. Indeed, non-human primate studies demonstrated that remapping observed in S1 actually reflects reorganisation in subcortical areas of the somatosensory pathway, principally the brainstem (Chand and Jain, 2015; Kambi et al., 2014). As such, the deprived S1 area receives reorganised somatosensory inputs upon tactile stimulation of neighbouring intact body parts. This would simultaneously allow the original S1 representation of the deprived body part to be preserved, as observed in our results when we directly probed the deprived S1 hand area through attempted finger movements.

Together, our findings indicate that in the first years after a tetraplegia the somatotopic S1 hand representation is preserved and can be activated through attempted movements even in the absence of retained sensory hand function, motor hand function, and spared spinal tissue bridges. These preserved S1 finger maps could be exploited in a functionally meaningful manner by rehabilitation approaches that aim to establish new functional connections between the brain and the hand after a tetraplegia, for example, through neuroprosthetic limbs or advanced exoskeletons that are directly controlled by the brain (Ajiboye et al., 2017; Armenta Salas et al., 2018; Bouton et al., 2016; Lebedev and Nicolelis, 2017).

Full details of the experimental protocol are available on clinicaltrials.gov under the number NCT03772548. Data is shared on https://osf.io/e8u95/.

1. 1. Adams RA
   2. Shipp S
   3. Friston KJ

   (2013) Predictions not commands: Active inference in the motor system

   Brain Structure & Function 218:611–643.

   https://doi.org/10.1007/s00429-012-0475-5

   • PubMed
   • Google Scholar
2. 1. Ajiboye AB
   2. Willett FR
   3. Young DR
   4. Memberg WD
   5. Murphy BA
   6. Miller JP
   7. Walter BL
   8. Sweet JA
   9. Hoyen HA
   10. Keith MW
   11. Peckham PH
   12. Simeral JD
   13. Donoghue JP
   14. Hochberg LR
   15. Kirsch RF

   (2017) Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration

   Lancet 389:1821–1830.

   https://doi.org/10.1016/S0140-6736(17)30601-3

   • PubMed
   • Google Scholar
3. 1. Akselrod M
   2. Martuzzi R
   3. Serino A
   4. van der Zwaag W
   5. Gassert R
   6. Blanke O

   (2017) 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 159:473–487.

   https://doi.org/10.1016/j.neuroimage.2017.06.021

   • PubMed
   • Google Scholar
4. Preprint

   1. Ariani G
   2. Pruszynski JA
   3. Diedrichsen J

   (2020) Motor Planning Brings Human Primary Somatosensory Cortex into Movement-Specific Preparatory States

   bioRxiv.

   https://doi.org/10.1101/2020.12.17.423254

   • Google Scholar
5. 1. Armenta Salas M
   2. Bashford L
   3. Kellis S
   4. Jafari M
   5. Jo H
   6. Kramer D
   7. Shanfield K
   8. Pejsa K
   9. Lee B
   10. Liu CY
   11. Andersen RA

   (2018) Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation

   eLife 7:e32904.

   https://doi.org/10.7554/eLife.32904

   • PubMed
   • Google Scholar
6. 1. Besle J
   2. Sánchez-Panchuelo RM
   3. Bowtell R
   4. Francis S
   5. Schluppeck D

   (2013) 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 109:2293–2305.

   https://doi.org/10.1152/jn.00499.2012

   • PubMed
   • Google Scholar
7. Book

   1. Borg I
   2. Groenen PJF

   (2005)

   Modern Multidimensional Scaling: Theory and Applications

   Springer.

   • Google Scholar
8. 1. Bouton CE
   2. Shaikhouni A
   3. Annetta NV
   4. Bockbrader MA
   5. Friedenberg DA
   6. Nielson DM
   7. Sharma G
   8. Sederberg PB
   9. Glenn BC
   10. Mysiw WJ
   11. Morgan AG
   12. Deogaonkar M
   13. Rezai AR

   (2016) Restoring cortical control of functional movement in a human with quadriplegia

   Nature 533:247–250.

   https://doi.org/10.1038/nature17435

   • PubMed
   • Google Scholar
9. 1. Bruurmijn MLCM
   2. Pereboom IPL
   3. Vansteensel MJ
   4. Raemaekers MAH
   5. Ramsey NF

   (2017) Preservation of hand movement representation in the sensorimotor areas of amputees

   Brain 140:3166–3178.

   https://doi.org/10.1093/brain/awx274

   • PubMed
   • Google Scholar
10. 1. Burman DD
    2. Lie-Nemeth T
    3. Brandfonbrener AG
    4. Parisi T
    5. Meyer JR

    (2008) Altered finger representations in sensorimotor cortex of musicians with focal dystonia: Precentral cortex

    Brain Imaging and Behavior 3:10–23.

    https://doi.org/10.1007/s11682-008-9046-z

    • Google Scholar
11. 1. Chand P
    2. Jain N

    (2015) 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 35:13475–13486.

    https://doi.org/10.1523/JNEUROSCI.2069-15.2015

    • PubMed
    • Google Scholar
12. 1. Corballis MC

    (2009) Comparing a single case with a control sample: Refinements and extensions

    Neuropsychologia 47:2687–2689.

    https://doi.org/10.1016/j.neuropsychologia.2009.04.007

    • Google Scholar
13. 1. Cramer SC
    2. Lastra L
    3. Lacourse MG
    4. Cohen MJ

    (2005) Brain motor system function after chronic, complete spinal cord injury

    Brain: A Journal of Neurology 128:2941–2950.

    https://doi.org/10.1093/brain/awh648

    • PubMed
    • Google Scholar
14. 1. Curt A
    2. Keck ME
    3. Dietz V

    (1998) Functional outcome following spinal cord injury: significance of motor-evoked potentials and ASIA scores

    Archives of Physical Medicine and Rehabilitation 79:81–86.

    https://doi.org/10.1016/S0003-9993(98)90213-1

    • PubMed
    • Google Scholar
15. 1. Da Costa S
    2. Saenz M
    3. Clarke S
    4. van der Zwaag W

    (2015) Tonotopic Gradients in Human Primary Auditory Cortex: Concurring Evidence From High-Resolution 7 T and 3 T fMRI

    Brain Topography 28:66–69.

    https://doi.org/10.1007/s10548-014-0388-0

    • PubMed
    • Google Scholar
16. 1. Da Rocha Amaral S
    2. Sanchez Panchuelo RM
    3. Francis S

    (2020) A Data-Driven Multi-scale Technique for fMRI Mapping of the Human Somatosensory Cortex

    Brain Topography 33:22–36.

    https://doi.org/10.1007/s10548-019-00728-6

    • PubMed
    • Google Scholar
17. 1. Dale AM
    2. Fischl B
    3. Sereno MI

    (1999) Cortical surface-based analysis

    NeuroImage 9:179–194.

    https://doi.org/10.1006/nimg.1998.0395

    • Google Scholar
18. 1. Delhaye BP
    2. Long KH
    3. Bensmaia SJ

    (2018) Neural basis of touch and proprioception in primate cortex

    Comprehensive Physiology 8:1575–1602.

    https://doi.org/10.1002/cphy.c170033

    • PubMed
    • Google Scholar
19. 1. Dempsey-Jones H
    2. Wesselink DB
    3. Friedman J
    4. Makin TR

    (2019) Organized Toe Maps in Extreme Foot Users

    Cell Reports 28:2748–2756.

    https://doi.org/10.1016/j.celrep.2019.08.027

    • PubMed
    • Google Scholar
20. 1. DeYoe EA
    2. Carman GJ
    3. Bandettini P
    4. Glickman S
    5. Wieser J
    6. Cox R
    7. Miller D
    8. Neitz J

    (1996) Mapping striate and extrastriate visual areas in human cerebral cortex

    PNAS 93:2382–2386.

    https://doi.org/10.1073/pnas.93.6.2382

    • PubMed
    • Google Scholar
21. 1. Dice LR

    (1945) Measures of the amount of ecologic association between species

    Ecology 26:297–302.

    https://doi.org/10.2307/1932409

    • Google Scholar
22. 1. Dienes Z

    (2014) Using Bayes to get the most out of non-significant results

    Frontiers in Psychology 5:1–17.

    https://doi.org/10.3389/fpsyg.2014.00781

    • PubMed
    • Google Scholar
23. 1. Ejaz N
    2. Hamada M
    3. Diedrichsen J

    (2015) Hand use predicts the structure of representations in sensorimotor cortex

    Nature Neuroscience 18:1034–1040.

    https://doi.org/10.1038/nn.4038

    • PubMed
    • Google Scholar
24. Book

    1. Ejaz N
    2. Sadnicka A
    3. Wiestler T
    4. Butler K
    5. Edwards M
    6. Diedrichsen J

    (2016)

    Finger Representations in Sensorimotor Cortex Are Not Disrupted in Musicians’ DystoniaSociety for Neuroscience Annual Meeting

    San Diego, USA: Society for Neuroscience Annual Meeting.

    • Google Scholar
25. 1. Elbert T
    2. Candia V
    3. Altenmüller E
    4. Rau H
    5. Sterr A
    6. Rockstroh B
    7. Pantev C
    8. Taub E

    (1998) Alteration of digital representations in somatosensory cortex in focal hand dystonia

    Neuroreport 9:3571–3575.

    https://doi.org/10.1097/00001756-199811160-00006

    • PubMed
    • Google Scholar
26. 1. Engel SA
    2. Glover GH
    3. Wandell BA

    (1997) Retinotopic organization in human visual cortex and the spatial precision of functional MRI

    Cerebral Cortex 7:181–192.

    https://doi.org/10.1093/cercor/7.2.181

    • PubMed
    • Google Scholar
27. 1. Fassett HJ
    2. Turco CV
    3. El-Sayes J
    4. Nelson AJ

    (2018) Alterations in motor cortical representation of muscles following incomplete spinal cord injury in humans

    Brain Sciences 8:E225.

    https://doi.org/10.3390/brainsci8120225

    • PubMed
    • Google Scholar
28. Preprint

    1. Fifer MS
    2. McMullen DP
    3. Thomas TM
    4. Osborn LE
    5. Nickl RW
    6. Candrea DN
    7. Pohlmeyer EA
    8. Thompson MC
    9. Anaya M
    10. Schellekens W
    11. Ramsey NF
    12. Bensmaia SJ
    13. Anderson WS
    14. Wester BA
    15. Crone NE
    16. Celnik PA
    17. Cantarero GL
    18. Tenore F

    (2020) Intracortical Microstimulation Elicits Human Fingertip Sensations

    medRxiv.

    https://www.medrxiv.org/content/10.1101/2020.05.29.20117374v3

    • Google Scholar
29. 1. Fischl B
    2. Liu A
    3. Dale AM

    (2001) Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex

    IEEE Transactions on Medical Imaging 20:70–80.

    https://doi.org/10.1109/42.906426

    • PubMed
    • Google Scholar
30. 1. Flesher SN
    2. Collinger JL
    3. Foldes ST
    4. Weiss JM
    5. Downey JE
    6. Tyler-Kabara EC
    7. Bensmaia SJ
    8. Schwartz AB
    9. Boninger ML
    10. Gaunt RA

    (2016) Intracortical microstimulation of human somatosensory cortex

    Science Translational Medicine 8:1–11.

    https://doi.org/10.1126/scitranslmed.aaf8083

    • Google Scholar
31. 1. Freund P
    2. Rothwell J
    3. Craggs M
    4. Thompson AJ
    5. Bestmann S

    (2011a) Corticomotor representation to a human forearm muscle changes following cervical spinal cord injury

    European Journal of Neuroscience 34:1839–1846.

    https://doi.org/10.1111/j.1460-9568.2011.07895.x

    • Google Scholar
32. 1. Freund P
    2. Weiskopf N
    3. Ward NS
    4. Hutton C
    5. Gall A
    6. Ciccarelli O
    7. Craggs M
    8. Friston K
    9. Thompson AJ

    (2011b) Disability, atrophy and cortical reorganization following spinal cord injury

    Brain: A Journal of Neurology 134:1610–1622.

    https://doi.org/10.1093/brain/awr093

    • PubMed
    • Google Scholar
33. Preprint

    1. Gooijers J
    2. Chalavi S
    3. Roebroeck A
    4. Kaas S
    5. Swinnen SP

    (2021) Representational similarity scores of digits in the sensorimotor cortex are associated with behavioral performance

    bioRxiv.

    https://doi.org/10.1101/2021.06.18.448803

    • Google Scholar
34. 1. Greve DN
    2. Fischl B

    (2009) Accurate and robust brain image alignment using boundary-based registration

    NeuroImage 48:63–72.

    https://doi.org/10.1016/j.neuroimage.2009.06.060

    • PubMed
    • Google Scholar
35. 1. Halder P
    2. Kambi N
    3. Chand P
    4. Jain N

    (2018) 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 28:3922–3938.

    https://doi.org/10.1093/cercor/bhx256

    • PubMed
    • Google Scholar
36. 1. Henderson LA
    2. Gustin SM
    3. Macey PM
    4. Wrigley PJ
    5. Siddall PJ

    (2011) Functional reorganization of the brain in humans following spinal cord injury: Evidence for underlying changes in cortical anatomy

    The Journal of Neuroscience 31:2630–2637.

    https://doi.org/10.1523/JNEUROSCI.2717-10.2011

    • PubMed
    • Google Scholar
37. 1. Horsfield MA
    2. Sala S
    3. Neema M
    4. Absinta M
    5. Bakshi A
    6. Sormani MP
    7. Rocca MA
    8. Bakshi R
    9. Filippi M

    (2010) Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: Application in multiple sclerosis

    NeuroImage 50:446–455.

    https://doi.org/10.1016/j.neuroimage.2009.12.121

    • PubMed
    • Google Scholar
38. 1. Hotz-Boendermaker S
    2. Funk M
    3. Summers P
    4. Brugger P
    5. Hepp-Reymond MC
    6. Curt A
    7. Kollias SS

    (2008) Preservation of motor programs in paraplegics as demonstrated by attempted and imagined foot movements

    NeuroImage 39:383–394.

    https://doi.org/10.1016/j.neuroimage.2007.07.065

    • PubMed
    • Google Scholar
39. 1. Huber E
    2. Lachappelle P
    3. Sutter R
    4. Curt A
    5. Freund P

    (2017) Are midsagittal tissue bridges predictive of outcome after cervical spinal cord injury?

    Annals of Neurology 81:740–748.

    https://doi.org/10.1002/ana.24932

    • PubMed
    • Google Scholar
40. 1. Jain N
    2. Catania KC
    3. Kaas JH

    (1998) A histologically visible representation of the fingers and palm in primate area 3b and its immutability following long-term deafferentations

    Cerebral Cortex 8:227–236.

    https://doi.org/10.1093/cercor/8.3.227

    • PubMed
    • Google Scholar
41. 1. Jain N
    2. Qi HX
    3. Collins CE
    4. Kaas JH

    (2008) Large-scale reorganization in the somatosensory cortex and thalamus after sensory loss in macaque monkeys

    The Journal of Neuroscience 28:11042–11060.

    https://doi.org/10.1523/JNEUROSCI.2334-08.2008

    • PubMed
    • Google Scholar
42. 1. Jenkinson M
    2. Bannister P
    3. Brady M
    4. Smith SM

    (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images

    NeuroImage 17:825–841.

    https://doi.org/10.1016/S1053-8119(02)91132-8

    • PubMed
    • Google Scholar
43. 1. Jutzeler CR
    2. Freund P
    3. Huber E
    4. Curt A
    5. Kramer JLK

    (2015) Neuropathic pain and functional reorganization in the primary sensorimotor cortex after spinal cord injury

    The Journal of Pain 16:1256–1267.

    https://doi.org/10.1016/j.jpain.2015.08.008

    • PubMed
    • Google Scholar
44. 1. Kalsi-Ryan S
    2. Beaton D
    3. Curt A
    4. Duff S
    5. Popovic MR
    6. Rudhe C
    7. Fehlings MG
    8. Verrier MC

    (2012) The Graded Redefined Assessment of Strength Sensibility and Prehension: Reliability and Validity

    Journal of Neurotrauma 29:905–914.

    https://doi.org/10.1089/neu.2010.1504

    • PubMed
    • Google Scholar
45. 1. Kalsi-Ryan S
    2. Beaton D
    3. Curt A
    4. Popovic MR
    5. Verrier MC
    6. Fehlings MG

    (2014) Outcome of the upper limb in cervical spinal cord injury: Profiles of recovery and insights for clinical studies

    The Journal of Spinal Cord Medicine 37:503–510.

    https://doi.org/10.1179/2045772314Y.0000000252

    • PubMed
    • Google Scholar
46. 1. Kambi N
    2. Halder P
    3. Rajan R
    4. Arora V
    5. Chand P
    6. Arora M
    7. Jain N

    (2014) Large-scale reorganization of the somatosensory cortex following spinal cord injuries is due to brainstem plasticity

    Nature Communications 5:3602.

    https://doi.org/10.1038/ncomms4602

    • PubMed
    • Google Scholar
47. 1. Kass RE
    2. Raftery AE

    (1995) Bayes Factors

    Journal of the American Statistical Association 90:773–795.

    https://doi.org/10.1080/01621459.1995.10476572

    • Google Scholar
48. 1. Kieliba P
    2. Clode D
    3. Maimon-Mor RO
    4. Makin TR

    (2021) Robotic hand augmentation drives changes in neural body representation

    Science Robotics 6:eabd7935.

    https://doi.org/10.1126/scirobotics.abd7935

    • Google Scholar
49. 1. Kikkert S
    2. Kolasinski J
    3. Jbabdi S
    4. Tracey I
    5. Beckmann CF
    6. Johansen-Berg H
    7. Makin TR

    (2016) Revealing the neural fingerprints of a missing hand

    eLife 5:e15292.

    https://doi.org/10.7554/eLife.15292

    • PubMed
    • Google Scholar
50. 1. Kikkert S
    2. Johansen-Berg H
    3. Tracey I
    4. Makin TR

    (2018) 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 106:174–184.

    https://doi.org/10.1016/j.cortex.2018.05.013

    • PubMed
    • Google Scholar
51. 1. Kikkert S
    2. Mezue M
    3. O’Shea J
    4. Henderson Slater D
    5. Johansen-Berg H
    6. Tracey I
    7. Makin TR

    (2019) Neural basis of induced phantom limb pain relief

    Annals of Neurology 85:59–73.

    https://doi.org/10.1002/ana.25371

    • PubMed
    • Google Scholar
52. 1. Kokotilo KJ
    2. Eng JJ
    3. Curt A

    (2009) Reorganization and preservation of motor control of the brain in spinal cord injury: a systematic review

    Journal of Neurotrauma 26:2113–2126.

    https://doi.org/10.1089/neu.2008.0688

    • PubMed
    • Google Scholar
53. 1. Kolasinski J
    2. Makin TR
    3. Jbabdi S
    4. Clare S
    5. Stagg CJ
    6. Johansen-Berg H

    (2016a) Investigating the stability of fine-grain digit somatotopy in individual human participants

    The Journal of Neuroscience 36:1113–1127.

    https://doi.org/10.1523/JNEUROSCI.1742-15.2016

    • PubMed
    • Google Scholar
54. 1. Kolasinski J
    2. Makin TR
    3. Logan JP
    4. Jbabdi S
    5. Clare S
    6. Stagg CJ
    7. Johansen-Berg H

    (2016b) Perceptually relevant remapping of human somatotopy in 24 hours

    eLife 5:e17280.

    https://doi.org/10.7554/eLife.17280

    • PubMed
    • Google Scholar
55. 1. Kriegeskorte N
    2. Mur M
    3. Bandettini P

    (2008) Representational similarity analysis - connecting the branches of systems neuroscience

    Frontiers in Systems Neuroscience 2:1–28.

    https://doi.org/10.3389/neuro.06.004.2008

    • PubMed
    • Google Scholar
56. 1. Kuehn E
    2. Haggard P
    3. Villringer A
    4. Pleger B
    5. Sereno MI

    (2018) Visually-driven maps in area 3b

    The Journal of Neuroscience 38:1295–1310.

    https://doi.org/10.1523/JNEUROSCI.0491-17.2017

    • PubMed
    • Google Scholar
57. 1. Lebedev MA
    2. Nicolelis MAL

    (2017) Brain-machine interfaces: From basic science to neuroprostheses and neurorehabilitation

    Physiological Reviews 97:767–837.

    https://doi.org/10.1152/physrev.00027.2016

    • PubMed
    • Google Scholar
58. 1. Levy WJ
    2. Amassian VE
    3. Traad M
    4. Cadwell J

    (1990) Focal magnetic coil stimulation reveals motor cortical system reorganized in humans after traumatic quadriplegia

    Brain Research 510:130–134.

    https://doi.org/10.1016/0006-8993(90)90738-W

    • PubMed
    • Google Scholar
59. 1. Liao C-C
    2. Qi H-X
    3. Reed JL
    4. Jeoung H-S
    5. Kaas JH

    (2021) Corticocuneate projections are altered after spinal cord dorsal column lesions in New World monkeys

    The Journal of Comparative Neurology 529:1669–1702.

    https://doi.org/10.1002/cne.25050

    • PubMed
    • Google Scholar
60. 1. Liu P
    2. Chrysidou A
    3. Doehler J
    4. Hebart MN
    5. Wolbers T
    6. Kuehn E

    (2021) The organizational principles of de-differentiated topographic maps in somatosensory cortex

    eLife 10:e60090.

    https://doi.org/10.7554/eLife.60090

    • PubMed
    • Google Scholar
61. 1. London BM
    2. Miller LE

    (2013) Responses of somatosensory area 2 neurons to actively and passively generated limb movements

    Journal of Neurophysiology 109:1505–1513.

    https://doi.org/10.1152/jn.00372.2012

    • PubMed
    • Google Scholar
62. 1. Losseff NA
    2. Webb SL
    3. O’Riordan JI
    4. Page R
    5. Wang L
    6. Barker GJ
    7. Tofts PS
    8. McDonald WI
    9. Miller DH
    10. Thompson AJ

    (1996) 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 119:701–708.

    https://doi.org/10.1093/brain/119.3.701

    • PubMed
    • Google Scholar
63. 1. Mair P
    2. Wilcox R

    (2020) Robust statistical methods in R using the WRS2 package

    Behavior Research Methods 52:464–488.

    https://doi.org/10.3758/s13428-019-01246-w

    • PubMed
    • Google Scholar
64. 1. Makin TR
    2. Scholz J
    3. Filippini N
    4. Henderson Slater D
    5. Tracey I
    6. Johansen-Berg H

    (2013) Phantom pain is associated with preserved structure and function in the former hand area

    Nature Communications 4:1570.

    https://doi.org/10.1038/ncomms2571

    • PubMed
    • Google Scholar
65. 1. Mancini F
    2. Haggard P
    3. Iannetti GD
    4. Longo MR
    5. Sereno MI

    (2012) Fine-grained nociceptive maps in primary somatosensory cortex

    The Journal of Neuroscience 32:17155–17162.

    https://doi.org/10.1523/JNEUROSCI.3059-12.2012

    • PubMed
    • Google Scholar
66. 1. Mancini F
    2. Wang AP
    3. Schira MM
    4. Isherwood ZJ
    5. McAuley JH
    6. Iannetti GD
    7. Sereno MI
    8. Moseley GL
    9. Rae CD

    (2019) Fine-Grained Mapping of Cortical Somatotopies in Chronic Complex Regional Pain Syndrome

    The Journal of Neuroscience 39:9185–9196.

    https://doi.org/10.1523/JNEUROSCI.2005-18.2019

    • Google Scholar
67. 1. Nili H
    2. Wingfield C
    3. Walther A
    4. Su L
    5. Marslen-Wilson W
    6. Kriegeskorte N

    (2014) A Toolbox for Representational Similarity Analysis

    PLOS Computational Biology 10:e1003553.

    https://doi.org/10.1371/journal.pcbi.1003553

    • PubMed
    • Google Scholar
68. 1. Nyström B
    2. Hagbarth KE

    (1981) Microelectrode recordings from transected nerves in amputees with phantom limb pain

    Neuroscience Letters 27:211–216.

    https://doi.org/10.1016/0304-3940(81)90270-6

    • PubMed
    • Google Scholar
69. 1. Ozdemir RA
    2. Perez MA

    (2018) Afferent Input and Sensory Function after Human Spinal Cord Injury

    Journal of Neurophysiology 119:134–144.

    https://doi.org/10.1152/jn.00354.2017

    • PubMed
    • Google Scholar
70. 1. Petersen JA
    2. Wilm BJ
    3. von Meyenburg J
    4. Schubert M
    5. Seifert B
    6. Najafi Y
    7. Dietz V
    8. Kollias S

    (2012) Chronic Cervical Spinal Cord Injury: DTI Correlates with Clinical and Electrophysiological Measures

    Journal of Neurotrauma 29:1556–1566.

    https://doi.org/10.1089/neu.2011.2027

    • PubMed
    • Google Scholar
71. 1. Pfyffer D
    2. Huber E
    3. Sutter R
    4. Curt A
    5. Freund P

    (2019) Tissue bridges predict recovery after traumatic and ischemic thoracic spinal cord injury

    Neurology 93:e1550–e1560.

    https://doi.org/10.1212/WNL.0000000000008318

    • PubMed
    • Google Scholar
72. 1. Pfyffer D
    2. Vallotton K
    3. Curt A
    4. Freund P

    (2021) Predictive Value of Midsagittal Tissue Bridges on Functional Recovery After Spinal Cord Injury

    Neurorehabilitation and Neural Repair 35:33–43.

    https://doi.org/10.1177/1545968320971787

    • PubMed
    • Google Scholar
73. 1. Puckett AM
    2. Bollmann S
    3. Barth M
    4. Cunnington R

    (2017) Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI

    NeuroImage 161:179–187.

    https://doi.org/10.1016/j.neuroimage.2017.08.014

    • PubMed
    • Google Scholar
74. 1. Puckett AM
    2. Bollmann S
    3. Junday K
    4. Barth M
    5. Cunnington R

    (2020) Bayesian population receptive field modeling in human somatosensory cortex

    NeuroImage 208:116465.

    https://doi.org/10.1016/j.neuroimage.2019.116465

    • PubMed
    • Google Scholar
75. 1. Sabbah P
    2. de SS
    3. Leveque C
    4. Gay S
    5. Pfefer F
    6. Nioche C
    7. Sarrazin JL
    8. Barouti H
    9. Tadie M
    10. Cordoliani YS

    (2002) Sensorimotor cortical activity in patients with complete spinal cord injury: A functional magnetic resonance imaging study

    Journal of Neurotrauma 19:53–60.

    https://doi.org/10.1089/089771502753460231

    • PubMed
    • Google Scholar
76. Preprint

    1. Sanders ZB
    2. Wesselink DB
    3. Dempsey-Jones H
    4. Makin TR

    (2019) Similar somatotopy for active and passive digit representation in primary somatosensory cortex

    bioRxiv.

    https://doi.org/10.1101/754648

    • Google Scholar
77. 1. Sereno MI
    2. Dale AM
    3. Reppas JB
    4. Kwong KK
    5. Belliveau JW
    6. Brady TJ
    7. Rosen BR
    8. Tootell RBH

    (1995) Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging

    Science 268:889–893.

    https://doi.org/10.1126/science.7754376

    • Google Scholar
78. 1. Smith SM

    (2002) Fast robust automated brain extraction

    Human Brain Mapping 17:143–155.

    https://doi.org/10.1002/hbm.10062

    • PubMed
    • Google Scholar
79. 1. Solstrand Dahlberg L
    2. Becerra L
    3. Borsook D
    4. Linnman C

    (2018) Brain changes after spinal cord injury, a quantitative meta-analysis and review

    Neuroscience and Biobehavioral Reviews 90:272–293.

    https://doi.org/10.1016/j.neubiorev.2018.04.018

    • PubMed
    • Google Scholar
80. 1. Streletz LJ
    2. Belevich JKS
    3. Jones SM
    4. Bhushan A
    5. Shah SH
    6. Herbison GJ

    (1995) Transcranial magnetic stimulation: Cortical motor maps in acute spinal cord injury

    Brain Topography 7:245–250.

    https://doi.org/10.1007/BF01202383

    • PubMed
    • Google Scholar
81. 1. Talavage TM
    2. Sereno MI
    3. Melcher JR
    4. Ledden PJ
    5. Rosen BR
    6. Dale AM

    (2004) Tonotopic Organization in Human Auditory Cortex Revealed by Progressions of Frequency Sensitivity

    Journal of Neurophysiology 91:1282–1296.

    https://doi.org/10.1152/jn.01125.2002

    • PubMed
    • Google Scholar
82. 1. Topka H
    2. Cohen LG
    3. Cole RA
    4. Hallett M

    (1991) Reorganization of corticospinal pathways following spinal cord injury

    Neurology 41:1276–1283.

    https://doi.org/10.1212/wnl.41.8.1276

    • PubMed
    • Google Scholar
83. 1. Urbin MA
    2. Royston DA
    3. Weber DJ
    4. Boninger ML
    5. Collinger JL

    (2019) What is the functional relevance of reorganization in primary motor cortex after spinal cord injury?

    Neurobiology of Disease 121:286–295.

    https://doi.org/10.1016/j.nbd.2018.09.009

    • PubMed
    • Google Scholar
84. 1. Vallotton K
    2. Huber E
    3. Sutter R
    4. Curt A
    5. Hupp M
    6. Freund P

    (2019) Width and neurophysiologic properties of tissue bridges predict recovery after cervical injury

    Neurology 92:E2793–E2802.

    https://doi.org/10.1212/WNL.0000000000007642

    • PubMed
    • Google Scholar
85. 1. Vaso A
    2. Adahan HM
    3. Gjika A
    4. Zahaj S
    5. Zhurda T
    6. Vyshka G
    7. Devor M

    (2014) Peripheral nervous system origin of phantom limb pain

    Pain 155:1384–1391.

    https://doi.org/10.1016/j.pain.2014.04.018

    • PubMed
    • Google Scholar
86. Software

    1. Wesselink DB
    2. Maimon-Mor R

    (2017) rsatoolbox

    Github.

    https://github.com/ronimaimon/rsatoolbox
87. 1. Wesselink DB
    2. van den Heiligenberg FM
    3. Ejaz N
    4. Dempsey-Jones H
    5. Cardinali L
    6. Tarall-Jozwiak A
    7. Diedrichsen J
    8. Makin TR

    (2019) Obtaining and maintaining cortical hand representation as evidenced from acquired and congenital handlessness

    eLife 8:e37227.

    https://doi.org/10.7554/eLife.37227

    • Google Scholar
88. Preprint

    1. Wesselink DB
    2. Kolasinski J
    3. Kikkert S
    4. Hurley SA
    5. Bridge H
    6. Makin TR

    (2021) Finger representation in the cortex of the congenitally blind

    bioRxiv.

    https://doi.org/10.1101/2021.03.16.435392

    • Google Scholar
89. 1. Wrigley PJ
    2. Press SR
    3. Gustin SM
    4. Macefield VG
    5. Gandevia SC
    6. Cousins MJ
    7. Middleton JW
    8. Henderson LA
    9. Siddall PJ

    (2009) Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury

    Pain 141:52–59.

    https://doi.org/10.1016/j.pain.2008.10.007

    • PubMed
    • Google Scholar
90. 1. Wrigley PJ
    2. Siddall PJ
    3. Gustin SM

    (2018) New evidence for preserved somatosensory pathways in complete spinal cord injury: A fMRI study

    Human Brain Mapping 39:588–598.

    https://doi.org/10.1002/hbm.23868

    • PubMed
    • Google Scholar
91. 1. Yousry TA
    2. Schmid UD
    3. Alkadhi H
    4. Schmidt D
    5. Peraud A
    6. Buettner A
    7. Winkler P

    (1997) Localization of the motor hand area to a knob on the precentral gyrus A new landmark

    Brain: A Journal of Neurology 120:141–157.

    https://doi.org/10.1093/brain/120.1.141

    • PubMed
    • Google Scholar
92. 1. Zeharia N
    2. Hertz U
    3. Flash T
    4. Amedi A

    (2015) New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity

    The Journal of Neuroscience 35:2845–2859.

    https://doi.org/10.1523/Jneurosci.4246-14.2015

    • PubMed
    • Google Scholar

Acceptance summary:

This paper demonstrates that the spatial organization of the somatosensory cortex deteriorates very slowly following spinal cord injury that results in tetraplegia. The findings contribute to a developing story on how sensory representations are formed, changed and maintained and has implications for the development of brain-machine interfaces.

Decision letter after peer review:

Thank you for submitting your article "Finger somatotopy is preserved after tetraplegia but deteriorates over time" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by Andrew Pruszynski as Reviewing Editor and Richard Ivry as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Sliman J Bensmaia (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this letter to help you prepare a revised submission.

Essential revisions:

1) The authors need to provide a clearer hypothesis about the mechanistic changes of the sensorimotor maps in the patients. This requires a thorough description of prior results and how these prior results motivated the present study and the analyses conducted. The reviewers emphasize that this will also require additional analyses that bring the present study into alignment with previous work. In this respect, Reviewer 1 and 2 indicate specific figures and analyses that need to be done and presented in a revised manuscript.

2) There is substantial concern that the key "typicality" analysis is not valid. As detailed by Reviewer 2 there are previous studies that have approached this issue but the present manuscript largely ignores this previous literature and uses their own ad hoc approach. The issue of defining typicality needs to be meaningfully (analytically) addressed in reference to previous established approaches.

3) There are several analytical points that require attention, either because the choices are unclear or that critical details are not reported.

4) Provide a more thorough Discussion, especially in the context of alternative explanations for the present findings. The reviewers all raise important concerns that the present account is very motor-effector dominated and dismisses other potential explanations. In particular, pay close attention to the comments raised by Reviewer #1 in terms of attentional mechanisms and how they may confound the present empirical results. This limitation needs to be addressed either experimentally, or given that possibility is unlikely, explicitly in the Discussion.

Reviewer #1 (Recommendations for the authors):

Abstract: It is unclear what evidence serves the foundation for the authors' claim that rehabilitation approaches would be most promising when applied within the first years after injury. I can see why this might be speculated, but is there any previous work showing that those with in-tact hand representations are more conducive to rehabilitation than those with deteriorated representations?

Lines 106-116: This section somewhat gives the impression that complete digit maps were found in everyone. Consider tempering this a bit by pointing out that, despite all maps displaying characteristics of typical digit maps, some digit representations are missing. That said, I appreciate the authors including each participant's map in the main paper – very nice to see all the examples!

Line 180: Upon first read, I misinterpreted the statement that "congenital one-handers do not have a missing hand representation". Consider hashing this out a bit more by explicitly stating that they do not develop a cortical representation for the missing body part and hence do not have a hand representation unlike amputees that develop the representation before losing the hand – and hence have a "missing hand representation". This notion is made a bit clearer on lines 266-267; maybe bring forward.

Line 527-529: Given that the map wasn't identified in the patient that reported performing imagined movement as well as the authors' emphasis that the movement was attempted and not imagined (lines 85-86, plus methods), consider adding a bit in the discussion regarding the difference between attempting and imagining a movement – and why they might lead to different activity patterns.

Reviewer #2 (Recommendations for the authors):

– I would suggest that the authors perform all analyses including the factor of finger, and that they report finger-specific statistics and tables on all reported analyses. Indeed, looking at the individual maps, it seems that in the patients, fingers are missing. It is also evident that the thumb seems more distant in controls compared to patients. This has to be tested for.

– I would suggest that the authors report % signal change both for the averaged map, for each single finger representation, and for the peak voxels of each finger.

– Prior results on SCI patients have to be described in more detail, also with respect to the used methods (TMS, fMRI).

– To target no 4 in the public review: Remove analyses.

– Conduct analyses on representation order and alignment, map size, and similarity and argue accordingly. Also, the conducted ANOVA is not mentioned in the Methods section, where I indeed wondered why a repeated measure ANOVA was conducted and not a mixed ANOVA with the factor "group". How do the authors want to detect group differences when "group" is not a factor in the ANOVA?

– Methods. It is not clear to me how the mean r was calculated. From what I understand, the authors use the higher r-value as a winner-takes-it-all approach to say which finger wins over the other fingers. When I understand correctly, no statistical threshold is applied here. Therefore, am I correct in assuming that a non-thresholded r map was then transferred to FDR correction?

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Finger somatotopy is preserved after tetraplegia but deteriorates over time" for further consideration by eLife. Your revised article has been reviewed by 3 reviewers and the evaluation has been overseen by Andrew Pruszynski as the Reviewing Editor and Richard Ivry as the Senior Editor.

The manuscript has been substantially improved and there remain only some small issues that need to be addressed as described below by Reviewers #1 and #2. Please play particular attention to (1) ensuring the abstract is clear and (2) that the finger specific RSA analysis is included in the supplement. We will not send this out to external review again.

Reviewer #1 (Recommendations for the authors):

I appreciate the thorough response from the authors and believe that the revised manuscript presents a much more complete and balanced view. My only remaining comment is that although I find the RSA analysis to be appropriate here, I disagree with the authors' claims that it has become the "most common" / "gold standard" approach to investigating inter-finger overlap / somatotopy. And I'm not confident that you'd find consensus for this position among those in the field. As such, consider walking this claim back a bit.

Reviewer #2 (Recommendations for the authors):

Overall

I thank the authors for performing additional analyses that improved the quality of manuscript and significantly strengthened the claims they made.

Concept

I thank the authors for adding more background information on nonhuman primates, behavioral and fMRI human studies to argue what (or what not) to expect in their study results. Nevertheless, I still think that the major question posed in the abstract is still not accurate. They write in the abstract:

It is not clear "whether somatotopic representations can be preserved despite alterations in net activity". This is really confusing because in the manuscript, the authors do not show alterations in net activity. In addition, in response to both reviewer 2 and 3, the authors removed the formulation "preserved" from the discussion. Please also remove this from the abstract (at present it is still used 2 times). In addition, as argued by reviewer 1, if attention is one of the mechanisms that triggers the activity, it is not clear whether attention-related net activity should be higher or lower. I would therefore suggest to be precise also in the abstract and write that they investigate "whether somatotopic representations can be activated topographically despite reduced or absent afferent input" (or similar).

Analyses/Results

I thank the authors for conducting an ANOVA including the factors group and finger pair for the RSA, and for conducting finger-specific analyses using percent signal change. It is interesting to see that there is no interaction between group and finger pair, and that individual fingers do not differ in signal change. The authors then say that they conducted individual finger analyses where the BF revealed inconclusive evidence for the RSA analyses. Later in the response letter, they say that those analyses have been included as figure supplement into the manuscript: however, within the material downloaded, I could not find these figures. If the finger pair-specific RSA values are therefore not yet included in the supplemental material, I would suggest adding those because 1. Prior studies hint towards finger-specific differences and researchers would like to see what this study revealed in this respect, 2. The amplitude analyses provide a hint towards differences for D4 that would be interesting to inspect for the RSA results too.

It is good to see that the typicality results did not change when using data of the control group as a basis. This makes this analysis much more convincing. Given the authors argue that it would be good to always use the same data set to compare patients against, in my view, it would be of great benefit for the community if the data and results could be made publicly available (in particular the data taken from the Wesselink study) so that potentially other researchers can compare their own results against those.

Reviewer #3 (Recommendations for the authors):

I am satisfied with the revisions.

Essential revisions:

1) The authors need to provide a clearer hypothesis about the mechanistic changes of the sensorimotor maps in the patients. This requires a thorough description of prior results and how these prior results motivated the present study and the analyses conducted. The reviewers emphasize that this will also require additional analyses that bring the present study into alignment with previous work. In this respect, Reviewer 1 and 2 indicate specific figures and analyses that need to be done and presented in a revised manuscript.

We have revised the Introduction accordingly and conducted the analysis suggested by the reviewers. For more details, please see our responses to the specific comments of the reviewers.

2) There is substantial concern that the key "typicality" analysis is not valid. As detailed by Reviewer 2 there are previous studies that have approached this issue but the present manuscript largely ignores this previous literature and uses their own ad hoc approach. The issue of defining typicality needs to be meaningfully (analytically) addressed in reference to previous established approaches.

We respectfully disagree that the typicality measure is not standard, invalid, or inaccurate. The representational structure of the fingers (assessed using RSA) has been shown to depict the invariant organization of S1 better than the exact spatial distribution of finger selective clusters (Ejaz et al., 2015). RSA-based measures are furthermore not prone to some of the problems of the measurements of finger selectivity (e.g., dependence on map thresholds). Indeed, over the past years RSA has become the gold standard to investigate somatotopy of finger representations, both in healthy (e.g. Akselrod et al., 2017; Ejaz et al., 2015; Kieliba et al., 2021; Kolasinski et al., 2016; Sanders et al., 2019) and patient populations (e.g. Dempsey-Jones et al., 2019; Ejaz et al., 2016; Kikkert et al., 2016; Wesselink et al., 2019). Moreover, various papers have been published in eLife and elsewhere that used the same RSA-based typicality criteria to assess plasticity in finger representations (Dempsey-Jones et al., 2019; Ejaz et al., 2015; Kieliba et al., 2021; Wesselink et al., 2019). We have added clarification regarding this to Introduction and Methods of the manuscript.

3) There are several analytical points that require attention, either because the choices are unclear or that critical details are not reported .

We thank the reviewers for pointing out this lack of clarity. We have adjusted our text to clarify these choices and added the suggested figures and analysis. Please see our response to the reviewers’ specific comments for further details.

4) Provide a more thorough Discussion, especially in the context of alternative explanations for the present findings. The reviewers all raise important concerns that the present account is very motor-effector dominated and dismisses other potential explanations. In particular, pay close attention to the comments raised by Reviewer #1 in terms of attentional mechanisms and how they may confound the present empirical results. This limitation needs to be addressed either experimentally, or given that possibility is unlikely, explicitly in the Discussion.

We agree that a more balanced speculation of the potential mechanisms underlying the phenomenon of preserved finger mapping would be valuable and have therefore adjusted the Discussion accordingly.

Reviewer #1 (Recommendations for the authors):

Abstract: It is unclear what evidence serves the foundation for the authors' claim that rehabilitation approaches would be most promising when applied within the first years after injury. I can see why this might be speculated, but is there any previous work showing that those with in-tact hand representations are more conducive to rehabilitation than those with deteriorated representations?

This is a speculation and we have removed this statement from the abstract in the revised manuscript. Instead, we now state the following:

Revised text Abstract:

“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.”

Lines 106-116: This section somewhat gives the impression that complete digit maps were found in everyone. Consider tempering this a bit by pointing out that, despite all maps displaying characteristics of typical digit maps, some digit representations are missing. That said, I appreciate the authors including each participant's map in the main paper – very nice to see all the examples!

We agree with the reviewer and we therefore removed the sentence stating that the patient and control maps were qualitatively similar between patients and controls. We instead state that despite all maps displaying aspects of characteristic finger maps, some finger representations were not visible in the thresholded patient and control maps.

Revised text Results:

“Overall, we found aspects of somatotopic finger selectivity in the maps of SCI patients’ hands, in which neighbouring clusters showed selectivity for neighbouring fingers in contralateral S1, similar to those observed in eighteen age-, sex-, and handedness-matched healthy controls. Notably, a characteristic hand map was even found in a patient who suffered complete paralysis and sensory deprivation of the hands (Figure 2, patient map 1; patient S01). Despite most maps (Figure 2, except patient map 3) displaying aspects of characteristic finger selectivity, some finger representations were not visible in the thresholded patient and control maps.”

Line 180: Upon first read, I misinterpreted the statement that "congenital one-handers do not have a missing hand representation". Consider hashing this out a bit more by explicitly stating that they do not develop a cortical representation for the missing body part and hence do not have a hand representation unlike amputees that develop the representation before losing the hand – and hence have a "missing hand representation". This notion is made a bit clearer on lines 266-267; maybe bring forward.

We thank the reviewer for highlighting this to us. We have added the suggested text to these lines in our revised manuscript.

Revised text Results:

“Congenital one-handers are born without a hand and therefore do not have a cortical representation of the missing hand (unlike amputees who develop the representation before losing the hand and hence have a ‘missing hand representation’; Wesselink et al., 2019).”

Line 527-529: Given that the map wasn't identified in the patient that reported performing imagined movement as well as the authors' emphasis that the movement was attempted and not imagined (lines 85-86, plus methods), consider adding a bit in the discussion regarding the difference between attempting and imagining a movement – and why they might lead to different activity patterns.

We thank the reviewer for their suggestion. We are however hesitant to make any strong claims about the putative difference between imagined and attempted movements based on the anecdotal report of this patient. We have revised the manuscript to stress the fact that after the measurement, this patient anecdotally mentioned that he had trouble performing the attempted movements. We are hesitant to speculate about what he might have done instead since we did not include a systematic debriefing procedure to document the patients’ strategies in sufficient detail (e.g., was this patient performing kinaesthetic or visual imagery, or was rather something different). We are aware this is a weakness and have therefore added this debriefing procedure to our follow-up studies.

Revised text Methods:

“We were unable to find a characteristic hand map in one patient who anecdotally reported post hoc that he was unable to perform attempted finger movements.”

Reviewer #2 (Recommendations for the authors):

– I would suggest that the authors perform all analyses including the factor of finger, and that they report finger-specific statistics and tables on all reported analyses. Indeed, looking at the individual maps, it seems that in the patients, fingers are missing. It is also evident that the thumb seems more distant in controls compared to patients. This has to be tested for.

With regards to the reviewer’s concern about missing fingers – note that the RSA analysis does not depend on any thresholding (i.e., it works with unthresholded data) and missing fingers due to clusters not surviving thresholding will not impact this analysis. A true missing finger would result in a low typicality score.

Following the reviewer’s suggestion, we have included individual participant inter-finger distance plots for both the controls and patients as Figure 3—figure supplement 2 and Figure 3—figure supplement 3, respectively. We believe this is more readily readable and interpretable than a table containing the 10 inter-finger distance scores for all 32 participants. Instead, these values have been made available online on https://osf.io/e8u95/.

Lastly, we have conducted a geodesic distance analysis to assess whether the finger representations of the SCI patients were aligned differently and/or shifted compared to the control participants. Note however that RSA-based inter-finger distance patterns have been shown to depict the invariant representational structure of fingers in S1 and M1 better than the size, shape, and exact location of the areas activated by finger movements (Ejaz et al., 2015). The geodesic cortical distance was calculated between each participant’s peak finger activation and a reference anchor in the S1 foot cortex. We used the blocked design data for this analysis as the travelling wave paradigm does not lend itself to accurately extract peak finger activation locations due to the consecutive movement task. A robust mixed ANOVA with a within-participants factor for finger (5 levels: thumb, index, middle, ring, and little finger) and a between-participants factor for group (2 levels: controls and patients) showed that, as expected, the geodesic distances were significantly different across fingers (i.e., a main effect for fingers; F_(1,18.81) = 4.29, p = 0.05). While the peak finger vertexes were located more lateral for the patient compared to the control group (i.e., a main effect for group; F_(4,13.93) = 85.66, p < 0.001), the geodesic distance pattern across the fingers was not significantly different across groups (i.e., no significant finger*group interaction; F_(4,13.93) = 0.91, p = 0.48). When testing for group differences per finger, the BF only revealed inconclusive evidence (BF > 0.34 and < 1.88; note that we could not run a Bayesian ANOVA due to normality violations). We have added this analysis to Appendix 1.

Revised text Methods:

“We further compared activity levels in finger-specific ROIs in S1 between groups and conducted a geodesic distance analysis to assess whether the finger representations of SCI patients were aligned differently and/or shifted compared to the control group (see Appendix 1).”

Please see Appendix 1, “Geodesic distance analysis” section for the revised text.

– I would suggest that the authors report % signal change both for the averaged map, for each single finger representation, and for the peak voxels of each finger.

We have adjusted our analysis, results, and figures in our main manuscript such that we now report % signal change rather than averaged z-standardised BOLD activity in the revised main manuscript.

– Prior results on SCI patients have to be described in more detail, also with respect to the used methods (TMS, fMRI).

We revised our Introduction accordingly.

– To target no 4 in the public review: Remove analyses.

We respectfully disagree with the reviewer on removing this analysis. We elaborated on the validity of our typicality analysis in response to public review comment 2.6.

– Conduct analyses on representation order and alignment, map size, and similarity and argue accordingly. Also, the conducted ANOVA is not mentioned in the Methods section, where I indeed wondered why a repeated measure ANOVA was conducted and not a mixed ANOVA with the factor "group". How do the authors want to detect group differences when "group" is not a factor in the ANOVA?

We have removed the sentence saying that ‘qualitatively the position, order of finger preference, and extent of the hand maps were generally similar between patients and controls’. We indeed do not support this claim with quantitative analysis. As per the suggestion of reviewer 1, we now state that despite all maps (except patient map 3) displaying aspects of characteristic finger maps, some finger representations were not visible in the thresholded patient and control maps.

As also indicated in our response to comment 2.11, to assess whether the maps of the SCI patients were aligned differently and/or shifted compared to the control participants, we extracted the geodesic distance per finger on a normalised cortical surface from each participant’s peak activated vertex to a reference vertex placed in the S1 foot cortex.

The ANOVA we conducted was an ANOVA with a within-participants factor for finger pair (3 levels: same, neighbouring and non-neighbouring finger pairs) and a between-participants factor for group (2 levels: controls and patients). We clarified this in the revised manuscript.

Revised text Methods:

“We tested whether the somatotopic relationship in the DOCs was different in controls and patients using a robust mixed ANOVA with a within-participants factor for finger pair (3 levels: same, neighbouring and non-neighbouring finger pairs) and a between-participants factor for group (2 levels: controls and patients).”

Revised text Results:

“Overall, split-half consistency was not significantly different between patients and controls, as tested using a robust mixed ANOVA (see Figure 2C; F_(1,20.32) = 0.51, p = 0.48).”

– Methods. It is not clear to me how the mean r was calculated. From what I understand, the authors use the higher r-value as a winner-takes-it-all approach to say which finger wins over the other fingers. When I understand correctly, no statistical threshold is applied here. Therefore, am I correct in assuming that a non-thresholded r map was then transferred to FDR correction?

We thank the reviewer for pointing out the lack of clarity. After calculating the r-values using the cross-correlation approach, the r-values were normalized using a Fisher r-to-z transformation. Following this, we used a winner-take-all approach to assign each voxel to one finger/lag exclusively based on the maximum z-value. We then calculated the threshold using the FDR q < 0.05 criterion based on winner-take-all finger/lag z-valued maps in native space (3D) and applied this threshold to the winner-take-all maps on the surface. We have clarified this in the Methods.

Revised text Methods:

“This resulted in 25 r-values per voxel per run that were normalised using a Fisher r-to-z transformation. […] Thresholding was applied to the winner-take-all finger-specific maps and lag-specific maps on the cortical surface using a false discovery criterion q < 0.05 based on the native (3D) values.”

References:

Adams RA, Shipp S, Friston KJ. 2013. Predictions not commands: Active inference in the motor system. Brain Struct Funct. doi:10.1007/s00429-012-0475-5

Akselrod M, Martuzzi R, Serino A, van der Zwaag W, Gassert R, Blanke O. 2017. 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 159:473–487. doi:10.1016/j.neuroimage.2017.06.021

Armenta Salas M, Bashford L, Kellis S, Jafari M, Jo H, Kramer D, Shanfield K, Pejsa K, Lee B, Liu CY, Andersen RA. 2018. Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation. eLife 7:1–11. doi:10.7554/eLife.32904

Berlot E, Prichard G, O’Reilly J, Ejaz N, Diedrichsen J. 2019. Ipsilateral finger representations in the sensorimotor cortex are driven by active movement processes, not passive sensory input. J Neurophysiol 121:418–426. doi:10.1152/jn.00439.2018

Besle J, Sánchez-Panchuelo R-M, Bowtell R, Francis S, Schluppeck D. 2013. Single-subject fMRI mapping at 7 T of the representation of fingertips in S1: a comparison of event-related and phase-encoding designs. J Neurophysiol 109:2293–305. doi:10.1152/jn.00499.2012

Bruurmijn MLCM, Pereboom IPL, Vansteensel MJ, Raemaekers MAH, Ramsey NF. 2017. Preservation of hand movement representation in the sensorimotor areas of amputees. Brain 140:3166–3178. doi:10.1093/brain/awx274

Burman DD, Lie-Nemeth T, Brandfonbrener AG, Parisi T, Meyer JR. 2009. Altered finger representations in sensorimotor cortex of musicians with focal dystonia: Precentral cortex. Brain Imaging Behav. doi:10.1007/s11682-008-9046-z

Chand P, Jain N. 2015. Intracortical and thalamocortical connections of the hand and face representations in somatosensory area 3b of macaque monkeys and effects of chronic spinal cord injuries. J Neurosci 35:13475–13486. doi:10.1523/JNEUROSCI.2069-15.2015

Chen LM, Qi H-X, Kaas JH. 2012. Dynamic Reorganization of Digit Representations in Somatosensory Cortex of Nonhuman Primates after Spinal Cord Injury. J Neurosci 32:14649–14663. doi:10.1523/JNEUROSCI.1841-12.2012

Cramer SC, Lastra L, Lacourse MG, Cohen MJ. 2005. Brain motor system function after chronic, complete spinal cord injury. Brain 128:2941–2950. doi:10.1093/brain/awh648

Da Costa S, Saenz M, Clarke S, van der Zwaag W. 2014. Tonotopic Gradients in Human Primary Auditory Cortex: Concurring Evidence From High-Resolution 7 T and 3 T fMRI. Brain Topogr 28:66–69. doi:10.1007/s10548-014-0388-0

Da Rocha Amaral S, Sanchez Panchuelo RM, Francis S. 2020. A Data-Driven Multi-scale Technique for fMRI Mapping of the Human Somatosensory Cortex. Brain Topogr 33:22–36. doi:10.1007/s10548-019-00728-6

Delhaye BP, Long KH, Bensmaia SJ. 2019. Neural basis of touch and proprioception in primate cortex. Compr Physiol 8:1575–1602. doi:10.1002/cphy.c170033

Dempsey-Jones H, Wesselink DB, Friedman J, Makin TR. 2019. Organized Toe Maps in Extreme Foot Users. Cell Rep 28:2748-2756.e4. doi:10.1016/j.celrep.2019.08.027

Deyoe EA, Carman GJ, Bandettini P, Glickman S, Wieser J, Cox R, Miller D, Neitz J. 1996. Mapping striate and extrastriate visual areas in human cerebral cortex. Proc Natl Acad Sci U S A 93:2382–2386. doi:10.1073/pnas.93.6.2382

Ejaz N, Hamada M, Diedrichsen J. 2015. Hand use predicts the structure of representations in sensorimotor cortex. Nat Neurosci 18:1034–1040.

Ejaz N, Sadnicka A, Wiestler T, Butler K, Edwards M, Diedrichsen J. 2016. Finger representations in sensorimotor cortex are not disrupted in musicians’ dystoniaSociety for Neuroscience Annual Meeting, San Diego, USA.

Engel SA, Glover GG, Wandell BA. 1997. Retintopic organization in human visual cortex and the spatial precision of functional MRI. Cereb Cortex 7:181–192. doi:10.1093/cercor/7.2.181

Fassett HJ, Turco C V., El-Sayes J, Nelson AJ. 2018. Alterations in motor cortical representation of muscles following incomplete spinal cord injury in humans. Brain Sci. doi:10.3390/brainsci8120225

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 V. 2020. Intracortical Microstimulation Elicits Human Fingertip Sensations. medRxiv 2020.05.29.20117374.

Flesher SN, Collinger JL, Foldes ST, Weiss JM, Downey JE, Tyler-Kabara EC, Bensmaia SJ, Schwartz AB, Boninger ML, Gaunt RA. 2016. Intracortical microstimulation of human somatosensory cortex. Sci Transl Medicne 1–11. doi:10.1126/scitranslmed.aaf8083

Florence SL. 1998. Large-Scale Sprouting of Cortical Connections After Peripheral Injury in Adult Macaque Monkeys. Science (80- ) 282:1117–1121. doi:10.1126/science.282.5391.1117

Freund P, Rothwell J, Craggs M, Thompson AJ, Bestmann S. 2011a. Corticomotor representation to a human forearm muscle changes following cervical spinal cord injury. Eur J Neurosci 34:1839–1846. doi:10.1111/j.1460-9568.2011.07895.x

Freund P, Schmidlin E, Wannier T, Bloch J, Mir A, Schwab ME, Rouiller EM. 2006. Nogo-A-specific antibody treatment enhances sprouting and functional recovery after cervical lesion in adult primates. Nat Med. doi:10.1038/nm1436

Freund P, Weiskopf N, Ward NS, Hutton C, Gall A, Ciccarelli O, Craggs M, Friston K, Thompson AJ. 2011b. Disability, atrophy and cortical reorganization following spinal cord injury. Brain 134:1610–1622. doi:10.1093/brain/awr093

Halder P, Kambi N, Chand P, Jain N. 2018. Altered Expression of Reorganized Inputs as They Ascend From the Cuneate Nucleus to Cortical Area 3b in Monkeys With Long-Term Spinal Cord Injuries. Cereb Cortex 28:3922–3938. doi:10.1093/cercor/bhx256

Henderson LA, Gustin SM, Macey PM, Wrigley PJ, Siddall PJ. 2011. Functional reorganization of the brain in humans following spinal cord injury: Evidence for underlying changes in cortical anatomy. J Neurosci 31:2630–2637. doi:10.1523/JNEUROSCI.2717-10.2011

Hotz-Boendermaker S, Funk M, Summers P, Brugger P, Hepp-Reymond MC, Curt A, Kollias SS. 2008. Preservation of motor programs in paraplegics as demonstrated by attempted and imagined foot movements. Neuroimage 39:383–394. doi:10.1016/j.neuroimage.2007.07.065

Huber E, Lachappelle P, Sutter R, Curt A, Freund P. 2017. Are midsagittal tissue bridges predictive of outcome after cervical spinal cord injury? Ann Neurol 81:740–748. doi:10.1002/ana.24932

Jain N, Qi H-X, Collins CE, Kaas JH. 2008. Large-scale reorganization in the somatosensory cortex and thalamus after sensory loss in macaque monkeys. J Neurosci 28:11042–11060. doi:10.1523/JNEUROSCI.2334-08.2008

Jutzeler CR, Freund P, Huber E, Curt A, Kramer JLK. 2015. Neuropathic pain and functional reorganization in the primary sensorimotor cortex after spinal cord injury. J Pain 16:1256–1267. doi:10.1016/j.jpain.2015.08.008

Kambi N, Halder P, Rajan R, Arora V, Chand P, Arora M, Jain N. 2014. Large-scale reorganization of the somatosensory cortex following spinal cord injuries is due to brainstem plasticity. Nat Commun 5:3602. doi:10.1038/ncomms4602

Kieliba P, Clode D, Maimon-mor RO, Makin TR. 2021. Robotic hand augmentation drives changes in neural body representation. Sci Robot 6:1–14. doi:10.1126/scirobotics.abd7935

Kikkert S, Kolasinski J, Jbabdi S, Tracey I, Beckmann CF, Johansen-Berg H, Makin TR. 2016. Revealing the neural fingerprints of a missing hand. eLife 5:e15292. doi:10.7554/eLife.15292

Kokotilo K, Eng J, Curt A. 2009. Reorganization and preservation of motor control of the brain in spinal cord injury: a systematic review. J Neurotrauma 26:2113–2126. doi:10.1089/neu.2008.0688.Reorganization

Kokotilo KJ, Eng JJ, Curt A. 2009. Reorganization and preservation of motor control of the brain in spinal cord injury: A systematic review. J Neurotrauma 26:2113–2126. doi:10.1089/neu.2008.0688

Kolasinski J., Makin TR, Jbabdi S, Clare S, Stagg CJ, Johansen-Berg H. 2016. Investigating the stability of fine-grain digit somatotopy in individual human participants. J Neurosci 36:1113–1127.

Kolasinski James, Makin TR, Logan JP, Jbabdi S, Clare S, Stagg CJ, Johansen-Berg H. 2016. Perceptually relevant remapping of human somatotopy in 24 hours. eLife 5:1–15. doi:10.7554/eLife.17280

Kriegeskorte N, Mur M, Bandettini P. 2008. Representational similarity analysis – connecting the branches of systems neuroscience. Front Syst Neurosci 2:1–28. doi:10.3389/neuro.06.004.2008

Kuehn E, Haggard P, Villringer A, Pleger B, Sereno MI. 2018. Visually-driven maps in area 3b. J Neurosci 38:0491–17. doi:10.1523/JNEUROSCI.0491-17.2017

Levy WJ, Amassian VE, Traad M, Cadwell J. 1990. Focal magnetic coil stimulation reveals motor cortical system reorganized in humans after traumatic quadriplegia. Brain Res. doi:10.1016/0006-8993(90)90738-W

London BM, Miller LE. 2013. Responses of somatosensory area 2 neurons to actively and passively generated limb movements. J Neurophysiol 109:1505–13. doi:10.1152/jn.00372.2012

Mancini F, Haggard P, Iannetti GD, Longo MR, Sereno MI. 2012. Fine-grained nociceptive maps in primary somatosensory cortex. J Neurosci 32:17155–17162. doi:10.1523/JNEUROSCI.3059-12.2012

Nili H, Wingfield C, Walther A, Su L, Marslen-Wilson W, Kriegeskorte N. 2014. A Toolbox for Representational Similarity Analysis. PLoS Comput Biol 10. doi:10.1371/journal.pcbi.1003553

Pfyffer D, Huber E, Sutter R, Curt A, Freund P. 2019. Tissue bridges predict recovery after traumatic and ischemic thoracic spinal cord injury. Neurology 93:e1550–e1560. doi:10.1212/WNL.0000000000008318

Pfyffer D, Vallotton K, Curt A, Freund P. 2021. Predictive Value of Midsagittal Tissue Bridges on Functional Recovery After Spinal Cord Injury. Neurorehabil Neural Repair 35:33–43. doi:10.1177/1545968320971787

Puckett AM, Bollmann S, Barth M, Cunnington R. 2017. Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI. Neuroimage 161:179–187. doi:10.1016/j.neuroimage.2017.08.014

Puckett AM, Bollmann S, Junday K, Barth M, Cunnington R. 2020. Bayesian population receptive field modeling in human somatosensory cortex. Neuroimage 208:116465. doi:10.1016/j.neuroimage.2019.116465

Sanders Z-B, Wesselink DB, Dempsey-Jones H, Makin TR. 2019. Similar somatotopy for active and passive digit representation in primary somatosensory cortex. bioRxiv 1–36. doi:10.1101/754648

Sereno MI, Dale AM, Reppas JB, Kwong KK, Belliveau JW, Brady TJ, Rosen BR, Tootell RBH. 1995. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science (80- ) 268:889–893. doi:10.1126/science.7754376

Solstrand Dahlberg L, Becerra L, Borsook D, Linnman C. 2018. Brain changes after spinal cord injury, a quantitative meta-analysis and review. Neurosci Biobehav Rev 90:272–293. doi:10.1016/j.neubiorev.2018.04.018

Streletz LJ, Belevich JKS, Jones SM, Bhushan A, Shah SH, Herbison GJ. 1995. Transcranial magnetic stimulation: Cortical motor maps in acute spinal cord injury. Brain Topogr. doi:10.1007/BF01202383

Talavage TM, Sereno MI, Melcher JR, Ledden PJ, Rosen BR, Dale AM. 2004. Tonotopic Organization in Human Auditory Cortex Revealed by Progressions of Frequency Sensitivity. J Neurophysiol 91:1282–1296. doi:10.1152/jn.01125.2002

Taub E, Elbert T, Candia V, Rockstroh B, Rau H, Pantev C, Altenmüller E, Sterr A. 1998. Alteration of digital representations in somatosensory cortex in focal hand dystonia. Neuroreport.

Topka H, Cohen LG, Cole RA, Hallett M. 1991. Reorganization of corticospinal pathways following spinal cord injury. Neurology. doi:10.1212/wnl.41.8.1276

Urbin MA, Royston DA, Weber DJ, Boninger ML, Collinger JL. 2019. What is the functional relevance of reorganization in primary motor cortex after spinal cord injury? Neurobiol Dis 121:286–295. doi:10.1016/j.nbd.2018.09.009

Vallotton K, Huber E, Sutter R, Curt A, Hupp M, Freund P. 2019. Width and neurophysiologic properties of tissue bridges predict recovery after cervical injury. Neurology 92:E2793–E2802. doi:10.1212/WNL.0000000000007642

Wesselink DB, Maimon-Mor R. 2017. Github.

Wesselink DB, van den Heiligenberg FM, Ejaz N, Dempsey-Jones H, Cardinali L, Tarall-Jozwiak A, Diedrichsen J, Makin TR. 2019. Obtaining and maintaining cortical hand representation as evidenced from acquired and congenital handlessness. eLife 8:1–19. doi:10.7554/eLife.37227

Wrigley PJ, Press SR, Gustin SM, Macefield VG, Gandevia SC, Cousins MJ, Middleton JW, Henderson LA, Siddall PJ. 2009. Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury. Pain 141:52–59. doi:10.1016/j.pain.2008.10.007

Wrigley PJ, Siddall PJ, Gustin SM. 2018. New evidence for preserved somatosensory pathways in complete spinal cord injury: A fMRI study. Hum Brain Mapp 39:588–598. doi:10.1002/hbm.23868

Zeharia N, Hertz U, Flash T, Amedi A. 2015. New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity. J Neurosci 35:2845–2859. doi:10.1523/Jneurosci.4246-14.2015

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

The manuscript has been substantially improved and there remain only some small issues that need to be addressed as described below by Reviewers #1 and #2. Please play particular attention to (1) ensuring the abstract is clear and (2) that the finger specific RSA analysis is included in the supplement. We will not send this out to external review again.

Reviewer #1 (Recommendations for the authors):

I appreciate the thorough response from the authors and believe that the revised manuscript presents a much more complete and balanced view. My only remaining comment is that although I find the RSA analysis to be appropriate here, I disagree with the authors' claims that it has become the "most common" / "gold standard" approach to investigating inter-finger overlap / somatotopy. And I'm not confident that you'd find consensus for this position among those in the field. As such, consider walking this claim back a bit.

Reviewer #2 (Recommendations for the authors):

Overall

I thank the authors for performing additional analyses that improved the quality of manuscript and significantly strengthened the claims they made.

Concept

I thank the authors for adding more background information on nonhuman primates, behavioral and fMRI human studies to argue what (or what not) to expect in their study results. Nevertheless, I still think that the major question posed in the abstract is still not accurate. They write in the abstract:

It is not clear "whether somatotopic representations can be preserved despite alterations in net activity". This is really confusing because in the manuscript, the authors do not show alterations in net activity. In addition, in response to both reviewer 2 and 3, the authors removed the formulation "preserved" from the discussion. Please also remove this from the abstract (at present it is still used 2 times). In addition, as argued by reviewer 1, if attention is one of the mechanisms that triggers the activity, it is not clear whether attention-related net activity should be higher or lower. I would therefore suggest to be precise also in the abstract and write that they investigate "whether somatotopic representations can be activated topographically despite reduced or absent afferent input" (or similar).

Analyses/Results

I thank the authors for conducting an ANOVA including the factors group and finger pair for the RSA, and for conducting finger-specific analyses using percent signal change. It is interesting to see that there is no interaction between group and finger pair, and that individual fingers do not differ in signal change. The authors then say that they conducted individual finger analyses where the BF revealed inconclusive evidence for the RSA analyses. Later in the response letter, they say that those analyses have been included as figure supplement into the manuscript: however, within the material downloaded, I could not find these figures. If the finger pair-specific RSA values are therefore not yet included in the supplemental material, I would suggest adding those because 1. Prior studies hint towards finger-specific differences and researchers would like to see what this study revealed in this respect, 2. The amplitude analyses provide a hint towards differences for D4 that would be interesting to inspect for the RSA results too.

It is good to see that the typicality results did not change when using data of the control group as a basis. This makes this analysis much more convincing. Given the authors argue that it would be good to always use the same data set to compare patients against, in my view, it would be of great benefit for the community if the data and results could be made publicly available (in particular the data taken from the Wesselink study) so that potentially other researchers can compare their own results against those.

Specifically:

– We removed our statement about RSA being the golden standard to investigate inter-finger overlap, as per the suggestion of Reviewer 1.

Revised text Methods:

“We estimated inter-finger overlap using RSA. Note that it is also possible to estimate somatotopic overlap from travelling wave data using an iterated Multigrid Priors (iMGP) method and population receptive field modelling (Da Rocha Amaral et al., 2020; Puckett et al., 2020).”

– We changed the terminology in our abstract according as per the suggestion of Reviewer 2.

Revised text Abstract:

“However, little is known about whether somatotopically-specific representations can be activated despite reduced or absent afferent hand inputs. […] We found that somatotopic hand representations can be activated through attempted finger movements in absence of sensory and motor hand functioning, and no spared spinal tissue bridges.

– We added a figure supplement to visualise inter-finger distances across finger pairs for controls and SCI patients, as per the suggestion of Reviewer 2.

Revised text Results:

“We then tested whether the inter-finger distances were different across finger pairs between controls and SCI patients using a robust mixed ANOVA with a within-participants factor for finger pair (10 levels) and a between-participants factor for group (2 levels: controls and patients; Figure 3—figure supplement 2).”

– The canonical RDM used for analysis has already been made publicly available on https://osf.io/e8u95/. In the revised manuscript we refer readers to the publicly available congenital amputees dataset (Wesselink et al., 2019) in the Methods section, according to the suggestion of Reviewer 2.

Revised text Methods:

“Controls’ and SCI patients’ typicality scores were compared to those of a group of individuals with congenital hand malformation (n = 13), hereafter one-handers, obtained in another study (data publicly available on https://osf.io/gmvua/; Wesselink et al., 2019).”

Author details

1. Sanne Kikkert

   1. Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
   2. Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Investigation, Project administration, Software, Supervision, Visualization, Writing - original draft, Writing – review and editing

   For correspondence

   sanne.kikkert@hest.ethz.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9952-4864

2. Dario Pfyffer

   Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland

   Contribution

   Conceptualization, Formal analysis, Investigation, Software, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2406-9251

3. Michaela Verling

   Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland

   Contribution

   Investigation, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

4. Patrick Freund

   1. Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
   2. Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
   3. Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom
   4. Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

   Contribution

   Conceptualization, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4851-2246

5. Nicole Wenderoth

   Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland

   Contribution

   Conceptualization, Funding acquisition, Resources, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3246-9386

• 677

  Page views

• 81

  Downloads

• 9

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.