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Long-term plasticity in adult somatosensory cortex: functional reorganization after surgical removal of an arteriovenous malformation ab

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Hana Burianová , Anina N. Rich , Mark Williams , Michael Morgan , Lars Marstaller , Paul e

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Maruff , Chris I. Baker & Greg Savage a

Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia

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ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, Australia

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Department of Cognitive Science, Macquarie University, Sydney, Australia

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Australian School of Advanced Medicine, Macquarie University, Sydney, Australia

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CogState Ltd, Melbourne, Australia

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Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA g

Department of Psychology, Macquarie University, Sydney, Australia Published online: 29 Sep 2014.

To cite this article: Hana Burianová, Anina N. Rich, Mark Williams, Michael Morgan, Lars Marstaller, Paul Maruff, Chris I. Baker & Greg Savage (2015) Long-term plasticity in adult somatosensory cortex: functional reorganization after surgical removal of an arteriovenous malformation, Neurocase: The Neural Basis of Cognition, 21:5, 618-627, DOI: 10.1080/13554794.2014.960429 To link to this article: http://dx.doi.org/10.1080/13554794.2014.960429

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Neurocase, 2015 Vol. 21, No. 5, 618–627, http://dx.doi.org/10.1080/13554794.2014.960429

Long-term plasticity in adult somatosensory cortex: functional reorganization after surgical removal of an arteriovenous malformation Hana Burianováa,b*, Anina N. Richb,c, Mark Williamsb,c, Michael Morgand, Lars Marstallerb,c, Paul Maruffe, Chris I. Bakerf and Greg Savageb,g a

Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; bARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, Australia; cDepartment of Cognitive Science, Macquarie University, Sydney, Australia; d Australian School of Advanced Medicine, Macquarie University, Sydney, Australia; eCogState Ltd, Melbourne, Australia; fLaboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; gDepartment of Psychology, Macquarie University, Sydney, Australia

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(Received 19 February 2014; accepted 26 August 2014) The temporal scale of neuroplasticity following acute alterations in brain structure due to neurosurgical intervention is still under debate. We conducted a longitudinal study with the objective of investigating the postoperative changes in a patient who underwent cerebrovascular surgery and who subsequently lost proprioception in the fingers of her right hand. The results show increased activation in contralesional somatosensory areas, additional recruitment of premotor and posterior parietal areas, and changes in functional connectivity with left postcentral gyrus. These findings demonstrate long-term modifications of cortical organization and as such have important implications for treatment strategies for patients with brain injury. Keywords: neuroplasticity; somatosensory; fMRI; proprioception; AVM

Neural plasticity is an intrinsic property of the central nervous system (CNS) that reflects changes in the properties of neural circuits in response to alterations in behavioral, environmental, or physiological conditions (Duffau, 2006; Pascual-Leone et al., 2011). Due to converging empirical findings, there is now a consensus that the brain is continuously changing throughout the life span (Johansson, 2004; Pascual-Leone, Amedi, Fregni, & Merabet, 2005) and that plasticity takes place at multiple loci in the nervous system, spanning from local cellular changes to reorganization of large-scale networks (Pascual-Leone et al., 2011). These plastic changes are responsible for everyday learning and adaptation to novel experiences, as well as for recovery from injury. Studies have demonstrated experience-dependent cortical reorganization following learning of complex visual motion (Draganski et al., 2004), fine motor skills (PascualLeone et al., 1995), highly abstract information (Draganski et al., 2006), and novel speech sounds (Golestani, Paus, & Zatorre, 2002), as well as plastic changes in individuals with expertise, such as trained musicians (Gaser & Schlaug, 2003), experienced taxi drivers (Maguire et al., 2000), expert phoneticians (Golestani, Price, & Scott, 2011), or blind Braille readers (Pascual-Leone & Torres, 1993). Post-lesion plasticity has been evidenced in studies showing functional reorganization of cortical and subcortical areas in patients with CNS lesions due to stroke *Corresponding author. Email: [email protected] © 2014 Taylor & Francis

(Wang et al., 2010; Weiller, Chollet, Friston, Wise, & Frackowiak, 1992) or arteriovenous malformations (AVMs; Alkadhi et al., 2000; Ducreux et al., 2004), as well as in patients with amputated limbs (Chen, Corwell, Yaseen, Hallett, & Cohen, 1998; Lotze, Flor, Grodd, Larbig, & Birbaumer, 2001), and in those suffering from chronic pain (Flor, Braun, Elbert, & Birbaumer, 1997; Vartiainen, Kirveskari, Kallio-Laine, Kalso, & Forss, 2009). In general, human plasticity studies are either experimental in healthy individuals (e.g., imaging the hippocampus in taxi drivers) or opportunistic in patients (e.g., comparing visual cortex in blind vs. sighted people). Despite extensive investigations of the characteristics of neural plasticity, our understanding of its underlying cellular mechanisms, time course, and relation to environmental effects is still incomplete. One of the critical issues involves the temporal scale of plastic changes. Some processes, such as long-term potentiation or long-term depression (Hess, Aizenman, & Donoghue, 1996; Hess & Donoghue, 1996), occur relatively fast, reflecting a reactive response to a disrupted equilibrium of excitation and inhibition (Xerri, 2008), whereas processes such as sprouting of axons or synaptogenesis (Toni, Buchs, Nikonenko, Bron, & Muller, 1999) may take months or years and are mediated and modulated by novel experiences and learning of new skills (Xerri, 2008). Thus, longitudinal examination of plastic changes is critically important in order to

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Neurocase elucidate the different stages of brain reorganization over time. This information is essential for theoretical models of neural plasticity, and also directly relevant for the development of new rehabilitative procedures. The objective of the current study was to investigate neural plasticity over an extended time in patient JT who underwent surgical removal of a cerebral AVM from her left postcentral gyrus. Cerebral AVMs are congenital vascular anomalies in the brain, consisting of a tangle of abnormal veins and arteries (Stapf et al., 2001). Although their etiology is still a matter of debate, they are assumed to be chronic lesions originating from dysfunction of various types of endothelial cells (Lasjaunias, 1997; Valavanis et al., 1998). Albeit generally unproblematic, in some cases, AVMs are surgically removed in order to prevent potential brain damage through, for instance, a rupture. Crucially for our study, JT had normal somatosensory functioning preoperatively, matching that of her age-matched healthy control counterpart. Immediately after successful removal of the AVM, however, she experienced spasticity and altered proprioception in her right hand. These symptoms recovered substantially over the following few months before plateauing with residual circumscribed right-hand numbness and mild clumsiness. These rare circumstances thus enabled us to study neuroplasticity in a novel way, combining experimental and opportunistic approaches. The specific aim of the study was to use functional magnetic resonance imaging (fMRI) to investigate long-term neural plasticity associated with JT’s acute postoperative alteration in proprioception in the fingers of her right hand and its subsequent partial recovery, by examining (i) postoperative changes in the localization and degree of activity in brain areas that support simple motoric behavior and (ii) postoperative changes in functional connectivity of left postcentral gyrus with the rest of the brain.

Methods Patient details JT was 47 years old at the commencement of the study. She is a right-handed, native English speaker with 10 years of formal education, employed as a pharmacy assistant before rising to a supervisory role and then retail manager, and at the time of assessment she was a personal assistant to a pharmaceutical CEO. Using the Wechsler Test of Adult Reading, her premorbid intellect was estimated to lie around the upper bound of the average range, consistent with her vocational history. JT had a lifelong history of migraine headache with no accompanying aura, but in her early thirties she developed aura sensations, which typically lasted around 5 min, involving tingling, numbness, and reduced movement in her right fingers, progressing up her arm and involving her face. Her left

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postcentral gyrus Spetzler–Martin Grade 2 AVM was diagnosed at the age of 43, following MRI of the brain after a prolonged migraine episode, and was treated with focused irradiation. The nidus shrank from 25 mm to 9 mm, and there was no apparent enduring impact on cognition or sensation from either the AVM itself or radiotherapy. Three years later, the AVM nidus was still persistent, causing increased blood vessel pressure through shunting. To prevent a potential rupture, the neurosurgeons decided to excise the AVM operatively. Her somatosensory functioning was normal at Session 1 of the study.

Preoperative cognition On assessment, JT endorsed mood inventory items consistent with moderate stress and anxiety, but indicated no significant depressive signs. Her performance on most cognitive measures was consistent with premorbid expectations, with the following test results placed in the average range: picture naming, working memory, word list learning and retention, and nonverbal memory. Table 1 shows standardized and percentile scores from her preoperative assessment and also at 7- and 14-month postoperative reviews. To provide an empirical verification Table 1.

JT’s cognitive performance over time.

Test Premorbid intellect WTAR-estimated FSIQ Working memory WMS-III mental control WAIS-III digit span Processing speed WAIS-III digit symbol coding Reasoning WAIS-III similarities WAIS-III picture completion Visuoconstruction WAIS-III block design Language Boston naming test D-KEFS category fluency Executive functioning D-KEFS letter fluency D-KEFS category switching Verbal memory CVLT-II total learning CVLT-II long delay free recall Nonverbal memory Rey figure delayed recall

Session 1 Session 2 Session 3 106 0 0.33

– −0.33

−0.33 −0.33

1.33

1.33

1.33

1.00 0.33

– –

1.00 1.67

1.00



1.67

50%ile 1.67

75%ile –

>90%ile 2.33

1.67 0.67

– –

1.67 1.33

−0.30 0.00

– –

0.50 1.00

−0.30



0.30

Notes: Data are z scores relative to normative average performance unless otherwise indicated. WTAR, Wechsler Test of Adult Reading; FSIQ, Full-scale IQ; WMS-III, Wechsler Memory Scale-Third edition; WAIS-III, Wechsler Adult Intelligence Scale-Third edition; D-KEFS, Delis–Kaplan Executive Function System; CVLT-II, California Verbal Learning Test-Second edition.

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that general cognition had recovered from the acute impact of craniotomy and general anesthesia before commencing functional imaging in the immediate postoperative period, we also tested JT with the CogState Brief computerized battery (Maruff et al., 2009). CogState Brief is a computerized battery, assessing intra-individual change between the established preoperative baseline level and postoperative performance in speed of information processing, working memory, and episodic memory.

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Postoperative cognition In the acute recovery period, JT noted mild dysarthria and clumsiness in her right hand, and by the time of her first computer-administered battery review 8 days after surgery, she was noting proprioceptive difficulty. She remarked that she had difficulty knowing whether she had actually pressed the computer keys as intended in making speeded responses, suggesting a breakdown in sensory feedback. Speed of responses was one standard deviation below baseline, but by 2 weeks after surgery her cognitive performance had returned to baseline levels; her proprioceptive difficulty remained, however. Seven months after her surgery, JT reported recovery of dysarthria and only minimal word-finding difficulty, but she did have a general sense of reduced automaticity in her thinking. Recovery of her right-hand sensation and function had plateaued after around 4 months, with residual numbness affecting her index finger and to a lesser extent, thumb and middle finger. Proprioceptive feedback was still impaired; for instance, she needed to visually verify that she had indeed clicked adequately when using a computer mouse or camera, she had difficulty picking up a cup, not knowing how much pressure to exert, and she was clumsy putting on earrings, or closing zips. At this time, she started to engage in adaptive motoric behaviors, such as using her whole hand to hold a pen and using larger-sized cutlery. A brief psychometric review now revealed no naming difficulty, with processing speed and working memory at preoperative levels. Fourteen months after her surgery, JT was reporting distractibility and forgetfulness, but this was not evident on formal testing; indeed, list learning was now entirely normal. Her right-hand function recovered partially but was still reduced; JT reported that she had learned to compensate behaviorally for reduced proprioception. Healthy control participant The healthy control participant (JO) is a right-handed female native English speaker with no neurological deficits or psychiatric disorder who was matched in terms of age and education (47 and 14 years, respectively). Both JT and JO provided written informed consent approved by the Macquarie University Human Research Ethics Committee.

fMRI study design JT participated in four fMRI sessions during the longitudinal study: 1 week prior to surgery, 3 weeks after surgery, 7 months after surgery, and 14 months after surgery. We had to exclude the 3-week postoperative scan because interpretation of this earliest postoperative data was potentially confounded by the side effects of postoperative medications. Hence, here we report results from three sessions – Session 1: prior to surgery, Session 2: 7 months after surgery, and Session 3: 14 months after surgery. For clarity, we refer to the three reported sessions as Sessions 1, 2, and 3 throughout. The experiment consisted of four functional runs of visually-cued index finger tapping, at a constant rate of 1 cue per second, alternating 16-s blocks of right finger tapping, left finger tapping, and fixation. The healthy control participant took part in two fMRI sessions, 3 weeks apart, in order to establish whether (i) preoperatively, JT’s blood oxygenation level-dependent (BOLD) response in somatosensory regions was normal (i.e., did not differ significantly from that of the control participant) and (ii) postoperatively, any changes in JT’s somatosensory activations were due to functional reorganization, rather than to carryover practice effects.

fMRI data preprocessing and analysis Anatomical and functional images were acquired at the Macquarie Medical Imaging (MMI) facility at Macquarie University Hospital in Sydney, using a 3 Tesla Siemens Magnetom Verio scanner with a 12-channel head coil. Anatomical images were acquired using a T1-weighted sequence (208 axial slices, repetition time (TR) = 2000 ms, echo time (TE) = 2.42 s, FOV = 240 mm, voxel size = 0.75 mm3, TI = 900, flip angle = 9°). Brain activation was assessed using the BOLD effect (Ogawa, Lee, Kay, & Tank, 1990) with optimal contrast. Functional images were obtained using a whole-head T2*-weighted echo-planar image (EPI) sequence (42 axial slices with interleaved acquisition, 0.5 mm gap, TR = 3000 ms, TE = 32 ms, flip angle = 90°, FOV = 192 mm, voxel size = 2.5 mm3). The acquired images were preprocessed and analyzed using the Statistical Parametric Mapping software (SPM8; Wellcome Department of Imaging Neuroscience; http:// www.fil.ion.ucl.ac.uk/spm). To correct for head motion, fMRIs of each run were realigned onto the mean image for head–motion correction, and then spatially normalized into a standard stereotaxic space with a voxel size of 2 mm3 using the Montreal Neurological Institute (MNI) EPI template. A spatial smoothing filter was employed for each volume by convolving with an isotropic Gaussian kernel (full width at half maximum = 6 mm). To remove low-frequency noise, the data were high-pass filtered using a set of discrete cosine basis functions with a cut-off

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period of 128 s. Functional volumes were treated as a time series, and the two conditions (“right finger tapping” and “left finger tapping”) were modeled using a boxcar function convolved with a synthetic hemodynamic response function (Friston et al., 1994). We obtained parameter estimates for each condition and created statistical maps by conducting t-tests between individual conditions across the three sessions (i.e., contrasts of interest). Results were displayed as a voxelwise statistical parametric map of tvalues. Voxels that survived a threshold of p < .05 corrected for multiple comparisons across the entire volume with family-wise error correction, using Gaussian Random Field Theory, are reported as significant. A cluster threshold of three contiguous voxels (k = 3) was used.

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components that reflect cohesive patterns of brain activity related to the experimental design and account for maximum covariance between regional activity changes and task and/or a behavioral measure. The significance for each LV was determined by 500 permutation tests (McIntosh et al., 1996). In addition to the permutation tests, a second and independent step was to determine the reliability of the weights for the brain voxels characterizing each pattern identified by the LVs. To do so, we estimated the standard error of each voxel’s salience on each LV by 100 bootstrap resampling steps (Efron & Tibshirani, 1985). Peak voxels with a bootstrap ratio (i.e., salience/standard error) >3.0 were considered to be reliable, as these approximate p < .005 (Sampson, Streissguth, Barr, & Bookstein, 1989).

Functional connectivity To assess the functional connectivity of left somatosensory cortex, we used seed partial least squares (PLS; McIntosh, Chau, & Protzner, 2004; McIntosh, Grady, Haxby, Ungerrleider, & Horwitz, 1996) analysis, which examines the relation of activity in a selected brain region or regions (i.e., a seed voxel or seed region) and activity in the rest of the brain across task conditions (Della-Maggiore et al., 2000; McIntosh, 1999; McIntosh, Nyberg, Bookstein, & Tulving, 1997; Schreurs et al., 1997). We selected the seed region in JT’s left postcentral gyrus [MNI coordinates: −34 −30 56] in the vicinity of her excised AVM. The BOLD values from the seed region were extracted for the condition of interest (“right finger tapping”) in each of the sessions and correlated with activity in the rest of the brain. These correlations were then combined into a matrix and decomposed with singular value decomposition, resulting in a set of latent variables (LVs),

Results Behavioral performance To compare JT’s pre- and postoperative behavioral performance, we analyzed visually-cued finger tapping reaction times across the three sessions (Figure 1). A 2 (condition: left and right finger tapping) × 3 (session: 1, 2, and 3) repeated-measures ANOVA of reaction times revealed a significant main effect of condition [F(1,297) = 14.42, p < .001] and a significant condition × session interaction [F(2,297) = 3.56, p = .030]. Post-hoc paired-sample t-tests revealed that during both post-surgery sessions (Sessions 2 and 3), right finger tapping was significantly slower than left finger tapping (p < .010 in Session 2, p < .050 in Session 3). Mean reaction times for finger tapping did not differ significantly between the right and left index fingers during Session 1 (p > .100). Furthermore, right finger tapping during Sessions 2 and 3 was significantly slower

Figure 1. Reaction times on the finger-tapping task across the three imaging sessions (1 = pre-surgery, 2 = 7 months post-surgery, 3 = 14 months post-surgery. **Significant at p < .01; *significant at p < .05. [To view this figure in color, please see the online version of this Journal.]

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than during Session 1 (ps < .010). There were no significant differences in reaction times for left finger tapping across the three sessions (ps > .100). Overall, JT’s behavioral results revealed significantly slower postsurgical right finger tapping, with the slowest mean reaction time at Session 2. For the control participant, a 2 (condition) × 2 (session) repeated-measures ANOVA of reaction times revealed no significant main effect or interaction (ps > .100), indicating no significant differences between the right and left finger tapping during either of the two sessions, i.e., no practice effect was evident at the second session.

fMRI results: right finger tapping In Session 1, right finger tapping activated left postcentral gyrus and primary motor cortex, right primary motor cortex, supplementary motor area (SMA) proper, pre-SMA, and bilateral dorsal premotor cortex (PMC; see Figure 2a top and Table 2). This pattern is similar to that of previous fMRI studies examining the neural correlates of simple motor actions (e.g., Rao et al., 1993), and to the pattern of activity of the control participant. Additional significant activations were observed in occipital cortices, which were presumably elicited by the visual cues that preceded each finger tap. In Session 2, significant sensorimotor activations included left postcentral gyrus and primary motor cortex, right primary motor cortex, SMA proper, pre-SMA, and bilateral dorsal PMC (see Figure 2a center). Descriptively, Session 2 yielded noticeably smaller left-hemispheric but larger right-hemispheric somatosensory clusters, as well as increased activations in SMAs (see Table 2).

Table 2. Brain regions significantly activated during right finger tapping. Right finger tapping > Fixation Cluster size Region

Session 1 Session 2 Session 3

Left hemisphere S1 + M1 Dorsal PMC Right hemisphere M1 Ventral PMC Dorsal PMC IPL Precuneus Supplementary motor Pre-SMA SMA proper (left) SMA proper (right)

z

815 104

563 36

431 347

>8.00 >8.00

172

278

451 534 632 584 127

>8.00 >8.00 >8.00 >8.00 >8.00

areas 41 202 125

139 242 153

223 314 636

6.68–8.00 >8.00 >8.00

Note: S1, primary somatosensory cortex; M1, primary motor cortex; PMC, premotor cortex; IPL, inferior parietal lobule; SMA, supplementary motor area.

In Session 3, as in the previous two sessions, significant sensorimotor activations included left postcentral gyrus and primary motor cortex, right primary motor cortex, SMA proper, pre-SMA, and bilateral dorsal PMC (see Figure 2a bottom). However, additional significant activations were found in right ventral PMC, right inferior parietal lobule, and precuneus. Descriptively, compared to the previous two sessions, Session 3 yielded smaller clusters of activation in the left hemisphere (left primary motor and sensory cortices) and larger clusters in the right hemisphere (right

Figure 2. Significant activations during right finger tapping (p < .05, k = 3; corrected for multiple comparisons). (a) Whole-brain patterns in each of the three scanning sessions; (b) significantly increased activity in left postcentral gyrus in Session 1 vs. Sessions 2 and 3; (c) significantly increased activity in premotor cortex and precuneus in Session 3 vs. Sessions 1 and 2. [To view this figure in color, please see the online version of this Journal.]

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Neurocase primary motor cortex, SMA, pre-SMA, and both dorsal and ventral premotor cortices; see Table 2). Direct statistical comparisons of right finger tapping across the three sessions revealed significant activation differences in Sessions 1 and 3, as contrasted with the other sessions. Session 1 vs. Session 2 and Session 1 vs. Session 3 yielded significantly more activation in left postcentral gyrus (79 voxels, z > 8.00; 73 voxels, z = 7.63, respectively; see Figure 2b). Session 3 vs. Session 1 showed significantly more activation in right ventral PMC (171 voxels, z = 7.58), bilateral dorsal PMC (left: 77 voxels, z > 8.00; right: 149 voxels, z > 8.00), and precuneus (66 voxels, z = 6.62; see Figure 2c top). Finally, Session 3 vs. Session 2 yielded increased activations in right ventral PMC (128 voxels, z > 8.00), bilateral dorsal PMC (left: 42 voxels, z > 8.00; right: 117 voxels, z = 7.58), precuneus (48 voxels, z = 6.86), and left inferior parietal lobule (89 voxels, z = 6.97; see Figure 2c bottom). Contrasts Session 2 vs. Session 1 and Session 2 vs. Session 3 were statistically not significant. fMRI results: left finger tapping In Session 1, left finger tapping activated right postcentral gyrus and primary motor cortex, SMA proper, and bilateral dorsal PMC (see Figure 3a top).

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In Session 2, significant sensorimotor activations included the same areas as in Session 1 with the exception of left dorsal PMC (see Figure 3a center). Descriptively, compared to Session 1, Session 2 showed larger righthemispheric somatosensory clusters. In Session 3, significant sensorimotor activations included the same areas as in Session 1 (see Figure 3a bottom). Descriptively, compared to Sessions 1 and 2, Session 3 showed further substantial increases in righthemispheric somatosensory activations during left finger tapping. Direct statistical comparisons of left finger tapping across the three sessions revealed significant activation differences only in Session 3 in comparison to the other sessions (see Figure 3b). Session 3 vs. Session 1 yielded more activation in right ventral and dorsal PMC (49 voxels, z = 7.14; 184 voxels, z > 8.00, respectively) and right primary motor cortex (398 voxels, z > 8.00). Session 3 vs. Session 2 yielded significant increases in activation in right ventral and dorsal PMC (74 voxels, z > 8.00; 91 voxels, z > 8.00, respectively) and left inferior parietal lobule (30 voxels, z = 6.14) (Table 3).

fMRI results: functional connectivity The seed PLS analysis assessed the functional connectivity of left postcentral cortex and the rest of the brain for each of

Figure 3. Significant activations during left finger tapping. (a) Whole-brain patterns in each of the three scanning sessions; (b) significantly increased activity in premotor and right primary motor cortex in Session 3 vs. Session 1 (top), and significantly increased activity in premotor cortex and left inferior parietal lobule in Session 3 vs. Session 2 (bottom). [To view this figure in color, please see the online version of this Journal.]

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Table 3. Brain regions significantly activated during left finger tapping. Left finger tapping > Fixation Cluster size Region

Session 1

Right hemisphere S1 + M1 880 Dorsal PMC 91 Left hemisphere Dorsal PMC 34 Supplementary motor areas SMA proper 141

Session 2

Session 3

z

1205 82

1749 272

>8.00 >8.00

126

7.19–8.00

122

7.26–8.00

70

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Note: S1, primary somatosensory cortex; M1, primary motor cortex; PMC, premotor cortex; SMA, supplementary motor area.

the three scans during right finger tapping. The analysis yielded one significant LV, which accounted for 40% of covariance in the data (p < .001), delineating a parieto-frontal network composed of left postcentral cortex, primary motor cortex, ventral PMC, bilateral dorsal PMC, and posterior parietal cortices. Importantly, during right finger tapping in Session 2, the functional connection of the parieto-frontal network to left postcentral gyrus was disrupted, suggesting significant functional changes in connectivity due to reductions in proprioception. In Session 3, the functional connection to left postcentral gyrus was restored, perhaps suggesting improvement of connectivity due to partial recovery of proprioception and/or utilization of adaptive motoric behaviors by the patient (see Figure 4).

Discussion The purpose of the current study, which utilizes a rare approach to studying neuroplasticity by combining the

experimental and opportunistic approaches, was to longitudinally examine plastic changes in patient JT who suffered acute postoperative reduction in proprioception in the fingers of her right hand. Our findings provide evidence for gradual and relatively slow cortical reorganization over the span of 14 months, reflecting increased activity in somatosensory areas contralateral to the AVM, decreased activity in somatosensory areas ipsilateral to the AVM, compensatory recruitment of premotor and posterior parietal areas, and changes in functional connectivity. Importantly, the greatest plastic changes became evident more than a year after surgery, correlating with JT’s partial recovery of proprioception. This recovery is presumably due to both spontaneous physiological changes, such as axonal rerouting, and alternative motoric behaviors, which JT developed a few months after surgery and gradually adapted into her daily routine. As such, these findings longitudinally demonstrate long-term functional changes in cortical organization and are important theoretically and clinically.

Changes in regional activations First, the neural processing underlying finger tapping exhibited a gradual shift in activity from ipsilesional to contralesional somatosensory areas, with the largest changes evident over a year post surgery. Previous studies have shown relatively immediate functional reorganization in somatosensory areas post injury (e.g., Kim & Nabekura, 2011), but very little is known about long-term functional reshaping in these areas. Second, right ventral and dorsal PMC, as well as posterior parietal cortex (PPC), were recruited during the later postoperative stages and seem to be associated with improvement in the patient’s proprioceptive feedback. This recruitment of additional neural resources can thus be interpreted as compensatory, in line with other neuroimaging studies that have reported an

Figure 4. Functional connectivity with left postcentral gyrus. (a) A pattern of correlated whole-brain activity with left postcentral gyrus in each scan session. Areas denoted in red/yellow positively correlate with left postcentral gyrus, whereas areas denoted in blue negatively correlate with left postcentral gyrus; (b) correlations between activity in left postcentral gyrus and regions seen in (a), for each session. Error bars denote 95% confidence intervals for the correlations calculated using the bootstrap procedure. [To view this figure in color, please see the online version of this journal.]

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Neurocase increased engagement of prefrontal and other brain areas due to a loss or reduction in function (e.g., Davis, Dennis, Daselaar, Fleck, & Cabeza, 2008; Grady, 2002; Schiavetto, Kohler, Grady, Winocur, & Moscovitch, 2002). In clinical investigations, functional compensation to adjacent sensorimotor regions has been shown primarily by studies examining reorganization in stroke (e.g., Liepert et al., 2000) or tumor patients (e.g., Duffau et al., 2003). The role of PMC and PPC in motor control has been demonstrated in a number of studies (e.g., Binkofski et al., 1998, 1999; Davare, Andres, Cosnard, Thonnard, & Olivier, 2006; Rizzolatti, Fogassi, & Gallese, 1997), with converging evidence suggesting that these regions are critically important in movement preparation, the integration of sensory and motor signals, coding of hand position, and sensory guidance of goal-directed motor movements, such as precision grasping (Fogassi & Luppino, 2005). Our results suggest that JT is able to exert greater motor control over a simple motor task, such as finger tapping, due to this compensatory recruitment of premotor and posterior parietal areas. We show that such functional reshaping may take months or longer and is largely due to exogenous influences, such as the learning of new, adaptive motoric behaviors. These findings have direct clinical implications, as they align with the evidence that rehabilitative training has significant impact on functional reorganization and thus benefits recovery of function (Nudo, Wise, SiFuentes, & Milliken, 1996). Changes in functional connectivity Preoperatively, right finger tapping engaged a fronto-parietal network with a critical connection to left postcentral cortex. Previous connectivity studies have demonstrated an integrative role of posterior parietal areas in somatosensory function (Lewis & Van Essen, 2000) and their connectivity with known somatosensory and somatomotor areas (e.g., Vogt & Pandya, 1978) as well as with both visual and somatosensory areas (e.g., Seltzer & Pandya, 1980). In the earlier postoperative stages, the connection to left postcentral cortex was disrupted and coincided with JT’s slowest reaction times on the finger tapping task and severe proprioceptive deficits. Over a year post surgery, however, the functional connection to left postcentral cortex was re-established, presumably reflecting JT’s ongoing recovery of proprioceptive function and improved finger tapping reaction times (which were, however, still significantly slower than the preoperative ones). Together with functional reorganization from the ipsilesional to contralesional hemisphere and contralesional recruitment of compensatory regions, the connectivity finding suggests largescale postoperative neural plasticity of proprioceptive function. It is of importance to emphasize, however, that whilst JT’s proprioceptive function was almost completely

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recovered, she still suffered residual deficits. Proprioception involves a multi-component sensory system consisting of peripheral receptors and several sensory afferent pathways via the spinal cord and cerebellum to the cortex (Johnson, Babis, Soultanis, & Soucacos, 2008). In addition, postcentral cortex has direct connections to regions that subserve motor control, such as primary and premotor motor cortices. Considering the multitude of feedforward and feedback connections in this complex proprioceptive circuitry, it is possible that, in addition to re-establishing the functional connection with ipsilesional postcentral cortex, full proprioceptive recovery necessitates additional cortical or subcortical rerouting. In conclusion, our study provides evidence of dynamic functional reorganization following invasive brain surgery. Our findings provide evidence for long-term functional plasticity at both regional and connectivity levels and suggest that, in addition to functional compensatory recruitment, the re-establishment of a critical functional connection may be necessary to regain proprioceptive feedback. The results lend support to the notion that postoperative plasticity is influenced by sensorimotor experiences that can take weeks to months following surgery. The implications of the study are directly relevant to the goals of neurological rehabilitation whose primary objective is to facilitate recovery of function. As our understanding of the underlying mechanisms of neural plasticity becomes more complete, we can effectively develop targeted rehabilitation techniques to enhance therapeutic outcomes by, for instance, behaviorally inducing relevant forms of plasticity. Acknowledgments The authors thank patient JT for her invaluable help and acknowledge the generous practical support provided by Jeff McIntosh and staff at MMI.

Disclosure statement No potential conflict of interest was reported by the authors.

Funding This work was funded by the National Health and Medical Research Council and was also supported by the Australian Research Council Centre of Excellence for Cognition and its Disorders [CE110001021] (http://www.ccd.edu.au).

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Long-term plasticity in adult somatosensory cortex: functional reorganization after surgical removal of an arteriovenous malformation.

The temporal scale of neuroplasticity following acute alterations in brain structure due to neurosurgical intervention is still under debate. We condu...
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