Biomedical subjects

Emilio Bizzi

Publications and source records attributed to Emilio Bizzi.

12 recordsLinked to original sources

PubMed2006

Disruption of primary motor cortex before learning impairs memory of movement dynamics.

Although multiple lines of evidence implicate the primary motor cortex (M1) in motor learning, the precise role of M1 in the adaptation to novel movement dynamics and in the subsequent consolidation of a memory of those dynamics remains unclear. Here we used repetitive transcranial magnetic stimulation (rTMS) to dissociate the contribution of M1 to these distinct aspects of motor learning. Subjects performed reaching movements in velocity-dependent force fields over three epochs: a null-field baseline epoch, a clockwise-field learning epoch (15 min after the baseline epoch), and a clockwise-field retest epoch (24 h after the learning epoch). Half of the subjects received 15 min of 1 Hz rTMS to M1 between the baseline and learning epochs. Subjects given rTMS performed identically to control subjects during the learning epoch. However, control subjects performed with significantly less error than rTMS subjects in the retest epoch on the following day. These results suggest that M1 is not critical to the network supporting motor adaptation per se but that, within this network, M1 may be important for initiating the development of long-term motor memories.

Adaptation, Physiological↗

PubMed2006

Intermittent practice facilitates stable motor memories.

Humans adaptively control reaching movements to maintain good performance in the presence of novel forces acting on the arm. A recent study suggested that motor memories of different force conditions are not transformed from fragile to stable states, but rather are always vulnerable to interference from newly learned conditions (Caithness et al., 2004). This is contrary to the results of previous studies (Brashers-Krug et al., 1996; Shadmehr and Brashers-Krug, 1997), although all of these studies followed similar methods. Here, we show that a seemingly insignificant and inconsistently applied methodological detail may reconcile this discrepancy. Catch trials, in which the novel forces are removed, may be randomly interspersed among the more frequent force trials to assess how a subject is learning to predict the pattern of forces. In the absence of an interfering condition, subjects retained their learning until retest a day later regardless of whether they experienced catch trials. But in the presence of an interfering condition, only the subjects who had experienced forces intermittently retained their learning and thereby showed resistance to the interference. Thus, intermittent rather than constant practice conditions appear to be critical for dynamic motor memory stabilization.

Adaptation, Physiological↗

PubMed2005

Neuronal correlates of movement dynamics in the dorsal and ventral premotor area in the monkey.

We investigated how neurons in the different motor areas of the frontal lobe reflect the movement dynamics, and how their neuronal activity undergoes plastic changes when monkeys adapt to perturbing forces (they learn new dynamics). Here we describe the results obtained in the dorsal premotor area (PMd) and ventral premotor area (PMv). Monkeys performed visually instructed, delayed reaching movements before, during and after exposure and adaptation to a viscous, curl force field. During movement planning (i.e., during an instructed delay that followed the cue and preceded the go signal), we found dynamics-related activity in PMd but not in PMv. A closer analysis revealed that the population of PMd reflected the dynamics of the upcoming movement increasingly over the course of the delay, starting from a kinematics-related signal. During movement execution, dynamics-related activity was present in both PMd and PMv. In this respect, the results for PMd were similar to that previously found for the supplementary motor area (SMA) whereas the results for PMv were more similar to that previously found for the primary motor cortex (M1). Plastic changes associated with the acquisition of new dynamics found in PMd and PMv were qualitatively similar to those previously observed in M1 and SMA. The ensemble of our experiments suggest a broader picture of the cortical control of movements, whereby multiple areas all contribute to the various sensorimotor processes, including "low" computations such as the movement dynamics, but also express a degree of specialization.

Action Potentials↗

PubMed2005

Central and sensory contributions to the activation and organization of muscle synergies during natural motor behaviors.

Previous studies have suggested that the motor system may simplify control by combining a small number of muscle synergies represented as activation profiles across a set of muscles. The role of sensory feedback in the activation and organization of synergies has remained an open question. Here, we assess to what extent the motor system relies on centrally organized synergies activated by spinal and/or supraspinal commands to generate motor outputs by analyzing electromyographic (EMG) signals collected from 13 hindlimb muscles of the bullfrog during swimming and jumping, before and after deafferentation. We first established that, for both behaviors, the intact and deafferented data sets possess low and similar dimensionalities. Subsequently, we used a novel reformulation of the non-negative matrix factorization algorithm to simultaneously search for synergies shared by, and synergies specific to, the intact and deafferented data sets. Most muscle synergies were identified as shared synergies, suggesting that EMGs of locomotor behaviors are generated primarily by centrally organized synergies. Both the amplitude and temporal patterns of the activation coefficients of most shared synergies, however, were altered by deafferentation, suggesting that sensory inflow modulates activation of those centrally organized synergies. For most synergies, effects of deafferentation on the activation coefficients were not consistent across frogs, indicating substantial interanimal variability of feedback actions. We speculate that sensory feedback might adapt recruitment of muscle synergies to behavioral constraints, and the few synergies specific to the intact or deafferented states might represent afferent-specific modules or feedback reorganization of spinal neuronal networks.

Afferent Pathways↗

PubMed2005

Localization and connectivity in spinal interneuronal networks: the adduction-caudal extension-flexion rhythm in the frog.

We have previously reported that focal intraspinal N-methyl-d-aspartate (NMDA) iontophoresis in the frog elicits a motor output, which is organized in terms of its constituent isometric force directions at the ipsilateral ankle and its topography. Furthermore, the associated EMG patterns can be reconstructed as the linear combinations of seven muscle synergies, labeled A to G. We now focus on one of the most common NMDA-elicited outputs, the adduction-caudal extension-flexion rhythm, and examine the relationship between the different force phases in terms of synergies and topography. Two distinct EMG patterns produce caudal extensions, and only one of the two patterns is used at most sites. The key synergy combinations for the two patterns are B + e and D + c (strongest synergies capitalized). These two patterns map at distinct locations in the lumbar cord. Within individual sites rhythms, we find linkages among the synergies used to produce adductions, the onsets of flexions after caudal extensions, and the synergy pattern producing the caudal extensions. For example, the synergy composition of adductions at B + e caudal extension sites is dominated by E + b and at D + c caudal extension sites by C + d. The two types of adductions map at distinct locations, situated between the two caudal extension regions. Specifically the linked patterns of caudal extension-adduction interleave rostrocaudally in a CE2-ADD1-ADD2-CE1 sequence, where 1 and 2 refer to the two pattern types. The implications of this topography and connectivity with respect to motor systems organization and behaviors are discussed.

Analysis of Variance↗

PubMed2005

Intrinsic musculoskeletal properties stabilize wiping movements in the spinalized frog.

The mechanical stability properties of hindlimb-hindlimb wiping movements of the spinalized frog were examined. One hindlimb, the wiping limb, was implanted with 12 electromyographic (EMG) electrodes and attached to a robot that both recorded its trajectory and applied brief force perturbations. Cutaneous electrical stimulation was applied to the other hindlimb, the target limb, to evoke the hindlimb-hindlimb wiping reflex. Kinematic and EMG data from both unperturbed trials and trials in which a phasic perturbation was applied were collected from each spinalized frog. In the perturbed behaviors, we found that the initially large displacement attributable to the perturbation was compensated such that the final position was statistically indistinguishable from the unperturbed final position in all of the frogs, thus indicating the dynamic stability of these movements. This stability was robust to the range of perturbation amplitudes and nominal kinematic variation observed in this study. In addition, we investigated the extent to which intrinsic viscoelastic properties of the limb and proprioceptive feedback play a role in stabilizing the movements. No significant changes were seen in the EMGs after the perturbation. Furthermore, deafferentation of the wiping limb did not significantly affect the stability of the wiping reflex. Thus, we found that the intrinsic viscoelastic properties of the hindlimb conferred robust stability properties to the hindlimb-hindlimb wiping behavior. This stability mechanism may simplify the control required by the frog spinal motor systems to produce successful movements in an unpredictable and varying environment.

Animals↗

PubMed2005

Shared and specific muscle synergies in natural motor behaviors.

Selecting the appropriate muscle pattern to achieve a given goal is an extremely complex task because of the dimensionality of the search space and because of the nonlinear and dynamical nature of the transformation between muscle activity and movement. To investigate whether the central nervous system uses a modular architecture to achieve motor coordination we characterized the motor output over a large set of movements. We recorded electromyographic activity from 13 muscles of the hind limb of intact and freely moving frogs during jumping, swimming, and walking in naturalistic conditions. We used multidimensional factorization techniques to extract invariant amplitude and timing relationships among the muscle activations. A decomposition of the instantaneous muscle activations as combinations of nonnegative vectors, synchronous muscle synergies, revealed a spatial organization in the muscle patterns. A decomposition of the same activations as a combination of temporal sequences of nonnegative vectors, time-varying muscle synergies, further uncovered specific characteristics in the muscle activation waveforms. A mixture of synergies shared across behaviors and synergies for specific behaviors captured the invariances across the entire dataset. These results support the hypothesis that the motor controller has a modular organization.

Animals↗

PubMed2004

Generalization in vision and motor control.

Learning is more than memory. It is not simply the building of a look-up table of labelled images, or a phone-directory-like list of motor acts and the corresponding sequences of muscle activation. Central to learning and intelligence is the ability to predict, that is, to generalize to new situations, beyond the memory of specific examples. The key to generalization, in turn, is the architecture of the system, more than the rules of synaptic plasticity. We propose a specific architecture for generalization for both the motor and the visual systems, and argue for a canonical microcircuit underlying visual and motor learning.

Animals↗

PubMed2003

Neuronal activity in the supplementary motor area of monkeys adapting to a new dynamic environment.

To execute visually guided reaching movements, the central nervous system (CNS) must transform a desired hand trajectory (kinematics) into appropriate muscle-related commands (dynamics). It has been suggested that the CNS might face this challenging computation by using internal forward models for the dynamics. Previous work in humans found that new internal models can be acquired through experience. In a series of studies in monkeys, we investigated how neurons in the motor areas of the frontal lobe reflect the movement dynamics and how their activity changes when monkeys learn a new internal model. Here we describe the results for the supplementary motor area (SMA-proper, or SMA). In the experiments, monkeys executed visually guided reaching movements and adapted to an external perturbing force field. The experimental design allowed dissociating the neuronal activity related to movement dynamics from that related to movement kinematics. It also allowed dissociating the changes related to motor learning from the activity related to motor performance (kinematics and dynamics). We show that neurons in SMA reflect the movement dynamics individually and as a population, and that their activity undergoes a variety of plastic changes when monkeys adapt to a new dynamic environment.

Action Potentials↗

PubMed2003

Combinations of muscle synergies in the construction of a natural motor behavior.

A central issue in motor control is how the central nervous system generates the muscle activity patterns necessary to achieve a variety of behavioral goals. The many degrees of freedom of the musculoskeletal apparatus provide great flexibility but make the control problem extremely complex. Muscle synergies--coherent activations, in space or time, of a group of muscles--have been proposed as building blocks that could simplify the construction of motor behaviors. To evaluate this hypothesis, we developed a new method to extract invariant spatiotemporal components from the simultaneous recordings of the activity of many muscles. We used this technique to analyze the muscle patterns of intact and unrestrained frogs during kicking, a natural defensive behavior. Here we show that combinations of three time-varying muscle synergies underlie the variety of muscle patterns required to kick in different directions, that the recruitment of these synergies is related to movement kinematics, and that there are similarities among the synergies extracted from different behaviors.

Animals↗

PubMed2002

Neuronal correlates of kinematics-to-dynamics transformation in the supplementary motor area.

It is widely acknowledged that movements are planned at the level of the kinematics. However, the central nervous system must ultimately transform kinematic plans into dynamics-related commands. How, when, and where the kinematics-to-dynamics (KD) transformation is processed represent fundamental and unanswered questions. We recorded from the supplementary motor area (SMA) of two monkeys as they executed visually instructed reaching movements. We specifically analyzed a delay period following the instruction but prior to the go signal (motor planning). During the delay, a group of neurons in the SMA progressively came to reflect the dynamics rather than the desired kinematics of the upcoming movement. This finding suggests that some neurons in the SMA participate in the KD transformation.

Action Potentials↗

PubMed2002

Coordination and localization in spinal motor systems.

We review here experiments examining the hypothesis that vertebrate spinal motor systems produce movement through the flexible combination of a small number of units of motor output. Using a variety of preparations and techniques, these experiments provide evidence for such spinally generated units and for the localization of the networks responsible for producing them within different regions of the spinal cord. Such an organization might help to simplify the production of movement, reducing the degrees of freedom that need to be specified by providing a set of units involved in regulating features common to a range of behaviors.

Animals↗