Journal of the Neurological Sciences 351 (2015) 52–57
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Fatigue in patients with multiple sclerosis: From movement preparation to motor execution Margherita Russo a,⁎,1, Domenica Crupi b,1, Antonino Naro a, Laura Avanzino c, Maria Buccafusca d, Vincenzo Dattola d, Carmen Terranova d, Fabrizio Sottile e, Vincenzo Rizzo d, Maria Felice Ghilardi f, Paolo Girlanda d, Marco Bove c, Angelo Quartarone d a
IRCCS Centro Neurolesi “Bonino Pulejo”, Messina, Italy Regional Epilepsy Centre “Bianchi Melacrino Morelli” Hospital, Reggio, Calabria, Italy c Department of Experimental Medicine, Section of Human Physiology and Centro Polifunzionale di Scienze Motorie, University of Genoa, Italy d Department of Neuroscience, University of Messina, Italy e Department of Clinical and Experimental Medicine, University of Messina, Italy f Department of Physiology, Pharmacology and Neuroscience, City University of New-York, Medical School, New York, USA b
a r t i c l e
i n f o
Article history: Received 15 September 2014 Received in revised form 9 February 2015 Accepted 17 February 2015 Available online 23 February 2015 Keywords: Multiple sclerosis Fatigue Motor task Transcranial magnetic stimulation Kinematic parameters Premotor facilitation
a b s t r a c t Background: The neural mechanisms underlying fatigue in multiple sclerosis (MS) are still poorly understood. Cortico-cortical and cortico-subcortical circuitry abnormalities may play a central role in its pathogenesis. Our previous studies suggest that central fatigue may be related to an impairment of volition drive during movement preparation. Objective: We further explored the central mechanisms of fatigue at the premovement level in MS patients during a sustained motor task. Methods: In MS patients with (MS-F) and without (MS-NF) fatigue and age-matched healthy controls, we evaluated the motor cortex excitability and the premovement facilitation (PMF) through transcranial magnetic stimulation before and after 5 min of sequenced finger-tapping movements at a fixed frequency of 2 Hz. Results: In MS-F patients, the number of correct sequences performed and the ability to keep a fixed movement rate during the 5-min motor task were significantly decreased in comparison to the normal controls and MS-NF patients. Also, in MS-F patients, post-exercise PMF was significantly decreased. The PMF abnormalities were highly correlated with the performance decay. Conclusions: PMF may be considered as a kind of servo-mechanism which could play a crucial role during sustained motor task in order to prevent motor performance disruption and to avoid motor exhaustion. © 2015 Elsevier B.V. All rights reserved.
1. Introduction The Multiple Sclerosis (MS) Council for Clinical Practice Guidelines has defined fatigue as “a subjective lack of physical and-or mental energy that is perceived by the individual or caregiver to interfere with usual and desired activities” [21]. Fatigue is one of the most troubling symptoms for about 75% of MS patients [2,16]. Approved treatments for MS have only a limited effect on fatigue [1]. Its causes are still poorly understood, although several pathophysiologic mechanisms have been proposed. On one hand, “central” abnormalities within cortico-cortical and cortico-subcortical circuits, in particular the thalamo-striatocortical loop, may play an important role [5,14]. On the other hand,
⁎ Corresponding author at: IRCCS Centro Neurolesi “Bonino-Pulejo” Messina, S.S. 113, Contrada Casazza, 98124, Messina, Italy. Tel.: +39 09060128954; fax: +39 09060128950. E-mail address: [email protected] (M. Russo). 1 These authors equally contributed to the work.
http://dx.doi.org/10.1016/j.jns.2015.02.031 0022-510X/© 2015 Elsevier B.V. All rights reserved.
impairment of cortical facilitatory–inhibitory circuits might also play a role, probably with a decrease of volition drive to the descending motor pathways that originates upstream the primary motor cortex [18,19]. Finally, a demyelization of either neural pathways to corticospinal-tract or the facilitatory afferent projections could contribute to fatigue [31]. We have recently shown that MS patients with fatigue tested in a resting condition lacked premovement facilitation (PMF) evaluated through transcranial magnetic stimulation (TMS). This abnormality significantly correlated with the frontal lobe lesion load and with the Fatigue Severity Scale (FSS) scores [20]. Since PMF reflects excitability changes of the motor cortex preceding the movement onset, it is conceivable that movement preparation might be abnormal in MS patients with fatigue. Therefore, with this work we further explored the central mechanisms of fatigue by focusing on the premovement interval in MS patients during a sustained motor task. For this purpose, we evaluated the changes in cortical excitability and in PMF before and after the performance of 5 min of sequenced finger movements at a frequency of 2 Hz.
M. Russo et al. / Journal of the Neurological Sciences 351 (2015) 52–57
2. Materials and methods 2.1. Subjects Ten healthy controls (HC) and 24 MS patients, of whom 12 complained fatigue (FSS N 36) (see Table 1) were enrolled in the study. Inclusion criteria for the patients were: age of 18–65 years, diagnosis of definite relapsing-remitting (RR), absence of clinical relapses from at least 6 months prior to study entry, no gadolinium enhanced lesions on baseline brain and spinal cord magnetic resonance imaging (MRI), mild neurological impairment with an Expanded Disability Status Scale (EDSS) score of ≤ 2.5, Hamilton rating depression scale (HRDS) score of ≤16, Frontal Assessment Battery (FAB) score N12, no history of psychosis, no concomitant therapy with drugs acting on central nervous system (i.e. steroids, amantadine, antidepressants or antipsychotics), right handedness, normal visual evoked potentials (since in our protocol patients had to react to a visual go signal), central conduction time in upper limbs of b 8 ms, and no contraindication to safety TMS procedure. Hand-skill preservation in HC was carefully clinically assessed. The experiment was approved by the local ethics committees and all subjects gave their written informed consent for the experiments, according to the declaration of Helsinki. 2.2. Transcranial magnetic stimulation Focal TMS was applied using a standard figure-of-eight coil with mean loop diameters of 9 cm connected to a High Power Magstim 200 stimulator (The Magstim Company, Whitland, UK). The coil was held tangentially to the skull with the handle pointing backwards and laterally at an angle of 45° to the sagittal plane, thus generating a posterior– anterior current in the brain. The optimal position for activating the contralateral abductor pollicis brevis (APB) (marked with a pen as the motor hot spot) was established by moving the coil in 0.5 cm steps around the presumed primary motor hand area. Stimulus intensity
Table 1 Clinical-demographic characteristics. Group
Gender
Age (years)
FSS
FAB
HRDS
EDSS
NF_1 NF_2* NF_3 NF_4* NF_5 NF_6 NF_7 NF_8 NF_9 NF_10 NF_11* NF_12* Mean ± SD F_1 F_2* F_3 F_4 F_5* F_6 F_7 F_8 F_9 F_10 F_11 F_12 Mean ± SD
M F M F M M M F M F F M F:42% M F F M F M F M M F F F F:58%
38 40 34 37 36 53 45 36 23 29 42 53 39 ± 9 49 39 37 48 43 32 29 38 38 49 41 46 41 ± 7
27 32 9 35 15 16 9 13 12 9 34 30 20 ± 11 48 39 56 55 37 54 44 59 53 51 48 52 50 ± 7
17 16 18 18 18 18 18 18 16 16 18 17 17 ± 1 17 17 17 18 17 17 16 18 16 16 17 17 17 ± 1
3 12 0 7 6 2 0 0 0 0 3 2 3±4 16 12 9 11 1 3 9 8 9 15 8 5 9±5
2 1.5 2.5 1.5 1 2.5 1 2 2 1.5 2 1.5 2±1 2.5 2 1 1 1.5 1 1.5 1.5 2 2.5 1 2 2±1
MS patients were grouped according to the FSS score, with a cut-off value of ≥36 [17]. Moreover, each patient showed an FAB value greater than the cut-off (N12) [15], and an HRDS score ranging from no depression (0–7), up to mild depression (8–16) [33]. Borderline FSS score patients are marked with *. EDSS: Expanded Disability Status Scale; HRDS: Hamilton Rating Depression Scale; FAB: Frontal Assessment Battery; FSS: Fatigue Severity Scale.
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was set at a stimulator output that induced motor evoked potentials (MEPs) of about 0.5 mV in the relaxed APB muscle. MEPs were recorded using a pair of Ag–AgCl surface electrodes placed over the APB using a belly-tendon montage. Raw signals were amplified and filtered using a time constant of 3 ms and a high pass filter set at 3 kHz (Neurolog System, Digitimer Ltd., Welwyn Garden City, Herts, UK) and digitalized using a CED1401 laboratory interface (Cambridge Electronic Design Ltd., Cambridge, UK). Data were collected on a personal computer (Signal 3.0, Cambridge Electronic Design Ltd., Cambridge, UK) and analyzed off-line. High gain audiovisual EMG monitoring was used to ensure complete muscular relaxation. Twenty MEPs without reaction time (RT) (i.e. control-MEP) were recorded from resting APB muscle, in order to assess the motor excitability (Fig. 1). Control-MEPs were collected at baseline and immediately (T 0 ), 15 (T 15) and 30 (T 30 ) min after the end of the sustained motor task. Control-MEP amplitudes after the motortask were normalized to the baseline control-MEP. 2.3. RT and PMF PMF was assessed with a simple reaction time paradigm [12] (Fig. 1). Subjects were sitting in front of a monitor, with the right hand resting comfortably on a surface. They were asked to completely relax between trials. During each trial, they were asked to briskly abduct the right thumb in response to a go signal presented on the screen. No prior warning signal was given. All participants performed the task properly after a few minutes of training. We first assessed the mean RT in twenty of such RT trials. Then, we used the same paradigm with TMS randomly delivered at 50, 100 or 150 ms prior to the movement onset, in order to assess the PMF. The TMS-movement-onset interval was individually adapted (Fig. 1). The intensity of magnetic stimuli was the same used for control-MEP elicitation. We recorded twenty RT-MEP at each of the three RT intervals (50, 100 or 150 ms), which were randomly intermingled with twenty control-RT (i.e., RT without TMS). The mean was calculated by averaging the reaction time from twenty such RT-trials. The investigators performing TMS were blinded to which group the subjects belonged. All these parameters (PMF at each interval and the RT) were tested at baseline and immediately (T0), 15 (T15) and 30 (T30) min after the end of the motor task. The RT-MEP amplitudes at 50 ms, 100 ms or 150 ms after the motortask were computed as ratio of the baseline RT-MEP. Hence the PMF presence is indexed by an MEP ratio ≥ 1. 2.4. Motor task Subjects wore a sensor-engineered glove [6] and were instructed to perform, with eyes closed, a 5-min task of repetitive finger opposition movements with the right hand (thumb to index–middle–ring–little), paced at 2 Hz through a metronome. Data were acquired at 1 kHz. For each movement, we measured: touch duration (TD), as the contact time (in ms) between thumb and a finger; inter-tapping interval (ITI), as the time between the end of a thumb-finger contact and the beginning of following one; the mean movement rate (MR); and the percentage of correct sequences (%SEQCORR), as the number of sequences without any errors (e.g. double contacts, missing contacts). Sequences in which a finger contact was erroneous or missing were automatically rejected. Hence, a single error was computed, without leading to a cascade of subsequent errors. 2.5. Statistical analysis The normal distribution of the data in each group was evaluated with the Kolmogorov–Smirnov test (for all p N 0.2). Baseline electrophysiological parameters (control-MEP, control-RT, RT-MEP) between the HC, MS-NF and MS-F patients were compared using unpairedsample t-tests. Motor performance was evaluated by means of two-
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M. Russo et al. / Journal of the Neurological Sciences 351 (2015) 52–57
Fig. 1. Experimental design and the RT paradigm. We measured at baseline the control-MEP, the RT, and the RT-MEP. Then, subjects performed the motor task and we measured the kinematic parameters. The baseline parameters were also measured immediately after the end of the motor task (T0), and after 15 (T15) and 30 min after (T30). The RT paradigm is reported in the lower part of the figure.
way repeated measure analysis of variance (rm-ANOVA) for every kinematic parameter (TD, ITI, %SEQCORR, and MR), with minute (five levels: min1, min2, min3, min4, and min5) as within-subject factor and group (three levels: HC, MS-NF, and MS-F) as between-subject factor. The effects of the fatiguing motor task on RT, MEP, and PMF were analyzed by means of an rm-ANOVA. In particular, for the dependent variable control-MEP amplitude we applied a two-way rm-ANOVA with time (four levels: baseline, T0, T15, and T30) as within-subject factor and group (three levels: HC, MS-NF, and MS-F) as between subject factor. Concerning PMF, for the dependent variable RT-MEP we carried out a three way rm-ANOVA with time (four levels: baseline, T0, T15, T30) and interval (three levels: 50, 100 and 150 ms) as within-subject factors, and group (three levels: HC, MS-NF and MS-F) as between-subject factor. A p-value b 0.05 was considered significant. The Greenhouse– Geisser method was used if necessary to correct for non-sphericity. Post-hoc paired sample t-tests were carried-out to assess the significance of every effect and interaction, applying the Bonferroni correction for multiple comparisons. Correlations were made using a Pearson's correlation analysis.
from the first minute of the task (p = 0.01). Also, the number of correct sequences was significantly lower at the end than at the beginning of the task in the MS-F group (p = 0.03), whereas MS-NF showed only a trend toward reduction. Analysis of MR yielded different results in the three groups, as revealed by the significant interaction minute × group (F(8,248) = 3.8, p = 0.01). Movement rate was lower at all time points in MS-F patients compared to the MS-F group (post-hoc: first minute: p = 0.009; last minute: p b 0.001; Fig. 3), and it continuously decreased throughout the task. MR in MS-NF patients and HC were constantly kept around 2 Hz for the duration of the task.
3. Results 3.1. Motor performance In all experiments, subjects learned to move at the frequency imposed by the metronome within the first 10–30 movements. During the 5-min task, the means of TD and ITI were stable in all groups, while the number of correct sequences significantly decreased over time, especially in the MS-F group (see Fig. 2). In fact, a repeated measure ANOVA showed a significant effect of factor minute (F(4,124) = 2.8, p = 0.04) and a post-hoc t-test revealed a decreased number of correct sequences in the MS-F group in comparison to MS-NF patients starting
Fig. 2. %SEQCORR timeline. Normal individuals (N) and non-fatigue (NF) patients sufficiently performed the motor task, whereas the fatigue patients (F) quickly worsened already from the beginning of the third minute. The error bars refer to SE. * indicates a statistically significant decrease (p b 0.05) of %SEQCORR in F patients, the # the NF-F difference (p b 0.05).
M. Russo et al. / Journal of the Neurological Sciences 351 (2015) 52–57
Fig. 3. MR timeline. Normal individuals (N) and non-fatigue (NF) patients sufficiently performed the motor task, whereas the fatigue patients (F) quickly worsened already from the beginning of motor task, and in particular in the last minute. The error bars refer to SE. * indicates a statistically significant decrease (p b 0.05) of %SEQCORR in F patients, # the NF-F difference (p b 0.05).
3.2. Control-MEP amplitude Control-MEP amplitude showed significant changes after the motor task in all groups, as revealed by the significant time × group interaction (F(6,186) = 2.3, p = 0.04). Specifically, after the 5-min motor task, the average amplitude of the control-MEP slightly increased in HC and decreased in MS-NF, although these changes did not reach statistical significance with post-hoc tests. On the other hand, the amplitude of control-MEP in MS-F patients significantly decreased immediately after the 5-min task at T0 (p = 0.003) and fully recovered already at T15 (Fig. 4).
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Fig. 5. PMF50ms modulation. We show the PMF50ms modulation before and after 5 min of sustained motor task in each group. In comparison to normal individuals (N) and non-fatigue (NF) patients, who showed a normal PMF (#, p b 0.05), i.e. a normal ratio between the RTMEP and the control-MEP, MS-F patients showed a failure in PMF already at baseline and no modulation after the sustained motor task. On the contrary, NF and N showed a post-exercise increase of RT-MEP/control-MEP ratio, although it was limited to T15 in NF patients. * refers to a significant increase (p b 0.05) in PMF amplitude in N at T0, T15 and T30, and at T0 in NF (p b 0.05).
0.006). Moreover, immediately after the end of the motor task (T0), HC showed a significant RT-MEP increase at 50 ms (p b 0.001), which lasted up to T30, while MS-NF patients presented a significant PMF50ms increase only at T0 (p = 0.02). On the other side, the MS-F patients did not show any amplitude change in PMF50ms (Fig. 5). We then performed correlative analyses between the changes in corticospinal excitability (control-MEP) and PMF immediately after the task (T0) in MS-F patients. We found that the PMF50ms lack of facilitation significantly correlated with post-task decrease of control-MEP amplitude (r = 0.9, p b 0.001) and with the decrease in MR (r = 0.8, p = 0.01). 4. Discussion
3.3. MEP amplitude during PMF paradigm RT during the facilitation paradigm (PMF) was longer at all time points in the MS-F than in the MS-NF group (257 ± 25 vs. 175 ± 20 ms, p = 0.02) and did not vary after the motor task. Concerning RTMEP, repetitive measure ANOVA showed a main effect of time (F(3,93) = 3.9, p = 0.01) and RT interval (F(2,62) = 4.5, p = 0.01) as well as a significant time × group interaction at 50 ms RT interval (F(6,186) = 4, p = 0.02). Indeed, at baseline (i.e. before the motor task), we observed a significant increase of RT-MEP amplitude at 50 ms of RT interval in MS-NF (p = 0.02) and in HC group (p b 0.001) (Fig. 5). On the other hand, in keeping with a previous finding of our group [20], MS-F patients did not show any significant PMF at 50 ms, with a significant difference between MS-F and MS-NF patients (p =
Fig. 4. Control-MEP amplitude modulation. We found a significant PED in the resting APB after 5 min of sustained motor task in fatigue patients (F). The error bars refer to SE. * indicates a significant difference (p b 0.05) in MEP amplitude at T0 for MS-F group.
In the present study, we assessed functional cortical changes induced by the execution of a simple motor task in healthy controls and in patients affected by MS with and without fatigue. Our results show that control-MEP amplitude decreases after a 5-min motor task in MS patients with fatigue. Indeed, we have previously found in the same motor task in healthy controls that 10 min of continuous motor performance induced a transient reduction of cortical excitability as indexed by the decrease of MEP amplitude immediately after the sustained motor task, whereas 5-min task did not induce such motor disruption [13]. This physiological phenomenon is known as “post-exercise depression” (PED). Indeed, in healthy subjects a non-exhaustive exercise usually induces an increase of MEP amplitude, the so-called post-exercise facilitation (PEF) [3]. However, if the exercise is prolonged until the muscle fatigue, border PEF is followed by an MEP amplitude decrease or PED, which is determined by intra-cortical phenomena [7, 8,27]. Interestingly, our MS-F patients exhibited PED after just a 5-min motor task, whereas controls and MS-NF showed facilitation. In MS-F patients, the control-MEP post-exercise depression was paralleled by a decrease in the number of correct sequences and in movement rate. Other studies have used TMS to study the genesis of central fatigue. Thickbroom and coworkers [29] found a greater post-exercise depression in MS-F than MS-NF patients. However, the motor task used had different characteristics, as they applied a 20-min intermittent submaximal (40%) contraction of the first dorsal interosseous muscle. Similar differences between MS-F and MS-NF patients in terms of post-exercise depression were reported in other studies [18,19,25,28]. On the other hand, the use of a short isometric contraction at half of maximal voluntary contraction as fatiguing exercise did not induce any significant post-exercise depression in MS-F patients [24]. The variable results are likely due to methodological differences of these studies. Indeed, we found in normal subjects a significant increase in premovement facilitation after a 5-minute continuous exercise, without any performance
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disruption. It is likely that the increase of premovement facilitation during sustained motor activity may assist motor cortex in maintaining an adequate cortico-spinal drive, thus preventing motor performance deterioration [13]. After the same 5-min exercise, we found an increase of PMF at 50 ms in the controls and in the MS-NF group, but not in the MS-F group. Indeed, MS-F patients displayed post-exercise depression as well as a deterioration of motor performance, suggesting that the two phenomena might be related. It is worthy to note that MS-NF patients showed an increase of PMF only at RT 50 ms at baseline, whereas in our previous study [20], we found similar increases also at RT 100 and 150 ms. This discrepancy might be due to differences in FSS scores, especially in terms of FSS borderline values (i.e. between 30 and 40, cutoff value 36). Indeed, our sample included a small number of borderline FSS patients, and differently distributed along the two MS-groups (4 patients in MS-NF group and 2 in MS-F), in comparison to the sample of Morgante's work (8 patients in the MS-F group). We previously demonstrated that the lesion load in frontal areas in MS patients correlates with the degree of fatigue expressed by the FSS score. This evidence was paralleled by a functional impairment of the motor areas involved in movement planning and preparation in fatigue patients, revealed by a lack of premovement facilitation. Interestingly, as reported in our previous paper [20], frontal gray matter (GM) volume was similar between MS-F and MS-NF, suggesting that fatigue might be related to a functional disconnection of frontal areas from basal ganglia, probably induced by an increased lesion load in those areas, rather than to a structural damage of frontal GM structures. This is in keeping with the notion of Roelcke and coworkers [26] who found in a fluorodeoxyglucose positron emission tomography study that MS patients with fatigue had decreased glucose metabolism within the frontal cortex and the basal ganglia in comparison with MS patients without fatigue. They also reported that FSS scores were negatively correlated with regional cerebral glucose metabolism in the right prefrontal cortex (BA 9/10). The authors suggested, in line with the theory by Chaudhuri and Behan [10], that demyelization of frontal white matter could give rise to disruption of the cerebral circuits connecting the cortex and basal ganglia, which in turn could cause fatigue. The role of basal ganglia on central fatigue in MS has been confirmed by subsequent studies. MRI perfusion studies of the deep GM in patients with relapsing-remitting and primary progressive MS demonstrated a decreased blood flow in the thalamus, putamen and caudate nuclei, correlating with FSS [10, 11]. In addition, Calabrese and co-workers showed reduced frontostriatal white mater integrity, basal ganglia and cortical atrophy in MS patients with fatigue [9]. In addition, it should be considered that the difficulty to keep the movement rate fixed at 2 Hz by the tones of a metronome in MS-F patients could be, at least in part, related to a dysfunction of the cerebello-thalamic-cortical pathways. Beside the involvement of cerebellum in the timing of movement [32], several other evidence supports this conclusion. In fact, recordings from the monkey's dentate nucleus in cerebellum [22] show that some neurons are preferentially involved in the movements triggered by visual cues (as in our visual reaction-time paradigm), as also suggested by the results of studies with externally triggered tasks in humans [5]. Furthermore, experimental damage of the monkey's dentate may decrease movement accuracy [4] as well as the amplitude of cortical premovement potentials in response to visual stimuli [30]. Further support comes from the recent finding of a positive correlation between subjective fatigue and temporal accuracy in MS patients with minimal disability; importantly, this association was mediated by the activity of orbitofrontal and cerebellar cortices [23]. Indeed, there are many limitations in the present study. Among them, the patient samples were relatively small; the subjective ratings of the fatigue perceived during and after the motor task were not assessed and no imaging studies were performed. In summary, the results of this study demonstrate that abnormal motor preparation may translate into an abnormal motor execution, as showed by the lack of PMF modulation during a sustained motor activity, the decreased number of correct sequences, and by the
difficulty of MS-F patients to perform movements at constant 2 Hz rate. Hence, we may argue that fatigue in MS is probably related to a functional impairment within the circuits engaged in movement preparation, upstream the corticospinal tract. However, at this point, a possible involvement of cerebello-thalamic-cortical pathways in motor execution deterioration cannot be ruled-out. Further studies are indeed required to ascertain the possible presence of structural abnormalities in the dorsolateral prefrontal–premotor networks and orbitofrontal– cerebellar loops of MS patients with fatigue. Conflict of interest None. Acknowledgements This study was supported by FISM (Fondazione Italiana Sclerosi Multipla) Grant 2008 awarded to A. Quartarone. References [1] Amato MP, Portaccio E. Management options in multiple sclerosis-associated fatigue. Expert Opin Pharmacother 2012;13:207–16. [2] Bakshi R. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler 2003;9:219–927. [3] Balbi P, Perretti A, Sannino M, Marcantonio L, Santoro L. Post-exercise facilitation of motor evoked potentials following transcranial magnetic stimulation: a study in normal subjects. Muscle Nerve 2002;25:448–52. [4] Beaubaton D, Trouche E. Participation of the cerebellar dentate nucleus in the control of a goal-directed movement in monkeys. Effects of reversible or permanent dentate lesion on the duration and accuracy of a pointing response. Exp Brain Res 1982;46:127–38. [5] Bonzano L, Tacchino A, Saitta L, Roccatagliata L, Avanzino L, Mancardi GL, et al. Basal ganglia are active during motor performance recovery after a demanding motor task. Neuroimage 2013;65:257–66. [6] Bove M, Tacchino A, Novellino A, Trompetto C, Abbruzzese G, Ghilardi MF. The effects of rate and sequence complexity on repetitive finger movements. Brain Res 2007;1153:84–91. [7] Brasil-Neto JP, Cohen LG, Hallett M. Central fatigue as revealed by postexercise decrement of motor evoked potentials. Muscle Nerve 1994;17:713–9. [8] Brasil-Neto JP, Pascual-Leone A, Valls-Solé J, Cammarota A, Cohen LG, Hallett M. Post-exercise depression of motor evoked potentials: a measure of central nervous system fatigue. Exp Brain Res 1993;93:181–4. [9] Calabrese M, Rinaldi F, Grossi P, Mattisi I, Bernardi V, Favaretto A, et al. Basal ganglia and frontal–parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Mult Scler 2010;16:1220–8. [10] Chaudhuri A, Behan PO. Fatigue and basal ganglia. J Neurol Sci 2000;179:34–42. [11] Chaudhuri A, Behan PO. Fatigue in neurological disorders. Lancet 2004;363:978–88. [12] Chen R, Tam A, Bütefisch C, Corwell B, Ziemann U, Rothwell JC, et al. Intracortical inhibition and facilitation in different representations of the human motor cortex. J Neurophysiol 1998;80:2870–81. [13] Crupi D, Cruciata G, Moisello C, Green PA, Naro A, Ricciardi L, et al. Protracted exercise without overt neuromuscular fatigue influences cortical excitability. J Mot Behav 2013;45:127–38. [14] DeLuca J, Genova HM, Hillary FG, Wylie G. Neural correlates of cognitive fatigue in multiple sclerosis using functional MRI. J Neurol Sci 2008;270:28–39. [15] Dubois B, Litvan I. The FAB: A frontal assessment battery at bedside. Neurology 2000; 55:1621–6. [16] Kos D, Kerckhofs E, Nagels G, D'hooghe MB, Ilsbroukx S. Origin of fatigue in multiple sclerosis: review of the literature. Neurorehabil Neural Repair 2008;22:91–100. [17] Krupp LB, La Rocca NG, Muir-Nash J, Steinberg AD. The Fatigue Severity Scale. Arch Neurol 1989;46:1121–3. [18] Ferrucci R, Vergari M, Cogiamanian F, Bocci T, Ciocca M, Tomasini E, et al. Transcranial direct current stimulation (tDCS) for fatigue in multiple sclerosis. Neurorehabilitation 2014;34:121–7. [19] Liepert J, Mingers D, Heesen C, et al. Motor cortex excitability and fatigue in multiple sclerosis: a transcranial magnetic stimulation study. Mult Scler 2005;11:316–21. [20] Morgante F, Dattola V, Crupi D, Russo M, Rizzo V, Ghilardi MF, et al. Is central fatigue in multiple sclerosis a disorder of movement preparation? J Neurol 2011;258: 263–72. [21] Multiple Sclerosis Council for Clinical Practice Guidelines. Fatigue and multiple sclerosis. Washington DC: Paralyzed Veterans of America; 1998. [22] Mushiake H, Strick PL. Preferential activity of dentate neurons during limb movements guided by vision. J Neurophysiol 1993;70:2660–4. [23] Pardini M, Bonzano L, Roccatagliata L, Mancardi GL, Bove M. The fatigue–motor performance paradox in multiple sclerosis. Sci Rep 2013;3:2001. [24] Perretti A, Balbi P, Orefice G, Trojano L, Marcantonio L, Brescia-Morra V, et al. Postexercise facilitation and depression of motor evoked potentials to transcranial magnetic stimulation: a study in multiple sclerosis. Clin Neurophysiol 2004;115: 2128–33.
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Fatigue in patients with multiple sclerosis: From movement preparation to motor execution Margherita Russo a,⁎,1, Domenica Crupi b,1, Antonino Naro a, Laura Avanzino c, Maria Buccafusca d, Vincenzo Dattola d, Carmen Terranova d, Fabrizio Sottile e, Vincenzo Rizzo d, Maria Felice Ghilardi f, Paolo Girlanda d, Marco Bove c, Angelo Quartarone d a
IRCCS Centro Neurolesi “Bonino Pulejo”, Messina, Italy Regional Epilepsy Centre “Bianchi Melacrino Morelli” Hospital, Reggio, Calabria, Italy c Department of Experimental Medicine, Section of Human Physiology and Centro Polifunzionale di Scienze Motorie, University of Genoa, Italy d Department of Neuroscience, University of Messina, Italy e Department of Clinical and Experimental Medicine, University of Messina, Italy f Department of Physiology, Pharmacology and Neuroscience, City University of New-York, Medical School, New York, USA b
a r t i c l e
i n f o
Article history: Received 15 September 2014 Received in revised form 9 February 2015 Accepted 17 February 2015 Available online 23 February 2015 Keywords: Multiple sclerosis Fatigue Motor task Transcranial magnetic stimulation Kinematic parameters Premotor facilitation
a b s t r a c t Background: The neural mechanisms underlying fatigue in multiple sclerosis (MS) are still poorly understood. Cortico-cortical and cortico-subcortical circuitry abnormalities may play a central role in its pathogenesis. Our previous studies suggest that central fatigue may be related to an impairment of volition drive during movement preparation. Objective: We further explored the central mechanisms of fatigue at the premovement level in MS patients during a sustained motor task. Methods: In MS patients with (MS-F) and without (MS-NF) fatigue and age-matched healthy controls, we evaluated the motor cortex excitability and the premovement facilitation (PMF) through transcranial magnetic stimulation before and after 5 min of sequenced finger-tapping movements at a fixed frequency of 2 Hz. Results: In MS-F patients, the number of correct sequences performed and the ability to keep a fixed movement rate during the 5-min motor task were significantly decreased in comparison to the normal controls and MS-NF patients. Also, in MS-F patients, post-exercise PMF was significantly decreased. The PMF abnormalities were highly correlated with the performance decay. Conclusions: PMF may be considered as a kind of servo-mechanism which could play a crucial role during sustained motor task in order to prevent motor performance disruption and to avoid motor exhaustion. © 2015 Elsevier B.V. All rights reserved.
1. Introduction The Multiple Sclerosis (MS) Council for Clinical Practice Guidelines has defined fatigue as “a subjective lack of physical and-or mental energy that is perceived by the individual or caregiver to interfere with usual and desired activities” [21]. Fatigue is one of the most troubling symptoms for about 75% of MS patients [2,16]. Approved treatments for MS have only a limited effect on fatigue [1]. Its causes are still poorly understood, although several pathophysiologic mechanisms have been proposed. On one hand, “central” abnormalities within cortico-cortical and cortico-subcortical circuits, in particular the thalamo-striatocortical loop, may play an important role [5,14]. On the other hand,
⁎ Corresponding author at: IRCCS Centro Neurolesi “Bonino-Pulejo” Messina, S.S. 113, Contrada Casazza, 98124, Messina, Italy. Tel.: +39 09060128954; fax: +39 09060128950. E-mail address: [email protected] (M. Russo). 1 These authors equally contributed to the work.
http://dx.doi.org/10.1016/j.jns.2015.02.031 0022-510X/© 2015 Elsevier B.V. All rights reserved.
impairment of cortical facilitatory–inhibitory circuits might also play a role, probably with a decrease of volition drive to the descending motor pathways that originates upstream the primary motor cortex [18,19]. Finally, a demyelization of either neural pathways to corticospinal-tract or the facilitatory afferent projections could contribute to fatigue [31]. We have recently shown that MS patients with fatigue tested in a resting condition lacked premovement facilitation (PMF) evaluated through transcranial magnetic stimulation (TMS). This abnormality significantly correlated with the frontal lobe lesion load and with the Fatigue Severity Scale (FSS) scores [20]. Since PMF reflects excitability changes of the motor cortex preceding the movement onset, it is conceivable that movement preparation might be abnormal in MS patients with fatigue. Therefore, with this work we further explored the central mechanisms of fatigue by focusing on the premovement interval in MS patients during a sustained motor task. For this purpose, we evaluated the changes in cortical excitability and in PMF before and after the performance of 5 min of sequenced finger movements at a frequency of 2 Hz.
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2. Materials and methods 2.1. Subjects Ten healthy controls (HC) and 24 MS patients, of whom 12 complained fatigue (FSS N 36) (see Table 1) were enrolled in the study. Inclusion criteria for the patients were: age of 18–65 years, diagnosis of definite relapsing-remitting (RR), absence of clinical relapses from at least 6 months prior to study entry, no gadolinium enhanced lesions on baseline brain and spinal cord magnetic resonance imaging (MRI), mild neurological impairment with an Expanded Disability Status Scale (EDSS) score of ≤ 2.5, Hamilton rating depression scale (HRDS) score of ≤16, Frontal Assessment Battery (FAB) score N12, no history of psychosis, no concomitant therapy with drugs acting on central nervous system (i.e. steroids, amantadine, antidepressants or antipsychotics), right handedness, normal visual evoked potentials (since in our protocol patients had to react to a visual go signal), central conduction time in upper limbs of b 8 ms, and no contraindication to safety TMS procedure. Hand-skill preservation in HC was carefully clinically assessed. The experiment was approved by the local ethics committees and all subjects gave their written informed consent for the experiments, according to the declaration of Helsinki. 2.2. Transcranial magnetic stimulation Focal TMS was applied using a standard figure-of-eight coil with mean loop diameters of 9 cm connected to a High Power Magstim 200 stimulator (The Magstim Company, Whitland, UK). The coil was held tangentially to the skull with the handle pointing backwards and laterally at an angle of 45° to the sagittal plane, thus generating a posterior– anterior current in the brain. The optimal position for activating the contralateral abductor pollicis brevis (APB) (marked with a pen as the motor hot spot) was established by moving the coil in 0.5 cm steps around the presumed primary motor hand area. Stimulus intensity
Table 1 Clinical-demographic characteristics. Group
Gender
Age (years)
FSS
FAB
HRDS
EDSS
NF_1 NF_2* NF_3 NF_4* NF_5 NF_6 NF_7 NF_8 NF_9 NF_10 NF_11* NF_12* Mean ± SD F_1 F_2* F_3 F_4 F_5* F_6 F_7 F_8 F_9 F_10 F_11 F_12 Mean ± SD
M F M F M M M F M F F M F:42% M F F M F M F M M F F F F:58%
38 40 34 37 36 53 45 36 23 29 42 53 39 ± 9 49 39 37 48 43 32 29 38 38 49 41 46 41 ± 7
27 32 9 35 15 16 9 13 12 9 34 30 20 ± 11 48 39 56 55 37 54 44 59 53 51 48 52 50 ± 7
17 16 18 18 18 18 18 18 16 16 18 17 17 ± 1 17 17 17 18 17 17 16 18 16 16 17 17 17 ± 1
3 12 0 7 6 2 0 0 0 0 3 2 3±4 16 12 9 11 1 3 9 8 9 15 8 5 9±5
2 1.5 2.5 1.5 1 2.5 1 2 2 1.5 2 1.5 2±1 2.5 2 1 1 1.5 1 1.5 1.5 2 2.5 1 2 2±1
MS patients were grouped according to the FSS score, with a cut-off value of ≥36 [17]. Moreover, each patient showed an FAB value greater than the cut-off (N12) [15], and an HRDS score ranging from no depression (0–7), up to mild depression (8–16) [33]. Borderline FSS score patients are marked with *. EDSS: Expanded Disability Status Scale; HRDS: Hamilton Rating Depression Scale; FAB: Frontal Assessment Battery; FSS: Fatigue Severity Scale.
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was set at a stimulator output that induced motor evoked potentials (MEPs) of about 0.5 mV in the relaxed APB muscle. MEPs were recorded using a pair of Ag–AgCl surface electrodes placed over the APB using a belly-tendon montage. Raw signals were amplified and filtered using a time constant of 3 ms and a high pass filter set at 3 kHz (Neurolog System, Digitimer Ltd., Welwyn Garden City, Herts, UK) and digitalized using a CED1401 laboratory interface (Cambridge Electronic Design Ltd., Cambridge, UK). Data were collected on a personal computer (Signal 3.0, Cambridge Electronic Design Ltd., Cambridge, UK) and analyzed off-line. High gain audiovisual EMG monitoring was used to ensure complete muscular relaxation. Twenty MEPs without reaction time (RT) (i.e. control-MEP) were recorded from resting APB muscle, in order to assess the motor excitability (Fig. 1). Control-MEPs were collected at baseline and immediately (T 0 ), 15 (T 15) and 30 (T 30 ) min after the end of the sustained motor task. Control-MEP amplitudes after the motortask were normalized to the baseline control-MEP. 2.3. RT and PMF PMF was assessed with a simple reaction time paradigm [12] (Fig. 1). Subjects were sitting in front of a monitor, with the right hand resting comfortably on a surface. They were asked to completely relax between trials. During each trial, they were asked to briskly abduct the right thumb in response to a go signal presented on the screen. No prior warning signal was given. All participants performed the task properly after a few minutes of training. We first assessed the mean RT in twenty of such RT trials. Then, we used the same paradigm with TMS randomly delivered at 50, 100 or 150 ms prior to the movement onset, in order to assess the PMF. The TMS-movement-onset interval was individually adapted (Fig. 1). The intensity of magnetic stimuli was the same used for control-MEP elicitation. We recorded twenty RT-MEP at each of the three RT intervals (50, 100 or 150 ms), which were randomly intermingled with twenty control-RT (i.e., RT without TMS). The mean was calculated by averaging the reaction time from twenty such RT-trials. The investigators performing TMS were blinded to which group the subjects belonged. All these parameters (PMF at each interval and the RT) were tested at baseline and immediately (T0), 15 (T15) and 30 (T30) min after the end of the motor task. The RT-MEP amplitudes at 50 ms, 100 ms or 150 ms after the motortask were computed as ratio of the baseline RT-MEP. Hence the PMF presence is indexed by an MEP ratio ≥ 1. 2.4. Motor task Subjects wore a sensor-engineered glove [6] and were instructed to perform, with eyes closed, a 5-min task of repetitive finger opposition movements with the right hand (thumb to index–middle–ring–little), paced at 2 Hz through a metronome. Data were acquired at 1 kHz. For each movement, we measured: touch duration (TD), as the contact time (in ms) between thumb and a finger; inter-tapping interval (ITI), as the time between the end of a thumb-finger contact and the beginning of following one; the mean movement rate (MR); and the percentage of correct sequences (%SEQCORR), as the number of sequences without any errors (e.g. double contacts, missing contacts). Sequences in which a finger contact was erroneous or missing were automatically rejected. Hence, a single error was computed, without leading to a cascade of subsequent errors. 2.5. Statistical analysis The normal distribution of the data in each group was evaluated with the Kolmogorov–Smirnov test (for all p N 0.2). Baseline electrophysiological parameters (control-MEP, control-RT, RT-MEP) between the HC, MS-NF and MS-F patients were compared using unpairedsample t-tests. Motor performance was evaluated by means of two-
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Fig. 1. Experimental design and the RT paradigm. We measured at baseline the control-MEP, the RT, and the RT-MEP. Then, subjects performed the motor task and we measured the kinematic parameters. The baseline parameters were also measured immediately after the end of the motor task (T0), and after 15 (T15) and 30 min after (T30). The RT paradigm is reported in the lower part of the figure.
way repeated measure analysis of variance (rm-ANOVA) for every kinematic parameter (TD, ITI, %SEQCORR, and MR), with minute (five levels: min1, min2, min3, min4, and min5) as within-subject factor and group (three levels: HC, MS-NF, and MS-F) as between-subject factor. The effects of the fatiguing motor task on RT, MEP, and PMF were analyzed by means of an rm-ANOVA. In particular, for the dependent variable control-MEP amplitude we applied a two-way rm-ANOVA with time (four levels: baseline, T0, T15, and T30) as within-subject factor and group (three levels: HC, MS-NF, and MS-F) as between subject factor. Concerning PMF, for the dependent variable RT-MEP we carried out a three way rm-ANOVA with time (four levels: baseline, T0, T15, T30) and interval (three levels: 50, 100 and 150 ms) as within-subject factors, and group (three levels: HC, MS-NF and MS-F) as between-subject factor. A p-value b 0.05 was considered significant. The Greenhouse– Geisser method was used if necessary to correct for non-sphericity. Post-hoc paired sample t-tests were carried-out to assess the significance of every effect and interaction, applying the Bonferroni correction for multiple comparisons. Correlations were made using a Pearson's correlation analysis.
from the first minute of the task (p = 0.01). Also, the number of correct sequences was significantly lower at the end than at the beginning of the task in the MS-F group (p = 0.03), whereas MS-NF showed only a trend toward reduction. Analysis of MR yielded different results in the three groups, as revealed by the significant interaction minute × group (F(8,248) = 3.8, p = 0.01). Movement rate was lower at all time points in MS-F patients compared to the MS-F group (post-hoc: first minute: p = 0.009; last minute: p b 0.001; Fig. 3), and it continuously decreased throughout the task. MR in MS-NF patients and HC were constantly kept around 2 Hz for the duration of the task.
3. Results 3.1. Motor performance In all experiments, subjects learned to move at the frequency imposed by the metronome within the first 10–30 movements. During the 5-min task, the means of TD and ITI were stable in all groups, while the number of correct sequences significantly decreased over time, especially in the MS-F group (see Fig. 2). In fact, a repeated measure ANOVA showed a significant effect of factor minute (F(4,124) = 2.8, p = 0.04) and a post-hoc t-test revealed a decreased number of correct sequences in the MS-F group in comparison to MS-NF patients starting
Fig. 2. %SEQCORR timeline. Normal individuals (N) and non-fatigue (NF) patients sufficiently performed the motor task, whereas the fatigue patients (F) quickly worsened already from the beginning of the third minute. The error bars refer to SE. * indicates a statistically significant decrease (p b 0.05) of %SEQCORR in F patients, the # the NF-F difference (p b 0.05).
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Fig. 3. MR timeline. Normal individuals (N) and non-fatigue (NF) patients sufficiently performed the motor task, whereas the fatigue patients (F) quickly worsened already from the beginning of motor task, and in particular in the last minute. The error bars refer to SE. * indicates a statistically significant decrease (p b 0.05) of %SEQCORR in F patients, # the NF-F difference (p b 0.05).
3.2. Control-MEP amplitude Control-MEP amplitude showed significant changes after the motor task in all groups, as revealed by the significant time × group interaction (F(6,186) = 2.3, p = 0.04). Specifically, after the 5-min motor task, the average amplitude of the control-MEP slightly increased in HC and decreased in MS-NF, although these changes did not reach statistical significance with post-hoc tests. On the other hand, the amplitude of control-MEP in MS-F patients significantly decreased immediately after the 5-min task at T0 (p = 0.003) and fully recovered already at T15 (Fig. 4).
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Fig. 5. PMF50ms modulation. We show the PMF50ms modulation before and after 5 min of sustained motor task in each group. In comparison to normal individuals (N) and non-fatigue (NF) patients, who showed a normal PMF (#, p b 0.05), i.e. a normal ratio between the RTMEP and the control-MEP, MS-F patients showed a failure in PMF already at baseline and no modulation after the sustained motor task. On the contrary, NF and N showed a post-exercise increase of RT-MEP/control-MEP ratio, although it was limited to T15 in NF patients. * refers to a significant increase (p b 0.05) in PMF amplitude in N at T0, T15 and T30, and at T0 in NF (p b 0.05).
0.006). Moreover, immediately after the end of the motor task (T0), HC showed a significant RT-MEP increase at 50 ms (p b 0.001), which lasted up to T30, while MS-NF patients presented a significant PMF50ms increase only at T0 (p = 0.02). On the other side, the MS-F patients did not show any amplitude change in PMF50ms (Fig. 5). We then performed correlative analyses between the changes in corticospinal excitability (control-MEP) and PMF immediately after the task (T0) in MS-F patients. We found that the PMF50ms lack of facilitation significantly correlated with post-task decrease of control-MEP amplitude (r = 0.9, p b 0.001) and with the decrease in MR (r = 0.8, p = 0.01). 4. Discussion
3.3. MEP amplitude during PMF paradigm RT during the facilitation paradigm (PMF) was longer at all time points in the MS-F than in the MS-NF group (257 ± 25 vs. 175 ± 20 ms, p = 0.02) and did not vary after the motor task. Concerning RTMEP, repetitive measure ANOVA showed a main effect of time (F(3,93) = 3.9, p = 0.01) and RT interval (F(2,62) = 4.5, p = 0.01) as well as a significant time × group interaction at 50 ms RT interval (F(6,186) = 4, p = 0.02). Indeed, at baseline (i.e. before the motor task), we observed a significant increase of RT-MEP amplitude at 50 ms of RT interval in MS-NF (p = 0.02) and in HC group (p b 0.001) (Fig. 5). On the other hand, in keeping with a previous finding of our group [20], MS-F patients did not show any significant PMF at 50 ms, with a significant difference between MS-F and MS-NF patients (p =
Fig. 4. Control-MEP amplitude modulation. We found a significant PED in the resting APB after 5 min of sustained motor task in fatigue patients (F). The error bars refer to SE. * indicates a significant difference (p b 0.05) in MEP amplitude at T0 for MS-F group.
In the present study, we assessed functional cortical changes induced by the execution of a simple motor task in healthy controls and in patients affected by MS with and without fatigue. Our results show that control-MEP amplitude decreases after a 5-min motor task in MS patients with fatigue. Indeed, we have previously found in the same motor task in healthy controls that 10 min of continuous motor performance induced a transient reduction of cortical excitability as indexed by the decrease of MEP amplitude immediately after the sustained motor task, whereas 5-min task did not induce such motor disruption [13]. This physiological phenomenon is known as “post-exercise depression” (PED). Indeed, in healthy subjects a non-exhaustive exercise usually induces an increase of MEP amplitude, the so-called post-exercise facilitation (PEF) [3]. However, if the exercise is prolonged until the muscle fatigue, border PEF is followed by an MEP amplitude decrease or PED, which is determined by intra-cortical phenomena [7, 8,27]. Interestingly, our MS-F patients exhibited PED after just a 5-min motor task, whereas controls and MS-NF showed facilitation. In MS-F patients, the control-MEP post-exercise depression was paralleled by a decrease in the number of correct sequences and in movement rate. Other studies have used TMS to study the genesis of central fatigue. Thickbroom and coworkers [29] found a greater post-exercise depression in MS-F than MS-NF patients. However, the motor task used had different characteristics, as they applied a 20-min intermittent submaximal (40%) contraction of the first dorsal interosseous muscle. Similar differences between MS-F and MS-NF patients in terms of post-exercise depression were reported in other studies [18,19,25,28]. On the other hand, the use of a short isometric contraction at half of maximal voluntary contraction as fatiguing exercise did not induce any significant post-exercise depression in MS-F patients [24]. The variable results are likely due to methodological differences of these studies. Indeed, we found in normal subjects a significant increase in premovement facilitation after a 5-minute continuous exercise, without any performance
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disruption. It is likely that the increase of premovement facilitation during sustained motor activity may assist motor cortex in maintaining an adequate cortico-spinal drive, thus preventing motor performance deterioration [13]. After the same 5-min exercise, we found an increase of PMF at 50 ms in the controls and in the MS-NF group, but not in the MS-F group. Indeed, MS-F patients displayed post-exercise depression as well as a deterioration of motor performance, suggesting that the two phenomena might be related. It is worthy to note that MS-NF patients showed an increase of PMF only at RT 50 ms at baseline, whereas in our previous study [20], we found similar increases also at RT 100 and 150 ms. This discrepancy might be due to differences in FSS scores, especially in terms of FSS borderline values (i.e. between 30 and 40, cutoff value 36). Indeed, our sample included a small number of borderline FSS patients, and differently distributed along the two MS-groups (4 patients in MS-NF group and 2 in MS-F), in comparison to the sample of Morgante's work (8 patients in the MS-F group). We previously demonstrated that the lesion load in frontal areas in MS patients correlates with the degree of fatigue expressed by the FSS score. This evidence was paralleled by a functional impairment of the motor areas involved in movement planning and preparation in fatigue patients, revealed by a lack of premovement facilitation. Interestingly, as reported in our previous paper [20], frontal gray matter (GM) volume was similar between MS-F and MS-NF, suggesting that fatigue might be related to a functional disconnection of frontal areas from basal ganglia, probably induced by an increased lesion load in those areas, rather than to a structural damage of frontal GM structures. This is in keeping with the notion of Roelcke and coworkers [26] who found in a fluorodeoxyglucose positron emission tomography study that MS patients with fatigue had decreased glucose metabolism within the frontal cortex and the basal ganglia in comparison with MS patients without fatigue. They also reported that FSS scores were negatively correlated with regional cerebral glucose metabolism in the right prefrontal cortex (BA 9/10). The authors suggested, in line with the theory by Chaudhuri and Behan [10], that demyelization of frontal white matter could give rise to disruption of the cerebral circuits connecting the cortex and basal ganglia, which in turn could cause fatigue. The role of basal ganglia on central fatigue in MS has been confirmed by subsequent studies. MRI perfusion studies of the deep GM in patients with relapsing-remitting and primary progressive MS demonstrated a decreased blood flow in the thalamus, putamen and caudate nuclei, correlating with FSS [10, 11]. In addition, Calabrese and co-workers showed reduced frontostriatal white mater integrity, basal ganglia and cortical atrophy in MS patients with fatigue [9]. In addition, it should be considered that the difficulty to keep the movement rate fixed at 2 Hz by the tones of a metronome in MS-F patients could be, at least in part, related to a dysfunction of the cerebello-thalamic-cortical pathways. Beside the involvement of cerebellum in the timing of movement [32], several other evidence supports this conclusion. In fact, recordings from the monkey's dentate nucleus in cerebellum [22] show that some neurons are preferentially involved in the movements triggered by visual cues (as in our visual reaction-time paradigm), as also suggested by the results of studies with externally triggered tasks in humans [5]. Furthermore, experimental damage of the monkey's dentate may decrease movement accuracy [4] as well as the amplitude of cortical premovement potentials in response to visual stimuli [30]. Further support comes from the recent finding of a positive correlation between subjective fatigue and temporal accuracy in MS patients with minimal disability; importantly, this association was mediated by the activity of orbitofrontal and cerebellar cortices [23]. Indeed, there are many limitations in the present study. Among them, the patient samples were relatively small; the subjective ratings of the fatigue perceived during and after the motor task were not assessed and no imaging studies were performed. In summary, the results of this study demonstrate that abnormal motor preparation may translate into an abnormal motor execution, as showed by the lack of PMF modulation during a sustained motor activity, the decreased number of correct sequences, and by the
difficulty of MS-F patients to perform movements at constant 2 Hz rate. Hence, we may argue that fatigue in MS is probably related to a functional impairment within the circuits engaged in movement preparation, upstream the corticospinal tract. However, at this point, a possible involvement of cerebello-thalamic-cortical pathways in motor execution deterioration cannot be ruled-out. Further studies are indeed required to ascertain the possible presence of structural abnormalities in the dorsolateral prefrontal–premotor networks and orbitofrontal– cerebellar loops of MS patients with fatigue. Conflict of interest None. Acknowledgements This study was supported by FISM (Fondazione Italiana Sclerosi Multipla) Grant 2008 awarded to A. Quartarone. References [1] Amato MP, Portaccio E. Management options in multiple sclerosis-associated fatigue. Expert Opin Pharmacother 2012;13:207–16. [2] Bakshi R. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler 2003;9:219–927. [3] Balbi P, Perretti A, Sannino M, Marcantonio L, Santoro L. Post-exercise facilitation of motor evoked potentials following transcranial magnetic stimulation: a study in normal subjects. Muscle Nerve 2002;25:448–52. [4] Beaubaton D, Trouche E. Participation of the cerebellar dentate nucleus in the control of a goal-directed movement in monkeys. Effects of reversible or permanent dentate lesion on the duration and accuracy of a pointing response. Exp Brain Res 1982;46:127–38. [5] Bonzano L, Tacchino A, Saitta L, Roccatagliata L, Avanzino L, Mancardi GL, et al. Basal ganglia are active during motor performance recovery after a demanding motor task. Neuroimage 2013;65:257–66. [6] Bove M, Tacchino A, Novellino A, Trompetto C, Abbruzzese G, Ghilardi MF. The effects of rate and sequence complexity on repetitive finger movements. Brain Res 2007;1153:84–91. [7] Brasil-Neto JP, Cohen LG, Hallett M. Central fatigue as revealed by postexercise decrement of motor evoked potentials. Muscle Nerve 1994;17:713–9. [8] Brasil-Neto JP, Pascual-Leone A, Valls-Solé J, Cammarota A, Cohen LG, Hallett M. Post-exercise depression of motor evoked potentials: a measure of central nervous system fatigue. Exp Brain Res 1993;93:181–4. [9] Calabrese M, Rinaldi F, Grossi P, Mattisi I, Bernardi V, Favaretto A, et al. Basal ganglia and frontal–parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Mult Scler 2010;16:1220–8. [10] Chaudhuri A, Behan PO. Fatigue and basal ganglia. J Neurol Sci 2000;179:34–42. [11] Chaudhuri A, Behan PO. Fatigue in neurological disorders. Lancet 2004;363:978–88. [12] Chen R, Tam A, Bütefisch C, Corwell B, Ziemann U, Rothwell JC, et al. Intracortical inhibition and facilitation in different representations of the human motor cortex. J Neurophysiol 1998;80:2870–81. [13] Crupi D, Cruciata G, Moisello C, Green PA, Naro A, Ricciardi L, et al. Protracted exercise without overt neuromuscular fatigue influences cortical excitability. J Mot Behav 2013;45:127–38. [14] DeLuca J, Genova HM, Hillary FG, Wylie G. Neural correlates of cognitive fatigue in multiple sclerosis using functional MRI. J Neurol Sci 2008;270:28–39. [15] Dubois B, Litvan I. The FAB: A frontal assessment battery at bedside. Neurology 2000; 55:1621–6. [16] Kos D, Kerckhofs E, Nagels G, D'hooghe MB, Ilsbroukx S. Origin of fatigue in multiple sclerosis: review of the literature. Neurorehabil Neural Repair 2008;22:91–100. [17] Krupp LB, La Rocca NG, Muir-Nash J, Steinberg AD. The Fatigue Severity Scale. Arch Neurol 1989;46:1121–3. [18] Ferrucci R, Vergari M, Cogiamanian F, Bocci T, Ciocca M, Tomasini E, et al. Transcranial direct current stimulation (tDCS) for fatigue in multiple sclerosis. Neurorehabilitation 2014;34:121–7. [19] Liepert J, Mingers D, Heesen C, et al. Motor cortex excitability and fatigue in multiple sclerosis: a transcranial magnetic stimulation study. Mult Scler 2005;11:316–21. [20] Morgante F, Dattola V, Crupi D, Russo M, Rizzo V, Ghilardi MF, et al. Is central fatigue in multiple sclerosis a disorder of movement preparation? J Neurol 2011;258: 263–72. [21] Multiple Sclerosis Council for Clinical Practice Guidelines. Fatigue and multiple sclerosis. Washington DC: Paralyzed Veterans of America; 1998. [22] Mushiake H, Strick PL. Preferential activity of dentate neurons during limb movements guided by vision. J Neurophysiol 1993;70:2660–4. [23] Pardini M, Bonzano L, Roccatagliata L, Mancardi GL, Bove M. The fatigue–motor performance paradox in multiple sclerosis. Sci Rep 2013;3:2001. [24] Perretti A, Balbi P, Orefice G, Trojano L, Marcantonio L, Brescia-Morra V, et al. Postexercise facilitation and depression of motor evoked potentials to transcranial magnetic stimulation: a study in multiple sclerosis. Clin Neurophysiol 2004;115: 2128–33.
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