scholarly journals A Revised Computational Neuroanatomy for Motor Control

2020 ◽  
Vol 32 (10) ◽  
pp. 1823-1836 ◽  
Author(s):  
Shlomi Haar ◽  
Opher Donchin
Keyword(s):  
Motor Control ◽  
Posterior Parietal Cortex ◽  
Motor Behavior ◽  
Premotor Cortex ◽  
Computational Neuroanatomy ◽  
Posterior Parietal ◽  
Optimal Information ◽  
Parietal Cortices ◽  
Recent Claim ◽  
New Framework

We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical–subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes that each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and BG. These subcortical areas are thus engaged in domain-appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modeled? We suggest that one fundamental division is between modeling of task and body whereas another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

scholarly journals A revised computational neuroanatomy for motor control

2019 ◽  
Author(s):  
Shlomi Haar ◽  
Opher Donchin
Keyword(s):  
Motor Control ◽  
Posterior Parietal Cortex ◽  
Motor Behavior ◽  
Premotor Cortex ◽  
Computational Neuroanatomy ◽  
Posterior Parietal ◽  
Optimal Information ◽  
Parietal Cortices ◽  
Recent Claim ◽  
New Framework

We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical-subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and basal ganglia. These subcortical areas are thus engaged in domain appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modelled? We suggest that one fundamental division is between modelling of task and body while another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

scholarly journals Dynamic Parieto-premotor Network for Mental Image Transformation Revealed by Simultaneous EEG and fMRI Measurement

2014 ◽  
Vol 26 (2) ◽  
pp. 232-246 ◽  
Author(s):  
Takafumi Sasaoka ◽  
Hiroaki Mizuhara ◽  
Toshio Inui
Keyword(s):  
Mental Rotation ◽  
Posterior Parietal Cortex ◽  
Premotor Cortex ◽  
Mental Image ◽  
Image Transformation ◽  
Temporal Properties ◽  
Posterior Parietal ◽  
Spatio Temporal ◽  
The Right ◽  
Parietal Cortices

Previous studies have suggested that the posterior parietal cortices and premotor areas are involved in mental image transformation. However, it remains unknown whether these regions really cooperate to realize mental image transformation. In this study, simultaneous EEG and fMRI were performed to clarify the spatio-temporal properties of neural networks engaged in mental image transformation. We adopted a modified version of the mental clock task used by Sack et al. [Sack, A. T., Camprodon, J. A., Pascual-Leone, A., & Goebel, R. The dynamics of interhemispheric compensatory processes in mental imagery. Science, 308, 702–704, 2005; Sack, A. T., Sperling, J. M., Prvulovic, D., Formisano, E., Goebel, R., Di Salle, F., et al. Tracking the mind's image in the brain II: Transcranial magnetic stimulation reveals parietal asymmetry in visuospatial imagery. Neuron, 35, 195–204, 2002]. In the modified mental clock task, participants mentally rotated clock hands from the position initially presented at a learned speed for various durations. Subsequently, they matched the position to the visually presented clock hands. During mental rotation of the clock hands, we observed significant beta EEG suppression with respect to the amount of mental rotation at the right parietal electrode. The beta EEG suppression accompanied activity in the bilateral parietal cortices and left premotor cortex, representing a dynamic cortical network for mental image transformation. These results suggest that motor signals from the premotor area were utilized for mental image transformation in the parietal areas and for updating the imagined clock hands represented in the right posterior parietal cortex.

scholarly journals Probing the interaction of the ipsilateral posterior parietal cortex with the premotor cortex using a novel transcranial magnetic stimulation technique

2016 ◽  
Vol 127 (2) ◽  
pp. 1475-1480 ◽  
Author(s):  
Jessica Shields ◽  
Jung E. Park ◽  
Prachaya Srivanitchapoom ◽  
Rainer Paine ◽  
Nivethida Thirugnanasambandam ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Parietal Cortex ◽  
Magnetic Stimulation ◽  
Posterior Parietal Cortex ◽  
Premotor Cortex ◽  
Posterior Parietal ◽  
Stimulation Technique

scholarly journals Rubber hand illusion modulates the influences of somatosensory and parietal inputs to the motor cortex

2019 ◽  
Vol 121 (2) ◽  
pp. 563-573 ◽  
Author(s):  
Reina Isayama ◽  
Michael Vesia ◽  
Gaayathiri Jegatheeswaran ◽  
Behzad Elahi ◽  
Carolyn A. Gunraj ◽  
...  
Keyword(s):  
Motor Control ◽  
Motor Cortex ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Rubber Hand Illusion ◽  
Body Ownership ◽  
Rubber Hand ◽  
Functional Connections ◽  
Afferent Inhibition ◽  
Posterior Parietal

The rubber hand illusion (RHI) paradigm experimentally produces an illusion of rubber hand ownership and arm shift by simultaneously stroking a rubber hand in view and a participant’s visually occluded hand. It involves visual, tactile, and proprioceptive multisensory integration and activates multisensory areas in the brain, including the posterior parietal cortex (PPC). Multisensory inputs are transformed into outputs for motor control in association areas such as PPC. A behavioral study reported decreased motor performance after RHI. However, it remains unclear whether RHI modifies the interactions between sensory and motor systems and between PPC and the primary motor cortex (M1). We used transcranial magnetic stimulation (TMS) and examined the functional connections from the primary somatosensory and association cortices to M1 and from PPC to M1 during RHI. In experiment 1, short-latency afferent inhibition (SAI) and long-latency afferent inhibition (LAI) were measured before and immediately after a synchronous (RHI) or an asynchronous (control) condition. In experiment 2, PPC-M1 interaction was measured using two coils. We found that SAI and LAI were reduced in the synchronous condition compared with baseline, suggesting that RHI decreased somatosensory processing in the primary sensory and the association cortices projecting to M1. We also found that greater inhibitory PPC-M1 interaction was associated with stronger RHI assessed by questionnaire. Our findings suggest that RHI modulates both the early and late stages of processing of tactile afferent, which leads to altered M1 excitability by reducing the gain of somatosensory afferents to resolve conflicts among multisensory inputs. NEW & NOTEWORTHY Perception of one’s own body parts involves integrating different sensory information and is important for motor control. We found decreased effects of cutaneous stimulation on motor cortical excitability during rubber hand illusion (RHI), which may reflect decreased gain of tactile input to resolve multisensory conflicts. RHI strength correlated with the degree of inhibitory posterior parietal cortex-motor cortex interaction, indicating that parietal-motor connection is involved in resolving sensory conflicts and body ownership during RHI.

scholarly journals Functional versus effector-specific organization of the human posterior parietal cortex: revisited

2016 ◽  
Vol 116 (4) ◽  
pp. 1885-1899 ◽  
Author(s):  
Tobias Heed ◽  
Frank T. M. Leone ◽  
Ivan Toni ◽  
W. Pieter Medendorp
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Premotor Cortex ◽  
Action Representation ◽  
Functional Versus ◽  
Activation Patterns ◽  
Fine Grained ◽  
Fmri Signal ◽  
Repetition Suppression ◽  
Posterior Parietal

It has been proposed that the posterior parietal cortex (PPC) is characterized by an effector-specific organization. However, strikingly similar functional MRI (fMRI) activation patterns have been found in the PPC for hand and foot movements. Because the fMRI signal is related to average neuronal activity, similar activation levels may result either from effector-unspecific neurons or from intermingled subsets of effector-specific neurons within a voxel. We distinguished between these possibilities using fMRI repetition suppression (RS). Participants made delayed, goal-directed eye, hand, and foot movements to visual targets. In each trial, the instructed effector was identical or different to that of the previous trial. RS effects indicated an attenuation of the fMRI signal in repeat trials. The caudal PPC was active during the delay but did not show RS, suggesting that its planning activity was effector independent. Hand and foot-specific RS effects were evident in the anterior superior parietal lobule (SPL), extending to the premotor cortex, with limb overlap in the anterior SPL. Connectivity analysis suggested information flow between the caudal PPC to limb-specific anterior SPL regions and between the limb-unspecific anterior SPL toward limb-specific motor regions. These results underline that both function and effector specificity should be integrated into a concept of PPC action representation not only on a regional but also on a fine-grained, subvoxel level.

scholarly journals Human posterior parietal cortex encodes the movement goal in a pro-/anti-reach task

2015 ◽  
Vol 114 (1) ◽  
pp. 170-183 ◽  
Author(s):  
Hanna Gertz ◽  
Katja Fiehler
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Premotor Cortex ◽  
Imaging Study ◽  
Visual Cue ◽  
Frontoparietal Network ◽  
Electrophysiological Studies ◽  
Posterior Parietal ◽  
Reach Planning ◽  
Premotor Areas

Previous research on reach planning in humans has implicated a frontoparietal network, including the precuneus (PCu), a putative human homolog of the monkey parietal reach region (PRR), and the dorsal premotor cortex (PMd). Using a pro-/anti-reach task, electrophysiological studies in monkeys have demonstrated that the movement goal rather than the location of the visual cue is encoded in PRR and PMd. However, if only the effector but not the movement goal is specified (underspecified condition), the PRR and PMd have been shown to represent all potential movement goals. In this functional magnetic resonance imaging study, we investigated whether the human PCu and PMd likewise encode the movement goal, and whether these reach-related areas also engage in situations with underspecified compared with specified movement goals. By using a pro-/anti-reach task, we spatially dissociated the location of the visual cue from the location of the movement goal. In the specified conditions, pro- and anti-reaches activated similar parietal and premotor areas. In the PCu contralateral to the moving arm, we found directionally selective activation fixed to the movement goal. In the underspecified conditions, we observed activation in reach-related areas of the posterior parietal cortex, including PCu. However, the activation was substantially weaker in parietal areas and lacking in PMd. Our results suggest that human PCu encodes the movement goal rather than the location of the visual cue if the movement goal is specified and even engages in situations when only the visual cue but not the movement goal is defined.

Evidence for Anticipatory Motor Control within a Cerebello-Diencephalic-Parietal Network

2008 ◽  
Vol 20 (5) ◽  
pp. 828-840 ◽  
Author(s):  
Bettina Pollok ◽  
Joachim Gross ◽  
Daniel Kamp ◽  
Alfons Schnitzler
Keyword(s):  
Motor Control ◽  
Functional Connectivity ◽  
Internal Model ◽  
Posterior Parietal Cortex ◽  
Phase Synchronization ◽  
Functional Interaction ◽  
Feedback Processing ◽  
Spatially Distributed ◽  
Posterior Parietal ◽  
Anticipatory Motor Control

The posterior parietal cortex and the cerebellum are assumed to contribute to anticipatory motor control. Thus, it is reasonable that these areas act as a functional unit. To identify a neural signature of anticipatory motor control, 11 healthy volunteers performed a bimanual finger-tapping task with respect to isochronous (i.e., regular) and randomized (i.e., irregular) auditory pacing. Neuromagnetic activity was recorded using a 122-channel whole-head neuromagnetometer. Functional interaction between spatially distributed brain areas was determined by measures of tap-related phase synchronization. Assuming that (i) the cerebellum predicts sensory events by an internal model and (ii) the PPC maintains this prediction, we hypothesized that functional interaction between both structures varies depending on the predictability of the pacing signal. During isochronous pacing, functional connectivity within a cerebello-diencephalic-parietal network before tap onset was evident, suggesting anticipatory motor control. During randomized pacing, however, functional connectivity after tap onset was increased within a parietal-cerebellar loop, suggesting mismatch detection and update of the internal model. Data of the present study imply that anticipatory motor control is implemented in a network-like manner. Our data agree well with the hypothesis that functional connectivity in a cerebello-diencephalic-parietal loop might be crucial for anticipatory motor control, whereas parietal-cerebellar interaction might be critical for feedback processing.

Integration of Target and Effector Information in the Human Brain During Reach Planning

2007 ◽  
Vol 97 (1) ◽  
pp. 188-199 ◽  
Author(s):  
S. M. Beurze ◽  
F. P. de Lange ◽  
I. Toni ◽  
W. P. Medendorp
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Human Subjects ◽  
Premotor Cortex ◽  
Insular Cortex ◽  
Spatial Location ◽  
Posterior Parietal ◽  
The Right ◽  
Integrative Processing ◽  
Reach Planning

To plan a reaching movement, the brain must integrate information about the location of the target with information about the limb selected for the reach. Here, we applied rapid event-related 3-T fMRI to investigate this process in human subjects ( n = 16) preparing a reach following two successive visual instruction cues. One cue instructed which arm to use; the other cue instructed the location of the reach target. We hypothesized that regions involved in the integration of target and effector information should not only respond to each of the two instruction cues, but should respond more strongly to the second cue due to the added integrative processing to establish the reach plan. We found bilateral regions in the posterior parietal cortex, the premotor cortex, the medial frontal cortex, and the insular cortex to be involved in target–arm integration, as well as the left dorsolateral prefrontal cortex and an area in the right lateral occipital sulcus to respond in this manner. We further determined the functional properties of these regions in terms of spatial and effector specificity. This showed that the posterior parietal cortex and the dorsal premotor cortex specify both the spatial location of a target and the effector selected for the response. We therefore conclude that these regions are selectively engaged in the neural computations for reach planning, consistent with the results from physiological studies in nonhuman primates.

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