Kay KN, Winawer J, Mezer A, Wandell BA. Compressive spatial summation in human visual cortex. J Neurophysiol 110: 481-494, 2013. First published April 24, 2013 doi:10.1152/jn.00105.2013.-Neurons within a small (a few cubic millimeters) region of visual cortex respond to stimuli within a restricted region of the visual field. Previous studies have characterized the population response of such neurons using a model that sums contrast linearly across the visual field. In this study, we tested linear spatial summation of population responses using blood oxygenation level-dependent (BOLD) functional MRI. We measured BOLD responses to a systematic set of contrast patterns and discovered systematic deviation from linearity: the data are more accurately explained by a model in which a compressive static nonlinearity is applied after linear spatial summation. We found that the nonlinearity is present in early visual areas (e.g., V1, V2) and grows more pronounced in relatively anterior extrastriate areas (e.g., LO-2, VO-2). We then analyzed the effect of compressive spatial summation in terms of changes in the position and size of a viewed object. Compressive spatial summation is consistent with tolerance to changes in position and size, an important characteristic of object representation. (Fig. 1). The validity of this assumption is important to examine, as it affects the accuracy of pRF estimates and may reveal insight into response properties at different stages of the visual map hierarchy. Assessments of linearity of spatial summation have been conducted in both electrophysiology and fMRI, but these have provided conflicting conclusions (e.g., Britten and Heuer 1999;Hansen et al. 2004;Kastner et al. 2001;Pihlaja et al. 2008). Thus the precise nature of spatial pooling, and how well the linear approximation describes physiological responses, remains unclear.In this study, we examine spatial summation using systematic measurements of blood oxygenation level-dependent (BOLD) fMRI responses in human visual cortex to a range of spatial contrast patterns. We uncover a small nonlinear effect (subadditive spatial summation) in primary visual cortex and find that the nonlinear effect is pronounced in extrastriate maps. To account for the effect, we develop a computational model in which a compressive static nonlinearity is applied after linear spatial summation; this model substantially improves cross-validation performance compared with a linear spatial summation model.

We describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent, quantitative estimate of macromolecular volume can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.

Properties of human brain tissue change across the lifespan. Here we model these changes in the living human brain by combining quantitative MRI measurements of R1 (1/T1) with diffusion MRI and tractography (N=102, ages 7–85). The amount of R1 change during development differs between white matter fascicles, but in each fascicle the rate of development and decline are mirror symmetric; the rate of R1 development as the brain approaches maturity predicts the rate of R1 degeneration in aging. Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue. In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age. Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white matter tissue properties over the lifespan.

The vertical occipital fasciculus (VOF) is the only major fiber bundle connecting dorsolateral and ventrolateral visual cortex. Only a handful of studies have examined the anatomy of the VOF or its role in cognition in the living human brain. Here, we trace the contentious history of the VOF, beginning with its original discovery in monkey by Wernicke (1881) and in human by Obersteiner (1888), to its disappearance from the literature, and recent reemergence a century later. We introduce an algorithm to identify the VOF in vivo using diffusion-weighted imaging and tractography, and show that the VOF can be found in every hemisphere (n = 74). Quantitative T1 measurements demonstrate that tissue properties, such as myelination, in the VOF differ from neighboring white-matter tracts. The terminations of the VOF are in consistent positions relative to cortical folding patterns in the dorsal and ventral visual streams. Recent findings demonstrate that these same anatomical locations also mark cytoarchitectonic and functional transitions in dorsal and ventral visual cortex. We conclude that the VOF is likely to serve a unique role in the communication of signals between regions on the ventral surface that are important for the perception of visual categories (e.g., words, faces, bodies, etc.) and regions on the dorsal surface involved in the control of eye movements, attention, and motion perception. T he vertical occipital fasciculus (VOF) is the only major fiber bundle connecting dorsal and ventral regions of occipital, parietal, and temporal cortex. The signals carried by the VOF are likely to play an essential role in an array of visual and cognitive functions. Characterizing the VOF connections and tissue structure in the living human brain is important for the study of human vision and cognitive neuroscience alike.Carl Wernicke discovered the VOF (1). For the next 30 y, the VOF was included in many major neuroanatomy atlases and journal articles (1-14). However, Wernicke's study contradicted a widely accepted principle of white-matter organization proposed by Meynert, Wernicke's mentor. Over the subsequent decades, there emerged a camp of neuroanatomists who acknowledged Wernicke's discovery and another group that, like Meynert, disregarded the discovery. Due to its controversial beginnings, haphazard naming convention, and the difficulty of standardizing postmortem procedures, the VOF largely disappeared from the literature for most of the next century. A century later, Yeatman et al. (15) rediscovered the VOF using diffusion magnetic resonance imaging (dMRI); they were the first to characterize the VOF cortical projections in the living, behaving, human brain.Why would such an important pathway disappear from the literature for so long? The disappearance can be traced to controversies and confusions among some of the most prominent neuroanatomists of the 19th century (1-13, 16-18). Modern, in vivo, MRI measurements and algorithms allow for precise, reproducible, scalable computations that can resolve these cen...

Diffusion imaging and bound pool fraction (BPF) mapping are two quantitative magnetic resonance imaging techniques that measure microstructural features of the white matter of the brain. Diffusion imaging provides a quantitative measure of the diffusivity of water in tissue. BPF mapping is a quantitative magnetization transfer (qMT) technique that estimates the proportion of exchanging protons bound to macromolecules, such as those found in myelin, and is thus a more direct measure of myelin content than diffusion. In this work, we combine BPF estimates of macromolecular content with measurements of diffusivity within human white matter tracts. Within the white matter, the correlation between BPFs and diffusivity measures such as fractional anisotropy and radial diffusivity was modest, suggesting that diffusion tensor imaging and bound pool fractions are complementary techniques. We found that several major tracts have high BPF, suggesting a higher density of myelin in these tracts. We interpret these results in the context of a quantitative tissue model.