Ventral Premotor Cortex Research Articles

The left supramarginal gyrus contributes to finger positioning for object use: a neuronavigated transcranial magnetic stimulation study.

In everyday actions, we grasp dozens of different manipulable objects in ways that accommodate their functional use. Neuroimaging studies showed that grasping objects in a way that is appropriate for their use involves a left-lateralized network including the supramarginal gyrus (SMG), the anterior intraparietal area (AIP) and the ventral premotor cortex (PMv). However, because previous works premised their conclusions on tasks requiring action execution, it has remained difficult to discriminate between the areas involved in specifying the position of fingers onto the object from those implementing the motor programme required to perform the action. To address this issue, we asked healthy participants to make judgements about pictures of manipulable objects, while repetitive transcranial magnetic stimulation (rTMS) was applied over the left SMG, AIP, PMv or, as a control, the vertex. The participants were asked to name the part of the image where the thumb or the index finger was expected to contact the object during its normal utilization or where a given attribute of the same object was located. The two tasks were strictly identical in terms of visual display, working memory demands and response requirements. Results showed that rTMS over SMG slowed down judgements of finger positions but not judgements of object attributes. Both types of judgements remained unaffected when rTMS was applied over AIP or PMv. This finding demonstrates that, within the parieto-frontal network dedicated to object use, at least the left SMG is involved in specifying the appropriate position of the thumb and index onto the object.

Cortical and subcortical connections of parietal and premotor nodes of the monkey hand mirror neuron network.

Mirror neurons (MNs) are a class of cells originally discovered in the monkey ventral premotor cortex (PMv) and inferior parietal lobule (IPL). They discharge during both action execution and action observation and appear to play a crucial role in understanding others' actions. It has been proposed that the mirror mechanism is based on a match between the visual description of actions, encoded in temporal cortical regions, and their motor representation, provided by PMv and IPL. However, neurons responding to action observation have been recently found in other cortical regions, suggesting that the mirror mechanism relies on a wider network. Here we provide the first description of this network by injecting neural tracers into physiologically identified IPL and PMv sectors containing hand MNs. Our results show that these sectors are reciprocally connected, in line with the current view, but IPL MN sectors showed virtually no direct connection with temporal visual areas. In addition, we found that PMv and IPL MN sectors share connections with several cortical regions, including the dorsal and mesial premotor cortex, the primary motor cortex, the secondary somatosensory cortex, the mid-dorsal insula and the ventrolateral prefrontal cortex, as well as subcortical structures, such as motor and polysensory thalamic nuclei and the mid-dorsal claustrum. We propose that each of these regions constitutes a node of an "extended network", through which information relative to ongoing movements, social context, environmental contingencies, abstract rules, and internal states can influence MN activity and contribute to several socio-cognitive functions.

Frontal eye field in prosimian galagos: Intracortical microstimulation and tracing studies.

The frontal eye field (FEF) in prosimian primates was identified as a small cortical region, above and anterior to the anterior frontal sulcus, from which saccadic eye movements were evoked with electrical stimulation. Tracer injections revealed FEF connections with cortical and subcortical structures participating in higher order visual processing. Ipsilateral cortical connections were the densest with adjoining parts of the dorsal premotor and prefrontal cortex (PFC). Label in a region corresponding to supplementary eye field (SEF) of other primates, suggests the existence of SEF in galagos. Other connections were with ventral premotor cortex (PMV), the caudal half of posterior parietal cortex, cingulate cortex, visual areas within the superior temporal sulcus, and inferotemporal cortex. Callosal connections were mostly with the region of the FEF of another hemisphere, SEF, PFC, and PMV. Most subcortical connections were ipsilateral, but some were bilateral. Dense bilateral connections were to caudate nuclei. Densest reciprocal ipsilateral connections were with the paralamellar portion of mediodorsal nucleus, intralaminar nuclei and magnocellular portion of ventral anterior nucleus. Other FEF connections were with the claustrum, reticular nucleus, zona incerta, lateral posterior and medial pulvinar nuclei, nucleus limitans, pretectal area, nucleus of Darkschewitsch, mesencephalic and pontine reticular formation and pontine nuclei. Surprisingly, the superior colliculus (SC) contained only sparse anterograde label. Although most FEF connections in galagos are similar to those in monkeys, the FEF-SC connections appear to be much less. This suggests that a major contribution of the FEF to visuomotor functions of SC emerged with the evolution of anthropoid primates.

Long-latency interhemispheric interactions between motor-related areas and the primary motor cortex: a dual site TMS study

The primary motor cortex (M1) is highly influenced by premotor/motor areas both within and across hemispheres. Dual site transcranial magnetic stimulation (dsTMS) has revealed interhemispheric interactions mainly at early latencies. Here, we used dsTMS to systematically investigate long-latency causal interactions between right-hemisphere motor areas and the left M1 (lM1). We stimulated lM1 using a suprathreshold test stimulus (TS) to elicit motor-evoked potentials (MEPs) in the right hand. Either a suprathreshold or a subthreshold conditioning stimulus (CS) was applied over the right M1 (rM1), the right ventral premotor cortex (rPMv), the right dorsal premotor cortex (rPMd) or the supplementary motor area (SMA) prior to the TS at various CS-TS inter-stimulus intervals (ISIs: 40–150 ms). The CS strongly affected lM1 excitability depending on ISI, CS site and intensity. Inhibitory effects were observed independently of CS intensity when conditioning PMv, rM1 and SMA at a 40-ms ISI, with larger effects after PMv conditioning. Inhibition was observed with suprathreshold PMv and rM1 conditioning at a 150-ms ISI, while site-specific, intensity-dependent facilitation was detected at an 80-ms ISI. Thus, long-latency interhemispheric interactions, likely reflecting indirect cortico-cortical/cortico-subcortical pathways, cannot be reduced to nonspecific activation across motor structures. Instead, they reflect intensity-dependent, connection- and time-specific mechanisms.

Decoding Kinematics Using Task-Independent Movement-Phase-Specific Encoding Models

Neural decoders of kinematic variables have largely relied on task-dependent (TD) encoding models of the neural activity. TD decoders, though, require prior knowledge of the tasks, which may be unavailable, lack scalability as the number of tasks grows, and require a large number of trials per task to reduce the effects of neuronal variability. The execution of movements involves a sequence of phases (e.g., idle, planning, and so on) whose progression contributes to the neuronal variability. We hypothesize that information about the movement phase facilitates the decoding of kinematics and compensates for the lack of prior knowledge about the task. We test this hypothesis by designing a task-independent movement-phase-specific (TI-MPS) decoding algorithm. The algorithm assumes that movements proceed through a consistent sequence of phases regardless of the specific task, and it builds one model per phase by combining data from different tasks. Phase transitions are detected online from neural data and, for each phase, a specific encoding model is used. The TI-MPS algorithm was tested on single-unit recordings from 437 neurons in the dorsal and ventral pre-motor cortices from two nonhuman primates performing 3-D multi-object reach-to-grasp tasks. The TI-MPS decoder accurately decoded kinematics from tasks it was not trained for and outperformed TD approaches (one-way ANOVA with Tukey's post-hoc test and -value <0.05). Results indicate that a TI paradigm with MPS models may help decoding kinematics when prior information about the task is unavailable and pave the way toward clinically viable prosthetics.

Cerebello-Cortical Differences in Effective Connectivity of the Dominant and Non-dominant Hand during a Visuomotor Paradigm of Grip Force Control.

Structural and functional differences are known to exist within the cortical sensorimotor networks with respect to the dominant vs. non-dominant hand. Similarly, the cerebellum, a key structure in the sensorimotor network with its cerebello-cortical connections, has been reported to respond differently when using the dominant vs. non-dominant hand. Several groups have already investigated causal interactions during diverse motor paradigms using effective connectivity but few have studied the larger visuomotor network, including key structures such as the parietal cortex and the cerebellum, with both hands. Moreover, the effect of force level on such interactions is still unclear. We therefore sought to determine the hemispheric asymmetries in the cerebello-cortical sensorimotor network in right-handers at two force levels (5% and 10% maximum voluntary contraction) for both hands. Cerebello-cortical modulations were investigated in 28 healthy, right-handed volunteers by determining the effective connectivity during a visuomotor task at two force levels under fMRI. A network was built consisting of the left and right primary motor (M1), ventral premotor (PMv) and posterior parietal cortices (PPC), in addition to the supplementary motor area (SMA), and the ipsilateral cerebellum (Cer) to the hand performing the motor task. Task performance (precision of isometric grip force tracking) did not differ between hands, nor did task-related activations in the sensorimotor areas apart from the contralateral primary motor cortex. However, during visuomotor control of the non-dominant hand, connectivity analysis revealed causal modulations between (i) the ipsilateral cerebellum and SMA, and (ii) the ipsilatearl cerebellum and contralateral PPC, which was not the case when using the dominant hand. These cerebello-cortical modulations for the non-dominant hand were more present at the higher of the two force levels. We conclude that precision force generation executed with the non-dominant hand, compared to the dominant hand, may require enhanced cerebello-cortical interaction to ensure equivalent left-right task performance.

Functional hemispheric asymmetries during the planning and manual control of virtual avatar movements.

Both hemispheres contribute to motor control beyond the innervation of the contralateral alpha motoneurons. The left hemisphere has been associated with higher-order aspects of motor control like sequencing and temporal processing, the right hemisphere with the transformation of visual information to guide movements in space. In the visuomotor context, empirical evidence regarding the latter has been limited though the right hemisphere’s specialization for visuospatial processing is well-documented in perceptual tasks. This study operationalized temporal and spatial processing demands during visuomotor processing and investigated hemispheric asymmetries in neural activation during the unimanual control of a visual cursor by grip force. Functional asymmetries were investigated separately for visuomotor planning and online control during functional magnetic resonance imaging in 19 young, healthy, right-handed participants. The expected cursor movement was coded with different visual trajectories. During planning when spatial processing demands predominated, activity was right-lateralized in a hand-independent manner in the inferior temporal lobe, occipito-parietal border, and ventral premotor cortex. When temporal processing demands overweighed spatial demands, BOLD responses during planning were left-lateralized in the temporo-parietal junction. During online control of the cursor, right lateralization was not observed. Instead, left lateralization occurred in the intraparietal sulcus. Our results identify movement phase and spatiotemporal demands as important determinants of dynamic hemispheric asymmetries during visuomotor processing. We suggest that, within a bilateral visuomotor network, the right hemisphere exhibits a processing preference for planning global spatial movement features whereas the left hemisphere preferentially times local features of visual movement trajectories and adjusts movement online.

Cortical Substrate of Supraspinal Fatigue following Exhaustive Aerobic Exercise Localizes to a Large Cluster in the Anterior Premotor Cortex.

Strenuous exercise leads to a progressive reduction in the performance of voluntary physical exercise. This is due to a process described as fatigue and is defined as the failure to maintain the required or expected power output. While some of this is muscular in origin, there are data suggestive of how fatigue is modulated by cortical signals, leading to a concept of central fatigue. The previously reported fatigue-induced changes in cortical activity may have been due to blood oxygen-dependent (BOLD) signal drift and/or neural habituation alone. We implemented a functional magnetic resonance imaging paradigm to effectively isolate brain areas responsible for central (supraspinal) fatigue following exercise. Our data identify a large cluster that includes dominant the anterior ventral premotor cortex (aPMv), the insula and postcentral gyrus as critical nodes in the brain network where supraspinal fatigue might have their functional neural imprints. Findings here show that activity in the ipsilateral aPMv and the adjacent areas in the premotor cortex correlates with both localized fatigue (fatigue specific hand grip contraction), and generalized full body exhaustive fatigue. In addition, from a methodological standpoint, we have also shown that the effects of BOLD signal drift can be modeled and removed to arrive at specific brain activity patterns in our experiments. Once the loci of central fatigue are isolated in this way, treatments aimed at modulating activity in these premotor areas may reduce exercise-induced fatigue and perhaps also benefit various clinical conditions in which fatigue is a major symptom.

Movement-related activity in the periarcuate cortex of monkeys during coordinated eye and hand movements.

To determine the role of the periarcuate cortex during coordinated eye and hand movements in monkeys, the present study examined neuronal activity in this region during movement with the hand, eyes, or both as effectors toward a visuospatial target. Similar to the primary motor cortex (M1), the dorsal premotor cortex contained a higher proportion of neurons that were closely related to hand movements, whereas saccade-related neurons were frequently recorded from the frontal eye field (FEF). Interestingly, neurons that exhibited activity related to both eye and hand movements were recorded most frequently in the ventral premotor cortex (PMv), located between the FEF and M1. Neuronal activity in the periarcuate cortex was highly modulated during coordinated movements compared with either eye or hand movement only. Additionally, a small number of neurons were active specifically during one of the three task modes, which could be dissociated from the effector activity. In this case, neuron onset was either ahead of or behind the onset of eye and/or hand movement, and some neuronal activity lasted until reward delivery signaled successful completion of reaching. The present findings indicate that the periarcuate cortex, particularly the PMv, plays important roles in orchestrating coordinated movements from the initiation to the termination of reaching. NEW & NOTEWORTHY Movement-related neuronal activity was recorded throughout the periarcuate cortex of monkeys that performed a task requiring them to move their hand only, eyes only, or both hand and eyes toward visuospatial targets. Most typically, neurons were found that were commonly active regardless of different effectors, from movement initiation to completion of a successful outcome. The findings suggest that the periarcuate cortex as a whole plays a crucial role in initiating and completing coordinated eye-hand movements.

Interactions Between the Corticospinal Tract and Premotor-Motor Pathways for Residual Motor Output After Stroke.

Brain imaging has continuously enhanced our understanding how different brain networks contribute to motor recovery after stroke. However, the present models are still incomplete and do not fit for every patient. The interaction between the degree of damage of the corticospinal tract (CST) and of corticocortical motor connections, that is, the influence of the microstructural state of one connection on the importance of another has been largely neglected. Applying diffusion-weighted imaging and probabilistic tractography, we investigated cross-network interactions between the integrity of ipsilesional CST and ipsilesional corticocortical motor pathways for variance in residual motor outcome in 53 patients with subacute stroke. The main finding was a significant interaction between the CST and corticocortical connections between the primary motor and ventral premotor cortex in relation to residual motor output. More specifically, the data indicate that the microstructural state of the connection primary motor-ventral premotor cortex plays only a role in patients with significant damage to the CST. In patients with slightly affected CST, this connection did not explain a relevant amount of variance in motor outcome. The present data show that patients with stroke with different degree of CST disruption differ in their dependency on structural premotor-motor connections for residual motor output. This finding might have important implications for future research on recovery prediction models and on responses to treatment strategies.

Recovery-related indicators of motor network plasticity according to impairment severity after stroke.

Brain connectivity analysis has been widely used to investigate brain plasticity and recovery-related indicators of patients with stroke. However, results remain controversial because of interindividual variability of initial impairment and subsequent recovery of function. In this study, we aimed to investigate the differences in network plasticity and motor recovery-related indicators according to initial severity. We divided participants (16 males and 14 females, aged 54.2 ± 12.0 years) into groups of different severity by Fugl-Mayer Assessment score, i.e. moderate (50-84), severe (20-49) and extremely severe (<20) impairment groups. Longitudinal resting-state functional magnetic resonance imaging data were acquired at 2 weeks and 3 months after onset. The differences in network plasticity and recovery-related indicators between groups were investigated using network distance and graph measurements. As the level of impairment increased, the network balance was more disrupted. Network balance, interhemispheric connectivity and network efficiency were recovered at 3 months only in the moderate impairment group. However, this was not the case in the extremely severe impairment group. A single connection strength between the ipsilesional primary motor cortex and ventral premotor cortex was implicated in the recovery of motor function for the extremely severe impairment group. The connections of the ipsilesional primary motor cortex-ventral premotor cortex were positively associated with motor recovery as the patients were more severely impaired. Differences in plasticity and recovery-related indicators of motor networks were noted according to impairment severity. Our results may suggest meaningful implications for recovery prediction and treatment strategies in future stroke research.

Parcellation of Macaque Cortex with Anatomical Connectivity Profiles.

The macaque model has been widely used to investigate the brain mechanisms of specific cognitive functions and psychiatric disorders. However, a detailed functional architecture map of the macaque cortex in vivo is still lacking. Here, we aimed to construct a new macaque cortex atlas based on its anatomical connectivity profiles using in vivo diffusion MRI. First, we defined the macaque cortical seed areas using the NeuroMaps atlas. Then, we applied the anatomical connectivity patterns-based parcellation approach to parcellate the macaque cortex into 80 subareas in each hemisphere, which were approximately symmetric between the two hemispheres. In each hemisphere, we identified 14 subareas in the frontal cortex, 9 subareas in the somatosensory cortex, 13 subareas in the parietal cortex, 16 subareas in the temporal cortex, 16 subareas in the occipital cortex, and 12 subareas in the limbic system. Finally, the graph-based network analyses of the anatomical network based on newly constructed macaque cortex atlas identified seven hub areas including bilateral ventral premotor cortex, bilateral superior parietal lobule, right medial precentral gyrus, and right precuneus. This newly constructed macaque cortex atlas may facilitate studies of the structure and functions of the macaque brain in the future.

An input-output linear time invariant model captures neuronal firing responses to external and behavioral events.

Investigating how neurons in different motor regions respond to external stimuli and behavioral events provides insight into motor control. A recent approach to studying neuronal activity is to construct a zero-input linear time invariant (ZI-LTI) state-space model, wherein the state vector consists of firing rate signals for different populations of neurons across motor regions. This approach allows for the populations to influence each other in a dynamical manner given an initial firing rate condition, and the model can accurately reconstruct firing rates within a limited epoch in the motor task during which no event occurs. Here, we generalize this LTI modeling approach to characterize firing responses of neurons to two events (a go cue and movement onset) in a movement task with a non-zero input LTI state-space model, herein referred to as input-output LTI (IO-LTI). Specifically, responses from 196 neurons in the primary motor (M1), ventral premotor (PMv), and dorsal premotor cortex (PMd) were recorded and modeled in two nonhuman primates executing a reach-to-grasp task. We found that a single IO-LTI model can reconstruct neuronal firing rate patterns of six populations of these neurons across the three areas in the presence of multiple events (go cue, movement onset). This is the first step towards constructing generative models of neuronal firing rates in the presence of multiple events, which then can be used to construct better decoders for brain machine interactive control.

FUNCTIONAL MRI OF TABLET-BASED COMPUTERIZED PAIRED ASSOCIATE LEARNING (PAL) WITH IMPROVED ECOLOGICAL VALIDITY

Administered with a computerized touch-screen display, PAL assists in characterizing memory and learning deficits in patients with probable early Alzheimer's disease (AD) (Blackwell Dement-Geriatr-Cogn-Disord 2003). FMRI may clarify the relationship between PAL performance and brain activity, but ecological validity is a concern during complex motor tasks. Previously, we developed an fMRI-compatible tablet including visual feedback of hand position (VFHP) and an augmented reality display (Tam HBM-2011; Karimpoor Frontiers-2015) to address this issue for AD patients with impaired motor planning (Ghilardi BrainRes-2000). The purpose of the present work is to characterize brain activity for an ecologically valid fMRI computerized PAL test. Prior to testing AD patients, initial work involved young adults. The PAL test involves making associative judgements of an increasing number of patterns (1–6 patterns) and their locations on the screen (Fig.1). Each task is repeated twice in a mixed fMRI design interspersed with baseline visual fixation. Ten young healthy right-handed adults performed PAL at 3T. The PRONTO toolkit was used to optimize fMRI preprocessing pipelines (Churchill PloSone-2015), and obtain Z-scored maps of retrieval phase vs. baseline, using a uni-variate Gauss Naïve Base (GNB) model. Principal Component Analysis (PCA) was performed on the Z-scored activation maps to obtain brain patterns explaining maximum variance across the group. Fig 2.a shows group maps during retrieval of 3 patterns (3pat) vs. baseline. Fig 2.b shows 6 patterns (6pat) vs. baseline. Increased activity in medial temporal lobe and dorsolateral prefrontal cortex is observed during 6pat compared to 3pat, consistent with the different difficulty levels. Activation of left ventral premotor cortex is consistent with visually-guided hand actions. Extensive activation of the left middle frontal gyrus, superior parietal lobule, and basal ganglia is observed during 6pat, compared to 3pat; consistent with differences in complex motor planning and visuospatial understanding. Results suggest that the fMRI-compatible tablet with VFHP enables PAL tests with good ecological validity involving complex fine motor movements. These methods and findings are relevant to future fMRI studies of AD patients; involving batteries of tasks required to probe different cognitive domains during limited scan time. fMRI-compatible PAL test. The first principal component depicting brain activity for 10 subjects performing PAL. a) Retrieval 3 patterns vs. baseline. b) Retrieval 6 patterns vs. baseline.

Visuotactile integration modulates motor performance in a perceptual decision-making task

Body ownership is critically dependent on multimodal integration as for instance revealed in the Rubber Hand Illusion (RHI) and a number of studies which have addressed the neural correlates of the processes underlying this phenomenon. Both experimental and clinical research have shown that the structures underlying body ownership seem to significantly overlap with those of motor control including the parietal and ventral premotor cortices, Temporal Parietal Junction (TPJ) and the insula. This raises the question of whether this structural overlap between body ownership and motor control structures is of any functional significance. Here, we investigate the specific question of whether experimentally induced ownership over a virtual limb can modulate the performance of that limb in a simple sensorimotor task. Using a Virtual reality (VR) environment we modulate body ownership in three experimental conditions with respect to the (in)congruence of stimulus configurations. Our results show that the degree of ownership directly modulates motor performance. This implies that body ownership is not exclusively a perceptual and/or subjective multimodal state but that it is tightly coupled to systems for decision-making and motor control.

Human neuroimaging reveals the subcomponents of grasping, reaching and pointing actions

Although the neural underpinnings of visually guided grasping and reaching have been well delineated within lateral and medial fronto-parietal networks (respectively), the contributions of subcomponents of visuomotor actions have not been explored in detail. Using careful subtraction logic, here we investigated which aspects of grasping, reaching, and pointing movements drive activation across key areas within visuomotor networks implicated in hand actions. For grasping tasks, we find activation differences based on the precision required (fine > coarse grip: anterior intraparietal sulcus, aIPS), the requirement to lift the object (grip + lift > grip: aIPS; dorsal premotor cortex, PMd; and supplementary motor area, SMA), and the number of digits employed (3-/5- vs. 2-digit grasps: ventral premotor cortex, PMv; motor cortex, M1, and somatosensory cortex, S1). For reaching/pointing tasks, we find activation differences based on whether the task required arm transport ((reach-to-point with index finger and reach-to-touch with knuckles) vs. point-without-reach; anterior superior parietal lobule, aSPL) and whether it required pointing to the object centre ((point-without-reach and reach-to-point) vs. reach-to-touch: anterior superior parieto-occipital cortex, aSPOC). For point-without-reach, in which the index finger is oriented towards the object centre but from a distance (point-without-reach > (reach-to-point and reach-to-touch)), we find activation differences that may be related to the communicative nature of the task (temporo-parietal junction, TPJ) and the need to precisely locate the target (lateral occipito-temporal cortex, LOTC). The present findings elucidate the different subcomponents of hand actions and the roles of specific brain regions in their computation.

Contrasting Modulatory Effects from the Dorsal and Ventral Premotor Cortex on Primary Motor Cortex Outputs.

The dorsal and ventral premotor cortices (PMd and PMv, respectively) each take part in unique aspects for the planning and execution of hand movements. These premotor areas are components of complex anatomical networks that include the primary motor cortex (M1) of both hemispheres. One way that PMd and PMv could play distinct roles in hand movements is by modulating the outputs of M1 differently. However, patterns of effects from PMd and PMv on the outputs of M1 have not been compared systematically. Our goals were to study how PMd within the same (i.e., ipsilateral or iPMd) and in the opposite hemisphere (i.e., contralateral or cPMd) can shape M1 outputs and then compare these effects with those induced by PMv. We used paired-pulse protocols with intracortical microstimulation techniques in sedated female cebus monkeys while recording EMG signals from intrinsic hand and forearm muscles. A conditioning stimulus was delivered in iPMd or cPMd concurrently or before a test stimulus in M1. The patterns of modulatory effects from PMd were compared with those from PMv collected in the same animals. Striking differences were revealed. Conditioning stimulation in iPMd induced more frequent and powerful inhibitory effects on M1 outputs compared with iPMv. In the opposite hemisphere, cPMd conditioning induced more frequent and powerful facilitatory effects than cPMv. These contrasting patterns of modulatory effects could allow PMd and PMv to play distinct functions for the control of hand movements and predispose them to undertake different, perhaps somewhat opposite, roles in motor recovery after brain injury.SIGNIFICANCE STATEMENT The dorsal and ventral premotor cortices (PMd and PMv, respectively) are two specialized areas involved in the control of hand movements in primates. One way that PMd and PMv could participate in hand movements is by modulating or shaping the primary motor cortex (M1) outputs to hand muscles. Here, we studied the patterns of modulation from PMd within the same and in the opposite hemisphere on the outputs of M1 and compared them with those from PMv. We found that PMd and PMv have strikingly different effects on M1 outputs. These contrasting patterns of modulation provide a substrate that may allow PMd and PMv to carry distinct functions for the preparation and execution of hand movements and for recovery after brain injury.

Neuroimaging of the speech network

Historically, the study of the neural underpinnings of speech has suffered from the lack of an animal model whose brain activity could be measured using invasive electrophysiological techniques. The development of non-invasive structural and functional neuroimaging techniques in the latter part of the 20th century has led to a dramatic improvement in our understanding of the network of brain regions responsible for speech production. Techniques for measuring regional cerebral blood flow, including positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), have illuminated the neural regions involved in various aspects of speech, including feedforward control mechanisms as well as auditory and somatosensory feedback control circuits. More recently, fMRI studies utilizing repetition suppression have been used to identify the neural representations used in different parts of the speech network, including the identification of a syllable representation in left ventral premotor cortex. Magnetic resonance imaging has also been used to investigate the anatomical structure of the speech network, providing crucial information regarding connectivity within the network as well as identifying anomalies in the sizes of neural regions and/or white matter pathways in speech disorders.

Neural foundations of overt and covert actions

We used fMRI to assess the human brain areas activated for execution, observation and 1st person motor imagery of a visually guided tracing task with the index finger. Voxel-level conjunction analysis revealed several cortical areas activated in common across all three motor conditions, namely, the upper limb representation of the primary motor and somatosensory cortices, the dorsal and ventral premotor, the superior and inferior parietal cortices as well as the posterior part of the superior and middle temporal gyrus including the temporo-parietal junction (TPj) and the extrastriate body area (EBA). Functional connectivity analyses corroborated the notion that a common sensory-motor fronto-parieto-temporal cortical network is engaged for execution, observation, and imagination of the very same action. Taken together these findings are consistent with the more parsimonious account of motor cognition provided by the mental simulation theory rather than the recently revised mirror neuron view Action imagination and observation were each associated with several additional functional connections, which may serve the distinction between overt action and its covert counterparts, and the attribution of action to the correct agent. For example, the central position of the right middle and inferior frontal gyrus in functional connectivity during motor imagery may reflect the suppression of movements during mere imagination of action, and may contribute to the distinction between ‘imagined’ and ‘real’ action. Also, the central role of the right EBA in observation, assessed by functional connectivity analysis, may be related to the attribution of action to the ‘external agent’ as opposed to the ‘self’.

SU105. Mechanisms of Yoga in Schizophrenia: Focus on Mirror Neuron Activity

Background: Schizophrenia is associated with positive symptoms, negative symptoms, and deficits in neurocognition as well as social cognition. Deficits in social cognition are more closely linked to functional outcome than general/nonsocial cognitive deficits. The “mirror-neuron system” is the substrate for social cognition and is shown to have diminished activation in schizophrenia. Of late, yoga been identified as a therapy across many psychiatric disorders, including schizophrenia. Recent understanding of mechanism of yoga in improving negative symptoms of schizophrenia could be due to enhancement of mirror neuron activation (MNA). Methods: Schizophrenia patients were offered add-on yoga therapy with ongoing medication. Subjects in yoga group underwent supervised yoga therapy for 1 month (20 sessions, 1-h duration). The control group included schizophrenia patients who received treatment as usual. Both groups were assessed on PANSS and socio-occupational functioning scale (SOFS) at the beginning and end of 1 month. Mirror neuron activity was assessed using functional Near Infra-Red Spectroscopy (fNIRS) with experimental task (action observation and action execution) before and after 1 month. Statistical analysis was done using R software. Results: There was a significantly greater increase in left ventral premotor cortex MNA in yoga therapy group (n = 7) when compared with control group (n = 7) (Mann-Whitney U = 5.0; P = .013). Conclusion: The current study provides preliminary evidence for response to yoga therapy in schizophrenia patients. Observation and imitation of yoga practices may cause changes in the activation of mirror neurons. Future studies need to systematically evaluate the same.