Inferior parietal somatosensory neurons coding face-hand coordination in Japanese macaques

Neuronal activities of the anterior part of the inferior parietal lobule (area 7b or PF) were investigated in five awake Japanese monkeys. There were neurons which had specific combinations of receptive field (RF) locations, most typically in both the face and hand; we refer to the seas Face-Hand neurons. The most interesting property of the Face-Hand neurons is that some of these neurons responded to specific behavior executed with synergism between the face (especially the mouth) and hand movements; namely, face-hand coordinated behavior (e.g., eating behavior). We call these cells Face-Hand coordination neurons (52% of all the Face-Hand neurons). These neurons discharged more strongly when the animal executed face-hand coordinated behavior, especially eating behavior, than when somatosensory stimuli were given to RFs passively, or when face movements and hand movements were executed separately. We thus propose that the neuronal activities of area 7b are related to the representation of face-hand coordination.     

Where the eye looks, the hand follows; limb-dependent magnetic misreaching in optic ataxia

The posterior parietal cortex (PPC) is thought to play an important role in the sensorimotor transformations associated with reaching movements. In humans, damage to the PPC, particularly bilateral lesions, leads to impairments of visually guided reaching movements (optic ataxia). Recent accounts of optic ataxia based upon electrophysiological recordings in monkeys have proposed that this disorder arises because of a breakdown in the tuning fields of parietal neurons responsible for integrating spatially congruent retinal, eye, and hand position signals to produce coordinated eye and hand movements . We present neurological evidence that forces a reconceptualization of this view. We report a detailed case study of a patient with a limb-dependent form of optic ataxia who can accurately reach with either hand to objects that he can foveate (thereby demonstrating coordinated eye-hand movements) but who cannot effectively decouple reach direction from gaze direction for movements executed using his right arm. The demonstration that our patient's misreaching is confined to movements executed using his right limb, and only for movements that are directed to nonfoveal targets, rules out explanations based upon simple perceptual or motor deficits but indicates an impairment in the ability to dissociate the eye and limb visuomotor systems when appropriate.     

Face or hand,not both: perceptual correlates of reafferentation in a former amputee

The topography of the somatosensory maps of our body can be largely shaped by alterations of peripheral sensory inputs. Following hand amputation, the hand cortical territory becomes responsive to facial cutaneous stimulation. Amputation-induced remapping, however, reverses after transplantation, as the grafted hand (re)gains its sensorimotor representation. Here, we investigate hand tactile perception in a former amputee by touching either grafted hand singly or in combination with another body part. The results showed that tactile sensitivity recovered rapidly, being remarkably good 5 months after transplant. In the right grafted hand, however, the newly acquired somatosensory awareness was strikingly hampered when the ipsilateral face was touched simultaneously, i.e., right face perception extinguished right hand perception. Ipsilateral face-hand extinction was present in the formerly dominant right hand 5 months after transplant and eventually disappeared 6 months afterwards. Control conditions' results showed that right hand tactile awareness was not extinguished either by contralateral left face and left hand stimulation or ipsilateral stimulation of the arm, which is bodily close to, but cortically far from, the hand. We suggest that ipsilateral face-hand extinction is a perceptual counterpart of the remapping that occurs after allograft and eyewitnesses the inherently competitive nature of sensory representations.     

Dorsal premotor neurons encode the relative position of the hand, eye, and goal during reach planning

When reaching to grasp an object, we often move our arm and orient our gaze together. How are these movements coordinated? To investigate this question, we studied neuronal activity in the dorsal premotor area (PMd) and the medial intraparietal area (area MIP) of two monkeys while systematically varying the starting position of the hand and eye during reaching. PMd neurons encoded the relative position of the target, hand, and eye. MIP neurons encoded target location with respect to the eye only. These results indicate that whereas MIP encodes target locations in an eye-centered reference frame, PMd uses a relative position code that specifies the differences in locations between all three variables. Such a relative position code may play an important role in coordinating hand and eye movements by computing their relative position.     

Do bimanual motor actions involve the dorsal premotor (PMd), cingulate (CMA) and posterior parietal (PPC) cortices? Comparison with primary and supplementary motor cortical areas

Single neuronal activity was recorded from the dorsal premotor cortex (PMd), the cingulate motor area (CMA) and the posterior parietal cortex (PPC) in two Macaca fascicularis trained to perform a delayed conditional sequence of coordinated pull and grasp movements. The monkey had to perform three types of trials instructed in a random manner: (i) bimanually, using the two hands in a coordinated sequence of movements; (ii) unimanually, using the left hand only; (iii) unimanually, using the right hand only. The aim of this study was first to assess the bilateral relationships of the three cortical areas for unimanual motor control. Second, to establish whether the three cortical areas contain units reflecting bimanual synergy. A total of 255 task-related neurons were recorded from the PMd, CMA and PPC, where most neurons exhibited a significant modulation of activity in both contralateral and ipsilateral unimanual trials (bilateral neurons: 85, 77 and 61%, respectively). Lower proportions of neurons in PMd (7%), CMA (16%) and PPC (6%) were active in unimanual contralateral trials, but not in unimanual ipsilateral trials. The reverse (modulation of activity in ipsilateral but not contralateral unimanual trials) represented 5% of neurons in PMd, 7% in CMA and 3% in PPC. When comparing unimanual and bimanual trials to search evidence for bimanual coordination, 57% of PMd task-related neurons were classified as bimanual, defined as units in which the activity observed in bimanual trials could not be predicted from that associated with unimanual trials when comparing the same events related to the same arm. The proportion of bimanual neurons in CMA (56%) was comparable to that found in PMd (55%), whereas PPC exhibited a higher proportion of bimanual neurons (74%). Furthermore, comparison of the present data with our previous results regarding the supplementary (SMA) and primary (M1) motor cortical areas shows that there is no statistically significant difference between PMd, CMA, SMA and M1 with respect to the proportions of bimanual neurons. Altogether, these results suggest that the five cortical areas PMd, CMA, PPC, SMA and M1 are participating to the control of sequential bimanually coordinated movements. Inter-limb coordination may thus be controlled by a widely distributed network including several cortical and sub-cortical areas.     

Do bimanual motor actions involve the dorsal premotor (PMd), cingulate (CMA) and posterior parietal (PPC) cortices? Comparison with primary and supplementary motor cortical areas

Single neuronal activity was recorded from the dorsal premotor cortex (PMd), the cingulate motor area (CMA) and the posterior parietal cortex (PPC) in two Macaca fascicularis trained to perform a delayed conditional sequence of coordinated pull and grasp movements. The monkey had to perform three types of trials instructed in a random manner: (i) bimanually, using the two hands in a coordinated sequence of movements; (ii) unimanually, using the left hand only; (iii) unimanually, using the right hand only. The aim of this study was first to assess the bilateral relationships of the three cortical areas for unimanual motor control. Second, to establish whether the three cortical areas contain units reflecting bimanual synergy. A total of 255 task-related neurons were recorded from the PMd, CMA and PPC, where most neurons exhibited a significant modulation of activity in both contralateral and ipsilateral unimanual trials (bilateral neurons: 85, 77 and 61%, respectively). Lower proportions of neurons in PMd (7%), CMA (16%) and PPC (6%) were active in unimanual contralateral trials, but not in unimanual ipsilateral trials. The reverse (modulation of activity in ipsilateral but not contralateral unimanual trials) represented 5% of neurons in PMd, 7% in CMA and 3% in PPC. When comparing unimanual and bimanual trials to search evidence for bimanual coordination, 57% of PMd task-related neurons were classified as bimanual, defined as units in which the activity observed in bimanual trials could not be predicted from that associated with unimanual trials when comparing the same events related to the same arm. The proportion of bimanual neurons in CMA (56%) was comparable to that found in PMd (55%), whereas PPC exhibited a higher proportion of bimanual neurons (74%). Furthermore, comparison of the present data with our previous results regarding the supplementary (SMA) and primary (M1) motor cortical areas shows that there is no statistically significant difference between PMd, CMA, SMA and M1 with respect to the proportions of bimanual neurons. Altogether, these results suggest that the five cortical areas PMd, CMA, PPC, SMA and M1 are participating to the control of sequential bimanually coordinated movements. Inter-limb coordination may thus be controlled by a widely distributed network including several cortical and sub-cortical areas.     

Neuronal chains for actions in the parietal lobe: a computational model

The inferior part of the parietal lobe (IPL) is known to play a very important role in sensorimotor integration. Neurons in this region code goal-related motor acts performed with the mouth, with the hand and with the arm. It has been demonstrated that most IPL motor neurons coding a specific motor act (e.g., grasping) show markedly different activation patterns according to the final goal of the action sequence in which the act is embedded (grasping for eating or grasping for placing). Some of these neurons (parietal mirror neurons) show a similar selectivity also during the observation of the same action sequences when executed by others. Thus, it appears that the neuronal response occurring during the execution and the observation of a specific grasping act codes not only the executed motor act, but also the agent's final goal (intention).In this work we present a biologically inspired neural network architecture that models mechanisms of motor sequences execution and recognition. In this network, pools composed of motor and mirror neurons that encode motor acts of a sequence are arranged in form of action goal-specific neuronal chains. The execution and the recognition of actions is achieved through the propagation of activity bursts along specific chains modulated by visual and somatosensory inputs.The implemented spiking neuron network is able to reproduce the results found in neurophysiological recordings of parietal neurons during task performance and provides a biologically plausible implementation of the action selection and recognition process.Finally, the present paper proposes a mechanism for the formation of new neural chains by linking together in a sequential manner neurons that represent subsequent motor acts, thus producing goal-directed sequences.     

The frames of reference of the motor-visual aftereffect

Repeatedly performing similar motor acts produces short-term adaptive changes in the agent's motor system. One striking use-dependent effect is the motor-to-visual aftereffect (MVA), a short-lasting negative bias in the conceptual categorization of visually-presented training-related motor behavior. The MVA is considered the behavioral counterpart of the adaptation of visuomotor neurons that code for congruent executed and observed motor acts. Here we characterize which features of the motor training generate the MVA, along 3 main dimensions: a) the relative role of motor acts vs. the semantics of the task-set; b) the role of muscular-specific vs. goal-specific training and c) the spatial frame of reference with respect to the whole body. Participants were asked to repeatedly push or pull some small objects in a bowl as we varied different components of adapting actions across three experiments. The results show that a) the semantic value of the instructions given to the participant have no role in generating the MVA, which depends only on the motor meaning of the training act; b) both intrinsic body movements and extrinsic action goals contribute simultaneously to the genesis of the MVA and c) changes in the relative position of the acting hand compared to the observed hand, when they do not involve changes to the movement performed or to the action meaning, do not have an effect on the MVA. In these series of experiments we confirm that recent motor experiences produce measurable changes in how humans see each others' actions. The MVA is an exquisite motor effect generated by two distinct motor sub-systems, one operating in an intrinsic, muscular specific, frame of reference and the other operating in an extrinsic motor space.     

Eye-Hand Coordination during Visuomotor Adaptation with Different Rotation Angles

This study examined adaptive changes of eye-hand coordination during a visuomotor rotation task. Young adults made aiming movements to targets on a horizontal plane, while looking at the rotated feedback (cursor) of hand movements on a monitor. To vary the task difficulty, three rotation angles (30°, 75°, and 150°) were tested in three groups. All groups shortened hand movement time and trajectory length with practice. However, control strategies used were different among groups. The 30° group used proportionately more implicit adjustments of hand movements than other groups. The 75° group used more on-line feedback control, whereas the 150° group used explicit strategic adjustments. Regarding eye-hand coordination, timing of gaze shift to the target was gradually changed with practice from the late to early phase of hand movements in all groups, indicating an emerging gaze-anchoring behavior. Gaze locations prior to the gaze anchoring were also modified with practice from the cursor vicinity to an area between the starting position and the target. Reflecting various task difficulties, these changes occurred fastest in the 30° group, followed by the 75° group. The 150° group persisted in gazing at the cursor vicinity. These results suggest that the function of gaze control during visuomotor adaptation changes from a reactive control for exploring the relation between cursor and hand movements to a predictive control for guiding the hand to the task goal. That gaze-anchoring behavior emerged in all groups despite various control strategies indicates a generality of this adaptive pattern for eye-hand coordination in goal-directed actions.     

Concatenation of Observed Grasp Phases with Observer’s Distal Movements: A Behavioural and TMS Study

The present study aimed at determining how actions executed by two conspecifics can be coordinated with each other, or more specifically, how the observation of different phases of a reaching-grasping action is temporary related to the execution of a movement of the observer. Participants observed postures of initial finger opening, maximal finger aperture, and final finger closing of grasp after observation of an initial hand posture. Then, they opened or closed their right thumb and index finger (experiments 1, 2 and 3). Response times decreased, whereas acceleration and velocity of actual finger movements increased when observing the two late phases of grasp. In addition, the results ruled out the possibility that this effect was due to salience of the visual stimulus when the hand was close to the target and confirmed an effect of even hand postures in addition to hand apparent motion due to the succession of initial hand posture and grasp phase. In experiments 4 and 5, the observation of grasp phases modulated even foot movements and pronunciation of syllables. Finally, in experiment 6, transcranial magnetic stimulation applied to primary motor cortex 300 ms post-stimulus induced an increase in hand motor evoked potentials of opponens pollicis muscle when observing the two late phases of grasp. These data suggest that the observation of grasp phases induced simulation which was stronger during observation of finger closing. This produced shorter response times, greater acceleration and velocity of the successive movement. In general, our data suggest best concatenation between two movements (one observed and the other executed) when the observed (and simulated) movement was to be accomplished. The mechanism joining the observation of a conspecific’s action with our own movement may be precursor of social functions. It may be at the basis for interactions between conspecifics, and related to communication between individuals.     

Neuron selection by relative importance for neural decoding of dexterous finger prosthesis control application

Future generations of upper limb prosthesis will have dexterous hand with individual fingers and will be controlled directly by neural signals. Neurons from the primary motor (M1) cortex code for finger movements and provide the source for neural control of dexterous prosthesis. Each neuron's activation can be quantified by the change in firing rate before and after finger movement, and the quantified value is then represented by the neural activity over each trial for the intended movement. Since this neural activity varies with the intended movement, we define the relative importance of each neuron independent of specific intended movements. The relative importance of each neuron is determined by the inter-movement variance of the neural activities for respective intended movements. Neurons are ranked by the relative importance and then a subpopulation of rank-ordered neurons is selected for the neural decoding. The use of the proposed neuron selection method in individual finger movements improved decoding accuracy by 21.5% in the case of decoding with only 5 neurons and by 9.2% in the case of decoding with only 10 neurons. With only 15 highly ranked neurons, a decoding accuracy of 99.5% was achieved. The performance improvement is still maintained when combined movements of two fingers were included though the decoding accuracy fell to 95.7%. Since the proposed neuron selection method can achieve the targeting accuracy of decoding algorithms with less number of input neurons, it can be significant for developing brain–machine interfaces for direct neural control of hand prostheses.     

Cortical control of mastication in the cat: properties of mastication-related neurons in motor and masticatory cortices

The aim of this study is to examine mastication-specific activity of orofacial neurons in the motor and masticatory cortices of the awake cat. We examine properties of mastication-related neurons (MRNs) in masticatory (MA, the rostral region of the orbital gyrus) and motor (area P, the lateral wall of the presylvian sulcus) cortical areas that are related to mastication of cats. MRNs in MA and area P had in common mechanoreceptive fields (RFs) in perioral, mandibular and lingual regions, and many MRNs had bilateral RFs in the tongue and mandibular regions. Facial RF size was the largest in area P. Eleven percent of MRN recording sites in MA, and 43% in area P evoked various motor effects with the use of intracortical microstimulation (ICMS). MRNs of the pre-movement type showing activities prior to mastication, or masticatory or lingual EMG, were 14% in MA and 45% in area P. Based on wheat germ agglutinin–horseradish peroxidase (WGA-HRP) injection into area P and MA, cortico-cortical connections were examined. After the unilateral area P injection, were reciprocal connections between the contralateral area P and bilateral MA were demonstrated. After the unilateral MA injection, there were reciprocal connections between the contralateral MA, bilateral area P and bilateral orofacial SI (the orofacial region of the first somatosensory area). These findings suggest that accurate masticatory movements may be executed by the cortical processing in MA and area P.     

Cortical control of mastication in the cat: properties of mastication-related neurons in motor and masticatory cortices

The aim of this study is to examine mastication-specific activity of orofacial neurons in the motor and masticatory cortices of the awake cat. We examine properties of mastication-related neurons (MRNs) in masticatory (MA, the rostral region of the orbital gyrus) and motor (area P, the lateral wall of the presylvian sulcus) cortical areas that are related to mastication of cats. MRNs in MA and area P had in common mechanoreceptive fields (RFs) in perioral, mandibular and lingual regions, and many MRNs had bilateral RFs in the tongue and mandibular regions. Facial RF size was the largest in area P. Eleven percent of MRN recording sites in MA, and 43% in area P evoked various motor effects with the use of intracortical microstimulation (ICMS). MRNs of the pre-movement type showing activities prior to mastication, or masticatory or lingual EMG, were 14% in MA and 45% in area P. Based on wheat germ agglutinin-horseradish peroxidase (WGA-HRP) injection into area P and MA, cortico-cortical connections were examined. After the unilateral area P injection, were reciprocal connections between the contralateral area P and bilateral MA were demonstrated. After the unilateral MA injection, there were reciprocal connections between the contralateral MA, bilateral area P and bilateral orofacial SI (the orofacial region of the first somatosensory area). These findings suggest that accurate masticatory movements may be executed by the cortical processing in MA and area P.     

Effects of reversible inactivation of the supplementary motor area (SMA) on unimanual grasp and bimanual pull and grasp performance in monkeys

Abstract The supplementary motor area (SMA) was reversibly inactivated by muscimol microinfusion in two monkeys while they were performing two motor tasks: (1) a delayed conditional bimanual drawer pulling and grasping sequence which was initiated on a self-paced basis; (2) a unimanual reach and grasp task (modified Kluver board task). Unilateral or bilateral inactivation of the SMA induced a prominent deficit in trial initiation of bimanual sequential movements, affecting the hand contralateral to the inactivated side or both hands, respectively. The deficit was a long lasting (10-15 min or more) inability of the monkey to place its hand (s) in the ready position on start touch-sensitive pads, a condition required to initiate the drawer task. However, if after such a deficit period, the experimenter put his hand on the start touch-sensitive pad to initiate the trial, then the monkey executed the drawer task without obvious motor deficit. SMA inactivation did not affect unimanual reaching and grasping movements in the board task. In contrast to the SMA, inactivation of other motor areas (primary, premotor dorsal, anterior intraparietal area) did not affect the initiation of movement sequences in the drawer task. These data thus indicate that the SMA plays a crucial and specific role in initiation of self-paced movement sequences. However, SMA inactivation did not prevent the monkeys to perform coordinated movements of the two forelimbs and hands, indicating that SMA is not necessary for bimanual coordination.     

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.     

Organization of cortical processing for facial movements during licking in cats

We proposed that cortical organization for the execution of adequate licking in cats was processed under the control of two kinds of affiliated groups for face and jaw & tongue movements (Hiraba H, Sato T. 2005A. Cerebral control of face, jaw, and tongue movements in awake cats: Changes in regional cerebral blood flow during lateral feeding Somatosens Mot Res 22:307–317). We assumed the cortical organization for face movements from changes in MRN (mastication-related neuron) activities recorded at area M (motor cortex) and orofacial behaviors after the lesion in the facial SI (facial region in the primary somatosensory cortex). Although we showed the relationship between facial SI (area 3b) and area M (area 4δ), the property of area C (area 3a) was not fully described. The aim of this present study is to investigate the functional role of area C (the anterior part of the coronal sulcus) that transfers somatosensory information in facial SI to area M, as shown in a previous paper (Hiraba H. 2004. The function of sensory information from the first somatosensory cortex for facial movements during ingestion in cats Somatosens Mot Res 21:87--97). We examined the properties of MRNs in area C and changes in orofacial behaviors after the area C or area M lesion. MRNs in area C had in common RFs in the lingual, perioral, and mandibular parts, and activity patterns of MRNs showed both post- and pre-movement types. Furthermore, cats with the area C lesion showed similar disorders to cats with the area M lesion, such as the dropping of food from the contralateral mouth, prolongation of the period of ingestion and mastication, and so on. From these results, we believe firmly the organization of unilateral cortical processing in facial SI, area C, and area M for face movements during licking.     

Eye-hand coordination: learning a new trick

In many manual tasks, a specific repertoire of eye movements accompanies the actions. A new study has shown how this pattern changes as eye and hand become coordinated when learning a new skill.     

Neural response to movement of the hand and mouth in the secondary somatosensory cortex of Japanese monkeys during a simple feeding task

Abstract

Neural activity was recorded in the secondary somatosensory cortex (SII) of macaque monkeys during a simple feeding task. Around the border between the representations of the hand and face in SII, we found neurons that became active during both retrieving with the hand and eating; 59% had receptive fields (RFs) in the hand/face and the remaining 41% had no RFs. Neurons that responded to touching objects were rarely found. This suggests their sensorimotor function rather than tactile object recognition.     

The neuronal basis of behavior in Tritonia. III. Neuronal mechanism of a fixed action pattern

We have investigated the roles played by numerous identified brain cells in initiating and controlling the coordinated sequence of movements of an instinctive escape-swimming sequence in an intact animal preparation of the nudibranch mollusc Tritonia diomedia. Intracellular electrical activity in different neurons has been correlated with the various phases of the behavior. We recognized four major stages in the response: (1) reflex local withdrawal; (2) preparation for swimming; (3) swimming; and (4) termination. We have located and studied brain cells whose activity is associated with the following aspects of swimming: withdrawal; elongation; triggering behavior; dorsal flexion; ventral flexion; and neurons which excite both dorsal and ventral flexor neurons simulataneously. We find that specific neurons play clearly defined and invariant roles in control of escape-swimming and that the neuronal circuitry underlying the coordination of the sequence is the same in different individuals of the species. Details of the neuronal circuitry and a number of the general functional attributes of interacting cell groups have been determined directly or inferred from observations of cell to cell interactions. A preliminary model of the neuronal apparatus which controls this behavior is discussed. The principal findings are: (1) a discrete group of electrically coupled neurons determines, by its output, whether or not escapeswimming will be executed; (2) the neuronal elements responsible for execution of the swimming stages of the sequence are maintained in an excited state for the required period, in part by a regenerative feedback system; (3) alternating bursts of impulses in functional antagonists are co-ordinated in part by reciprocal inhibition between them; and (4) termination of the sequence occurs abruptly at a particular phase in the swimming cycle and appears to be an active neural process, rather than a simple running-down.     

ON TEMPERATURE CHARACTERISTICS FOR DIFFERENT PROCESSES IN THE SAME ORGANISM

The temperature characteristics (µ) for two activities (heart beat and respiratory movements) studied simultaneously in the same individual organism (Daphnia magna) were always found to differ in magnitude. The type of graph obtained when the frequency of these movements was plotted according to the Arrhenius equation was also distinctly different for each activity. The organism therefore does not determine a uniform magnitude of the temperature characteristic for each of its activities; the values of µ must therefore have, to this extent, a local, specific meaning.