Common and specific activations supporting optic flow processing and navigation as revealed by a meta-analysis of neuroimaging studies.

Optic flow provides useful information in service of spatial navigation. However, whether brain networks supporting these two functions overlap is still unclear. Here we used Activation Likelihood Estimation (ALE) to assess the correspondence between brain correlates of optic flow processing and spatial navigation and their specific neural activations. Since computational and connectivity evidence suggests that visual input from optic flow provides information mainly during egocentric navigation, we further tested the correspondence between brain correlates of optic flow processing and that of both egocentric and allocentric navigation. Optic flow processing shared activation with egocentric (but not allocentric) navigation in the anterior precuneus, suggesting its role in providing information about self-motion, as derived from the analysis of optic flow, in service of egocentric navigation. We further documented that optic flow perception and navigation are partially segregated into two functional and anatomical networks, i.e., the dorsal and the ventromedial networks. Present results point to a dynamic interplay between the dorsal and ventral visual pathways aimed at coordinating visually guided navigation in the environment.

Neural sensitivity to translational self- and object-motion velocities.

The ability to detect and assess world-relative object-motion is a critical computation performed by the visual system. This computation, however, is greatly complicated by the observer's movements, which generate a global pattern of motion on the observer's retina. How the visual system implements this computation is poorly understood. Since we are potentially able to detect a moving object if its motion differs in velocity (or direction) from the expected optic flow generated by our own motion, here we manipulated the relative motion velocity between the observer and the object within a stationary scene as a strategy to test how the brain accomplishes object-motion detection. Specifically, we tested the neural sensitivity of brain regions that are known to respond to egomotion-compatible visual motion (i.e., egomotion areas: cingulate sulcus visual area, posterior cingulate sulcus area, posterior insular cortex [PIC], V6+, V3A, IPSmot/VIP, and MT+) to a combination of different velocities of visually induced translational self- and object-motion within a virtual scene while participants were instructed to detect object-motion. To this aim, we combined individual surface-based brain mapping, task-evoked activity by functional magnetic resonance imaging, and parametric and representational similarity analyses. We found that all the egomotion regions (except area PIC) responded to all the possible combinations of self- and object-motion and were modulated by the self-motion velocity. Interestingly, we found that, among all the egomotion areas, only MT+, V6+, and V3A were further modulated by object-motion velocities, hence reflecting their possible role in discriminating between distinct velocities of self- and object-motion. We suggest that these egomotion regions may be involved in the complex computation required for detecting scene-relative object-motion during self-motion.

Functional organization of the caudal part of the human superior parietal lobule.

Like in macaque, the caudal portion of the human superior parietal lobule (SPL) plays a key role in a series of perceptive, visuomotor and somatosensory processes. Here, we review the functional properties of three separate portions of the caudal SPL, i.e., the posterior parieto-occipital sulcus (POs), the anterior POs, and the anterior part of the caudal SPL. We propose that the posterior POs is mainly dedicated to the analysis of visual motion cues useful for object motion detection during self-motion and for spatial navigation, while the more anterior parts are implicated in visuomotor control of limb actions. The anterior POs is mainly involved in using the spotlight of attention to guide reach-to-grasp hand movements, especially in dynamic environments. The anterior part of the caudal SPL plays a central role in visually guided locomotion, being implicated in controlling leg-related movements as well as the four limbs interaction with the environment, and in encoding egomotion-compatible optic flow. Together, these functions reveal how the caudal SPL is strongly implicated in skilled visually-guided behaviors.

Visuo-spatial attention and semantic memory competition in the parietal cortex.

Neuroimaging studies associate specific functional roles to distinct brain regions investigating separate cognitive processes using dedicated tasks. For example, using both correlative (i.e., fMRI) and causal (i.e., TMS) approaches it has been shown the involvement of intra-parietal sulcus (IPS), as part of the dorsal attention network, in spatial attentional tasks as well as the importance of the angular gyrus (AG), as part of the default mode network, during the selection of relevant information in semantic memory. Nonetheless, in our daily life attention and semantic memory are rarely needed in isolation. In the present TMS study we investigate how the brain combines attentional and semantic memory demands in a single task. Results showed that, compared to a pseudo-TMS, stimulation of IPS, but not AG, affects behavioral performance, thus suggesting its preponderant role in such a combined task. Moreover, the lack of difference between the effect of IPS and AG stimulations seems to suggest that the two regions may be coactivated or that a third-party source might indirectly mediate the interaction between the two networks.

Interhemispheric interplay between the left and right premotor cortex during grasping as assessed by dynamic causal modelling.

Research on the contribution of the ipsilateral hemisphere to unilateral movements, and how it is mediated by transcallosal connections, has so far provided contradictory findings. By using dynamic causal modelling (DCM) and Parametric Empirical Bayes analyses applied to fMRI data, we sought to describe effective connectivity during pantomimed and imagined right-hand grasping within the grasping network, namely the anterior intraparietal sulcus, ventral and dorsal (PMd) premotor cortex, supplementary motor area and primary motor cortex (M1). The two-fold aim of the present work was to explore a) whether right and left parieto-frontal areas show similar connectivity couplings, and b) the interhemispheric dynamics between these regions across the two hemispheres. We detected a network architecture comparable across hemispheres during executed but not imagined grasping movements. Furthermore, during pantomimed grasping the interhemispheric crosstalk was mainly driven by premotor areas: we found an inhibitory influence from the right PMd toward the left premotor and motor areas and excitatory couplings between homologous ventral premotor and supplementary motor regions. Overall, our results support the view that dissociable components of unilateral grasping execution are encoded by a non-lateralized set of brain areas complexly intertwined by interhemispheric dynamics, whereas motor imagery obeys different principles.

Effect of optic flow on spatial updating: insight from an immersive virtual reality study.

Self-motion information is required to keep track of where we are with respect to our environment (spatial updating). Visual signals such as optic flow are relevant to provide information about self-motion, especially in the absence of vestibular and/or proprioceptive cues generated by physical movement. However, the role of optic flow on spatial updating is still debated. A virtual reality system based on a head-mounted display was used to allow participants to experience a self-motion sensation within a naturalistic environment in the absence of physical movement. We asked participants to keep track of spatial positions of a target during simulated self-motion while manipulating the availability of optic flow coming from the lower part of the environment (ground plane). In each trial, the ground could be a green lawn (optic flow ON) or covered in snow (optic flow OFF). We observed that the lack of optic flow on the ground had a detrimental effect on spatial updating. Furthermore, we explored the interaction between the optic flow availability and different characteristics of self-motion: we observed that increasing self-motion speed had a detrimental effect on spatial updating, especially in the absence of optic flow, while self-motion direction (leftward, forward, rightward) and path (translational and curvilinear) had no statically significant effect. Overall, we demonstrated that, in the absence of some idiothetic cues, the optic flow provided by the ground has a dominant role for the self-motion estimation and, hence, for the ability to update the spatial relationships between one's position and the position of the surrounding objects.

The human middle temporal cortex responds to both active leg movements and egomotion-compatible visual motion.

The human middle-temporal region MT+ is highly specialized in processing visual motion. However, recent studies have shown that this region is modulated by extraretinal signals, suggesting a possible involvement in processing motion information also from non-visual modalities. Here, we used functional MRI data to investigate the influence of retinal and extraretinal signals on MT+ in a large sample of subjects. Moreover, we used resting-state functional MRI to assess how the subdivisions of MT+ (i.e., MST, FST, MT, and V4t) are functionally connected. We first compared responses in MST, FST, MT, and V4t to coherent vs. random visual motion. We found that only MST and FST were positively activated by coherent motion. Furthermore, regional analyses revealed that MST and FST were positively activated by leg, but not arm, movements, while MT and V4t were deactivated by arm, but not leg, movements. Taken together, regional analyses revealed a visuomotor role for the anterior areas MST and FST and a pure visual role for the anterior areas MT and V4t. These findings were mirrored by the pattern of functional connections between these areas and the rest of the brain. Visual and visuomotor regions showed distinct patterns of functional connectivity, with the latter preferentially connected with the somatosensory and motor areas representing leg and foot. Overall, these findings reveal a functional sensitivity for coherent visual motion and lower-limb movements in MST and FST, suggesting their possible involvement in integrating sensory and motor information to perform locomotion.

Egomotion-related visual areas respond to goal-directed movements.

Integration of proprioceptive signals from the various effectors with visual feedback of self-motion from the retina is necessary for whole-body movement and locomotion. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by goal-directed movements (as saccades or pointing) performed with different effectors (eye, hand, and foot), suggesting a role in visually guiding movements through the external environment. To achieve this aim, we used a combined approach of task-evoked activity and effective connectivity (PsychoPhysiological Interaction, PPI) by fMRI. We localized a set of six egomotion-responsive visual areas through the flow field stimulus and distinguished them into visual (pIPS/V3A, V6+ , IPSmot/VIP) and visuomotor (pCi, CSv, PIC) areas according to recent literature. We tested their response to a visuomotor task implying spatially directed delayed eye, hand, and foot movements. We observed a posterior-to-anterior gradient of preference for eye-to-foot movements, with posterior (visual) regions showing a preference for saccades, and anterior (visuomotor) regions showing a preference for foot pointing. No region showed a clear preference for hand pointing. Effective connectivity analysis showed that visual areas were more connected to each other with respect to the visuomotor areas, particularly during saccades. We suggest that visual and visuomotor egomotion regions can play different roles within a network that integrates sensory-motor signals with the aim of guiding movements in the external environment.

Individual differences in mental imagery modulate effective connectivity of scene-selective regions during resting state.

Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals' ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex, and Occipital Place Area (OPA) using Dynamic Causal Modelling for resting-state functional magnetic resonance data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire. We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

Reduced Priming Effect for Visual-Spatial Perspective Taking in Patients With Severe Acquired Brain Injury.

OBJECTIVE: Social cognition can be impaired after a severe acquired brain injury (sABI), but mechanisms potentially underlying these difficulties remain to be clarified. This study aimed at investigating perspective taking ability in individuals with sABI. METHOD: Twenty individuals with sABI and 20 healthy controls (HCs) have been enrolled in this case-control study. All participants were submitted to an experimental visual-spatial priming memory procedure and a self-report assessment of perspective taking (i.e., the Interpersonal Reactivity Index [IRI]). Individuals with sABI were submitted to neuropsychological tests to assess executive subcomponents, working memory, and visual attention. RESULTS: The analysis on self-report scales data documents a significant between groups difference in the IRI-Fantasy subscale, with HCs showing a higher tendency to imaginatively transpose oneself into fictional situations than individuals with sABI. Analysis of performance on the experimental procedure revealed the priming effect in HCs but not in sABI individuals. Moreover, individuals with sABI performed significantly poorer than HCs on the indices of the experimental procedure. CONCLUSIONS: Our data preliminarily demonstrated that visual-spatial perspective taking is reduced after sABI. Findings above could give some clues for the rehabilitative intervention in sABI and suggest the possible application of the procedure here used in assessing perspective taking after sABI.

Multisensory integration in cortical regions responding to locomotion-related visual and somatomotor signals.

During real-world locomotion, in order to be able to move along a path or avoid an obstacle, continuous changes in self-motion direction (i.e. heading) are needed. Control of heading changes during locomotion requires the integration of multiple signals (i.e., visual, somatomotor, vestibular). Recent fMRI studies have shown that both somatomotor areas (human PEc [hPEc], human PE [hPE], primary somatosensory cortex [S-I]) and egomotion visual regions (cingulate sulcus visual area [CSv], posterior cingulate area [pCi], posterior insular cortex [PIC]) respond to either leg movements and egomotion-compatible visual stimulations, suggesting a role in the analysis of both visual attributes of egomotion and somatomotor signals with the aim of guiding locomotion. However, whether these regions are able to integrate egomotion-related visual signals with somatomotor inputs coming from leg movements during heading changes remains an open question. Here we used a combined approach of individual functional localizers and task-evoked activity by fMRI. In thirty subjects we first localized three egomotion areas (CSv, pCi, PIC) and three somatomotor regions (S-I, hPE, hPEc). Then, we tested their responses in a multisensory integration experiment combining visual and somatomotor signals relevant to locomotion in congruent or incongruent trials. We used an fMR-adaptation paradigm to explore the sensitivity to the repeated presentation of these bimodal stimuli in the six regions of interest. Results revealed that hPE, S-I and CSv showed an adaptation effect regardless of congruency, while PIC, pCi and hPEc showed sensitivity to congruency. PIC exhibited a preference for congruent trials compared to incongruent trials. Areas pCi and hPEc exhibited an adaptation effect only for congruent and incongruent trials, respectively. PIC, pCi and hPEc sensitivity to the congruency relationship between visual (locomotion-compatible) cues and (leg-related) somatomotor inputs suggests that these regions are involved in multisensory integration processes, likely in order to guide/adjust leg movements during heading changes.

Neural representations underlying mental imagery as unveiled by representation similarity analysis.

It is commonly acknowledged that visual imagery and perception rely on the same content-dependent brain areas in the high-level visual cortex (HVC). However, the way in which our brain processes and organizes previous acquired knowledge to allow the generation of mental images is still a matter of debate. Here, we performed a representation similarity analysis of three previous fMRI experiments conducted in our laboratory to characterize the neural representation underlying imagery and perception of objects, buildings and faces and to disclose possible dissimilarities in the neural structure of such representations. To this aim, we built representational dissimilarity matrices (RDMs) by computing multivariate distances between the activity patterns associated with each pair of stimuli in the content-dependent areas of the HVC and HC. We found that spatial information is widely coded in the HVC during perception (i.e. RSC, PPA and OPA) and imagery (OPA and PPA). Also, visual information seems to be coded in both preferred and non-preferred regions of the HVC, supporting a distributed view of encoding. Overall, the present results shed light upon the spatial coding of imagined and perceived exemplars in the HVC.

Lower visual field preference for the visuomotor control of limb movements in the human dorsomedial parietal cortex.

Visual cues coming from the lower visual field (VF) play an important role in the visual guidance of upper and lower limb movements. A recently described region situated in the dorsomedial parietal cortex, area hPEc (Pitzalis et al. in NeuroImage 202:116092, 2019), might have a role in integrating visually derived information with somatomotor signals to guide limb interaction with the environment. In macaque, it has been demonstrated that PEc receives visual information mostly from the lower visual field but, to date, there has been no systematic investigation of VF preference in the newly defined human homologue of macaque area PEc (hPEc). Here we examined the VF preferences of hPEc while participants performed a visuomotor task implying spatially directed delayed eye-, hand- and foot-movements towards different spatial locations within the VF. By analyzing data as a function of the different target locations towards which upcoming movements were planned (and then executed), we observed the presence of asymmetry in the vertical dimension of VF in area hPEc, being this area more strongly activated by limb movements directed towards visual targets located in the lower compared to the upper VF. This result confirms the view, first advanced in macaque monkey, that PEc is involved in processing visual information to guide body interaction with the external environment, including locomotion. We also observed a contralateral dominance for the lower VF preference in the foot selective somatomotor cortex anterior to hPEc. This result might reflect the role of this cortex (which includes areas PE and S-I) in providing highly topographically organized signals, likely useful to achieve an appropriate foot posture during locomotion.

Preference for locomotion-compatible curved paths and forward direction of self-motion in somatomotor and visual areas.

During locomotion, leg movements define the direction of walking (forward or backward) and the path one is taking (straight or curved). These aspects of locomotion produce characteristic visual motion patterns during movement. Here, we tested whether cortical regions responding to either egomotion-compatible visual motion, or leg movements, or both, are sensitive to these locomotion-relevant aspects of visual motion. We compared a curved path (typically the visual feedback of a changing direction of movement in the environment) to a linear path for simulated forward and backward motion in an event-related fMRI experiment. We used an individual surface-based approach and two functional localizers to define (1) six egomotion-related areas (V6+, V3A, intraparietal motion area [IPSmot], cingulate sulcus visual area [CSv], posterior cingulate area [pCi], posterior insular cortex [PIC]) using the flow field stimulus and (2) three leg-related cortical regions (human PEc [hPEc], human PE [hPE] and primary somatosensory cortex [S-I]) using a somatomotor task. Then, we extracted the response from all these regions with respect to the main event-related fMRI experiment, consisting of passive viewing of an optic flow stimulus, simulating a forward or backward direction of self-motion in either linear or curved path. Results showed that some regions have a significant preference for the curved path motion (hPEc, hPE, S-I, IPSmot) or a preference for the forward motion (V3A), while other regions have both a significant preference for the curved path motion and for the forward compared to backward motion (V6+, CSv, pCi). We did not find any significant effects of the present stimuli in PIC. Since controlling locomotion mainly means controlling changes of walking direction in the environment during forward self-motion, such a differential functional profile among these cortical regions suggests that they play a differentiated role in the visual guidance of locomotion.

Assessing the effective connectivity of premotor areas during real vs imagined grasping: a DCM-PEB approach.

The parieto-frontal circuit underlying grasping, which requires the serial involvement of the anterior intraparietal area (aIPs) and the ventral premotor cortex (PMv), has been recently extended enlightening the role of the dorsal premotor cortex (PMd). The supplementary motor area (SMA) has been also suggested to encode grip force for grasping actions; furthermore, both PMd and SMA are known to play a crucial role in motor imagery. Here, we aimed at assessing the dynamic couplings between left aIPs, PMv, PMd, SMA and primary motor cortex (M1) by comparing executed and imagined right-hand grasping, using Dynamic Causal Modelling (DCM) and Parametrical Empirical Bayes (PEB) analyses. 24 subjects underwent an fMRI exam (3T) during which they were asked to perform or imagine a grasping movement visually cued by photographs of commonly used objects. We tested whether the two conditions a) exert a modulatory effect on both forward and feedback couplings among our areas of interest, and b) differ in terms of strength and sign of these parameters. Results of the real condition confirmed the serial involvement of aIPs, PMv and M1. PMv also exerted a positive influence on PMd and SMA, but received an inhibitory feedback only from PMd. Our results suggest that a general motor program for grasping is planned by the aIPs-PMv circuit; then, PMd and SMA encode high-level features of the movement. During imagery, the connection strength from aIPs to PMv was weaker and the information flow stopped in PMv; thus, a less complex motor program was planned. Moreover, results suggest that SMA and PMd cooperate to prevent motor execution. In conclusion, the comparison between execution and imagery reveals that during grasping premotor areas dynamically interplay in different ways, depending on task demands.

A common neural substrate for processing scenes and egomotion-compatible visual motion.

Neuroimaging studies have revealed two separate classes of category-selective regions specialized in optic flow (egomotion-compatible) processing and in scene/place perception. Despite the importance of both optic flow and scene/place recognition to estimate changes in position and orientation within the environment during self-motion, the possible functional link between egomotion- and scene-selective regions has not yet been established. Here we reanalyzed functional magnetic resonance images from a large sample of participants performing two well-known "localizer" fMRI experiments, consisting in passive viewing of navigationally relevant stimuli such as buildings and places (scene/place stimulus) and coherently moving fields of dots simulating the visual stimulation during self-motion (flow fields). After interrogating the egomotion-selective areas with respect to the scene/place stimulus and the scene-selective areas with respect to flow fields, we found that the egomotion-selective areas V6+ and pIPS/V3A responded bilaterally more to scenes/places compared to faces, and all the scene-selective areas (parahippocampal place area or PPA, retrosplenial complex or RSC, and occipital place area or OPA) responded more to egomotion-compatible optic flow compared to random motion. The conjunction analysis between scene/place and flow field stimuli revealed that the most important focus of common activation was found in the dorsolateral parieto-occipital cortex, spanning the scene-selective OPA and the egomotion-selective pIPS/V3A. Individual inspection of the relative locations of these two regions revealed a partial overlap and a similar response profile to an independent low-level visual motion stimulus, suggesting that OPA and pIPS/V3A may be part of a unique motion-selective complex specialized in encoding both egomotion- and scene-relevant information, likely for the control of navigation in a structured environment.

Prompting future events: Effects of temporal cueing and time on task on brain preparation to action.

Prediction about event timing plays a leading role in organizing and optimizing behavior. We recorded anticipatory brain activities and evaluated whether temporal orienting processes are reflected by the novel prefrontal negative (pN) component, as already shown for the contingent negative variation (CNV). Fourteen young healthy participants underwent EEG and fMRI recordings in separate sessions; they were asked to perform a Go/No-Go task in which temporal orienting was manipulated: the external condition (a visual display indicating the time of stimulus onset) and the internal condition (time information not provided). In both conditions, the source of the pN was localized in the pars opercularis of the iFg; the source of the CNV was localized in the supplementary motor area and cingulate motor area, as expected. Anticipatory activity was also found in the occipital-parietal cortex. Time on task EEG analysis showed a marked learning effect in the internal condition, while the effect was minor in the external condition. In fMRI, the two conditions had a similar pattern; similarities and differences of results obtained with the two techniques are discussed. Overall, data are consistent with the view that the pN reflects a proactive cognitive control, including temporal orienting.

Real and Imagined Grasping Movements Differently Activate the Human Dorsomedial Parietal Cortex.

Object prehension typically includes a transport phase (reaching) and a grip phase (grasping). Within the posterior parietal cortex (PPC), grasping movements have been traditionally associated to a lateral activation, although recent monkey evidence suggests also a medial involvement. Here, we wanted to determine whether grasping-related activities are present in the human dorsomedial parietal cortex, by focusing on two cortical regions specialized in the monkey in controlling limb movements, i.e., V6A (composed by its ventral and dorsal sectors, V6Av and V6Ad, respectively) and PEc, both recently defined also in humans. We acquired functional magnetic resonance images while participants performed both real (pantomimed) and imagined grasping of visually-presented objects. We found that the human areas V6Ad (hV6Ad) and PEc (hPEc) were both activated by real grasping, whereas hV6Ad only was activated by the imagery of grasping movements. hV6Av was not involved in either types of grasping. These results speak against the traditional notion of a medial-to-lateral segregation of reaching versus grasping information within the PPC and strengthen the idea that the human dorsomedial parietal cortex implements the whole complex pattern of visuomotor transformations required for object-oriented actions. Our findings suggest that hV6Ad is particularly involved in implementing all the visuomotor transformations needed to create an abstract representation of the object-directed action, while hPEc is involved in implementing the sensorimotor transformations needed to actually perform that action.

Neural bases of self- and object-motion in a naturalistic vision.

To plan movements toward objects our brain must recognize whether retinal displacement is due to self-motion and/or to object-motion. Here, we aimed to test whether motion areas are able to segregate these types of motion. We combined an event-related functional magnetic resonance imaging experiment, brain mapping techniques, and wide-field stimulation to study the responsivity of motion-sensitive areas to pure and combined self- and object-motion conditions during virtual movies of a train running within a realistic landscape. We observed a selective response in MT to the pure object-motion condition, and in medial (PEc, pCi, CSv, and CMA) and lateral (PIC and LOR) areas to the pure self-motion condition. Some other regions (like V6) responded more to complex visual stimulation where both object- and self-motion were present. Among all, we found that some motion regions (V3A, LOR, MT, V6, and IPSmot) could extract object-motion information from the overall motion, recognizing the real movement of the train even when the images remain still (on the screen), or moved, because of self-movements. We propose that these motion areas might be good candidates for the "flow parsing mechanism," that is the capability to extract object-motion information from retinal motion signals by subtracting out the optic flow components.

A putative human homologue of the macaque area PEc.

The cortical area PEc is anatomically and functionally well-defined in macaque, but it is unknown whether it has a counterpart in human. Since we know that macaque PEc, but not the nearby posterior regions, hosts a lower limb representation, in an attempt to recognize a possible human PEc we looked for the existence of leg representations in the human parietal cortex using individual cortical surface-based analysis, task-evoked paradigms and resting-state functional connectivity. fMRI images were acquired while thirty-one participants performed long-range leg movements through an in-house MRI-compatible set-up. We revealed the existence of multiple leg representations in the human dorsomedial parietal cortex, here defined as S-I (somatosensory-I), hPE (human PE, in the postcentral sulcus), and hPEc (human PEc, in the anterior precuneus). Among the three "leg" regions, hPEc had a unique functional profile, in that it was the only one responding to both arm and leg movements, to both hand-pointing and foot pointing movements, and to flow field visual stimulation, very similar to macaque area PEc. In addition, hPEc showed functional connections with the somatomotor regions hosting a lower limb representation, again as in macaque area PEc. Therefore, based on similarity in brain position, functional organization, cortical connections, and relationship with the neighboring areas, we propose that this cortical region is the human homologue of macaque area PEc.