Transcranial magnetic stimulation (TMS) has been a powerful tool to understand the function of the motor cortex. It has been used to investigate its role in decision-making (Michelet et al., 2010), movement preparation (Soto et al., 2010) and, in a recent study by Gritsenko and colleagues in the Journal of Neuroscience, knowledge of limb dynamics (Gritsenko et al., 2011).
Knowledge of limb dynamics is essential for the control of reaching movements. Indeed, shoulder motion produces interaction torques at the elbow and movements of the elbow generate torques at the shoulder joint. This complex inter-segmental dynamics must clearly be taken into account during movement planning and execution in order to produce the typical straight paths that characterizes natural reaching movements (Hollerbach and Flash, 1982). The source of interaction torque compensation has been a matter of debate for years. Some argue that compensation takes place at the level of the spinal cord (Bizzi et al., 2000) whereas others argue for a more direct control of muscle activation mediated by the primary motor cortex (M1) (Todorov, 2000; Scott, 2004). Whether the descending motor commands accounts for inter-segmental dynamics remains a significant open question at the centre of spinal versus cortical control hypotheses.
From these interaction effects, Gritsenko and colleagues suggest that the correlation between M1 excitability (inferred from increased MEPs after normalization) and interaction torques reflects the integration of intersegmental dynamics in the descending motor commands. For the shoulder muscles, the MEP gain was well correlated with interaction torque at the shoulder joint but not with the level of co-contraction or total torque. Interestingly, a similar correlation was found between the MEP gain of the bi-articular muscles and interaction torque at the elbow but not for the monoarticular muscles. The modulation of the MEP gain with interaction torques was present both before and during the movements.
Most TMS studies that investigated modulation of MEPs during movement used single-joint motor tasks (e.g. MacKinnon and Rothwell, 2000). In those studies, the proportional relationship between EMG activity and MEP size was only broken around movement onset. The study by Gritsenko and colleagues demonstrates that such modest changes in cortical excitability observed during movement execution may be specific to single-joint movements. For multi-joint movements, the MEP gain clearly varied beyond movement onset. Interaction effects were observed from the start to the end of the movements, highlighting that M1 may be more involved for controlling complex arm dynamics. In addition, the presence of this modulation before the movement suggests that movement planning at the level of M1 incorporates knowledge of limb dynamics.
These results parallel recent findings on feedback responses to mechanical perturbations. Rapid motor responses are tuned to the actual underlying torque in as little as 50 ms relative to perturbation onset, which reflects the processing of multi-joint afferent feedback via an internal model of arm dynamics (Kurtzer et al., 2008). Single unit recordings in the monkey coupled with a TMS study recently demonstrated that M1 is causally involved in fine-tuning these fast corrective responses to the actual underlying torque (Pruszynski et al., 2011)(Pruszynski et al., 2011). Therefore, internal models in M1 appear as a general cortical function driving planning and execution of voluntary movements as well as rapid feedback corrections for mechanical perturbations.
The work of Gritsenko and colleagues raises some significant questions. First, these authors suggest that spanning the shoulder and elbow joints confers the biarticular muscles an advantageous anatomical situation to compensate for interaction torques. However, the preferred torque directions of both monoarticular and biarticular muscles systematically differ from their theoretical actions: monoarticular muscles show preference for multi-joint torques and biarticulars preferred in some cases parallel single joint torques (Kurtzer et al., 2006). Therefore, all upper limb muscles are potentially involved in the control of multi-joint dynamics and how the compensation for interaction torques is distributed across them is still unresolved.
Second, it is proposed that M1 excitability is not responsible for modulation of joints stiffness, which was inferred from co-contraction levels. Stiffness control is known to be a determinant strategy to stabilize motor control. However, there are many different factors that influence joint stiffness (Hasan, 1992)(Hasan, 1992), and modest changes in co-contraction have only a limited impact on (Pruszynski et al., 2009)stiffness (Pruszynski et al., 2009)(Pruszynski et al., 2009)(Pruszynski et al., 2009)(Pruszynski et al., 2009). The control process underlying stiffness control and its possible contribution in stabilizing interaction dynamics remains to be investigated.
Finally, it is known that other brain areas are important for the control of voluntary movements. For instance, cerebellar ataxia patients have a reduced ability to take interaction torques into account during movement planning (Bastian et al., 1996; Bastian et al., 2000; Cooper et al., 2000). Similarly, Parkinson Disease patients compensate for interaction torques differently than control subjects (Leiguarda et al., 2000; Seidler et al., 2001). Consistent with this study, hemiparetic stroke patients have trouble with inter-joint coordination as well (Beer et al., 2000). Therefore, although Gritsenko et al. focused on the primary motor cortex, the specific contribution of M1 and of other brain areas in shaping the descending motor command remains to be investigated.
In all, these results reflect that the nonlinear arm dynamics, often presented as a difficulty for experimental design or modeling studies, is actually a strong asset to address brain functions associated with motor planning and execution as well as feedback control.
Bastian AJ, Martin TA, Keating JG, Thach WT (1996) Cerebellar ataxia: abnormal control of interaction torques across multiple joints. J Neurophysiol 76:492-509.
Beer RF, Dewald JP, Rymer WZ (2000) Deficits in the coordination of multijoint arm movements in patients with hemiparesis: evidence for disturbed control of limb dynamics. Exp Brain Res 131:305-319.
Bizzi E, Tresch MC, Saltiel P, d'Avella A (2000) New perspectives on spinal motor systems. Nat Rev Neurosci 1:101-108.
Cooper SE, Martin JH, Ghez C (2000) Effects of inactivation of the anterior interpositus nucleus on the kinematic and dynamic control of multijoint movement [In Process Citation]. J Neurophysiol 84:1988-2000.
Gritsenko V, Kalaska JF, Cisek P (2011) Descending corticospinal control of intersegmental dynamics. J Neurosci 31:11968-11979.
Hasan Z (1992) IS STIFFNESS THE MAINSPRING OF POSTURE AND MOVEMENT. Behavioral and Brain Sciences 15:756-758.
Hollerbach MJ, Flash T (1982) Dynamic interactions between limb segments during planar arm movement. Biol Cybern 44:67-77.
Kurtzer I, Pruszynski JA, Herter TM, Scott SH (2006) Primate upper limb muscles exhibit activity patterns that differ from their anatomical action during a postural task. J Neurophysiol 95:493-504.
Kurtzer IL, Pruszynski JA, Scott SH (2008) Long-latency reflexes of the human arm reflect an internal model of limb dynamics. Curr Biol 18:449-453.
Leiguarda R, Merello M, Balej J, Starkstein S, Nogues M, Marsden CD (2000) Disruption of spatial organization and interjoint coordination in Parkinson's disease, progressive supranuclear palsy, and multiple system atrophy. Mov Disord 15:627-640.
MacKinnon CD, Rothwell JC (2000) Time-varying changes in corticospinal excitability accompanying the triphasic EMG pattern in humans. J Physiol 528:633-645.
Michelet T, Duncan GH, Cisek P (2010) Response competition in the primary motor cortex: corticospinal excitability reflects response replacement during simple decisions. J Neurophysiol 104:119-127.
Palmer E, Ashby P (1992) Evidence that a long latency stretch reflex in humans is transcortical. J Physiol 449:429-440.
Scott SH (2004) Optimal feedback control and the neural basis of volitional motor control. Nat Rev Neurosci 5:532-546.
Seidler RD, Alberts JL, Stelmach GE (2001) Multijoint movement control in Parkinson's disease. Exp Brain Res 140:335-344.
Soto O, Valls-Solé J, Kumru H (2010) Paired-pulse transcranial magnetic stimulation during preparation for simple and choice reaction time tasks. J Neurophysiol 104:1392-1400.
Todorov E (2000) Direct cortical control of muscle activation in voluntary arm movements: a model. Nat Neurosci 3:391-398.