A fundamental organising principle in the primary somatosensory cortex (SI) is somatotopic mapping, where adjacent body parts are represented more proximally on the cortical sheet than those further apart (Penfield and Rasmussen, 1950). In the cortical hand area, this topographic organising principle results in a detailed digit map (Kaas et al., 1979; Penfield and Rasmussen, 1950), where neighbouring digits on the hand are represented closer together on the neocortex than non-neighbouring digits, as can be shown with functional MRI (fMRI) (Kolasinski et al., 2016). More generally, cortical activity patterns for neighbouring fingers overlap more – and are therefore more similar – than non-neighbouring fingers, independent of the exact spatial arrangement of these patterns (Ejaz et al., 2015). The representational structure (i.e. the relative dissimilarity of activity patterns for different movements) is thought to reflect the natural statistics of hand use over one’s life course (Graziano and Aflalo, 2007; Overduin et al., 2012): Concurrent inputs to neighbouring digits will increase representational similarity (Wang et al., 1995), while greater individuation of inputs will induce greater representational dissimilarity (Ejaz et al., 2015). Some have even suggested that alterations of these inter-digit representational boundaries after the hand map has been formed, for example due to digit overuse, can disrupt (musician’s dystonia [Elbert et al., 1998], but see Ejaz et al., 2016) or improve perception and action (tactile discrimination [Recanzone et al., 1992; Pleger et al., 2003]).

We (Kikkert et al., 2016) and others (Flesher et al., 2016; Bruurmijn et al., 2017) recently challenged the view that structured input from the periphery is required for preserving sensorimotor hand representation (Dempsey-Jones et al., 2016; see also Davis et al., 1998, Mercier et al., 2006, Garbarini et al., 2018 for related brain stimulation and behavioural findings). We took advantage of a well-documented phenomenon whereby some amputees report being able to volitionally move their phantom hand, resulting in kinaesthetic phantom sensations (Henderson and Smyth, 1948). Phantom limb movements have been shown to elicit both central and peripheral motor signals that are different from those found during movement imagery (Reilly et al., 2006; Raffin et al., 2012a; Raffin et al., 2012b; Makin et al., 2013b). Using 7T imaging we explored whether three amputees experiencing exceptionally vivid phantom sensations maintained the canonical hand representation, exemplified by somatotopically organised representation of individual digits. We found that although digit selectivity was reduced, digit order and the extent of the missing hand maps in SI were similar to what is observed in controls.

Our previous findings demonstrate the stability of SI hand organisation despite decades of amputation. It remains unknown, however, whether hand representation after amputation reflects phantom sensations, and as such only persists in individuals with highly vivid phantom sensations. Here, we asked whether persistent representation of a missing hand reflects an organisational principle in the sensorimotor cortex, and thus will even be observed in amputees with little phantom sensations. To address this question, we measured cortical hand representation in 18 acquired amputees with varying vividness of their phantom sensations (hereafter amputees). To test the idea that the development of a hand representation requires sensory experience, we also tested 13 individuals missing one hand from birth (due to congenital amelia; hereafter congenital one-handers). All participants underwent fMRI while performing a visually cued motor task involving individual digit movements (of both the missing hand and the intact hand). Activity patterns in the missing hand of SI and M1 were analysed using representational similarity analysis (Walther et al., 2016; Diedrichsen et al., 2016). We hypothesised that normal peripheral input is necessary to establish normal sensory hand representation, but not to maintain it.

Here, we demonstrated long-term stability of SI hand representation in a group of acquired amputees with diverse phantom sensations, including those experiencing limited phantom sensations. Using RSA, we find that amputees show individuated digit representation for their missing hand, as exemplified by significantly greater inter-digit dissimilarity values in amputees versus congenital one-handers. The inter-digit pattern comprising the missing hand representation was typical to SI hand representation in amputees and was not significantly different from controls (as supported by a Bayesian analysis). Importantly, by studying individuals with a varying range of phantom sensations, we were able to confirm stable hand representation even after phantom sensations have diminished. This result confirms the persistence of hand representation as a general principle in amputees, contrary to recent reports (Serino et al., 2017). Using the same task, we were unable to identify similar digit representation for the missing hand of congenital one-handers, demonstrated by significantly reduced pattern typicality compared to amputees (and even in comparison to those few amputees with little phantom sensations), as well as controls. This result confirms that the persistent hand representation observed in amputees does not reflect mere cognitive task demands (e.g. visual feedback, Kuehn et al., 2018; or attention, Puckett et al., 2017).

We also explored whether we could activate the representation of the missing hand indirectly by movements of the fingers of the intact hand. Previous studies in two-handers have demonstrated that contralateral and ipsilateral hand movements produce identical representational patterns (Diedrichsen et al., 2018). Since this ipsilateral representation is completely overwritten by the contralateral hand if the two hands are engaged in dissociated movements (Diedrichsen et al., 2013, Exp. 2), it has been proposed that the ipsilateral hand reactivates the cortical resources associated with the contralateral hand. Based on this evidence, the ipsilateral digit representation can serve as an indirect measure of the contralateral hand representation. This discovery provides us with a unique and novel opportunity to interrogate the information content underlying the ‘deprived’ hand cortex despite the physical absence of the hand. This approach provided converging evidence, but using different task demands, for similar (missing) hand representation for amputees and controls, but not for congenital one-handers. It might be worth considering whether congenital one-hander’s deprived cortex could have developed separate representations for both the contralateral (missing) and ipsilateral (intact) hand, which are uncorrelated due to anatomical or behavioural differences from two-handers. If this were possible, we would predict maintained, or even stronger, ipsilateral representation of the intact hand. Yet, our data does not reflect this hypothesis. Moreover, poor ipsilateral representation in the deprived cortex does not seem to stem from reduced inter-hemispheric connectivity, which appears to be functionally and structurally preserved in congenital one-handers, depending on lateralisation strategies in daily behaviour (Hahamy et al., 2015; Hahamy et al., 2017; Makin et al., 2013a). Finally, it is still possible that rudimentary missing hand representation, for example determined by genetic factors (Miyashita-Lin et al., 1999; Rubenstein et al., 1999), has originally formed in congenital one-handers but later diminished due to lack of consistent sensorimotor input. Bearing this caveat in mind, our findings suggest that early-life experience is potentially necessary to create typical functional sensory organisation, but not to maintain it.

It has previously been shown that restored peripheral input, for example via hand transplantation (Frey et al., 2008) or targeted reinnervation (Serino et al., 2017) can reinstate sensorimotor hand representation, indicating that the canonical hand representation is, to an extent, immutable to change. Moreover, we reported that the SI hand map can persist independently of the original peripheral input, as observed in a patient sustaining a brachial plexus avulsion injury, abolishing communication between the periphery and the central nervous system (Kikkert et al., 2016). Similarly, in the current study amputees showed, on average, persistent SI representation despite suffering diverse nerve injuries spanned varying degrees of amputation (Table 1). It is therefore necessary to consider alternative inputs that might contribute to the stability of the missing hand map in amputees. Considering that our task required active phantom movements, it is likely that the SI representation pattern is driven by motor efferent inputs. Indeed, while motor signals can no longer reach their final output muscle terminal, the motor cortex in amputees remains functional (Raffin et al., 2012a; see Kokotilo et al., 2009 for similar results in spinal cord injury patients). When a motor command is sent out (e.g. in the form of an attempted hand movement), efference signals are thought to reach SI and generate corollary discharge, suggested to resemble the expected sensory feedback activity pattern, resulting from the movement (London and Miller, 2013; Adams et al., 2013). Since congenital one-handers have never operated a hand, it is likely that this sensorimotor predictive coding architecture never formed in the first place, explaining the lack of inter-digit dissimilarity found in the present study.

It is important to consider how the finding of robust persistence of hand representation, despite the physical absence of a hand, conceptually aligns with other reports of brain reorganisation. Since the pioneering work of Hubel and Wiesel, demonstrating that input loss to visual cortex in early development leads to profound physiological changes (Wiesel and Hubel, 1965b; Hubel and Wiesel, 1965; Wiesel and Hubel, 1965a), it has long been established that sensory deprivation causes cortical reorganisation. Later seminal electrophysiological studies in monkeys further demonstrated that deprivation-driven reorganisation following peripheral input-loss also occurs in adults (Kaas et al., 1983). For example, following peripheral deafferentation of the hand and arm, the missing hand SI area becomes responsive to touch applied to the monkey’s lower face (Pons et al., 1991), likely due to subcortical re-routing of inputs (Kambi et al., 2014; Liao et al., 2016). Recent research in humans indicates extensive reorganisation of multiple body-part representations onto the deprived hand area of congenital one-handers (Hahamy et al., 2017; Striem-Amit et al., 2018; Stoeckel et al., 2009). In amputees sustaining input loss in adulthood, original reports emphasised facial remapping in SI, akin to the reorganisation observed in monkeys (Flor et al., 1995), as a driving mechanism for phantom limb pain (maladaptive plasticity; Flor et al., 2006). Later research challenged the notion that the deprived hand area gets taken over by facial inputs (Makin et al., 2013b; Makin et al., 2015; Raffin et al., 2016) and instead emphasised increased representation of the intact hand in the missing hand cortex as a potential neural correlate of adaptive plasticity (Makin et al., 2013a; Philip and Frey, 2014; see further discussion below). More recently, we have suggested that functional reorganisation is more limited than originally considered (Makin and Bensmaia, 2017). Regardless of the ongoing debate over the functional role of SI reorganisation in the adult (Andoh et al., 2018; Kuner and Flor, 2017) and developing brain (Hahamy et al., 2017; Striem-Amit et al., 2018), common to all these previous studies of reorganisation is that to activate the deprived cortex researchers studied representations of the spared body parts (e.g. the face or the intact hand). While this approach is suitable for documenting cortical remapping, it leaves unexplored the possibility that the original functional organisation of the now-deprived area may be preserved, though latent. We propose that reorganisation in the missing hand cortex does not necessarily abolish the original functional layout in sensory cortex. For example, persistent representation, in the form of efferent cortico-cortical input would engage a separate cortical layer (Felleman and Van Essen, 1991; Adams et al., 2013) than brainstem and thalamic facial inputs to the deprived cortex (Kambi et al., 2014). It still remains to be determined whether these two forms of persistent representation and reorganisation are functionally orthogonal, or interactive (Andoh et al., 2018).

As mentioned above, the missing hand cortex in amputees, but not in congenital one-handers, has been previously shown to respond to inputs from the intact hand (Bogdanov et al., 2012; Makin et al., 2013a; Hahamy et al., 2017; Philip and Frey, 2014), presumably through functional reorganisation. Here, we used RSA to dissect the information content underlying ipsilateral activity of the intact hand. We find that amputees, but not congenital one-handers, showed similar measures of dissimilarity and typicality as controls. However, the fact that ipsilateral dissimilarity was not significantly greater in amputees than in controls is inconsistent with the interpretation of increased intact hand activity as a neural correlate of adaptive reorganisation (Makin et al., 2013a). Regardless, the existence of ipsilateral digit-specific organisation in the missing hand cortex of amputees might provide an alterantive mechanism for the preservation of the missing hand digit maps. While we previously showed that the phantom hand map is activated by phantom hand movements independently of the intact hand (Kikkert et al., 2016; Philip and Frey, 2014), it is still possible that structured inputs from the intact hand (via ipsilateral pathways) sustains the missing hand map, despite the loss of the original peripheral inputs.

To conclude, here we show that once sensorimotor hand-representation is formed, it is generally immutable to change: We identified stable hand representation in amputees’ sensorimotor cortex using representational similarity analysis, despite years (and even decades) of amputation and irrespective of their phantom sensations vividness. In contrast, individuals born with a missing hand (congenital one-handers) did not show normal representation of their nonexisting hand. We therefore suggest that consistent sensory representation despite input loss may be a common organising principle (Striem-Amit et al., 2015; Collignon et al., 2013; Baseler et al., 2011). How can our findings of persistent representation, despite massive and long-lasting input change, be resolved with multiple observations of updated hand representation due to altered experience (e.g. due to nerve/digit deafferentation [Merzenich et al., 1983; Merzenich et al., 1984], increased usage [Jenkins et al., 1990], syndactyly [Allard et al., 1991; Wang et al., 1995], or mobile phone usage [Gindrat et al., 2015])? Here we show that amputees with greater phantom kinaesthetic sensations better retained their missing hand representation. In light of this, we suggest that daily life experience could shape the fine-grained aspects of hand representation, but the large-scale functional organisation of the hand area is fundamentally stable.

The data analysed in this study has been shared as a major dataset.

1. 1. Daan B Wesselink
   2. Fiona MZ van den Heiligenberg
   3. Tamar R Makin

   (2019) Open Science Framework

   ID gmvua. Effects of arm amputation on motor control.

   https://osf.io/gmvua/

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

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

   Brain Structure and Function 218:611–643.

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

   • PubMed
   • Google Scholar
2. 1. Allard T
   2. Clark SA
   3. Jenkins WM
   4. Merzenich MM

   (1991) Reorganization of somatosensory area 3b representations in adult owl monkeys after digital syndactyly

   Journal of Neurophysiology 66:1048–1058.

   https://doi.org/10.1152/jn.1991.66.3.1048

   • PubMed
   • Google Scholar
3. 1. Andoh J
   2. Milde C
   3. Tsao JW
   4. Flor H

   (2018) Cortical plasticity as a basis of phantom limb pain: fact or fiction?

   Neuroscience 387:85–91.

   https://doi.org/10.1016/j.neuroscience.2017.11.015

   • PubMed
   • Google Scholar
4. 1. Baseler HA
   2. Gouws A
   3. Haak KV
   4. Racey C
   5. Crossland MD
   6. Tufail A
   7. Rubin GS
   8. Cornelissen FW
   9. Morland AB

   (2011) Large-scale remapping of visual cortex is absent in adult humans with macular degeneration

   Nature Neuroscience 14:649–655.

   https://doi.org/10.1038/nn.2793

   • PubMed
   • Google Scholar
5. 1. Beauchamp MS
   2. Laconte S
   3. Yasar N

   (2009) Distributed representation of single touches in somatosensory and visual cortex

   Human Brain Mapping 30:3163–3171.

   https://doi.org/10.1002/hbm.20735

   • PubMed
   • Google Scholar
6. 1. Berlot E
   2. Prichard G
   3. O'Reilly J
   4. Naveed E
   5. Diedrichsen J

   (2018) Ipsilateral finger representations in the sensorimotor cortex are driven by active movement processes, not passive sensory input

   Journal of Neurophysiology 9:.

   https://doi.org/10.1152/jn.00439.2018

   • Google Scholar
7. 1. Bogdanov S
   2. Smith J
   3. Frey SH

   (2012) Former hand territory activity increases after amputation during intact hand movements, but is unaffected by illusory visual feedback

   Neurorehabilitation and Neural Repair 26:604–615.

   https://doi.org/10.1177/1545968311429687

   • PubMed
   • Google Scholar
8. Book

   1. Borg I
   2. Groenen PJF

   (2005) Modern Multidimensional Scaling: Theory and Applications

   New York, United States: Springer-Verlag .

   https://doi.org/10.1007/0-387-28981-X

   • Google Scholar
9. 1. Bruurmijn M
   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. Collignon O
    2. Dormal G
    3. Albouy G
    4. Vandewalle G
    5. Voss P
    6. Phillips C
    7. Lepore F

    (2013) Impact of blindness onset on the functional organization and the connectivity of the occipital cortex

    Brain 136:2769–2783.

    https://doi.org/10.1093/brain/awt176

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

    (1999) Cortical surface-based analysis. I. segmentation and surface reconstruction

    NeuroImage 9:179–194.

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

    • PubMed
    • Google Scholar
12. 1. Davis KD
    2. Kiss ZH
    3. Luo L
    4. Tasker RR
    5. Lozano AM
    6. Dostrovsky JO

    (1998) Phantom sensations generated by thalamic microstimulation

    Nature 391:385–387.

    https://doi.org/10.1038/34905

    • PubMed
    • Google Scholar
13. 1. Dempsey-Jones H
    2. Harrar V
    3. Oliver J
    4. Johansen-Berg H
    5. Spence C
    6. Makin TR

    (2016) Transfer of tactile perceptual learning to untrained neighboring fingers reflects natural use relationships

    Journal of Neurophysiology 115:1088–1097.

    https://doi.org/10.1152/jn.00181.2015

    • PubMed
    • Google Scholar
14. Preprint

    1. Diedrichsen J
    2. Provost S
    3. Zareamoghaddam H

    (2016) On the distribution of cross-validated mahalanobis distances

    arXiv.

    https://arxiv.org/abs/1607.01371

    • Google Scholar
15. 1. Diedrichsen J
    2. Shadmehr R

    (2005) Detecting and adjusting for artifacts in fMRI time series data

    NeuroImage 27:624–634.

    https://doi.org/10.1016/j.neuroimage.2005.04.039

    • PubMed
    • Google Scholar
16. 1. Diedrichsen J
    2. Wiestler T
    3. Krakauer JW

    (2013) Two distinct ipsilateral cortical representations for individuated finger movements

    Cerebral Cortex 23:1362–1377.

    https://doi.org/10.1093/cercor/bhs120

    • PubMed
    • Google Scholar
17. 1. Diedrichsen J
    2. Yokoi A
    3. Arbuckle SA

    (2018) Pattern component modeling: a flexible approach for understanding the representational structure of brain activity patterns

    NeuroImage 180:119–133.

    https://doi.org/10.1016/j.neuroimage.2017.08.051

    • PubMed
    • Google Scholar
18. 1. Dienes Z

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

    Frontiers in Psychology 5:781.

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

    • PubMed
    • Google Scholar
19. 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
20. 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 ́dystonia

    Society for Neuroscience Annual Meeting 2016:.

    https://doi.org/10.1038/srep37632

    • Google Scholar
21. 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
22. 1. Felleman DJ
    2. Van Essen DC

    (1991) Distributed hierarchical processing in the primate cerebral cortex

    Cerebral Cortex 1:1–47.

    https://doi.org/10.1093/cercor/1.1.1

    • PubMed
    • Google Scholar
23. 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
24. 1. Fischl B
    2. Rajendran N
    3. Busa E
    4. Augustinack J
    5. Hinds O
    6. Yeo BT
    7. Mohlberg H
    8. Amunts K
    9. Zilles K

    (2008) Cortical folding patterns and predicting cytoarchitecture

    Cerebral Cortex 18:1973–1980.

    https://doi.org/10.1093/cercor/bhm225

    • PubMed
    • Google Scholar
25. 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 8:361ra141.

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

    • PubMed
    • Google Scholar
26. 1. Flor H
    2. Elbert T
    3. Knecht S
    4. Wienbruch C
    5. Pantev C
    6. Birbaumer N
    7. Larbig W
    8. Taub E

    (1995) Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation

    Nature 375:482–484.

    https://doi.org/10.1038/375482a0

    • PubMed
    • Google Scholar
27. 1. Flor H
    2. Nikolajsen L
    3. Staehelin Jensen T

    (2006) Phantom limb pain: a case of maladaptive CNS plasticity?

    Nature Reviews Neuroscience 7:873–881.

    https://doi.org/10.1038/nrn1991

    • PubMed
    • Google Scholar
28. 1. Frey SH
    2. Bogdanov S
    3. Smith JC
    4. Watrous S
    5. Breidenbach WC

    (2008) Chronically deafferented sensory cortex recovers a grossly typical organization after allogenic hand transplantation

    Current Biology 18:1530–1534.

    https://doi.org/10.1016/j.cub.2008.08.051

    • PubMed
    • Google Scholar
29. 1. Garbarini F
    2. Bisio A
    3. Biggio M
    4. Pia L
    5. Bove M

    (2018) Motor sequence learning and intermanual transfer with a phantom limb

    Cortex 101:181–191.

    https://doi.org/10.1016/j.cortex.2018.01.011

    • PubMed
    • Google Scholar
30. 1. Gindrat AD
    2. Chytiris M
    3. Balerna M
    4. Rouiller EM
    5. Ghosh A

    (2015) Use-dependent cortical processing from fingertips in touchscreen phone users

    Current Biology 25:109–116.

    https://doi.org/10.1016/j.cub.2014.11.026

    • PubMed
    • Google Scholar
31. 1. Graziano MS
    2. Aflalo TN

    (2007) Mapping behavioral repertoire onto the cortex

    Neuron 56:239–251.

    https://doi.org/10.1016/j.neuron.2007.09.013

    • PubMed
    • Google Scholar
32. 1. Hahamy A
    2. Sotiropoulos SN
    3. Henderson Slater D
    4. Malach R
    5. Johansen-Berg H
    6. Makin TR

    (2015) Normalisation of brain connectivity through compensatory behaviour, despite congenital hand absence

    eLife 4:e04605.

    https://doi.org/10.7554/eLife.04605

    • Google Scholar
33. 1. Hahamy A
    2. Macdonald SN
    3. van den Heiligenberg F
    4. Kieliba P
    5. Emir U
    6. Malach R
    7. Johansen-Berg H
    8. Brugger P
    9. Culham JC
    10. Makin TR

    (2017) Representation of multiple body parts in the Missing-Hand territory of congenital One-Handers

    Current Biology 27:1350–1355.

    https://doi.org/10.1016/j.cub.2017.03.053

    • PubMed
    • Google Scholar
34. 1. Henderson WR
    2. Smyth GE

    (1948) Phantom limbs

    Journal of Neurology, Neurosurgery & Psychiatry 11:88–112.

    https://doi.org/10.1136/jnnp.11.2.88

    • Google Scholar
35. 1. Hubel DH
    2. Wiesel TN

    (1965) Binocular interaction in striate cortex of kittens reared with artificial squint

    Journal of Neurophysiology 28:1041–1059.

    https://doi.org/10.1152/jn.1965.28.6.1041

    • PubMed
    • Google Scholar
36. 1. Jenkins WM
    2. Merzenich MM
    3. Ochs MT
    4. Allard T
    5. Guíc-Robles E

    (1990) Functional reorganization of primary somatosensory cortex in adult owl monkeys after behaviorally controlled tactile stimulation

    Journal of Neurophysiology 63:82–104.

    https://doi.org/10.1152/jn.1990.63.1.82

    • PubMed
    • Google Scholar
37. 1. Jenkinson M
    2. Bannister P
    3. Brady M
    4. Smith S

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

    NeuroImage 17:825–841.

    https://doi.org/10.1006/nimg.2002.1132

    • PubMed
    • Google Scholar
38. 1. Jenkinson M
    2. Beckmann CF
    3. Behrens TE
    4. Woolrich MW
    5. Smith SM

    (2012) FSL

    NeuroImage 62:782–790.

    https://doi.org/10.1016/j.neuroimage.2011.09.015

    • PubMed
    • Google Scholar
39. 1. Kaas JH
    2. Nelson RJ
    3. Sur M
    4. Lin CS
    5. Merzenich MM

    (1979) Multiple representations of the body within the primary somatosensory cortex of primates

    Science 204:521–523.

    https://doi.org/10.1126/science.107591

    • PubMed
    • Google Scholar
40. 1. Kaas JH
    2. Merzenich MM
    3. Killackey HP

    (1983) The reorganization of somatosensory cortex following peripheral nerve damage in adult and developing mammals

    Annual Review of Neuroscience 6:325–356.

    https://doi.org/10.1146/annurev.ne.06.030183.001545

    • PubMed
    • Google Scholar
41. 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 5:1–10.

    https://doi.org/10.1038/ncomms4602

    • Google Scholar
42. 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
43. 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
44. 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
45. 1. Kolasinski J
    2. Makin TR
    3. Jbabdi S
    4. Clare S
    5. Stagg CJ
    6. Johansen-Berg H

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

    Journal of Neuroscience 36:1113–1127.

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

    • PubMed
    • Google Scholar
46. 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
47. 1. Kuner R
    2. Flor H

    (2017) Structural plasticity and reorganisation in chronic pain

    Nature Reviews Neuroscience 18:113.

    https://doi.org/10.1038/nrn.2017.5

    • PubMed
    • Google Scholar
48. 1. Liao CC
    2. Reed JL
    3. Kaas JH
    4. Qi HX

    (2016) Intracortical connections are altered after long-standing deprivation of dorsal column inputs in the hand region of area 3b in squirrel monkeys

    Journal of Comparative Neurology 524:1494–1526.

    https://doi.org/10.1002/cne.23921

    • PubMed
    • Google Scholar
49. 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
50. 1. Makin TR
    2. Cramer AO
    3. Scholz J
    4. Hahamy A
    5. Henderson Slater D
    6. Tracey I
    7. Johansen-Berg H

    (2013a) Deprivation-related and use-dependent plasticity go hand in hand

    eLife 2:e01273.

    https://doi.org/10.7554/eLife.01273

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

    (2013b) 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
52. 1. Makin TR
    2. Scholz J
    3. Henderson Slater D
    4. Johansen-Berg H
    5. Tracey I

    (2015) Reassessing cortical reorganization in the primary sensorimotor cortex following arm amputation

    Brain 138:2140–2146.

    https://doi.org/10.1093/brain/awv161

    • PubMed
    • Google Scholar
53. 1. Makin TR
    2. Bensmaia SJ

    (2017) Stability of sensory topographies in adult cortex

    Trends in Cognitive Sciences 21:195–204.

    https://doi.org/10.1016/j.tics.2017.01.002

    • PubMed
    • Google Scholar
54. 1. Mercier C
    2. Reilly KT
    3. Vargas CD
    4. Aballea A
    5. Sirigu A

    (2006) Mapping phantom movement representations in the motor cortex of amputees

    Brain 129:2202–2210.

    https://doi.org/10.1093/brain/awl180

    • PubMed
    • Google Scholar
55. 1. Merzenich MM
    2. Kaas JH
    3. Wall J
    4. Nelson RJ
    5. Sur M
    6. Felleman D

    (1983) Topographic reorganization of somatosensory cortical areas 3b and 1 in adult monkeys following restricted deafferentation

    Neuroscience 8:33–55.

    https://doi.org/10.1016/0306-4522(83)90024-6

    • PubMed
    • Google Scholar
56. 1. Merzenich MM
    2. Nelson RJ
    3. Stryker MP
    4. Cynader MS
    5. Schoppmann A
    6. Zook JM

    (1984) Somatosensory cortical map changes following digit amputation in adult monkeys

    The Journal of Comparative Neurology 224:591–605.

    https://doi.org/10.1002/cne.902240408

    • PubMed
    • Google Scholar
57. 1. Miyashita-Lin EM
    2. Hevner R
    3. Wassarman KM
    4. Martinez S
    5. Rubenstein JL

    (1999) Early neocortical regionalization in the absence of thalamic innervation

    Science 285:906–909.

    https://doi.org/10.1126/science.285.5429.906

    • PubMed
    • Google Scholar
58. 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
59. 1. Overduin SA
    2. d'Avella A
    3. Carmena JM
    4. Bizzi E

    (2012) Microstimulation activates a handful of muscle synergies

    Neuron 76:1071–1077.

    https://doi.org/10.1016/j.neuron.2012.10.018

    • PubMed
    • Google Scholar
60. 1. Penfield W
    2. Rasmussen T

    (1950) The cerebral cortex of man: a clinical study of localization of function

    Jama Network 144:1412.

    https://doi.org/10.1001/jama.1950.02920160086033

    • Google Scholar
61. 1. Philip BA
    2. Frey SH

    (2014) Compensatory changes accompanying chronic forced use of the nondominant hand by unilateral amputees

    Journal of Neuroscience 34:3622–3631.

    https://doi.org/10.1523/JNEUROSCI.3770-13.2014

    • PubMed
    • Google Scholar
62. 1. Pleger B
    2. Schwenkreis P
    3. Dinse HR
    4. Ragert P
    5. Höffken O
    6. Malin JP
    7. Tegenthoff M

    (2003) Pharmacological suppression of plastic changes in human primary somatosensory cortex after motor learning

    Experimental Brain Research 148:525–532.

    https://doi.org/10.1007/s00221-002-1324-1

    • PubMed
    • Google Scholar
63. 1. Pons TP
    2. Garraghty PE
    3. Ommaya AK
    4. Kaas JH
    5. Taub E
    6. Mishkin M

    (1991) Massive cortical reorganization after sensory deafferentation in adult macaques

    Science 252:1857–1860.

    https://doi.org/10.1126/science.1843843

    • PubMed
    • Google Scholar
64. 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
65. 1. Raffin E
    2. Giraux P
    3. Reilly KT

    (2012a) The moving phantom: motor execution or motor imagery?

    Cortex 48:746–757.

    https://doi.org/10.1016/j.cortex.2011.02.003

    • PubMed
    • Google Scholar
66. 1. Raffin E
    2. Mattout J
    3. Reilly KT
    4. Giraux P

    (2012b) Disentangling motor execution from motor imagery with the phantom limb

    Brain 135:582–595.

    https://doi.org/10.1093/brain/awr337

    • PubMed
    • Google Scholar
67. 1. Raffin E
    2. Richard N
    3. Giraux P
    4. Reilly KT

    (2016) Primary motor cortex changes after amputation correlate with phantom limb pain and the ability to move the phantom limb

    NeuroImage 130:134–144.

    https://doi.org/10.1016/j.neuroimage.2016.01.063

    • PubMed
    • Google Scholar
68. 1. Recanzone GH
    2. Merzenich MM
    3. Jenkins WM
    4. Grajski KA
    5. Dinse HR

    (1992) Topographic reorganization of the hand representation in cortical area 3b owl monkeys trained in a frequency-discrimination task

    Journal of Neurophysiology 67:1031–1056.

    https://doi.org/10.1152/jn.1992.67.5.1031

    • PubMed
    • Google Scholar
69. 1. Reilly KT
    2. Mercier C
    3. Schieber MH
    4. Sirigu A

    (2006) Persistent hand motor commands in the amputees' brain

    Brain 129:2211–2223.

    https://doi.org/10.1093/brain/awl154

    • PubMed
    • Google Scholar
70. 1. Rubenstein JL
    2. Anderson S
    3. Shi L
    4. Miyashita-Lin E
    5. Bulfone A
    6. Hevner R

    (1999) Genetic control of cortical regionalization and connectivity

    Cerebral Cortex 9:524–532.

    https://doi.org/10.1093/cercor/9.6.524

    • PubMed
    • Google Scholar
71. 1. Serino A
    2. Akselrod M
    3. Salomon R
    4. Martuzzi R
    5. Blefari ML
    6. Canzoneri E
    7. Rognini G
    8. van der Zwaag W
    9. Iakova M
    10. Luthi F
    11. Amoresano A
    12. Kuiken T
    13. Blanke O

    (2017) Upper limb cortical maps in amputees with targeted muscle and sensory reinnervation

    Brain 140:2993–3011.

    https://doi.org/10.1093/brain/awx242

    • PubMed
    • Google Scholar
72. Software

    1. Singh AK

    (2018) Bayes factor(Dienes) calculator

    Github.

    https://medstats.github.io/bayesfactor.html
73. 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
74. 1. Smith SM
    2. Jenkinson M
    3. Woolrich MW
    4. Beckmann CF
    5. Behrens TE
    6. Johansen-Berg H
    7. Bannister PR
    8. De Luca M
    9. Drobnjak I
    10. Flitney DE
    11. Niazy RK
    12. Saunders J
    13. Vickers J
    14. Zhang Y
    15. De Stefano N
    16. Brady JM
    17. Matthews PM

    (2004) Advances in functional and structural MR image analysis and implementation as FSL

    NeuroImage 23:S208–S219.

    https://doi.org/10.1016/j.neuroimage.2004.07.051

    • PubMed
    • Google Scholar
75. 1. Stoeckel MC
    2. Seitz RJ
    3. Buetefisch CM

    (2009) Congenitally altered motor experience alters somatotopic organization of human primary motor cortex

    PNAS 106:2395–2400.

    https://doi.org/10.1073/pnas.0803733106

    • PubMed
    • Google Scholar
76. 1. Striem-Amit E
    2. Ovadia-Caro S
    3. Caramazza A
    4. Margulies DS
    5. Villringer A
    6. Amedi A

    (2015) Functional connectivity of visual cortex in the blind follows retinotopic organization principles

    Brain 138:1679–1695.

    https://doi.org/10.1093/brain/awv083

    • PubMed
    • Google Scholar
77. Preprint

    1. Striem-Amit E
    2. Vannuscorps G
    3. Caramazza A

    (2018) Limitations of compensatory plasticity: the organization of the primary sensorimotor cortex in foot-using bilateral upper limb dysplasics

    bioRxiv.

    https://doi.org/10.1101/190462

    • Google Scholar
78. 1. Thompson B

    (1995) Exploring the replicability of a study's results: bootstrap statistics for the multivariate case

    Educational and Psychological Measurement 55:84–94.

    https://doi.org/10.1177/0013164495055001008

    • Google Scholar
79. 1. van den Heiligenberg FM
    2. Yeung N
    3. Brugger P
    4. Culham JC
    5. Makin TR

    (2017) Adaptable categorization of hands and tools in prosthesis users

    Psychological Science 28:395–398.

    https://doi.org/10.1177/0956797616685869

    • PubMed
    • Google Scholar
80. 1. Walther A
    2. Nili H
    3. Ejaz N
    4. Alink A
    5. Kriegeskorte N
    6. Diedrichsen J

    (2016) Reliability of dissimilarity measures for multi-voxel pattern analysis

    NeuroImage 137:188–200.

    https://doi.org/10.1016/j.neuroimage.2015.12.012

    • PubMed
    • Google Scholar
81. 1. Wang X
    2. Merzenich MM
    3. Sameshima K
    4. Jenkins WM

    (1995) Remodelling of hand representation in adult cortex determined by timing of tactile stimulation

    Nature 378:71–75.

    https://doi.org/10.1038/378071a0

    • PubMed
    • Google Scholar
82. 1. Wesselink DB
    2. Kikkert S
    3. Bridge H
    4. Makin TR

    (2018) Sensorimotor finger-specific information in the cortex of the congenitally blind

    Journal of Vision 18:99.

    https://doi.org/10.1167/18.10.99

    • Google Scholar
83. Software

    1. Wesselink DB
    2. Maimon-Mor R

    (2017) rsatoolbox, version 20fbe05

    Github.

    https://github.com/ronimaimon/rsatoolbox
84. 1. Wetzels R
    2. Matzke D
    3. Lee MD
    4. Rouder JN
    5. Iverson GJ
    6. Wagenmakers EJ

    (2011) Statistical evidence in experimental psychology: an empirical comparison using 855 t tests

    Perspectives on Psychological Science : A Journal of the Association for Psychological Science 6:291–298.

    https://doi.org/10.1177/1745691611406923

    • PubMed
    • Google Scholar
85. 1. Wiesel TN
    2. Hubel DH

    (1965a) Comparison of the effects of unilateral and bilateral eye closure on cortical unit responses in kittens

    Journal of Neurophysiology 28:1029–1040.

    https://doi.org/10.1152/jn.1965.28.6.1029

    • PubMed
    • Google Scholar
86. 1. Wiesel TN
    2. Hubel DH

    (1965b) Extent of recovery from the effects of visual deprivation in kittens

    Journal of Neurophysiology 28:1060–1072.

    https://doi.org/10.1152/jn.1965.28.6.1060

    • PubMed
    • Google Scholar
87. 1. Wiestler T
    2. Diedrichsen J

    (2013) Skill learning strengthens cortical representations of motor sequences

    eLife 2:e00801.

    https://doi.org/10.7554/eLife.00801

    • PubMed
    • Google Scholar
88. 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 120:141–157.

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

    • PubMed
    • Google Scholar

Author details

1. Daan B Wesselink

   1. Institute of Cognitive Neuroscience, University College London, London, United Kingdom
   2. Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom

   Contribution

   Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   Contributed equally with

   Fiona MZ van den Heiligenberg

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3229-0925

2. Fiona MZ van den Heiligenberg

   1. Institute of Cognitive Neuroscience, University College London, London, United Kingdom
   2. Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing—review and editing

   Contributed equally with

   Daan B Wesselink

   Competing interests

   No competing interests declared

3. Naveed Ejaz

   1. Brain and Mind Institute, University of Western Ontario, London, Canada
   2. Department of Computer Science, University of Western Ontario, London, Canada

   Contribution

   Conceptualization, Resources, Software, Formal analysis, Validation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8370-4588

4. Harriet Dempsey-Jones

   1. Institute of Cognitive Neuroscience, University College London, London, United Kingdom
   2. Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom

   Contribution

   Investigation, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

5. Lucilla Cardinali

   1. Brain and Mind Institute, University of Western Ontario, London, Canada
   2. Unit for Visually Impaired People, Istituto Italiano di Tecnologia, Genoa, Italy

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0441-1806

6. Aurelie Tarall-Jozwiak

   Queen Mary’s Hospital, London, United Kingdom

   Contribution

   Resources, Writing—review and editing

   Competing interests

   No competing interests declared

7. Jörn Diedrichsen

   1. Brain and Mind Institute, University of Western Ontario, London, Canada
   2. Department of Computer Science, University of Western Ontario, London, Canada

   Contribution

   Conceptualization, Software, Supervision

   Competing interests

   Member of eLife BRE

   "This ORCID iD identifies the author of this article:" 0000-0003-0264-8532

8. Tamar R Makin

   1. Institute of Cognitive Neuroscience, University College London, London, United Kingdom
   2. Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
   3. Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   For correspondence

   t.makin@ucl.ac.uk

   Competing interests

   Member of eLife BRE

   "This ORCID iD identifies the author of this article:" 0000-0002-5816-8979

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