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Somatotopy of anterior cingulate cortex (ACC) and supplementary motor area (SMA) for electric stimulation of the median and tibial nerves: An fMRI study
www.elsevier.com/locate/ynimg NeuroImage 33 (2006) 700 – 705
Somatotopy of anterior cingulate cortex (ACC) and supplementary motor area (SMA) for electric stimulation of the median and tibial nerves: An fMRI study D. Arienzo,a,b,⁎ C. Babiloni,c A. Ferretti,a,b M. Caulo,a,b C. Del Gratta,a,b A. Tartaro,a,b P.M. Rossini,d and G.L. Romani a,b a
Department of Clinical Sciences and Bioimaging, G. D’Annunzio University, Chieti, Italy Institute for Advanced Biomedical Technologies, G. D’Annunzio University Foundation, Chieti, Italy c Department of Human Physiology and Pharmacology, La Sapienza University of Rome, Rome, Italy d Department of Neurology, Campus Biomedico University, Rome, Italy b
Received 23 December 2005; revised 12 May 2006; accepted 7 June 2006 Available online 28 August 2006 In this study, we tested whether there is a somatotopic sensory organization in human anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in 15 normal young adults during nonpainful and painful electric stimulation of median nerve at the wrist and tibial nerve at the medial malleolus. Results showed that the representation of median nerve area was more anterior in the ACC and more inferior in the SMA than the one of tibial nerve area. This was true for both nonpainful and painful stimulation intensities. These results point to a somatotopic sensory organization of human ACC and SMA. © 2006 Elsevier Inc. All rights reserved. Keywords: Functional magnetic resonance imaging (fMRI); Median-tibial nerve electrical stimulation; Secondary somatosensory cortex (SII); Anterior cingulate cortex (ACC); Supplementary motor area (SMA)
Introduction Fine somatotopic organization of human primary (SI) and secondary (SII) somatosensory cortices has been specified by functional magnetic resonance imaging (fMRI; Del Gratta et al., 2000; Ruben et al., 2001). An open issue is whether this is true for anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of a central feed-back sensory processing for the guidance of movements. Indeed, it is well known that these areas are involved in motivational and motoric aspects of human movements.
Functional neuroimaging studies have pointed to a motorotopic organization of ACC and SMA in subjects performing motor tasks (Colebatch et al., 1991; Luppino et al., 1991; Grafton et al., 1993). Of interest, only one study could demonstrate a separate motoric representation of hand, shoulder, and leg in all subjects (Fink et al., 1997). On the whole, there would be a rostro-caudal distribution of the face, hand, and foot areas supporting the theory of the somatotopic organization of the human SMA in motor control. Subsequent functional neuroimaging studies have provided additional specifications to the rostro-caudal distribution of hand and foot motoric representations in human SMA (Rijntjes et al., 1999; Mayer et al., 2001; Hanakawa et al., 2001; Debaere et al., 2001; Indovina and Sanes, 2001; Luft et al., 2002). These results are also in agreement with electric stimulation data in patients with intractable seizures (Hanakawa et al., 2001; Lim et al., 1994; Fried et al., 1991) and with surgical observations (Fontaine et al., 2002). Furthermore, they extend previous findings of intracranial microstimulation in monkeys showing the rostro-caudal organization of orofacial and limb motoric representations within the SMA (Woolsey et al., 1952; Mitz and Wise, 1987; Luppino et al., 1991). In this study, we tested whether there is a somatotopic sensory organization in human ACC and SMA, as a possible reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in normal subjects during nonpainful and painful electric stimulation of upper and lower limb. Methods Subjects
⁎ Corresponding author. Department of Clinical Sciences and Bioimaging, G. D’Annunzio University, Chieti, Italy. E-mail address: [email protected] (D. Arienzo). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2006.06.030
Fifteen healthy volunteers (6 males, 9 females; 19 to 23 years; right handed according to the Edinburgh Inventory Oldfield, 1971) were enrolled. All subjects gave their written informed consent
D. Arienzo et al. / NeuroImage 33 (2006) 700–705
according to the Declaration of Helsinki (World Medical Association Declaration of Helsinki, 1997). The general procedures were approved by the local Institutional Ethics Committee. Stimulation procedures Both the nonpainful and painful stimuli were rectangular pulses with 2-Hz repetition rate and 400-μs duration and were delivered in different recording runs to either the right median, or right tibial nerve via nonmagnetic AgCl electrodes. Two intensity levels were used: I1: motor threshold, and I2: stimulus intensity producing moderate pain according to a subjective scale, ranging from 0 (no sensation) to 10 (pain tolerance threshold). Level I1 (0.5–9 mA—mean value 5.1 ± 3.0 mA—for the median nerve and 5–18 mA—mean value 12.3 ± 4.2 mA—for the tibial nerve) corresponded to 2 (painless thumb and hallux twitch), and the level I2 (10–32 mA—mean value 22.0 ± 7.5 mA—for the median nerve and 24–32 mA—mean value 31.4 ± 1.7 mA—for the tibial nerve), corresponded to 6 (moderate pain) in this scale. Individual stimulation levels were assessed outside the scanner just before the fMRI session, including four functional runs: nonpainful and painful stimulation of the median and tibial nerve. subjects were not required to count the perceived stimulus during the experiment, in order to avoid any effect due to arousal and topdown attentional processes. fMRI recordings BOLD contrast functional imaging data were acquired at 1.5 T by means of T2*-weighted EPI-FID sequences (TR 3 s, TE 60 ms, matrix size 64 × 64, FOV 256 mm, in-plane voxel size 4 mm × 4 mm, flip angle 90°, slice thickness 4 mm and no gap). Functional volumes consisted of 22 transaxial slices parallel to the AC–PC line. fMRI recordings BOLD contrast functional imaging data were acquired at 1.5 T by means of T2*-weighted EPI-FID sequences (TR 3 s, TE 60 ms, matrix size 64 × 64, FOV 256 mm, in-plane voxel size 4 mm × 4 mm, flip angle 90°, slice thickness 4 mm and no gap). Functional volumes consisted of 22 transaxial slices parallel to the AC–PC line. The experimental paradigm was a block design and consisted of 4 functional runs (corresponding to four experimental conditions: nonpainful and painful stimulations delivered to either the right median or the right tibial nerve; the order of the runs pseudo-randomly varied across participants). For each run, 84 volumes were acquired, alternating a state of stimulation of 27 s (corresponding, with the given TR of 3 s, to the acquisition of 9 functional volumes) with a control state having the same duration. Each run started with a control period of 12 volumes, followed by 4 stimulation blocks and 5 control blocks for each experimental condition. With a stimulus repetition rate of 2 Hz, 54 stimuli were delivered for each stimulation block. This methodological approach has been successfully used in previous fMRI studies (Fink et al., 1997, Ruben et al., 2001, Del Gratta et al., 2002, Ferretti et al., 2004). A high-resolution structural MRI volume was acquired at the end of the session via a 3D MPRAGE sequence (sagittal, matrix 256 × 256, FoV 256 mm, slice thickness 1 mm, no gap, in-plane voxel size 1 mm × 1 mm, flip angle 12°, TR = 9.7 ms, TE = 4 ms).
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Data analysis Raw data were analyzed by means of the Brain Voyager 4.9 software (Brain Innovation, The Netherlands). Due to T1 saturation effects, the first 3 scans of each run were discarded from the analysis. Functional scans were corrected for motion and linear trends, and then coregistered with the corresponding structural image. Both structural and functional volumes were transformed into the Talairach space (Talairach and Tournoux, 1998), and functional volumes were resampled at a voxel size of 3 mm × 3 mm × 3 mm. Statistical analysis was performed for individual subjects using the general linear model (GLM) (Friston et al., 1995) with correction for temporal autocorrelation (Bullmore et al., 1996; Woolrich et al., 2001), considering a separate predictor for each stimulated nerve and stimulus intensity. To account for the hemodynamic delay, the boxcar waveform representing the rest and task conditions was convolved with an empirically founded hemodynamic response function (Boynton et al., 1996). No spatial or temporal smoothing was applied. Individual statistical maps were thresholded at P < 0.0004 at the voxel level and a cluster size of at least four voxels was required. These thresholds and an estimate of the spatial correlation of voxels were used as input in a Monte Carlo simulation (3dFWHM and AlphaSim routines of AFNI package, Cox, 1996; Forman et al., 1995) in order to assess the overall significance level (the probability of a false detection for the entire functional volume). In this way we obtained P < 0.05 as the significance level corrected for multiple comparisons. Individual thresholded statistical maps were then superimposed on the respective structural scans for the localization of significantly activated areas. Talairach coordinates of each activated area were derived considering the centroid of the corresponding cluster of activation. In addition to single-subject analysis, a fixed-effect voxelwise group analysis was performed as well. In this case, the time series from each run and subject were z-normalized and concatenated prior to the GLM computation. Results Group analysis Activation across subjects was observed at the two stimulus intensities, and for both median and tibial nerve stimulations, in contralateral SI, bilateral SII, bilateral insular cortex (Ferretti et al., 2004), ACC, and SMA. Activation in the SMA was observed only in the contralateral hemisphere, whereas activation in the ACC was observed both in the contralateral and the ipsilateral hemisphere. The Talairach coordinates of the observed clusters of activation in SMA, ACC and Insular cortex are depicted in Figs. 1 and 2 for the two stimulus intensities, respectively. The group data suggest a somatotopic organization in both ACC and SMA for painful and nonpainful stimulation, as shown in Figs. 1 and 2. Analysis of individual subjects in ACC and SMA Due to intersubject anatomical variability, the relative location of different activated areas was studied using fMRI data from individuals. This procedure allowed to avoid the problems of a voxel-wise analysis due to the intrinsic limitations of Talairach
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Fig. 1. Results of the statistical group analysis of the fMRI responses showing the centroids (with standard deviation) of activated areas after the nonpainful stimulation of median and tibial nerve. (A) (sagittal view) Anterior cingulate cortex (ACC) and supplementary motor area (SMA) of the left (contralateral) hemisphere. (B) (axial view) Activation in the insular cortex. The centroids of clusters of activation were superimposed on a Talairach transformed anatomical scan of one of the subjects.
spatial normalization, as described for example in Beauchamp et al. (2004). Activation in the supplementary motor area (SMA) was observed after median nerve stimulation in eight out of fifteen subjects for nonpainful stimulus intensities and in nine out of fifteen subjects for painful stimulus intensities, after tibial nerve stimulation in seven out of fifteen subjects for nonpainful stimulus intensities and in ten out of fifteen subjects for painful stimulus intensities. The Activation in the Anterior Cingulate Cortex (ACC) was observed after median nerve stimulation in four out of fifteen subjects for nonpainful stimulus intensities and in seven out of fifteen subjects for painful stimulus intensities, after tibial nerve stimulation in seven out of fifteen subjects for nonpainful stimulus intensities and in eleven out of fifteen subjects for painful stimulus
intensities. Subjects with activation in the ACC or in the SMA for both median and tibial nerve stimulation for both stimulus intensities were selected from the group and the locations of the respective activations were compared. The statistical significance of differences in the individual Talairach coordinates between median and tibial nerve activation was tested for ACC and SMA with an ANOVA. The ANOVA post hoc testing indicated significant differences in the ACC when comparing the y-coordinates of the median and tibial activation (P < 0.01 for painful stimulation and P < 0.02 for nonpainful stimulation), and in the SMA when comparing the z-coordinates of the median and tibial activation (P < 0.01 for painful stimulation and P < 0.02 for nonpainful stimulation). The ANOVA revealed no statistical differences when comparing the coordinates of the nonpainful
Fig. 2. Results of the statistical group analysis of the fMRI responses showing the centroids (with standard deviation) of activated areas after the painful stimulation of median and tibial nerve. (A) (sagittal view) Anterior cingulate cortex (ACC) and supplementary motor area (SMA) of the left (contralateral) hemisphere. (B) (axial view) Activation in the insular cortex. The centroids of clusters of activation were superimposed on a Talairach transformed anatomical scan of one of the subjects.
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and painful activation in both the ACC and the SMA. The statistic suggests that while the ACC and SMA contain separate representations of the median and tibial nerves, they do not distinguish between painful and nonpainful stimulation. A schematic view of the relative anatomical locations of the ACC and the SMA is shown in Fig. 3. Activation in the insular cortex A statistically significant activation of the bilateral insula was observed in eight out of fifteen subjects after median nerve stimulation and in fourteen out of fifteen subjects after tibial nerve stimulation. For both median and tibial nerve stimulations, two distinct regions in the anterior–posterior axis of the Insular cortex were active in both the contralateral and ipsilateral hemispheres. Subjects with activation in the Insular cortex for both median and tibial nerve stimulation and for both stimulus intensities were
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selected from the group and the locations of the respective activations were compared. An ANOVA revealed no statistical differences in the coordinates of median and tibial nerve activation in both the anterior and posterior insular cortex for both stimulation intensities. This suggests that the insular cortex is involved in the processing of somatosensory information originating from different body parts. Additionally, these results suggest that the Insular cortex does not distinguish between painful and nonpainful stimulation. Discussion Are hand and foot somatosensory representations in ACC and SMA separate and, if affirmative, is this somatotopy preserved for noxious stimuli? When compared to the foot representation as obtained by fMRI, the hand representation was located more anteriorly in the ACC and more inferiorly in the SMA. This was true for both nonpainful and painful stimulation. These results
Fig. 3. Schematic view of the position of SMA and ACC subregions in the Talairach space (mean values of centroid of cluster of activation and standard errors across subjects). The significance of differences among the mean coordinates was assessed by means of analysis of variance.
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support the idea that spatial information of somatosensory stimuli, which is extracted by SI and bilateral SII (Del Gratta et al., 2000, 2002; Ruben et al., 2001; Bingel et al., 2004), is also represented within ACC and SMA. Furthermore, they extend previous neuroimaging results, which point to a motorotopic organization in ACC and SMA in subjects performing movements of different body segments, into the somatotopic domain (Colebatch et al., 1991; Luppino et al., 1991; Grafton et al., 1993; Fink et al., 1997; Rijntjes et al., 1999; Mayer et al., 2001; Hanakawa et al., 2001; Debaere et al., 2001; Indovina and Sanes, 2001; Luft et al., 2002). Finally, these results replicate findings of ACC and SMA activation due to somatosensory stimulation from electrophysiological studies in monkeys (Romo et al., 2003; Akazawa et al., 2000) and humans (Allison et al., 2006; Luders, 1996) and also in neuroimaging studies in humans (Lin et al., 1996; Polonara et al., 1999). The present results support the idea that nonpainful and painful stimuli have a similar somatotopic representation in ACC and SMA. This is at odds with the organization of human lateral discriminative somatosensory systems including SI and SII, in which nonpainful and painful somatosensory stimuli are spatially segregated and are diversely processed by sequential and parallel processes, respectively (Ploner et al., 1999; Treede et al., 2000). How can somatosensory information reach ACC and SMA? At the present stage of research, the functional counterpart of this anatomical connectivity can only be hypothesized. SI somatotopy would reflect the early cortical processing of spatial somatosensory information, whereas SII somatotopy would principally reflect sensorimotor and cognitive integration (Luppino et al., 1993). After early processing, SII and insular cortex would alert frontal systems (Mesulam and Mufson, 1982). The segregation of spatial somatosensory information within ACC and SMA would reflect a modular organization of the motor plans for body segments, able to optimize motor coordination and control. This might allow integration of the attentional enhancement of the stimuli, emotional coloring, and appropriate motor commands in order to respond to the source of stimulation. A possible anatomical substrate would be the presence of a separate and somatotopically organized streamline connecting primary motor cortex, SMA, and ACC (Morecraft and Van Hoesen, 1992). Unlike SI and SII, where a consistent activation associated with tactile stimulation was found in all subjects, SMA and ACC only show activity in some individuals. This finding suggests that, unlike SI and SII, SMA and ACC do not play an essential role in the extraction of information from sensory stimuli, but rather reflect individual differences occurring at a later stage of processing. Consistent with this interpretation, it is conceivable that, similar to the activity in the insula, activation in SMA and ACC be determined by the different saliency expressed by the same stimuli in different subjects, and reflect individual strategies aimed at manipulating the tactile stimulus or withdrawing from a source of pain. A brief methodological remark regarding the spatial resolution of our fMRI approach in the dissociation of activation loci in ACC and SMA is in order. Given the close position of the two areas, the classification of the activated areas based only on the Talairach coordinates should be considered cautiously. In fact, the anatomy of a single brain may deviate significantly from the Talairach brain making its normalization difficult. However, the present results seem to clearly disentangle the hand and foot representations within ACC and SMA. We classified the activation for each
individual subject by projecting statistical maps onto the structural brain image. This allowed a safe localization of the cortical activity in the surface of ACC when compared to SMA. Conclusion To our knowledge, this is the first demonstration of the idea of a somatotopic organization in both human ACC and SMA as revealed by nonpainful and painful stimulations. The hand and foot representations in ACC and SMA are separate for nonpainful as well as painful stimulation. This suggests a functional parietofrontal connectivity as a reasonable neural correlate of the ability to spatially locate nonpainful and painful stimuli and to promote motor coordination for both handling and immediate defence/ withdrawal behavior. Acknowledgments This work was partially supported by a grant from the Italian Ministry of Research to the Center of Excellence on Aging of the University of Chieti. References Akazawa, T., Tokuno, H., Nambu, A., Hamada, I., Ito, Y., Ikeuchi, Y., Imanishi, M., Hasegawa, N., Hatanaka, N., Takada, M., 2000. A cortical motor region that represents the cutaneous back muscles in the macaque monkey. Neurosci. Lett. 282 (3), 125–128. Allison, T., McCarthy, G., Luby, M., Puce, A., Spencer, D.D., 2006. Localization of functional regions of human mesial cortex by somatosensory evoked potential recording and by cortical stimulation. Electroencephalogr. Clin. Neurophysiol. 100 (2), 126–140 (Review). Beauchamp, M.S., Lee, K.E., Argall, B.D., Martin, A., 2004. Integration of auditory and visual information about objects in superior temporal sulcus. Neuron 41, 809–823. Bingel, U., Lorenz, J., Glauche, V., Knab, R., Glascher, J., Weiller, C., Bunchel, C., 2004. Somatotopic organization of human somatosensory cortices for pain: a single trial fMRI study. NeuroImage 23, 224–232. Boynton, G.M., Engel, S.A., Glover, G.H., Heeger, D.J., 1996. Linear systems analysis of functional magnetic resonance imaging in human V1. J. Neurosci. 16, 4207–4241. Bullmore, E., Brammer, M., Williams, S., Rabe-Hesketh, S., Janot, N., David, A., Mellers, J., Howard, R., Sham, P., 1996. Statistical methods of estimation and inference for functional MR image analysis. Magn. Reson. Med. 35, 261–277. Colebatch, J.G., Deiber, M.P., Passingham, R.E., Friston, K.J., Frackowiak, R.S., 1991. Regional cerebral blood flow during voluntary arm and hand movements in human subjects. J. Neurophysiol. 65 (6), 1392–1401. Cox, R.W., 1996. AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162–173. Debaere, F., Swinnen, S.P., Beatse, E., Sunaert, S., Van Hecke, P., Duysens, J., 2001. Brain areas involved in interlimb coordination: a distributed network. NeuroImage 14 (5), 947–958. Del Gratta, C., Della Penna, S., Tartaro, A., Ferretti, A., Torquati, K., Bonomo, L., Romani, G.L., Rossini, P.M., 2000. Topographic organization of the human primary and secondary somatosensory areas: an fMRI study. NeuroReport 11 (9), 2035–2043. Del Gratta, C., Della Penna, S., Ferretti, A., Franciotti, R., Pizzella, V., Tartaro, A., Torquati, K., Bonomo, L., Romani, G.L., Rossini, P.M., 2002. Topographic organization of the human primary and secondary somatosensory cortices: comparison of fMRI and MEG findings. NeuroImage 17, 1373–1383.
D. Arienzo et al. / NeuroImage 33 (2006) 700–705 Ferretti, A., Del Gratta, C., Babiloni, C., Caulo, M., Arienzo, D., Tartaro, A., Rossini, P.M., Romani, G.L., 2004. Functional topography of the secondary somatosensory cortex for non painful and painful stimulation of median and tibial nerve: an fMRI study. NeuroImage 23 (3), 1217–1225. Fink, G.R., Frackowiak, R.S., Pietrzyk, U., Passingham, R.E., 1997. Multiple nonprimary motor areas in the human cortex. J. Neurophysiol. 77 (4), 2164–2174. Fontaine, D., Capelle, L., Duffau, H., 2002. Somatotopy of the supplementary motor area: evidence from correlation of the extent of surgical resection with the clinical patterns of deficit. Neurosurgery 50 (2), 297–303. Forman, S.D., Cohen, J.D., Fitzgerald, M., Eddy, W.F., Mintun, M.A., Noll, D.C., 1995. Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn. Reson. Med. 33, 636–647. Fried, I., Katz, A., McCarthy, G., Sass, K.J., Williamson, P., Spencer, S.S., Spencer, D.D., 1991. Functional organization of human supplementary motor cortex studied by electrical stimulation. J. Neurosci. 11 (11), 3656–3666. Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.P., Frith, C.D., Frackowiak, R.S.J., 1995. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2, 173–181. Grafton, S.T., Woods, R.P., Mazziotta, J.C., 1993. Within-arm somatotopy in human motor areas determined by position emission tomography imaging of cerebral blood flow. Exp. Brain Res. 95 (1), 172–176. Hanakawa, T., Ikeda, A., Sadato, N., Okada, T., Fukuyama, H., Nagamine, T., Honda, M., Sawamoto, N., Yazawa, S., Kunieda, T., Ohara, S., Taki, W., Hashimoto, N., Yonekura, Y., Konishi, J., Shibasaki, H., 2001. Functional mapping of human medial frontal motor areas. The combined use of functional magnetic resonance imaging and cortical stimulation. Exp. Brain Res. 138 (4), 403–409. Indovina, I., Sanes, J.N., 2001. On somatotopic representation centers for finger movements in human primary motor cortex and supplementary motor area. NeuroImage 13 (6 Pt. 1), 1027–1034. Lim, S.H., Dinner, D.S., Pillay, P.K., Luders, H., Morris, H.H., Klem, G., Wyllie, E., Awad, I.A., 1994. Functional anatomy of the human supplementary sensorimotor area: results of extraoperative electrical stimulation. Electroencephalogr. Clin. Neurophysiol. 91 (3), 179–193. Lin, W., Kuppusamy, K., Haacke, E.M., Burton, H., 1996. Functional MRI in human somatosensory cortex activated by touching textured surfaces. J. Magn. Reson. Imaging 6 (4), 565–572. Luders, H.O., 1996. The supplementary sensorimotor area. An overview. Adv. Neurol. 70, 1–16 (Review). Luft, A.R., Smith, G.V., Forrester, L., Whitall, J., Macko, R.F., Hauser, T.K., Goldberg, A.P., Hanley, D.F., 2002. Comparing brain activation associated with isolated upper and lower limb movement across corresponding joints. Hum. Brain Mapp. 17 (2), 131–140. Luppino, G., Matelli, M., Camarda, R.M., Gallese, V., Rizzolatti, G., 1991. Multiple representations of body movements in mesial area 6 and the
705
adjacent cingulate cortex: an intracortical microstimulation study in the macaque monkey. J. Comp. Neurol. 311 (4), 463–482. Luppino, G., Matelli, M., Camarda, R., Rizzolatti, G., 1993. Corticocortical connections of area F3 (SMA-proper) and area F6 (pre-SMA) in the macaque monkey. J. Comp. Neurol. 338 (1), 114–140. Mayer, A.R., Zimbelman, J.L., Watanabe, Y., Rao, S.M., 2001. Somatotopic organization of the medial wall of the cerebral hemispheres: a 3 Tesla fMRI study. NeuroReport 12 (17), 3811–3814. Mesulam, M.M., Mufson, E.J., 1982. Insula of the old world monkey: III. Efferent cortical output and comments on function. J. Comp. Neurol. 212 (1), 38–52. Mitz, A.R., Wise, S.P., 1987. The somatotopic organization of the supplementary motor area: intracortical microstimulation mapping. J. Neurosci. 7 (4), 1010–1021. Morecraft, R.J., Van Hoesen, G.W., 1992. Cingulate input to the primary and supplementary motor cortices in the rhesus monkey: evidence for somatotopy in areas 24c and 23c. J. Comp. Neurol. 322 (4), 471–489. Oldfield, R.C., 1971. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113. Ploner, M., Schmitz, F., Freund, H.J., Schnitzler, A., 1999. Parallel activation of primary and secondary somatosensory cortices in human pain processing. J. Neurophysiol. 81 (6), 3100–3104. Polonara, G., Fabri, M., Manzoni, T., Salvolini, U., 1999. Localization of the first and second somatosensory areas in the human cerebral cortex with functional MR imaging. Am. J. Neuroradiol. 20 (2), 199–205. Rijntjes, M., Dettmers, C., Buchel, C., Kiebel, S., Frackowiak, R.S., Weiller, C., 1999. A blueprint for movement: functional and anatomical representations in the human motor system. J. Neurosci. 19 (18), 8043–8048. Romo, R., Ruiz, S., Crespo, P., Zainos, A., Merchant, H., 2003. Representation of tactile signals in primate supplementary motor area. J. Neurophysiol. 70 (6), 2690–2694. Ruben, J., Schwiemann, J., Deuchert, M., Meyer, R., Krause, T., Curio, G., Villringer, K., Kurth, R., Villringer, A., 2001. Somatotopic organization of human secondary somatosensory cortex. Cereb. Cortex 11, 463–473. Talairach, J., Tournoux, P., 1998. Co-planar Stereotaxic Atlas of the Human Brain. Thieme, New York. Treede, R.D., Apkarian, A.V., Bromm, B., Greenspan, J.D., Lenz, F.A., 2000. Cortical representation of pain: functional characterization of nociceptive areas near the lateral sulcus. Pain 87 (2), 113–119 (Review). Woolrich, M.W., Ripley, B.D., Brady, M., Smith, S.M., 2001. Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage 14, 1370–1386. Woolsey, C.N., Settlage, P.H., Meyer, D.R., Sencer, W., Pinto Hamuy, T., Travis, A.M., 1952. Patterns of localization in precentral and supplementary motor areas and their relation to the concept of a premotor area. Res. Publ.-Assoc. Res. Nerv. Ment. Dis. 30, 238–264. World Medical Association Declaration of Helsinki, 1997. Recommendations guiding physicians in biomedical research involving human subjects. J. Am. Med. Assoc. 277 (11), 925–926.
Somatotopy of anterior cingulate cortex (ACC) and supplementary motor area (SMA) for electric stimulation of the median and tibial nerves: An fMRI study D. Arienzo,a,b,⁎ C. Babiloni,c A. Ferretti,a,b M. Caulo,a,b C. Del Gratta,a,b A. Tartaro,a,b P.M. Rossini,d and G.L. Romani a,b a
Department of Clinical Sciences and Bioimaging, G. D’Annunzio University, Chieti, Italy Institute for Advanced Biomedical Technologies, G. D’Annunzio University Foundation, Chieti, Italy c Department of Human Physiology and Pharmacology, La Sapienza University of Rome, Rome, Italy d Department of Neurology, Campus Biomedico University, Rome, Italy b
Received 23 December 2005; revised 12 May 2006; accepted 7 June 2006 Available online 28 August 2006 In this study, we tested whether there is a somatotopic sensory organization in human anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in 15 normal young adults during nonpainful and painful electric stimulation of median nerve at the wrist and tibial nerve at the medial malleolus. Results showed that the representation of median nerve area was more anterior in the ACC and more inferior in the SMA than the one of tibial nerve area. This was true for both nonpainful and painful stimulation intensities. These results point to a somatotopic sensory organization of human ACC and SMA. © 2006 Elsevier Inc. All rights reserved. Keywords: Functional magnetic resonance imaging (fMRI); Median-tibial nerve electrical stimulation; Secondary somatosensory cortex (SII); Anterior cingulate cortex (ACC); Supplementary motor area (SMA)
Introduction Fine somatotopic organization of human primary (SI) and secondary (SII) somatosensory cortices has been specified by functional magnetic resonance imaging (fMRI; Del Gratta et al., 2000; Ruben et al., 2001). An open issue is whether this is true for anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of a central feed-back sensory processing for the guidance of movements. Indeed, it is well known that these areas are involved in motivational and motoric aspects of human movements.
Functional neuroimaging studies have pointed to a motorotopic organization of ACC and SMA in subjects performing motor tasks (Colebatch et al., 1991; Luppino et al., 1991; Grafton et al., 1993). Of interest, only one study could demonstrate a separate motoric representation of hand, shoulder, and leg in all subjects (Fink et al., 1997). On the whole, there would be a rostro-caudal distribution of the face, hand, and foot areas supporting the theory of the somatotopic organization of the human SMA in motor control. Subsequent functional neuroimaging studies have provided additional specifications to the rostro-caudal distribution of hand and foot motoric representations in human SMA (Rijntjes et al., 1999; Mayer et al., 2001; Hanakawa et al., 2001; Debaere et al., 2001; Indovina and Sanes, 2001; Luft et al., 2002). These results are also in agreement with electric stimulation data in patients with intractable seizures (Hanakawa et al., 2001; Lim et al., 1994; Fried et al., 1991) and with surgical observations (Fontaine et al., 2002). Furthermore, they extend previous findings of intracranial microstimulation in monkeys showing the rostro-caudal organization of orofacial and limb motoric representations within the SMA (Woolsey et al., 1952; Mitz and Wise, 1987; Luppino et al., 1991). In this study, we tested whether there is a somatotopic sensory organization in human ACC and SMA, as a possible reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in normal subjects during nonpainful and painful electric stimulation of upper and lower limb. Methods Subjects
⁎ Corresponding author. Department of Clinical Sciences and Bioimaging, G. D’Annunzio University, Chieti, Italy. E-mail address: [email protected] (D. Arienzo). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2006.06.030
Fifteen healthy volunteers (6 males, 9 females; 19 to 23 years; right handed according to the Edinburgh Inventory Oldfield, 1971) were enrolled. All subjects gave their written informed consent
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according to the Declaration of Helsinki (World Medical Association Declaration of Helsinki, 1997). The general procedures were approved by the local Institutional Ethics Committee. Stimulation procedures Both the nonpainful and painful stimuli were rectangular pulses with 2-Hz repetition rate and 400-μs duration and were delivered in different recording runs to either the right median, or right tibial nerve via nonmagnetic AgCl electrodes. Two intensity levels were used: I1: motor threshold, and I2: stimulus intensity producing moderate pain according to a subjective scale, ranging from 0 (no sensation) to 10 (pain tolerance threshold). Level I1 (0.5–9 mA—mean value 5.1 ± 3.0 mA—for the median nerve and 5–18 mA—mean value 12.3 ± 4.2 mA—for the tibial nerve) corresponded to 2 (painless thumb and hallux twitch), and the level I2 (10–32 mA—mean value 22.0 ± 7.5 mA—for the median nerve and 24–32 mA—mean value 31.4 ± 1.7 mA—for the tibial nerve), corresponded to 6 (moderate pain) in this scale. Individual stimulation levels were assessed outside the scanner just before the fMRI session, including four functional runs: nonpainful and painful stimulation of the median and tibial nerve. subjects were not required to count the perceived stimulus during the experiment, in order to avoid any effect due to arousal and topdown attentional processes. fMRI recordings BOLD contrast functional imaging data were acquired at 1.5 T by means of T2*-weighted EPI-FID sequences (TR 3 s, TE 60 ms, matrix size 64 × 64, FOV 256 mm, in-plane voxel size 4 mm × 4 mm, flip angle 90°, slice thickness 4 mm and no gap). Functional volumes consisted of 22 transaxial slices parallel to the AC–PC line. fMRI recordings BOLD contrast functional imaging data were acquired at 1.5 T by means of T2*-weighted EPI-FID sequences (TR 3 s, TE 60 ms, matrix size 64 × 64, FOV 256 mm, in-plane voxel size 4 mm × 4 mm, flip angle 90°, slice thickness 4 mm and no gap). Functional volumes consisted of 22 transaxial slices parallel to the AC–PC line. The experimental paradigm was a block design and consisted of 4 functional runs (corresponding to four experimental conditions: nonpainful and painful stimulations delivered to either the right median or the right tibial nerve; the order of the runs pseudo-randomly varied across participants). For each run, 84 volumes were acquired, alternating a state of stimulation of 27 s (corresponding, with the given TR of 3 s, to the acquisition of 9 functional volumes) with a control state having the same duration. Each run started with a control period of 12 volumes, followed by 4 stimulation blocks and 5 control blocks for each experimental condition. With a stimulus repetition rate of 2 Hz, 54 stimuli were delivered for each stimulation block. This methodological approach has been successfully used in previous fMRI studies (Fink et al., 1997, Ruben et al., 2001, Del Gratta et al., 2002, Ferretti et al., 2004). A high-resolution structural MRI volume was acquired at the end of the session via a 3D MPRAGE sequence (sagittal, matrix 256 × 256, FoV 256 mm, slice thickness 1 mm, no gap, in-plane voxel size 1 mm × 1 mm, flip angle 12°, TR = 9.7 ms, TE = 4 ms).
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Data analysis Raw data were analyzed by means of the Brain Voyager 4.9 software (Brain Innovation, The Netherlands). Due to T1 saturation effects, the first 3 scans of each run were discarded from the analysis. Functional scans were corrected for motion and linear trends, and then coregistered with the corresponding structural image. Both structural and functional volumes were transformed into the Talairach space (Talairach and Tournoux, 1998), and functional volumes were resampled at a voxel size of 3 mm × 3 mm × 3 mm. Statistical analysis was performed for individual subjects using the general linear model (GLM) (Friston et al., 1995) with correction for temporal autocorrelation (Bullmore et al., 1996; Woolrich et al., 2001), considering a separate predictor for each stimulated nerve and stimulus intensity. To account for the hemodynamic delay, the boxcar waveform representing the rest and task conditions was convolved with an empirically founded hemodynamic response function (Boynton et al., 1996). No spatial or temporal smoothing was applied. Individual statistical maps were thresholded at P < 0.0004 at the voxel level and a cluster size of at least four voxels was required. These thresholds and an estimate of the spatial correlation of voxels were used as input in a Monte Carlo simulation (3dFWHM and AlphaSim routines of AFNI package, Cox, 1996; Forman et al., 1995) in order to assess the overall significance level (the probability of a false detection for the entire functional volume). In this way we obtained P < 0.05 as the significance level corrected for multiple comparisons. Individual thresholded statistical maps were then superimposed on the respective structural scans for the localization of significantly activated areas. Talairach coordinates of each activated area were derived considering the centroid of the corresponding cluster of activation. In addition to single-subject analysis, a fixed-effect voxelwise group analysis was performed as well. In this case, the time series from each run and subject were z-normalized and concatenated prior to the GLM computation. Results Group analysis Activation across subjects was observed at the two stimulus intensities, and for both median and tibial nerve stimulations, in contralateral SI, bilateral SII, bilateral insular cortex (Ferretti et al., 2004), ACC, and SMA. Activation in the SMA was observed only in the contralateral hemisphere, whereas activation in the ACC was observed both in the contralateral and the ipsilateral hemisphere. The Talairach coordinates of the observed clusters of activation in SMA, ACC and Insular cortex are depicted in Figs. 1 and 2 for the two stimulus intensities, respectively. The group data suggest a somatotopic organization in both ACC and SMA for painful and nonpainful stimulation, as shown in Figs. 1 and 2. Analysis of individual subjects in ACC and SMA Due to intersubject anatomical variability, the relative location of different activated areas was studied using fMRI data from individuals. This procedure allowed to avoid the problems of a voxel-wise analysis due to the intrinsic limitations of Talairach
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Fig. 1. Results of the statistical group analysis of the fMRI responses showing the centroids (with standard deviation) of activated areas after the nonpainful stimulation of median and tibial nerve. (A) (sagittal view) Anterior cingulate cortex (ACC) and supplementary motor area (SMA) of the left (contralateral) hemisphere. (B) (axial view) Activation in the insular cortex. The centroids of clusters of activation were superimposed on a Talairach transformed anatomical scan of one of the subjects.
spatial normalization, as described for example in Beauchamp et al. (2004). Activation in the supplementary motor area (SMA) was observed after median nerve stimulation in eight out of fifteen subjects for nonpainful stimulus intensities and in nine out of fifteen subjects for painful stimulus intensities, after tibial nerve stimulation in seven out of fifteen subjects for nonpainful stimulus intensities and in ten out of fifteen subjects for painful stimulus intensities. The Activation in the Anterior Cingulate Cortex (ACC) was observed after median nerve stimulation in four out of fifteen subjects for nonpainful stimulus intensities and in seven out of fifteen subjects for painful stimulus intensities, after tibial nerve stimulation in seven out of fifteen subjects for nonpainful stimulus intensities and in eleven out of fifteen subjects for painful stimulus
intensities. Subjects with activation in the ACC or in the SMA for both median and tibial nerve stimulation for both stimulus intensities were selected from the group and the locations of the respective activations were compared. The statistical significance of differences in the individual Talairach coordinates between median and tibial nerve activation was tested for ACC and SMA with an ANOVA. The ANOVA post hoc testing indicated significant differences in the ACC when comparing the y-coordinates of the median and tibial activation (P < 0.01 for painful stimulation and P < 0.02 for nonpainful stimulation), and in the SMA when comparing the z-coordinates of the median and tibial activation (P < 0.01 for painful stimulation and P < 0.02 for nonpainful stimulation). The ANOVA revealed no statistical differences when comparing the coordinates of the nonpainful
Fig. 2. Results of the statistical group analysis of the fMRI responses showing the centroids (with standard deviation) of activated areas after the painful stimulation of median and tibial nerve. (A) (sagittal view) Anterior cingulate cortex (ACC) and supplementary motor area (SMA) of the left (contralateral) hemisphere. (B) (axial view) Activation in the insular cortex. The centroids of clusters of activation were superimposed on a Talairach transformed anatomical scan of one of the subjects.
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and painful activation in both the ACC and the SMA. The statistic suggests that while the ACC and SMA contain separate representations of the median and tibial nerves, they do not distinguish between painful and nonpainful stimulation. A schematic view of the relative anatomical locations of the ACC and the SMA is shown in Fig. 3. Activation in the insular cortex A statistically significant activation of the bilateral insula was observed in eight out of fifteen subjects after median nerve stimulation and in fourteen out of fifteen subjects after tibial nerve stimulation. For both median and tibial nerve stimulations, two distinct regions in the anterior–posterior axis of the Insular cortex were active in both the contralateral and ipsilateral hemispheres. Subjects with activation in the Insular cortex for both median and tibial nerve stimulation and for both stimulus intensities were
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selected from the group and the locations of the respective activations were compared. An ANOVA revealed no statistical differences in the coordinates of median and tibial nerve activation in both the anterior and posterior insular cortex for both stimulation intensities. This suggests that the insular cortex is involved in the processing of somatosensory information originating from different body parts. Additionally, these results suggest that the Insular cortex does not distinguish between painful and nonpainful stimulation. Discussion Are hand and foot somatosensory representations in ACC and SMA separate and, if affirmative, is this somatotopy preserved for noxious stimuli? When compared to the foot representation as obtained by fMRI, the hand representation was located more anteriorly in the ACC and more inferiorly in the SMA. This was true for both nonpainful and painful stimulation. These results
Fig. 3. Schematic view of the position of SMA and ACC subregions in the Talairach space (mean values of centroid of cluster of activation and standard errors across subjects). The significance of differences among the mean coordinates was assessed by means of analysis of variance.
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support the idea that spatial information of somatosensory stimuli, which is extracted by SI and bilateral SII (Del Gratta et al., 2000, 2002; Ruben et al., 2001; Bingel et al., 2004), is also represented within ACC and SMA. Furthermore, they extend previous neuroimaging results, which point to a motorotopic organization in ACC and SMA in subjects performing movements of different body segments, into the somatotopic domain (Colebatch et al., 1991; Luppino et al., 1991; Grafton et al., 1993; Fink et al., 1997; Rijntjes et al., 1999; Mayer et al., 2001; Hanakawa et al., 2001; Debaere et al., 2001; Indovina and Sanes, 2001; Luft et al., 2002). Finally, these results replicate findings of ACC and SMA activation due to somatosensory stimulation from electrophysiological studies in monkeys (Romo et al., 2003; Akazawa et al., 2000) and humans (Allison et al., 2006; Luders, 1996) and also in neuroimaging studies in humans (Lin et al., 1996; Polonara et al., 1999). The present results support the idea that nonpainful and painful stimuli have a similar somatotopic representation in ACC and SMA. This is at odds with the organization of human lateral discriminative somatosensory systems including SI and SII, in which nonpainful and painful somatosensory stimuli are spatially segregated and are diversely processed by sequential and parallel processes, respectively (Ploner et al., 1999; Treede et al., 2000). How can somatosensory information reach ACC and SMA? At the present stage of research, the functional counterpart of this anatomical connectivity can only be hypothesized. SI somatotopy would reflect the early cortical processing of spatial somatosensory information, whereas SII somatotopy would principally reflect sensorimotor and cognitive integration (Luppino et al., 1993). After early processing, SII and insular cortex would alert frontal systems (Mesulam and Mufson, 1982). The segregation of spatial somatosensory information within ACC and SMA would reflect a modular organization of the motor plans for body segments, able to optimize motor coordination and control. This might allow integration of the attentional enhancement of the stimuli, emotional coloring, and appropriate motor commands in order to respond to the source of stimulation. A possible anatomical substrate would be the presence of a separate and somatotopically organized streamline connecting primary motor cortex, SMA, and ACC (Morecraft and Van Hoesen, 1992). Unlike SI and SII, where a consistent activation associated with tactile stimulation was found in all subjects, SMA and ACC only show activity in some individuals. This finding suggests that, unlike SI and SII, SMA and ACC do not play an essential role in the extraction of information from sensory stimuli, but rather reflect individual differences occurring at a later stage of processing. Consistent with this interpretation, it is conceivable that, similar to the activity in the insula, activation in SMA and ACC be determined by the different saliency expressed by the same stimuli in different subjects, and reflect individual strategies aimed at manipulating the tactile stimulus or withdrawing from a source of pain. A brief methodological remark regarding the spatial resolution of our fMRI approach in the dissociation of activation loci in ACC and SMA is in order. Given the close position of the two areas, the classification of the activated areas based only on the Talairach coordinates should be considered cautiously. In fact, the anatomy of a single brain may deviate significantly from the Talairach brain making its normalization difficult. However, the present results seem to clearly disentangle the hand and foot representations within ACC and SMA. We classified the activation for each
individual subject by projecting statistical maps onto the structural brain image. This allowed a safe localization of the cortical activity in the surface of ACC when compared to SMA. Conclusion To our knowledge, this is the first demonstration of the idea of a somatotopic organization in both human ACC and SMA as revealed by nonpainful and painful stimulations. The hand and foot representations in ACC and SMA are separate for nonpainful as well as painful stimulation. This suggests a functional parietofrontal connectivity as a reasonable neural correlate of the ability to spatially locate nonpainful and painful stimuli and to promote motor coordination for both handling and immediate defence/ withdrawal behavior. Acknowledgments This work was partially supported by a grant from the Italian Ministry of Research to the Center of Excellence on Aging of the University of Chieti. References Akazawa, T., Tokuno, H., Nambu, A., Hamada, I., Ito, Y., Ikeuchi, Y., Imanishi, M., Hasegawa, N., Hatanaka, N., Takada, M., 2000. A cortical motor region that represents the cutaneous back muscles in the macaque monkey. Neurosci. Lett. 282 (3), 125–128. Allison, T., McCarthy, G., Luby, M., Puce, A., Spencer, D.D., 2006. Localization of functional regions of human mesial cortex by somatosensory evoked potential recording and by cortical stimulation. Electroencephalogr. Clin. Neurophysiol. 100 (2), 126–140 (Review). Beauchamp, M.S., Lee, K.E., Argall, B.D., Martin, A., 2004. Integration of auditory and visual information about objects in superior temporal sulcus. Neuron 41, 809–823. Bingel, U., Lorenz, J., Glauche, V., Knab, R., Glascher, J., Weiller, C., Bunchel, C., 2004. Somatotopic organization of human somatosensory cortices for pain: a single trial fMRI study. NeuroImage 23, 224–232. Boynton, G.M., Engel, S.A., Glover, G.H., Heeger, D.J., 1996. Linear systems analysis of functional magnetic resonance imaging in human V1. J. Neurosci. 16, 4207–4241. Bullmore, E., Brammer, M., Williams, S., Rabe-Hesketh, S., Janot, N., David, A., Mellers, J., Howard, R., Sham, P., 1996. Statistical methods of estimation and inference for functional MR image analysis. Magn. Reson. Med. 35, 261–277. Colebatch, J.G., Deiber, M.P., Passingham, R.E., Friston, K.J., Frackowiak, R.S., 1991. Regional cerebral blood flow during voluntary arm and hand movements in human subjects. J. Neurophysiol. 65 (6), 1392–1401. Cox, R.W., 1996. AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162–173. Debaere, F., Swinnen, S.P., Beatse, E., Sunaert, S., Van Hecke, P., Duysens, J., 2001. Brain areas involved in interlimb coordination: a distributed network. NeuroImage 14 (5), 947–958. Del Gratta, C., Della Penna, S., Tartaro, A., Ferretti, A., Torquati, K., Bonomo, L., Romani, G.L., Rossini, P.M., 2000. Topographic organization of the human primary and secondary somatosensory areas: an fMRI study. NeuroReport 11 (9), 2035–2043. Del Gratta, C., Della Penna, S., Ferretti, A., Franciotti, R., Pizzella, V., Tartaro, A., Torquati, K., Bonomo, L., Romani, G.L., Rossini, P.M., 2002. Topographic organization of the human primary and secondary somatosensory cortices: comparison of fMRI and MEG findings. NeuroImage 17, 1373–1383.
D. Arienzo et al. / NeuroImage 33 (2006) 700–705 Ferretti, A., Del Gratta, C., Babiloni, C., Caulo, M., Arienzo, D., Tartaro, A., Rossini, P.M., Romani, G.L., 2004. Functional topography of the secondary somatosensory cortex for non painful and painful stimulation of median and tibial nerve: an fMRI study. NeuroImage 23 (3), 1217–1225. Fink, G.R., Frackowiak, R.S., Pietrzyk, U., Passingham, R.E., 1997. Multiple nonprimary motor areas in the human cortex. J. Neurophysiol. 77 (4), 2164–2174. Fontaine, D., Capelle, L., Duffau, H., 2002. Somatotopy of the supplementary motor area: evidence from correlation of the extent of surgical resection with the clinical patterns of deficit. Neurosurgery 50 (2), 297–303. Forman, S.D., Cohen, J.D., Fitzgerald, M., Eddy, W.F., Mintun, M.A., Noll, D.C., 1995. Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn. Reson. Med. 33, 636–647. Fried, I., Katz, A., McCarthy, G., Sass, K.J., Williamson, P., Spencer, S.S., Spencer, D.D., 1991. Functional organization of human supplementary motor cortex studied by electrical stimulation. J. Neurosci. 11 (11), 3656–3666. Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.P., Frith, C.D., Frackowiak, R.S.J., 1995. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2, 173–181. Grafton, S.T., Woods, R.P., Mazziotta, J.C., 1993. Within-arm somatotopy in human motor areas determined by position emission tomography imaging of cerebral blood flow. Exp. Brain Res. 95 (1), 172–176. Hanakawa, T., Ikeda, A., Sadato, N., Okada, T., Fukuyama, H., Nagamine, T., Honda, M., Sawamoto, N., Yazawa, S., Kunieda, T., Ohara, S., Taki, W., Hashimoto, N., Yonekura, Y., Konishi, J., Shibasaki, H., 2001. Functional mapping of human medial frontal motor areas. The combined use of functional magnetic resonance imaging and cortical stimulation. Exp. Brain Res. 138 (4), 403–409. Indovina, I., Sanes, J.N., 2001. On somatotopic representation centers for finger movements in human primary motor cortex and supplementary motor area. NeuroImage 13 (6 Pt. 1), 1027–1034. Lim, S.H., Dinner, D.S., Pillay, P.K., Luders, H., Morris, H.H., Klem, G., Wyllie, E., Awad, I.A., 1994. Functional anatomy of the human supplementary sensorimotor area: results of extraoperative electrical stimulation. Electroencephalogr. Clin. Neurophysiol. 91 (3), 179–193. Lin, W., Kuppusamy, K., Haacke, E.M., Burton, H., 1996. Functional MRI in human somatosensory cortex activated by touching textured surfaces. J. Magn. Reson. Imaging 6 (4), 565–572. Luders, H.O., 1996. The supplementary sensorimotor area. An overview. Adv. Neurol. 70, 1–16 (Review). Luft, A.R., Smith, G.V., Forrester, L., Whitall, J., Macko, R.F., Hauser, T.K., Goldberg, A.P., Hanley, D.F., 2002. Comparing brain activation associated with isolated upper and lower limb movement across corresponding joints. Hum. Brain Mapp. 17 (2), 131–140. Luppino, G., Matelli, M., Camarda, R.M., Gallese, V., Rizzolatti, G., 1991. Multiple representations of body movements in mesial area 6 and the
705
adjacent cingulate cortex: an intracortical microstimulation study in the macaque monkey. J. Comp. Neurol. 311 (4), 463–482. Luppino, G., Matelli, M., Camarda, R., Rizzolatti, G., 1993. Corticocortical connections of area F3 (SMA-proper) and area F6 (pre-SMA) in the macaque monkey. J. Comp. Neurol. 338 (1), 114–140. Mayer, A.R., Zimbelman, J.L., Watanabe, Y., Rao, S.M., 2001. Somatotopic organization of the medial wall of the cerebral hemispheres: a 3 Tesla fMRI study. NeuroReport 12 (17), 3811–3814. Mesulam, M.M., Mufson, E.J., 1982. Insula of the old world monkey: III. Efferent cortical output and comments on function. J. Comp. Neurol. 212 (1), 38–52. Mitz, A.R., Wise, S.P., 1987. The somatotopic organization of the supplementary motor area: intracortical microstimulation mapping. J. Neurosci. 7 (4), 1010–1021. Morecraft, R.J., Van Hoesen, G.W., 1992. Cingulate input to the primary and supplementary motor cortices in the rhesus monkey: evidence for somatotopy in areas 24c and 23c. J. Comp. Neurol. 322 (4), 471–489. Oldfield, R.C., 1971. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113. Ploner, M., Schmitz, F., Freund, H.J., Schnitzler, A., 1999. Parallel activation of primary and secondary somatosensory cortices in human pain processing. J. Neurophysiol. 81 (6), 3100–3104. Polonara, G., Fabri, M., Manzoni, T., Salvolini, U., 1999. Localization of the first and second somatosensory areas in the human cerebral cortex with functional MR imaging. Am. J. Neuroradiol. 20 (2), 199–205. Rijntjes, M., Dettmers, C., Buchel, C., Kiebel, S., Frackowiak, R.S., Weiller, C., 1999. A blueprint for movement: functional and anatomical representations in the human motor system. J. Neurosci. 19 (18), 8043–8048. Romo, R., Ruiz, S., Crespo, P., Zainos, A., Merchant, H., 2003. Representation of tactile signals in primate supplementary motor area. J. Neurophysiol. 70 (6), 2690–2694. Ruben, J., Schwiemann, J., Deuchert, M., Meyer, R., Krause, T., Curio, G., Villringer, K., Kurth, R., Villringer, A., 2001. Somatotopic organization of human secondary somatosensory cortex. Cereb. Cortex 11, 463–473. Talairach, J., Tournoux, P., 1998. Co-planar Stereotaxic Atlas of the Human Brain. Thieme, New York. Treede, R.D., Apkarian, A.V., Bromm, B., Greenspan, J.D., Lenz, F.A., 2000. Cortical representation of pain: functional characterization of nociceptive areas near the lateral sulcus. Pain 87 (2), 113–119 (Review). Woolrich, M.W., Ripley, B.D., Brady, M., Smith, S.M., 2001. Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage 14, 1370–1386. Woolsey, C.N., Settlage, P.H., Meyer, D.R., Sencer, W., Pinto Hamuy, T., Travis, A.M., 1952. Patterns of localization in precentral and supplementary motor areas and their relation to the concept of a premotor area. Res. Publ.-Assoc. Res. Nerv. Ment. Dis. 30, 238–264. World Medical Association Declaration of Helsinki, 1997. Recommendations guiding physicians in biomedical research involving human subjects. J. Am. Med. Assoc. 277 (11), 925–926.