ABSTRACT
Despite extensive research, the functional architecture of the subregions of the dorsal posterior parietal cortex (PPC) involved in sensorimotor processing is far from clear. Here, we draw a thorough picture of the large-scale functional organization of the PPC to disentangle the fronto-parietal networks mediating visuomotor functions. To this aim, we reanalyzed available human functional magnetic resonance imaging data collected during the execution of saccades, hand, and foot pointing, and we combined individual surface-based activation, resting-state functional connectivity, and effective connectivity analyses. We described a functional distinction between a more lateral region in the posterior intraparietal sulcus (lpIPS), preferring saccades over pointing and coupled with the frontal eye fields (FEF) at rest, and a more medial portion (mpIPS) intrinsically correlated to the dorsal premotor cortex (PMd). Dynamic causal modeling revealed feedforward-feedback loops linking lpIPS with FEF during saccades and mpIPS with PMd during pointing, with substantial differences between hand and foot. Despite an intrinsic specialization of the action-specific fronto-parietal networks, our study reveals that their functioning is finely regulated according to the effector to be used, being the dynamic interactions within those networks differently modulated when carrying out a similar movement (i.e. pointing) but with distinct effectors (i.e. hand and foot).
Subject(s)
Brain Mapping , Motor Cortex , Humans , Brain Mapping/methods , Motor Cortex/physiology , Saccades , Parietal Lobe/physiology , Movement/physiology , Magnetic Resonance ImagingABSTRACT
The perception and imagery of landmarks activate similar content-dependent brain areas, including occipital and temporo-medial brain regions. However, how these areas interact during visual perception and imagery of scenes, especially when recollecting their spatial location, remains unknown. Here, we combined functional magnetic resonance imaging (fMRI), resting-state functional connectivity (rs-fc), and effective connectivity to assess spontaneous fluctuations and task-induced modulation of signals among regions entailing scene-processing, the primary visual area and the hippocampus (HC), responsible for the retrieval of stored information. First, we functionally defined the scene-selective regions, that is, the occipital place area (OPA), the retrosplenial complex (RSC) and the parahippocampal place area (PPA), by using the face/scene localizer, observing that two portions of the PPA-anterior and posterior PPA-were consistently activated in all subjects. Second, the rs-fc analysis (n = 77) revealed a connectivity pathway similar to the one described in macaques, showing separate connectivity routes linking the anterior PPA with RSC and HC, and the posterior PPA with OPA. Third, we used dynamic causal modelling to evaluate whether the dynamic couplings among these regions differ between perception and imagery of familiar landmarks during a fMRI task (n = 16). We found a positive effect of HC on RSC during the retrieval of imagined places and an effect of occipital regions on both RSC and pPPA during the perception of scenes. Overall, we propose that under similar functional architecture at rest, different neural interactions take place between regions in the occipito-temporal higher-level visual cortex and the HC, subserving scene perception and imagery.
Subject(s)
Brain Mapping , Neocortex , Brain Mapping/methods , Occipital Lobe/physiology , Temporal Lobe/physiology , Visual Perception/physiology , Magnetic Resonance Imaging , Photic StimulationABSTRACT
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.
Subject(s)
Hand Strength/physiology , Imagination/physiology , Magnetic Resonance Imaging/methods , Motor Cortex/physiology , Nerve Net/physiology , Psychomotor Performance/physiology , Adult , Bayes Theorem , Female , Humans , Imaging, Three-Dimensional/methods , Male , Motor Cortex/diagnostic imaging , Nerve Net/diagnostic imaging , Photic Stimulation/methodsABSTRACT
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.
Subject(s)
Motor Cortex , Motor Cortex/diagnostic imaging , Bayes Theorem , Brain , Movement , Hand , Brain Mapping , Magnetic Resonance ImagingABSTRACT
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.