Interoperable atlases of the human brain

International audienceThe last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different as-pects of the human brain including micro-and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topo-graphically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and represen-tation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored

Bayesian Modeling of Perceived Surface Slant from Actively-Generated and Passively-Observed Optic Flow

We measured perceived depth from the optic flow (a) when showing a stationary physical or virtual object to observers who moved their head at a normal or slower speed, and (b) when simulating the same optic flow on a computer and presenting it to stationary observers. Our results show that perceived surface slant is systematically distorted, for both the active and the passive viewing of physical or virtual surfaces. These distortions are modulated by head translation speed, with perceived slant increasing directly with the local velocity gradient of the optic flow. This empirical result allows us to determine the relative merits of two alternative approaches aimed at explaining perceived surface slant in active vision: an “inverse optics” model that takes head motion information into account, and a probabilistic model that ignores extra-retinal signals. We compare these two approaches within the framework of the Bayesian theory. The “inverse optics” Bayesian model produces veridical slant estimates if the optic flow and the head translation velocity are measured with no error; because of the influence of a “prior” for flatness, the slant estimates become systematically biased as the measurement errors increase. The Bayesian model, which ignores the observer's motion, always produces distorted estimates of surface slant. Interestingly, the predictions of this second model, not those of the first one, are consistent with our empirical findings. The present results suggest that (a) in active vision perceived surface slant may be the product of probabilistic processes which do not guarantee the correct solution, and (b) extra-retinal signals may be mainly used for a better measurement of retinal information

The `Parahippocampal Place Area' Responds Selectively to High Spatial Frequencies

Defining the exact mechanisms by which the brain processes visual objects and scenes remains an unresolved challenge. Valuable clues to this process have emerged from the demonstration that clusters of neurons (“modules”) in inferior temporal cortex apparently respond selectively to specific categories of visual stimuli, such as places/scenes. However, the higher-order “category-selective” response could also reflect specific lower-level spatial factors. Here we tested this idea in multiple functional MRI experiments, in humans and macaque monkeys, by systematically manipulating the spatial content of geometrical shapes and natural images. These tests revealed that visual spatial discontinuities (as reflected by an increased response to high spatial frequencies) selectively activate a well-known place-selective region of visual cortex (the “parahippocampal place area”) in humans. In macaques, we demonstrate a homologous cortical area, and show that it also responds selectively to higher spatial frequencies. The parahippocampal place area may use such information for detecting object borders and scene details during spatial perception and navigation.National Institutes of Health (U.S.) (NIH Grant R01 MH6752)National Institutes of Health (U.S.) (grant R01 EY017081)Athinoula A. Martinos Center for Biomedical ImagingNational Center for Research Resources (U.S.)Mind Research Institut

Hemodynamic Traveling Waves in Human Visual Cortex

Functional MRI (fMRI) experiments rely on precise characterization of the blood oxygen level dependent (BOLD) signal. As the spatial resolution of fMRI reaches the sub-millimeter range, the need for quantitative modelling of spatiotemporal properties of this hemodynamic signal has become pressing. Here, we find that a detailed physiologically-based model of spatiotemporal BOLD responses predicts traveling waves with velocities and spatial ranges in empirically observable ranges. Two measurable parameters, related to physiology, characterize these waves: wave velocity and damping rate. To test these predictions, high-resolution fMRI data are acquired from subjects viewing discrete visual stimuli. Predictions and experiment show strong agreement, in particular confirming BOLD waves propagating for at least 5–10 mm across the cortical surface at speeds of 2–12 mm s-1. These observations enable fundamentally new approaches to fMRI analysis, crucial for fMRI data acquired at high spatial resolution

Connectivity of the Primate Superior Colliculus Mapped by Concurrent Microstimulation and Event-Related fMRI

Background: Neuroanatomical studies investigating the connectivity of brain areas have heretofore employed procedures in which chemical or viral tracers are injected into an area of interest, and connected areas are subsequently identified using histological techniques. Such experiments require the sacrifice of the animals and do not allow for subsequent electrophysiological studies in the same subjects, rendering a direct investigation of the functional properties of anatomically identified areas impossible. Methodology/Principal Findings: Here, we used a combination of microstimulation and fMRI in an anesthetized monkey preparation to study the connectivity of the superior colliculus (SC). Microstimulation of the SC resulted in changes in the blood oxygenation level-dependent (BOLD) signals in the SC and in several cortical and subcortical areas consistent with the known connectivity of the SC in primates. Conclusions/Significance: These findings demonstrates that the concurrent use of microstimulation and fMRI can be used to identify brain networks for further electrophysiological or fMRI investigation

Adaptation reveals sensory and decision components in the visual estimation of locomotion speed

Locomotion speed provides important social information about an individual’s fitness, mood and intent. Visual estimation of locomotion speed is a complex task for the visual system because viewing distance must be taken into account, and the estimate has to be calibrated by recent experience of typical speeds. Little is known about how locomotion speed judgements are made. Previous research indicates that the human visual system possesses neurons that respond specifically to moving human forms. This research used point-light walker (PLW) displays that are known to activate these cells, in order to investigate the process mediating locomotion speed judgements. The results of three adaptation experiments show that these judgements involve both a low-level sensory component and a high-level decision component. A simple theoretical scheme is proposed, in which neurons sensitive to image flicker rate (temporal frequency) provide a sensory speed code, and a benchmark ‘norm’ value of the speed code, based on prevailing locomotion speeds, is used to make decisions about objective speed. The output of a simple computational model of the scheme successfully captured variations in locomotion speed in the stimuli used in the experiments. The theory offers a biologically-motivated account of how locomotion speed can be visually estimated

Visuospatial Integration: Paleoanthropological and Archaeological Perspectives

The visuospatial system integrates inner and outer functional processes, organizing spatial, temporal, and social interactions between the brain, body, and environment. These processes involve sensorimotor networks like the eye–hand circuit, which is especially important to primates, given their reliance on vision and touch as primary sensory modalities and the use of the hands in social and environmental interactions. At the same time, visuospatial cognition is intimately connected with memory, self-awareness, and simulation capacity. In the present article, we review issues associated with investigating visuospatial integration in extinct human groups through the use of anatomical and behavioral data gleaned from the paleontological and archaeological records. In modern humans, paleoneurological analyses have demonstrated noticeable and unique morphological changes in the parietal cortex, a region crucial to visuospatial management. Archaeological data provides information on hand–tool interaction, the spatial behavior of past populations, and their interaction with the environment. Visuospatial integration may represent a critical bridge between extended cognition, self-awareness, and social perception. As such, visuospatial functions are relevant to the hypothesis that human evolution is characterized by changes in brain–body–environment interactions and relations, which enhance integration between internal and external cognitive components through neural plasticity and the development of a specialized embodiment capacity. We therefore advocate the investigation of visuospatial functions in past populations through the paleoneurological study of anatomical elements and archaeological analysis of visuospatial behaviors

Accelerating the Evolution of Nonhuman Primate Neuroimaging

Nonhuman primate neuroimaging is on the cusp of a transformation, much in the same way its human counterpart was in 2010, when the Human Connectome Project was launched to accelerate progress. Inspired by an open data-sharing initiative, the global community recently met and, in this article, breaks through obstacles to define its ambitions