Cortical depth dependent functional responses in humans at 7T: improved specificity with 3D GRASE

Ultra high fields (7T and above) allow functional imaging with high contrast-to-noise ratios and improved spatial resolution. This, along with improved hardware and imaging techniques, allow investigating columnar and laminar functional responses. Using gradient-echo (GE) (T2* weighted) based sequences, layer specific responses have been recorded from human (and animal) primary visual areas. However, their increased sensitivity to large surface veins potentially clouds detecting and interpreting layer specific responses. Conversely, spin-echo (SE) (T2 weighted) sequences are less sensitive to large veins and have been used to map cortical columns in humans. T2 weighted 3D GRASE with inner volume selection provides high isotropic resolution over extended volumes, overcoming some of the many technical limitations of conventional 2D SE-EPI, whereby making layer specific investigations feasible. Further, the demonstration of columnar level specificity with 3D GRASE, despite contributions from both stimulated echoes and conventional T2 contrast, has made it an attractive alternative over 2D SE-EPI. Here, we assess the spatial specificity of cortical depth dependent 3D GRASE functional responses in human V1 and hMT by comparing it to GE responses. In doing so we demonstrate that 3D GRASE is less sensitive to contributions from large veins in superficial layers, while showing increased specificity (functional tuning) throughout the cortex compared to GE

Interaction of cortical networks mediating object motion detection by moving observers

Published in final edited form as: Exp Brain Res. 2012 August ; 221(2): 177–189. doi:10.1007/s00221-012-3159-8.The task of parceling perceived visual motion into self- and object motion components is critical to safe and accurate visually guided navigation. In this paper, we used functional magnetic resonance imaging to determine the cortical areas functionally active in this task and the pattern connectivity among them to investigate the cortical regions of interest and networks that allow subjects to detect object motion separately from induced self-motion. Subjects were presented with nine textured objects during simulated forward self-motion and were asked to identify the target object, which had an additional, independent motion component toward or away from the observer. Cortical activation was distributed among occipital, intra-parietal and fronto-parietal areas. We performed a network analysis of connectivity data derived from partial correlation and multivariate Granger causality analyses among functionally active areas. This revealed four coarsely separated network clusters: bilateral V1 and V2; visually responsive occipito-temporal areas, including bilateral LO, V3A, KO (V3B) and hMT; bilateral VIP, DIPSM and right precuneus; and a cluster of higher, primarily left hemispheric regions, including the central sulcus, post-, pre- and sub-central sulci, pre-central gyrus, and FEF. We suggest that the visually responsive networks are involved in forming the representation of the visual stimulus, while the higher, left hemisphere cluster is involved in mediating the interpretation of the stimulus for action. Our main focus was on the relationships of activations during our task among the visually responsive areas. To determine the properties of the mechanism corresponding to the visual processing networks, we compared subjects’ psychophysical performance to a model of object motion detection based solely on relative motion among objects and found that it was inconsistent with observer performance. Our results support the use of scene context (e.g., eccentricity, depth) in the detection of object motion. We suggest that the cortical activation and visually responsive networks provide a potential substrate for this computation.This work was supported by NIH grant RO1NS064100 to L.M.V. We thank Victor Solo for discussions regarding models of functional connectivity and our subjects for participating in the psychophysical and fMRI experiments. This research was carried out in part at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, using resources provided by the Center for Functional Neuroimaging Technologies, P41RR14075, a P41 Regional Resource supported by the Biomedical Technology Program of the National Center for Research Resources (NCRR), National Institutes of Health. This work also involved the use of instrumentation supported by the NCRR Shared Instrumentation Grant Program and/or High-End Instrumentation Grant Program; specifically, grant number S10RR021110. (RO1NS064100 - NIH; National Center for Research Resources (NCRR), National Institutes of Health; S10RR021110 - NCRR)Accepted manuscrip

Making a stronger case for comparative research to investigate the behavioral and neurological bases of three-dimensional navigation

The rich diversity of avian natural history provides exciting possibilities for comparative research aimed at understanding three-dimensional navigation. We propose some hypotheses relating differences in natural history to potential behavioral and neurological adaptations possessed by contrasting bird species. This comparative approach may offer unique insights into some of the important questions raised by Jeffery et al

Navigating in a three-dimensional world

The study of spatial cognition has provided considerable insight into how animals (including humans) navigate on the horizontal plane. However, the real world is three-dimensional, having a complex topography including both horizontal and vertical features, which presents additional challenges for representation and navigation. The present article reviews the emerging behavioral and neurobiological literature on spatial cognition in non-horizontal environments. We suggest that three-dimensional spaces are represented in a quasi-planar fashion, with space in the plane of locomotion being computed separately and represented differently from space in the orthogonal axis-a representational structure we have termed "bicoded.” We argue that the mammalian spatial representation in surface-travelling animals comprises a mosaic of these locally planar fragments, rather than a fully integrated volumetric map. More generally, this may be true even for species that can move freely in all three dimensions, such as birds and fish. We outline the evidence supporting this view, together with the adaptive advantages of such a schem

Self-adaptive context aware audio localization for robots using parallel cerebellar models

An audio sensor system is presented that uses multiple cerebellar models to determine the acoustic environment in which a robot is operating, allowing the robot to select appropriate models to calibrate its audio-motor map for the detected environment. The use of the adaptive filter model of the cerebellum in a variety of robotics applications has demonstrated the utility of the so-called cerebellar chip. This paper combines the notion of cerebellar calibration of a distorted audio-motor map with the use of multiple parallel models to predict the context (acoustic environment) within which the robot is operating. The system was able to correctly predict seven different acoustic contexts in almost 70% of cases tested