Motor representation can be studied at different physiological, anatomical and behavioural spatial scales. If motor representation is observed in relation to large anatomical structures, the scale of observation may be termed a macroscale of motor representation. Clinically, this scale is used to localize the motor cortex presurgically. Often, in this approach the implicit methodological assumption is that all signals arise from a single site with little or no expansion (e.g. dipole analysis in EEG studies). In our study, this scale was used to compare TMS mapping results with the anatomy of the underlying cortex and with results obtained with cortical activation studies using PET.
If details of motor representation at a millimetre or submillimetre range are investigated, the scale of observation may be termed a microscale of motor representation. This scale can be approached by electrophysiological methods of mapping motor representations, which have recently been reviewed by Cheney (1996). The exact amount of the excited cortex depends on the methodological details of the stimulation technique used. As a rule, an increasingly sophisticated picture of the organization of the motor cortex emerges with smaller stimulation electrodes, and the intracortical microstimulation (ICMS) technique probably comes closest to an anatomical description of motor representation because it is least confounded by stimulus spread.
Macroscale representation: comparison of TMS maps to anatomy and PET activation studies
Using TMS, previous studies have investigated muscle representations of the upper extremity (Brasil-Neto et al. 1992a,b; Wilson et al. 1993) or muscles of the hand and the leg (Singh et al. 1997) and found a somatotopical arrangement of cortical muscle representation in agreement with the traditional homunculus extended over the lateral surface of the precentral gyrus (Penfield & Boldrey, 1937). Our results confirm and extend these findings using target muscles of three different body parts. We employed the centre-of-gravity method (Wassermann et al. 1992, 1996) to integrate TMS maps with the underlying anatomy and metabolic activation studies. The mean COG projection of the FDI was located on the posterior lip of the precentral gyrus and close to the anatomical projection of the COG of the PET activation areas (Fig. 9). The location of the TMS projection corresponded to the location of the highest density of corticospinal neurones, and in particular, of the Betz cells, which are located in the posterior bank of the precentral gyrus (Porter & Lemon, 1995) and which are likely to be the anatomical origin of the fast-descending volleys generated by TMS. COG projections of TMS-derived maps and COGs of regional activation both lay on the posterior lip of the precentral gyrus and in close proximity to each other. TMS-derived COGs were located slightly anterior with respect to PET-derived COGs. One possibility would be that the site of excitation corresponded to the site of maximal magnetic field intensity, directly under the junction of the coil, rather than to the site of the virtual cathode as determined in preliminary experiments on peripheral nerves and used in the present study. Because the location of the virtual cathode was only 1 mm away from the junction of the coil, this difference would not provide a sufficient explanation. One could also argue that the different location of TMS-derived COGs could be due to the fact that the TMS maps were obtained in the relaxed state, and the PET maps in the activated state. This possibility is unlikely because muscle activation did not induce a systematic anterior displacement of TMS-derived COGs (Fig. 4). Instead, we suggest that the more posterior location of the PET-derived COGs results from the fact that TMS maps indicate activation of the motor output system, while the area of metabolic activation in PET reflects activity of both the motor output circuits as well as of the reafferent activity in the primary somatosensory cortex.
TMS mapping has been compared with structural anatomy and functional brain activation as assessed by imaging techniques in three recent studies (Wassermann et al. 1996; Krings et al. 1997; Singh et al. 1997). Of these, only the study by Wassermann et al., using the method of projecting the TMS-derived COGs into the brain, showed a clear anatomical correspondence of the site of TMS activation with the precentral gyrus. Because Krings et al. (1997) used the POE, rather than the COG, to integrate TMS maps with anatomy, the projection was found to overlay the postcentral gyrus (cf. their Fig. 1). Since the boundaries of TMS-derived maps and those generated by functional activation studies are both defined by arbitrary thresholds, it seems more appropriate to compare the spatial co-ordinates of their COGs rather than the location of the TMS-derived COG in a spatially extended functional activation map. Such a comparison is lacking in previously published studies. Thus the present findings, although in general confirming previous findings of correlational analyses (Wassermann et al. 1996; Krings et al. 1997; Singh et al. 1997), extend those findings in demonstrating a high degree of correspondence between TMS-derived and PET-derived COGs.
TMS mapping has been advocated as a tool to identify the motor cortex presurgically. Integration of TMS maps with anatomy involves many intermediate steps each of which adds to spatial inaccuracies. Therefore we believe that for surgical purposes, the accuracy of individual anatomo-physiological integration should be improved by precise acquisition of positional coil data. This approach was used by Wassermann et al. (1996). In our view, there is no real advantage in visualizing on line the position of the stimulating coil in an MR data set obtained prior to the investigation (Krings et al. 1997) if the accuracy of the transformation procedure rests on only three landmarks. Even with highly accurate integration methods mapping results in surgical patients should be interpreted with caution, since there are only anecdotal reports of the validity of the TMS mapping technique under the circumstances of a grossly distorted anatomy (Krings et al. 1997). This issue also becomes important when TMS is used outside the motor cortex, and in particular as an interventional, rather than as a probing tool.
Microscale representation: methodological constraints and spatial aspects of TMS maps
In humans, the TMS mapping technique has been employed to investigate motor cortical plasticity (Pascual-Leone et al. 1995; Cohen et al. 1996; Rijntjes et al. 1997). In some studies employing TMS mapping, implicit assumptions have been made concerning the spatial interpretation of maps generated by TMS. However, some principles of how TMS maps are influenced have apparently been neglected. The principal cortical factor determining size and shape of TMS-derived maps is excitability of the stimulated region. For example, at a fixed stimulus intensity, the number of scalp positions from which MEPs can be evoked increases with increasing excitability of the cortical elements generating corticospinal commands. Similarly, the number of positions will increase with larger stimulus intensity. A simple demonstration that the spatial information is not readily available from TMS maps is evident from studies projecting MEP amplitude maps directly onto MRI scans (Levy et al. 1991; Krings et al. 1997). Clearly, corticospinal commands targeting α-motoneurons cannot arise from all the cortical sites from which the corresponding overlying scalp positions yielded EMG responses. Another example of an overly simple interpretation of TMS-generated maps is claims that different muscles have overlapping representational cortical areas (Verhagen Metman et al. 1993), since physical stimulus spread would cause a similar overlap of maps if the commands to the muscles originated from small and non-overlapping anatomical regions. TMS clearly cannot resolve the mosaic-like micro-organisation of the motor cortex in as much detail as revealed by single-neurone recordings or ICMS, because of the physical dimensions of the magnetic and the electric field induced within the cortex. Given the dimensions of physical and biological stimulus spread, it is a reasonable question whether TMS maps can at all justifiably be used to retrieve any detailed spatial information on the microscale level of the motor cortex. Indeed, Ridding & Rothwell (1997) have argued that, in paradigms of motor plasticity, TMS maps cannot distinguish between effects on the organization of the cortex and on changes in excitability.
The spatial extension of the anatomical hand representation in the primary motor cortex is not known in humans. Nudo & Masterton (1990) measured the size of the anatomical sources of the corticospinal tract in mammals from twenty-two different species. They found that the amount of corticospinal tract cortex is closely related to the total amount of neocortex and that the relationship of the amount of corticospinal tract cortex to total cortex is constant along the anthropoid lineage. The same constancy was observed for the ratio of the subregion containing Brodmann area 4 to total amount of neocortex (see their Fig. 5), but the ratio for anatomical size of area 4 to total amount of neocortex was not investigated. If the same rule were applicable to area 4 itself, then an estimate of the size of human anatomical forearm representation could be made using an ICMS approximation of anatomical representation in squirrel monkeys (Nudo et al. 1992, 1996): the average spatial extent of the squirrel monkey forearm representation was 9.69 mm2 (Nudo et al. 1992) to 12.08 mm2 (Nudo et al. 1996). The squirrel monkey neocortex has an approximate area of 2150 mm2 (Nudo & Masterton, 1990). The human neocortex (220 000 mm2; Zenker, 1985) is approximately 100 times larger than the squirrel monkey cortex and therefore the human motor cortical forearm representation would have an extension of around 970–1210 mm2 (or from 3.1 cm × 3.1 cm to 3.5 cm × 3.5 cm). This estimate neglects minor inaccuracies resulting from using ICMS as an approximation of anatomical representation. Although human area 4 is partially buried in the anterior wall of the central sulcus, where it may be less excitable by low-intensity TMS, a part of it is exposed at the crest of the precentral gyrus and oriented in parallel with the skull surface (Zilles et al. 1995). TMS presumably activates corticospinal neurones trans-synaptically via horizontal afferent projections (Rothwell, 1997) and the distance that those projections can travel within the cortex is a few millimetres (Huntley, 1997).
The minimum spatial resolution of TMS (i.e. the smallest distance at which a difference in amplitude of the evoked potentials can be reliably recognized) has been estimated to be 5 mm in previous mapping studies (Brasil-Neto et al. 1992b). This methodological spatial resolution does not directly reflect a spatial resolution of the excited cortical area. However, it is important to note that its dimension and the magnitude of the variability of COG measurements found in the present study are substantially below the above estimates of anatomical size of the origin of the corticospinal tract targeting α-motoneurons of the small hand and finger muscles. Thus, TMS maps are indeed likely to contain information on the spatial organization of the underlying cortex if certain methodological constraints are observed (see below). These conclusions are also in agreement with experimental findings that the number of excitable scalp positions can increase in the absence of changes in spinal excitability and alterations of motor threshold at the POE (Cohen et al. 1996).
How can this ‘microscale’ spatial information be retrieved? For reasons outlined above, there is no direct way to calculate the dimensions of the excited area from the dimensions of the TMS maps. Changes in excitability and spatial changes, associated with experimental conditions, can be partially disentangled by using fixed multiples of motor threshold during mapping or by using normalized maps. In this approach, arbitrary thresholds are used to define spatial borders. The number of positions meeting a certain relative threshold criterion will remain constant if excitability changes homogeneously within an excitable area and if the extension of that area remains constant. Conversely, the number of positions will increase if (i) excitability at the point of maximum excitability remains constant and the active area enlarges, or (ii) the increase in excitability at the point of maximum excitability is less than at the neighbouring sites. In the present study, we did not systematically explore the dependence of the number of excitable positions on the arbitrary threshold. However, the T3P measure seems to maintain a balance between two requirements of an arbitrary threshold: sensitivity to spatial changes in excitability and reasonable relationship to the size of the excitable nervous tissue.
While the number of positions associated with amplitudes exceeding an arbitrary threshold is likely to be sensitive to a symmetrical spatial expansion of excitability within or outside the original representational area, the centre of gravity (e.g. Wilson et al. 1993, 1996), on the other hand, is likely to be a measure of relative shifts in excitability within the representational area, as well as of an asymmetric expansion. Surprisingly, neither of the two variables has previously been sufficiently characterized.
The dependence of COG accuracy and number of T3Ps on stimulation parameters lead to specific methodological constraints when experimental differences of maps are investigated. For TMS mapping of different successive experimental conditions (e.g. prior to and following an intervention), it is safe to apply parameters for which the confidence region of the mean COG distance from the optimal COG estimate is smaller than the expected change in COG. For example, to detect a mean COG difference of 1 mm, preferably ten trials per site and a maximally extended stimulation area should be used. However, in an individual subject, as was argued above, using ten trials per site and a maximal extension of the stimulation area, only a distance in COGs greater than 3.1 mm in any two successive sessions would indicate a significant change of COG positions. Similarly, at least eight to ten stimuli per site must be used to estimate the number of T3Ps correctly in a group of subjects. Extending the stimulated field to positions where no responses could be elicited occasionally yielded a substantial improvement in accuracy of COG when compared with calculations of COG based on a fixed 7 cm × 7 cm area of stimulation. Therefore it seems appropriate, for future mapping studies, to recommend the use of maximally extended stimulation areas rather than a fixed radius around the pPOE. There was no advantage of completely randomizing the site of magnetic stimuli as opposed to finishing the set of trials first on one site before moving on to the next site. Using the above-listed parameters, a TMS map can be completed relatively quickly and it is feasible to investigate multiple experimental conditions in an individual subject. Does the TMS mapping procedure influence its own results? It has been shown that repetitive cortical stimulation at frequencies of about 1 Hz leads to a change of cortical representational maps and excitability (Nudo et al. 1990). In our study, using stimulation frequencies around 0.3 Hz, the number of T3Ps was independent of the trial order, supplying indirect evidence that TMS mapping induced no cortical excitability changes at this stimulation frequency.
Handedness and somatotopy
ICMS studies in monkeys have shown a larger representation of hand muscles on the dominant as compared with the non-dominant hemisphere (Nudo et al. 1992). In humans, the size of the precentral gyrus differs between the dominant and the non-dominant hemisphere (Amunts et al. 1996). Lower motor thresholds, indicating an increased cortical excitability of dominant hand muscles, have previously been found by employing TMS in humans (Triggs et al. 1994). Furthermore, the dominant hand occupied a larger area of the cortex in a recent study combining fMRI and TMS (Krings et al. 1997). In another TMS study, however, no significant differences were found in a number of variables comparing dominant with non-dominant hand muscle representation (Cicinelli et al. 1997). In our study, there was a trend toward a greater number of T3Ps on the dominant hemisphere, but the difference was not significant. It is likely that the lack of clear differences between the dominant and the non-dominant hemisphere found in our study and in the study by Cicinelli and co-workers (1997) results from the fact that a substantial, and presumably interindividually variable part of Brodmann area 4 controlling hand movements is buried in the intrasulcal surface of the precentral gyrus where the cortical output elements are less readily excited by TMS (Rothwell, 1997). Indeed, it is the intrasulcal surface where the differences between dominant and non-dominant hemispheres have been found morphometrically (Amunts et al. 1996).
It has previously been shown that both ipsilateral and contralateral cortical stimulation evoke responses in facial muscles suggesting that the corticonuclear tract projects bilaterally to the corresponding motoneurons. In single motor unit studies, evidence was found for an oligosynaptic corticobulbar pathway projecting mainly contralaterally as well as for a polysynaptic pathway projecting bilaterally (Meyer et al. 1994). However, it remains unclear whether ipsilateral and contralateral projections have spatially separate cortical representations. Therefore it is remarkable that the mean COGs of ipsilateral and contralateral facial muscle representations were virtually identical. This may indicate that ipsi- and contralateral facial muscle representations share the same neuronal substrates. In this respect, facial muscles differ from small hand muscles, since two spatially distinct zones have been found for ipsilateral and contralateral FDI representations (Wassermann et al. 1994).
Centres of gravity at target muscle relaxation versus preactivation
Using slightly different stimulation parameters, we have confirmed previous studies demonstrating a difference of COGs of the relaxed as compared with the contracted muscle (Wilson et al. 1995). In our study, the mean 2-D distance of the COG with preactivation from the COG at rest was 2.7 ± 0.2 mm and, thus fell outside the 95 % confidence interval for the mean difference of COG measurement from the optimal COG estimate at the stimulation parameters used. COG co-ordinates, however, did not change systematically in the lateromedial direction. The mean deviation along the coronal axis was only 1.0 ± 1.6 mm and substantially less than the approximately 6 mm medial displacement of the COG induced by contraction of the APB observed by Wilson and co-workers (1995). A possible reconciliation of the two apparently diverging results could be that the COG of thumb muscle representation is located at the lateral border of the finger representation while the muscles subserving the index finger are located preferentially towards the centre of the finger representation (Penfield & Boldrey, 1937). If recruitment of additional neuronal elements with preactivation were confined to the upper limb representation (see e.g. Donoghue & Sanes, 1994), the thumb (APB) representation would have to expand medially while the index finger (FDI) representation could expand in both directions.