Marc H. Schieber

Partial Inactivation of the Primary Motor Cortex Hand Area: Effects on Individuated Finger Movements

After large lesions of the primary motor cortex (M1), voluntary movements of affected body parts are weak and slow. In addition, the relative independence of moving one body part without others is lost; attempts at individuated movements of a given body part are accompanied by excessive, unintended motion of contiguous body parts. The effects of partial inactivation of the M1 hand area are comparatively unknown, however. If the M1 hand area contains the somatotopically ordered finger representations implied by the classic homunculus or simiusculus, then partial inactivation might produce weakness, slowness, and loss of independence of one or two adjacent digits without affecting other digits. But if control of each finger movement is distributed in the M1 hand area as many studies suggest, then partial inactivation might produce dissociation of weakness, slowness, and relative independence of movement, and which fingers movements are impaired might be unrelated to the location of the inactivation along the central sulcus. To investigate the motoric deficits resulting from partial inactivation of the M1 hand area, we therefore made single intracortical injections of muscimol as trained monkeys performed visually cued, individuated flexion–extension movements of the fingers and wrist. We found little if any evidence that which finger movements were impaired after each injection was related to the injection location along the central sulcus. Unimpaired fingers could be flanked on both sides by impaired fingers, and the flexion movements of a given finger could be unaffected even though the extension movements were impaired, or vice versa. Partial inactivation also could produce dissociated weakness and slowness versus loss of independence in a given finger movement. These findings suggest that control of each individuated finger movement is distributed widely in the M1 hand area.

How might the motor cortex individuate movements

The ability to individuate movements--that is, the ability to move one or more body parts independently of the movement or posture of other contiguous body parts--imparts an increasing flexibility to the motor repertoire of higher mammals. The movements used in walking, grasping, or eating contrast greatly with the phylogenetically more recent movements of the same body parts used, respectively, in dancing, playing a musical instrument, or talking. The movements used in the latter functions depend critically on the primary motor cortex (area 4). With advances in our understanding of the output organization of the motor cortex (reviewed recently by Roger Lemon), which have been based largely on studies of the hand area in primates, we can now consider more fully certain problems inherent in moving body parts individually, and some ways in which the motor cortex might accomplish this feat.

Definition and Classification of Negative Motor Signs in Childhood

In this report we describe the outcome of a consensus meeting that occurred at the National Institutes of Health in Bethesda, Maryland, March 12 through 14, 2005. The meeting brought together 39 specialists from multiple clinical and research disciplines including developmental pediatrics, neurology, neurosurgery, orthopedic surgery, physical therapy, occupational therapy, physical medicine and rehabilitation, neurophysiology, muscle physiology, motor control, and biomechanics. The purpose of the meeting was to establish terminology and definitions for 4 aspects of motor disorders that occur in children: weakness, reduced selective motor control, ataxia, and deficits of praxis. The purpose of the definitions is to assist communication between clinicians, select homogeneous groups of children for clinical research trials, facilitate the development of rating scales to assess improvement or deterioration with time, and eventually to better match individual children with specific therapies. “Weakness” is defined as the inability to generate normal voluntary force in a muscle or normal voluntary torque about a joint. “Reduced selective motor control” is defined as the impaired ability to isolate the activation of muscles in a selected pattern in response to demands of a voluntary posture or movement. “Ataxia” is defined as an inability to generate a normal or expected voluntary movement trajectory that cannot be attributed to weakness or involuntary muscle activity about the affected joints. “Apraxia” is defined as an impairment in the ability to accomplish previously learned and performed complex motor actions that is not explained by ataxia, reduced selective motor control, weakness, or involuntary motor activity. “Developmental dyspraxia” is defined as a failure to have ever acquired the ability to perform age-appropriate complex motor actions that is not explained by the presence of inadequate demonstration or practice, ataxia, reduced selective motor control, weakness, or involuntary motor activity.

Somatotopic gradients in the distributed organization of the human primary motor cortex hand area : evidence from small infarcts

Abstract Nine cases of relatively selective hand weakness produced by stroke were analyzed to examine the degree to which representations of different fingers are segregated in the human primary motor cortex (M1). In five cases, all the digits were involved uniformly; in four cases the radial versus ulnar digits of the hand were involved differentially. No patient showed discrete involvement of a single digit, nor did any patient have greatest weakness in the index, middle or ring finger. These findings provide little evidence that each digit is represented in a separate cortical territory, but rather suggest that broadly overlapping gradients – with the radial digits somewhat more heavily represented laterally and the ulnar digits somewhat more heavily represented medially – are superimposed on an underlying organization in which control of each finger is distributed widely throughout the human M1 hand area.

Orderly Somatotopy in Primary Motor Cortex: Does It Exist?

In the current issue of NeuroImage and an upcoming issue of Cerebral Cortex appear data relevant to a fundamental question about the functional organization of the primary motor cortex (M1) of primates (Beisteiner et al., 2001; Hlustik et al., 2001; Indovina and Sanes, 2001), that is, does there exist an orderly somatotopy in M1 and, by extension, in other major motor areas of the brain. A fundamental finding of these papers provides support for separation between representations for finger and hand movement that adheres to a somatotopic organization. The new findings extend previous reports of somatotopically ordered representations for voluntary movements of various joints of the human upper extremity, fingers, wrist, elbow, and shoulder (Grafton et al., 1993; Kleinchmidt et al., 1997; Lotze et al., 2000), but conflict with thers (Rao et al., 1995; Sanes et al., 1995). However, as others and we have noted, the degree of somatotopic representation within the upper extremity representation appears rather limited (Schieber, 1999; Sanes and Donoghue, 2000). Clearly the major body parts—lower limb (hindlimb), upper limb (forelimb), and head—have functional and largely independent subdivisions to represent the muscles and movements controlled by the respective parts of M1. These functional subdivisions of M1 are commonly laid out along the cortical surface of primates with the lower (hind) limb most medial, the head most lateral, and the upper (fore) limb in between; they have acquired the designation of “areas,” such as the “M1 arm area,” though the term “representation” might provide a more suitable functional name. No serious challenge has emerged for this basic large-scale organization pattern in M1, but

Asynchronous Decoding of Dexterous Finger Movements Using M1 Neurons

Previous efforts in brain-machine interfaces (BMI) have looked at decoding movement intent or hand and arm trajectory, but current cortical control strategies have not focused on the decoding of 3 actions such as finger movements. The present work demonstrates the asynchronous decoding (i.e., where cues indicating the onset of movement are not known) of individual and combined finger movements. Single-unit activities were recorded sequentially from a population of neurons in the M1 hand area of trained rhesus monkeys during flexion and extension movements of each finger and the wrist. Nonlinear filters were designed to detect the onset of movement and decode the movement type from randomly selected neuronal ensembles (assembled from individually recorded single-unit activities). Average asynchronous decoding accuracies as high as 99.8%, 96.2%, and 90.5%, were achieved for individuated finger and wrist movements with three monkeys. Average decoding accuracy was still 92.5% when combined movements of two fingers were included. These results demonstrate that it is possible to asynchronously decode dexterous finger movements from a neuronal ensemble with high accuracy. This work takes an important step towards the development of a BMI for direct neural control of a state-of-the-art, multifingered hand prosthesis.

Bilateral Spike-Triggered Average Effects in Arm and Shoulder Muscles from the Monkey Pontomedullary Reticular Formation

Pontomedullary reticular formation (PMRF) neurons (309) were recorded simultaneously with electromyographic activity from arm and shoulder muscles in four monkeys performing arm-reaching tasks. Spike-triggered averages (SpikeTAs) were compiled for 292 neurons (3836 neuron–muscle pairs). Fourteen PMRF neurons located in a region ventral to the abducens nucleus produced 42 significant SpikeTA effects in arm and shoulder muscles. Of these 14 PMRF neurons, nine produced SpikeTA effects bilaterally. Overall, PMRF neurons facilitated ipsilateral flexors and contralateral extensors, while suppressing ipsilateral extensors and contralateral flexors. Spike- and stimulus-triggered averaging effects obtained from the same recording site were similar. These findings indicate that single PMRF neurons can directly influence movements of both upper limbs.

Neural Coding of Finger and Wrist Movements

Previous work (Schieber and Hibbard, 1993) has shown that single motor cortical neurons do not discharge specifically for a particular flexion-extension finger movement but instead are active with movements of different fingers. In addition, neuronal populations active with movements of different fingers overlap extensively in their spatial locations in the motor cortex. These data suggested that control of any finger movement utilizes a distributed population of neurons. In this study we applied the neuronal population vector analysis (Georgopoulos et al., 1983) to these same data to determine (1) whether single cells are tuned in an abstract, three-dimensional (3D) instructed finger and wrist movement space with hand-like geometry and (2) whether the neuronal population encodes specific finger movements. We found that the activity of 132/176 (75%) motor cortical neurons related to finger movements was indeed tuned in this space. Moreover, the population vector computed in this space predicted well the instructed finger movement. Thus, although single neurons may be related to several disparate finger movements, and neurons related to different finger movements are intermingled throughout the hand area of the motor cortex, the neuronal population activity does specify particular finger movements.

Decoding Individuated Finger Movements Using Volume-Constrained Neuronal Ensembles in the M1 Hand Area

Individuated finger and wrist movements can be decoded using random subpopulations of neurons that are widely distributed in the primary motor (M1) hand area. This work investigates 1) whether it is possible to decode dexterous finger movements using spatially-constrained volumes of neurons as typically recorded from a microelectrode array; and 2) whether decoding accuracy differs due to the configuration or location of the array within the M1 hand area. Single-unit activities were sequentially recorded from task-related neurons in two rhesus monkeys as they performed individuated movements of the fingers and the wrist. Simultaneous neuronal ensembles were simulated by constraining these activities to the recording field dimensions of conventional microelectrode array architectures. Artificial neural network (ANN) based filters were able to decode individuated finger movements with greater than 90% accuracy for the majority of movement types, using as few as 20 neurons from these ensemble activities. Furthermore, for the large majority of cases there were no significant differences (p < 0.01) in decoding accuracy as a function of the location of the recording volume. The results suggest that a brain-machine interface (BMI) for dexterous control of individuated fingers and the wrist can be implemented using microelectrode arrays placed broadly in the M1 hand area.

Primary motor cortex reorganization in a long-term monkey amputee

The primary motor cortex (M1) was mapped with intracortical microstimulation (ICMS) in a 15 year-old macaque whose right upper extremity was amputated at the shoulder joint prior to 2 years of age. Movements of the right shoulder girdle and stump were evoked by ICMS throughout the left M1 upper extremity region. The size of the left M1 upper extremity region contralateral to the amputated arm was not appreciably different from the size of the right upper extremity region contralateral to the intact arm. Long stimulus trains and/or higher stimulus currents were needed to evoke detectable movements at significantly more loci in the left than in the right M1 upper extremity region. These observations would be consistent with unmasking of a high threshold representation of shoulder musculature that normally exists throughout the central core of the upper extremity region, where it underlies a lower threshold representation of the distal forelimb. Alternatively, invasion of the de-efferented distal forelimb core by surrounding shoulder representation may have occurred. Differences between the limited M1 reorganization observed in the present study and the more extensive reorganization of S1 observed in other studies may reflect fundamental differences between M1 and S1, and/or differences in the extent of de-efferentation versus deafferentation.