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In humans, the posterior cingulate cortex contains an area sensitive to visual cues to self-motion. This cingulate sulcus visual area (CSv) is structurally and functionally connected with several (multi)sensory and (pre)motor areas recruited during locomotion. In nonhuman primates, electrophysiology has shown that the cingulate cortex is also related to spatial navigation. Recently, functional MRI in macaque monkeys identified a cingulate area with similar visual properties to human CSv. In order to bridge the gap between human and nonhuman primate research, we examined the structural and functional connectivity of putative CSv in three macaque monkeys adopting the same approach as in humans based on diffusion MRI and resting-state functional MRI. The results showed that putative monkey CSv connects with several visuo-vestibular areas (e.g., VIP/FEFsem/VPS/MSTd) as well as somatosensory cortex (e.g., dorsal aspects of areas 3/1/2), all known to process sensory signals that can be triggered by self-motion. Additionally, strong connections are observed with (pre)motor areas located in the dorsal prefrontal cortex (e.g., F3/F2/F1) and within the anterior cingulate cortex (e.g., area 24). This connectivity pattern is strikingly reminiscent of that described for human CSv, suggesting that the sensorimotor control of locomotion relies on similar organizational principles in human and nonhuman primates., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Macular degeneration (MD) affects central vision and represents the leading cause of visual diseases in elderly population worldwide. As a consequence of central vision loss, MD patients develop a preferred retinal locus (PRL), an eccentric fixation point that replaces the fovea. Here, our aim was to determine whether and to what extent spontaneous plasticity takes place in the cortical regions formerly responding to central vision and whether a visual training based on perceptual learning (PL) can boost this plasticity within the PRL area. Spontaneous and PL-induced cortical plasticity were characterized by using lateral masking, a contrast sensitivity modulation induced by collinear flankers. This configuration is known to be sensitive to neural plasticity and underlies several rehabilitation trainings. Results in a group of 4 MD patients showed that collinear facilitation was similar to what observed in age- and eccentricity-matched controls. However, MD patients exhibited significantly reduced collinear inhibition, a sign of neural plasticity, consistent with the hypothesis of partial cortical reorganization. Three AMD patients from the same group showed a further reduction of inhibition after training, but not controls. This result suggests that PL might further boost neural plasticity, opening promising perspectives for the development of rehabilitation protocols for MD patients.

This study investigates neural magneto-encephalographic (MEG) correlates of visual form and motion binding. Steady-state visual evoked fields (SSVEF) were recorded in MEG while observers reported their bound or unbound perception of moving bars arranged in a square shape. By using pairs of oscillating vertical and horizontal bars, "frequency-tagged" at f1 and f2, we identified a region with enhanced sustained power at 2f1+2f2 intermodulation frequency correlated with perceptual reports. Intermodulation power is more important during perceptual form/motion integration than during the perceptual segmentation of the stimulus into individual component motions, indicating that intermodulation frequency power is a neuromarker of form/motion integration. Source reconstruction of cortical activities at the relevant frequencies further reveals well segregated activity in the occipital lobe at the fundamental of the stimulation, f1 and f2, widely spread activity at 2f1 and 2f2 and a focal activity in the medial part of the right precentral sulcus region at the intermodulation component, 2f1+2f2. The present findings indicate that motion tagging provides a powerful way of investigating the processes underlying visual form/motion binding non-invasively in humans., (Copyright © 2011. Published by Elsevier B.V.)

Although the spatial organization of visual areas can be revealed by functional Magnetic Resonance Imaging (fMRI), the synoptic, non-invasive access to the temporal characteristics of the information flow amongst distributed visual processes remains a technical and methodological challenge. Using frequency-encoded steady-state visual stimulation together with a combination of time-resolved functional magnetic source imaging from magnetoencephalography (MEG) and anatomical magnetic resonance imaging (MRI), this study evidences maps of visuotopic sustained oscillatory neural responses distributed across the visual cortex. Our results further reveal relative phase delays across responding striate and extra-striate visual areas, which thereby shape the chronometry of neural processes amongst these regions. The methodology developed in this study points at further developments in time-resolved analyses of distributed visual processes in the millisecond range, and to new ways of exploring the dynamics of functional processes within the human visual cortex non-invasively., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Imaging neural generators from MEG magnetic fields is often considered as a compromise between computationally-reasonable methodology that usually yields poor spatial resolution on the one hand, and more sophisticated approaches on the other hand, potentially leading to intractable computational costs. We approach the problem of obtaining well-resolved source images with unexcessive computation load with a multiresolution image model selection (MiMS) technique. The building blocks of the MiMS source model are parcels of the cortical surface which can be designed at multiple spatial resolutions with the combination of anatomical and functional priors. Computation charge is reduced owing to 1) compact parametric models of the activation of extended brain parcels using current multipole expansions and 2) the optimization of the generalized cross-validation error on image models, which is closed-form for the broad class of linear estimators of neural currents. Model selection can be complemented by any conventional imaging approach of neural currents restricted to the optimal image support obtained from MiMS. The estimation of the location and spatial extent of brain activations is discussed and evaluated using extensive Monte-Carlo simulations. An experimental evaluation was conducted with MEG data from a somatotopic paradigm. Results show that MiMS is an efficient image model selection technique with robust performances at realistic noise levels.

Detection of activity from the primary visual cortex is a difficult challenge to magneto-encephalography (MEG) source imaging techniques: the geometry of the visual cortex is intricate, with structured visual field maps extending deeper along the calcarine fissure. This questions the very sensitivity of MEG to the corresponding neural responses of visual stimuli and the usage of MEG source imaging for innovative retinotopic explorations. In this context, we compare two imaging models of MEG generators in realistic simulations of activations within the visual cortex. Localization and spatial extent of neural activity in the visual cortex were extracted from retinotopic maps obtained in fMRI. We prove that the suggested approaches are robust and succeed in accurately recovering the activation patterns with satisfactory match with fMRI results. These results suggest that fast retinotopic exploration of the visual cortex could be obtained from MEG as a complementary alternative to more standard fMRI approaches. The excellent time resolution of MEG imaging further opens interesting perspectives on the temporal and spectral processes sustained by the human visual system.

We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal ganglia and the hippocampus may also contribute to distant, scalp MEG and EEG measurements. We first design a realistic anatomical and electrophysiological model of these structures and subsequently run Monte-Carlo experiments to evaluate the respective sensitivity of the MEG and EEG to signals from deeper origins. Results indicate that MEG/EEG may indeed localize these deeper generators, which is confirmed here from experimental MEG data reporting on the modulation of alpha brain waves.