Cortical Plasticity After Peripheral Nerve Injury

Chapter 64

Cortical Plasticity After Peripheral Nerve Injury Aaron D.C. Knox1, Ruma Goswami2, Dimitri J. Anastakis3 and Karen D. Davis2,4,5,* 1

Division of Plastic and Reconstructive Surgery, Department of Surgery, University of British Columbia, Vancouver, British Columbia, Canada. 2 Division

of Brain, Imaging & Behaviour—Systems Neuroscience, Toronto Western Research Institute, Toronto, Ontario, Canada. 3 Division of Plastic and Reconstructive Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada. 4 Department of Surgery and Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada. 5 University of Toronto Centre for the Study of Pain, Toronto, Ontario, Canada. *

Corresponding author: e-mail: [email protected]

INTRODUCTION Historically, it was thought that brain structure was fixed after childhood. However, it is now well established that the adult brain is highly malleable as demonstrated by the changes induced following stroke, amputation, and nerve injury (Anastakis, Chen, Davis, & Mikulis, 2005; Elbert et al., 1994; Navarro, Vivo´, & Valero-Cabre´, 2007). Today, the old inelastic model of functional organization has been replaced with one of pliability and responsiveness to motor or sensory changes (Davis, Taylor, & Anastakis, 2011). This capability of the nervous system to modify its structural and functional organization at biochemical, electrophysiological, and structural levels in response to a wide variety of environmental conditions is known as neuroplasticity (Anwyl, 1999; Byrne, 1997; McAllister, Katz, & Lo, 1999; Woolf & Salter, 2000). Neuroplasticity can occur across the entire neuraxis (Figure 64.1). The human hand can accurately and rapidly discriminate between characteristics of objects using cues from texture, size, spatial properties, and temperature. This results from coordinated communication between central nervous mechanisms, peripheral nerve endings, and mechanoreceptors in the fingertips (Lundborg, 2000). In the normal uninjured extremity, sensory stimulation of individual fingers activates primary afferent activity that is transmitted through one axonal branch to deep laminae in the spinal cord dorsal horn, and through another branch up the dorsal column of the spinal cord to terminate onto neurons in the cuneate nucleus in the brain stem. This information is carried by second-order neurons to the contralateral ventroposterior nucleus in thalamus and then thalamocortical axons carry information to the cerebral cortex. Normally, nuclei within these structures contain a precise somatotopic arrangement

Nerves and Nerve Injuries, Vol. 2. http://dx.doi.org/10.1016/B978-0-12-802653-3.00113-5 © 2015 Elsevier Ltd. All rights reserved.

corresponding to body locations (Florence, Garraghty, Wall, & Kaas, 1994; Kaas, 1991). However, nerve injury can induce organizational changes in these nuclei (Davis et al., 2011; Dostrovsky, Millar, & Wall, 1976; Finnerup, Nikolajsen, & Jensen, 2012; Florence & Kaas, 1995; Florence, Jain, & Kaas, 1997; Jain, Florence, Qi, & Kaas, 2000; Navarro et al., 2007). Within the primary somatosensory and motor cortices, each body part has a corresponding representational area. The areas devoted to the hand and upper extremity are disproportionately large. Therefore, injuries to the hand and upper extremity result in profound changes to the brain in addition to the peripheral nervous system that result in substantial loss of motor and sensory function. These changes may influence functional outcomes following peripheral nerve injury (PNI) and may contribute to differences in patient outcomes following successful surgical repair. Accordingly, it is important that all surgeons have a basic understanding of cortical plasticity following upper extremity injury, reconstruction, and rehabilitation. Despite surgical innovations, including nerve transfers, that have greatly contributed to the treatment of PNI, whether or not patients regain good sensorimotor function following upper extremity PNI and surgical repair does not appear to be predictable on the basis of surgical technique alone (Taylor, Anastakis, & Davis, 2009). Barring technical issues, outcomes do not seem to reflect the quality of nerve repair or nerve regeneration. Patient-related factors including personality and brain structure, connectivity, and function are important contributors to outcome and quality of life after PNI. Consequently, the overall prognosis may be influenced by CNS factors including cortical plasticity (Davis et al., 2011).

1055

1056 PART VII The Future of Peripheral Nerve Injury

FIGURE 64.1 Summary diagram outlining locations and mechanisms of plasticity following nerve injury. Used with permission from Navarro et al. (2007).

Much of our understanding of the mechanisms underlying cortical plasticity following nerve injury is based on primate studies that demonstrate reorganization in the somatosensory cortex following amputation or transection of the median nerve (Merzenich, Kaas, Sur, & Lin, 1978; Merzenich, Kaas, Wall, Nelson, et al., 1983; Merzenich et al., 1984, 1987). Recently, advances in noninvasive neuroimaging and brain stimulation techniques have provided opportunities to study plasticity in humans, further advancing our understanding of what happens to the sensorimotor cortex following upper extremity injury, reconstruction, and rehabilitation (Davis et al., 2011) (see below). Peripheral nerve surgery may have advanced to the point where further improvements in patient outcomes may rely on the manipulation of the structural and molecular mechanisms responsible for cortical plasticity. Following repair, plasticity may play a beneficial role in rehabilitation by promoting sensory reeducation (see below) and motor learning, but it can also lead to dysfunctional changes resulting in chronic pain or inferior functional outcomes (Lundborg & Rose´n, 2007; Moseley & Flor, 2012). Although significant advances have been made in our understanding of plasticity following PNI and repair, the factors governing the degree of plasticity and whether the changes will be adaptive or maladaptive are unclear. Although important first steps have been taken to understand and define the molecular systems underlying these

fundamental processes and their induction, the remaining challenge is to further understand, elucidate, and manipulate these relationships between cortical representational maps and the function of individual synapses at biochemical, electrophysiological, and structural levels (Anastakis et al., 2005). Exploring these underlying mechanisms may allow us to manipulate the CNS through development of new therapeutic interventions designed to promote adaptive plasticity while preventing maladaptive plasticity. These treatments along with strategies that link cortical mapping and remapping with sensory and motor reeducation might then be incorporated into rehabilitation programs to improve motor and sensory outcomes.

BASIC SCIENCE Poor recovery after PNI may be due to a variety of cellular and metabolic processes (Lundborg & Rose´n, 2007). For example, after nerve transection, “chromatolysis” occurs within the nerve cell body, leading to swelling of the cell body, loss of Nissl bodies, and migration of the nucleus from the center of the cell to the peripheral cell membrane (Fenrich & Gordon, 2003; Geuna, Tos, & Battiston, 2009). This process is associated with changes in the cytoskeleton of the membrane, and mRNA synthesis and a shift from “signaling” mode to “growth” mode (Fenrich & Gordon, 2003; Navarro et al., 2007; Tos, Ronchi, Geuna, &

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

Battiston, 2012). Axons in the proximal segment undergo retrograde degeneration from the site of injury to the first node of Ranvier from the injury (Geuna et al., 2009). Within hours of transection, distal nerve stumps undergo Wallerian degeneration to prepare the environment for regenerating axons (Zochodne, 2008). Over 3-6 weeks, Schwann cells and macrophages produce endoneurial tubes, which are important to guide axonal regrowth (Fawcett & Keynes, 1990; Fu & Gordon, 1995). In culture, growth cones that emerge from the proximal nerve stump extend along the Schwann cell basal lamina in the distal segment by which neurite-promoting factors such as fibronectin and laminin, cell adhesion molecules, and cadherins facilitate attachment and advancement of regenerating axons at a rate of about 1-3 mm per day (Geuna et al., 2009; Fenrich & Gordon, 2003; Lundborg & Rose´n, 2007).

Methodologies to Study Human Cortical Plasticity Cortical plasticity has traditionally been studied in animal models and postmortem studies using histological or tracing techniques. However, noninvasive neuroimaging and brain stimulation techniques can be used for in vivo investigations of plasticity in the human brain. Listed below are common methodologies used to assess cortical activity and structural changes in response to initial injury and progression and in efficacy of treatments.

Positron Emission Tomography Positron emission tomography (PET) is a technique that can be used to study functional processes in the brain in vivo. This modality images the tissue uptake of a radiolabeled compound in circulating blood after it is injected intravenously. When the isotope decays, it emits a positron that then collides with an electron, causing emission of two photons in opposite directions. Subsequently, a tomograph detects the photons and brain tissue and can image the concentration of radioisotopes (Hutchinson, O’Connell, Kirkpatrick, & Pickard, 2002). There are three common types of PET studies: the most commonly used PET tracer for research purposes is [15O] water, used to measure regional cerebral blood flow that relates to the amount of neuronal activity (Raichle, Martin, Herscovitch, Mintun, & Markham, 1973). Another common type of PET tracer in research is fluorodeoxyglucose, which is used to measure cerebral metabolism (Reivich et al., 1979). Finally, the most powerful use of PET for basic research is through the use of radiolabeled neurotransmitters that can assess receptor binding and release of specific neurotransmitters (e.g., opiates, dopamine, GABA, serotonin) (Heiss & Herholz, 2006).

1057

Transcranial Magnetic Stimulation Transcranial magnetic stimulation (TMS) is a noninvasive method of delivering stimulation to the brain and has been used to examine CNS physiology, mainly focused on the motor system. TMS is thought to either activate or block neuronal activity, depending on the type of stimuli delivered through the TMS coils (Dayan, Censor, Buch, Sandrini, & Cohen, 2013). Single low-frequency pulses can disrupt the function of a cortical area for a brief period of time, thus creating a “virtual brain lesion” and providing information of the role of a cortical region toward a given role or behavior (Pascual-Leone, 1999). High-frequency TMS currents can increase cortical excitability, which is useful for motor sequence learning and examining cortical plasticity and function (Anastakis et al., 2005; Dayan et al., 2013). TMS can assess cortical inhibition by stimulating the motor cortex and measuring the resultant peripheral muscle activity with electromyography, providing information about the functioning of central motor pathways (Barr, Farzan, Davis, Fitzgerald, & Daskalakis, 2013).

Functional and Structural Magnetic Resonance Imaging Functional magnetic resonance imaging (fMRI) is a sensitive noninvasive tool used to examine activation patterns in the brain during tasks and in response to stimulation, offering the capability to understand the impact of injury on neural processing. The technique is based on the relationship between neuronal activity and blood flow/oxygenation (i.e., neurovascular coupling). Most fMRI studies depend on the blood oxygenation level-dependent (BOLD) contrast effect (Ogawa, Lee, Nayak, & Glynn, 1990). An increase in neuronal activity leads to a large increase in blood flow that surpasses the metabolic rate of oxygen consumption, leading to decreased concentration of deoxyhemoglobin and creates the MRI BOLD signal (Logothetis & Wandell, 2004) (Figure 64.2). The signals detected by high field MRI machines and particular sequences have good spatial resolution in the order of millimeters. More recently, fMRI has been developed to examine brain activity at “rest” and thus can identify networks of functionally connected brain regions based on low-frequency synchronous activity (Davis & Moayedi, 2013). There are also MRI methods to measure structure that are useful to assess neuropathologies and disease progression. For example, voxel-based morphology and cortical thickness analysis are commonly used approaches to quantify gray matter (Ashburner & Friston, 2000; Fischl & Dale, 2000). Gray matter changes in terms of volume, density, thickening, and thinning are not well understood but may be related to changes in vasculature, neuronal cell size, glial number or size, or changes in axonal or dendritic architecture (Zatorre, Fields, & Johansen-Berg, 2012).

1058 PART VII The Future of Peripheral Nerve Injury

FIGURE 64.2 Overview of the development of the fMRI BOLD response from stimulus, neurovascular coupling to changes in blood flow and oxygenation levels, and MRI parameters used to detect the changes. Used with permission from Arthurs and Boniface (2002).

MRI-based assessment of white matter is now commonly done from diffusion-weighted scans and diffusion tensor imaging (DTI). DTI is based on the diffusion properties of water molecules in white matter. The patterns of water diffusion are important for elucidating microstructural details of white matter in normal and injured tissue. In regions with little or no physical constraints, water is free to move randomly in all directions, termed isotropic diffusion. However, the movement of a water molecule along a white matter fiber is constrained within the boundaries of the axon sheath, causing movement to occur along the length of the fiber, termed anisotropic diffusion (Mori & Zhang, 2006). DTI also can be used to assess anatomical brain connectivity with a technique called tractography. As well, abnormalities in white matter structure can be described by DTI metrics, the most common being fractional anisotropy (FA). FA reflects the degree of anisotropy along an axon; low FA indicates disrupted white matter (Beaulieu, 2002). In addition, axial diffusivity, referred to as parallel diffusion, can be affected by axonal changes, while mean diffusivity, representing the overall movement of water molecules, and radial diffusivity, referred to as perpendicular diffusion, can be useful in providing information about the cell membrane and myelination (Beaulieu, 2002). Pathological features such as crossing fibers, axonal changes, neuroinflammation, and edema in peripheral nerves are associated with changes in DTI metrics (Lehmann, Zhang, Mori, & Sheikh, 2010; Takagi et al., 2009). Using MRI and psychophysics, Taylor et al. (2009) and Taylor, Anastakis, and Davis (2010) examined the impact of PNI on brain function and structure more than 1.5 years after a total nerve transection. Compared to healthy controls, these patients had sensory loss in the hand territory of the transected nerve, reduced activation of the primary

somatosensory cortex induced by vibrotactile stimulation of this hand region, and abnormal fMRI responses to vibration in the cortical attention network. Furthermore, the authors found cortical thinning in the contralesional primary and secondary somatosensory cortex and in regions of the brain associated with somatosensory processing and pain, emotion, cognition, and interoception as well as white matter abnormalities (Apkarian, Bushnell, Treede, € & Zubieta, 2005; Critchley, Wiens, Rotshtein, Ohman, & Dolan, 2004).

Mechanism of Cortical Plasticity Cortical plasticity has been associated with a variety of cellular events, including changes in synaptic efficacy of preexisting synapses and creation of new connections (Navarro, 2009). Use-dependent plasticity can occur normally through modifications in the strength of existing subthreshold excitatory inputs due to regulation of neurotransmitters (Flor, Nikolajsen, & Jensen, 2006). Following nerve transection, significant functional and structural changes of somatopic maps occur within minutes to hours (Melzack, Coderre, Katz, & Vaccarino, 2001; Sagi et al., 2012). The mechanisms underlying these changes include rapid unmasking of previously inactive connections to adjacent cortical and subcortical structures and slower formation of new connections through collateral axonal sprouting of intact afferents in adjacent cortical or subcortical areas (Anastakis, Malessy, Chen, Davis, & Mikulis, 2008; Chen, Cohen, & Hallett, 2002; Florence & Kaas, 1995; Hickmott & Steen, 2005) (Figure 64.3). These changes can be accompanied by altered receptive fields, spontaneous and stimulus-evoked activity, gray matter, and white matter structure and connectivity (Box 64.1).

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

FIGURE 64.3 Diagram outlining unmasking and axonal sprouting as two anatomic mechanisms of plasticity following deafferentation. Used with permission from Taub, Uswatte, and Elbert (2002).

BOX 64.1 Potential neuronal mechanisms of CNS plasticity: l Unmasking/strengthening of silent or ineffective synapses l Collateral sprouting l Loss of GABAergic inhibition (i.e., disinhibition) l Loss of temporally correlated activity Responses of CNS indicating plasticity following peripheral nerve injury: l Spontaneous neuronal firing activity l Abnormal bursting activity l Expansion of receptive fields l New stimulus-evoked projected field l Changes in somatotopy l Gray matter loss/gain l White matter loss/gain l Altered functional or structural connectivity between brain regions/networks Used with permission from Davis et al. (2011).

Mechanism of Cortical Plasticity—Unmasking Unmasking of existing but inactive synapses and neural pathways is one mechanism thought to contribute to cortical plasticity (Bj€ orkman, Rose´n, & Lundborg, 2004; Calford & Tweedale, 1990). Following deafferentiation, adjacent cortical areas rapidly expand into the cortical territory that represents the injured peripheral nerve (Gilbert & Wiesel, 1992; Merzenich et al., 1984; Pons et al., 1991). Animal studies provide evidence that one of the mechanisms of this invasion is through unmasking existing latent connections through loss of GABA-mediated inhibition (Millar, Basbaum, & Wall, 1976; Wall & Egger, 1971). Dostrovsky et al. (1976) observed that inactivating dorsal

1059

column activity resulted in cortical receptive fields switches from the leg to the abdomen. These receptive fields reverted to their original locations after the block was removed. Similar changes have been observed following digit amputation (Calford & Tweedale, 1988) and peripheral nerve transection (Cusick, Wall, Whiting, & Wiley, 1990). This process is rapid, and Byrne and Calford (1991) found that denervation of the hind paw via amputation or anesthetic resulted in expansion of neuronal receptive fields in the primary somatosensory cortex into the deafferentated areas within 5 min of denervation. Similarly, Jacobs and Donoghue (1991) observed functional reorganization of the primary motor cortex (M1) within 1 h following intracortical injection of a GABA antagonist. The authors suggest that this rapid reorganization is due to alterations in existing synaptic connections and that even small adjustments in intracortical inhibition are sufficient to unmask latent connections and reorganize the M1 map. TMS studies suggest that this process may also extend to humans. In healthy volunteers experiencing partial hand sensory anesthesia, Rossini et al. (1996) observed transient and rapid rearrangements of the cortical motor area of muscles surrounded by the anesthetized skin, suggesting unmasking and/or activation of preexisting, silent connections (Rossini et al., 1996). Furthermore, fMRI observations of humans following limb amputation suggest that reorganization of sensory pathways develops quickly after amputation, implying that this initial reorganization occurs via altered effectiveness of existing connections rather than formation of new connections. Borsook et al. (1998) observed modality-specific phantom sensations from face stimulation within 24 h of arm amputation that corroborated with fMRI findings a month later. The rate of appearance of referred sensations was ascribed to reactivation of preexisting functionally silent connections. Together, these findings highlight the speed with which cortical plasticity can occur following injury and explain the rapid cortical expansion seen in representations of adjacent noninjured nerves.

Mechanism of Cortical Plasticity—Axonal Sprouting Slow cortical plasticity over larger distances can occur through formation of new axons at cortical or subcortical levels (Darian-Smith & Gilbert, 1994; Yamahachi, Marik, McManus, Denk, & Gilbert, 2009). Tracing studies in animal models (Bao et al., 2002; Dancause et al., 2005; Hickmott & Steen, 2005; Jain et al., 2000; Wu & Kaas, 2002) support the view that the sprouting of intact afferents occurs at the level of the dorsal horn, dorsal column nuclei, thalamus, and cerebral cortex and may account for largescale long-term reorganization occurring over weeks and months (Florence & Kaas, 1995; Sengelaub et al., 1997;

1060 PART VII The Future of Peripheral Nerve Injury

Wall, Xu, & Wang, 2002). Large-scale and large-distance cortical reorganizations have also been reported in humans after injury. For example, Pons et al. (1991) observed that 12 years following deafferentation of an entire limb, the cortical representation of the upper limb became responsive to stimulation of the face. Axonal sprouting is thought to contribute to structural plasticity through changes to gray and white matter connectivity. MRI studies have recently confirmed gray and white matter changes following limb amputation and chronic pain (Apkarian et al., 2004; Davis et al., 2008; Draganski et al., 2006; Geha et al., 2008; Zatorre et al., 2012). Identification of altered fMRI activation maps have also been observed in other conditions involving plasticity such as spinal cord injury, toe-to-thumb transfer, and carpel tunnel syndrome (Jurkiewicz, Crawley, Verrier, Fehlings, & Mikulis, 2006; Lotze, Flor, Grodd, Larbig, & Birbaumer, 2001; Manduch, Bezuhly, Anastakis, Crawley, & Mikulis, 2002; Napadow et al., 2006).

Intra- versus Interhemispheric Plasticity Differences in intra- and interhemispheric connectivity caused by unmasking and axonal sprouting may provide insight into the process of ongoing plasticity during recovery. Long-term follow-up fMRI studies in patients with median nerve injury and direct repair demonstrate differences between subacute injury and repair states. At 5 years postinjury and repair, increased activation in the contralateral primary somatosensory cortex is observed (Fornander, Nyman, Hansson, Ragnehed, & Brismar, 2010; Taylor et al., 2009). In patients 14 years postrepair, this pattern of contralateral activation persists; however, increased activation is also seen in the ipsilateral cortex (Rose´n et al., 2012). Such increased ipsilateral activation may represent a compensatory mechanism (Pelled, Chuang, Dodd, & Koretsky, 2007). Decreased intrahemispheric connectivity has also been reported after facial nerve palsy (Klingner et al., 2011), whereas weakened interhemispheric functional connectivity has been reported following brachial plexus avulsion injury (Liu et al., 2013). In both cases, these alterations in connectivity could result in less efficient information transfer and desynchronization of brain areas, ultimately resulting in decreased collaboration both within and between hemispheres.

CLINICAL SECTION PNI results in immediate and long-lasting consequences on cortical representations (Garraghty & Muja, 1996). Following injury, a damaged nerve can cease to function entirely or can convey abnormal ectopic activity to the CNS. How a PNI results in cortical changes is dependent on the nature of the nerve lesion. PNI without repair results

in a complete loss of afferent input from peripheral nerves distal to the site of injury. Following amputation of a single digit, the cortical representations of adjacent digits will expand to occupy the areas previously receiving sensory input from the amputated digit. In other words, the cortical area deprived of its driving inputs will contain patches of unresponsive cortex mixed with areas that rapidly become occupied and responsive to inputs from body parts with adjacent cortical representations. Similarly, transection of a single nerve will result in expansion of cortical representations of adjacent nerves. In the primate, transection of the median nerve immediately resulted in a “silent” area in the somatosensory cortex that was unresponsive to cutaneous stimulation and corresponded to the representations of the thumb and of the index, middle, and ring fingers (Merzenich, Kaas, Wall, Nelson, et al., 1983; Merzenich, Kaas, Wall, Sur, et al., 1983) (Figure 64.4). Subsequently, this representational cortical territory was occupied by patches of unresponsive cortex mingled with areas that respond to stimulation of adjacent ulnar and radial nerve territories. Initially, input into this zone is unorganized and overlapping; however, within 3 weeks, the representation of new inputs in this zone becomes increasingly well demarcated with smaller receptive fields and sharp borders between the expanding territories and adjacent cortical areas corresponding to the ulnar and radial nerves (Merzenich & Jenkins, 1993; Wall et al., 1986). Similar observations are seen following combined radial and median nerve transection in adult squirrel monkeys (Silva, Rasey, Wu, & Wall, 1996). Initially, changes in cortical size are observed within minutes of transection. Subsequently, cortical representation of ulnar nerve inputs and face and forearm inputs expanded into areas of the hand cortex with similar patterns of receptive field changes observed across different animals. Following hand amputation, resulting in complete loss of afferent input from the radial, ulnar, and median nerves, adjacent facial sensory representational regions are found to extend into the zone formally represented by the hand (Elbert et al., 1994; Yang et al., 1994).

Cortical Reorganization in PNI Following Crush Injury Compression or crush injuries can stop conduction of action potentials across a nerve segment due to either a localized loss of myelin or a loss of continuity within the axon. Dykes and Terzis performed a series of experiments on baboon ulnar nerves to examine differences in cortical reorganization following various types of nerve injuries (Dykes & Terzis, 1979; Terzis & Dykes, 1980). Following recovery after nerve crush injury, mechanoreceptor receptive fields and sensory thresholds were nearly normal, indicating that regenerating axons successfully reinnervated their original

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

1061

FIGURE 64.4 Changes in cortical representation of the somatosensory cortex following amputation or nerve injury followed by regeneration. Used with permission from Lundborg (2000).

1062 PART VII The Future of Peripheral Nerve Injury

peripheral targets. Because the endoneurial tube remains intact, regenerating axons will ultimately reach their original cutaneous locations (Lundborg, 1988), and the resulting cortical representation of the nerve-innervating cutaneous areas after regeneration following nerve crush injury will not be substantially different from the normal uninjured representation (Davis et al., 2011; Wall, Felleman, & Kaas, 1983).

Cortical Reorganization in PNI Following Transection without Repair In contrast to crush injuries, complete transection of a peripheral nerve results in both immediate and ongoing changes to the representational area in the cortex corresponding to that specific nerve (Garraghty, Hanes, Florence, & Kaas, 1994; Merzenich, Kaas, Wall, Nelson, et al., 1983; Silva et al., 1996; Wall et al., 1986). Complete deafferentation interrupts endoneurial tube continuity, and these types of nerve injuries typically have poor functional outcomes. The initial cortical changes seen following complete neurotemesis are similar to those seen following amputation. Specifically, the cortical representations of adjacent innervated skin will expand to occupy areas that were previously receiving input from the injured nerve (Merzenich & Jenkins, 1993; Wall et al., 1986). These cortical changes may persist if a nerve is not permitted to regenerate (Anastakis et al., 2008).

Cortical Reorganization in PNI Following Transection with Repair Following complete nerve transection and surgical repair, it is highly unlikely that the original peripheral targets will be reinnervated by their original axons because of misdirection in axonal growth across the repair site. This problem is compounded in mixed motor and sensory nerves by the possibility of sensory and motor nerve mismatch leading to aberrant reinnervation of end organs. In a pure motor or sensory nerve, recovery is generally more successful because axonal misdirection is less severe, and aberrant growth of a sensory axon into motor nerve basal laminae or vice versa does not occur (Lundborg, 2005). Either scenario results in impaired function and below normal values for axonal diameter, conduction velocity, and excitability at the site of injury (Navarro et al., 2007). This inadequate structural regenerative process is associated with significant reorganization changes in the cortex in those regions where input from the injured nerve is normally represented. Following repair and regeneration, the overall cortical area corresponding to the injured nerve will remain essentially unchanged. However, it will be totally remodeled due to disorganized input from the regenerating axons. For example, prior to injury, sensory information from the median nerve projects onto well-defined bands of cortical representation corresponding to the representations of the

thumb and of the index, middle, and ring fingers. Following injury, the previously well-defined bands for each finger will be replaced by dispersed discontinuous islands represented across multiple small patches within the regenerated nerve cortical area (Florence et al., 1994; Jain, Florence, & Kaas, 1998; Kaas & Florence, 1997; Wall et al., 1986). This disorganized remodeling is responsible for loss of fine sensory functions such as stereognosis (McAllister & Calder, 1995). One year following transection and repair, the deafferented cortex remains a patchy discontinuous representation of the transected and adjacent nerves (Wall et al., 1986). After 1 year, the small and irregular mechanoreceptor receptive field representations from regenerating nerves that are innervating inappropriate peripheral targets begin to coalesce into one continuous area (Davis et al., 2011). This would suggest that changes in the cortical maps of a cutaneous surface following nerve transection with repair are ongoing and that central plasticity may play a role in resolution or persistence of sensory and motor abnormalities (Anastakis et al., 2005).

Structural and Functional Cortical Changes Following PNI Structural and functional plasticity result from incomplete recovery after nerve transection and repair. Following nerve transection, it is estimated that 20-50% of dorsal root ganglion neurons die (Liss, Af Ekenstam, & Wiberg, 1996), resulting in a significant loss of afferent input to the cortex. This loss of afferent input and incomplete regeneration results in long-term somatosensory impairments, gray matter and white matter atrophy in key somatosensory regions, and functional changes in key somatosensory regions (Taylor et al., 2009) (Figure 64.5). Previous research has demonstrated gray matter alterations in a wide range of psychological and neurological conditions. Similar changes are seen following traumatic injury to the spinal cord (Jurkiewicz et al., 2006) and are present in chronic pain following limb amputation (Draganski et al., 2006). Differences in gray matter connectivity also correlate with personality traits such as neuroticism and extraversion (Omura, Constable, & Canli, 2005) that are thought to be related to poor outcomes following PNI. It is important to note that structural and functional changes in gray and white matter are not limited to the injury state and may have important implications for outcomes following rehabilitation. Gray matter networks have been shown to change during normal brain maturation (Raznahan et al., 2011) and are sensitive to learning (Bermudez, Lerch, Evans, & Zatorre, 2009; May et al., 2007). Jenkins, Merzenich, Ochs, Allard, and GuicRobles (1990) observed that when training monkeys to use a single digit more than other digits, there was

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

1063

FIGURE 64.5 Structural and functional plasticity result from incomplete recovery after nerve transection and repair. Structural and functional changes further impact sensory recovery and may influence each other. Used with permission from Taylor et al. (2009).

expansion of the cortical representation for the trained finger at the expense of the other fingers. Similarly, extensive use of hands and fingers by expert musicians (Elbert, Pantev, Wienbruch, Rockstroh, & Taub, 1995) or long-standing braille users (Pascual-Leone & Torres, 1993) results in enlargement of areas in the brain corresponding to the extremity or digits being used. These observations suggest that during motor learning, the brain undergoes adaptive changes resulting in specific expansion of those zones that are most strongly connected to the learned skill. Classen, Liepert, Wise, Hallett, and Cohen (1998) found that even short transient training sessions of

basic movements were capable of causing rapid changes to the motor cortex, and Karni et al. (1995) demonstrated that reorganization of the motor cortex seen in normal subjects learning to perform a rapid sequence of finger movements through daily practice continued to evolve over a series of weeks. Together, these findings would suggest that at the onset of learning a new motor skill, there is a rapid expansion of motor cortical representation and an immediate increase in excitability and decrease in intracortical inhibition that effectively “primes” the cortex for motor learning (Anastakis et al., 2005) (Figure 64.6). As practice progresses, there is a further increase in the amount of

FIGURE 64.6 Observations using functional magnetic resonance imaging and transcranial magnetic stimulation during motor skills learning. Initially when learning a new motor skill, there is a rapid expansion of motor cortical representation and an immediate increase in excitability and decrease in intracortical inhibition effectively priming the cortex for motor learning. As the subject learns and becomes an expert, decreased cortical activation, decreased cortical excitability, and increased inhibition are observed. Used with permission from Wehrli, Bonnard, and Anastakis (2011).

1064 PART VII The Future of Peripheral Nerve Injury

cortical representation until the degrees of cortical representation and excitability decrease and approach normal levels as the skill is mastered. Cohort studies looking at differences in brain structure or function reflective of skill, knowledge, or expertise in groups of taxi drivers (Maguire et al., 2000) or musicians (Bermudez et al., 2009) suggest that changes to the brain may be experience-dependent. It is difficult to discern whether anatomical changes are the cause or the consequence of expertise (Zatorre et al., 2012); however, longitudinal prospective studies demonstrating changes in both gray and white matter connectivity of healthy participants learning motor tasks (Draganski et al., 2004; Taubert et al., 2010) also lend some support for anatomical changes being a result of learning.

Chronic Neuropathic Pain After PNI The idea that central plasticity is involved in the development of pathological pain was initially brought forth following clinical postulations that CNS changes result in pain sensitivity, referred pain, and postoperative pain (see review by Melzack et al., 2001). After nerve injuries, signs of neuropathic pain often develop, including allodynia, hyperalgesia, and referred pain. Taylor et al. (2010) examined patients with complete medial or ulnar nerve transections by comparing sensorimotor abilities in patients presenting with pain and without pain at least 1 year after nerve repair. Patients without chronic pain exhibited increased latency and decreased amplitudes during nerve conduction testing, sensory deficits, reduced dexterity, and reduced sensorimotor integration. In contrast, patients with chronic pain exhibited the same constellation of abnormalities as the pain-free patients but with greater severity and additional pain intensity and unpleasantness ratings to cold stimuli. The persistent perceptual abnormalities associated with chronic pain are challenging to attribute to underlying tissue injury alone and are therefore thought to be related to cortical changes induced by the experience of chronic pain (Jensen & Baron, 2003; Moseley, Gallace, & Spence, 2012). Phantom limb pain is a common experience following leg or arm amputation (Melzack, 1990; Weeks & Tsao, 2010). Phantom limb pain is often described as cramping, burning, or other discomfort and has also been attributed to a central mechanism (Katz & Melzack, 1990). Retention of a thalamic representation of the missing limb may be required for phantom sensations (Davis et al., 1998). However, at the cortical level, Flor et al. (1995, 1996) found that in fMRI studies of human patients following amputation, reorganizational changes occurred only in amputees with phantom limb pain but not in amputees without pain. Furthermore, the amount of cortical reorganization was found to correlate with the magnitude of pain. The authors suggest that that phantom-limb pain is related to, and may

be a consequence of, plastic changes in primary somatosensory cortex (Moseley & Flor, 2012). Similarly, Gustin et al. (2012) used fMRI and structural magnetic resonance imaging (sMRI) to demonstrate that human patients with chronic orofacial neuropathic pain displayed cortical reorganization and changes in somatosensory cortex activity whereas patients with nonneuropathic chronic pain did not. Taken together, these studies suggest that cortical reorganization is not simply a function of injury but rather that the development of aberrant sensations such as pain has important implications for changes to brain structure that may in turn influence further sensory and motor outcomes (Flor et al., 1995; Lotze et al., 1999; Moseley & Flor, 2012). The interplay between cortical plasticity and chronic pain highlights the limitations of current treatment strategies and suggests that plasticity may play a promising role in future therapies.

Behavioral Alterations Associated with Chronic Neurogenic Pain In addition to cortical remodeling, chronic neuropathic pain is also associated with functional alterations in affective dimensions such as catastrophizing, neuroticism, and depressive behavior (Taylor et al., 2010). Pain catastrophizing is defined as a maladaptive cognitive-affective response to pain that involves negative thinking regarding the pain experience (Sullivan, Lynch, & Clark, 2005). Catastrophizing and neuroticism have previously been linked with pain intensity and duration of chronic pain (Wiech, Ploner, & Tracey, 2008), and chronic pain patients who catastrophize are found to have more pain, disability, and psychological distress (Severeijns, Vlaeyen, van den Hout, & Weber, 2001). Similarly, catastrophizing and depression symptoms have been associated with higher DASH scores (Niekel, Lindenhovius, Watson, Vranceanu, & Ring, 2009; Novak, Anastakis, Beaton, Mackinnon, & Katz, 2011), poor surgical outcome, and high levels of disability (Novak & Katz, 2010; Novak et al., 2011). To better understand disorders that are diagnosed on the basis of behavioral disturbances, it is essential to further establish the relationships between behavior and structure. Similar to difficulties in discerning whether anatomical brain variations are attributable to expertise or vice versa, it is currently unknown whether behavioral factors such as chronic pain, catastrophizing, and depression are the cause of, or are caused by, poor motor and sensory recovery following PNI and repair.

Adaptive and Maladaptive Plasticity Optimal functional outcome after PNI and repair depends on successful reinnervation of the sensory receptors and motor endplates and appropriate remodeling within the

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

sensorimotor cortex. Examples of adaptive cortical reorganization have previously been demonstrated following surgery to separate webbed fingers (Mogilner et al., 1993) after toe-thumb transfer (Manduch et al., 2002) and nerve transfers for brachial plexus reconstruction (Hua et al., 2013). Following thumb reconstruction and nerve transfers, a distinct temporal pattern of activation is observed that correlates with return of active flexion and return of sensation. This pattern may represent a “signature” of adaptive plasticity leading to good functional recovery. Conversely, reconstructive failures that occur despite intact neuromuscular connections in the periphery might be explainable by a lack of cortical sensorimotor network recruitment. These failures may represent maladaptive plasticity pointing to a “central” mechanism of treatment failure. Because changes in cortical activation correspond to specific events in the reconstruction and functional recovery, it is possible that in the future, these “signatures” of superior or inferior functional motor outcomes may have potential implications for prognosis during recovery and rehabilitation (Anastakis et al., 2005).

Brachial Plexus Injury Nerve Transfers for Sensory and Motor Function The concept of plasticity influencing outcomes following nerve transfer is not new. Thirty years ago, Narakas (1984) speculated that there must be a central mechanism resulting in successful outcomes following transfer of the intercostal nerves (ICN) to the musculocutaneous nerve (MCN) for elbow flexion. Since that time, surgeons have become increasingly aware of the importance of cortical plasticity and motor relearning (see below) in functional recovery following a nerve transfer. This has led to suggestions that maladaptive cortical plasticity contributes to poor clinical outcomes (Lundborg & Rose´n, 2007).

Oberlin Nerve Transfer Oberlin first described partial ulnar nerve transfers to the biceps branch of the MCN for restoration of bicep flexion in the mid 1990s (Leechavengvongs, Witoonchart, Uerpairojkit, Thuvasethakul, & Ketmalasiri, 1998; Oberlin et al., 1994). Cortical plasticity may contribute to the success of using the ulnar nerve as a donor compared to other potential donors. For example, findings in a rat model suggest that plasticity is facilitated when the donor and recipient nerve are originally responsible for similar functions (Li et al., 2013). This suggests that superior results for elbow flexion would result from partial transfer of the ulnar nerve (a donor with synergistic function) as opposed to using the radial nerve (a donor with antagonistic function).

1065

Intercostal Nerve Transfer ICN-MCN transfers are used to restore useful biceps function (Malessy & Thomeer, 1998). The ICNs innervate inspiratory and expiratory respiratory muscles that are involved in complex thoracic movements (De Troyer & Estenne, 1988; Taylor, 1960), and corticospinal neurons projecting to the intercostal muscles are active during respiration or posture control. Following an ICN-MCN transfer, central motor programs controlling respiration and posture control must also control biceps flexion (Malessy, van Dijk, & Thomeer, 1993). Immediately following reinnervation, EMG data demonstrate that respiratory activity may be present without clinical contraction of the biceps. As reinnervation progresses, patients are able to initiate involuntary elbow flexion with respiration resulting in synkinetic movement of the elbow during respiration. Even after voluntary control is regained, often a conscious respiratory effort is still required. Toward the final stages of reinnervation, voluntary biceps contraction is independent of respiratory activity (Anastakis et al., 2008), and this dissociation reflects cortical reorganization in the CNS (Mano et al., 1995). Ravnborg, Blinkenberg, and Dahl (1991) and Rothwell, Thompson, Day, Boyd, and Marsden (1991) found that the CNS connections to the donor ICN change in terms of both location of control and strength of signal from those controlling respiration to those controlling biceps contraction. This shift in motor control has also been confirmed by fMRI and TMS (Malessy, Bakker, Dekker, van Dijk, & Thomeer, 2003). Following reinnervation, fMRI data suggest that activity continues to be induced and localized within the primary motor area (M1) and that level of activation is the same between reinnervated biceps and control limbs (Malessy et al., 2003). In other words, it would appear that neural input activity for volitional biceps control from the original cortical “biceps area” continues to regulate biceps contraction, even though cerebral activity could not reach the biceps by following the original nervous system pathway. Furthermore, TMS studies in normal controls revealed that the cortical representation of the ICN is localized in the midline whereas the bicep muscle is represented a few centimeters lateral from the midline (Malessy, van der Kamp, Thomeer, & van Dijk, 1998). Following reinnervation, the location of the biceps TMS map is indistinguishable from that of the normal biceps location and is different from that of the medial location of the intercostal muscles, suggesting that plastic changes occur in the neural output activity (Malessy et al., 1998). (Figure 64.7a and b). Together these studies demonstrate that following functional biceps reinnervation after ICN-MCN transfer, neural input for purposeful biceps control is reactivated and the target changes from the deinnervated C5-6 motor neuron pool to the reinnervated thoracic ICN motor neuron pool.

Posture respiration

ICN

Shortly after transfer Magnetic stimulation ICN Donor (medial)

fMRI: No input plasticity

MCN Elbow flexion

MCN Acceptor (lateral)

Elbow flexion

(A) (A)

(B)

Lateral output

Common input response

(B)

Lateral Output, less excitable, smaller (TMS)

No spinal plasticity

Elbow flexion

between ICN donor and MCN acceptor Interneurons

Lateral Input (fMRI)

Elbow flexion

(b)

(a)

(C)

(C)

FIGURE 64.7 (a) Schematic representation of the ICN-MCN transfer. (A) Normal innervation. The central motor program for elbow flexion is connected to the MCN and the central motor program for respiration and/or posture control is connected to the ICN. (B) Following transfer, central ICN motor programs become connected to the biceps. Initially, biceps contraction requires a voluntary respiratory effort. Central adaptation is required to regain independent control. Red arrows represent central input to the pyramidal tract. (C) No spinal plasticity. Neural activity in the original biceps area cannot excite ICN a-motor neurons because novel spinal pathways have not been formed. The “x” through the arrow indicates that such input or connections are not present. (b) Cortical plasticity following ICN-MCN transfer. (A) Neural input activity for volitional biceps control does not show plastic changes following ICN-MCN transfer. Red arrows represent central input to the pyramidal tract. The “x” through the arrow indicates that such input or connections are not present. (B) The center-of-gravity of the ICN-MCN biceps TMS map is indistinguishable from that of the normal biceps location and is different from that of the medial location of the intercostal muscles. These findings show that plastic changes occur in the neural output activity. (C) An interneuronal network between the ICN donor and the MCN acceptor creates an accessible output pathway by mediating the response to a common input. Used with permission from Anastakis et al. (2008). Originally from Malessy et al. (2003).

1066 PART VII The Future of Peripheral Nerve Injury

Normal innervation

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

For this to occur, the cortical neurons controlling the biceps muscle must respond to a central flexion motor program, and they must be linked, either directly or indirectly, with ICN alpha-motor neurons. This plasticity could arise from the formation of new connections between ICN and MCN neurons or from strengthening the activity of previously silent synaptic connections between ICNs and MCN neurons. Imaging studies have demonstrated that cortical plasticity occurs following ICN-MCN nerve transfer in patients with brachial plexus injury (Sokki, Bhat, & Devi, 2012); however, animal and imaging studies would suggest that this plasticity occurs supraspinally (Cheng, Shoung, Wu, Chen, & Lee, 1997; Kawai, 2000). Although axonal sprouting is an important element in cortical reorganization (Florence et al., 1996), the formation of new direct connections between flexion and intercostal corticospinal neurons would require axonal sprouting over a span of several centimeters. Moreover, the change in control from respiratory commands to voluntary flexion takes months rather than years (Malessy et al., 1993), suggesting that unmasking of existing connections is more probable. The effectiveness of ICN-MCN transfer may be due to a preexisting interneuronal network for coordination of the contraction of upper extremity and thoracic muscles involved in elbow flexion. Postural control over the thorax is an essential prerequisite for upper extremity movements, and flexing the elbow to lift an object requires simultaneous contraction of the intercostal muscle for thorax stabilization and postural control. The presence of existing intercortical connections between biceps and intercostal corticospinal neurons may explain why successful restoration of volitional control over biceps contraction is possible following ICN-MCN transfer but not hypoglossal-MCN transfer (Malessy, Hoffmann, & Thomeer, 1999). In order to become functionally effective, there needs to be a common input response between donor and acceptor (either from the same motor control area or a connection between areas). This has important implications for selection of donor nerves during nerve transfer. The ICN has also been transferred to the nerve of the triceps for restoration of elbow extension (Gao, Lao, Zhao, & Gu, 2013; Zheng, Xu, Qiu, Xu, & Gu, 2010). Given that thoracic muscles involved in elbow flexion are also involved in stabilizing the body during elbow extension, theoretically this transfer should also be effective. Zheng et al. (2010) reported poor recovery of triceps function after ICN transfer to the long head triceps branch when combined with phrenic nerve transfer to the MCN and suggested that that the poor outcomes were a result of pairing two donor nerves with synergistic function (phrenic nerve and ICNs for respiration) with two recipient nerves with antagonistic function (musculocutaneous and radial nerves for elbow flexion and extension, respectively). In contrast, Gao et al. (2013) observed good outcomes using the same

1067

technique and hypothesized that cortical areas for the phrenic nerve and ICNs are independent and should not affect each other despite having similar functions. Although both the phrenic and ICNs are involved in respiration and controlled by the motor control area for breathing, they may be preferentially involved in either inspiration or expiration and thus able to drive recipient nerves with antagonistic function. It was speculated that the results would have been different had they used multiple ICNs to repair both the MCN and the triceps branch simultaneously because a single motor program responsible for ICN donor control area might not be able to drive both flexion and extension.

Contralateral C7 Nerve Transfer The contralateral C7 (cC7) is another popular donor for nerve transfer because there is minimal or no long-term motor or sensory deficit following harvest (Liu, Pho, Kour, Zhang, & Ong, 1997). Restoration of elbow flexion has been described using the cC7 root as a donor nerve and the MCN or lateral cord as the recipient nerve (Gu et al., 1992). The donor C7 fibers are normally involved in adduction and extension of the intact arm. In contrast to ipsilateral transfers when the cC7 root is used as a donor nerve, the control of flexion of the reconstructed upper extremity is transferred from the contralateral cortex to the ipsilateral cortex. Initially, following reconstruction, the cerebral hemisphere ipsilateral to the reconstructed limb will control both extension of the intact limb and flexion of the reconstructed limb. Multiple studies of adult rats subjected to plexus injury and repair using cC7 nerve root suggest that following repair, the brain undergoes plastic changes in an attempt to restore the preinjury somatotopic representation of hemispheric laterality (Jiang et al., 2010; Lou, Shou, Li, Li, & Gu, 2006; Stephenson, Li, Yan, Hyde, & Matloub, 2013). Immediately following root avulsion, full loss of cortical activation is observed. At 3-5 months following the nerve transfer, motor control of the injured forepaw is located in the hemisphere ipsilateral to the injury. From 7 to 10 months, movement of the injured forepaw can be induced to varying degrees by stimulating the bilateral motor cortex. Divergence in degree of response to stimulation during this time may imply a divergence in individual functional recovery. At 8-16 months, the motor control of the affected forepaw returns exclusively to the contralateral hemisphere. These observations are supported by clinical studies. Beaulieu et al. (2006) used fMRI to study cortical activation following biceps reinnervation using a cC7 transfer to the MCN or lateral cord. At 1-2 years after repair, they observed cortical activation in the primary motor areas ipsilateral to the injured extremity during flexion of both the

1068 PART VII The Future of Peripheral Nerve Injury

normal and reconstructed limbs. Additionally, flexion of the reconstructed limb led to activation of the contralateral cortical network, meaning that the original motor control area was contributing to the control of elbow flexion through bilateral premotor and primary motor cortex connections (Beaulieu et al., 2006; Zuo et al., 2010). Interestingly, the location of activation in the hemisphere ipsilateral to the injured limb (now responsible for elbow flexion via the cC7 donor) was similar for all patients, whereas the location of activation in the hemisphere contralateral to the injured limb (the original motor control area prior to injury) was markedly different among patients. This heterogeneity likely reflects varying degrees of plasticity due to individual differences in preexisting bilateral motor network connections. The cC7 nerve has also been transferred to the median nerve for restoration of hand function. Initially following cC7 root transfers, patients find that they need to move their healthy arm in order to move the repaired arm (Gu, Xu, Chen, Wang, & Hu, 2002). This is similar to the cC7MCN transfer when patients must initially perform an extension adduction movement with their noninjured limb to illicit flexion in their reconstructed limb (Beaulieu et al., 2006). This coupling of voluntary and involuntary motor responses may represent a “signature” of the early stage toward recovery, during which the ipsilateral motor cortex is responsible for motor control of both extremities. At later intervals of the cC7-median nerve transfer, patients begin to flex their fingers on the injured side somewhat independently from the contralateral healthy arm, meaning that movement of the ipsilateral limb is controlled by activation in both motor cortexes. Less is known about longterm results in humans; however, some evidence suggests that cortical changes following cC7 nerve transfer are ongoing and persist long after the initial repair and recovery phase. Hua et al. (2013) observed that some patients eventually regain total independent control of the affected hand, which may represent plasticity resulting in a return of the preinjury somatotopic representation of the brain. It was suggested that the final exclusive contralateral motor control of the paralyzed hand might indicate good motor recovery following cC7 nerve transfer. Similarly, Dimou, Biggs, Tonkin, Hickie, and Lagopoulos (2013) performed a complete contralateral brachial plexus transfer for a single patient following amputation of one upper extremity and simultaneous complete plexus avulsion in the other. At 3 years and 8 months into recovery, the authors observed cortical activation in the hemisphere ipsilateral to the plexus injury during elbow flexion and finger-tapping motor tasks, suggesting the cortex mapping to the donor plexus was successfully controlling the reconstructed limb. During both tasks, the authors also observed activation in the hemisphere contralateral to the injured plexus that was more pronounced

during injured elbow flexion compared to finger tapping. Importantly, this discrepancy in activation correlated with the patient’s account that she no longer had to think about flexing her nonreconstructed extremity in order to elicit flexion in the elbow of her reconstructed extremity. Conversely, the finger-tapping exercise still required this concentration in order to achieve movement in the reinnervated hand. These observations, together with the knowledge that elbow flexion returned earlier and more completely, suggest that the degree of cortical reorganization may predict clinical outcomes and ease of movement during recovery. It is not known whether the level of independent control that can be attained following nerve transfer can be predicted or whether the quality of control is dependent on individual variations in preexisting intra- and interhemispheric coordination networks. Future advanced brain-imaging studies are needed to evaluate changes in connectivity within and between both hemispheres following nerve transfer.

Strategies for Sensory Reeducation Sensory reeducation is an integral component of rehabilitation following PNI, and the best outcome may be maximized by strategies that target sensorimotor control and cortical remapping (Novak, 2011) (Figure 64.8). Sensory reeducation is defined as “the gradual and progressive process of reprogramming the brain through the use of cognitive learning techniques such as visualization and verbalization, the use of alternate senses such as vision or hearing, and the use of graded tactile stimuli designed to maintain and/or restore sensory areas affected by nerve injury or compression to improve tactile gnosis” (Jerosch-Herold, 2011). Sensory reeducation treatments focus on strategies to alter the detrimental effects of deafferentation and are used to improve sensibility and simultaneously prevent development of chronic pain, allodynia, and hyperalgesia. A variety of techniques have been described involving stimulation with varying textures or localization, discrimination, and mobility tasks. In an attempt to optimize cortical remapping, task difficulty is increased to continually challenge the sensory system as sensibility improves (Novak & von der Heyde, 2013). Sensory reeducation programs typically commence as soon as there is evidence of sensory end-organ reinnervation, although early phase reeducation programs (including mirror imagery, temporary anesthesia, and audio-tactile and visuo-tactile training) before reinnervation have been described with the goal of promoting earlier cortical reorganization (Lundborg, Rose´n, & Lindberg, 1999; Rose´n, Bj€ orkman, & Lundborg, 2006; Rose´n & Lundborg, 2005, 2008). It is thought that sensory reeducation programs that use stimulation training improve pain and discriminative ability

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

1069

FIGURE 64.8 Principles for sensory reeducation following median nerve injury and repair. (a) Diagrammatic representation of normal “mapping” of a round ball in somatosensory cortex. (b) Following nerve transection and regenerating nerve fibers, the mapping is completely changed due to axonal misdirection and subsequent functional reorganization in the sensory cortex. (c, d) In the sensory reeducation program, visual and tactile impressions are combined to train the brain to understand the “new language spoken by the hand.” Used with permission from Lundborg (2000). Originally from Lundborg (1999).

via some sort of cortical reorganization. This could occur as the result of strengthening of synapses based on behaviorally relevant and temporally correlated inputs. In animals who were trained to detect frequency differences in tactile stimuli over a period of 20 weeks, frequency discrimination was accompanied by cortical changes in S1, including increased complexity of the cortical representations, increased cortical representation corresponding to the stimulated skin location, and larger receptive fields within the trained region (Recanzone, Jenkins, Hradek, & Merzenich, 1992; Recanzone, Merzenich, & Jenkins, 1992; Recanzone, Merzenich, & Schreiner, 1992). Comparable findings have been observed in patients with amputations (Flor, Denke, Schaefer, & Gru¨sser, 2001) and complex regional pain syndrome (Moseley, Zalucki, & Wiech, 2008). Similar to animal studies of behavioral training (Plautz, Milliken, & Nudo, 2000; Remple, Bruneau, VandenBerg, Goertzen, & Kleim, 2001), simply providing stimulation to the reinnervated area appears to be insufficient in inducing the desired changes in the sensory cortex unless the characteristics of the stimuli or the objective of the activity are perceived to be important in a functional context (Flor et al., 2001; Moseley & Flor, 2012).

Lotze et al. (1999) found that the use of a myoelectric prosthesis to provide sensory, visual, and motor feedback to amputee patients improved sensory outcomes and resulted in less cortical reorganization and less pain than those who used a simple cosmetic prosthesis. The authors observed that frequent use of the prosthesis negatively correlated with cortical reorganization of the lip into deafferented cortical areas and positively correlated with decreased phantom limb pain, suggesting that visual feedback, ongoing stimulation, and muscular training of the stump is preventive of maladaptive cortical plasticity in amputees. This suggests that it might be possible to prevent phantom pain and improve functional and symptomatic outcomes (Ehrsson, Spence, & Passingham, 2004).

Strategies to Improve Motor Function During the period from nerve injury to reinnervation, many patients develop altered compensatory movement patterns, muscle weakness, and altered sensorimotor cortical mapping. Because motor learning is also dependent on sensory input, ensuring optimal sensory function before undertaking motor reconstruction may be an important

1070 PART VII The Future of Peripheral Nerve Injury

strategy to consider in the reconstructive plans for patients with combined deficits. Following injury to a motor nerve resulting in muscle denervation, the initial repair must occur within the critical time window for reinnervation of the motor end plate after which muscle degeneration is not reversible and reinnervation is not possible (Fu & Gordon, 1995; Williams, 1996a, 1996b). Beyond this initial repair, the importance of cortical changes and plasticity in optimizing the motor outcomes cannot be overemphasized. Approaches to improve motor recovery have been directed toward enhancing nerve regeneration and decreasing the duration of denervation and promoting motor relearning. Proposed strategies include exercise training, the use of electrical stimulation, and biofeedback programs. Optimal recovery of muscle function occurs when a large number of motor axons are promptly supplied to denervated muscle. This can be challenging to accomplish partly because of slow, incomplete axonal regeneration that is subject to misdirection. Activity-dependent treatments including exercise and electrostimulation have been proposed as useful strategies to increase axonal regeneration and functional recovery after nerve lesions (Udina, Cobianchi, Allodi, & Navarro, 2011). These treatments are thought to benefit neuropathy through increased expression of fundamental neurotrophic factors that influence sensitization of neural networks. Following PNI and repair, regenerating axons in treadmill-trained animals elongate considerably farther than untrained controls without an increase in misdirection (English, Wilhelm, & Sabatier, 2011). Animal models demonstrate that electric stimulation of denervated muscle is useful to maintain muscle mass and force (Dow et al., 2004) while accelerating reinnervation and functional recovery (Ahlborn, Schachner, & Irintchev, 2007). Similarly, following sciatic nerve section and suture repair, rats that were subjected to forced treadmill running combined with electrical stimulation demonstrated enhanced motor and sensory reinnervation and expression of neurotransmitters with strong antianalgesic effects (Cobianchi, Casals-Diaz, Jaramillo, & Navarro, 2013). Benefits of electrostimulation have also been observed clinically with postoperative stimulation of the median nerve following carpal tunnel release, resulting in accelerated axonal regeneration and improved motor and sensory parameters (Gordon et al., 2009; Gordon, Amirjani, Edwards, & Chan, 2010). Because passive stimulation alone is insufficient to successfully establish a new motor program, patients must be encouraged to actively participate. To further optimize establishment of new sensorimotor patterns, addition of visual and auditory biofeedback to electrical simulation has been proposed (Novak & von der Heyde, 2013). Early during recovery, patients often experience difficulty isolating the intended muscle contraction when initiating a movement. Using

biofeedback to prevent of cocontraction of a stronger intact antagonistic muscle may be a useful strategy to assist with strengthening the weaker reinnervated one. Performance of any new motor task requires adaptability, efficiency, consistency, and opportunities for practice and repetition (Duff, 2005). Establishing new motor patterns following nerve transfer is especially challenging because the source of innervation to the reinnervated muscle is altered, meaning that cortical mapping and relearning become key factors in optimizing patient outcome. Studies that demonstrate cortical plasticity following nerve transfers emphasize that is necessary to establish new motor patterns and cortical mapping to reestablish functional use of the extremity (Anastakis et al., 2005; Chen, Anastakis, Haywood, Mikulis, & Manktelow, 2003). Wehrli et al. (2011) make several recommendations regarding optimization of the process of motor relearning following nerve transfer. Patients should practice the movements required to activate the nerve transfer in advance of the reconstruction and should be educated regarding the importance of early and long-term practice and repetition. Sensory and motor reeducation programs should consist of focused practice and repetition with a therapist. These programs should be initiated during early stages of motor learning and continued for at least 2 years following motor reinnervation. Studies in patients following free-functioning muscle transfers suggest that the process of motor reorganization continues to evolve and may be modified by training and experience long after motor reconstruction (Chen et al., 2003), meaning that there may be inherent value in increasing the duration of therapy beyond the traditional 2-year cut off. All rehabilitation programs following motor nerve transfers should include muscle strengthening with the emphasis on muscle balance, reeducation, cortical mapping, and normal motor patterns (Novak & von der Heyde, 2013). As recovery progresses, patients should be encouraged to perform activities that require the use of both extremities whenever possible. Bimanual tasks will integrate both the injured and uninjured limbs and provide the opportunity for input from the contralateral cortical region to normal movement patterns.

CONCLUSION Cortical plasticity is an important phenomenon that plays a key role in the outcome following peripheral nerve surgery. Following PNI, the CNS undergoes significant changes that may be either adaptive (e.g., motor relearning) or maladaptive (e.g., chronic pain). It is not known why some patients develop adaptive and others maladaptive cortical changes. Thus, new therapeutic interventions should move beyond simply enhancing axonal regeneration and promoting selective target reinnervation. Future research will

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

focus on specific “signatures” of cortical plasticity that are associated with superior or inferior outcomes, determination of whether those patterns can be modulated through pharmacologic or behavioral interventions, and determination of the optimal timing of such therapies (Stephenson et al., 2013). Additional advances in neuroimaging will further clarify brain function and regional interactions and inform the development of new cellular and molecular therapies. New therapies could manipulate cortical plasticity through pharmacologic means—perhaps even “priming” the brain to learn a new motor skill. In the future, surgeons could then work directly with neuroscientists and neurorehabilitation therapists to develop individualized treatment programs based on a patient’s specific “signature” of cortical plasticity leading to further improvements surgical outcomes.

REFERENCES Ahlborn, P., Schachner, M., Irintchev, A., 2007. One hour electrical stimulation accelerates functional recovery after femoral nerve repair. Experimental Neurology 208 (1), 137–144. Anastakis, D.J., Chen, R., Davis, K.D., Mikulis, D., 2005. Cortical plasticity following upper extremity injury and reconstruction. Clinics in Plastic Surgery 32 (4), 617–634. Anastakis, D.J., Malessy, M.J., Chen, R., Davis, K.D., Mikulis, D., 2008. Cortical plasticity following nerve transfer in the upper extremity. Hand Clinics 24 (4), 425–444. Anwyl, R., 1999. Metabotropic glutamate receptors: Electrophysiological properties and role in plasticity. Brain Research Reviews 29 (1), 83–120. Apkarian, A.V., Bushnell, M.C., Treede, R.D., Zubieta, J.K., 2005. Human brain mechanisms of pain perception and regulation in health and disease. European Journal of Pain 9 (4), 463–484. Apkarian, A.V., Sosa, Y., Sonty, S., Levy, R.M., Harden, R.N., Parrish, T.B., Gitelman, D.R., 2004. Chronic back pain is associated with decreased prefrontal and thalamic gray matter density. The Journal of Neuroscience 24 (46), 10410–10415. Arthurs, O.J., Boniface, S., 2002. How well do we understand the neural origins of the fMRI BOLD signal? Trends in Neurosciences 25 (1), 27–31. Ashburner, J., Friston, K.J., 2000. Voxel-based morphometry—The methods. NeuroImage 11, 805–821. Bao, L., Wang, H.F., Cai, H.J., Tong, Y.G., Jin, S.X., Lu, Y.J., et al., 2002. Peripheral axotomy induces only very limited sprouting of coarse myelinated afferents into inner lamina II of rat spinal cord. European Journal of Neuroscience 16 (2), 175–185. Barr, M.S., Farzan, F., Davis, K.D., Fitzgerald, P.B., Daskalakis, Z.J., 2013. Measuring GABAergic inhibitory activity with TMS-EEG and its potential clinical application for chronic pain. Journal of Neuroimmune Pharmacology 8, 535–546. Beaulieu, C., 2002. The basis of anisotropic water diffusion in the nervous system – A technical review. NMR in Biomedicine 15 (7-8), 435–455. Beaulieu, J.Y., Blustajn, J., Teboul, F., Baud, P., De Schonen, S., Thiebaud, J.B., Oberlin, C., 2006. Cerebral plasticity in crossed C7 grafts of the brachial plexus: An fMRI study. Microsurgery 26 (4), 303–310.

1071

Bermudez, P., Lerch, J.P., Evans, A.C., Zatorre, R.J., 2009. Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry. Cerebral Cortex 19 (7), 1583–1596. Bj€orkman, A., Rose´n, B., Lundborg, G., 2004. Acute improvement of hand sensibility after selective ipsilateral cutaneous forearm anaesthesia. European Journal of Neuroscience 20 (10), 2733–2736. Borsook, D., Becerra, L., Fishman, S., Edwards, A., Jennings, C.L., Stojanovic, M., et al., 1998. Acute plasticity in the human somatosensory cortex following amputation. NeuroReport 9 (6), 1013–1017. Byrne, J.H., 1997. Synapses plastic plasticity. Nature 389 (6653), 791–792. Byrne, J.A., Calford, M.B., 1991. Short-term expansion of receptive fields in rat primary somatosensory cortex after hindpaw digit denervation. Brain Research 565 (2), 218–224. Calford, M.B., Tweedale, R., 1988. Immediate and chronic changes in responses of somatosensory cortex in adult flying-fox after digit amputation. Nature 332 (6163), 446–448. Calford, M.B., Tweedale, R., 1990. Interhemispheric transfer of plasticity in the cerebral cortex. Science 249 (4970), 805–807. Chen, R., Anastakis, D.J., Haywood, C.T., Mikulis, D.J., Manktelow, R.T., 2003. Plasticity of the human motor system following muscle reconstruction: A magnetic stimulation and functional magnetic resonance imaging study. Clinical Neurophysiology 114 (12), 2434–2446. Chen, R., Cohen, L.G., Hallett, M., 2002. Nervous system reorganization following injury. Neuroscience 111 (4), 761–773. Cheng, H., Shoung, H.M., Wu, Z.A., Chen, K.C., Lee, L.S., 1997. Functional connectivity of the transected brachial plexus after intercostal neurotization in monkeys. The Journal of Comparative Neurology 380 (2), 155–163. Classen, J., Liepert, J., Wise, S.P., Hallett, M., Cohen, L.G., 1998. Rapid plasticity of human cortical movement representation induced by practice. Journal of Neurophysiology 79 (2), 1117–1123. Cobianchi, S., Casals-Diaz, L., Jaramillo, J., Navarro, X., 2013. Differential effects of activity dependent treatments on axonal regeneration and neuropathic pain after peripheral nerve injury. Experimental Neurology 240, 157–167. € Critchley, H.D., Wiens, S., Rotshtein, P., Ohman, A., Dolan, R.J., 2004. Neural systems supporting interoceptive awareness. Nature Neuroscience 7 (2), 189–195. Cusick, C.G., Wall, J.T., Whiting Jr., J.H., Wiley, R.G., 1990. Temporal progression of cortical reorganization following nerve injury. Brain Research 537 (1), 355–358. Dancause, N., Barbay, S., Frost, S.B., Plautz, E.J., Chen, D., Zoubina, E.V., et al., 2005. Extensive cortical rewiring after brain injury. The Journal of Neuroscience 25 (44), 10167–10179. Darian-Smith, C., Gilbert, C.D., 1994. Axonal sprouting accompanies functional reorganization in adult cat striate cortex. Nature 368 (6473), 737–740. Davis, K.D., Kiss, Z.H., Luo, L., Tasker, R.R., Lozano, A.M., Dostrovsky, J.O., 1998. Phantom sensations generated by thalamic microstimulation. Nature 391 (6665), 385–387. Davis, K.D., Moayedi, M., 2013. Central mechanisms of pain revealed through functional and structural MRI. Journal of Neuroimmune Pharmacology 8 (3), 518–534. Davis, K.D., Pope, G., Chen, J., Kwan, C.L., Crawley, A.P., Diamant, N.E., 2008. Cortical thinning in IBS: Implications for homeostatic, attention, and pain processing. Neurology 70 (2), 153–154. Davis, K.D., Taylor, K.S., Anastakis, D.J., 2011. Nerve injury triggers changes in the brain. The Neuroscientist 17 (4), 407–422.

1072 PART VII The Future of Peripheral Nerve Injury

Dayan, E., Censor, N., Buch, E.R., Sandrini, M., Cohen, L.G., 2013. Noninvasive brain stimulation: From physiology to network dynamics and back. Nature Neuroscience 16 (7), 838–844. De Troyer, A., Estenne, M., 1988. Functional anatomy of the respiratory muscles. Clinics in Chest Medicine 9 (2), 175. Dimou, S., Biggs, M., Tonkin, M., Hickie, I.B., Lagopoulos, J., 2013. Motor cortex neuroplasticity following brachial plexus transfer. Frontiers in Human Neuroscience 7, 500. Dostrovsky, J.O., Millar, J., Wall, P.D., 1976. The immediate shift of afferent drive of dorsal column nucleus cells following deafferentation: A comparison of acute and chronic deafferentation in gracile nucleus and spinal cord. Experimental Neurology 52 (3), 480–495. Dow, D.E., Cederna, P.S., Hassett, C.A., Kostrominova, T.Y., Faulkner, J. A., Dennis, R.G., 2004. Number of contractions to maintain mass and force of a denervated rat muscle. Muscle & Nerve 30 (1), 77–86. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., May, A., 2004. Neuroplasticity: Changes in grey matter induced by training. Nature 427 (6972), 311–312. Draganski, B., Moser, T., Lummel, N., Ga¨nssbauer, S., Bogdahn, U., Haas, F., May, A., 2006. Decrease of thalamic gray matter following limb amputation. NeuroImage 31 (3), 951–957. Duff, S.V., 2005. Impact of peripheral nerve injury on sensorimotor control. Journal of Hand Therapy 18 (2), 277–291. Dykes, R.W., Terzis, J.K., 1979. Reinnervation of glabrous skin in baboons: Properties of cutaneous mechanoreceptors subsequent to nerve crush. Journal of Neurophysiology 42 (5), 1461–1478. Ehrsson, H.H., Spence, C., Passingham, R.E., 2004. That’s my hand! Activity in premotor cortex reflects feeling of ownership of a limb. Science 305 (5685), 875–877. Elbert, T., Flor, H., Birbaumer, N., Knecht, S., Hampson, S., Larbig, W., Taub, E., 1994. Extensive reorganization of the somatosensory cortex in adult humans after nervous system injury. NeuroReport 5 (18), 2593–2597. Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B., Taub, E., 1995. Increased cortical representation of the fingers of the left hand in string players. Science 270 (5234), 305–307. English, A.W., Wilhelm, J.C., Sabatier, M.J., 2011. Enhancing recovery from peripheral nerve injury using treadmill training. Annals of Anatomy 193 (4), 354–361. Fawcett, J.W., Keynes, R.J., 1990. Peripheral nerve regeneration. Annual Review of Neuroscience 13 (1), 43–60. Fenrich, K., Gordon, T., 2003. Canadian Association of Neuroscience review: Axonal regeneration in the peripheral and central nervous systems – Current issues and advances. The Canadian Journal of Neurological Sciences 31 (2), 142–156. Finnerup, N.B., Nikolajsen, L., Jensen, T.S., 2012. Are we neglecting spinal reorganization following nerve damage? Pain 153 (2), 269–272. Fischl, B., Dale, A.M., 2000. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America 97 (20), 11050–11055. Flor, H., Denke, C., Schaefer, M., Gru¨sser, S., 2001. Effect of sensory discrimination training on cortical reorganisation and phantom limb pain. The Lancet 357 (9270), 1763–1764. Flor, H., Elbert, T., Knecht, S., Wienbruch, C., Pantev, C., Birbaumer, N., et al., 1995. Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation. Nature 375 (6531), 482–484.

Flor, H., Nikolajsen, L., Jensen, T.S., 2006. Phantom limb pain: A case of maladaptive CNS plasticity? Nature Reviews. Neuroscience 7 (11), 873–881. Florence, S.L., Garraghty, P.E., Wall, J.T., Kaas, J.H., 1994. Sensory afferent projections and area 3b somatotopy following median nerve cut and repair in macaque monkeys. Cerebral Cortex 4 (4), 391–407. Florence, S.L., Jain, N., Kaas, J.H., 1997. Plasticity of somatosensory cortex in primates. Seminars in Neuroscience 9 (1), 3–12. Florence, S.L., Jain, N., Pospichal, M.W., Beck, P.D., Sly, D.L., Kaas, J.H., 1996. Central reorganization of sensory pathways following peripheral nerve regeneration in fetal monkeys. Nature 381, 69–71. Florence, S.L., Kaas, J.H., 1995. Large-scale reorganization at multiple levels of the somatosensory pathway follows therapeutic amputation of the hand in monkeys. The Journal of Neuroscience 15 (12), 8083–8095. Fornander, L., Nyman, T., Hansson, T., Ragnehed, M., Brismar, T., 2010. Age-and time-dependent effects on functional outcome and cortical activation pattern in patients with median nerve injury: A functional magnetic resonance imaging study: Clinical article. Journal of Neurosurgery 113 (1), 122–128. Fu, S.Y., Gordon, T., 1995. Contributing factors to poor functional recovery after delayed nerve repair: Prolonged denervation. The Journal of Neuroscience 15 (5), 3886–3895. Gao, K., Lao, J., Zhao, X., Gu, Y., 2013. Outcome after transfer of intercostal nerves to the nerve of triceps long head in 25 adult patients with total brachial plexus root avulsion injury: Clinical article. Journal of Neurosurgery 118 (3), 606–610. Garraghty, P.E., Hanes, D.P., Florence, S.L., Kaas, J.H., 1994. Pattern of peripheral deafferentation predicts reorganizational limits in adult primate somatosensory cortex. Somatosensory & Motor Research 11 (2), 109–117. Garraghty, P.E., Muja, N., 1996. NMDA receptors and plasticity in adult primate somatosensory cortex. The Journal of Comparative Neurology 367 (2), 319–326. Geha, P.Y., Baliki, M.N., Harden, R.N., Bauer, W.R., Parrish, T.B., Apkarian, A.V., 2008. The brain in chronic CRPS pain: Abnormal gray-white matter interactions in emotional and autonomic regions. Neuron 60 (4), 570–581. Geuna, S., Tos, P., Battiston, B. (Eds.), 2009. Essays on peripheral nerve repair and regeneration. International Review of Neurobiology, Vol. 87, Academic Press, New York. Gilbert, C.D., Wiesel, T.N., 1992. Receptive field dynamics in adult primary visual cortex. Nature 356 (6365), 150–152. Gordon, T., Amirjani, N., Edwards, D.C., Chan, K.M., 2010. Brief postsurgical electrical stimulation accelerates axon regeneration and muscle reinnervation without affecting the functional measures in carpal tunnel syndrome patients. Experimental Neurology 223 (1), 192–202. Gordon, T., Chan, K.M., Sulaiman, O.A., Udina, E., Amirjani, N., Brushart, T.M., 2009. Accelerating axon growth to overcome limitations in functional recovery after peripheral nerve injury. Neurosurgery 65 (4), A132–A144. Gu, Y., Xu, J., Chen, L., Wang, H., Hu, S., 2002. Long term outcome of contralateral C7 transfer: A report of 32 cases. Chinese Medical Journal 115 (6), 866–868. Gu, Y.D., Zhang, G.M., Chen, D.S., Yan, J.G., Cheng, X.M., Chen, L., 1992. Seventh cervical nerve root transfer from the contralateral

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

healthy side for treatment of brachial plexus root avulsion. The Journal of Hand Surgery (British Volume) 17 (5), 518–521. Gustin, S.M., Peck, C.C., Cheney, L.B., Macey, P.M., Murray, G.M., Henderson, L.A., 2012. Pain and plasticity: Is chronic pain always associated with somatosensory cortex activity and reorganization? The Journal of Neuroscience 32 (43), 14874–14884. Heiss, W., Herholz, K., 2006. Brain receptor imaging. The Journal of Nuclear Medicine 46 (2), 302–312. Hickmott, P.W., Steen, P.A., 2005. Large-scale changes in dendritic structure during reorganization of adult somatosensory cortex. Nature Neuroscience 8 (2), 140–142. Hua, X.Y., Liu, B., Qiu, Y.Q., Tang, W.J., Xu, W.D., Liu, H.Q., et al., 2013. Long-term ongoing cortical remodeling after contralateral C-7 nerve transfer: Clinical article. Journal of Neurosurgery 118 (4), 725–729. Hutchinson, P.J., O’Connell, M.T., Kirkpatrick, P.J., Pickard, J.D., 2002. How can we measure substrate, metabolite and neurotransmitter concentrations in the human brain? Physiological Measurement 23 (2), 75. Jacobs, K.M., Donoghue, J.P., 1991. Reshaping the cortical motor map by unmasking latent intracortical connections. Science 251 (4996), 944–947. Jain, N., Florence, S.L., Kaas, J.H., 1998. Reorganization of somatosensory cortex after nerve and spinal cord injury. Physiology 13 (3), 143–149. Jain, N., Florence, S.L., Qi, H.X., Kaas, J.H., 2000. Growth of new brainstem connections in adult monkeys with massive sensory loss. Proceedings of the National Academy of Sciences of the United States of America 97 (10), 5546–5550. Jenkins, W.M., Merzenich, M.M., Ochs, M.T., Allard, T., Guic-Robles, E., 1990. Functional reorganization of primary somatosensory cortex in adult owl monkeys after behaviorally controlled tactile stimulation. Journal of Neurophysiology 63 (1), 82–104. Jensen, T.S., Baron, R., 2003. Translation of symptoms and signs into mechanisms in neuropathic pain. Pain 102 (1), 1–8. Jerosch-Herold, C., 2011. Sensory relearning in peripheral nerve disorders of the hand: A web-based survey and delphi consensus method. Journal of Hand Therapy 24 (4), 292–299. Jiang, S., Li, Z.Y., Hua, X.Y., Xu, W.D., Xu, J.G., Gu, Y.D., 2010. Reorganization in motor cortex after brachial plexus avulsion injury and repair with the contralateral C7 root transfer in rats. Microsurgery 30 (4), 314–320. Jurkiewicz, M.T., Crawley, A.P., Verrier, M.C., Fehlings, M.G., Mikulis, D.J., 2006. Somatosensory cortical atrophy after spinal cord injury: A voxelbased morphometry study. Neurology 66 (5), 762–764. Kaas, J.H., 1991. Plasticity of sensory and motor maps in adult mammals. Annual Review of Neuroscience 14 (1), 137–167. Kaas, J.H., Florence, S.L., 1997. Mechanisms of reorganization in sensory systems of primates after peripheral nerve injury. Advances in Neurology 73, 147. Karni, A., Meyer, G., Jezzard, P., Adams, M.M., Turner, R., Ungerleider, L.G., 1995. Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature 377, 155–158. Katz, J., Melzack, R., 1990. Pain ‘memories’ in phantom limbs: Review and clinical observations. Pain 43 (3), 319–336. Kawai, H., 2000. Intercostal nerve transfer. In: Kawai, H., Kawabata, H. (Eds.), Brachial plexus palsy. World Scientific, Singapore, pp. 161–236. Klingner, C.M., Volk, G.F., Maertin, A., Brodoehl, S., Burmeister, H.P., Guntinas-Lichius, O., Witte, O.W, 2011. Cortical reorganization in Bell’s palsy. Restorative Neurology and Neuroscience 29 (3), 203–214.

1073

Leechavengvongs, S., Witoonchart, K., Uerpairojkit, C., Thuvasethakul, P., Ketmalasiri, W., 1998. Nerve transfer to biceps muscle using a part of the ulnar nerve in brachial plexus injury (upper arm type): A report of 32 cases. The Journal of Hand Surgery 23 (4), 711–716. Lehmann, H.C., Zhang, J., Mori, S., Sheikh, K.A., 2010. Diffusion tensor imaging to assess axonal regeneration in peripheral nerves. Experimental Neurology 223 (1), 238–244. Li, R., Hettinger, P.C., Machol, J.A., Liu, X., Stephenson, J.B., Pawela, C. P., et al., 2013. Cortical plasticity induced by different degrees of peripheral nerve injuries: A rat functional magnetic resonance imaging study under 9.4 Tesla. Journal of Brachial Plexus and Peripheral Nerve Injury 8 (1), 4. Liss, A.G., Af Ekenstam, F.W., Wiberg, M., 1996. Loss of neurons in the dorsal hoot ganglia after transection of a peripheral sensory nerve: An anatomical study in monkeys. Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery 30 (1), 1–6. Liu, B., Li, T., Tang, W.J., Zhang, J.H., Sun, H.P., Xu, W.D., et al., 2013. Changes of inter-hemispheric functional connectivity between motor cortices after brachial plexuses injury: A resting-state fMRI study. Neuroscience 243, 33–39. Liu, J., Pho, R.W., Kour, A.K., Zhang, A.H., Ong, B.K., 1997. Neurologic deficit and recovery in the donor limb following cross-C7 transfer in brachial-plexus injury. Journal of Reconstructive Microsurgery 13 (04), 237–242. Logothetis, N.K., Wandell, B.A., 2004. Interpreting the BOLD signal. Annual Review of Physiology 66, 735–769. Lotze, M., Flor, H., Grodd, W., Larbig, W., Birbaumer, N., 2001. Phantom movements and pain. An fMRI study in upper limb amputees. Brain 124 (11), 2268–2277. Lotze, M., Grodd, W., Birbaumer, N., Erb, M., Huse, E., Flor, H., 1999. Does use of a myoelectric prosthesis prevent cortical reorganization and phantom limb pain? Nature Neuroscience 2 (6), 501–502. Lou, L., Shou, T., Li, Z., Li, W., Gu, Y., 2006. Transhemispheric functional reorganization of the motor cortex induced by the peripheral contralateral nerve transfer to the injured arm. Neuroscience 138 (4), 1225–1231. Lundborg, G., 1988. Nerve injury and repair. Churchill Livingstone, Edinburgh. Lundborg, G., 1999. Handkirurgi-skador, sjukdomar, diagnostik och behandling. Studentlitteratur, Lund. Lundborg, G., 2000. Brain plasticity and hand surgery: An overview. The Journal of Hand Surgery (British Volume) 25 (3), 242–252. Lundborg, G., 2005. Nerve injury and repair: Regeneration, reconstruction, and cortical remodeling, 2nd ed. Churchill Livingstone, Philadelphia. Lundborg, G., Rose´n, B., 2007. Hand function after nerve repair. Acta Physiologica 189 (2), 207–217. Lundborg, G., Rose´n, B., Lindberg, S., 1999. Hearing as substitution for sensation: A new principle for artificial sensibility. The Journal of Hand Surgery 24 (2), 219–224. Maguire, E.A., Gadian, D.G., Johnsrude, I.S., Good, C.D., Ashburner, J., Frackowiak, R.S., Frith, C.D., 2000. Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences of the United States of America 97 (8), 4398–4403. Malessy, M.J., Bakker, D., Dekker, A.J., van Dijk, J.G., Thomeer, R.T., 2003. Functional magnetic resonance imaging and control over the biceps muscle after intercostal-musculocutaneous nerve transfer. Journal of Neurosurgery 98 (2), 261–268.

1074 PART VII The Future of Peripheral Nerve Injury

Malessy, M.J., Hoffmann, C.F., Thomeer, R.T., 1999. Initial report on the limited value of hypoglossal nerve transfer to treat brachial plexus root avulsions. Journal of Neurosurgery 91 (4), 601–604. Malessy, M.J., Thomeer, R.T., 1998. Evaluation of intercostal to musculocutaneous nerve transfer in reconstructive brachial plexus surgery. Journal of Neurosurgery 88 (2), 266–271. Malessy, M.J., van der Kamp, W., Thomeer, R.T., van Dijk, J.G., 1998. Cortical excitability of the biceps muscle after intercostal-tomusculocutaneous nerve transfer. Neurosurgery 42 (4), 787–794. Malessy, M.J., van Dijk, J.G., Thomeer, R.T., 1993. Respiration-related activity in the biceps brachii muscle after intercostal-musculocutaneous nerve transfer. Clinical Neurology & Neurosurgery 95, 95–102. Manduch, M., Bezuhly, M., Anastakis, D.J., Crawley, A.P., Mikulis, D.J., 2002. Serial fMRI of adaptive changes in primary sensorimotor cortex following thumb reconstruction. Neurology 59 (8), 1278–1281. Mano, Y., Nakamuro, T., Tamural, R., Takayanagi, T., Kawanishi, K., Tamai, S., Mayer, R.E., 1995. Central motor reorganization after anastomosis of the musculocutaneous and intercostal nerves following cervical root avulsion. Annals of Neurology 38 (1), 15–20. May, A., Hajak, G., Ga¨nssbauer, S., Steffens, T., Langguth, B., Kleinjung, T., Eichhammer, P., 2007. Structural brain alterations following 5 days of intervention: Dynamic aspects of neuroplasticity. Cerebral Cortex 17 (1), 205–210. McAllister, R.M.R., Calder, J.S., 1995. Paradoxical clinical consequences of peripheral nerve injury: A review of anatomical, neurophysiological and psychological mechanisms. British Journal of Plastic Surgery 48 (6), 384–395. McAllister, A.K., Katz, L.C., Lo, D.C., 1999. Neurotrophins and synaptic plasticity. Annual Review of Neuroscience 22 (1), 295–318. Melzack, R., 1990. Phantom limbs and the concept of a neuromatrix. Trends in Neurosciences 13 (3), 88–92. Melzack, R., Coderre, T.J., Katz, J., Vaccarino, A.L., 2001. Central neuroplasticity and pathological pain. Annals of the New York Academy of Sciences 933 (1), 157–174. Merzenich, M.M., Jenkins, W.M., 1993. Reorganization of cortical representations of the hand following alterations of skin inputs induced by nerve injury, skin island transfers, and experience. Journal of Hand Therapy 6 (2), 89–104. Merzenich, M.M., Kaas, J.H., Sur, M., Lin, C.S., 1978. Double representation of the body surface within cytoarchitectonic area 3b and 1 in “SI” in the owl monkey (Aotus trivirgatus). The Journal of Comparative Neurology 181 (1), 41–73. Merzenich, M.M., Kaas, J.H., Wall, J., Nelson, R.J., Sur, M., Felleman, D., 1983. Topographic reorganization of somatosensory cortical areas 3b and 1 in adult monkeys following restricted deafferentation. Neuroscience 8 (1), 33–55. Merzenich, M.M., Kaas, J.H., Wall, J.T., Sur, M., Nelson, R.J., Felleman, D.J., 1983. Progression of change following median nerve section in the cortical representation of the hand in areas 3b and 1 in adult owl and squirrel monkeys. Neuroscience 10 (3), 639–665. Merzenich, M.M., Nelson, R.J., Kaas, J.H., Stryker, M.P., Jenkins, W.M., Zook, J.M., et al., 1987. Variability in hand surface representations in areas 3b and 1 in adult owl and squirrel monkeys. The Journal of Comparative Neurology 258 (2), 281–296. Merzenich, M.M., Nelson, R.J., Stryker, M.P., Cynader, M.S., Schoppmann, A., Zook, J.M., 1984. Somatosensory cortical map changes following digit amputation in adult monkeys. The Journal of Comparative Neurology 224 (4), 591–605.

Millar, J., Basbaum, A.I., Wall, P.D., 1976. Restructuring of the somatotopic map and appearance of abnormal neuronal activity in the gracile nucleus after partial deafferentation. Experimental Neurology 50 (3), 658–672. Mogilner, A., Grossman, J.A., Ribary, U., Joliot, M., Volkmann, J., Rapaport, D., et al., 1993. Somatosensory cortical plasticity in adult humans revealed by magnetoencephalography. Proceedings of the National Academy of Sciences of the United States of America 90 (8), 3593–3597. Mori, S., Zhang, J., 2006. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51 (5), 527–539. Moseley, G.L., Flor, H., 2012. Targeting cortical representations in the treatment of chronic pain: A review. Neurorehabilitation & Neural Repair 26 (6), 646–652. Moseley, G.L., Gallace, A., Spence, C., 2012. Bodily illusions in health and disease: Physiological and clinical perspectives and the concept of a cortical ‘body matrix’. Neuroscience & Biobehavioral Reviews 36 (1), 34–46. Moseley, G.L., Zalucki, N.M., Wiech, K., 2008. Tactile discrimination, but not tactile stimulation alone, reduces chronic limb pain. Pain 137 (3), 600–608. Napadow, V., Kettner, N., Ryan, A., Kwong, K.K., Audette, J., Hui, K.K., 2006. Somatosensory cortical plasticity in carpal tunnel syndrome – A cross-sectional fMRI evaluation. NeuroImage 31 (2), 520–530. Narakas, A.O., 1984. Thoughts on neurotization or nerve transfers in irreparable nerve lesions. Clinics in Plastic Surgery 11 (1), 153–159. Navarro, X., 2009. Neural plasticity after nerve injury and regeneration. International Review of Neurobiology 87, 483–505. Navarro, X., Vivo´, M., Valero-Cabre´, A., 2007. Neural plasticity after peripheral nerve injury and regeneration. Progress in Neurobiology 82 (4), 163–201. Niekel, M.C., Lindenhovius, A.L., Watson, J.B., Vranceanu, A.M., Ring, D., 2009. Correlation of DASH and QuickDASH with measures of psychological distress. The Journal of Hand Surgery 34 (8), 1499–1505. Novak, C.B., 2011. Clinical commentary in response to: Sensory relearning in peripheral nerve disorders of the hand: A web-based survey and Delphi consensus method. Journal of Hand Therapy 24 (4), 300–302. Novak, C.B., Anastakis, D.J., Beaton, D.E., Mackinnon, S.E., Katz, J., 2011. Biomedical and psychosocial factors associated with disability after peripheral nerve injury. The Journal of Bone & Joint Surgery. American Volume 93 (10), 929–936. Novak, C.B., Katz, J., 2010. Neuropathic pain in patients with upperextremity nerve injury. Physiotherapy Canada 62 (3), 190–201. Novak, C.B., von der Heyde, R.L., 2013. Evidence and techniques in rehabilitation following nerve injuries. Hand Clinics 29 (3), 383–392. Oberlin, C., Beal, D., Leechavengvongs, S., Salon, A., Dauge, M.C., Sarcy, J.J., 1994. Nerve transfer to biceps muscle using a part of ulnar nerve for C5–C6 avulsion of the brachial plexus: Anatomical study and report of four cases. The Journal of Hand Surgery 19 (2), 232–237. Ogawa, S., Lee, T.M., Nayak, A.S., Glynn, P., 1990. Oxygenationsensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magnetic Resonance in Medicine 14 (1), 68–78. Omura, K., Constable, R.T., Canli, T., 2005. Amygdala gray matter concentration is associated with extraversion and neuroticism. NeuroReport 16 (17), 1905–1908.

Cortical Plasticity After Peripheral Nerve Injury Chapter 64

Pascual-Leone, A., 1999. Transcranial magnetic stimulation: Studying the brain–behaviour relationship by induction of ’virtual lesions’. Philosophical Transactions of the Royal Society of London 354 (1387), 1229–1238. Pascual-Leone, A., Torres, F., 1993. Plasticity of the sensorimotor cortex representation of the reading finger in Braille readers. Brain 116, 39–52. Pelled, G., Chuang, K.H., Dodd, S.J., Koretsky, A.P., 2007. Functional MRI detection of bilateral cortical reorganization in the rodent brain following peripheral nerve deafferentation. NeuroImage 37 (1), 262–273. Plautz, E.J., Milliken, G.W., Nudo, R.J., 2000. Effects of repetitive motor training on movement representations in adult squirrel monkeys: Role of use versus learning. Neurobiology of Learning and Memory 74 (1), 27–55. Pons, T.P., Garraghty, P.E., Ommaya, A.K., Kaas, J.H., Taub, E., Mishkin, M., 1991. Massive cortical reorganization after sensory deafferentation in adult macaques. Science 252, 1857–1860. Raichle, M.E., Martin, W.R.W., Herscovitch, P., Mintun, M.A., Markham, J., 1973. Brain blood flow measured with intravenous H15 2 O. II. Implementation and validation. Journal of Nuclear Medicine 24, 790–798. Ravnborg, M., Blinkenberg, M., Dahl, K., 1991. Standardization of facilitation of compound muscle action potentials evoked by magnetic stimulation of the cortex. Results in healthy volunteers and in patients with multiple sclerosis. Electroencephalography and Clinical Neurophysiology 81 (3), 195–201. Raznahan, A., Lerch, J.P., Lee, N., Greenstein, D., Wallace, G.L., Stockman, M., et al., 2011. Patterns of coordinated anatomical change in human cortical development: A longitudinal neuroimaging study of maturational coupling. Neuron 72 (5), 873–884. Recanzone, G.H., Jenkins, W.M., Hradek, G.T., Merzenich, M.M., 1992. Progressive improvement in discriminative abilities in adult owl monkeys performing a tactile frequency discrimination task. Journal of Neurophysiology 67 (5), 1015–1030. Recanzone, G.H., Merzenich, M.M., Jenkins, W.M., 1992. Frequency discrimination training engaging a restricted skin surface results in an emergence of a cutaneous response zone in cortical area 3a. Journal of Neurophysiology 67 (5), 1057–1070. Recanzone, G.H., Merzenich, M.M., Schreiner, C.E., 1992. Changes in the distributed temporal response properties of SI cortical neurons reflect improvements in performance on a temporally based tactile discrimination task. Journal of Neurophysiology 67 (5), 1071–1091. Reivich, M., Kuhl, D., Wolf, A., Greenberg, J., Phelps, M., Ido, T., et al., 1979. The [18F]fluorodeoxyglucose method for the measurement of local cerebral glucose utilization in man. Circulation Research 44, 127–137. Remple, M.S., Bruneau, R.M., VandenBerg, P.M., Goertzen, C., Kleim, J.A., 2001. Sensitivity of cortical movement representations to motor experience: Evidence that skill learning but not strength training induces cortical reorganization. Behavioural Brain Research 123 (2), 133–141. Rose´n, B., Bj€ orkman, A., Lundborg, G., 2006. Improved sensory relearning after nerve repair induced by selective temporary anaesthesia – a new concept in hand rehabilitation. The Journal of Hand Surgery (British Volume) 31 (2), 126–132. Rose´n, B., Chemnitz, A., Weibull, A., Andersson, G., Dahlin, L.B., Bj€ orkman, A., 2012. Cerebral changes after injury to the median nerve: A long-term follow up. Journal of Plastic Surgery and Hand Surgery 46 (2), 106–112.

1075

Rose´n, B., Lundborg, G., 2005. Training with a mirror in rehabilitation of the hand. Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery 39 (2), 104–108. Rose´n, B., Lundborg, G., 2008. Sensory re-education following nerve repair. In: Slutsky, D.J. (Ed.), Upper extremity nerve repair – Tips and techniques: A master skills publication. American Society for Surgery of the Hand, Rosemont, IL, pp. 159–178. Rossini, P.M., Rossi, S., Tecchio, F., Pasqualetti, P., Finazzi-Agro`, A., Sabato, A., 1996. Focal brain stimulation in healthy humans: Motor maps changes following partial hand sensory deprivation. Neuroscience Letters 214 (2), 191–195. Rothwell, J.C., Thompson, P.D., Day, B.L., Boyd, S., Marsden, C.D., 1991. Stimulation of the human motor cortex through the scalp. Experimental Physiology 76 (2), 159–200. Sagi, Y., Tavor, I., Hofstetter, S., Tzur-Moryosef, S., BlumenfeldKatzir, T., Assaf, Y., 2012. Learning in the fast lane: New insights into neuroplasticity. Neuron 73 (6), 1195–1203. Sengelaub, D.R., Muja, N., Mills, A.C., Myers, W.A., Churchill, J.D., Garraghty, P.E., 1997. Denervation-induced sprouting of intact peripheral afferents into the cuneate nucleus of adult rats. Brain Research 769 (2), 256–262. Severeijns, R., Vlaeyen, J.W., van den Hout, M.A., Weber, W.E., 2001. Pain catastrophizing predicts pain intensity, disability, and psychological distress independent of the level of physical impairment. The Clinical Journal of Pain 17 (2), 165–172. Silva, A.C., Rasey, S.K., Wu, X., Wall, J.T., 1996. Initial cortical reactions to injury of the median and radial nerves to the hands of adult primates. The Journal of Comparative Neurology 366 (4), 700–716. Sokki, A.M., Bhat, D.I., Devi, B.I., 2012. Cortical reorganization following neurotization: A diffusion tensor imaging and functional magnetic resonance imaging study. Neurosurgery 70 (5), 1305–1311. Stephenson IV, J.B., Li, R., Yan, J.G., Hyde, J., Matloub, H., 2013. Transhemispheric cortical plasticity following contralateral C7 nerve transfer: A rat functional magnetic resonance imaging survival study. The Journal of Hand Surgery 38 (3), 478–487. Sullivan, M.J., Lynch, M.E., Clark, A.J., 2005. Dimensions of catastrophic thinking associated with pain experience and disability in patients with neuropathic pain conditions. Pain 113 (3), 310–315. Takagi, T., Nakamura, M., Yamada, M., Hikishima, K., Momoshima, S., Fujiyoshi, K., et al., 2009. Visualization of peripheral nerve degeneration and regeneration: Monitoring with diffusion tensor tractography. NeuroImage 44 (3), 884–892. Taub, E., Uswatte, G., Elbert, T., 2002. New treatments in neurorehabiliation founded on basic research. Nature Reviews. Neuroscience 3 (3), 228–236. Taubert, M., Draganski, B., Anwander, A., Mu¨ller, K., Horstmann, A., Villringer, A., Ragert, P., 2010. Dynamic properties of human brain structure: Learning-related changes in cortical areas and associated fiber connections. The Journal of Neuroscience 30 (35), 11670–11677. Taylor, A., 1960. The contribution of the intercostal muscles to the effort of respiration in man. The Journal of Physiology 151 (2), 390–402. Taylor, K.S., Anastakis, D.J., Davis, K.D., 2009. Cutting your nerve changes your brain. Brain 132 (11), 3122–3133. Taylor, K.S., Anastakis, D.J., Davis, K.D., 2010. Chronic pain and sensorimotor deficits following peripheral nerve injury. Pain 151 (3), 582–591. Terzis, J.K., Dykes, R.W., 1980. Reinnervation of glabrous skin in baboons: Properties of cutaneous mechanoreceptors subsequent to nerve transection. Journal of Neurophysiology 44 (6), 1214–1225.

1076 PART VII The Future of Peripheral Nerve Injury

Tos, P., Ronchi, G., Geuna, S., Battiston, B., 2012. Future perspectives in nerve repair and regeneration. International Review of Neurobiology 109, 165–192. Udina, E., Cobianchi, S., Allodi, I., Navarro, X., 2011. Effects of activitydependent strategies on regeneration and plasticity after peripheral nerve injuries. Annals of Anatomy 193 (4), 347–353. Wall, P.D., Egger, M.D., 1971. Formation of new connections in adult rat brains after partial deafferentation. Nature 232, 542–545. Wall, J.T., Felleman, D.J., Kaas, J.H., 1983. Recovery of normal topography in the somatosensory cortex of monkeys after nerve crush and regeneration. Science 221 (4612), 771–773. Wall, J.T., Kaas, J.H., Sur, M., Nelson, R.J., Felleman, D.J., Merzenich, M. M., 1986. Functional reorganization in somatosensory cortical areas 3b and 1 of adult monkeys after median nerve repair: Possible relationships to sensory recovery in humans. The Journal of Neuroscience 6 (1), 218–233. Wall, J.T., Xu, J., Wang, X., 2002. Human brain plasticity: An emerging view of the multiple substrates and mechanisms that cause cortical changes and related sensory dysfunctions after injuries of sensory inputs from the body. Brain Research Reviews 39 (2), 181–215. Weeks, S.R., Tsao, J.W., 2010. Incorporation of another person’s limb into body image relieves phantom limb pain: A case study. Neurocase 16 (6), 461–465. Wehrli, L., Bonnard, C., Anastakis, D.J., 2011. Current status of brachial plexus reconstruction: Restoration of hand function. Clinics in Plastic Surgery 38 (4), 661–681. Wiech, K., Ploner, M., Tracey, I., 2008. Neurocognitive aspects of pain perception. Trends in Cognitive Sciences 12 (8), 306–313. Williams, H.B., 1996a. A clinical pilot study to assess functional return following continuous muscle stimulation after nerve injury and repair

in the upper extremity using a completely implantable electrical system. Microsurgery 17 (11), 597–605. Williams, H.B., 1996b. The value of continuous electrical muscle stimulation using a completely implantable system in the preservation of muscle function following motor nerve injury and repair: An experimental study. Microsurgery 17 (11), 589–596. Woolf, C.J., Salter, M.W., 2000. Neuronal plasticity: Increasing the gain in pain. Science 288 (5472), 1765–1768. Wu, C.W.H., Kaas, J.H., 2002. The effects of long-standing limb loss on anatomical reorganization of the somatosensory afferents in the brainstem and spinal cord. Somatosensory & Motor Research 19 (2), 153–163. Yamahachi, H., Marik, S.A., McManus, J.N., Denk, W., Gilbert, C.D., 2009. Rapid axonal sprouting and pruning accompany functional reorganization in primary visual cortex. Neuron 64 (5), 719–729. Yang, T.T., Gallen, C.C., Ramachandran, V.S., Cobb, S., Schwartz, B.J., Bloom, F.E., 1994. Noninvasive detection of cerebral plasticity in adult human somatosensory cortex. NeuroReport 5, 701–704. Zatorre, R.J., Fields, R.D., Johansen-Berg, H., 2012. Plasticity in gray and white: Neuroimaging changes in brain structure during learning. Nature Neuroscience 15 (4), 528–536. Zheng, M.X., Xu, W.D., Qiu, Y.Q., Xu, J.G., Gu, Y.D., 2010. Phrenic nerve transfer for elbow flexion and intercostal nerve transfer for elbow extension. The Journal of Hand Surgery 35 (8), 1304–1309. Zochodne, D.W., 2008. Neurobiology of peripheral nerve regeneration. Cambridge University Press, Cambridge. Zuo, C.T., Hua, X.Y., Guan, Y.H., Xu, W.D., Xu, J.G., Gu, Y.D., 2010. Long-range plasticity between intact hemispheres after contralateral cervical nerve transfer in humans: Clinical article. Journal of Neurosurgery 113 (1), 133–140.