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1Neuropediatric Research Unit, Department of Woman and Child Health, Karolinska Institutet, Stockholm, Sweden; and 2Wellcome Department of Imaging Neuroscience, Institute of Neurology, London, United Kingdom
Submitted 30 November 2006; accepted in final form 22 July 2006
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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; Westling and Johansson 1984). The stability of the grasp is threatened if the load force suddenly and unexpectedly increases, such as when a dog pulls its leash or when holding a basket into which someone unexpectedly puts a bottle of milk when shopping at the supermarket. During such "loading events," there is an unpredictable increase in the load force, which means that the frictional force becomes too low and a small slip, or microslip, occurs. This slip activates sensory receptors in the skin of the fingertips, which in turn results in an automatic increase in the grip force, with a latency of about 40–60 ms (Johansson and Westling 1988; Johansson et al. 1992a,b,c, 1994; Macefield and Johansson 2003; Macefield et al. 1996), which has been called a reactive or a catch-up response. This latency is longer than most spinal reflexes in intrinsic hand muscles (about 35 ms), which suggests that the reactive grip-force response is mediated by supraspinal centers.
One view is that the primary motor cortex (M1) is responsible for the generation of the grip-force response during loading. The main motivation for this hypothesis is that the latency of the grip-force response is similar to the "long-latency" reflexes that can be elicited by muscle stretch (Marsden et al. 1976; Matthews 1991) or electrical stimulation of the digital nerves (Evans et al. 1989; Garnett and Stephens 1980; Stephens et al. 1978), both of which are considered to involve the M1 (Matthews 1991; Palmer and Ashby 1992). However, unlike the long-latency muscle stretch reflexes, the reactive grip-force responses during loading depend mainly on cutaneous afferents from the fingertips (Johansson et al. 1992a,b,c; Macefield et al. 1996). Furthermore, it is possible that subcortical structures, the most likely of which is probably the cerebellum, could contribute to the reactive grip-force responses. The supposition is substantiated by the knowledge that tactile information from the upper limbs reaches the cerebellum through several different pathways (Bloedel and Courville 1981; Ito 1984) and that neurons in the cerebellar cortex of monkeys respond to load perturbations when performing a precision grip (Dugas and Smith 1992). Further, a human study using magnetoencephalography showed that the cerebellar responses to median nerve stimulation can precede the activity evoked in the primary sensorimotor cortex (Tesche and Karhu 2000). Thus although the exact neuronal mechanisms producing the reactive grip-force responses in the normal brain remain uncertain, both the M1 and the cerebellum are key candidates.
When we hold an object and the load force is unexpectedly reduced, there is an upward perturbation of the partially relieved hand (Hugon et al. 1982) and another type of grip-force response is triggered (an "unloading event"). During these unexpected decreases in load force, the grip force is reduced smoothly over a period of several hundred milliseconds, until the grip force once again matches the weight of the object and the surface friction (Johansson et al. 1992a,b,c). No rapid reactive "catch-up" response is observed. Although there is no risk of a slip occurring, the initial excessive force level is inappropriate because it potentially could cause muscle fatigue and physical damage to fragile objects, and thus it is reduced by the CNS. The primary mechanism responsible for the grip force the reduction in the grip force during unloading is not known, although the difference in the speed at which the grip responses are modulated during loading and unloading indicates that the underlying neural substrates are likely to differ.
The aim of the research reported here was to identify the neuronal correlates of the grip-force modulations associated with loading and unloading events. We scanned the brains of six healthy subjects using functional magnetic resonance imaging (fMRI). The participants held an instrumented test object (200 g) between the tips of right index finger and thumb (precision grip). Every so often, the weight of the object was suddenly increased or decreased by 90 g, with the interval between these changes being between 8 and 45 s to ensure that the changes were not anticipated. This perturbation elicited loading or unloading grip-force modulations. We analyzed the transient increases in the fMRI signal that were time-locked to these grip-force responses using statistical parametric mapping with an event-related design (Friston et al. 2004). We hypothesized that the primary motor cortex (Johansson et al. 1994; Picard and Smith 1992) and subcortical structures (Harrison et al. 2000), probably the cerebellum (Dugas and Smith 1992), would reflect the grip-force response during loading. In contrast, we predicted that activity in nonprimary sensory and motor areas would be associated with the unloading response because of the relatively slow time course of the force reduction.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Six right-handed healthy male subjects with no history of neurological disease participated in the study (20–32 yr of age). They were naive with respect to the specific purposes of the experiments. The participants had given their written consent and the Ethical Committee of the Karolinska Hospital had approved the study, which was performed in accordance with the guidelines of the Declaration of Helsinki 1975.
During the experiments the participants rested in a supine position in an MR scanner. A bite bar was used to restrict head movements. Each participant's arms were extended and oriented parallel to his trunk and supported from the elbow to the radial side of the hand. The subjects used their right hand to perform a radial flexion of the wrist to lift and hold a nonmagnetic object between the tips of the thumb and the index finger (Fig. 1). The object was lifted about 5 cm up from the support and was held still at that height. The object had vertical flat and parallel contact surfaces (spaced 30 mm apart; 35 x 35 mm) covered with sandpaper (grit: 180). The handle of the object was connected by a taut string to a receptacle located outside the MR scanner. Onto this receptacle, an extra weight of 90 g could easily be added and removed between trials by the experimenter. This weight was chosen because pilot experiments previously showed that it produced robust grip-force responses during loading but without any accidental slips of the object. This extra weight was attached to a string that was held by the experimenter. The weight of the object before adding the additional weight was 200 g. The object was equipped with optometric transducers that measured the mean forces normal to the contact surfaces (the grip force) and the sum of the vertical (load) forces. An optometric position sensor captured the lifting movement by measuring the position of the string. The participants were blindfolded throughout the experiments. They wore headphones to receive auditory instructions and to reduce the noise from the MR scanner.
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The participants lifted the object and held it still for 3 min and 15 s, and then put it down and released it. After a 45-s rest period, to avoid muscle fatigue, they repeated the lift for another 3 min and 15 s. The subjects were instructed not to apply an excessive grip force or to make any movements when holding the object. During the holding period, sudden changes in the weight of the object occurred, at random intervals of between 8 and 45 s, intended to eliminate any anticipatory grip-force responses and learning-related effects. Two different types of changes in the weight occurred (loading and unloading). During the loading trials the changes were performed by dropping the 90 g weight onto the receptacle (see Fig. 1). This extra weight was dropped from a height of about 2 cm. This generated a transient increase in the load force. In contrast, during the unloading events, the weight was lifted from the receptacle with a brisk movement, almost instantaneously reducing the load force. The experimenter, seated beside the end of the scanner bed, received computer-generated visual instructions that were projected onto the surface of the scanner about when to drop or raise the weight. Before the scanning, the subjects trained at lifting the object and were presented with loading and unloading stimuli.
Behavioral analysis
During the scanning, a data acquisition and analysis system (SC/ZOOM, Department of Physiology Section, IMB, University of Umeå, Sweden) was used to sample the signals from the force transducers and the position sensors. The SC/ZOOM system also recorded the time of acquisition of each MR image so that we knew the exact relative timing of the force and fMRI data. The force and position signals were displayed on-line and stored at 400 Hz with 14-bit resolution. All data were manually inspected and confirmed before further analysis. The timing of all load/unload events was registered and used in the analysis of the MR images (see following text). Each participant was asked to perform between 52 and 55 load events and between 50 and 54 unload events. We picked 10 load and 10 unload events at random per participant for detailed behavioral analysis. For each event, five measurements were made, as follows: 1) position change, reflecting the movement of the hand by measuring the maximum vertical change in fingertip position; 2) reaction onset, the latency between the onset of the event and the increase or decrease in the reactive grip force (defined as the maximum of the second derivate of the force data); 3) reaction peak, the latency between the onset of the event and the peak reactive grip force (there was no corresponding negative peak for the unloading events); 4) peak grip force increase/decrease, the amplitude of the difference between the grip force applied at the reaction peak and the grip force at the onset of the event; and 5) new steady state, the time taken to reach the new steady state measured as the time to have elapsed between the onset of the event and the point in time where the grip force had stopped changing and had settled to the appropriate level for the new load force. (This time point was defined as the first time that the force reached a value that was within ±2 SD of the baseline force.) The results are presented for each subject in Table 1. Values are presented as group mean ± SD unless otherwise stated. All differences between the load and the unload events were tested for their statistical significance. First we analyzed the data for the subjects individually (the asterisks show the level of significance), then mean values were compared across subjects; the latter are reported with the resulting P values.
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Functional MRI was conducted on a 1.5-T scanner (Signa Horizon Echospeed, General Electric Medical Systems, Milwaukee, WI) equipped with a head coil. We collected gradient-echo, echo-planar (EPI) T2*-weighted image volumes with blood oxygenation level–dependent (BOLD) contrast. The imaging parameters were: echo time (TE) = 50 ms; field of view (FOV) = 22 cm; matrix size = 64 x 64; pixel size = 3.4 x 3.4 mm; and flip angle = 90°. Twenty-four contiguous axial slices of 6 mm thickness were collected in each volume to cover the whole brain.
Functional-image volumes were collected in six separate runs. In each run, 110 volumes were acquired continuously, with one volume being collected every 5,000 ms (TR = 5.00 s). By jittering the grip-force events and the acquisition of the MRI scans, an effective temporal resolution of about 1 s was achieved. To allow for T1 equilibration effects, we started each experiment by recording four "dummy" volumes that were not stored. A total of 660 volumes were collected for each participant.
Data analysis and image processing
We used the Statistical Parametric Mapping software to process and analyze the images (SPM99; http//:www.fil.ion.ucl.ac.uk/spm; Wellcome Department of Cognitive Neurology, London, UK). The volumes were realigned, coregistered to each individual anatomical T1-weighted image (3D-SPGR), and normalized to the stereotactic coordinate system defined by Talaraich and Tournoux using the standard brain space of SPM99 and the Montreal Neurological Institute (MNI). Thus the coordinates used to report the location of the activations are all in MNI space. In all subjects, the estimated head movements were <3 mm, which is considered to be good and is not too great for the realignment process to deal with appropriately. The image volumes were subsequently spatially smoothed with an isotropic Gaussian filter of 10 mm full width at half-maximum (FWHM) and smoothed temporally with a Gaussian kernel of 4-s width to increase the signal-to-noise ratio and to satisfy the Gaussian assumptions made in SPM99. The data were modeled using the general linear model (GLM). We fitted a linear regression model (the GLM) to the data of all subjects together. For each subject, the static holding periods and the rest periods were modeled as boxcar functions and the loading and unloading responses were modeled as brief events. We time-locked these modeled events to the first change in load force during the perturbation trials and we used the standard SPM hemodynamic response function to filter the boxcar waveform that defined the different experimental conditions. The head movement parameters were entered in the GLM to remove, by regression, any residual head-movement–related activity that had not been compensated for by the realignment process described above (six parameters defining rigid body movement). Importantly, because the neural responses associated with the loading/unloading events are delayed by 6 s as a consequence of the hemodynamic response, whereas potential artifacts arising from head movement are not, the latter cannot influence our results. A high-pass filter (with cutoff at 100 s) was used to remove low-frequency drift and fluctuations in the signal. Proportional scaling was applied to compensate for global changes in the signal.
Because we had only six subjects, we used conjunction analysis to identify areas that are consistently activated across subjects (Friston 1999a, 2005). By estimating the task-specific effects using linear contrasts in the GLM for each subject, we created statistical images [i.e., statistical parametric maps (SPMs)] with a t-distribution (SPM|t|) that we transformed, subsequently, to the Z-distribution (SPM|Z|). For the conjunction analyses, the SPM|t| resulting from the six contrasts obtained for each of the six subjects are combined to generate a new SPM|tmin| that describes the minimum t-value detected in the contrasts. The minimum t-statistic can be related to the population prevalence of individuals showing activation (Friston et al. 1999a). We used the threshold of P < 0.05 (corrected), which corresponds to a prevalence of 60% (i.e., 60% of the population will be expected to show activation). This approach is similar to a random-effects analysis in the sense that the results are generalized to the general population (Friston et al. 1999a, 2005; Nichols 2005). We used the threshold P < 0.05 after a correction of the number of multiple comparisons in the whole brain volume (false discovery rate correction in SPM99). In the contralateral primary motor cortex, the ipsilateral cerebellum (both discussed in the INTRODUCTION) and the cingulate and the supplementary motor areas (as discussed by Cadoret and Smith 1997), where we had an a priori hypothesis that there would be activation during loading, we used a small volume correction (a sphere with a 15-mm radius) and a threshold of P < 0.05, corrected, taking the coordinates from a previous study (Ehrsson et al. 2000b).
Our experimental design, with a sparse presentation of events, was optimized to detect neuronal responses evoked by the loading and unloading events relative to the baseline (Friston et al. 1999b), although this design is inefficient when it comes to making a direct contrast between the perturbations events. Thus in this paper, the main analysis consists of the contrasts identifying activity associated with the loading and unloading events compared with the baseline, respectively, and for this we use the threshold of P < 0.05, corrected. The contrasts between the loading and unloading events represent a supplementary analysis for which we used the threshold of P < 0.001, uncorrected. This analysis was restricted to areas that were significantly active (i.e., P < 0.05, corrected) during the loading/unloading events.
Finally, in previous precision grip studies we pooled all data across subjects and performed a fixed-effects analysis (Ehrsson et al. 2000a, 2001; Kuhtz-Buschbeck et al. 2001); we also ran this type of analysis on the present data to enable comparisons to be made. All the areas in the results presented here were significantly activated when we performed the fixed-effects analysis (P < 0.05, corrected using the whole brain as the search space).
The anatomical localization of the activation was related to the major sulci and gyri (Duvernoy 1991) distinguishable in a mean standardized anatomical MRI obtained from the six subjects.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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The results of the analysis of the force and position data from all subjects are summarized in Table 1. Load reactions were characterized by a grip-force peak (1.40 ± 0.60 N; mean ± SD across subjects) at 0.27 ± 0.11 s (Fig. 2A). The earliest onset of the grip-force response was observed after 0.08 ± 0.02 s. This is in agreement with similar studies (Johansson and Westling 1988). The load impact perturbed the hand position slightly downward (–5 ± 2 mm). The grip force slowly settled to a new steady-state level that was appropriate for the new load, some 1.42 ± 0.57 s after the load impact.
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Brain activation
NEURAL RESPONSES ASSOCIATED WITH LOADING. We first searched for areas associated with loading events. In the cortex these were associated with significant activation of the left primary motor cortex and primary somatosensory cortex (with the peak being in the anterior bank of the central sulcus), the left dorsal premotor cortex (PMD), and the left cingulate motor area. Subcortically, we found activity in the right lateral cerebellum and the medial cerebellum (vermis) (P < 0.05, corrected; see Table 2 and Fig. 3).
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NEURAL RESPONSES ASSOCIATED WITH UNLOADING. Next we examined the areas that were active during the unloading events (Table 3 and Fig. 4). Significant cortical activation (P < 0.05, corrected) was observed in the left supplementary motor area, the left cingulate motor area, the left pre-SMA, the bilateral superior temporal cortex, and the medial wall of the left posterior parietal cortex (the precuneus and SSA). Subcortically, activity was detected in the left ventral lateral thalamus and the medial cerebellum (vermis). No activity was observed in the primary motor cortex, the primary somatosensory cortex, or in the ventral posterolateral thalamic nucleus during the unloading events, even when we lowered the statistical threshold (P > 0.001, uncorrected).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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A potential confounder in the present study relates to changes in attention associated with the unpredictable sensorimotor events. Previous fMRI studies showed that areas in the prefrontal, posterior parietal, and temporal cortex are active in conjunction with unpredictable changes in sensory stimulation, even when these stimuli do not elicit a motor response (Downar et al. 2000). Thus it is possible that the activations we found in the superior temporal cortex, the anterior cingulate cortex, the pre-SMA, and the precuneus could be accounted for by "reflexive" shifts in attention to the hand during the unloading events. However, such attention-related processes could probably not explain the activation of the genuine motor areas that were found to be active (e.g., M1, the cerebellum, and posterior sections of the SMA and PMD). Furthermore, the activations in M1 and the SSA were found when we made direct comparisons between the activation associated with loading and unloading and, because these events were equally unexpected, the attentional factors could be expected to be matched.
In the present experiments the loading and unloading events were, respectively, achieved by dropping or rapidly lifting a weight onto or off a platform. This results in more rapid changes in the load force in the loading condition. However, these differences in the rate of the force change are probably insufficient to explain the characteristic force responses associated with loading and unloading or the qualitative differences in neural responses observed in the primary sensorimotor cortex and the SSA. The risk of dropping the object is present only when loading, thereby explaining why, in this case, the central control system responds with a rapid increase in the grip force. When decreasing the load, the response can be understood only as the elimination of excessive grip forces and thereby minimizing energy consumption (see INTRODUCTION).
Loading
An important question is whether the grip-force responses occurring during loading are mediated by the primary motor cortex or by subcortical structures, of which the cerebellum is the foremost candidate. Our findings are consistent with either of these scenarios, but provide the strongest evidence in favor of the involvement of M1 because increases in M1 activity were observed only during loading. This is a finding that associates the M1 activity closely with the sensorimotor processes involved in the generation of the loading grip-force response.
We know from single-cell recordings that many cells in M1 are highly sensitive to tangential force perturbations (Picard and Smith 1992). Many of these cells have cutaneous receptive fields on the hand and respond in a reflexive-like manner to the perturbations, which suggests that the output from these cells mediates the grip-force responses (Picard and Strick 2003). Thus it is likely that the fMRI activation observed here corresponds to M1 cells involved in generating grip-force responses based on cutaneous inputs. The BOLD signal is generally considered to reflect the overall synaptic activity in an area (Logothetis et al. 2001). Thus the present M1 activation corresponds to synaptic input to interneurons and corticospinal neurons in a large population of M1 cells. Although fMRI activity cannot be equated with activation of the corticospinal tract, its engagement is likely because a previous transcranial magnetic resonance stimulation study reported enhancement of the motor cortical excitability during reactive grip-force responses to loading perturbations (Johansson et al. 1994). The corticospinal neurons are the most critical for mediating the grip-forces responses because they are monosynaptically connected to motor neurons in the ventral horn of the spinal cord, which in turn innervate the muscles of the fingers and hand (Lemon 1993).
The loading grip-force response critically depends on afferent tactile inputs from the fingertips (Johansson and Westling 1988; Johansson et al. 1992a,b,c; Picard and Smith 1992). The neuronal populations in M1 receive both tactile inputs from the skin of the fingertips and kinesthetic inputs from the finger muscles. These afferent signals are conveyed by cortico-cortical projections from S1 (Darian-Smith et al. 1993; Jones 1984; Jones et al. 1978; Stepniewska et al. 1993) and directly by connections from the spinal cord by the ventral posterolateral nucleus of the thalamus (Darian-Smith and Darian-Smith 1993; Jones 1984; Stepniewska et al. 1994). Thus the fact that we found significant activity in the S1 and M1 (area 3b; P < 0.05, corrected), in conjunction with weak activity in the ventral posterolateral thalamus (P = 0.008, uncorrected; see RESULTS), is consistent with both thalamocortical afferents and cortico-cortical transmission of tactile information from S1 to M1. We suggest that the M1 activation found in the present study could reflect an "M1 long loop reflex," which produces a grip-force response during loading perturbations based on tactile inputs. Having made this suggestion, it should be stated that we cannot exclude the possibility that the M1 activation reflects the kinesthetic sensations associated with the loading events (Naito et al. 1999, 2002), rather than the sensorimotor transformations that are directly responsible for the force response. Thus the most reasonable interpretation of the present M1 activation is that it reflects both the processing of afferent cutaneous inputs and activity related to producing reactive grip forces.
The cerebellum is considered to be an important subcortical candidate for reactive grip-force control. We found two active cerebellar foci when we analyzed the fMRI data time-locked with the loading responses. One of these was located in the right (ipsilateral) anterior cerebellar hemisphere. This part of the cerebellum receives inputs from the primary motor cortex and the premotor areas by the pons (Brodal 1979, 1980; Glickstein et al. 1985; Middleton and Strick 2000; Schmahmann and Pandya 1997). In turn, it influences the cortical motor output by its connections back to the motor cortex by the contralateral ventrolateral thalamus (Holsapple et al. 1991; Middleton and Strick 2000; Zemanick et al. 1991). In this way, the lateral cerebellum can play a supplementary role by fine-tuning the motor commands being formed in M1 in direct response to the perturbation. Weaker activity was found in the ventrolateral thalamus and pons during the loading trials (P < 0.008, uncorrected; see RESULTS), supporting this interpretation. The lateral cerebellar activity may also reflect the neural control of the exactly timed sequence of agonist and antagonist activation of the finger and hand muscles after the loading perturbation (Vilis and Hore 1977). There are also pathways from the cerebellar hemisphere to the spinal motor networks by connections through the interposed nuclei and the red nucleus (Asanuma et al. 1983; Courville 1966; Kennedy et al. 1986), although these structures are probably too small to be detected using our scanning protocol (no activity was observed) and therefore the involvement of this pathway is uncertain.
The second cerebellar focus was located in the medial cerebellum (vermis). This part of the cerebellum receives prominent somatosensory inputs from the spinal cord by several direct and indirect pathways and has the capacity to control movements by directly influencing the spinal networks by connections through the fastigial nucleus and the lateral vestibular nuclei (Carleton and Carpenter 1983; Ruggiero et al. 1977). In addition to this, the vermis can influence the M1 by connections through the ventrolateral thalamus (Holsapple et al. 1991; Schmahmann and Pandya 1997). Thus the finding that the medial cerebellum was active in the present study, both during loading and unloading, is consistent with the view that this structure could be involved in the mediation of changes in grip forces as a consequence of changes in the sensory feedback from the fingertips.
We also observed increased activity in the nonprimary motor areas associated with the loading perturbations. Prominent activations were located in the cingulate sulcus, in the CMA near the border between this area and the SMA. A focus of activity was also observed in the left PMD. In macaque monkeys holding an object with a precision grip, "reflexive-like" excitation of neurons in the hand sections of ventral cingulate motor area and the SMA was evoked when the object was subjected to forceful perturbations (Cadoret and Smith 1997). However, these authors also indicated that the number of cells in these areas receiving cutaneous inputs was substantially lower than that in the M1 (Picard and Smith 1992), suggesting that these areas are less implicated in the modulation of the grip force based on cutaneous feedback. In addition to this, it is known that fewer cells in the SMA and CMA (Cadoret and Smith 1997) respond to force perturbations than in the M1 (Picard and Smith 1992). Thus although these nonprimary motor areas are activated during changes in the load when performing a precision grip, their relative importance for the mediation of the fast reactive grip-force response during loading remains somewhat uncertain.
Unloading
The unloading response is characterized by the absence of a rapid reflexive-like grip-force modulation and a slower reduction in the grip force. There was a conspicuous lack of M1 activation (even when using a very liberal threshold of P < 0.05, uncorrected; as can be seen in Fig. 5). Thus the grip-force attenuation during unloading does not seem to be associated with significant increases in synaptic activity in the M1. Of course, negative findings in functional imaging studies should be interpreted with caution because fMRI is less sensitive than direct neuronal recordings (Logothesis et al. 2001). In the present experiments the unloading responses were relatively weak because the additional weight was quite light (only 90 g). Experiments conducted in the future should investigate removal of larger weights. However, our results do suggest that the nonprimary sensorimotor areas, including the SSA, are more important than the primary sensorimotor cortices for the control of the unloading response. A previous study reported activation of the M1 during voluntary relaxation of a contracted muscle (Toma et al. 1999). Major differences between this study and the present unloading responses are that the muscle relaxations were voluntary and involved proprioceptive muscle sensations. In contrast, the unloading events are automatic and the participants do not perceive any changes in the muscular force exhibited.
Unloading-related responses were observed in the medial wall motor areas (SMA, CMA), the medial posterior parietal cortex (precuneus and SSA), and the medial cerebellum (vermis). The strongest response was observed in the SMA and CMA, which are nonprimary motor areas. Because the CMA was also active during the loading response (P < 0.05, corrected) and the SMA showed a statistical trend for activation (P < 0.001, uncorrected), we propose that these phenomena reflect the change in the force output rather than the grip-force reduction per se. Thus the active neuronal populations in the CMA and SMA could be involved in processing information about the change in fingertip forces in the context of holding an object. This interpretation is consistent with an earlier study that showed that the activity on the medial wall of the frontal lobes (SMA) increases both during the initiation of muscle contraction and during the subsequent relaxation of the muscle (Toma et al. 1999).
An interesting observation was activation in the SSA that occurred only during unloading. This suggests that the SSA participates in the reduction in the grip force during unloading, although the exact mechanism remains uncertain. The SSA is considered to be a higher-order somatosensory area (Roland 1993; Seitz et al. 1991). In the monkey brain it is located in the posterior part of the cingulate sulcus and has a distinct somatosensory representation (Murray and Coulter 1981a,b). It is anatomically connected with sensorimotor areas, most notably the SMA, CMA, PMd, areas 4, 3, 1, and 2, the superior parietal cortex (area 5), and the secondary somatosensory cortex (Morecraft et al. 2004). Thus this area has the capacity both to analyze somatosensory information and to send this information to the frontal motor areas, including the M1. It is not likely that the SSA response reflected afferent tactile input because the tactile input was greater when the mass was dropped in the loading event. Furthermore, it is not likely to correspond to a somatic representation of the object weight or a change in the forcefulness of the grip because, in that case, it would have been expected that the SSA would also have been activated during the loading events. Rather, our interpretation is based on the fact that one key feature of the unloading event is the inappropriately high grip force. The grip force is greater than required to avoid slip—that is, the slip margin is excessive. It is economic for the CNS to have a mechanism to adjust such excessive grip forces. Thus it is possible that the SSA activity reflects the somatic analysis of the excessive grip-load force ratio. This information could then be conveyed to other sensorimotor areas, supporting the reduction in the force output until the grip-load force ratio has been normalized. What may speak against this interpretation is that the loading responses include excessive grip forces after the initial increase in the reactive grip force, but no activation was seen in the SSA in association with this type of perturbation.
It could be argued that all that is needed to produce the grip-force responses seen during loading and unloading is a natural tendency to decrease the force over time, coupled with reactive grip-force increases triggered by microslips. However, this model cannot fully explain the normal stability of the grasp as seen when humans hold an object statically above a support surface. According to the simple model outlined above, one would expect cycles of reductions in the grip forces, coupled with reactive loading responses, and this certainly does not always occur. For example, in our data, such cyclical changes in force were not seen. In fact, the stability of the human grasp indicates that the brain contains central representations of the fingertip forces and the weight of the object and has access to information about the slip force.
In summary, our results reveal the neural correlates of loading and unloading grip-force responses. Earlier human studies described the active cortical networks associated with fingertip force control in various precision grip tasks when subjects voluntarily apply forces (Ehrsson et al. 2000a, 2001, 2003; Kinoshita et al. 2000; Kuhtz-Buschbeck et al. 2001; Schmitz et al. 2005). The study reported on here is the first to identify the neural correlates of automatic force adjustments to external perturbations. The loading and unloading responses are two important control mechanisms that are used by the CNS to maintain grasp stability. Thus the present findings contribute to our understanding of the neural substrates of manual dexterity in humans.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: H. H. Ehrsson, Institute of Neurology, Functional Imaging Laboratory, Wellcome Department of Imaging Neuroscience, 12 Queen Square, London WC1N 3BG, UK (E-mail: H.Ehrsson{at}fil.ion.ucl.ac.uk)
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Bloedel J, Courville J. A Review of Cerebellar Afferent Systems. Bethesda, MD: Am. Physiol. Soc., 1981.
Brodal P. The pontocerebellar projection in the rhesus monkey: an experimental study with retrograde axonal transport of horseradish peroxidase. Neuroscience 4: 193–208, 1979.[CrossRef][ISI][Medline]
Brodal P. The cortical projection to the nucleus reticularis tegmenti pontis in the rhesus monkey. Exp Brain Res 38: 19–27, 1980.[ISI][Medline]
Cadoret G, Smith AM. Comparison of the neuronal activity in the SMA and the ventral cingulate cortex during prehension in the monkey. J Neurophysiol 77: 153–166, 1997.
Carleton SC, Carpenter MB. Afferent and efferent connections of the medial, inferior and lateral vestibular nuclei in the cat and monkey. Brain Res 278: 29–51, 1983.[CrossRef][ISI][Medline]
Courville J. Somatotopical organization of the projection from the nucleus interpositus anterior of the cerebellum to the red nucleus. An experimental study in the cat with silver impregnation methods. Exp Brain Res 2: 191–215, 1966.[ISI][Medline]
Darian-Smith C, Darian-Smith I. Thalamic projections to areas 3a, 3b, and 4 in the sensorimotor cortex of the mature and infant macaque monkey. J Comp Neurol 335: 173–199, 1993.[CrossRef][ISI][Medline]
Darian-Smith C, Darian-Smith I, Burman K, Ratcliffe N. Ipsilateral cortical projections to areas 3a, 3b, and 4 in the macaque monkey. J Comp Neurol 335: 200–213, 1993.[CrossRef][ISI][Medline]
Downar J, Crawley AP, Mikulis DJ, Davis KD. A multimodal cortical network for the detection of changes in the sensory environment. Nat Neurosci 3: 277–283, 2000.[CrossRef][ISI][Medline]
Dugas C, Smith AM. Responses of cerebellar Purkinje cells to slip of a hand-held object. J Neurophysiol 67: 483–495, 1992.
Duvernoy HM. The Human Brain: Surface, Blood Supply, and Three-Dimensional Sectional Anatomy. New York: Springer-Verlag, 1991.
Ehrsson HH, Fagergren A, Johansson RS, Forssberg H. Evidence for the involvement of the posterior parietal cortex in coordination of fingertip forces for grasp stability in manipulation. J Neurophysiol 90: 2978–2986, 2003.
Ehrsson HH, Fagergren A, Jonsson T, Westling G, Johansson RS, Forssberg H. Cortical activity in precision- versus power-grip tasks: an fMRI study. J Neurophysiol 83: 528–536, 2000a.
Ehrsson HH, Fagergren E, Forssberg H. Differential fronto-parietal activation depending on force used in a precision grip task: an fMRI study. J Neurophysiol 85: 2613–2623, 2001.
Ehrsson HH, Naito E, Geyer S, Amunts K, Zilles K, Forssberg H, Roland PE. Simultaneous movements of upper and lower limbs are coordinated by motor representations that are shared by both limbs: a PET study. Eur J Neurosci 12: 3385–3398, 2000b.[CrossRef][ISI][Medline]
Evans AL, Harrison LM, Stephens JA. Task-dependent changes in cutaneous reflexes recorded from various muscles controlling finger movement in man. J Physiol 418: 1–12, 1989.
Friston K, Ashburner J, Penny W, Kiebel S, Holmes A, Poline JB, Kherif F, Glaser JB, Henson R, Mechelli A, Turner R, Price C, Brett M, Worsley K, Nichols T, Buchüel C, Harrison L. Part two: imaging neuroscience—theory and analysis. In: Human Brain Function, edited by Frackowiak RS, Friston K, Frith CD, Dolan RJ, Price CJ, Zeki S, Ashburner J, Penny W. San Diego, CA: Elsevier/Academic Press, 2004, p. 599–968.
Friston KJ, Zarahn E, Josephs O, Henson RN, Dale AM. How many subjects constitute a study? Neuroimage 10: 1–5, 1999a.[CrossRef][ISI][Medline]
Friston KJ, Zarahn E, Josephs O, Henson RN, Dale AM. Stochastic designs in event-related fMRI. Neuroimage 10: 607–619, 1999b.[CrossRef][ISI][Medline]
Friston KJ, Zarahn E, Josephs O, Henson RN, Dale AM. Conjunction revisited. Neuroimage 25: 661–667, 2005.[CrossRef][ISI][Medline]
Garnett R, Stephens JA. The reflex responses of single motor units in human first dorsal interosseous muscle following cutaneous afferent stimulation. J Physiol 303: 351–364, 1980.
Glickstein M, May JG 3rd, Mercier BE. Corticopontine projection in the macaque: the distribution of labelled cortical cells after large injections of horseradish peroxidase in the pontine nuclei. J Comp Neurol 235: 343–359, 1985.[CrossRef][ISI][Medline]
Harrison LM, Mayston MJ, Johansson RS. Reactive control of precision grip does not depend on fast transcortical reflex pathways in X-linked Kallmann subjects. J Physiol 527: 641–652, 2000.
Holsapple JW, Preston JB, Strick PL. The origin of thalamic inputs to the "hand" representation in the primary motor cortex. J Neurosci 11: 2644–2654, 1991.[Abstract]
Hugon M, Massion J, Wiesendanger M. Anticipatory postural changes induced by active unloading and comparison with passive unloading in man. Pfluegers Arch 393: 292–296, 1982.[CrossRef][ISI][Medline]
Ito M. The Cerebellum and Neural Control. New York: Raven, 1984.
Johansson RS, Hager C, Backstrom L. Somatosensory control of precision grip during unpredictable pulling loads. III. Impairments during digital anesthesia. Exp Brain Res 89: 204–213, 1992b.[CrossRef][ISI][Medline]
Johansson RS, Hager C, Riso R. Somatosensory control of precision grip during unpredictable pulling loads. II. Changes in load force rate. Exp Brain Res 89: 192–203, 1992a.[ISI][Medline]
Johansson RS, Lemon RN, Westling G. Time-varying enhancement of human cortical excitability mediated by cutaneous inputs during precision grip. J Physiol 481: 761–775, 1994.[ISI][Medline]
Johansson RS, Riso R, Hager C, Backstrom L. Somatosensory control of precision grip during unpredictable pulling loads. I. Changes in load force amplitude. Exp Brain Res 89: 181–191, 1992c.[CrossRef][ISI][Medline]
Johansson RS, Westling G. Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Exp Brain Res 56: 550–564, 1984.[ISI][Medline]
Johansson RS, Westling G. Programmed and triggered actions to rapid load changes during precision grip. Exp Brain Res 71: 72–86, 1988.[ISI][Medline]
Jones EG. Connectivity of the primate sensory-motor cortex. In: Sensory-Motor Areas and Aspects of Cortical Connectivity, edited by Jones EG, Peters A. New York: Plenum Press, 1984, p. 113–174.
Jones EG, Coulter JD, Hendry SH. Intracortical connectivity of architectonic fields in the somatic sensory, motor and parietal cortex of monkeys. J Comp Neurol 181: 291–347, 1978.[CrossRef][ISI][Medline]
Kennedy PR, Gibson AR, Houk JC. Functional and anatomic differentiation between parvicellular and magnocellular regions of red nucleus in the monkey. Brain Res 364: 124–136, 1986.[CrossRef][ISI][Medline]
Kinoshita H, Oku N, Hashikawa K, Nishimura T. Functional brain areas used for the lifting of objects using a precision grip: a PET study. Brain Res 857: 119–130, 2000.[CrossRef][ISI][Medline]
Kuhtz-Buschbeck JP, Ehrsson HH, Forssberg H. Human brain activity in the control of fine static precision grip forces: an fMRI study. Eur J Neurosci 14: 382–390, 2001.[CrossRef][ISI][Medline]
Lemon RN. The G. L. Brown Prize lecture: cortical control of the primate hand. Exp Physiol 78: 263–301, 1993.[ISI][Medline]
Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature 412: 150–157, 2001.[CrossRef][Medline]
Macefield VG, Hager-Ross C, Johansson RS. Control of grip force during restraint of an object held between finger and thumb: responses of cutaneous afferents from the digits. Exp Brain Res 108: 155–171, 1996.[ISI][Medline]
Macefield VG, Johansson RS. Loads applied tangential to a fingertip during an object restraint task can trigger short-latency as well as long-latency EMG responses in hand muscles. Exp Brain Res 152: 143–149, 2003.[CrossRef][ISI][Medline]
Marsden CD, Merton PA, Morton HB. Stretch reflex and servo action in a variety of human muscles. J Physiol 259: 531–560, 1976.
Matthews PB. The human stretch reflex and the motor cortex. Trends Neurosci 14: 87–91, 1991.[CrossRef][ISI][Medline]
Middleton FA, Strick PL. Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Res Brain Res Rev 31: 236–250, 2000.[CrossRef][Medline]
Morecraft RJ, Cipolloni PB, Stilwell-Morecraft KS, Gedney MT, Pandya DN. Cytoarchitecture and cortical connections of the posterior cingulate and adjacent somatosensory fields in the rhesus monkey. J Comp Neurol 469: 37–69, 2004.[CrossRef][ISI][Medline]
Murray EA, Coulter JD. Organization of corticospinal neurons in the monkey. J Comp Neurol 195: 339–365, 1981a.[CrossRef][ISI][Medline]
Murray EA, Coulter JD. Supplementary sensory area. The medial parietal cortex in monkey. In: Cortical Sensory Organization. Multiple Somatic Sensory Areas, edited by Woolsey CN. Clifton, NJ: Humana Press, 1981b, vol. 1, p. 167–195.
Naito E, Ehrsson HH, Geyer S, Zilles K, Roland PE. Illusory arm movements activate cortical motor areas: a PET study. J Neurosci 19: 6134–6144, 1999.
Naito E, Roland PE, Ehrsson HH. I feel my hand moving: a new role of the primary motor cortex in somatic perception of limb movement. Neuron 36: 979–988, 2002.[CrossRef][ISI][Medline]
Palmer E, Ashby P. Evidence that a long latency stretch reflex in humans is transcortical. J Physiol 449: 429–444, 1992.
Picard N, Smith AM. Primary motor cortical responses to perturbations of prehension in the monkey. J Neurophysiol 68: 1882–1894, 1992.
