Cerebral Cortex Advance Access originally published online on February 15, 2006
Cerebral Cortex 2007 17(1):205-210; doi:10.1093/cercor/bhj138
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Structural Brain Alterations following 5 Days of Intervention: Dynamic Aspects of Neuroplasticity
1 Department of Systems Neuroscience, University of Hamburg, Martinist. 52, 20246 Hamburg, Germany, 2 Department of Psychiatry and Psychotherapy, University of Regensburg, Universitätsstrasse 84, 93059 Regensburg, Germany, 3 Department of Neurology, University of Regensburg, Universitätsstrasse 84, 93059 Regensburg, Germany, 4 Department of ENT, University of Regensburg, Universitätsstrasse 84, 93059 Regensburg, Germany
Address correspondence to Arne May, MD, Assistant Professor of Neurology, Department of Systems Neuroscience, Universitäts-Krankenhaus Eppendorf (UKE), Martinistrasse 52, D-20246 Hamburg, Germany. Email: a.may{at}uke.uni-hamburg.de.
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Activation-dependent brain plasticity in humans on a structural level has been demonstrated in adults after 3 months of training a visio-motor skill. The exact timescale of usage-dependent structural changes, whether days, months, or years, is, however, still debated. A better understanding of the temporal parameters may help elucidate to what extent this type of cortical plasticity contributes to fast adapting cortical processes that may be relevant to learning and effects of treatments. Using voxel-based morphometry, we are able to show that repetitive transcranial magnetic stimulation delivered to the superior temporal cortex causes macroscopic cortical changes in gray matter (GM) in the auditory cortex as early as within 5 days of continuous intervention. These structural alterations are mirrored by changes in cortical evoked potentials attributed to the GM changes and demonstrate the rapid dynamics of these processes, which occur within a time range characteristic for the onset of behavioral effects induced by a variety of treatment methods for neuropsychiatric diseases. Our finding suggests that cortical plasticity on a structural level in adult humans is already detectable after 1 week, which provides support for fast adjusting neuronal systems, such as spine and synapse turnover, and contradicts slow evolving mechanisms, such as neuronal or glial cell genesis.
Key Words: auditory cortex • plasticity • rTMS • voxel-based morphometry
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Brain plasticity refers to the brain's ability to undergo functional and structural alterations in response to internal and external environmental changes. The actual underlying causes are attributed to a multitude of different mechanisms, which in the case of structural plasticity may involve variance in spine density (Grutzendler and others 2002
; Trachtenberg and others 2002) and glial- or possibly even neurogenesis (Kempermann and others 1997). Animal models, however, suggest that the capacity for adaptive change is limited. Whereas traditional research has focused on functional forms of neuroplasticity, current theoretically based concepts suggest structural types of cortical plasticity in adult brains to play a crucial role in adaptation to environmental changes and disease. Support for this hypothesis comes from a recent study demonstrating activity-dependent selective changes in gray matter (GM) induced in human adults after 3 months of training (Draganski and others 2004), although age may still limit the capacity for reorganization. As activation-dependent brain plasticity in humans on a structural level has to date only been demonstrated in younger adults after 3 months of training (Draganski and others 2004), further studies are needed to establish an empirical understanding of whether and to what extent the brain responds to environmental demands in relationship to other parameters (i.e., age and temporal parameters). Because the therapeutic effects of centrally acting agents are often not instantaneous, but instead emerge over an extended period of time from weeks to months, longer duration changes such as functional or even structural plasticity may be important in the mechanism of action of centrally acting agents. Detailed knowledge about the temporal parameters of structural neuroplasticity may help elucidate to what extent this type of cortical plasticity is involved in mediating short- and long-term clinical effects.
Focusing on the issue of whether structural neuroplasticity may arise in a matter of days rather than months (Draganski and others 2004), we used a double-blinded, placebo-controlled study design with low-frequency repetitive transcranial magnetic stimulation (rTMS) in 2 homogenous groups of volunteers who received either active or sham rTMS for 5 days. We used rTMS as it has increasingly and successfully been used to explore the mechanisms and consequences of functional plasticity in the human cortex (Bäumer and others 2003; Siebner and Rothwell 2003). Depending on the stimulation frequency, rTMS can induce neurobiological effects resembling direct electrical stimulation, which has been shown to inducing neuroplasticity in animals (Wang and others 1996; Post and others 1997). Consequently, rTMS is not only used as a diagnostic tool but also to treat specific symptoms. In humans, low-frequency 1-Hz rTMS targeting the left temporoparietal cortex caused a remarkable and sustained reduction of auditory hallucinations in schizophrenia (Hoffman and Cavus 2002; Poulet and others 2005). In addition, 1-Hz rTMS targeting of the auditory cortex is efficient in reducing chronic tinnitus (Eichhammer and others 2003; Plewnia and others 2003). In light of these observations, the involvement of neuroplastic processes in mediating 1-Hz rTMS effects has already been discussed (Chen and others 1996; Langguth and others 2003). We therefore predicted that rTMS of the left auditory cortex may alter the brain morphology in this region, representing the structural counterpart of the above mentioned functional neuroplasticity. In line with this hypothesis, we decided to investigate healthy volunteers using a well-controlled study design to avoid the possible pathophysiological condition of patients suffering from tinnitus.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Volunteers
We studied 36 healthy volunteers (27 females, 9 males; mean age, 24.8 years) and split them into 2 groups matched equally for sex and age: receiving either active or sham rTMS (sham group: mean age = 23.5 ± 4 years, 15 females, 3 males; active group: mean age = 24.0 ± 5 years; 12 females, 6 males). None of the volunteers suffered from any diseases, in particular, the neurological and otorhinolaryngological examination were entirely normal. The subjects were recruited locally, and they were informed that the purpose of the current study was to investigate the central nervous system's adaptive behavior to repeated stimulation using rTMS.
The study was given ethical approval by the local ethics committee and written informed consent was obtained from all study participants prior to examination.
Repetitive Transcranial Magnetic Stimulation
The rTMS was administered both in the active as well as in the sham condition by means of a neuronavigational system, conventionally used in neurosurgery (Gumprecht and others 1999) and further developed and adopted for transcranial magnetic stimulation (TMS) (Vector-Vision, BrainLab AG, München-Heimstetten, Germany). This system allows real time stereotactic monitoring of coil location with respect to the individual cortex (Eichhammer and others 2003). Based on individual structural images acquired in our lab using T1-weighted magnetic resonance (MR) scans, the left superior temporal gyrus (Brodmann area 41/42), corresponding to the primary auditory cortex, could be marked as the target for rTMS application (Schonfeldt-Lecuona and others 2004). As has been demonstrated recently, this procedure guarantees the placement of the TMS coil at a particular brain region with high precision and reliability (Herwig and others 2001).
The rTMS was administered by means of a Magstim Rapid stimulator (Magstim Co., Whiteland, Dyfed, UK) using a figure-of-eight coil. Stimulation was applied daily for 5 days, with 1 Hz stimulus frequency and at 110% motor threshold intensity. Because biological effects of TMS are known to be dose dependent, we chose suprathreshold intensity for stimulation, frequently used in treatment studies. Per session, 2000 stimuli were administered. For sham stimulation, a specific sham-coil system was used (Magstim Co., Whiteland, Dyfed, UK). The specifically designed sham coil does not induce a magnetic field but evokes an acoustic artifact comparable with the popping sound generated by the active coil.
VBM—Data Acquisition
Both groups received a T1-weighted magnetic resonance imaging (MRI) scan on day 1 and on day 6, immediately following the intervention period. All volunteers were scanned again after a time period of 3 months without any intervention. MRI was performed on a Siemens Symphony scanner operating at 1.5 T. A 3-dimensional (3D) structural MRI was acquired for each subject using a T1-weighted gradient echo magnetization prepared rapid gradient echo sequence (time repetition 11.08 ms, echo time 4 ms, time to inversion 300 ms, flip angle 15°, matrix size 256 x 192, field of view 256 x 192) yielding 150 sagittal slices with a defined voxel size of 1 x 1 x 1.08 mm. Conventional T1 MRI showed no morphological abnormalities or artifacts in either the patient or the volunteer groups.
Voxel based morphometry (VBM) is based on high-resolution structural 3D MR images, transformed into a common stereotactic space and is designed to seek significant regional differences by applying voxelwise statistics in the context of Gaussian random fields (Friston and others 1999; Ashburner and Friston 2000). VBM has been cross validated with region-of-interest measurements and functional data in a number of studies (May and others 1999; Woermann and others 1999).
VBM Protocol
Data preprocessing and analysis were performed with Statistical Parametric Mapping 2 (Welcome Department of Cognitive Neurology, London, UK) running under Matlab (Mathworks, Sherborn, MA, USA). Preprocessing of the data involved spatial normalization, segmentation, modulation, and spatial smoothing with a Gaussian kernel (Friston and others 1999; Ashburner and others 2000).
In order to reduce the scanner-specific bias, we created a customized GM anatomical template from the volunteers in this study. To facilitate optimal segmentation, we estimated normalization parameters while removing nonbrain voxels (skull, sinus) using an optimized protocol (Good and others 2001b). The optimized parameters, estimated while normalizing extracted GM images to the customized GM template, were reapplied to the original whole brain images. The images aligned with the stereotactic space defined by the Montreal Neurological Institute (International Consortium for Brain Mapping, http://www.loni.ucla.edu/ICBM/ [Evans and others 1994]) were corrected for nonuniformities in signal intensity and partitioned into GM and WM, cerebrospinal fluid (CSF), and background using a modified mixture model cluster analysis. In addition, we performed a correction for volume changes (modulation) by modulating each voxel with the Jacobian determinants derived from the spatial normalization, allowing us to also test for regional differences in the absolute amount of GM (Ashburner and Friston 2000; Ashburner and others 2000). Subsequently, all images were smoothed by convolving them with an isotropic Gaussian kernel of 10 mm full-width at half maximum.
Statistical Analysis
Voxel-by-voxel t-tests using the general linear model were used to test for regionally specific GM and WM differences between the groups. The groups were closely matched for age and sex with no significant differences between the groups, and, therefore, no age or sex confounds were included. We used a time points (before intervention, after intervention) by group (TMS, sham) interaction analysis, testing for greater changes in the active rTMS group. The factor time points was modeled as a transient increase (increase from time point 1 to 2 then decrease again between time points 2 and 3 or vice versa). For the statistical analysis, we excluded all voxels with a GM or WM value below 0.2 (with a maximum value of 1) to avoid possible edge effects around the border between GM and WM and to include only voxels with sufficient GM proportion.
We hypothesized, based on the finding that induction of neuroplasticity may be a key consequence of 1-Hz rTMS (Chen and others 1996; Tergau and others 1999; Langguth and others 2003), that rTMS of the left auditory cortex may alter the brain morphology in this region. We applied a threshold of P < 0.05 (corrected across the whole brain for multiple comparisons). For regions for which we had an a priori hypothesis, a small volume correction (SVC), using a sphere of 6 mm radius in the left auditory cortex, was performed.
Auditory Measurement
All subjects obtained microscopic examination of the ear to exclude a tympanic membrane defect or middle ear effusion. The hearing status was confirmed on the basis of auditory tests. All auditory measurements were made before and after the stimulation period.
Normal middle ear status was demonstrated by tympanometry and the measurement of stapedius reflexes. "Normal hearing" was defined as pure tone thresholds of better than 20 dBHL in the frequency range of 0.25–8 KHz. The auditory threshold was determined by pure tone audiometry between 0.125 and 8 KHz.
Evoked potentials were collected in 8 out of 18 subjects of the verum group using Cz as the active electrode referenced to the contralateral mastoid. The ground electrode was placed on the forehead. The electroencephalography was sampled at 10 kHz (bandpass 1–500 Hz, ERA-System, ZLE Systemtechnik, Munich, Germany). The stimulus for cortical auditory evoked cotentials (CAEP) measurements was a 1-KHz tone burst of 400 ms plateau duration (2 cycles linear on- and offset). Each averaged waveform of 124 stimuli (interstimulus interval 1920 ms) was digitally low-pass filtered offline at 19 Hz (finite impulse response, zero phase shift) in order to enhance detection of the CAEP components, which were identified visually in the averaged data. P1 was defined as the first robust positive waveform. N1 was defined as the first negativity occurring after the P1 response and in the range of about 80–140 ms after stimulation. The P2 peak was determined as the most positive voltage reversal between 140 and 200 ms after stimulus onset. The N2 peak was determined separately as the most negative reversal occurring after P2.
Statistical Analyses
The effects of active and sham stimulation as well as stimulated versus unstimulated side on amplitude differences P1–N1, P2–N2, N1–P2 were evaluated by nonparametric Wilcoxon matched pairs test. All probabilities are 2-tailed.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Based on the results using VBM, the group comparison at the beginning (baseline) demonstrated no significant regional difference in GM between the active and sham treated groups, whereas comparison at the end of the treatment period revealed differences between the groups. Volunteers treated with active rTMS showed a significant transient increase exclusively in GM in the left superior temporal area (which was targeted by the TMS coil) between the 1st and the 2nd scan (x = –62, y = –3, z = 1; t = 3.36), which again decreased toward the 3rd scan (Z interaction P < 0.05 small volume corrected; Fig. 1). No white matter (WM) changes were detected. The dynamic pattern of the GM changes was specific to the active rTMS, as the sham group revealed no GM changes during the same period of time. Pure tone audiometry could not detect significant differences between both groups after TMS treatment, whereas in CAEP, a significant (P = 0.002) increase in P2–N2 amplitude could be found, indicating alterations in auditory processing between active and sham treated volunteers.
|
Additionally, we also found a transient increase and decrease of GM in the superior temporal area contralateral to the site of stimulation and bilaterally in the thalamus (P < 0.001, uncorrected; see Fig. 2). However, we had no a priori hypothesis for these regions and consequently did not perform any SVCs. Because these findings did not survive correction for multiple comparisons, we only report them as trends. A boxplot showing the mean, standard deviation, and range for each time point (Fig. 3), as well as a table showing changes in specific brain regions (Table 1) are included in the supplementary material.
|
Regarding the auditory measurements, in the active group, the amplitude difference P2–N2 was significantly larger (Wilcoxon test, P = 0.008) compared with the change in amplitude of P2–N2 after sham stimulation (Wilcoxon test, P = 0.461). The amplitude difference in P2–N2 before and after the stimulation procedure of the unstimulated left ear, in contrast, did not differ significantly in either group (Wilcoxon test, P = 0.313 vs. P = 0.383). Our model of the potential influence of plasticity on CAEP generators included the a priori hypothesis that only the amplitudes of the CAEP are influenced. We solely considered amplitude, as we were using VBM to look for GM changes, and any changes as a consequence of repeated TMS could only influence the amplitudes of CAEP. Neither latencies nor other amplitude differences were significantly different at all after the stimulation procedure in both groups and both ears. Because the auditory measurements were only done in 8 subjects, we have not correlated the amplitude difference P2–N2 and the amount of change in GM because statistically more subjects are necessary to detect possible significant changes.
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Our results suggest that dynamic alterations in GM can occur very rapidly and at least within a time range of 1 week. This period of time corresponds to the onset of therapeutic effects in neuropsychiatric diseases initiated by TMS (Tergau and others 1999
) and antipsychotic agents (Stahl and others 2001), indicating that cortical plasticity at a structural level may be involved in mediating sustained clinical improvement.
The local changes mirroring structural neuroplasticity are in line with current studies, demonstrating that low-frequency rTMS is able to produce powerful and widespread changes in regional synaptic activity within cortical and subcortical structures (Bäumer and others 2003; Siebner and others 2003; Li and others 2004). The significant increase in GM in the superior temporal area contralateral to the site of stimulation reflects close functional connectivity between both auditory cortices (Read and others 2002). Moreover, the increase in GM in the thalamus suggests reciprocal interconnections between this brain structure and the temporal cortex (Nolte 2001). Both in vivo electrical stimulation of the cortex and low-frequency rTMS in patients with depression have been shown to produce neurobiological effects in a variety of thalamic nuclei, including the mediodorsal nucleus and the pulvinar (Destexhe and others 1998; Li and others 2004). The fact that unilateral rTMS leads to bilateral changes on a functional level was demonstrated in previous studies using functional imaging and may reflect close connectivity between directly stimulated brain regions and remote areas in both brain hemispheres (Siebner and others 2003).
Although the sham coil which we used in our study is the best available sham condition for rTMS studies, one could argue that active and sham rTMS are still different in the acoustical sensation and that any changes in GM reflect auditory stimulation rather than the effects of the magnetic field. Although we cannot entirely deny that subtle differences between active and sham rTMS in terms of acoustic artifacts exist, there is no literature based on precise acoustic measurements supporting this argumentation. Considering the critical impact of acoustic stimuli alone on brain plasticity, the sham-rTMS–treated group (which were also subject to repetitive acoustic stimuli) should have demonstrated changes in the auditory cortex, too. On the other hand, subtle differences in sound compete with a multitude of different acoustic stimuli that our subjects are exposed to during non-TMS. Moreover, the majority of our volunteers was not aware of any difference, including the loudness, between active and sham stimulation, and the main finding of our study—changes in GM as early as 5 days of intervention—is valuable, even if the sound rather than the magnetic input is the source of the changes.
Using the very conservative approach of an interaction analysis, the changes in GM are exclusively seen in the active group. It is tempting to argue in favor of a direct effect of rTMS on brain plasticity. The crucial question regarding the mechanisms of rTMS is whether these changes are due to the direct impact of magnetic waves versus sound or possibly even sensory input due to stimulation of the underlying scalp muscles. As our study aimed at understanding the temporal effects of structural plasticity rather than understanding the mechanisms of rTMS, our model is not valuable regarding the latter.
Although changes in GM further underline the potential of rTMS to interfere actively with cortical plasticity in humans (Siebner and Rothwell 2003), the neurobiological basis of these structural alterations on a microscopic level is not well defined. VBM detects changes in GM concentration per voxel as well as changes in the classification of individual voxels, for example, from WM to GM (Good and others 2001a) and probably a combination of both. In general, an increase in GM could be due to an increase in cell size, neural or glial cell genesis, spine density, or even changes in blood flow or interstitial fluid. The latter possibility (increased interstitial fluid due to some sort of "injury") is unlikely as animal data show no such lesion (Okada and others 2002; Liebetanz and others 2003) and 2 weeks of repeated rTMS to the prefrontal cortex does not alter T2-weighted MRI in humans (Nahas and others 2000). Although the changes in GM that we observed may reflect alterations in cell genesis, the time course of our data suggest fast adjusting neuronal systems, such as spine and synapse turnover (Trachtenberg and others 2002), rather than such slow evolving mechanisms as neuronal or glial cell genesis (Kempermann and others 1997). Further work is needed to clarify whether vascular changes due to increased cerebral blood volume and/or cerebral blood flow may have additional effects to the observed changes (Swain and others 2003).
Independent of the precise histological nature of these structural alterations, our results support theoretical considerations stressing structural forms of neuroplasticity to be important in processing the information in dynamic networks according to novel informational demands (Chambers and others 2004). Based on our results, functional and structural cortical changes may not differ substantially with regard to onset. Rather the occurrence of dynamic structural alterations mirrored by changes in functional processing, such as in our study, exemplifies structural neuroplasticity as a counterpart of function. The obvious benefit of the central nervous system's capacity to change is the acquisition of new skills. In the process of learning, the brain has to change to be able to encode and appropriately implement new knowledge. It is reasonable to assume that plasticity is a characteristic of the nervous system that evolved for coping with changes in the environment. The challenge we face is to unravel the exact nature of the dynamic structural alterations and ultimately to be able to adapt and modulate this knowledge for disease management. Understanding normative changes in brain structure as a result of environmental changes and demands is pivotal to understanding the characteristic ability of the brain to adapt.
Ethical Considerations
As we have shown structural brain changes as a consequence of rTMS, some ethical considerations need to be addressed. When we first discussed this study with the local ethics committee, it was already known that rTMS does induce functional changes in humans (Bäumer and others 2003; Siebner and others 2003; Li and others 2004) and that rTMS can induce neurobiological effects resembling direct electrical stimulation producing neuroplasticity in animals (Wang and others 1996; Post and others 1997). However, as it was not clear whether we would find any possible structural changes, so we agreed to use the term "investigation of neuroplastic changes" on the consent form. Using the results of our study, one could argue that structural changes, that is, impact on cell structure, may reflect potential risks for the patients and that rTMS, at least if administered therapeutically, may therefore be harmful. None of our volunteers reported any side effects from either active or sham stimulation, and it needs to be pointed out that the changes in GM were transient and decreased again when the stimulation stopped.
Viewing our data in the context of a recent study demonstrating activity-dependent selective changes in GM induced in human adults after 3 months of training (Draganski and others 2004), we would rather suggest that any significant environmental change that requires specific functions, including learning specific tasks, has the potential to change brain structure. Our results certainly support theoretical considerations stressing structural forms of neuroplasticity to be important for processing information in dynamic networks according to novel informational demands (Chambers and others 2004). In future studies using rTMS as a therapeutical tool, we suggest that the possibility of functional along with structural brain changes as an eventual consequence to be included in the written informed consent form. Although 2 weeks of repeated rTMS to the prefrontal cortex does not alter T2-weighted MRI (Nahas and others 2000), animal studies are certainly mandatory to understand the mechanisms underlying VBM changes.
|
Supplementary Material |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Supplementary material can be found at: http://www.cercor.oxfordjournals.org/
|
Acknowledgments |
|---|
The authors wish to thank all volunteers for the participation in this study, G. Schuirer, and N. Lummel for technical support and E. Schoell and C. Buechel for valuable discussions. AM is supported by a grant of the Deutsche Forschungsgemeinschaft (MA 1862/2). Conflict of Interest: None declared.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionSupplementary MaterialReferences |
|---|
Ashburner J, Andersson JL, Friston KJ. (2000) Image registration using a symmetric prior—in three dimensions. Hum Brain Mapp 9:212–225.[CrossRef][Web of Science][Medline]
Ashburner J and Friston KJ. (2000) Voxel-based morphometry—the methods. Neuroimage 11:805–821.[CrossRef][Web of Science][Medline]
Bäumer T, Lange R, Liepert J, Weiller C, Siebner HR, Rothwell JC, Munchau A. (2003) Repeated premotor rTMS leads to cumulative plastic changes of motor cortex excitability in humans. Neuroimage 20:550–560.[CrossRef][Web of Science][Medline]
Chambers RA, Potenza MN, Hoffman RE, Miranker W. (2004) Simulated apoptosis/neurogenesis regulates learning and memory capabilities of adaptive neural networks. Neuropsychopharmacology 29:747–758.[CrossRef][Web of Science][Medline]
Chen WR, Lee S, Kato K, Spencer DD, Shepherd GM, Williamson A. (1996) Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex. Proc Natl Acad Sci USA 93:8011–8015.
Destexhe A, Contreras D, Steriade M. (1998) Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells. J Neurophysiol 79:999–1016.
Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A. (2004) Neuroplasticity: changes in grey matter induced by training. Nature 427:311–312.[CrossRef][Medline]
Eichhammer P, Langguth B, Marienhagen J, Kleinjung T, Hajak G. (2003) Neuronavigated repetitive transcranial magnetic stimulation in patients with tinnitus: a short case series. Biol Psychiatry 54:862–865.[CrossRef][Web of Science][Medline]
Evans AC, Kamber M, Collins DL, MacDonald D. (1994) An MRI-based probabilistic atlas of neuroanatomy. In Shorvon S, Fish D, Andermann F, Bydder GM, Stefan H (Eds.). Magnetic resonance scanning and epilepsy(Plenum Press, New York (NY)) pp. 263–274.
Friston KJ, Holmes AP, Ashburner J, Poline J-B. 1999. SPM99. Available at: http://www.fil.ion.ucl.as.uk/spm.
Good CD, Johnsrude I, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. (2001a) Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains. Neuroimage 14:685–700.[CrossRef][Web of Science][Medline]
Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. (2001b) A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14:21–36.[CrossRef][Web of Science][Medline]
Grutzendler J, Kasthuri N, Gan WB. (2002) Long-term dendritic spine stability in the adult cortex. Nature 420:812–816.[CrossRef][Medline]
Gumprecht HK, Widenka DC, Lumenta CB. (1999) BrainLab VectorVision neuronavigation system: technology and clinical experiences in 131 cases. Neurosurgery 44:97–104; discussion 10:4–105.
Herwig U, Schonfeldt-Lecuona C, Wunderlich AP, von Tiesenhausen C, Thielscher A, Walter H, Spitzer M. (2001) The navigation of transcranial magnetic stimulation. Psychiatry Res 108:123–131.[CrossRef][Web of Science][Medline]
Hoffman RE and Cavus I. (2002) Slow transcranial magnetic stimulation, long-term depotentiation, and brain hyperexcitability disorders. Am J Psychiatry 159:1093–1102.
Kempermann G, Kuhn HG, Gage FH. (1997) More hippocampal neurons in adult mice living in an enriched environment. Nature 386:493–495.[CrossRef][Medline]
Langguth B, Eichhammer P, Wiegand R, Marienhegen J, Maenner P, Jacob P, Hajak G. (2003) Neuronavigated rTMS in a patient with chronic tinnitus. Effects of 4 weeks treatment. Neuroreport 14:977–980.[CrossRef][Web of Science][Medline]
Li X, Nahas Z, Kozel FA, Anderson B, Bohning DE, George MS. (2004) Acute left prefrontal transcranial magnetic stimulation in depressed patients is associated with immediately increased activity in prefrontal cortical as well as subcortical regions. Biol Psychiatry 55:882–890.[CrossRef][Web of Science][Medline]
Liebetanz D, Fauser S, Michaelis T, Czeh B, Watanabe T, Paulus W, Frahm J, Fuchs E. (2003) Safety aspects of chronic low-frequency transcranial magnetic stimulation based on localized proton magnetic resonance spectroscopy and histology of the rat brain. J Psychiatr Res 37:277–286.[CrossRef][Web of Science][Medline]
May A, Ashburner J, Buchel C, McGonigle DJ, Friston KJ, Frackowiak RS, Goadsby PJ. (1999) Correlation between structural and functional changes in brain in an idiopathic headache syndrome. Nat Med 5:836–838.[CrossRef][Web of Science][Medline]
Nahas Z, DeBrux C, Chandler V, Lorberbaum JP, Speer AM, Molloy MA, Liberatos C, Risch SC, George MS. (2000) Lack of significant changes on magnetic resonance scans before and after 2 weeks of daily left prefrontal repetitive transcranial magnetic stimulation for depression. J Ect 16:380–390.[Web of Science][Medline]
Nolte J. (2001) The human brain: an intoduction to its functional anatomy(Mosby, St. Louis, MO).
Okada K, Matsunaga K, Yuhi T, Kuroda E, Yamashita U, Tsuji S. (2002) The long-term high-frequency repetitive transcranial magnetic stimulation does not induce mRNA expression of inflammatory mediators in the rat central nervous system. Brain Res 957:37–41.[CrossRef][Web of Science][Medline]
Plewnia C, Bartels M, Gerloff C. (2003) Transient suppression of tinnitus by transcranial magnetic stimulation. Ann Neurol 53:263–266.[CrossRef][Web of Science][Medline]
Post RM, Weiss SR, Smith M, Li H, McCann U. (1997) Kindling versus quenching. Implications for the evolution and treatment of posttraumatic stress disorder. Ann N Y Acad Sci 821:285–295.[Web of Science][Medline]
Poulet E, Brunelin J, Bediou B, Bation R, Forgeard L, Dalery J, d'Amato T, Saoud M. (2005) Slow transcranial magnetic stimulation can rapidly reduce resistant auditory hallucinations in schizophrenia. Biol Psychiatry 57:188–191.[CrossRef][Web of Science][Medline]
Read HL, Winer JA, Schreiner CE. (2002) Functional architecture of auditory cortex. Curr Opin Neurobiol 12:433–440.[CrossRef][Web of Science][Medline]
Schonfeldt-Lecuona C, Gron G, Walter H, Buchler N, Wunderlich A, Spitzer M, Herwig U. (2004) Stereotaxic rTMS for the treatment of auditory hallucinations in schizophrenia. Neuroreport 15:1669–1673.[CrossRef][Web of Science][Medline]
Siebner HR, Filipovic SR, Rowe JB, Cordivari C, Gerschlager W, Rothwell JC, Frackowiak RS, Bhatia KP. (2003) Patients with focal arm dystonia have increased sensitivity to slow-frequency repetitive TMS of the dorsal premotor cortex. Brain 126:2710–2725.
Siebner HR and Rothwell J. (2003) Transcranial magnetic stimulation: new insights into representational cortical plasticity. Exp Brain Res 148:1–16.[CrossRef][Web of Science][Medline]
Stahl SM, Nierenberg AA, Gorman JM. (2001) Evidence of early onset of antidepressant effect in randomized controlled trials. J Clin Psychiatry 62(Suppl 4):17–23; discussion 3:7–40.
Swain RA, Harris AB, Wiener EC, Dutka MV, Morris HD, Theien BE, Konda S, Engberg K, Lauterbur PC, Greenough WT. (2003) Prolonged exercise induces angiogenesis and increases cerebral blood volume in primary motor cortex of the rat. Neuroscience 117:1037–1046.[CrossRef][Web of Science][Medline]
Tergau F, Naumann U, Paulus W, Steinhoff BJ. (1999) Low-frequency repetitive transcranial magnetic stimulation improves intractable epilepsy. Lancet 353:2209.[CrossRef][Web of Science][Medline]
Trachtenberg JT, Chen BE, Knott GW, Feng G, Sanes JR, Welker E, Svoboda K. (2002) Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nature 420:788–794.[CrossRef][Medline]
Wang H, Wang X, Scheich H. (1996) LTD and LTP induced by transcranial magnetic stimulation in auditory cortex. Neuroreport 7:521–525.[Web of Science][Medline]
Woermann FG, Free SL, Koepp MJ, Ashburner J, Duncan JS. (1999) Voxel-by-voxel comparison of automatically segmented cerebral gray matter—A rater-independent comparison of structural MRI in patients with epilepsy. Neuroimage 10:373–384.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  A. May Morphing voxels: the hype around structural imaging of headache patients Brain, June 1, 2009; 132(6): 1419 - 1425. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. D. Fourkas, V. Bonavolonta, A. Avenanti, and S. M. Aglioti Kinesthetic Imagery and Tool-Specific Modulation of Corticospinal Representations in Expert Tennis Players Cereb Cortex, October 1, 2008; 18(10): 2382 - 2390. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. G. Duerden and D. Laverdure-Dupont Practice Makes Cortex J. Neurosci., August 27, 2008; 28(35): 8655 - 8657. [Full Text] [PDF]
|
|
|
|
|
|
R. Ilg, A. M. Wohlschlager, C. Gaser, Y. Liebau, R. Dauner, A. Woller, C. Zimmer, J. Zihl, and M. Muhlau Gray Matter Increase Induced by Practice Correlates with Task-Specific Activation: A Combined Functional and Morphometric Magnetic Resonance Imaging Study J. Neurosci., April 16, 2008; 28(16): 4210 - 4215. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. K. Holzel, U. Ott, T. Gard, H. Hempel, M. Weygandt, K. Morgen, and D. Vaitl Investigation of mindfulness meditation practitioners with voxel-based morphometry Soc Cogn Affect Neurosci, March 1, 2008; 3(1): 55 - 61. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Aydin, A. Ucar, K.K. Oguz, O.O. Okur, A. Agayev, Z. Unal, S. Yilmaz, and C. Ozturk Increased Gray Matter Density in the Parietal Cortex of Mathematicians: A Voxel-Based Morphometry Study AJNR Am. J. Neuroradiol., November 1, 2007; 28(10): 1859 - 1864. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Rossi, A. De Capua, M. Ulivelli, S. Bartalini, V. Falzarano, G. Filippone, and S. Passero Effects of repetitive transcranial magnetic stimulation on chronic tinnitus: a randomised, crossover, double blind, placebo controlled study J. Neurol. Neurosurg. Psychiatry, August 1, 2007; 78(8): 857 - 863. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||