SYNAPSE 69:1–6 (2015)

Short Communication

Increased Cerebellar Volume and BDNF Level Following Quadrato Motor Training TAL DOTAN BEN-SOUSSAN,1* CLAUDIA PIERVINCENZI,2,3 SABRINA VENDITTI,4 LOREDANA VERDONE,5 MICAELA CASERTA,5 AND FILIPPO CARDUCCI2 1 Research Institute for Neuroscience, Education and Didactics, Patrizio Paoletti Foundation, Assisi, Italy 2 Department of Physiology and Pharmacology, Neuroimaging Laboratory, Sapienza University, Rome, Italy 3 Institute for Advanced Biomedical Technologies, University of G. d’Annunzio Chieti-Pescara, Chieti, Italy 4 Dipartimento di Biologia e Biotecnologie “Charles Darwin”, Sapienza Universit a di Roma, Italy 5 Istituto di Biologia e Patologia Molecolari, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy

KEY WORDS

neuroplasticity; sensorimotor training; cerebellum; MRI; brain-derived neurotrophic factor

INTRODUCTION Maintaining neuroplasticity is an important goal, which can be stimulated through training, by activating molecular mechanisms, for example, regulation of growth factors (GF; Cotman and Berchtold, 2002). Multidisciplinary studies combining the examination of training-induced structural and GF changes in humans are scarce. Consequently, the relationship between training-induced structural and GF changes in humans has yet to be established. Therefore, the aim of the current exploratory study was to examine the link between structural and GF changes following sensorimotor training. We conducted a pilot multimodal magnetic resonance imaging (MRI) longitudinal study designed to identify the possible link between structural and molecular effects of a 12-week daily practice of quadrato motor training (QMT), a sensorimotor training which has recently been reported to increase functional connectivity and cognitive function (Ben-Soussan et al., 2013, 2014a,b). Structural high-resolution 3D T1-weighted (sMRI) and diffusion tensor imaging (DTI) data were acquired for three healthy female volunteers. For DTI, we used fractional anisotropy (FA) value, a marker of white matter (WM) integrity (Pfefferbaum et al., 2000). As animal studies have demonstrated that severe deficiencies in motor coordination in brain-derived neurotrophic factor (BDNF) knockout mice are linked to abnormal cerebellar development (Ernfors et al., 1994; Schwartz et al., 1997), for the molecular examination we focused on BDNF, a key GF mediating neuronal connectivity and use-dependent plasticity (Cotman and Berchtold, 2002; Gatt et al., 2008). Although this is a small sample study which still needs further support, the current research Ó 2014 WILEY PERIODICALS, INC.

may shed light on the relationship between sensorimotor training-induced structural and molecular changes. MATERIALS AND METHODS The participants were three healthy women (53, 49, and 29 years) who never practiced QMT before. Written informed consent was obtained from all participants. Details about the QMT are reported in Ben-Soussan et al. (2013). Structural and molecular examinations were conducted in parallel before the beginning of the training and after 12 weeks of daily QMT practice. Structural examination The sMRI and DTI data were acquired using a Siemens MAGNETOM Sonata (Erlangen, Germany) 1.5 T scanner (sMRI: 3D T1-weighted MP-RAGE sequence, TR 5 3000 ms, TE 5 4.38 ms, flip angle 515 , matrix 5 192 3 192, FOV 5 240 mm2, 160 sagittal slices, voxel size 5 1.25 3 1.25 3 1.20 mm3; DTI: 12 noncollinear direction sequence, TR 5 7100 ms, TE 5 94 ms, flip angle 5 90 , matrix5256 3 192, FOV 5 240 3 320 mm2, b 5 0 and 900 s/mm2, 48 axial slices, voxel size 5 1.25 3 1.25 3 3.0 mm3). The sMRI data were analyzed using the voxel-based morphometry technique (VBM, Good et al., 2001) and DTI data were analyzed using the tract-based spatial statistics Additional Supporting Information may be found in the online version of this article. *Correspondence to: Tal Dotan Ben-Soussan; Research Institute for Neuroscience, Education and Didactics, Patrizio Paoletti Foundation for Development and Communication, Via Cristoforo Cecci 2, 06081 – Santa Maria degli Angeli, Assisi (PG), Italy. E-mail: [email protected] Received 19 May 2014; Revised 28 August 2014; Accepted 9 September 2014 DOI: 10.1002/syn.21787 Published online 13 (wileyonlinelibrary.com).

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Fig. 1. Western blot analysis of proBDNF level. 50 mg of total proteins were resolved by SDS-PAGE on a 4–15% gradient gel, transferred onto 0.2 mm polyvinylidene fluoride (PVDF) membrane, and hybridized with anti-BDNF (Santa Cruz Biotechnology, sc-546, 1:1000), followed by anti-rabbit secondary antibody (Jackson ImmunoResearch, 111-035-003, 1:20000). Histograms represent the average of the triplicate proBDNF values (pre and post) normalized to the most intense band present in the corresponding lane of the protein loading control. M: molecular size marker (75, 50, and 25 kD).

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Fig. 2. (A) Significant increases after 12 weeks of QMT daily practice in GM volume and FA values. (B) Regions of GM volume and FA values positively correlated with proBDFN. For (A) and (B), FA values images: red-yellow color bar is based on min–max statistical threshold. Refer to corresponding Supporting Information tables for more neuroanatomical and statistical details.

(TBSS, Smith et al., 2006); The sMRI were longitudinally processed with voxel-based morphometry (VBM2) toolbox (http://dbm.neuro.uni-jena.de/vbm/) of statistical parametric map (SPM2) (http://www.fil.ion. ucl.ac.uk/spm/; Draganski et al., 2004; Golestani et al., 2002; Maguire et al., 2000; May et al., 2006). In short, pre-QMT images were aligned to the T1 template and then, post-QMT images were coregistered to the pre-QMT T1-aligned scans. All scans were bias-corrected and segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) compartments. GM maps were normalized to Montreal Neurological Institute (MNI) atlas space (1 3 1 3 1 mm voxels) and smoothed using a 8 mm FWHM Gaussian kernel. Preprocessing of DTI data was performed with FSL (http://www.fmrib.ox.ac.uk/ fsl). DTIs were corrected for motion and eddy currents distortions and then skull-stripped using BET (Smith, 2002). Maps of FA were computed by fitting a tensor model to the raw diffusion data using the FMRIB’s Diffusion Toolbox. These maps were projected onto a mean FA tract skeleton, before applying voxelwise intrasubject statistics to compare them between time points (Scholz et al., 2009). Statistical analysis VBM data were analyzed using a general linear model. Anatomical localization was performed with the MNI Space Utility toolbox of SPM MNI Space Utility. Statistical analysis of TBSS data was per-

formed using a permutation-based inference tool for nonparametric statistical thresholding. Anatomical localization was obtained using AtlasQuery FSL tool. Pre-QMT and post-QMT results were compared using a paired t-test with subject’s age as nuisance variable. A similar methodology of combining TBSS and VBM has been recently applied in several studies (Ambrosi et al., 2013; Bodini et al., 2009; Della Nave et al., 2008; Douaud et al., 2007). Two multiple regression analyses were performed to investigate if pre-QMT, post-QMT, and proBDNF levels separately correlated to the corresponding GM and FA changes. The result maps of VBM and TBSS analyses were considered as explicit masks for GM and FA, respectively. Statistical analyses were performed with multiple regression analyses run on SPM. Molecular examination Salivary BDNF was examined in triplicate to take into consideration potential variability due to flow rate. Saliva samples were collected always in the morning between 8 and 9 am, and specific instructions were given to the participants including avoiding: brushing teeth within 1 h prior to collection, using salivary stimulants, consuming a major meal within 1 h prior to collection, consuming alcohol 12 h prior to collection, as well as consuming acidic or high sugar foods within 20 min prior to collection of the saliva. In addition, they were asked to rinse mouth with water 10 min prior to sample collection. Synapse

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Unstimulated whole saliva samples were collected by passive drool, and stored at 280 C. Prior to electrophoresis, samples were subjected to vortex for 30 s, and then centrifuged at maximum speed for 15 min. Saliva supernatants were transferred to fresh tubes, protein inhibitor cocktail (Roche) was added, and total protein concentration was determined. Western blot analysis Fifty micrograms of total proteins were resolved by SDS-PAGE on a 4–15% gradient gel, transferred onto 0.2 mm PVDF membrane, and hybridized with antiBDNF (Santa Cruz Biotechnology, sc-546, 1:1000), followed by anti-rabbit secondary antibody (Jackson ImmunoResearch, 111-035-003, 1:20000). The bands corresponding to proBDNF were quantified with Image Lab software, and normalized to the most intense band visible on the membrane in the protein loading control. RESULTS ProBDNF level significantly increased in all the participants (Fig. 1). In each panel, the bands visualized after immunoblot with anti-BDNF antibody (Santa Cruz Biotechnology, sc-546) correspond to proBDNF, while mature BDNF could not be detected. As a control, after mild stripping of the filter, we used an antibody against the precursor proBDNF (Santa Cruz Biotechnology, sc-65513), and the results were confirmed (Supporting Information Fig. S1). When we analyzed changes in proBDNF level in the absence of any training, no significant variation was observed (Supporting Information Fig. S2). Peripheral proBDNF was analyzed because it was reported in saliva and salivary glands of both humans and rats (Mandel et al., 2011; Saruta et al., 2010), and because a positive correlation between saliva and brain levels was suggested in rats (Saruta et al., 2010). VBM analysis showed significant (P < 0.05 FDR corrected) GM volume increase bilaterally in the cerebellum, in right thalamus and limbic lobe (Fig. 2A, Supporting Information Table 1). TBSS analysis showed significant (P < 0.001 uncorrected) FA increases mainly located in the corpus callosum, anterior thalamic radiations, corticospinal tracts, cerebellar peduncles, and superior longitudinal fascicule (Fig. 2A, Supporting Information Table 2). The correlation analysis revealed positive correlations (P < 0.05 uncorrected) between proBDNF values and GM and FA maps (Supporting Information Tables 3 and 4), respectively, located bilaterally in the cerebellum and mainly in the right anterior thalamic radiation, forceps minor, and right inferior cerebellar peduncle (Fig. 2B). The QMT-induced structural changes are consistent with previous results observed after longSynapse

term motor and mental training (Draganski et al., 2004; H€olzel et al., 2011; Scholz et al., 2009; Vestergaard-Poulsen et al., 2009). The cerebellar reorganization is most likely related to sensorimotor coordination and attention (Fossella et al., 2008; H€olzel et al., 2011) required in the QMT. The FA increases in the corpus callosum may be related to a more efficient interhemispheric connection and increased alpha activity, as previously found following QMT (BenSoussan et al., 2013). Interestingly, both parameters were found to be BDNF dependent (Gatt et al., 2008). The interrelated structural reorganization and close spatial proximity of GM and FA increases point to a causal relationship between behavioral adaptation and structural brain plasticity (Taubert et al., 2010), and suggest that QMT leads to increased GM volume, reflecting an altered organization of underlying WM pathways (Ben-Soussan et al., 2014a). In addition, the positive correlation between cerebellar and proBDNF increases are in line with previous studies demonstrating that training relies on structural changes related to underlying cellular events, including synaptogenesis and dendritic arborization (Gatt et al., 2008; Scholz et al., 2009), and with studies using animal models demonstrating that motor training is accompanied by increased cerebellar BDNF mRNA amount (Morrison and Mason, 1998; Neeper et al., 1996). As training-induced plasticity is favorable for learning and memory, many researchers have aimed at finding ways at enhancing it. While most studies and animal models have focused on pharmacological €rtner and electrophysiological interventions (e.g., Ga and Staiger, 2002), some have studied the effects of active training and enriched environment (Bose et al., 2010; MacGillivray et al., 2012; Yang et al., 2013). In line with these models, the current results suggest cerebellar microstructural changes following sensorimotor training (Carbon et al., 2008, 2010). In turn, the increased cerebellar volume may be mediated by increased BDNF level. In addition, we suggest that increased cerebellar size could be related to the important role of cerebellar alpha oscillations in voluntary action (Ivry et al., 2002; Tesche and Karhu, 2000). In fact, Ben-Soussan et al. (2014a) have recently reported increased cerebellar alpha power following a month of daily QMT practice. To verify whether cerebellar alpha oscillations are the underlying electrophysiological mechanism mediating change in cerebellar size, a combination of MRI and electroencephalography (EEG) should be conducted. We are currently working in this direction. This study is a preliminary attempt to examine empirically the question of the dynamic relationship between structural and neurotrophic changes following training. The main limitations of the study are the small sample size and the use of only one

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training paradigm. The choice of QMT was based on recent studies demonstrating that changes in functional connectivity, cerebellar activity, and cognitive changes, namely increased creativity and improved spatial cognition, are QMT specific, and were not observed in two control groups (Ben-Soussan et al., 2013, 2014a,b). In the future, a study on a larger sample that includes several training regimes and a passive control as well as additional physical exercise as opposed to mental paradigms, such as meditation, should be examined. Additional factors which could explain the results should be examined in the future, such as particular sequence of seasonal changes. Lastly, extending the neurotrophin analysis to blood and plasma samples, for which a significant correlation between brain and periphery was shown (Karege et al., 2002; Lang et al., 2007; Rasmussen et al., 2009), would also help to strengthen the correlation we observe following QMT. Nevertheless, the present exploratory work strengthens previous findings related to the effects of sensorimotor training, providing novel insights regarding the possible underlying neural and molecular mechanisms. REFERENCES Ambrosi E, Rossi-Espagnet MC, Kotzalidis GD, Comparelli A, Del Casale A, Carducci F, Romano A, Manfredi G, Tatarelli R, Bozzao A, Girardi P. 2013. Structural brain alterations in bipolar disorder II: A combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) study. J Affect Disord 150:610–615. Ben-Soussan TD, Glicksohn J, Goldstein A, Berkovich-Ohana A, Donchin O. 2013. Into the square and out of the box: The effects of quadrato motor training on creativity and alpha coherence. PLoS One 8:e55023. Ben-Soussan TD, Avirame K, Glicksohn J, Goldstein A, Harpaz Y, Ben-Shachar M. 2014a. Changes in cerebellar activity and interhemispheric coherence accompany improved reading performance following quadrato motor training. Front Syst Neurosci. 8:81. Ben-Soussan TD, Berkovich-Ohana A, Glicksohn J, Goldstein A. 2014b. A suspended act: Increased reflectivity and genderdependent electrophysiological change following quadrato motor training. Front Psychol 5:55. Bodini B, Khaleeli Z, Cercignani M, Miller DH, Thompson AJ, Ciccarelli O. 2009. Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: An in vivo study with TBSS and VBM. Hum Brain Mapp 30:2852–2861. Bose M, Mu~ noz-llancao P, Roychowdhury S, Nichols, JA, Jakkamsetti V, Porter B, Byrapureddy R, Salgado H, Kilgard MP, Aboitiz F, Dagnino-Subiabre A, Atzori M. 2010. Effect of the environment on the dendritic morphology of the rat auditory cortex. Synapse 64:97–110. Carbon M, Kingsley PB, Tang C, Bressman S, Eidelberg D. 2008. Microstructural white matter changes in primary torsion dystonia. Mov Disord 23:234–239. Carbon M, Argyelan M, Habeck C, Ghilardi MF, Fitzpatrick T, Dhawan V, Pourfar M, Bressman SB, Eidelberg, D. 2010. Increased sensorimotor network activity in DYT1 dystonia: A functional imaging study. Brain 133:690–700. Cotman CW, Berchtold NC. 2002. Exercise: A behavioral intervention to enhance brain health and plasticity. Trends Neurosci 25: 295–301. Della Nave R, Ginestroni A, Tessa C, Salvatore E, Bartolomei I, Salvi F, Dotti MT, De Michele G, Piacentini S, Mascalchia M. 2008. Brain white matter tracts degeneration in Friedreich ataxia. An in vivo MRI study using tract-based spatial statistics and voxel-based morphometry. Neuroimage 40:19–25. Douaud G, Smith S, Jenkinson M, Behrens T, Johansen-Berg H, Vickers J, James S, Voets N, Watkins K, Matthews PM, Jame A.

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Increased cerebellar volume and BDNF level following quadrato motor training.

Using whole-brain structural measures coupled to analysis of salivary brain-derived neurotrophic factor (BDNF), we demonstrate sensory motor training-...
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