Neuronal activity in somatosensory cortex of monkeys using a precision grip. I. Receptive fields and discharge patterns

Relationships between balance performance and connectivity of motor cortex with primary somatosensory cortex and cerebellum in middle aged and older adults

Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.

Neural Correlates of Impaired Grasp Function in Children with Unilateral Spastic Cerebral Palsy

Unilateral spastic cerebral palsy (USCP) is caused by damage to the developing brain and affects motor function, mainly lateralized to one side of the body. Children with USCP have difficulties grasping objects, which can affect their ability to perform daily activities. Although cerebral palsy is typically classified according to motor function, sensory abnormalities are often present as well and may contribute to motor impairments, including grasping. In this review, we show that the integrity and connectivity pattern of the corticospinal tract (CST) is related to execution and anticipatory control of grasping. However, as this may not explain all the variance of impairments in grasping function, we also describe the potential roles of sensory and sensorimotor integration deficits that contribute to grasp impairments. We highlight studies measuring fingertip forces during object manipulation tasks, as this approach allows for the dissection of the close association of sensory and motor function and can detect the discriminant use of sensory information during a complex, functional task (i.e., grasping). In addition, we discuss the importance of examining the interactions of the sensory and motor systems together, rather than in isolation. Finally, we suggest future directions for research to understand the underlying mechanisms of grasp impairments.

Dynamic peripheral nerve stimulation can produce cortical activation similar to punctate mechanical stimuli

During contact, phasic and tonic responses provide feedback that is used for task performance and perceptual processes. These disparate temporal dynamics are carried in peripheral nerves, and produce overlapping signals in cortex. Using longitudinal intrafascicular electrodes inserted into the median nerve of a nonhuman primate, we delivered composite stimulation consisting of onset and release bursts to capture rapidly adapting responses and sustained stochastic stimulation to capture the ongoing response of slowly adapting receptors. To measure the stimulation's effectiveness in producing natural responses, we monitored the local field potential in somatosensory cortex. We compared the cortical responses to peripheral nerve stimulation and vibrotactile/punctate stimulation of the fingertip, with particular focus on gamma band (30-65 Hz) responses. We found that vibrotactile stimulation produces consistently phase locked gamma throughout the duration of the stimulation. By contrast, punctate stimulation responses were phase locked at the onset and release of stimulation, but activity maintained through the stimulation was not phase locked. Using these responses as guideposts for assessing the response to the peripheral nerve stimulation, we found that constant frequency stimulation produced continual phase locking, whereas composite stimulation produced gamma enhancement throughout the stimulus, phase locked only at the onset and release of the stimulus. We describe this response as an "Appropriate Response in the gamma band" (ARγ), a trend seen in other sensory systems. Our demonstration is the first shown for intracortical somatosensory local field potentials. We argue that this stimulation paradigm produces a more biomimetic response in somatosensory cortex and is more likely to produce naturalistic sensations for readily usable neuroprosthetic feedback.

Functional characterization of the fronto-parietal reaching and grasping network: reversible deactivation of M1 and areas 2, 5, and 7b in awake behaving monkeys

In the present investigation, we examined the role of different cortical fields in the fronto-parietal reaching and grasping network in awake, behaving macaque monkeys. This network is greatly expanded in primates compared to other mammals and coevolved with glabrous hands with opposable thumbs and the extraordinary dexterous behaviors employed by a number of primates, including humans. To examine this, we reversibly deactivated the primary motor area (M1), anterior parietal area 2, and posterior parietal areas 5L and 7b individually while monkeys were performing two types of reaching and grasping tasks. Reversible deactivation was accomplished with small microfluidic thermal regulators abutting specifically targeted cortical areas. Placement of these devices in the different cortical fields was confirmed post hoc in histologically processed tissue. Our results indicate that the different areas examined form a complex network of motor control that is overlapping. However, several consistent themes emerged that suggest the independent roles that motor cortex, area 2, area 7b, and area 5L play in the motor planning and execution of reaching and grasping movements. Area 5L is involved in the early stages and area 7b the later stages of a reaching and grasping movement, motor cortex is involved in all aspects of the execution of the movement, and area 2 provides proprioceptive feedback throughout the movement. We discuss our results in the context of previous studies that explored the fronto-parietal network, the overlapping (but also independent) functions of different nodes of this network, and the rapid compensatory plasticity of this network.NEW & NOTEWORTHY This is the first study to directly compare the results of cooling different portions of the fronto-parietal reaching and grasping network (motor cortex, anterior and posterior parietal cortex) in the same animals and the first to employ a complex, bimanual reaching and grasping task that is ethologically relevant. Whereas cooling area 7b or area 5L evoked deficits at distinct task phases, cooling M1 evoked a general set of deficits and cooling area 2 evoked proprioceptive deficits.

The Interactions Between Primary Somatosensory and Motor Cortex during Human Grasping Behaviors

Afferent inputs to the primary somatosensory cortex (S1) are differentially processed during precision and power grip in humans. However, it remains unclear how S1 interacts with the primary motor cortex (M1) during these two grasping behaviors. To address this question, we measured short-latency afferent inhibition (SAI), reflecting S1-M1 interactions via thalamo-cortical pathways, using paired-pulse transcranial magnetic stimulation (TMS) during precision and power grip. The TMS coil over the hand representation of M1 was oriented in the posterior-anterior (PA) and anterior-posterior (AP) direction to activate distinct sets of corticospinal neurons. We found that SAI increased during precision compared with power grip when AP, but not PA, currents were applied. Notably, SAI tested in the AP direction were similar during two-digit than five-digit precision grip. The M1 receives movement information from S1 through direct cortico-cortical pathways, so intra-hemispheric S1-M1 interactions using dual-site TMS were also evaluated. Stimulation of S1 attenuated M1 excitability (S1-M1 inhibition) during precision and power grip, while the S1-M1 inhibition ratio remained similar across tasks. Taken together,our findings suggest that distinct neural mechanisms for S1-M1 interactions mediate precision and power grip, presumably by modulating neural activity along thalamo-cortical pathways.

Anisotropic Psychophysical Trends in the Discrimination of Tactile Direction in a Precision Grip

Tactile cues arising from interactions with objects have a sense of directionality which affects grasp. Low latency responses to varied grip perturbations indicate that grasp safety margins are exaggerated in certain directions and conditions. In a grip with the ulnar-radial axis vertical, evidence suggests that distal and downward directions are more sensitive to task parameters and have larger safety margins. This suggests that, for the purpose of applying forces with the fingers, reference frames with respect to the hand and gravity are both in operation. In this experiment, we examined human sensitivities to the direction of tactile movement in the context of precision grip in orientations either orthogonal to or parallel to gravity. Subjects performed a two-alternative-forced-choice task involving a textured cube which moved orthogonal to their grip axis. Subjects' arms were placed in a brace that allowed for finger movement but minimized arm movement. Movement of thumb and index joints were monitored via PhaseSpace motion capture. The subject was presented with a textured cube and instructed to lightly grasp the cube, as if it were slipping. In each trial the object was first translated 1 cm in 0° (proximal), 90° (radial), 180° (distal), or 270° (ulnar) and returned to its origin. This primary stimulus was immediately followed by a 10 mm secondary stimulus at a random 5° interval between -30° and 30° of the primary stimulus. Response from the subject after each pair of stimuli indicated whether the test direction felt the same as or different from the primary stimulus. Traditional bias and sensitivity analyses did not provide conclusive results but suggested that performance is best in the ulnar-radial axis regardless of gravity. Modeling of the response curve generated a detection threshold for each primary stimulus. Lower thresholds, indicating improved detection, persisted in the ulnar-radial axis. Anisotropic thresholds of increased detection appear to coincide with digit displacement and appear to be independent of the grasp orientation.

Neural Coding of Contact Events in Somatosensory Cortex

Manual interactions with objects require precise and rapid feedback about contact events. These tactile signals are integrated with motor plans throughout the neuraxis to achieve dexterous object manipulation. To better understand the role of somatosensory cortex in interactions with objects, we measured, using chronically implanted arrays of electrodes, the responses of populations of somatosensory neurons to skin indentations designed to simulate the initiation, maintenance, and termination of contact with an object. First, we find that the responses of somatosensory neurons to contact onset and offset dwarf their responses to maintenance of contact. Second, we show that these responses rapidly and reliably encode features of the simulated contact events-their timing, location, and strength-and can account for the animals' performance in an amplitude discrimination task. Third, we demonstrate that the spatiotemporal dynamics of the population response in cortex mirror those of the population response in the nerves. We conclude that the responses of populations of somatosensory neurons are well suited to encode contact transients and are consistent with a role of somatosensory cortex in signaling transitions between task subgoals.

Primate somatosensory cortical neurons are entrained to both spontaneous and peripherally evoked spindle oscillations

Recurrent thalamocortical circuits produce a number of rhythms critical to brain function. In slow-wave sleep, spindles (7-16 Hz) are a prominent spontaneous oscillation generated by thalamic circuits and triggered by cortical slow waves. In wakefulness and under anesthesia, brief peripheral sensory stimuli can evoke 10-Hz reverberations due potentially to similar thalamic mechanisms. Functionally, sleep spindles and peripherally evoked spindles may play a role in memory consolidation and perception, respectively. Yet, rarely have the circuits involved in these two rhythms been compared in the same animals and never in primates. Here, we investigated the entrainment of primary somatosensory cortex (S1) neurons to both rhythms in ketamine-sedated macaques. First, we compared spontaneous spindles in sedation and natural sleep to validate the model. Then, we quantified entrainment with spike-field coherence and phase-locking statistics. We found that S1 neurons entrained to spontaneous sleep spindles were also entrained to the evoked spindles, although entrainment strength and phase systematically differed. Our results indicate that the spindle oscillations triggered by top-down spontaneous cortical activity and bottom-up peripheral input share a common cortical substrate.NEW & NOTEWORTHY Brief sensory stimuli evoke 10-Hz oscillations in thalamocortical neuronal activity and in perceptual thresholds. The mechanisms underlying this evoked rhythm are not well understood but are thought to be similar to those generating sleep spindles. We directly compared the entrainment of cortical neurons to both spontaneous spindles and peripherally evoked oscillations in sedated monkeys. We found that the entrainment strengths to each rhythm were positively correlated, although with differing entrainment phases, implying involvement of similar networks.

Neural Basis of Touch and Proprioception in Primate Cortex

The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex. © 2018 American Physiological Society. Compr Physiol 8:1575-1602, 2018.

Differential neural encoding of sensorimotor and visual body representations

Sensorimotor processing specifically impacts mental body representations. In particular, deteriorated somatosensory input (as after complete spinal cord injury) increases the relative weight of visual aspects of body parts’ representations, leading to aberrancies in how images of body parts are mentally manipulated (e.g. mental rotation). This suggests that a sensorimotor or visual reference frame, respectively, can be relatively dominant in local (hands) versus global (full-body) bodily representations. On this basis, we hypothesized that the recruitment of a specific reference frame could be reflected in the activation of sensorimotor versus visual brain networks. To this aim, we directly compared the brain activity associated with mental rotation of hands versus full-bodies. Mental rotation of hands recruited more strongly the supplementary motor area, premotor cortex, and secondary somatosensory cortex. Conversely, mental rotation of full-bodies determined stronger activity in temporo-occipital regions, including the functionally-localized extrastriate body area. These results support that (1) sensorimotor and visual frames of reference are used to represent the body, (2) two distinct brain networks encode local or global bodily representations, and (3) the extrastriate body area is a multimodal region involved in body processing both at the perceptual and representational level.

Correlation of fingertip shear force direction with somatosensory cortical activity in monkey

To examine the activity of somatosensory cortex (S1) neurons to self-generated shear forces on the index and thumb, two monkeys were trained to grasp a stationary metal tab with a key grip and exert forces without the fingers slipping in one of four orthogonal directions for 1 s. A majority (∼85%) of slowly adapting and rapidly adapting (RA) S1 neurons had activity modulated with shear force direction. The cells were recorded mainly in areas 1 and 2 of the S1, although some area 3b neurons also responded to shear direction or magnitude. The preferred shear vectors were distributed in every direction, with tuning arcs varying from 50° to 170°. Some RA neurons sensitive to dynamic shear force direction also responded to static shear force but within a narrower range, suggesting that the direction of the shear force may influence the adaptation rate. Other neurons were modulated with shear forces in diametrically opposite directions. The directional sensitivity of S1 cortical neurons is consistent with recordings from cutaneous afferents showing that shear direction, even without slip, is a powerful stimulus to S1 neurons.

Neuronal activity in somatosensory cortex related to tactile exploration

The very light contact forces (∼0.60 N) applied by the fingertips during tactile exploration reveal a clearly optimized sensorimotor strategy. To investigate the cortical mechanisms involved with this behavior, we recorded 230 neurons in the somatosensory cortex (S1), as two monkeys scanned different surfaces with the fingertips in search of a tactile target without visual feedback. During the exploration, the monkeys, like humans, carefully controlled the finger forces. High-friction surfaces offering greater tangential shear force resistance to the skin were associated with decreased normal contact forces. The activity of one group of neurons was modulated with either the normal or tangential force, with little or no influence from the orthogonal force component. A second group responded to kinetic friction or the ratio of tangential to normal forces rather than responding to a specific parameter, such as force magnitude or direction. A third group of S1 neurons appeared to respond to particular vectors of normal and tangential force on the skin. Although 45 neurons correlated with scanning speed, 32 were also modulated by finger forces, suggesting that forces on the finger should be considered as the primary parameter encoding the skin compliance and that finger speed is a secondary parameter that co-varies with finger forces. Neurons (102) were also tested with different textures, and the activity of 62 of these increased or decreased in relation to the surface friction.

Spinal premotor interneurons mediate dynamic and static motor commands for precision grip in monkeys

The extent of spinal interneuron (IN) contribution to dexterous hand movements is unclear. Here, we studied the response patterns and force relationships of spinal premotor INs (PreM-INs) in three awake, behaving monkeys performing a precision grip task. We recorded activity from the cervical spinal cord (C5-T1) simultaneously with electromyographic (EMG) activity from hand and arm muscles during the task. Spike-triggered averaging of EMGs showed that 25 PreM-INs had postspike effects on EMG activity. Most PreM-INs (23/25) displayed movement-related firing rate modulations: 11 had phasic followed by tonic facilitation (p+t+); 4 were pure phasic; 4 were pure tonic; and 4 were deactivated, while their target muscles consistently had p+t+ activity (65/66 muscles). PreM-IN phasic activity started earlier than target muscle activity (49 ± 81.4 ms, mean ± SD), and the peak amplitude was correlated with the peak amplitude of the rate of change of grip force (4/17, p < 0.05), suggesting that they contributed to force initiation. In contrast, PreM-IN tonic activity started at almost the same time as the target muscle activity and the mean firing rate was correlated with the mean grip force during the hold period (4/15, p < 0.05), suggesting that they contributed to force maintenance. These results indicated that the neural pathway mediated by the spinal PreM-INs makes a significant contribution to the control of precision grip in primates.

Somato-motor haptic processing in posterior inner perisylvian region (SII/pIC) of the macaque monkey

The posterior inner perisylvian region including the secondary somatosensory cortex (area SII) and the adjacent region of posterior insular cortex (pIC) has been implicated in haptic processing by integrating somato-motor information during hand-manipulation, both in humans and in non-human primates. However, motor-related properties during hand-manipulation are still largely unknown. To investigate a motor-related activity in the hand region of SII/pIC, two macaque monkeys were trained to perform a hand-manipulation task, requiring 3 different grip types (precision grip, finger exploration, side grip) both in light and in dark conditions. Our results showed that 70% (n = 33/48) of task related neurons within SII/pIC were only activated during monkeys’ active hand-manipulation. Of those 33 neurons, 15 (45%) began to discharge before hand-target contact, while the remaining neurons were tonically active after contact. Thirty-percent (n = 15/48) of studied neurons responded to both passive somatosensory stimulation and to the motor task. A consistent percentage of task-related neurons in SII/pIC was selectively activated during finger exploration (FE) and precision grasping (PG) execution, suggesting they play a pivotal role in control skilled finger movements. Furthermore, hand-manipulation-related neurons also responded when visual feedback was absent in the dark. Altogether, our results suggest that somato-motor neurons in SII/pIC likely contribute to haptic processing from the initial to the final phase of grasping and object manipulation. Such motor-related activity could also provide the somato-motor binding principle enabling the translation of diachronic somatosensory inputs into a coherent image of the explored object.

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

Grasping an object involves shaping the hand and fingers in relation to the object's physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation.

The use of peripheral vision to guide perturbation-evoked reach-to-grasp balance-recovery reactions

For a reach-to-grasp reaction to prevent a fall, it must be executed very rapidly, but with sufficient accuracy to achieve a functional grip. Recent findings suggest that the CNS may avoid potential time delays associated with saccade-guided arm movements by instead relying on peripheral vision (PV). However, studies of volitional arm movements have shown that reaching is slower and/or less accurate when guided by PV, rather than central vision (CV). The present study investigated how the CNS resolves speed-accuracy trade-offs when forced to use PV to guide perturbation-evoked reach-to-grasp balance-recovery reactions. These reactions were evoked, in 12 healthy young adults, via sudden unpredictable antero-posterior platform translation (barriers deterred stepping reactions). In PV trials, subjects were required to look straight-ahead at a visual target while a small cylindrical handhold (length 25%> hand-width) moved intermittently and unpredictably along a transverse axis before stopping at a visual angle of 20°, 30°, or 40°. The perturbation was then delivered after a random delay. In CV trials, subjects fixated on the handhold throughout the trial. A concurrent visuo-cognitive task was performed in 50% of PV trials but had little impact on reach-to-grasp timing or accuracy. Forced reliance on PV did not significantly affect response initiation times, but did lead to longer movement times, longer time-after-peak-velocity and less direct trajectories (compared to CV trials) at the larger visual angles. Despite these effects, forced reliance on PV did not compromise ability to achieve a functional grasp and recover equilibrium, for the moderately large perturbations and healthy young adults tested in this initial study.

Cutaneous stimulation of the digits and lips evokes responses with different adaptation patterns in primary somatosensory cortex

Neuromagnetic evoked fields were recorded to compare the adaptation of the primary somatosensory cortex (SI) response to tactile stimuli delivered to the glabrous skin at the fingertips of the first three digits (condition 1) and between midline upper and lower lips (condition 2). The stimulation paradigm allowed to characterize the response adaptation in the presence of functional integration of tactile stimuli from adjacent skin areas in each condition. At each stimulation site, cutaneous stimuli (50 ms duration) were delivered in three runs, using trains of 6 pulses with regular stimulus onset asynchrony (SOA). The pulses were separated by SOAs of 500 ms, 250 ms or 125 ms in each run, respectively, while the inter-train interval was fixed (5s) across runs. The evoked activity in SI (contralateral to the stimulated hand, and bilaterally for lips stimulation) was characterized from the best-fit dipoles of the response component peaking around 70 ms for the hand stimulation, and 8 ms earlier (on average) for the lips stimulation. The SOA-dependent long-term adaptation effects were assessed from the change in the amplitude of the responses to the first stimulus in each train. The short-term adaptation was characterized by the lifetime of an exponentially saturating model function fitted to the set of suppression ratios of the second relative to the first SI response in each train. Our results indicate: 1) the presence of a rate-dependent long-term adaptation effect induced only by the tactile stimulation of the digits; and 2) shorter recovery lifetimes for the digits compared with the lips stimulation.

A tactile stimulator for studying passive shape perception

We describe a computer-controlled tactile stimulator for use in human psychophysical and monkey neurophysiological studies of 3D shape perception. The stimulator is constructed primarily of commercially available parts, as well as a few custom-built pieces for which we will supply diagrams upon request. There are two components to the stimulator: a tactile component and a hand positioner component. The tactile component consists of multiple stimulating units that move about in a Cartesian plane above the restrained hand. Each stimulating unit contains a servo-controlled linear motor with an attached small rotary stepper motor, allowing arbitrary stimulus shapes to contact the skin through vibration, static indentation, or scanning. The hand positioner component modifies the conformation of the restrained hand through a set of mechanical linkages under motorized control. The present design controls the amount of spread between digits 2 and 3, the spread between digits 4 and 3, and the degree to which digit 3 is flexed or extended, thereby simulating different conformations of the hand in contact with objects. This design is easily modified to suit the needs of the experimenter. Because the two components of the stimulator are independently controlled, the stimulator allows for parametric study of the mechanoreceptive and proprioceptive contributions to 3D tactile shape perception.

Neural representation of hand kinematics during prehension in posterior parietal cortex of the macaque monkey

Studies of hand manipulation neurons in posterior parietal cortex of monkeys suggest that their spike trains represent objects by the hand postures needed for grasping or by the underlying patterns of muscle activation. To analyze the role of hand kinematics and object properties in a trained prehension task, we correlated the firing rates of neurons in anterior area 5 with hand behaviors as monkeys grasped and lifted knobs of different shapes and locations in the workspace. Trials were divided into four classes depending on the approach trajectory: forward, lateral, and local approaches, and regrasps. The task factors controlled by the animal-how and when he used the hand-appeared to play the principal roles in modulating firing rates of area 5 neurons. In all, 77% of neurons studied (58/75) showed significant effects of approach style on firing rates; 80% of the population responded at higher rates and for longer durations on forward or lateral approaches that included reaching, wrist rotation, and hand preshaping prior to contact, but only 13% distinguished the direction of reach. The higher firing rates in reach trials reflected not only the arm movements needed to direct the hand to the target before contact, but persisted through the contact, grasp, and lift stages. Moreover, the approach style exerted a stronger effect on firing rates than object features, such as shape and location, which were distinguished by half of the population. Forty-three percent of the neurons signaled both the object properties and the hand actions used to acquire them. However, the spread in firing rates evoked by each knob on reach and no-reach trials was greater than distinctions between different objects grasped with the same approach style. Our data provide clear evidence for synergies between reaching and grasping that may facilitate smooth, coordinated actions of the arm and hand.

A novel device to measure power grip forces in squirrel monkeys

Understanding the neural bases for grip force behaviors in both normal and neurologically impaired animals is imperative prior to improving treatments and therapeutic approaches. The present paper describes a novel device for the assessment of power grip forces in squirrel monkeys. The control of grasping and object manipulation represents a vital aspect of daily living by allowing the performance of a wide variety of complex hand movements. However, following neurological injury such as stroke, these grasping behaviors are often severely affected, resulting in persistent impairments in strength, grip force modulation and kinematic hand control. While there is a significant clinical focus on rehabilitative strategies to address these issues, there exists the need for translational animal models. In the study presented here, we describe a simple grip force device designed for use in non-human primates, which provides detailed quantitative information regarding distal grip force dynamics. Adult squirrel monkeys were trained to exceed a specific grip force threshold, which was rewarded with a food pellet. One of these subjects then received an infarct of the M1 hand representation area. Results suggest that the device provides detailed and reliable information on grip behaviors in healthy monkeys and can detect deficits in grip dynamics in monkeys with cortical lesions (significantly longer release times). Understanding the physiological and neuroanatomical aspects of grasping function following neurological injury may lead to more effective rehabilitative interventions.

Responses of areas 3b and 1 in anesthetized squirrel monkeys to single- and dual-site stimulation of the digits

Stimulation of the skin evokes topographically organized activation in somatosensory cortex. This representation is context dependent, however, since a different cortical topography is observed in area 3b when stimulated with complex tactile stimuli that evoke the von Békésy funneling illusion. Here we report on the population responses, as observed with intrinsic optical imaging, of area 1 and area 3b in the anesthetized squirrel monkey to pressure indentation of distal finger pads. Individual finger pad stimulation revealed that area 1 exhibited a smaller magnification factor than 3b, as evidenced by a smaller area of activation elicited by distal finger pad stimulation. Effects of paired finger pad stimulation produced largely similar effects in area 1 and area 3b. Paired finger pad stimulation produced reductions in the area of digit activation in area 1, suggesting the presence of lateral inhibition and funneling of information in area 1. Suppressive effects were stronger for paired stimulations at adjacent than at nonadjacent sites. Single-unit recordings revealed a mixture of either a summation or a suppression of the response to paired finger stimulation, compared with single finger pad stimulation of the primary digit. However, the average population response showed that paired finger pad stimulation resulted in response suppression. Based on this study and previous studies, we suggest the presence of at least three distinct ranges of lateral inhibition in areas 3b and 1.

Failure to disrupt the ‘sensorimotor’ memory for lifting objects with a precision grip

When repetitively lifting an object with mechanical properties that vary from lift-to-lift, the fingertip forces for gripping and lifting are influenced strongly by the previous lift, revealing a 'sensorimotor' memory. Two recent reports indicate that the sensorimotor memory for grip force is easily disrupted by an unrelated task like a strong pinch or vibration, even when the lift was performed with the hand contralateral to the vibration or preceding pinch. These findings indicate that this memory may reflect sensory input or muscle contraction levels, rather than object properties or the specific task of gripping and lifting. Here we report that the predictive scaling of lift force was not disrupted by conditioning tasks that featured exerting a vertical isometric force with the upper extremity. When subjects lifted a 2 N object repetitively the peak lift force rate was 26.4 N/s. The lift force rate increased to 36.1 N/s when the 2 N object was lifted (regardless of hand) after lifting the 8 N object with the right hand, which reveals the expected 'sensorimotor' memory. The lift force rate did not increase (24.8 vs. 26.4 N/s for the control condition) when a bout of isometric exertion (9.8 N) in the vertical direction with the distal right forearm preceded lifts of the 2 N object. This finding was confirmed with another isometric task designed to more closely mimic lifting an object with a precision grip. This difference in the sensitivity of grip versus lift force to a preceding isometric contraction indicates that separate sensorimotor memories contribute to the predictive scaling of the commands for gripping and lifting an object.

Neurophysiology of prehension. II. Response diversity in primary somatosensory (S-I) and motor (M-I) cortices

Prehension responses of 76 neurons in primary somatosensory (S-I) and motor (M-I) cortices were analyzed in three macaques during performance of a grasp and lift task. Digital video recordings of hand kinematics synchronized to neuronal spike trains were compared with responses in posterior parietal areas 5 and AIP/7b (PPC) of the same monkeys during seven task stages: 1) approach, 2) contact, 3) grasp, 4) lift, 5) hold, 6) lower, and 7) relax. S-I and M-I firing patterns signaled particular hand actions, rather than overall task goals. S-I responses were more diverse than those in PPC, occurred later in time, and focused primarily on grasping. Sixty-three percent of S-I neurons fired at peak rates during contact and/or grasping. Lift, hold, and lowering excited fewer S-I cells. Only 8% of S-I cells fired at peak rates before contact, compared with 27% in PPC. M-I responses were also diverse, forming functional groups for hand preshaping, object acquisition, and grip force application. M-I activity began < or =500 ms before contact, coinciding with the earliest activity in PPC. Activation of specific muscle groups in the hand was paralleled by matching patterns of somatosensory feedback from S-I needed for efficient performance. These findings support hypotheses that predictive and planning components of prehension are represented in PPC and premotor cortex, whereas performance and feedback circuits dominate activity in M-I and S-I. Somatosensory feedback from the hand to S-I enables real-time adjustments of grasping by connections to M-I and updates future prehension plans through projections to PPC.

The cutaneous contribution to adaptive precision grip

Only after injury, or perhaps prolonged exposure to cold that is sufficient to numb the fingers, do we suddenly appreciate the complex neural mechanisms that underlie our effortless dexterity in manipulating objects. The nervous system is capable of adapting grip forces to a wide range of object shapes, weights and frictional properties, to provide optimal and secure handling in a variety of potentially perturbing environments. The dynamic interplay between sensory information and motor commands provides the basis for this flexibility, and recent studies supply somewhat unexpected evidence of the essential role played by cutaneous feedback in maintaining and acquiring predictive grip force control. These examples also offer new insights into the adaptive control of other voluntary movements.

Dominance of the right hemisphere and role of area 2 in human kinesthesia

We have previously shown that motor areas are engaged when subjects experience illusory limb movements elicited by tendon vibration. However, traditionally cytoarchitectonic area 2 is held responsible for kinesthesia. Here we use functional magnetic resonance imaging and cytoarchitectural mapping to examine whether area 2 is engaged in kinesthesia, whether it is engaged bilaterally because area 2 in non-human primates has strong callosal connections, which other areas are active members of the network for kinesthesia, and if there is a dominance for the right hemisphere in kinesthesia as has been suggested. Ten right-handed blindfolded healthy subjects participated. The tendon of the extensor carpi ulnaris muscles of the right or left hand was vibrated at 80 Hz, which elicited illusory palmar flexion in an immobile hand (illusion). As control we applied identical stimuli to the skin over the processus styloideus ulnae, which did not elicit any illusions (vibration). We found robust activations in cortical motor areas [areas 4a, 4p, 6; dorsal premotor cortex (PMD) and bilateral supplementary motor area (SMA)] and ipsilateral cerebellum during kinesthetic illusions (illusion-vibration). The illusions also activated contralateral area 2 and right area 2 was active in common irrespective of illusions of right or left hand. Right areas 44, 45, anterior part of intraparietal region (IP1) and caudo-lateral part of parietal opercular region (OP1), cortex rostral to PMD, anterior insula and superior temporal gyrus were also activated in common during illusions of right or left hand. These right-sided areas were significantly more activated than the corresponding areas in the left hemisphere. The present data, together with our previous results, suggest that human kinesthesia is associated with a network of active brain areas that consists of motor areas, cerebellum, and the right fronto-parietal areas including high-order somatosensory areas. Furthermore, our results provide evidence for a right hemisphere dominance for perception of limb movement.

Grip force control during object manipulation in cerebral stroke

OBJECTIVE

To analyze impairments of manipulative grip force control in patients with chronic cerebral stroke and relate deficits to more elementary aspects of force and grip control.

METHODS

Nineteen chronic stroke patients with fine motor deficits after unilateral cerebral lesions were examined when performing 3 manipulative tasks consisting of stationary holding, transport, and vertical cyclic movements of an instrumented object. Technical sensors measured the grip force used to stabilize the object in the hand and the object accelerations, from which the dynamic loads were calculated.

RESULTS

Many patients produced exaggerated grip forces with their affected hand in all types of manipulations. The amount of finger displacement in a grip perturbation task emerged as a highly sensitive measure for predicting the force increases. Measures of grip strength and maximum speed of force changes could not account for the impairments with comparable accuracy. In addition to force economy, the precision of the coupling between grip and load forces was impaired. However, no temporal delays were typically observed between the grip and load force profiles during cyclic movements.

CONCLUSIONS

Impaired sensibility and sensorimotor processing, evident by delayed reactions in the perturbation task, lead to an excessive increase of the safety margin between the actual grip force and the minimum force necessary to prevent object slipping. In addition to grip force scaling, cortical sensorimotor areas are responsible for smoothly and precisely adjusting grip forces to loads according to predictions about movement-induced loads and sensory experiences. However, the basic feedforward mechanism of grip force control by internal models appears to be preserved, and thus may not be a cortical but rather a subcortical or cerebellar function, as has been suggested previously.

Feedback-dependent modulation of isometric force control: an EEG study in visuomotor integration

The primary purpose of this investigation was to examine the cortical mechanisms underlying visuomotor integration in an experiment directly manipulating visual feedback (control-signal gain) as participants executed a grasping task. This was accomplished by assessing human electroencephalograms in both time and frequency domains and relating these measures to the performance accuracy of isometric force control. The basic experimental manipulation consisted of subjects controlling a grip dynamometer and the subsequent force trace displayed on a computer monitor at various magnitudes of force output and control-signal gain. Several findings from this study were of interest. First, the effects of control-signal gain and its interplay with the magnitude of force were most evident across the parietal and frontocentral electrode locations--areas specifically related to multi-modal sensory evaluation (parietal lobe) and higher-order movement control (supplementary and mesial premotor areas). Second, electroencephalography (EEG) measures in the time domain, i.e., slow-wave potentials, were sensitive to control-signal gain only during the ramp phase of force production (period of reaching the target force), not the static phase (period of maintaining the target force level). Third, EEG measures within the frequency domain (event-related desynchronization), unlike the slow-wave potential measures, were sensitive to control-signal gain during the static phase of force production--a sensitivity that was directly related to improvements in the accuracy of isometric force control. The findings of this investigation are described in relation to the existent literature on human visuomotor integration with special attention paid to the distinct spatial and temporal electrocortical patterns exhibited under varying degrees of visual feedback and magnitudes of force output during grasping.

Precision grip force dynamics: a system identification approach

A linear model of the dynamics of the human precision grip is presented. The transfer function is identified as representing the peripheral motor subsystem, from the motoneuron pool to the final production of a grip force between the tip of the index finger and the thumb. The transfer function captures the limiting isometric muscle dynamics that, e.g., cortical motor areas have to act through. When identifying the transfer function we introduce a novel technique, common subsystem identification. This characterizes a specific subsystem in a complex biomechanical system. This technique requires data from two functionally different experiments that both involve the subsystem of interest. Two transfer functions, one for each experiment, are then estimated using a linear black box technique. The common mathematical factors, represented by poles and zeros, are used to form a new transfer function. It is concluded that this transfer function represents the common biological subsystem involved in both experiments. Here, we use one active and one reactive isometric grip force experiment to capture the subsystem of interest, i.e., the motoneuron pool, motor units, muscles, tendons and fingertip tissue. The characteristics of the dynamics are in agreement with previously published experiments on human neuro-muscular systems. The model, H(s) = 280/(s2 + 22s + 280), is well suited for the representation of a force producing end-effector in simulations including a control system with sensory feedback.

Functional brain areas used for the lifting of objects using a precision grip: a PET study

Positron emission tomography (PET) was performed in 10 normal volunteers to investigate regional cortical and subcortical activation induced by the lifting of an object repetitively using a precision grip between the index finger and thumb. Data were obtained for three object weights (4, 200 and 600 g) and a resting condition. Grip and lift forces on a similar object and the activity of selected muscles in the hand, arm and shoulder were also recorded in separate lifting trials. A comparison between all movement conditions and the resting condition revealed significant activation of the primary motor (M1), primary sensory (S1), dorso-caudal premotor (PM), caudal supplementary motor (SMA) and cingulate motor (CMA) cortices contralateral to the hand used. On the ipsilateral side, activation of the M1, caudal SMA and inferior parietal cortex (BA 40) was also found. In the subcortical areas, the bilateral hemispheres and right vermis of the cerebellum, left basal ganglia and thalamus were activated. Behavioral adaptation to a heavier object weight was revealed in a nearly proportional increase of both grip and lift forces, prolonged force application period and a higher level of hand and arm muscle activities. An increase in the rCBF associated with these changes was noted in several cortical and subcortical areas. However, consistent object weight-dependent activation was observed only in the M1/S1 contralateral to the hand used.

Neuronal activity in somatosensory cortex of monkeys using a precision grip. II. Responses To object texture and weights

Three monkeys were trained to lift and hold a test object within a 12- to 25-mm position window for 1 s. The activity of single neurons was recorded during performance of the task in which both the weight and surface texture of the object were systematically varied. Whenever possible, each cell was tested with three weights (15, 65, and 115 g) and three textures (smooth metal, fine 200 grit sandpaper, and rough 60 grit sandpaper). Of 386 cells recorded in 3 monkeys, 45 cells had cutaneous receptive fields on the index or thumb or part of the thenar eminence and were held long enough to be tested in all 9 combinations of texture and weight. Recordings were made for the entire anterior-posterior extent of the thumb and index finger areas in somatosensory cortex including area 7b. However, the statistical analysis required a selection of only those cells for which nine complete recording conditions were available limiting the sample to cells in areas 2, 5, and 7b. Significant differences in the grip force accompanied 98% of the changes in texture and 78% of the changes in weight. Increasing the object weight also increased the force tangential to the skin surface as measured by the load or lifting force. The peak discharge during lifting was judged to be the most sensitive index of cell activity and was analyzed with a two-way analysis of variance (ANOVA). In addition, peak cell discharge was normalized to allow comparisons among different combinations of texture and weight as well as comparisons among different neurons. Overall, the peak firing frequency of 87% of the cells was significantly modulated by changes in object texture, but changes in object weight affected the peak activity of only 58% of the cells. Almost all (17/18, 94%) of the static cells were influenced by the object texture, and 81% of the dynamic cells that were active only briefly at grip and lift onset were modulated by texture. For some cells, surface texture had a significant effect on neuronal discharge that was independent of the object weight. In contrast, weight-related responses were never simple main effects of the weight alone and appeared instead as significant interactions between texture and weight. Four neurons either increased or decreased activity in a graded fashion with surface structure (roughness) regardless of the object weight (P < 0.05). Ten other neurons showed increases or decreases in response to one or two textures, which might represent either a graded response or a tuning preference for a specific texture. The firing frequency of the majority (31/45) of neurons reflected an interaction of both texture and weight. The cells with texture-related but weight-independent activities were thought to encode surface characteristics that are largely independent of the grip and lifting forces used to manipulate the object. Such constancies could be used to construct internal representations or mental models for planning and controlling object manipulation.

Neuronal activity in somatosensory cortex of monkeys using a precision grip. III. Responses to altered friction perturbations

The purpose of this investigation was to examine the activity changes in single units of the somatosensory cortex in response to lubricating and adhesive coatings applied to a hand-held object. Three monkeys were trained to grasp an object between the thumb and index fingers and to lift and hold it stationary within a narrow position window for 1 s before release. Grip forces normal to the skin surface, load forces tangential to the skin surface, and the displacement of the object were measured on each trial. Adhesive (rosin) and lubricant (petroleum jelly) coatings were applied to the smooth metal surface of the object to alter the friction against the skin. In addition, neuronal activity evoked by force pulse-perturbations generating shear forces and slip on the skin were compared with the patterns of activity elicited by grasping and lifting the coated surfaces. Following changes in surface coatings, both monkeys modulated the rate at which grip forces normal to the skin surface and load forces tangential to the skin surface were applied during the lifting phase of the task. As a result, the ratio of the rates of change of the two forces was proportionately scaled to the surface coating properties with the more slippery surfaces, having higher ratios. This precise control of normal and tangential forces enabled the monkeys to generate adequate grip forces and prevent slip of the object. From a total of 386 single neurons recorded in the hand area of the somatosensory cortex, 92 were tested with at least 1 coating. Cell discharge changed significantly with changes in surface coating in 62 (67%) of these cells. Of these coating-related cells, 51 were tested with both an adhesive and lubricating coating, and 45 showed significant differences in activity between the untreated metal surface and either the lubricant or the adhesive coating. These cells were divided into three main groups on the basis of their response patterns. In the first group (group A), the peak discharge increased significantly when the grasped surface was covered with lubricant. These cells appeared to be selectively sensitive to slip of the object on the skin. The second group (group B) was less activated by the adhesive surface compared with either the untreated metal or the lubricated surface, and they responded mainly to variations in the force normal to the skin surface. These cells provide useful feedback for the control of grip force. The third group (group C) responded to both slips and to changes in forces tangential to the skin. Most of these cells responded with a biphasic pattern reflecting the bidirectional changes in load force as the object was first accelerated and then decelerated. One hundred sixty-eight of the 386 isolated neurons were tested with brief perturbations during the task. Of these, 147 (88%) responded to the perturbation with a significant change in activity. In most of the cells, the response to the perturbation was shorter than 100 ms with a mean latency of 44.1 +/- 16.3 (SD) ms. For each of the cell groups, the activity patterns triggered by the perturbations were consistent with the activity patterns generated during the grasping and lifting of the coated object.