Biology subjects

Swinnen, S. P.

Publications and source records attributed to Swinnen, S. P..

16 recordsLinked to original sources

bioRxiv2026

Resting-state and task-related neurometabolite levels differentially relate to cortical excitability in the sensorimotor and prefrontal cortex

BackgroundNormal brain function requires a dynamic balance between inhibition and excitation. While magnetic resonance spectroscopy (MRS) quantifies the chief inhibitory and excitatory neurometabolites, GABA and glutamate-glutamine (Glx), the combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) provides a complementary measure of cortical inhibition-excitation dynamics via transcranial evoked potentials (TEPs). However, the relationship between neurometabolite concentrations and TEPs is unclear. ObjectiveTo characterize the relationship between neurometabolite concentrations and TEPs, as a function of TEP component, TMS pulse type, brain region, neurometabolite, and MRS brain state. MethodsTwenty-five young healthy adults completed a 4-day protocol. Sessions 1 and 2 involved screening, anatomical MRI, and functional MRI localization of DLPFC. In session 3, single- and paired-pulse TMS-EEG were applied over SM1 and DLPFC. Session 4 included resting-state and motor-task-related MRS of SM1 and DLPFC. ResultsIn SM1, task-related GABAergic tone strongly predicted early to mid-latency TEPs. In DLPFC, local early to mid-latency TEPs showed no relationship to neurometabolites, whereas late and global TEP outcomes revealed some links. The later N100 TEP was the only component consistently modulated by paired-pulse TMS. Task-related MRS measures consistently outperformed resting-state measures in predicting TEPs for SM1, while the opposite was true for DLPFC. ConclusionsSingle-pulse TEPs reliably index the local inhibitory tone in SM1, with limited added value from paired-pulse paradigms. These findings support the use of single-pulse TEPs as accessible markers of cortical inhibition, especially for SM1, and may inform biomarkers and strategies for individualized neuromodulation. Key point summaryO_LINormal brain function relies on a balance between inhibition and excitation, yet the relationship between local cortical neurometabolite levels and cortical excitability in humans remains poorly understood. C_LIO_LIWe measured inhibitory and excitatory neurometabolites using magnetic resonance spectroscopy and assessed cortical excitability responses to non-invasive stimulation using combined transcranial magnetic stimulation - electroencephalography (TMS-EEG). C_LIO_LIIn the primary sensorimotor cortex (SM1), local cortical responses to stimulation were best explained by inhibitory GABA levels during motor task performance. In the dorsolateral prefrontal cortex (DLPFC), global cortical responses were best predicted by resting-state neurometabolite levels. C_LIO_LIOverall, paired-pulse TMS paradigms offered little additional value over single-pulse paradigms for informing on neurometabolite levels. C_LIO_LIBy demonstrating region- and state-dependent links between neurometabolite levels and cortical excitability, our findings position TMS-EEG as an accessible biomarker of cortical inhibition, particularly in SM1. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/701225v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@132b3faorg.highwire.dtl.DTLVardef@1c5ebeeorg.highwire.dtl.DTLVardef@1048a75org.highwire.dtl.DTLVardef@11e1a4f_HPS_FORMAT_FIGEXP M_FIG C_FIG Abstract figure legendThe left panel provides a stepwise overview of the study protocol, including (i) participant screening, (ii) functional and anatomical magnetic resonance imaging (MRI) scanning for individualization purposes, (iii) single- and paired-pulse transcranial magnetic stimulation-electroencephalography (TMS-EEG), and (iv) magnetic resonance spectroscopy (MRS) acquired at rest and during a bimanual motor task. The middle and right panels show the grand-average EEG responses to single-pulse TMS over the sensorimotor cortex (SM1, red) and dorsolateral prefrontal cortex (DLPFC, blue), respectively. The topographical maps below each EEG response depict the averaged scalp distributions corresponding to each canonical transcranial evoked potential. Per region, the top left illustration shows the group-level MRS voxel placement, whereas the top right illustration shows the simulated TMS-induced electric fields. While early to mid-latency local cortical responses were best predicted by task-related GABAergic inhibition in SM1, global cortical responses following DLPFC stimulation were best predicted by resting-state neurometabolite levels.

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bioRxiv2024

Effect of interhemispheric zero-phase entrainment of the intrinsic mu-rhythm on behavioral and neural markers of predictive coding

Goal-directed behavior requires the integration of information from the outside world and internal (somatosensory) sources about our own actions. Expectations (or internal models) are generated from prior knowledge and constantly updated based on sensory feedback. This optimized information integration (predictive coding) results in a global behavioral advantage of anticipated action in the presence of uncertainty. Our goal was to probe the effect of phase entrainment of the sensorimotor mu-rhythm on visuomotor integration. Participants received transcranial alternating current stimulation over bilateral motor cortices (M1) while performing a visually-guided force adjustment task during functional magnetic resonance imaging. Inter-hemispheric zero-phase entrainment resulted in effector-specific modulation of performance precision and effector-generic minimization of force signal complexity paralleled by BOLD activation changes in bilateral caudate and increased functional connectivity between the right M1 and contralateral putamen, inferior parietal, and medial temporal regions. While effector-specific changes in performance precision were associated with contralateral caudate and hippocampal activation decreases, only the global reduction in force signal complexity was associated with increased functional M1 connectivity with bilateral striatal regions. We propose that zero-phase synchronization represents a neural mode of optimized information integration related to internal model updating within the recursive perception-action continuum associated with predictive coding.

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bioRxiv2024

Neurophysiological Correlates of Phase-Specific Enhancement of Motor Memory Consolidation via Slow-Wave Closed-Loop Targeted Memory Reactivation

Memory consolidation can be enhanced during sleep using targeted memory reactivation (TMR) and closed-loop (CL) acoustic stimulation on the up-phase of slow oscillations (SOs). Here, we tested whether applying TMR at specific phases of the SOs (up vs. down vs. no reactivation) could influence the behavioral and neural correlates of motor memory consolidation in healthy young adults. Results showed that up- (as compared to down-) state cueing resulted in greater performance improvement. Sleep electrophysiological data indicated that up-stimulated SOs exhibited higher amplitude and greater peak-nested sigma power. Task-related functional magnetic resonance images revealed that up-state cueing strengthened activity in - and segregation of - striato-motor and hippocampal networks; and that these modulations were related to the beneficial effect of TMR on sleep features and performance. Overall, these findings highlight the potential of CL-TMR to induce phase-specific modulations of motor performance, sleep oscillations and brain responses during motor memory consolidation.

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bioRxiv2021

Multimodal lesion network mapping to predict sensorimotor behavior in stroke patients

Lesion network mapping (LNM) has proved to be a successful technique to map symptoms to brain networks after acquired brain injury. Beyond the characteristics of a lesion, such as its etiology, size or location, LNM has shown that common symptoms in patients after injury may reflect the effects of their lesions on the same circuits, thereby linking symptoms to specific brain networks. Here, we extend LNM to its multimodal form, using a combination of functional and structural connectivity maps drawn from data from 1000 healthy participants in the Human Connectome Project. We applied the multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Test scores were predicted using a Canonical Correlation Analysis with multimodal brain maps as independent variables, and cross-validation strategies were employed to overcome overfitting. The results obtained led us to draw three conclusions. First, the multimodal analysis reveals how functional connectivity maps contribute more than structural connectivity maps in the optimal prediction of sensorimotor behavior. Second, the maximal association solution between the behavioral outcome and multimodal lesion connectivity maps suggests an equal contribution of sensory and motor coefficients, in contrast to the unimodal analyses where the sensory contribution dominates in both structural and functional maps. Finally, when looking at each modality individually, the performance of the structural connectivity maps strongly depends on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect of larger lesions that produce more severe sensorimotor dysfunction. By contrast, the maps of functional connectivity performed similarly irrespective of any correction for lesion size. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of imaging modalities, and the influence of their corresponding brain networks on behavioral performance after acquired brain injury.

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bioRxiv2021

High-order functional interactions in ageing explained via alterations in the connectome in a whole-brain model

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brains connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the age differences in high-order functional interactions can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modelling more complex forms of pathological ageing or cognitive deficits. Author summaryModern neuroimaging techniques allow us to study how the human brains anatomical architecture (a.k.a. structural connectome) changes under different conditions or interventions. Recently, using functional neuroimaging data, we have shown that complex patterns of interactions between brain areas change along the lifespan, exhibiting increased redundant interactions in the older population. However, the mechanisms that underlie these functional differences are still unclear. Here, we extended this work and hypothesized that the variations of functional patterns can be explained by the dynamics of the brains anatomical networks, which are known to degenerate as we age. To test this hypothesis, we implemented a whole-brain model of neuronal activity, where different brain regions are anatomically wired using real connectomes from 161 participants with ages ranging from 10 to 80 years old. Analyzing different functional aspects of brain activity when varying the empirical connectomes, we show that the increased redundancy found in the older group can indeed be explained by precise rules affecting anatomical connectivity, thus emphasizing the critical role that the brain connectome plays for shaping complex functional interactions and the efficiency in the global communication of the human brain.

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bioRxiv2021

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL, can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

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bioRxiv2020

Regional and age-dependent Effects of Cortical Magnetic Stimulation on Unconstrained Reaching Behavior

BackgroundThe specific and dynamic contributions of premotor and supplementary motor areas to reaching movements in aging humans are not well understood. ObjectiveTo better understand the role of cortical motor regions and age on the control of unconstrained reaches against gravity by neurologically intact, younger and older adults. MethodsDouble pulse transcranial magnetic stimulation (TMS) was applied at locations targeting primary motor cortex (M1), dorsal premotor area (PMA), supplementary motor area (SMA), or dorsolateral prefrontal cortex (DLPFC). Paired stimuli were delivered before or after a visual cue was presented to initiate self-paced right-handed reaches to one of three, vertically oriented target locations. ResultsRegional stimulation effects on movement amplitude were observed both early and late in the reach. PMA stimulation increased reach distance to a greater extent than M1, SMA, and DLPFC stimulation. M1 and PMA stimulation increased deviation from the straight-line path around the time of peak velocity to an extent that was greater than SMA and DLPFC stimulation. Cortical stimulation increased the time that elapsed after, but not before, peak velocity. Despite stronger effects of stimulation on reaches in the younger group, this group had shorter times to reach the target after reaching peak velocity. ConclusionThese results provide support for a role of PMA in visually guided movement after movement initiation. For older subjects, the increased time to arrive at the target after peak velocity despite weaker stimulation effects suggests an age-related reduction in sensorimotor processing flexibility for online control of unconstrained reaching. HighlightsO_LIDorsal premotor area stimulation at any time during the reaction-time period and early reaching affected early reach kinematics at least as much as stimulation of primary motor cortex. C_LIO_LIOlder individuals had more stimulation-related interference in the late components of reaching despite having less early effect of stimulation, suggesting a reduction in flexibility of dynamic motor control due to aging. C_LIO_LIThe antigravity component of unconstrained reaching did not have special aspects for regional cortical effects of stimulation. C_LI

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bioRxiv2020

Effects of beta- and gamma-band rhythmic stimulation on motor inhibition

Voluntary movements are accompanied by an increase in gamma-band oscillatory activity (60-100Hz) and a strong desynchronization of beta-band activity (13-30Hz) in the motor system at both the cortical and subcortical level. Conversely, successful motor inhibition is associated with increased beta power in a fronto-basal-ganglia network. Intriguingly, gamma activity also increases in response to a stop-signal. In this study, we used transcranial alternating current stimulation to drive beta and gamma oscillations to investigate whether these frequencies are causally related to motor inhibition. We found that 20Hz stimulation targeted at the pre-supplementary motor area enhanced inhibition and increased beta oscillatory activity around the time of the stop-signal in trials directly following stimulation. In contrast, 70Hz stimulation seemed to slow down the braking process, and predominantly affected go task performance. These results demonstrate that the effects of tACS are state-dependent and that especially fronto-central beta activity is a functional marker for successful motor inhibition.

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bioRxiv2020

Normal aging affects unconstrained three-dimensional reaching against gravity with reduced vertical precision and increased co-contraction

Reaching for an object in space forms the basis for many activities of daily living and is important in rehabilitation after stroke and in other neurological and orthopedic conditions. It has been the object of motor control and neuroscience research for over a century, but studies often constrain movement to eliminate the effect of gravity or reduce the degrees of freedom. In some studies, aging has been shown to reduce target accuracy, with a mechanism suggested to be impaired corrective movements. We sought first to explore the changes in control of shoulder and elbow joint movements that occur with aging during performance of reaching movements to different target heights with the normal effects of gravity, unconstrained hand movement, and stable target locations. Three-dimensional kinematic data and electromyography were collected in 14 young (25{+/-}6 years) and 10 older adults (68{+/-}3 years) during second-long reaches to three targets aligned vertically in front of the participants. Older adults took longer to initiate a movement than the young adults and were more variable and inaccurate in their initial and final movements. Target height had greater effect on trajectory curvature variability in older than young adults, with angle variability relative to target position being greater in older adults around the time of peak speed. There were significant age-related differences in use of the multiple degrees of freedom of the upper extremity, with less variability in shoulder abduction in the older group. Muscle activation patterns were similar, except for a higher biceps-triceps co-contraction and tonic levels of some proximal muscle activation. The path length of movements was not affected by age. These results show an age-related deficit in the motor planning and online correction of reaching movements against a predictable force (i.e., gravity). These results will facilitate interpretation of our forthcoming study of transcranial magnetic stimulation effects on the same task in these two populations, and is relevant to any study that seeks to measure the effect of pathological processes on upper extremity motor performance in the elderly.

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bioRxiv2020

Aging alters the mediating effect of endogenous GABA on the interaction between functional connectivity and motor-state transitions.

The flexible adjustment of ongoing behavior challenges the nervous systems dynamic control mechanisms and has shown to be specifically susceptible to age-related decline. Previous work links endogenous gamma-aminobutyric acid (GABA) with behavioral efficiency across perceptual and cognitive domains, with potentially the strongest impact on those behaviors that require a high level of dynamic control. Based on the integrated analyses of behavior and modulation of interhemispheric phase-based connectivity during dynamic motor state transitions and endogenous GABA concentration, we provide converging evidence for age-related differences in the behaviorally more beneficial state of endogenous GABA concentration. We suggest that the increased interhemispheric connectivity seen in the older adults represents a compensatory mechanism caused by rhythmic entrainment of neural populations in homotopic motor cortices. This mechanism appears to be most relevant in the presence of a less optimal tuning of the inhibitory tone to uphold the required flexibility of behavioral action.

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bioRxiv2020

Hippocampal and striatal responses during motor learning are modulated byprefrontal cortex stimulation

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof- of-concept study employed a comprehensive multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and striatum during motor learning. Our results indicate that stimulation influenced task-related connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

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bioRxiv2020

High-order interdependencies in the aging brain

Brain interdependencies can be studied either from a structural/anatomical perspective ("structural connectivity", SC) or by considering statistical interdependencies ("functional connectivity", FC). Interestingly, while SC is typically pairwise (white-matter fibers start in a certain region and arrive at another), FC is not; however, most FC analyses focus only on pairwise statistics and neglect high-order interactions. A promising tool to study high-order interdependencies is the recently proposed O-Information, which can quantify the intrinsic statistical synergy and redundancy in groups of three or more interacting variables. In this paper we used the O-Information to investigate how high-order statistical interdependencies are affected by age. For this, we analised functional magnetic resonance imaging (fMRI) data at rest obtained from 164 healthy participants, ranging from 10 to 80 years old. Our results show that older subjects (age ranging from 60 to 80 years) exhibit a higher predominance of redundant dependencies than younger subjects; moreover, this effect seems to be pervasive, taking place at all interaction orders. Additionally, we found that these effects are highly heterogeneous across brain regions, and suggest the existence of a "redundancy core" formed by the prefrontal and motor cortices - thus involving functions such as working memory, executive and motor functions. Our methodology to assess high-order interdependencies in fMRI data has unlimited applications. The code to calculate these metrics is freely available.

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bioRxiv2020

Low variability of dynamical functional connectivity in cerebellar networks

Brain networks can be defined and explored using different types of connectivity. Here, we studied P=48 healthy participants with neuroimaging state-of-the-art techniques and analyzed the relationship between the actual structural connectivity (SC) networks (between 2514 regions of interest covering the entire brain and brainstem) and the dynamical functional connectivity (DFC) among the same regions. To do so, we focused on a combination of two metrics: the first one measures the degree of SC-DFC similarity -i.e. how much functional correlations can be explained by structural pathways- and the second one, the intrinsic variability of DFC networks across time. Overall, we found that cerebellar networks have smaller DFC variability than other networks in the cerebrum. Moreover, our results clearly evidence the internal structure of the cerebellum, which is divided in two differentiated networks, the posterior and anterior parts, the latter also being connected to the brain stem. The mechanism for keeping the DFC variability low in the posterior part of the cerebellum is consistent with another finding, namely, it exhibits the highest SC-DFC similarity among all other sub-networks, i.e. its structure constrains very strongly its dynamics. On the other hand, the anterior part of the cerebellum, which also exhibits a low level of DFC variability, has the lowest SC-DFC similarity, suggesting very different dynamical mechanisms. It is likely that its connections with the brain stem -which regulates sleep cycles, cardiac and respiratory functioning- might have a critical role in DFC variations in the anterior part. A lot is known about cerebellar networks, such as having extremely rich and complex anatomy and functionality, connecting to the brainstem, and cerebral hemispheres, and participating in a large variety of cognitive functions, such as movement control and coordination, executive function, visual-spatial cognition, language processing, and emotional regulation. However, as far as we know, our findings of low variability in the dynamical functional connectivity of cerebellar networks and its possible relation with the above functions, have not been reported so far. Further research is still needed to shed light on these findings.

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bioRxiv2019

Skill Acquisition is Enhanced by Reducing Trial-To-Trial Repetition

Developing approaches to improve motor skill learning is of considerable interest across multiple disciplines. Previous research has typically shown that repeating the same action on consecutive trials enhances short-term performance, but has detrimental effects on longer term skill acquisition. However, most prior research has contrasted the effects of repetition only at the block level; here we examined the effects of repeating individual trials embedded in a larger randomized block a feature that is often overlooked when generating random trial orders in learning tasks. With four days of practice, a "Minimal Repeats Group", who rarely experienced repeating stimuli on consecutive trials during training improved to a greater extent than a "Frequent Repeats Group", who were frequently presented with repeating stimuli on consecutive trials during training. Our results extend the previous finding of the beneficial effects of random as compared to blocked practice on performance, showing that reduced trial-to-trial repetition during training is favorable with regards to skill learning. This research highlights that limiting the number of repeats on consecutive trials is a simple behavioral manipulation that can enhance the process of skill learning. Data/analysis code and supplementary materials available at https://osf.io/p3278/ NEW & NOTEWORTHYNumerous studies have shown that performing different sub-tasks across consecutive blocks of trials enhances learning. Here we examined whether the same effect would occur on a trial-to-trial level. Our Minimal Repeats Group, who primarily responded to different stimuli on consecutive trials, learned more than our Frequent Repeats Group, who frequently responded to the same stimulus on consecutive trials. This shows that minimizing trial-to-trial repetition is a simple and easily applicable manipulation that can enhance learning.

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bioRxiv2017

Reward and automatic processes in exercise behavior: A new approach and a systematic review

BackgroundIn a time of physical inactivity pandemic, attempts to better understand the factors underlying the regulation of exercise behavior is important. The dominant neuropsychological approach to exercise behavior explains physical activity as a reward. However, the opposite of physical exertion -- behaviors minimizing energy cost -- may also be a reward, which activates automatic reactions favoring the engagement in behaviors associated with lower energetic costs.\n\nObjectiveOur objective was to systematically review studies testing the automatic reactions triggered by stimuli associated with different types of exercise behavior (e.g., physical activity, sedentary behaviors) and energetic cost variations (e.g., behaviors minimizing energetic cost).\n\nMethodsTwo authors systematically searched, screened, extracted, and analyzed data from articles in the MEDLINE database.\n\nResultsWe included 26 studies. Three types of automatic processes were tested: Affective reactions, attentional capture, and approach tendencies. Results show that automatic reactions toward stimuli depicting exercise behaviors explained individuals level of physical activity. Brain imaging results show that stimuli associated with exercise behavior activate regions associated with reward, but these studies were scarce.\n\nConclusionReward is an important factor of exercise behavior. There is strong evidence showing that physical activity is a reward. While brain imaging results suggest that sedentary behaviors are also a reward, behaviors minimizing energetic cost have not been investigated so far. Additional studies are required to establish a strong and complete framework of reward in exercise behavior.\n\nKey points- Behavioral and brain imaging studies using different types of automatic behavior show that physical activity is a reward\n- Behaviors minimizing energetic cost have been essential to evolutionary survival and are likely to be a reward. However, experimental evidence remains scarce\n- The dominant neuropsychological approaches to exercise behavior may be incomplete, which may partly explain our current inability to counteract the pandemic of physical inactivity

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bioRxiv2017

Neural Correlates of Motor Imagery, Action Observation, and Movement Execution: A Comparison Across Quantitative Meta-Analyses

There is longstanding interest in the relationship between motor imagery, action observation, and movement execution. Several models propose that these tasks recruit the same brain regions in a similar manner; however, there is no quantitative synthesis of the literature that compares their respective networks. Here we summarized data from neuroimaging experiments examining Motor Imagery (303 experiments, 4,902 participants), Action Observation (595 experiments, 11,032 participants), and related control tasks involving Movement Execution (142 experiments, 2,302 participants). Motor Imagery recruited a network of premotor-parietal cortical regions, alongside the thalamus, putamen, and cerebellum. Action Observation involved a cortical premotor-parietal and occipital network, with no consistent subcortical contributions. Movement Execution engaged sensorimotor-premotor areas, and the thalamus, putamen, and cerebellum. Comparisons across these networks highlighted key differences in their recruitment of motor cortex,and parietal cortex, and subcortical structures. Conjunction across all three tasks identified a consistent premotor-parietal and somatosensory network. These data amend previous models of the relationships between motor imagery, action observation, and movement execution, and quantify the relationships between their respective networks.\n\nHighlightsO_LIWe compared quantitative meta-analyses of movement imagery, observation, and execution\nC_LIO_LISubcortical structures were most commonly associated with imagery and execution\nC_LIO_LIConjunctions identified a consistent premotor-parietal-somatosensory network\nC_LIO_LIThese data can inform basic and translational work using imagery and observation\nC_LI

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