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. 2009 Mar 16;587(Pt 9):1977–1987. doi: 10.1113/jphysiol.2009.171066

Mapping of direction and muscle representation in the human primary motor cortex controlling thumb movements

W J Z’Graggen 1, A B Conforto 1,4, R Wiest 2, L Remonda 2,3, C W Hess 1, A Kaelin-Lang 1
PMCID: PMC2689337  PMID: 19289547

Abstract

Larger body parts are somatotopically represented in the primary motor cortex (M1), while smaller body parts, such as the fingers, have partially overlapping representations. The principles that govern the overlapping organization of M1 remain unclear. We used transcranial magnetic stimulation (TMS) to examine the cortical encoding of thumb movements in M1 of healthy humans. We performed M1 mapping of the probability of inducing a thumb movement in a particular direction and used low intensity TMS to disturb a voluntary thumb movement in the same direction during a reaction time task. With both techniques we found spatially segregated representations of the direction of TMS-induced thumb movements, thumb flexion and extension being best separated. Furthermore, the cortical regions corresponding to activation of a thumb muscle differ, depending on whether the muscle functions as agonist or as antagonist for flexion or extension. In addition, we found in the reaction time experiment that the direction of a movement is processed in M1 before the muscles participating in it are activated. It thus appears that one of the organizing principles for the human corticospinal motor system is based on a spatially segregated representation of movement directions and that the representation of individual somatic structures, such as the hand muscles, overlap.

An important organizing principle of the primary motor cortex (M1) is somatotopy: the motor control of specific body parts is represented in specific cortical regions. This concept was first suggested by Hughlings Jackson in 1863 (Jackson, 1931). Later, Penfield & Boldrey (1937) performed focal electrical stimulation of the exposed cortex and described the classic motor homunculus. Yet, the representation of different body parts by M1 is not quite as somatotopic as the homunculus seems to suggest. Although larger body parts do have spatial and mostly non-overlapping representations, the representations of smaller body parts, like the fingers, may overlap with each other and are relatively diffusely distributed within the major regions of M1 (Schieber, 2001). The gross somatotopic organization of the human M1 has been confirmed by co-registration of the results of intraoperative cortical mapping with those of transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) (Singh et al. 1997; Beisteiner et al. 2001; Hlustik et al. 2001; Indovina & Sanes, 2001; Dechent & Frahm, 2003).

Furthermore, it is now generally accepted that the organization of the primate M1 is not exclusively somatotopic, but that functional aspects of movement are also represented (Humphrey, 1986) such as direction (Georgopoulos et al. 1986; Caminiti et al. 1990), velocity (Reina et al. 2001), joint angles (Scott & Kalaska, 1995) or muscle tension (Evarts, 1968; Cheney et al. 1985; Donoghue et al. 1992; Kakei et al. 1999). Kakei and co-workers (Kakei et al. 1999) showed a mixed representation in M1: many M1 neurons display activity that is correlated with individual muscles, but a larger population of neurons is better correlated with movement direction than individual muscle activity.

Nonetheless, it remains unclear how the coding of the parameters of a particular movement is performed in M1 if anatomical structures such as muscles, and kinematics properties such as movement direction, are both represented in the same cortical area.

Our major hypothesis is that the human M1 possesses both a functional and an anatomical somatotopic organization for the processing of hand/finger movements with kinematic parameters such as movement direction represented in the cortex in a spatially segregated fashion. This, in turn, implies that the cortical representations of individual anatomical structures, such as muscles, will be variable. In other words, the cortical representation of a muscle will be at a different location depending on the task.

In this study we tested this hypothesis with the aid of TMS in healthy, awake human subjects. The probability of inducing a movement in a particular direction by TMS is a stochastic process that has been extensively used as a measure of training-induced changes in M1 (Classen et al. 1998; Butefisch et al. 2000; Sawaki et al. 2003; Kaelin-Lang et al. 2005; Sawaki et al. 2006). Here we correlate the direction of a TMS-evoked movement with the muscle(s) participating in the same movement. An overlapping and dynamic encoding in M1 would implicate also an additional temporal processing with the kinematic aspects of a movement being selected before the required muscles are activated. To test for an additional temporal processing in M1, we studied the effect of TMS applied during a reaction time experiment on onset of movement and recruitment of muscles based on the knowledge that TMS applied to M1 can delay movement onset (Pascual-Leone et al. 1992a; Classen et al. 1998).

Methods

Subjects and ethical approval

Fifteen healthy subjects (11 female, 4 male, aged 23–39 years, mean 28.3 years) participated in this study. Experiments were undertaken with the understanding and written consent of each subject. All procedures were approved by the local ethics committee (Kantonale Ethikkommission Bern) and conformed to the Declaration of Helsinki. All subjects were right-handed according to the Edinburgh scale (Oldfield, 1971).

Stimulation and recording

Subjects were comfortably seated in a chair. The right forearm was immobilized in flexion in an armrest, with the four long fingers supported. The thumb was held in a vertical position with the metacarpophalangeal joints entirely unconstrained. Thumb movements were recorded with a three-dimensional accelerometer mounted on the immobilized distal joint of the thumb (Fig. 2A) (Kistler Instrument, Amherst, NY, USA) (Classen et al. 1998). Acceleration signals were recorded in four individually adjusted movement sectors (flexion, extension, abduction, adduction, see Figs 1 and 2A) and digitalized at 5 kHz. To determine the individual movement sectors subjects were asked to perform 15 consecutive brisk movements in flexion, extension, abduction and adduction at the end of each mapping session (see below). Mean direction of the first acceleration vector was calculated for all four voluntary movement directions separately. Movement sectors were defined as the angular sectors in each direction with boundaries calculated by bisecting angles between neighbouring mean movement directions (Fig. 2A).

Figure 2. Cortical maps.

Figure 2

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A, experimental setup showing the recording of the movements of the thumb with a three-dimensional accelerometer (A) mounted on the immobilized distal joint (*). The thumb was held in a vertical position with the metacarpophalangeal joint entirely unconstrained. Amplitude and direction of the first acceleration vector were recorded in four individually adjusted movement sectors separately (flexion, extension, abduction, adduction). B, 2-D map of the average positions of the centres of gravity (n= 10) of the probability of generating a movement in a specific direction (flexion, extension, abduction, adduction). Error bars indicate s.e.m.C–F, topographical 2-D maps for the mean vector length (normalized to the maximal vector amplitude, n= 10) for movements in flexion (C), extension (D), abduction (E) and adduction (F). Largest movements were observed in areas depicted red. No movements were recorded in areas coloured dark green. The coordinates (0/0) indicate ‘the hot spot’ (see Methods).

Figure 1. TMS-induced movement directions in relation to the site of stimulation in a single subject.

Figure 1

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The pictogram in the upper left corner shows the individual sectoring of movement directions. Movement directions are displayed using a standard direction vector. The coordinates 0/0 indicate the starting point of the mapping corresponding to the hot spot. The direction vectors in flexion and abduction were more frequently observed in the medial part of the maps whereas direction vectors in extension were more frequently observed in the lateral part. According to the anatomical location of the central sulcus and of the precentral gyrus, the map was located on a 45 deg oblique position (dashed line).

Surface electromyographic activity was recorded from the right flexor pollicis brevis (FPB) and extensor pollicis brevis (EPB) muscles with silver–silver chloride electrodes in a tendon belly arrangement. The EMG signal was pre-amplified and band-pass filtered (1 Hz to 1 kHz) with a Neurodata Amplifier System connected to an IPS230 Isolated Power System (Grass-Telefactor, Braintree, MA, USA). The output was fed into a computerized data acquisition system built with the LabView graphical programming language (sampling rate 5 kHz) (Kaelin-Lang & Cohen, 2000).

Single, monophasic TMS pulses were delivered to the left motor cortex through a custom-made, figure-of-8-shaped coil (diameter 5 cm, maximal field strength 2.89 T) connected to a Magstim 200 (the Magstim Company Limited, Whitland, UK). The coil was held tangentially to the scalp with the intersection of the two wings at a 45 deg angle to the midline, in order to induce electrical current in the cortex in the posterior–anterior direction and thereby trans-synaptically activate the corticospinal system (Brasil-Neto et al. 1992; Kaneko et al. 1996).

Mapping experiment

Seven female and three male subjects (aged 23–39 years) participated in this experiment. Four of them also participated in the reaction time experiment (see below). The subjects were instructed to keep their arms relaxed in the same position as described above. Relaxation was controlled using the ‘conditional triggering’ feature of the program (Kaelin-Lang & Cohen, 2000). TMS stimuli were delivered with a random inter-stimulus interval of 5–7 s. The experiment started with identification of the starting point of the map (Conforto et al. 2004), which was arbitrarily chosen and corresponded to the ‘hot spot’ (i.e. the optimal scalp position) for activation of the contralateral FPB. The resting motor threshold (RMT) was defined as the lowest TMS intensity eliciting a motor-evoked potential (MEP) of at least 50 μV in 5 out of 10 consecutive trials at rest (Rossini et al. 1994). A grid of positions 1 cm apart with reference to the ‘hot spot’ was marked on a swimming cap firmly fixed to the scalp. The intensity of TMS was set at 130% RMT and 10 stimuli were delivered at each location. Stimulation was begun at the ‘hot spot’ and was continued in all directions until no further MEPs could be elicited by TMS. The direction of TMS-induced movement was defined as the maximal acceleration vector within the first 20 ms after the onset of movement. The amplitude of the movement was defined as the length of this acceleration vector (in N m−2).

We constructed two types of maps: first a 2-dimensional map of the movement amplitude for each movement direction separately (Fig. 2C–F). Second, a 2-dimensional map of the probability of inducing a movement in either flexion, extension, abduction or adduction. For both maps, the coordinates of the maps were rotated by 45 deg (see Fig. 1) in order to have the X-axis roughly parallel to the central sulcus and the Y-axis perpendicular. We then calculated for further statistical analysis the location of the centres of gravity (COG) (Wassermann et al. 1992) for all maps.

Furthermore, we reconstructed the COGs of the main agonist and antagonist hand muscles for movements in flexion and extension (FPB and EPB) depending on the direction of movement.

In order to check the accuracy of our TMS mapping technique and to anatomically localize the stimulation points on the underlying cortex, an MRI scan of the head was performed in six subjects on a 1.5 T Siemens Magnetom Sonata Scanner with regular head coils. The COGs from the TMS mapping experiments were localized on the surface of the skull using the coordinates of the mapping experiment and projected onto the brain surface for each subject separately. In four of these subjects, additional functional MRI (fMRI) was performed during a finger-tapping task (alternating flexion and extension of the right thumb) in order to confirm that the region stimulated by TMS is at the same location as the region activated by voluntary movements (for details see online Supplemental material).

Reaction time task

Temporal processing in M1 for direction of movement and muscle representation was studied by measuring the effect of single subthreshold TMS pulses delivered to the ‘hot spot’ defined as the optimal scalp position for activation of the contralateral FPB in awake subjects who executed voluntary hand movements while performing a reaction time (RT) task. TMS was applied at different time points in a random order during the preparation phase of two distinct voluntary movements of the right thumb: flexion and extension (Fig. 4). We used these two movement directions because they were best segregated in the mapping experiment.

Figure 4. Experimental setup for reaction time task.

Figure 4

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A, the diagram indicates the vertical starting position of the thumb. Thumb movements were recorded with a 3-dimensional accelerometer (A) mounted on the immobilized distal joint of the thumb (*), similar to the mapping experiment. In addition, surface electromyographic activity was recorded from the flexor pollicis brevis and extensor pollicis brevis muscles with silver–silver chloride electrodes in a tendon belly arrangement. B, schematic representation of the warning-imperative signal protocol. An auditory warning signal was followed, after a randomly chosen delay of 1, 1.5, 2 or 2.5 s, by a visual ‘go’ signal. Subjects had to respond to the ‘go’ signal with either brisk flexion or brisk extension of the right thumb. TMS was delivered at different randomly inter-mixed time points. One-fifth of all trials were control trials without TMS, another fifth were ‘catch’ trials (TMS was delivered without a preceding go-signal). In the remaining trials TMS was applied either at the same time as the ‘go’ signal or 50 or 80 ms (one-fifth of trials each) earlier than the median reaction time as measured during an initial practice experiment.

Ten subjects (9 female, 1 male, aged 23–39 years) participated in this experiment. An auditory warning signal (Sawaki et al. 1999) (1000 Hz tone of 200 ms duration) was followed, after a randomly chosen delay of 1, 1.5, 2 or 2.5 s, by a visual ‘go’ signal (100 ms duration, light-emitting diode (LED) at eye level 75–85 cm in front of the subject). Each experimental session consisted of 288 trials, presented in two practice blocks of 24 trials each and six test blocks of 40 trials each, with 3 min breaks between blocks to minimize fatigue. In each block, the subjects were instructed to respond to the ‘go’ signal with either brisk flexion or brisk extension of the right thumb (depending on the block). They were told to perform the task as rapidly and precisely as possible.

The intensity of the TMS for the RT experiment was set at 95% active motor threshold (AMT). The AMT was determined during 5–10% background facilitation of the FPB (Kujirai et al. 1993; Chen et al. 1998; Ziemann, 1999; Sohn et al. 2003) and was defined as the minimum intensity of stimulation necessary to induce MEPs of at least 100 μV, or a silent period, in 5 of 10 trials (Sohn et al. 2003). The site of TMS remained unchanged throughout the experiment.

In the initial practice blocks (one each for flexion and extension), 8 of the 24 trials were control trials without TMS, in 8 trials TMS was applied at the same time as the ‘go’ signal, and the remaining 8 trials were ‘catch’ trials, in which TMS was delivered without a preceding ‘go’ signal. These trials were presented in random order with a constant inter-trial interval of 8 s. ‘Catch’ trials ensured that subjects responded only to the ‘go’ signal. During the practice blocks the median RTs in the control trials (time between ‘go’ signal and onset of EMG activity) were assessed for flexion and extension separately and were used to define the TMS times to be used during the test blocks.

Of the 40 trials in each test block, 8 were control trials without TMS, 8 were ‘catch’ trials, and 24 were trials with TMS, applied either at the same time as the ‘go’ signal or 50 or 80 ms earlier than the median reaction time of the control trials (see above, 8 trials each). Just after the RT experiment, 30 TMS stimuli at higher intensity were delivered with a random inter-stimulus interval of 5–7 s at the same position on the scalp to determine the preferred direction of TMS-induced movements. The intensity of TMS was set at 130% RMT. The ‘conditional triggering’ feature of the program was used to deliver TMS stimuli only when the FPB muscle was relaxed (Kaelin-Lang & Cohen, 2000). Subjects also received acoustic feedback for FPB relaxation. In addition, 5–10 brisk voluntary thumb movements in abduction, adduction, flexion and extension were recorded to determine the kinematic aspects of unconstrained voluntary movement in each direction (see above).

In all experiments, RT was measured automatically from the onset of the ‘go’ signal to the onset of voluntary EMG activity (for the FPB and the EPB) and to the onset of movement (acceleration signal). The time of onset of voluntary EMG activity or movement was defined according to Hodges & Bui (1996) as the moment when the mean rectified EMG amplitude or acceleration signal exceeded the baseline activity by 3 s.d. In a few trials (< 5%) TMS evoked an MEP with peak-to-peak amplitude greater than 500 μV. These trials were excluded. For further analysis, the mean RT for movement (flexion or extension) and for the onset of EMG activity (in FPB or EPB) was calculated for trials under the same experimental conditions in each subject separately. In addition, the effective time between the TMS pulse and the onset of movement and EMG activity was measured for each of these experimental conditions off-line. In three subjects, the off-line analysis revealed an inconstant performance and the effective time between the TMS pulse and the onset of movement in flexion was markedly different from the effective time between the TMS pulse and the onset of movement in extension (> 20 ms), precluding a meaningful comparison between flexion and extension tasks. These three subjects were used for the mapping experiment but excluded from further analysis of the RT experiment (with the exception of the control condition, where TMS occurred together with the LED signal). Statistical analysis was performed for the following time windows. ‘LED’: TMS applied at the same time as the visual ‘go’ signal (n= 10); ‘EARLY’: TMS applied 75–145 ms before the onset of movement (n= 7); ‘LATE’: TMS applied 25–75 ms before the onset of movement (n= 7).

To determine the preferred direction of TMS-induced movements, the angle of the acceleration vectors was measured in 30 TMS trials at an intensity of 130% RMT. The direction of movement was defined as that of the maximal acceleration vector in the first 20 ms after the onset of the TMS-induced movement, as for the mapping experiment (see above). The measured direction was related to voluntary thumb movements in abduction, adduction, flexion and extension, from which a sector for each direction of movement was calculated (see above).

Statistical analysis

Data are presented as mean ± standard error of the mean (s.e.m.). ANOVA for repeated measures was used. For all mapping experiments, X and Y coordinates were separately analysed. Post hoc analysis was performed with t tests. Statistical analyses were performed with SPSS 12.0.1 (SPSS Inc., USA). Mauchly's test of sphericity was always performed to test the accuracy of the ANOVA procedure. The Greenhouse–Geisser correction of the P value was used if required. A P value < 0.05 was considered significant.

Results

Mapping experiment

Map of movement directions

Figure 1 shows TMS-induced movement directions in relation to the site of stimulation in a single representative subject. Stimulation of more medially (closer to the vertex) located sites resulted in a higher probability of thumb flexion, whereas extension movements were elicited more frequently at laterally located positions. Adduction and abduction movements were predominantly evoked centrally. All subjects taken together, the direction of the mean acceleration vector calculated for each stimulated site separately out of 10 stimulations was preferentially located in the angular sectors corresponding to thumb flexion (38.7 ± 5.4%, averaged across all subjects). Other movement directions were less frequently induced (abduction, 29.9 ± 3.9%; adduction, 18.3 ± 5.1%; extension, 13.7 ± 4.1%).

To further test the hypothesis of the spatial representation of the direction of movement, we calculated the probability of inducing a thumb movement in one of the four main movement directions (flexion, extension, abduction, adduction) with suprathreshold TMS at a particular scalp position. Figure 2B shows the COGs for the probability of movements in all four directions (n= 10). Coordinates of the COG on the medio-lateral X-axis parallel to the central sulcus were significantly different according to the direction (ANOVA for repeated measures, F= 5.1, P < 0.01). Post hoc analysis revealed that the movement directions flexion and extension were best segregated: the COG for flexion was located medial and slightly anterior to the COG for extension (Fig. 3A). This typical distribution of the COGs could be observed in all but one subject. Statistical analysis of the position of the COGs along the Y-axis (anterior–posterior to the central sulcus) did not reveal any significant differences.

Figure 3.

Figure 3

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A, 2-D map of the average positions for the centres of gravity (n= 10) for the movement directions flexion (▴) and extension (♦). B, average centres of gravity (n= 10) for MEPs recorded from flexor pollicis brevis (open symbols) and extensor pollicis brevis muscles (filled symbols) for movements in flexion (triangles) and extension (rectangles) separately. See text for discussion. Error bars indicate s.e.m.

Map of acceleration vector amplitude

The 2-dimensional maps of the mean TMS-induced vector amplitudes (length, n= 10) for each movement direction separately are shown in Fig. 2C–F. Although there was an overlap of the maps, a tendency for a spatial segregation of the areas of the largest TMS-induced vector length can be seen, e.g. the strongest flexion movements were elicited in an area located medial and slightly anterior to the one for extension. Statistical analysis of the COGs, however, did not reveal significant differences, either for the X- or for the Y-axis.

MEP maps

In addition, we analysed the cortical representation of the FPB and EPB muscles according to the movement directions flexion and extension to test the hypothesis that the cortical representation, e.g. of the FPB, depends on the induced movement direction.

Figure 3B shows the averaged COGs across all subjects for MEPs recorded from the FPB and EPB for each of the two movement directions separately (flexion and extension). For both movement directions, the COG for MEPs recorded from the FPB was medial to that for the EPB. On the other hand, for each of the two muscles (FPB or EPB), the mean COG for flexion was significantly different from that for extension. ANOVA of the coordinates of the centre of gravity for each muscle and each movement direction revealed a significant interaction between the factors ‘movement direction’ and ‘muscle’ (F= 9.13, P= 0.01).

Reaction time task

Analysis across all subjects revealed that TMS induced a significant change of the mean RT for the onset of movement in either direction, depending on the time at which TMS was delivered. An analysis of variance (ANOVA) revealed that the main factor determining the degree of change in RT was the time of stimulation (F= 17.11, P < 0.001), while there was no significant interaction between the factors ‘time of stimulation’ and ‘movement direction’ (ANOVA, F= 0.64, P= 0.59). These findings indicate a general effect of TMS on RT that was independent of the direction of thumb movement. There was a significant shortening of RT when the signal was simultaneously applied with the ‘go’ signal or in the ‘EARLY’ time window (TMS delivered 75–145 ms before the expected onset of movement) and a slight non-significant delay when TMS was applied in the ‘LATE’ period (TMS delivered 25–75 ms before the expected movement onset) (see Fig. 4B for RT protocol).

TMS-induced changes of RT for movement onset (i.e. the differences in RT between trials with and without TMS) for flexion were negatively correlated with those for extension when TMS was applied during the EARLY time window (simple regression analysis: R2= 0.56, P= 0.05), but not when TMS was applied during the LATE time window or simultaneously with the LED. In other words, stimulating M1 at a particular location 75–145 ms before the onset of a simple finger movement interfered preferentially with either flexion or extension in each subject: the greater the disturbance was for movements in one direction, the less it was for movements in the other direction. This finding suggests that TMS applied 75–145 ms before movement onset specifically interacts with the encoding of a certain movement direction.

Temporal processing

We further study how and when the muscles required for a particular movement are activated. There was no significant correlation between the TMS-induced changes in RT in the FPB and EPB when TMS was delivered at the same time as the ‘go’ signal or during the EARLY time window. However, there was a significant positive correlation, when TMS was delivered during the LATE time window (R2= 0.49, P≤ 0.01). This result suggests that TMS applied less than 75 ms before the onset of movement interferes specifically with the activation of the muscles required for a particular movement. In contrast, TMS applied in the EARLY time window, or at the same time as the ‘go’ signal, does not show this interaction.

Discussion

In this study, we investigated cortical representation of movement directions and cortical representation of single muscles in human M1 by using TMS. Our results revealed that the direction of TMS-evoked thumb movements is segregated in the human M1 and that the representation of a thumb muscle differs, depending on whether the muscle functions as agonist or as antagonist for flexion or extension.

We used four objectively defined thumb movement direction sectors with arbitrarily defined boundaries based on voluntary movements. As expected with these individually defined sectors, the maps were overlapping and differences in location were small. Nevertheless, for the map of the probability of inducing a movement in a particular direction we found a significant difference in the cortical location of the COGs. In contrast, a more classical method investigating the mapping of the acceleration vector itself did not reveal significant differences. The difference between both techniques is not surprising, since movement direction but not force is known to be specifically encoded in primate M1 (Kakei et al. 1999). Furthermore, the amplitude of the acceleration vector of a TMS-induced movement is more likely to be influenced by confounding factors such as spinal excitability changes than the direction of the same movement. Thus, we suggest that our TMS mapping technique, that represents the probability of inducing a thumb movement in a particular direction with suprathreshold TMS at a particular scalp position, was more robust in identifying the cortical location of a particular thumb movement direction in spite of the low spatial resolution of TMS. This mapping technique is therefore better adapted to the stochastic and variable nature of TMS-induced movements.

The same concept has been extensively used to investigate training-induced changes of movement direction in humans with the use of an objectively defined movement direction sector. As in our study, this movement direction sector, ‘the training target zone’, has first to be calculated and changes in the probability of inducing movements in this sector are used as a primary endpoint. With this technique, it has been shown that active but not passive training increases the probability of inducing a TMS-induced movement in the direction of the trained movement for about 30 min (Classen et al. 1998; Butefisch et al. 2000; Sawaki et al. 2003; Kaelin-Lang et al. 2005; Sawaki et al. 2006).

The differences were particularly clear for thumb extension and flexion: in all but one subject the COG for extension was located more laterally than the COG for flexion. Furthermore, the COG for a particular direction was always located in the cortical region showing specific activation during voluntary movements in an fMRI task (see Supplemental material). Hence, the cortical position at which TMS has the highest probability of inducing flexion is spatially distinct from that at which TMS has the highest probability of inducing extension, independently from the amplitude of the movement.

In contrast, the cortical region corresponding to activation of the FPB or EPB was at different locations depending on the direction of the evoked movement. For each of the two muscles separately the COG for flexion was significantly different from that for extension.

The COG is one of the most stable and precise parameters of TMS maps, and allows the detection of small changes between muscle representations in spite of the low spatial resolution of TMS maps (Classen et al. 1998). Furthermore, because we recorded MEPs and movements simultaneously, the results of a distributed representation of FPB and EPB muscle according to the movement direction cannot be explained by the lack of spatial resolution of TMS maps or by an imprecise coil position during the stimulation; neither can it be explained by anatomical factors such as the geometry of the motor cortex or difference in the distance between coil and cortical surface. However, a significant difference between the location of the COG between two different maps does not imply a true small-scale difference in the location of a completely segregated neuronal structure but it rather implies that the spatial extent of two partially overlapping cortical networks are not identical.

There is both a divergence and a convergence of cortical neurons projecting to spinal motoneurons controlling hand muscles (e.g. Cheney et al. 1985). On the other hand, TMS-induced movements are a stochastic process (Classen et al. 1998), and the direction of a single TMS-induced movement is also variable and most likely to be related to the corticomotoneuronal connection with the lowest threshold just at the time of stimulation. Nevertheless, our data suggest that these corticomotoneuronal connections are not uniformly distributed in the hand area but are spatially segregated according to the movement direction.

We therefore suggest that one of the parameters represented in the human M1 is the direction of movement, and that the human M1 has a spatial segregation for this parameter. In contrast, the representation of anatomical structures, such as muscles, depends on the selected movement direction. This hypothesis may explain why in the human M1 both a gross somatotopical organization and an overlapping non-somatotopical organization co-exist. These findings are consistent with those of earlier studies in non-human primates implying that the primate M1 may influence functional aspects of movements, such as direction or velocity (Georgopoulos et al. 1986; Caminiti et al. 1990; Reina et al. 2001). In one such study, for example, a monkey was trained to perform a wrist step-tracking task, and single-neuron recordings in M1 revealed two distinct groups of neurons: a smaller number whose firing was related to the activity of individual muscles, and a larger number whose firing was related to the direction of movement (Kakei et al. 1999). Our results suggest in addition that in the human M1, a functional map of the kinematics of a hand movement is associated with an overlapping, distributed representation of the participating anatomical structures (muscles).

In addition, the organization of M1 possesses a temporal segregation. This sequential organization of M1 is revealed by the results of our RT experiment, which documents that low-intensity TMS applied 75–145 ms before the onset of a simple finger movement interferes preferentially with a particular movement direction. If TMS is applied less than 75 ms before the onset of movement, the activation of the muscles required for a particular movement is disturbed.

As in previous reports (Pascual-Leone et al. 1992b; Ziemann et al. 1997; Sawaki et al. 1999; Leocani et al. 2000), we found that subthreshold TMS delivered over the contralateral motor area for the hand may shorten RT if applied at the same time as the ‘go’ signal or more than 75 ms before the onset of movement. Maximal RT shortening was found when TMS was simultaneous with the ‘go’ signal. These findings imply that part of the effect of TMS is not due to a direct modulation of the motor system, and that this is most evident when TMS is delivered together with the ‘go’ signal. This non-specific effect might be due to (1) intersensory facilitation between acoustic and visual inputs (Terao et al. 1997) and (2) additional facilitation of sensory processing in the RT protocol triggered by the acoustic stimulus of TMS (Pascual-Leone et al. 1992b; Valls-Sole et al. 1995). In addition, however, our results clearly reveal two specific effects of subthreshold TMS delivered over the contralateral motor area for the hand: (1) a slight delay of RT, if subthreshold TMS is delivered 25–75 ms before movement onset; and (2) a direction-specific perturbation, if it is delivered yet earlier. A similar effect on RT is known to occur with TMS intensities above RMT (Day et al. 1989; Rothwell et al. 1989; Pascual-Leone et al. 1992b; Leocani et al. 2000).

The TMS-induced delay in RT has been attributed to an inhibitory neuronal process in the final motor output stage since it resembles the silent period observed in tonic voluntary EMG after motor cortex stimulation (Rothwell et al. 1989; Pascual-Leone et al. 1992b; Ziemann et al. 1997). Furthermore, it is generally accepted that low-intensity TMS pulses below the AMT mainly activate intracortical circuitry rather than the descending corticomotoneuronal tract. Thus, it seems that the changes in RT induced by subthreshold TMS in our study were probably due to stimulation of neural elements in M1, which are activated late in the process of movement release from the final motor output stage.

Hence, the functional aspect of a movement appears to be segregated within the motor cortex, not only spatially, but also temporally: the direction of a movement is processed before the muscles participating in it are activated. A study of the dynamics of precise spike synchronization and rate modulation in a population of neurons in the simian M1, revealed that synchronous neuronal activity in the motor cortex is involved in early preparatory and motor cognitive processes (Riehle et al. 1997). In contrast, the firing rate may control movement initiation and execution (Grammont & Riehle, 2003). These findings suggest a possible physiological correlate, on the neuronal level, for the temporal segregation found in our study. One interpretation of our results is that the human M1 is involved in multiple (at least two) stages of movement processing, rather than merely the final computation that determines the degree to which all of the participating muscles will be activated as previously suggested in non-human primates (Kakei et al. 1999). In addition to these muscle connections there seems to be a stable spatial segregation for the direction of movement, which is probably superimposed on a coarse somatotopic scheme.

Acknowledgments

This work was supported by a grant from the Swiss National Science Foundation (3100-066929.01/1) to A.K.-L. A.B.C. was supported by an IBRO Fellowship for Young Investigators from the Swiss National Science Foundation. The authors are grateful to Pietro Ballinari for statistical assistance, to Ethan Taub for editing and to Rudolf Burkhalter and his team from the Electronics Department of the Inselspital, Berne, Switzerland, for their technical support.

Glossary

Abbreviations

AMT

active motor threshold

COG

center of gravity

EPB

extensor pollicis brevis muscle

fMRI

functional magnetic resonance imaging

FPB

flexor pollicis brevis muscle

LED

light-emitting diode

M1

primary motor cortex

MEP

motor evoked potential

MRI

magnetic resonance imaging

RMT

resting motor threshold

RT

reaction time

SD

standard deviation

TMS

transcranial magnetic stimulation

Supplemental material

Online supplemental material for this paper can be accessed at:

tjp0587-1977-SD1.pdf (728.5KB, pdf)

http://jp.physoc.org/cgi/content/full/jphysiol.2009.171066/DC1

References

  1. Beisteiner R, Windischberger C, Lanzenberger R, Edward V, Cunnington R, Erdler M, Gartus A, Streibl B, Moser E, Deecke L. Finger somatotopy in human motor cortex. Neuroimage. 2001;13:1016–1026. doi: 10.1006/nimg.2000.0737. [DOI] [PubMed] [Google Scholar]
  2. Brasil-Neto JP, Cohen LG, Panizza M, Nilsson J, Roth BJ, Hallett M. Optimal focal transcranial magnetic activation of the human motor cortex: effects of coil orientation, shape of the induced current pulse, and stimulus intensity. J Clin Neurophysiol. 1992;9:132–136. [PubMed] [Google Scholar]
  3. Butefisch CM, Davis BC, Wise SP, Sawaki L, Kopylev L, Classen J, Cohen LG. Mechanisms of use-dependent plasticity in the human motor cortex. Proc Natl Acad Sci U S A. 2000;97:3661–3665. doi: 10.1073/pnas.050350297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Caminiti R, Johnson PB, Urbano A. Making arm movements within different parts of space: dynamic aspects in the primate motor cortex. J Neurosci. 1990;10:2039–2058. doi: 10.1523/JNEUROSCI.10-07-02039.1990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chen R, Tam A, Butefisch C, Corwell B, Ziemann U, Rothwell JC, Cohen LG. Intracortical inhibition and facilitation in different representations of the human motor cortex. J Neurophysiol. 1998;80:2870–2881. doi: 10.1152/jn.1998.80.6.2870. [DOI] [PubMed] [Google Scholar]
  6. Cheney PD, Fetz EE, Palmer SS. Patterns of facilitation and suppression of antagonist forelimb muscles from motor cortex sites in the awake monkey. J Neurophysiol. 1985;53:805–820. doi: 10.1152/jn.1985.53.3.805. [DOI] [PubMed] [Google Scholar]
  7. Classen J, Liepert J, Wise SP, Hallett M, Cohen LG. Rapid plasticity of human cortical movement representation induced by practice. J Neurophysiol. 1998;79:1117–1123. doi: 10.1152/jn.1998.79.2.1117. [DOI] [PubMed] [Google Scholar]
  8. Conforto AB, Z’Graggen WJ, Kohl AS, Rosler KM, Kaelin-Lang A. Impact of coil position and electrophysiological monitoring on determination of motor thresholds to transcranial magnetic stimulation. Clin Neurophysiol. 2004;115:812–819. doi: 10.1016/j.clinph.2003.11.010. [DOI] [PubMed] [Google Scholar]
  9. Day BL, Rothwell JC, Thompson PD, Maertens de Noordhout A, Nakashima K, Shannon K, Marsden CD. Delay in the execution of voluntary movement by electrical or magnetic brain stimulation in intact man. Evidence for the storage of motor programs in the brain. Brain. 1989;112:649–663. doi: 10.1093/brain/112.3.649. [DOI] [PubMed] [Google Scholar]
  10. Dechent P, Frahm J. Functional somatotopy of finger representations in human primary motor cortex. Hum Brain Mapp. 2003;18:272–283. doi: 10.1002/hbm.10084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Donoghue JP, Leibovic S, Sanes JN. Organization of the forelimb area in squirrel monkey motor cortex: representation of digit, wrist, and elbow muscles. Exp Brain Res. 1992;89:1–19. doi: 10.1007/BF00228996. [DOI] [PubMed] [Google Scholar]
  12. Evarts EV. Relation of pyramidal tract activity to force exerted during voluntary movement. J Neurophysiol. 1968;31:14–27. doi: 10.1152/jn.1968.31.1.14. [DOI] [PubMed] [Google Scholar]
  13. Georgopoulos AP, Schwartz AB, Kettner RE. Neuronal population coding of movement direction. Science. 1986;233:1416–1419. doi: 10.1126/science.3749885. [DOI] [PubMed] [Google Scholar]
  14. Grammont F, Riehle A. Spike synchronization and firing rate in a population of motor cortical neurons in relation to movement direction and reaction time. Biol Cybern. 2003;88:360–373. doi: 10.1007/s00422-002-0385-3. [DOI] [PubMed] [Google Scholar]
  15. Hlustik P, Solodkin A, Gullapalli RP, Noll DC, Small SL. Somatotopy in human primary motor and somatosensory hand representations revisited. Cereb Cortex. 2001;11:312–321. doi: 10.1093/cercor/11.4.312. [DOI] [PubMed] [Google Scholar]
  16. Hodges PW, Bui BH. A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. Electroencephalogr Clin Neurophysiol. 1996;101:511–519. doi: 10.1016/s0013-4694(96)95190-5. [DOI] [PubMed] [Google Scholar]
  17. Humphrey DR. Representation of movements and muscles within the primate precentral motor cortex: historical and current perspectives. Fed Proc. 1986;45:2687–2699. [PubMed] [Google Scholar]
  18. Indovina I, Sanes JN. On somatotopic representation centers for finger movements in human primary motor cortex and supplementary motor area. Neuroimage. 2001;13:1027–1034. doi: 10.1006/nimg.2001.0776. [DOI] [PubMed] [Google Scholar]
  19. Jackson JH. Selected Writings of John Hughlings Jackson. Vol. 1. London: Hodder and Stoughton; 1931. [Google Scholar]
  20. Kaelin-Lang A, Cohen LG. Enhancing the quality of studies using transcranial magnetic and electrical stimulation with a new computer-controlled system. J Neurosci Methods. 2000;102:81–89. doi: 10.1016/s0165-0270(00)00284-3. [DOI] [PubMed] [Google Scholar]
  21. Kaelin-Lang A, Sawaki L, Cohen LG. Role of voluntary drive in encoding an elementary motor memory. J Neurophysiol. 2005;93:1099–1103. doi: 10.1152/jn.00143.2004. [DOI] [PubMed] [Google Scholar]
  22. Kakei S, Hoffman DS, Strick PL. Muscle and movement representations in the primary motor cortex. Science. 1999;285:2136–2139. doi: 10.1126/science.285.5436.2136. [DOI] [PubMed] [Google Scholar]
  23. Kaneko K, Kawai S, Fuchigami Y, Morita H, Ofuji A. The effect of current direction induced by transcranial magnetic stimulation on the corticospinal excitability in human brain. Electroencephalogr Clin Neurophysiol. 1996;101:478–482. doi: 10.1016/s0013-4694(96)96021-x. [DOI] [PubMed] [Google Scholar]
  24. Kujirai T, Caramia MD, Rothwell JC, Day BL, Thompson PD, Ferbert A, Wroe S, Asselman P, Marsden CD. Corticocortical inhibition in human motor cortex. J Physiol. 1993;471:501–519. doi: 10.1113/jphysiol.1993.sp019912. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Leocani L, Cohen LG, Wassermann EM, Ikoma K, Hallett M. Human corticospinal excitability evaluated with transcranial magnetic stimulation during different reaction time paradigms. Brain. 2000;123:1161–1173. doi: 10.1093/brain/123.6.1161. [DOI] [PubMed] [Google Scholar]
  26. Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971;9:97–113. doi: 10.1016/0028-3932(71)90067-4. [DOI] [PubMed] [Google Scholar]
  27. Pascual-Leone A, Brasil-Neto JP, Valls-Sole J, Cohen LG, Hallett M. Simple reaction time to focal transcranial magnetic stimulation. Comparison with reaction time to acoustic, visual and somatosensory stimuli. Brain. 1992;115:109–122. doi: 10.1093/brain/115.1.109. [DOI] [PubMed] [Google Scholar]
  28. Pascual-Leone A, Valls-Sole J, Wassermann EM, Brasil-Neto J, Cohen LG, Hallett M. Effects of focal transcranial magnetic stimulation on simple reaction time to acoustic, visual and somatosensory stimuli. Brain. 1992;115:1045–1059. doi: 10.1093/brain/115.4.1045. [DOI] [PubMed] [Google Scholar]
  29. Penfield W, Boldrey E. Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain. 1937;60:389–443. [Google Scholar]
  30. Reina GA, Moran DW, Schwartz AB. On the relationship between joint angular velocity and motor cortical discharge during reaching. J Neurophysiol. 2001;85:2576–2589. doi: 10.1152/jn.2001.85.6.2576. [DOI] [PubMed] [Google Scholar]
  31. Riehle A, Grun S, Diesmann M, Aertsen A. Spike synchronization and rate modulation differentially involved in motor cortical function. Science. 1997;278:1950–1953. doi: 10.1126/science.278.5345.1950. [DOI] [PubMed] [Google Scholar]
  32. Rossini PM, Barker AT, Berardelli A, Caramia MD, Caruso G, Cracco RQ, Dimitrijevic MR, Hallett M, Katayama Y, Lucking CH, et al. Non-invasive electrical and magnetic stimulation of the brain, spinal cord and roots: basic principles and procedures for routine clinical application. Report of an IFCN committee. Electroencephalogr Clin Neurophysiol. 1994;91:79–92. doi: 10.1016/0013-4694(94)90029-9. [DOI] [PubMed] [Google Scholar]
  33. Rothwell JC, Day BL, Thompson PD, Marsden CD. Interruption of motor programmes by electrical or magnetic brain stimulation in man. Prog Brain Res. 1989;80:467–472. doi: 10.1016/s0079-6123(08)62244-x. discussion 465–466. [DOI] [PubMed] [Google Scholar]
  34. Sawaki L, Okita T, Fujiwara M, Mizuno K. Specific and non-specific effects of transcranial magnetic stimulation on simple and go/no-go reaction time. Exp Brain Res. 1999;127:402–408. doi: 10.1007/s002210050808. [DOI] [PubMed] [Google Scholar]
  35. Sawaki L, Wu CW, Kaelin-Lang A, Cohen LG. Effects of somatosensory stimulation on use-dependent plasticity in chronic stroke. Stroke. 2006;37:246–247. doi: 10.1161/01.STR.0000195130.16843.ac. [DOI] [PubMed] [Google Scholar]
  36. Sawaki L, Yaseen Z, Kopylev L, Cohen LG. Age-dependent changes in the ability to encode a novel elementary motor memory. Ann Neurol. 2003;53:521–524. doi: 10.1002/ana.10529. [DOI] [PubMed] [Google Scholar]
  37. Schieber MH. Constraints on somatotopic organization in the primary motor cortex. J Neurophysiol. 2001;86:2125–2143. doi: 10.1152/jn.2001.86.5.2125. [DOI] [PubMed] [Google Scholar]
  38. Scott SH, Kalaska JF. Changes in motor cortex activity during reaching movements with similar hand paths but different arm postures. J Neurophysiol. 1995;73:2563–2567. doi: 10.1152/jn.1995.73.6.2563. [DOI] [PubMed] [Google Scholar]
  39. Singh KD, Hamdy S, Aziz Q, Thompson DG. Topographic mapping of trans-cranial magnetic stimulation data on surface rendered MR images of the brain. Electroencephalogr Clin Neurophysiol. 1997;105:345–351. doi: 10.1016/s0924-980x(97)96699-6. [DOI] [PubMed] [Google Scholar]
  40. Sohn YH, Jung HY, Kaelin-Lang A, Hallett M. Excitability of the ipsilateral motor cortex during phasic voluntary hand movement. Exp Brain Res. 2003;148:176–185. doi: 10.1007/s00221-002-1292-5. [DOI] [PubMed] [Google Scholar]
  41. Terao Y, Ugawa Y, Suzuki M, Sakai K, Hanajima R, Gemba-Shimizu K, Kanazawa I. Shortening of simple reaction time by peripheral electrical and submotor-threshold magnetic cortical stimulation. Exp Brain Res. 1997;115:541–545. doi: 10.1007/pl00005724. [DOI] [PubMed] [Google Scholar]
  42. Valls-Sole J, Sole A, Valldeoriola F, Munoz E, Gonzalez LE, Tolosa ES. Reaction time and acoustic startle in normal human subjects. Neurosci Lett. 1995;195:97–100. doi: 10.1016/0304-3940(94)11790-p. [DOI] [PubMed] [Google Scholar]
  43. Wassermann EM, McShane LM, Hallett M, Cohen LG. Noninvasive mapping of muscle representations in human motor cortex. Electroencephalogr Clin Neurophysiol. 1992;85:1–8. doi: 10.1016/0168-5597(92)90094-r. [DOI] [PubMed] [Google Scholar]
  44. Ziemann U. Intracortical inhibition and facilitation in the conventional paired TMS paradigm. Electroencephalogr Clin Neurophysiol Suppl. 1999;51:127–136. [PubMed] [Google Scholar]
  45. Ziemann U, Tergau F, Netz J, Homberg V. Delay in simple reaction time after focal transcranial magnetic stimulation of the human brain occurs at the final motor output stage. Brain Res. 1997;744:32–40. doi: 10.1016/s0006-8993(96)01062-1. [DOI] [PubMed] [Google Scholar]

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